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Publisher: Elsevier   (Total: 3031 journals)

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Showing 1 - 200 of 3031 Journals sorted alphabetically
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 20, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 16, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 79, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 22, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 27, SJR: 2.515, h-index: 90)
Achievements in the Life Sciences     Open Access   (Followers: 4)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 5, SJR: 0.338, h-index: 19)
Acta Astronautica     Hybrid Journal   (Followers: 302, SJR: 0.726, h-index: 43)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Biomaterialia     Hybrid Journal   (Followers: 25, SJR: 2.02, h-index: 104)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription  
Acta de Investigación Psicológica     Open Access   (Followers: 2)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.172, h-index: 29)
Acta Haematologica Polonica     Free   (SJR: 0.123, h-index: 8)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.604, h-index: 38)
Acta Materialia     Hybrid Journal   (Followers: 195, SJR: 3.683, h-index: 202)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.615, h-index: 21)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.442, h-index: 21)
Acta Oecologica     Hybrid Journal   (Followers: 9, SJR: 0.915, h-index: 53)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription   (Followers: 1)
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.311, h-index: 16)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 2)
Acta Poética     Open Access   (Followers: 4)
Acta Psychologica     Hybrid Journal   (Followers: 21, SJR: 1.365, h-index: 73)
Acta Sociológica     Open Access  
Acta Tropica     Hybrid Journal   (Followers: 5, SJR: 1.059, h-index: 77)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 4)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 3)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.383, h-index: 19)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 2)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 5, SJR: 0.141, h-index: 3)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 4, SJR: 0.112, h-index: 2)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 4)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.967, h-index: 57)
Addictive Behaviors     Hybrid Journal   (Followers: 15, SJR: 1.514, h-index: 92)
Addictive Behaviors Reports     Open Access   (Followers: 5)
Additive Manufacturing     Hybrid Journal   (Followers: 7, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 20)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 119, SJR: 5.2, h-index: 222)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.265, h-index: 53)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, SJR: 0.739, h-index: 33)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.299, h-index: 15)
Advances in Agronomy     Full-text available via subscription   (Followers: 15, SJR: 2.071, h-index: 82)
Advances in Anesthesia     Full-text available via subscription   (Followers: 24, SJR: 0.169, h-index: 4)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 3)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 6, SJR: 1.054, h-index: 35)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 10, SJR: 0.801, h-index: 26)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 21, SJR: 1.286, h-index: 49)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 16, SJR: 3.31, h-index: 42)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.277, h-index: 43)
Advances in Botanical Research     Full-text available via subscription   (Followers: 3, SJR: 0.619, h-index: 48)
Advances in Cancer Research     Full-text available via subscription   (Followers: 26, SJR: 2.215, h-index: 78)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 0.9, h-index: 30)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 2.139, h-index: 42)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 24, SJR: 0.183, h-index: 23)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.665, h-index: 29)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 8, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, SJR: 0.938, h-index: 33)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 18, SJR: 2.314, h-index: 130)
Advances in Computers     Full-text available via subscription   (Followers: 16, SJR: 0.223, h-index: 22)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 4)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 22)
Advances in Ecological Research     Full-text available via subscription   (Followers: 39, SJR: 3.25, h-index: 43)
Advances in Engineering Software     Hybrid Journal   (Followers: 25, SJR: 0.486, h-index: 10)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 38, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 3)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 8)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 41, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 14)
Advances in Genetics     Full-text available via subscription   (Followers: 15, SJR: 2.558, h-index: 54)
Advances in Genome Biology     Full-text available via subscription   (Followers: 11)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 2.325, h-index: 20)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 18, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.497, h-index: 31)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.396, h-index: 27)
Advances in Immunology     Full-text available via subscription   (Followers: 33, SJR: 4.152, h-index: 85)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 1.132, h-index: 42)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 3, SJR: 1.274, h-index: 27)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 4)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 4)
Advances in Life Course Research     Hybrid Journal   (Followers: 7, SJR: 0.764, h-index: 15)
Advances in Lipobiology     Full-text available via subscription   (Followers: 1)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Marine Biology     Full-text available via subscription   (Followers: 16, SJR: 1.645, h-index: 45)
Advances in Mathematics     Full-text available via subscription   (Followers: 10, SJR: 3.261, h-index: 65)
Advances in Medical Sciences     Hybrid Journal   (Followers: 5, SJR: 0.489, h-index: 25)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.44, h-index: 51)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 21)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 10)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 6, SJR: 0.324, h-index: 8)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 3)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 15, SJR: 2.885, h-index: 45)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.148, h-index: 11)
Advances in Parasitology     Full-text available via subscription   (Followers: 7, SJR: 2.37, h-index: 73)
Advances in Pediatrics     Full-text available via subscription   (Followers: 20, SJR: 0.4, h-index: 28)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 14)
Advances in Pharmacology     Full-text available via subscription   (Followers: 13, SJR: 1.718, h-index: 58)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 7, SJR: 0.384, h-index: 26)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.248, h-index: 11)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 8)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 17, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 56)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 5, SJR: 0.478, h-index: 32)
Advances in Radiation Oncology     Open Access  
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 1, SJR: 0.1, h-index: 2)
Advances in Space Research     Full-text available via subscription   (Followers: 332, SJR: 0.606, h-index: 65)
Advances in Structural Biology     Full-text available via subscription   (Followers: 7)
Advances in Surgery     Full-text available via subscription   (Followers: 6, SJR: 0.823, h-index: 27)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 28, SJR: 1.321, h-index: 56)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 14)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 12)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 1.878, h-index: 68)
Advances in Water Resources     Hybrid Journal   (Followers: 42, SJR: 2.408, h-index: 94)
Aeolian Research     Hybrid Journal   (Followers: 5, SJR: 0.973, h-index: 22)
Aerospace Science and Technology     Hybrid Journal   (Followers: 303, SJR: 0.816, h-index: 49)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.318, h-index: 36)
African J. of Emergency Medicine     Open Access   (Followers: 4, SJR: 0.344, h-index: 6)
Ageing Research Reviews     Hybrid Journal   (Followers: 7, SJR: 3.289, h-index: 78)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 389, SJR: 1.385, h-index: 72)
Agri Gene     Hybrid Journal  
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 15, SJR: 2.18, h-index: 116)
Agricultural Systems     Hybrid Journal   (Followers: 29, SJR: 1.275, h-index: 74)
Agricultural Water Management     Hybrid Journal   (Followers: 36, SJR: 1.546, h-index: 79)
Agriculture and Agricultural Science Procedia     Open Access  
Agriculture and Natural Resources     Open Access   (Followers: 1)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 48, SJR: 1.879, h-index: 120)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.434, h-index: 14)
Air Medical J.     Hybrid Journal   (Followers: 3, SJR: 0.234, h-index: 18)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.285, h-index: 3)
Alcohol     Hybrid Journal   (Followers: 9, SJR: 0.922, h-index: 66)
Alcoholism and Drug Addiction     Open Access   (Followers: 5)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.436, h-index: 12)
Alexandria J. of Medicine     Open Access  
Algal Research     Partially Free   (Followers: 7, SJR: 2.05, h-index: 20)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 3)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.46, h-index: 29)
Allergology Intl.     Open Access   (Followers: 5, SJR: 0.776, h-index: 35)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 6, SJR: 0.158, h-index: 9)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 45, SJR: 4.289, h-index: 64)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 5)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 3)
American Heart J.     Hybrid Journal   (Followers: 45, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 47, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 34, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 6, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.653, h-index: 93)
American J. of Human Genetics     Hybrid Journal   (Followers: 32, SJR: 8.769, h-index: 256)
American J. of Infection Control     Hybrid Journal   (Followers: 25, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 31, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 48, SJR: 2.023, h-index: 189)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 173, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 51, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 2)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.249, h-index: 88)
American J. of Otolaryngology     Hybrid Journal   (Followers: 22, SJR: 0.59, h-index: 45)
American J. of Pathology     Hybrid Journal   (Followers: 23, SJR: 2.653, h-index: 228)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 21, SJR: 2.764, h-index: 154)
American J. of Surgery     Hybrid Journal   (Followers: 32, SJR: 1.286, h-index: 125)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 13, SJR: 0.653, h-index: 70)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 5)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.066, h-index: 51)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 52, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 3)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 2, SJR: 0.209, h-index: 27)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription   (SJR: 0.104, h-index: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 2, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 38, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 152, SJR: 0.725, h-index: 154)
Analytical Chemistry Research     Open Access   (Followers: 7, SJR: 0.18, h-index: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 10)
Anesthésie & Réanimation     Full-text available via subscription  
Anesthesiology Clinics     Full-text available via subscription   (Followers: 21, SJR: 0.421, h-index: 40)
Angiología     Full-text available via subscription   (SJR: 0.124, h-index: 9)
Angiologia e Cirurgia Vascular     Open Access  
Animal Behaviour     Hybrid Journal   (Followers: 141, SJR: 1.907, h-index: 126)
Animal Feed Science and Technology     Hybrid Journal   (Followers: 5, SJR: 1.151, h-index: 83)
Animal Reproduction Science     Hybrid Journal   (Followers: 5, SJR: 0.711, h-index: 78)
Annales d'Endocrinologie     Full-text available via subscription   (SJR: 0.394, h-index: 30)
Annales d'Urologie     Full-text available via subscription  
Annales de Cardiologie et d'Angéiologie     Full-text available via subscription   (SJR: 0.177, h-index: 13)
Annales de Chirurgie de la Main et du Membre Supérieur     Full-text available via subscription  
Annales de Chirurgie Plastique Esthétique     Full-text available via subscription   (Followers: 2, SJR: 0.354, h-index: 22)
Annales de Chirurgie Vasculaire     Full-text available via subscription   (Followers: 1)

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Journal Cover Advanced Engineering Informatics
  [SJR: 1.265]   [H-I: 53]   [11 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1474-0346
   Published by Elsevier Homepage  [3031 journals]
  • A variable fidelity information fusion method based on radial basis
           function
    • Authors: Qi Zhou; Ping Jiang; Xinyu Shao; Jiexiang Hu; Longchao Cao; Li Wan
      Pages: 26 - 39
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Qi Zhou, Ping Jiang, Xinyu Shao, Jiexiang Hu, Longchao Cao, Li Wan
      Radial basis function (RBF) model has been widely used in complex engineering design process to replace the computational-intensive simulation models. This paper proposes a variable-fidelity metamodeling (VFM) approach based on RBF, in which different levels fidelity information can be integrated and fully exploited. In the proposed VFM approach, a RBF metamodel is constructed for the low-fidelity (LF) model as a start. Then by taking the constructed LF metamodel as a prior-knowledge and mapping the output space of the LF metamodel to that of the studied high-fidelity (HF) model, a variable fidelity (VF) metamodel is created to approximate the relationships between the design variables and corresponding output responses. A numerical illustrative example is adopted to make a detailed comparison between the VFM approach developed in this research and three existing scaling function based VFM approaches, considering different sample sizes and sample noises. Results illustrate that the proposed VFM approach outperforms the scaling function based VFM approaches both in global and local accuracy. Then the proposed VFM approach is applied to two engineering problems, modeling aerodynamic data for a three-dimensional aircraft and the prediction of weld bead profile in laser welding, to illustrate its ability in support of complex engineering design.

      PubDate: 2017-01-06T09:02:10Z
      DOI: 10.1016/j.aei.2016.12.005
      Issue No: Vol. 32 (2017)
       
  • Measurement system design for civil infrastructure using expected utility
    • Authors: Romain Pasquier; James-A. Goulet; Ian F.C. Smith
      Pages: 40 - 51
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Romain Pasquier, James-A. Goulet, Ian F.C. Smith
      For system identification, most sensor-placement strategies are based on the minimization of the model-parameter uncertainty. However, reducing the uncertainty in remaining-life prognosis of structures is often more relevant. This paper proposes an optimization strategy using utility theory and probabilistic behavior prognoses based on model falsification to support decisions related to monitoring interventions. This approach, illustrated by the full-scale case study of a bridge, allows quantification of the expected utility of measurement systems while also indicating the profitability of monitoring actions. In addition, this approach is able to determine when the expected performance of monitoring configurations is reduced due to over-instrumentation. The use of model falsification for system identification allows for explicit inclusion of engineering heuristics in this knowledge intensive task while also offering robustness to effects of systematic modeling errors that are associated with idealization of complex civil structures.

      PubDate: 2017-01-06T09:02:10Z
      DOI: 10.1016/j.aei.2016.12.002
      Issue No: Vol. 32 (2017)
       
  • A quantitative approach to design alternative evaluation based on
           data-driven performance prediction
    • Authors: Zi-jian Zhang; Lin Gong; Yan Jin; Jian Xie; Jia Hao
      Pages: 52 - 65
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Zi-jian Zhang, Lin Gong, Yan Jin, Jian Xie, Jia Hao
      Design alternative evaluation in the early stages of engineering design plays an important role in determining the success of new product development, as it influences considerably the subsequent design activities. However, existing approaches to design alternative evaluation are overly reliant on experts’ ambiguous and subjective judgments and qualitative descriptions. To reduce subjectivity and improve efficiency of the evaluation process, this paper proposes a quantitative evaluation approach through data-driven performance predictions. In this approach, the weights of performance characteristics are determined based on quantitative assessment of expert judgments, and the ranking of design alternatives is achieved by predicting performance values based on historical product design data. The experts’ subjective and often vague judgments are captured quantitatively through a rough number based Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. In order to facilitate performance based quantitative ranking of alternatives at the early stages of design where no performance calculation is possible, a particle swarm optimization based support vector machine (PSO-SVM) is applied for historical data based performance prediction. The final ranking of alternatives given the predicted values of multiple performance characteristics is achieved through Višekriterijumska Optimizacija I kompromisno Rešenje (VIKOR). A case study is carried out to demonstrate the validity of the proposed approach.

      PubDate: 2017-01-14T09:16:24Z
      DOI: 10.1016/j.aei.2016.12.009
      Issue No: Vol. 32 (2017)
       
  • Data analysis for metropolitan economic and logistics development
    • Authors: Shulin Lan; Chen Yang; George Q. Huang
      Pages: 66 - 76
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Shulin Lan, Chen Yang, George Q. Huang
      Logistics industry is an integral sector encompassing transportation, warehousing, handling, circulation and processing, delivery and information technology. With the progress of economic globalization and integration, logistics industry has become a new momentum driving the fast development of national and regional economy. The close relationship between economic development and logistics advancement receives wide attention from the academia. However, current research on the coordination between economy and logistics mostly focuses on concept interpretation, and qualitative discussions. Very rarely do scholars conduct quantitative analysis on the coordination of metropolitan economy and logistics. To fill this gap, we first examine whether there exist interactions between metropolitan logistics and economy by building evaluation index systems for metropolitan logistics and economy. Then we introduce the entropy method and Granger causality test to evaluate and test the level of logistics and economic development in five cities: Beijing, Shanghai, Guangzhou, Chongqing, and Tianjin from 2009 to 2013. From the dimensions of regional economic investment, regional economic capacity and strength, we finally test the relationship between three economic subsystems and three logistics subsystems to further validate the relationship between metropolitan economy and logistics.

      PubDate: 2017-01-28T08:47:07Z
      DOI: 10.1016/j.aei.2017.01.003
      Issue No: Vol. 32 (2017)
       
  • A rule-based servicescape design support system from the design patterns
           of theme parks
    • Authors: Deedee Aram Min; Kyung Hoon Hyun; Sun-Joong Kim; Ji-Hyun Lee
      Pages: 77 - 91
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Deedee Aram Min, Kyung Hoon Hyun, Sun-Joong Kim, Ji-Hyun Lee
      Servicescape design of leisure spaces such as theme parks influence the level of visitor satisfaction and the re-visitation rate. However, only a few large theme park operators have a separate theme of specialists with heuristic knowledge for servicescaping. In response, small companies turn to the specialists paying high fees and royalties usually leading to outdated servicescape designs. In order to help small companies to design servicescape that provide satisfying experience to the visitors, a systematical understanding of the multi-layered and complex service environment of theme parks is necessary. The purpose of this research is to integrate the concept of precedent-based design into a rule-based system by identifying and organizing the design patterns of servicescape into reusable knowledge, propose a servicescape design support system, and confirm whether if the system helps to increase designers’ credence regarding their design in terms of its market success. To accomplish these research aims, six steps were carried out: (1) selection of globally accepted facilities for being successful, (2) analysis of precedents for the discovery of repeating servicescape design patterns, (3) knowledge acquisition and organization for each design patterns, (4) formulation of servicescape rules using the acquired and organized knowledge, (5) integration of the rules into a general design process of a facility as a system, and (6) application of the system in practice. The resulting system was presented to an expert in the field of theme park designs to confirm whether the design process is applicable and how it will perform in practice. From this interview, we received positive feedbacks and well as feedbacks for improvements in the aspects of the system’s applicability in practice, its functionality, and usability. After confirming the applicability of the overall process of the system, we conducted an experiment to experts in practice from various design and planning fields and asked to go through two sets of scenarios in which the first is to design a given site without the system and the second is to design the same site with the system. After each scenario, the subjects were asked to fill out a revised After-Scenario Questionnaire (ASQ). From this experiment, the results indicate that the subjects felt an increase in their credence toward their designs in terms of its market success while the satisfaction with the easiness and the time it took decreased. If our system is revised in the aspects of usability and functionality, our system which uses precedent design patterns could be used to help small company designers to produce servicescape concept designs with more design credence.

      PubDate: 2017-01-28T08:47:07Z
      DOI: 10.1016/j.aei.2017.01.005
      Issue No: Vol. 32 (2017)
       
  • Research on a knowledge modelling methodology for fault diagnosis of
           machine tools based on formal semantics
    • Authors: Qiang Zhou; Ping Yan; Yang Xin
      Pages: 92 - 112
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Qiang Zhou, Ping Yan, Yang Xin
      Fault diagnosis is a critical activity in PHM (Prognostics and Health Management) of machine tools due to its great significance in such efforts as prolonging lifespan, improving production efficiency, and reducing production costs. An efficient knowledge model is necessary to build an intelligent fault diagnosis system. There have been several achievements in knowledge representation and modelling. However, due to their various purposes and depths, the established knowledge models are less compatible, reusable or transplantable, which restricts knowledge sharing and integration. A knowledge modelling methodology for fault diagnosis of machine tools based on formal semantics (KMM-MTFD) is proposed in this paper to build an open, shared, and scalable ontology-based knowledge model of fault diagnosis of various machine tools (OKM-MTFD). First, the proposed predicate-logic-based analysis method of fault elements is adopted to study the fault diagnosis domain and extract the common domain knowledge, which enables the establishment of the core ontology of OKM-MTFD to assure formal semantics. Next, using the proposed two-stage classification method of fault elements and external ontology reference methods, the core ontology can be extended into OKM-MTFD for a type or a specific machine tool. The knowledge reasoning and querying methods based on OWL axioms, SWRL rules, special fault attributes and SPARQL are provided to utilize the knowledge base efficiently. Finally, an ontology-based knowledge model and knowledge base of a hobbing machine tool is presented to exemplify the validity of the proposed KMM-MTFD.

      PubDate: 2017-02-04T09:00:27Z
      DOI: 10.1016/j.aei.2017.01.002
      Issue No: Vol. 32 (2017)
       
  • Private local automation clouds built by CPS: Potential and challenges for
           distributed reasoning
    • Authors: Borja Ramis Ferrer; Jose Luis Martinez Lastra
      Pages: 113 - 125
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Borja Ramis Ferrer, Jose Luis Martinez Lastra
      The employment of cyber-physical systems allows the control of processes in modern production lines. On the other hand, several research works have recently presented how ontology-based knowledge representation can be a suitable method for modelling industrial systems. However, system models are located far away from where the data is generated which adds complexity for cross-domain communications and resource management. Current embedded devices can encapsulate ontological models that can be accessed as local resources. This article presents the integration of interconnected devices as the computational nodes of a cloud which is private and local. In this way, functionalities, such as knowledge management and process control can be performed closer to the industrial equipment. Moreover, this research work discusses the potential and challenges for performing distributed reasoning in the private local automation cloud. In addition, the article describes main aspects of the system architecture and the behaviour of the networked embedded devices in the cloud. The research work results will be used as a high-level roadmap for further system implementation.

      PubDate: 2017-02-10T09:06:50Z
      DOI: 10.1016/j.aei.2017.01.007
      Issue No: Vol. 32 (2017)
       
  • Self-corrective knowledge-based hybrid tracking system using BIM and
           multimodal sensors
    • Authors: JeeWoong Park; Jingdao Chen; Yong K. Cho
      Pages: 126 - 138
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): JeeWoong Park, Jingdao Chen, Yong K. Cho
      Researchers have recently devoted considerable attention to acquiring location awareness of assets. They have explored various technologies, such as video cameras, radio signal strength indicator-based sensors, and motion sensors, in the development of tracking systems. However, each system presents unique drawbacks especially when applied in complex indoor construction environments; this paper classifies them into two categories: absolute tracking and relative tracking. By understanding the nature of problems in each tracking category, this research develops a novel tracking methodology that uses knowledge of the strengths and weaknesses of various components used in the proposed tracking system. This paper presents the development of a hybrid-tracking system that integrates Bluetooth Low Energy (BLE) technology, motion sensors, and Building Information Model (BIM). The hypothesis tested through this integration was whether such knowledge-based integration could provide a method that can correct errors found in each of the used sensing technologies and thereby improve the reliability of the tracking system. Field experimental trials were conducted in a full-scale indoor construction site to assess the performance of individual components and the integrated system. The results indicated that the addition of map knowledge from a BIM model showed the capability of correcting improbable movements. Furthermore, the knowledge-based decision making process demonstrated its capability to make positive interaction by reducing the positioning errors by 42% on average. In sum, the proposed hybrid-tracking system presented a novel method to compensate for the weakness of each system component and thus achieve a more accurate and precise tracking in dynamic and complex indoor construction sites.

      PubDate: 2017-02-15T10:55:53Z
      DOI: 10.1016/j.aei.2017.02.001
      Issue No: Vol. 32 (2017)
       
  • Intelligent fault diagnosis of rolling bearing using hierarchical
           convolutional network based health state classification
    • Authors: Chen Lu; Zhenya Wang; Bo Zhou
      Pages: 139 - 151
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Chen Lu, Zhenya Wang, Bo Zhou
      Rolling bearing tips are often the most susceptible to electro-mechanical system failure due to high-speed and complex working conditions, and recent studies on diagnosing bearing health using vibration data have developed an assortment of feature extraction and fault classification methods. Due to the strong non-linear and non-stationary characteristics, an effective and reliable deep learning method based on a convolutional neural network (CNN) is investigated in this paper making use of cognitive computing theory, which introduces the advantages of image recognition and visual perception to bearing fault diagnosis by simulating the cognition process of the cerebral cortex. The novel feature representation method for bearing data is first discussed using supervised deep learning with the goal of identifying more robust and salient feature representations to reduce information loss. Next, the deep hierarchical structure is trained in a robust manner that is established using a transmitting rule of greedy training layer by layer. Convolution computation, rectified linear units, and sub-sampling are applied for weight replication and reducing the number of parameters that need to be learned to improve the general feed-forward back propagation training. The CNN model could thus reduce learning computation requirements in the temporal dimension, and an invariance level of working condition fluctuation and ambient noise is provided by identifying the elementary features of bearings. A top classifier followed by a back propagation process is used for fault classification. Contrast experiments and analyses have been undertaken to delineate the effectiveness of the CNN model for fault classification of rolling bearings.

      PubDate: 2017-03-01T21:30:59Z
      DOI: 10.1016/j.aei.2017.02.005
      Issue No: Vol. 32 (2017)
       
  • An error correction framework for sequences resulting from known
           state-transition models in Non-Intrusive Load Monitoring
    • Authors: Suman Giri; Mario Bergés
      Pages: 152 - 162
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Suman Giri, Mario Bergés
      Non-Intrusive Load Monitoring (NILM), the set of techniques used for disaggregating total electricity consumption in a building into its constituent electrical loads, has recently received renewed interest in the research community, partly due to the roll-out of smart metering technology worldwide. Event-based NILM approaches (i.e., those that are based on first segmenting the power time-series and associating each segment with the operation of electrical appliances) are a commonly implemented solution but are prone to the propagation of errors through the data processing pipeline. Thus, during energy estimation (the final step in the process), many corrections need to be made to account for errors incurred during segmentation, feature extraction and classification (the other steps typically present in event-based approaches). A robust framework for energy estimation should use the labels from classification to (1) model the different state transitions that can occur in an appliance; (2) account for any misclassifications by correcting event labels that violate the extracted model; and (3) accurately estimate the energy consumed by that appliance over a period of time. In this paper, we address the second problem by proposing an error-correcting algorithm which looks at sequences generated by Finite State Machines (FSMs) and corrects for errors in the sequence; errors are defined as state transitions that violate the said FSM. We evaluate our framework on simulated data and find that it improves energy estimation errors. We further test it on data from 43 appliances collected from 19 houses and find that the framework significantly improves errors in energy estimates when compared to the case with no correction in 19 appliances, leaves 17 appliances unchanged, and has a slightly negative impact on 6 appliances.

      PubDate: 2017-03-01T21:30:59Z
      DOI: 10.1016/j.aei.2017.01.006
      Issue No: Vol. 32 (2017)
       
  • The documentation of product configuration systems: A framework and an IT
           solution
    • Authors: Sara Shafiee; Lars Hvam; Anders Haug; Michael Dam; Katrin Kristjansdottir
      Pages: 163 - 175
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Sara Shafiee, Lars Hvam, Anders Haug, Michael Dam, Katrin Kristjansdottir
      When designing and maintaining a product configuration system (PCS), complete and up-to-date documentation of the system is needed in the form of a product model that outlines the structures, attributes, and constraints of the PCS. Furthermore, up-to-date documentation for the PCS is crucial for maintenance, further development, system quality and communication with domain experts. Product models are the main communication and documentation tools used in PCS projects. Recent studies have shown that up-to-date documentation for the PCS is often lacking due to the significant amount of work required to maintain product models. To address these challenges, this paper proposes an approach for documenting the PCS that is based on the structure, attributes, and constraints modelled within the PCS, in which the product model is generated directly from the PCS. The suggested approach avoids knowledge duplication, as knowledge needs to be maintained within the PCS only. It involves two steps: the first is the building of the initial product model, which is used for the programming of the PCS. In the second step, the product model is generated directly from the PCS and is based on the structure, attributes, and constraints inside the PCS. The product model does not need to be maintained, therefore, outside the PCS. This approach meets the demand for agile documentation and efficient communication with domain experts, and uses the fewest resources possible. Furthermore, to support the framework, an IT documentation system is proposed that is capable of retrieving knowledge from the PCS and thus generating the product model. Our framework and IT documentation system were developed and tested at a case company on five different projects. The results confirm that benefits can be achieved by using the proposed IT documentation system, as time and resources are saved, while the quality of the PCS is improved.
      Graphical abstract image

      PubDate: 2017-03-08T17:15:30Z
      DOI: 10.1016/j.aei.2017.02.004
      Issue No: Vol. 32 (2017)
       
  • Heuristic approach for solving employee bus routes in a large-scale
           industrial factory
    • Authors: Komgrit Leksakul; Uttapol Smutkupt; Raweeroj Jintawiwat; Suriya Phongmoo
      Pages: 176 - 187
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Komgrit Leksakul, Uttapol Smutkupt, Raweeroj Jintawiwat, Suriya Phongmoo
      This paper compares different methods for solving a location-routing problem (LRP), using real-world data from the bus transport service for employees of a large-scale industrial factory in Thailand. We tested four AI (artificial intelligence) techniques Maximin, K-means, Fuzzy C-means, and Competitive Learning and two hybrids of these four K-means with Competitive Learning and K-means with Maximin to allocate the bus stops. The efficiency of the algorithms was compared, in terms of the quality of the solutions. The K-means with Maximin provided the best solution, as it minimized number of bus stop locations and employees’ total traveling distance while satisfied employee at maximum radius 1.73km, compared to K-means with Competitive Learning, as the same number of bus stop it provided higher total traveling distance and maximum radius. The other non-hybrid techniques provided higher number of bus stop locations. We then used ant colony optimization (ACO) to determine the optimal routing between the 300–700 bus stops as allocated by K-means with Maximin. The optimal bus routing to transport the factory’s 5000 plus employees required 134 buses (134 independent routes) covering 500 bus stops and traveling nearly 5000km. While optimal, this routing was costly and created monitoring difficulties. To address these concerns, we constrained the number of bus routes; while this dramatically increased the total distance, it provided a more practical solution for the factory.

      PubDate: 2017-03-08T17:15:30Z
      DOI: 10.1016/j.aei.2017.02.006
      Issue No: Vol. 32 (2017)
       
  • Inspection equipment study for subway tunnel defects by grey-scale image
           processing
    • Authors: Hongwei Huang; Yan Sun; Yadong Xue; Fei Wang
      Pages: 188 - 201
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Hongwei Huang, Yan Sun, Yadong Xue, Fei Wang
      In recent years, much attention has been paid to Machine Vision-Based (MVB) technology for tunnel main defect (leakage and crack) inspection as an innovative technology. Based on the principle of MVB technology, various researchers have developed tunnel inspection equipment, but most of them need either a trailer or an external power supply, which cannot meet the demand of subway tunnel inspection in China. The limited inspection time, high demand for precision, rigid requirements of operational management and high cost of the equipment restrict the application of this method in China. MTI-100 (Moving Tunnel Inspection) was developed under these circumstances. To capture stable, high-quality images of the lining surface as the raw data of inspection, an image capture system is well designed based on CCD (Charge-coupled Device) camera scanning. Additionally, equipment optimization design of the mechanism and electricity requirements for the inspection accuracy of subway tunnel inspection is investigated. The maximal size and weight of equipment elements determined the convenience of inspection, which is primarily conditioned by these designs. The effects of lighting and vibration have been considered. A method to calculate the image shift caused by vibration is proposed. The software network is another core component of the equipment, which connects the image acquisition, image storage and defect recognition. The famous Otsu method is used for leakage recognition. A new algorithm based on the features of the local image grid is developed to recognize cracks. A comparative study shows its high accuracy for crack recognition. Finally, a simulative tunnel test and field inspection are undertaken to verify the performance of the non-destructive subway tunnel inspection equipment. Through these tests, the accuracy, stability, repeatability, labor intensity and efficiency of the equipment have been verified. A real project test certified that the developed MTI-100 is quite suitable for practical tunnel inspection.

      PubDate: 2017-03-27T04:17:29Z
      DOI: 10.1016/j.aei.2017.03.003
      Issue No: Vol. 32 (2017)
       
  • 3D parametric human face modeling for personalized product design:
           Eyeglasses frame design case
    • Authors: Chih-Hsing Chu; I-Jan Wang; Jeng-Bang Wang; Yuan-Ping Luh
      Pages: 202 - 223
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Chih-Hsing Chu, I-Jan Wang, Jeng-Bang Wang, Yuan-Ping Luh
      Personalized design enhances the values added by a product or service by satisfying individual customer requirements. It has nowadays become a trend in consumer product development. This paper proposes a computational framework for personalized design of the eyeglasses frame based on parametric face modeling. A large amount of three-dimensional facial models is collected by non-contact scanning as training data. Applying principal component analysis reduces the data complexity while preserving sufficient data variance. The reduced models are modified using cross-parameterization so that they have the same mesh connectivity. Kriging characterizes the correlation between the mesh point coordinates of a face model and a set of feature parameters. The Kriging result synthesizes 3D facial geometry approximating to individual users with given parameter values. Rendering the synthesized geometry with facial images of real persons generates realistic face models. These models not only allow adjusting the frame design in real-time, but also evaluating whether or how the design style fits individual face characteristics. This study enhances the practical values of 3D anthropometric data by realizing the concept of human-centric design.

      PubDate: 2017-03-27T04:17:29Z
      DOI: 10.1016/j.aei.2017.03.001
      Issue No: Vol. 32 (2017)
       
  • Selection of target LEED credits based on project information and climatic
           factors using data mining techniques
    • Authors: M.A. Jun; Jack C.P. Cheng
      Pages: 224 - 236
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): M.A. Jun, Jack C.P. Cheng
      Developed by the United States Green Building Council, Leadership in Energy and Environmental Design (LEED) is a credit-based rating system that provides third-party verification for green buildings. Selection of target credits is important yet challenging for LEED managers because various factors such as target certification grade level and building features need to be considered on a case-by-case basis. Local climatic factors could affect the selection of green building technologies and hence the target credits, but currently there is no research suggesting target LEED credits based on climatic factors. This paper presents a methodology for the selection of target LEED credits based on project information and climatic factors. This study focuses on projects certified with LEED for Existing Buildings (LEED-EB). Information of 912 projects and their surrounding climatic circumstances was collected and studied. 55 classification models for 47 LEED-EB credits were then constructed and optimized using three classification algorithms - Random Forests, AdaBoost Decision Tree, and Support Vector Machine (SVM). The results showed that Random Forests performed the best in most of the 55 classification models. With a combination of the three algorithms, the trained classification models were used to develop a web-based decision support system for LEED credit selection. The system was tested using 20 recently certified LEED projects, and the results showed that our system had an accuracy of 82.56%.

      PubDate: 2017-03-27T04:17:29Z
      DOI: 10.1016/j.aei.2017.03.004
      Issue No: Vol. 32 (2017)
       
  • A function-based computational method for design concept evaluation
    • Authors: Jia Hao; Qiangfu Zhao; Yan Yan
      Pages: 237 - 247
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Jia Hao, Qiangfu Zhao, Yan Yan
      Concept generation is an indispensable step of innovation design. However, the limited knowledge and design thinking fixation of designers often impede the generation of novel design concepts. Computational tools can be a necessary supplement for designers. They can generate a big number of design concepts based on an existing knowledge base. For filtering these design concepts, this work presents a computational measurement of novelty, feasibility and diversity based on 500,000 granted patents. First, about 1700 functional terms (terminologies) are mapped to high dimensional vectors (100 dimensional space) by word embedding technique. The resulted database is knowledge base-I (KB-I). Then, we adopt circular convolution to convert patents into high dimensional vectors. The resulted database is KB-II. Based on the two knowledge bases, the computational definitions of novelty, feasibility and diversity are developed. We conduct six experiments based on KB-II, a random dataset and a real product dataset, and the results show that these metrics can be used to roughly filter a big number of design concepts, and then expert-based method can be further used. This work provides a computational framework for measuring the novelty, feasibility and diversity of design concept.

      PubDate: 2017-04-03T15:24:46Z
      DOI: 10.1016/j.aei.2017.03.002
      Issue No: Vol. 32 (2017)
       
  • Signage visibility analysis and optimization system using BIM-enabled
           virtual reality (VR) environments
    • Authors: Ali Motamedi; Zhe Wang; Nobuyoshi Yabuki; Tomohiro Fukuda; Takashi Michikawa
      Pages: 248 - 262
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Ali Motamedi, Zhe Wang, Nobuyoshi Yabuki, Tomohiro Fukuda, Takashi Michikawa
      The proper placement of signage greatly influences pathfinding and information provision in public spaces. Clear visibility, easy comprehension, and efficient placement are all important for successful signage. We propose a signage visibility analysis and optimization system, utilizing an updated Building Information Model (BIM) and a game engine software application to simulate the movement of pedestrians. BIM can provide an up-to-date digital representation of a building and its assets, while computer simulation environments have the potential to simulate the movement of pedestrians. Combining these two technologies provides an opportunity to create a tool that analyzes the efficiency of installed signage and visualizes them in VR environments. The proposed tool contains algorithms, functions and predefined scenarios to calculate the coverage and the visibility of a building’s signage system. This system assists building managers to analyze (visually or by using statistics) the visibility of signboards, to assess their proper placement, and to optimize their placement. The applicability of the method has been validated in case studies performed in subway stations in Japan.

      PubDate: 2017-04-03T15:24:46Z
      DOI: 10.1016/j.aei.2017.03.005
      Issue No: Vol. 32 (2017)
       
  • Multi-class US traffic signs 3D recognition and localization via
           image-based point cloud model using color candidate extraction and
           texture-based recognition
    • Authors: Vahid Balali; Arash Jahangiri; Sahar Ghanipoor Machiani
      Pages: 263 - 274
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Vahid Balali, Arash Jahangiri, Sahar Ghanipoor Machiani
      Continuous condition monitoring and inspection of traffic signs are essential to ensure that safety and performance criteria are met. The use of 3D point cloud modeling by the construction industry has been significantly increased in recent years especially for recording the as-is conditions of facilities. The high-precision and dense 3D point clouds generated by photogrammetry can facilitate the process of asset condition assessment. This paper presents an automated computer-vision based method that detects, classifies, and localizes traffic signs via street-level image-based 3D point cloud models. The proposed pipeline integrates 3D object detection algorithm. An improved Structure-from-Motion (SfM) procedure is developed to create a 3D point cloud of roadway assets from the street level imagery. In order to assist with accurate 3D recognition and localization by color and texture features extraction, an automated process of point cloud cleaning and noise removal is proposed. Using camera pose information from SfM, the points within the bounding box of detected traffic signs are then projected into the cleaned point cloud by using the triangulation method (linear and non-linear) and the 3D points corresponding to the traffic sign in question are labeled and visualized in 3D. The proposed framework is validated using real-life data, which represent the most common types of traffic signs. The robustness of the proposed pipeline is evaluated by analyzing the accuracy in detection of traffic signs as well as the accuracy in localization in 3D point cloud model. The results promise to better and more accurate visualize the location of the traffic signs with respect to other roadway assets in 3D environment.

      PubDate: 2017-04-03T15:24:46Z
      DOI: 10.1016/j.aei.2017.03.006
      Issue No: Vol. 32 (2017)
       
  • Crowd-based velocimetry for surface flows
    • Authors: Yao-Yu Yang; Shih-Chung Kang
      Pages: 275 - 286
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Yao-Yu Yang, Shih-Chung Kang
      Flow velocity measurement is important in hydrology. Recently, owing to the popularity of sensors and processors, image-based flow velocity measurement methods have become an important research direction. Particle image velocimetry (PIV) is a key example. However, due to the uncertainty of the features, PIV sometimes provides very inaccurate results and always requires customized setups. In this research, we take advantage of the human perception system, that is, the strong abilities related to feature identification and tracking, in order to estimate the surface flow velocity of a river. We developed a method called crowd-based velocimetry (CBV) to incorporate the human perception capacity in the estimation of the flow velocity. CBV includes three main steps: (1) video processing, (2) crowd processing, and (3) statistical processing. We validated CBV by measuring a fast, steady, and uniform river surface flow in an artificial canal. The results show that compared to radar measurements from the center of the flow, CBV measured the surface flow velocity with a deviation ranging between +12.1% and +17.3% from the radar measurement, while PIV resulted in a −1.7% to −24.3% deviation. With rapidly improving mobile devices, CBV allows enormous numbers of people to engage in flow measurement, making CBV more reliable, more efficient, and more economical.

      PubDate: 2017-04-10T15:44:52Z
      DOI: 10.1016/j.aei.2017.03.007
      Issue No: Vol. 32 (2017)
       
  • Fast convergence optimization model for single and multi-purposes
           reservoirs using hybrid algorithm
    • Authors: Mohammad Ehteram; Sayed-Farhad Mousavi; Hojat Karami; Saeed Farzin; Mohammad Emami; Faridah Binti Othman; Zahra Amini; Ozgur Kisi; Ahmed El-Shafie
      Pages: 287 - 298
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Mohammad Ehteram, Sayed-Farhad Mousavi, Hojat Karami, Saeed Farzin, Mohammad Emami, Faridah Binti Othman, Zahra Amini, Ozgur Kisi, Ahmed El-Shafie
      Developing optimal operation policy for single or multi-purposes dams and reservoirs is a complex engineering application. The main reasons for such complexity are the stochastic nature of the system input and slow convergence of the optimization method. Furthermore, searching optimal operation for multi-purposes or chain reservoir systems, becomes even more complex because of interfering operations between successive dams. In this study, a new hybrid algorithm has been introduced by merging the genetic algorithm (GA) with the krill algorithm. In fact, the proposed hybrid algorithm amalgamates the advantages of both algorithms, first, the ability to converge fast for global optimum and, second, considering the effect of stochastic nature of the system. Three benchmark functions were used to evaluate the performance of this proposed optimization model. In addition, the proposed hybrid algorithm was examined for Karun-4 reservoir in Iran as an example for a hydro-power generation dam. Two benchmark problems of hydropower operations for multi-purposes reservoir systems, namely four-reservoir and ten-reservoir systems were considered in the study. Results showed that the proposed hybrid algorithm outperformed the well-developed traditional nonlinear programming solvers, such as Lingo 8 software.

      PubDate: 2017-04-10T15:44:52Z
      DOI: 10.1016/j.aei.2017.04.001
      Issue No: Vol. 32 (2017)
       
  • A descriptive semantics of modelling process catering for whole product
           parametric
    • Authors: Xiao-Bo Ge; Xiao-Dong Shao; Shen Li; Dou Wang
      Pages: 299 - 311
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Xiao-Bo Ge, Xiao-Dong Shao, Shen Li, Dou Wang
      To date, the entire product parametric technology has made great progress to significantly improve product design efficiency. However, the technology uses an established modelling process, which makes it very difficult to adapt to changing product requirements. A method that can be customised for the whole machine is discussed in this paper; this method is intended to increase the adaptability of the entire product parametric technology. First, a frame model concept is proposed based on an analysis of a large number of product modelling processes. Second, a semantic model for describing the modelling process is proposed, and its instantiation is studied. Next, according to the semantics of the modelling process, a product parametric modelling system is established. Finally, based on an examination of the electronic module modelling, it was found that modelling efficiency increased significantly.

      PubDate: 2017-04-24T16:28:01Z
      DOI: 10.1016/j.aei.2017.04.004
      Issue No: Vol. 32 (2017)
       
  • An IFC schema extension and binary serialization format to efficiently
           integrate point cloud data into building models
    • Authors: Thomas Krijnen; Jakob Beetz
      Abstract: Publication date: Available online 3 April 2017
      Source:Advanced Engineering Informatics
      Author(s): Thomas Krijnen, Jakob Beetz
      In this paper we suggest an extension to the Industry Foundation Classes (IFC) model to integrate point cloud datasets. The proposal includes a schema extension to the core model allowing the storage of points, either as Cartesian coordinates, points in parametric space of associated building element surfaces or as discrete height fields projected as grids onto building elements. To handle the considerable amounts of data generated in the process of scanning building structures, we present intelligent compression approaches combined with the Hierarchical Data Format (HDF) as an efficient serialization and an alternative to clear text encoded ISO 10303 part 21 files. Based on prototypical implementations we show results of various serialization options and their impacts on storage efficiency. In this proposal the deepened semantic relationships have been favoured over compression ratios. Nevertheless, with various near-lossless layers of compression and binary serialization applied, a compression ratio of up to 67.7% is obtained for a building model with integrated point clouds, compared to the raw source data. The binary serialization is able to handle hundreds of millions of points, out of which specific spatial and semantic subsets can rapidly be extracted due to the containerized hierarchical storage model and association to building elements. The authors advocate the use of binary storage for sizeable point cloud scans, but also show how especially the grid discretization can result into usable points cloud segments embedded into text-based IFC models.

      PubDate: 2017-04-10T15:44:52Z
      DOI: 10.1016/j.aei.2017.03.008
       
  • A framework to design a human-centred adaptive manufacturing system for
           aging workers
    • Authors: Margherita Peruzzini; Marcello Pellicciari
      Abstract: Publication date: Available online 22 February 2017
      Source:Advanced Engineering Informatics
      Author(s): Margherita Peruzzini, Marcello Pellicciari
      The so-called smart manufacturing systems (SMS) combine smart manufacturing technologies, cyber-physical infrastructures, and data control to realize predictive and adaptive behaviours. In this context, industrial research focused mainly on improving the manufacturing system performance, almost neglecting human factors (HF) and their relation to the production systems. However, in order to create an effective smart factory context, human performance should be included to drive smart system adaptation in efficient and effective way, also by exploiting the linkages between tangible and intangible entities offered by Industry 4.0. Furthermore, modern companies are facing another interesting trend: aging workers. The age of workers is generally growing up and, consequently, the percentage of working 45–64years old population with different needs, capabilities, and reactions, is increasing. This research focuses on the design of human-centred adaptive manufacturing systems (AMS) for the modern companies, where aging workers are more and more common. In particular, it defines a methodology to design AMS able to adapt to the aging workers’ needs considering their reduced workability, due to both physical and cognitive functional decrease, with the final aim to improve the human-machine interaction and the workers’ wellbeing. The paper finally presents an industrial case study focusing on the woodworking sector, where an existing machine has been re-designed to define a new human-centred AMS. The new machine has been engineered and prototyped by adopting cyber-physical systems (CPS) and pervasive technologies to smartly adapt the machine behaviour to the working conditions and the specific workers’ skills, tasks, and cognitive-physical abilities, with the final aim to support aging workers. The achieved benefits were expressed in terms of system usability, focusing on human-interaction quality.

      PubDate: 2017-02-22T21:18:34Z
      DOI: 10.1016/j.aei.2017.02.003
       
  • The generation of hierarchic structures via robust 3D topology
           optimisation
    • Authors: Hèrm Hofmeyer; Mattias Schevenels; Sjonnie Boonstra
      Abstract: Publication date: Available online 21 February 2017
      Source:Advanced Engineering Informatics
      Author(s): Hèrm Hofmeyer, Mattias Schevenels, Sjonnie Boonstra
      Commonly used building structures often show a hierarchic layout of structural elements. It can be questioned whether such a layout originates from practical considerations, e.g. related to its construction, or that it is (relatively) optimal from a structural point of view. This paper investigates this question by using topology optimisation in an attempt to generate hierarchical structures. As an arbitrarily standard design case, the principle of a traditional timber floor that spans in one direction is used. The optimisation problem is first solved using classical sensitivity and density filtering. This leads indeed to solutions with a hierarchic layout, but they are practically unusable as the floor boarding is absent. A Heaviside projection is therefore considered next, but this does not solve the problem. Finally, a robust approach is followed, and this does result in a design similar to floor boarding supported by timber joists. The robust approach is then followed to study a floor with an opening, two floors that span in two directions, and an eight-level concrete building. It can be concluded that a hierarchic layout of structural elements likely originates from being optimal from a structural point of view. Also clear is that this conclusion cannot be obtained by means of standard topology optimisation based on sensitivity or density filtering (as often found in commercial finite element codes); robust 3D optimisation is required to obtain a usable, constructible (or in the future: 3D printable) structural design, with a crisp black-and-white density distribution.

      PubDate: 2017-02-22T21:18:34Z
      DOI: 10.1016/j.aei.2017.02.002
       
  • Are you a human or a humanoid: Predictive user modelling through
           behavioural analysis of online gameplay data
    • Authors: Chen Gao; Kaiqi Jin; Haifeng Shen; Muhammed Ali Babar
      Abstract: Publication date: Available online 7 February 2017
      Source:Advanced Engineering Informatics
      Author(s): Chen Gao, Kaiqi Jin, Haifeng Shen, Muhammed Ali Babar
      Intelligent agents are widely used in robotics, gaming and simulation. A key issue is modelling human behaviours so that intelligent agents can use a human’s behavioural model to imitate them and predict their next moves. In this article, we use Internet-based multiplayer online gaming (MOG) as a case study to present our approach to predictive user modelling through behavioural analysis of online gameplay data. As latency is an inherited bottleneck of the Internet and is likely to remain so into a foreseeable future, a lot of efforts have been made to address the resulting issues. Most of the existing latency handling techniques are based on the assumption that latency is within an acceptable threshold so that they can alleviate or even completely hide its negative impact on players’ quality of experience (QoE) that directly determines consumers’ satisfaction of the provided MOG services. While this assumption is mostly valid, it is worth noting that a player’s Internet connection latency always fluctuates (known as jitter), possibly to the extent of exceeding a MOG’s designated threshold in which case none of the techniques can handle properly but disconnecting the player from the gameplay session. Forcing a player to quit prematurely simply due to a spike of unusual high latency has a significant negative impact both on the gameplay’s fairness and on the player’s QoE. To improve customer satisfaction of a MOG service, we propose a more tolerant approach by temporarily substituting a player with a humanoid bot in the event of latency hikes so that the player always remains in the gameplay session. The challenge in this approach is to create a personalised humanoid bot that can imitate the playing pattern of the individual human player being substituted. Our solution is to first extract key variables that have impact on the human player’s decision-makings through behavioural analysis of the player’s historical gameplay data, then model the relationships among these variables, and finally creates the player’s humanoid bot with the model. In this paper, we use a multiplayer online pong game as a case study to explain behavioural variables, modelling techniques, processes, outcomes, and performance studies.

      PubDate: 2017-02-10T09:06:50Z
      DOI: 10.1016/j.aei.2017.01.004
       
  • Advanced design, analysis, and implementation of pervasive and smart
           collaborative systems enabled with knowledge modelling and big data
           analytics
    • Authors: Amy J.C. Trappey; Fredrik Elgh; Timo Hartmann; Anne James; Josip Stjepandic; Charles V. Trappey; Nel Wognum
      Abstract: Publication date: Available online 4 February 2017
      Source:Advanced Engineering Informatics
      Author(s): Amy J.C. Trappey, Fredrik Elgh, Timo Hartmann, Anne James, Josip Stjepandic, Charles V. Trappey, Nel Wognum


      PubDate: 2017-02-10T09:06:50Z
      DOI: 10.1016/j.aei.2017.01.001
       
  • Recognition of process patterns for BIM-based construction schedules
    • Authors: Kateryna Sigalov; Markus König
      Abstract: Publication date: Available online 18 January 2017
      Source:Advanced Engineering Informatics
      Author(s): Kateryna Sigalov, Markus König
      Construction scheduling is a very demanding and time intensive process. Building information modeling (BIM) is becoming increasingly important for planning and scheduling, as it provides significant support for this difficult assignment. Further improvements can be achieved by applying predefined process templates for BIM-based schedules. It can reduce the planning time and thus increase the productivity. However, a manual definition of proper and application-specific process templates is very challenging. The automatic detection of recurring similar configurations of construction processes, called process patterns, would greatly support this complex task. Identified process patterns can be subsequently generalized, supporting the design of process templates. This contribution presents an overall concept for process pattern recognition in BIM-based construction schedules by applying graph-based methods. Due to the fact that graph matching algorithms are in general very time- and resource-consuming, an indexing technique based on features is used to solve this problem more efficiently. The paper focuses on the estimation of similarity in construction schedules, describing feature-based methods and similarity measure definitions in detail. Another emphasis is the preparation of schedules for the recognition of process patterns, including decomposition of schedules into smaller parts, referred to as subschedules, and normalization of features. The potential of this concept is demonstrated by two different case studies. The proper results of the evaluation show that the proposed method and similarity metrics are sufficient for the recognition of process patterns in construction schedules.

      PubDate: 2017-01-22T08:30:34Z
      DOI: 10.1016/j.aei.2016.12.003
       
  • Leveraging existing occupancy-related data for optimal control of
           commercial office buildings: A review
    • Authors: Weiming Shen; Guy Newsham; Burak Gunay
      Abstract: Publication date: Available online 18 January 2017
      Source:Advanced Engineering Informatics
      Author(s): Weiming Shen, Guy Newsham, Burak Gunay
      A primary strategy for the energy-efficient operation of commercial office buildings is to deliver building services, including lighting, heating, ventilating, and air conditioning (HVAC), only when and where they are needed, in the amount that they are needed. Since such building services are usually delivered to provide occupants with satisfactory indoor conditions, it is important to accurately determine the occupancy of building spaces in real time as an input to optimal control. This paper first discusses the concepts of building occupancy resolution and accuracy and briefly reviews conventional (explicit) occupancy detection approaches. The focus of this paper is to review and classify emerging, potentially low-cost approaches to leveraging existing data streams that may be related to occupancy, usually referred to as implicit/ambient/soft sensing approaches. Based on a review and a comparison of related projects/systems (in terms of occupancy sensing type, resolution, accuracy, ground truth data collection method, demonstration scale, data fusion and control strategies) the paper presents the state-of-the-art of leveraging existing occupancy-related data for optimal control of commercial office buildings. It also briefly discusses technology trends, challenges, and future research directions.

      PubDate: 2017-01-22T08:30:34Z
      DOI: 10.1016/j.aei.2016.12.008
       
  • Knowledge-based design for assembly in agile manufacturing by using Data
           Mining methods
    • Authors: R. Kretschmer; A. Pfouga; S. Rulhoff; J. Stjepandić
      Abstract: Publication date: Available online 10 January 2017
      Source:Advanced Engineering Informatics
      Author(s): R. Kretschmer, A. Pfouga, S. Rulhoff, J. Stjepandić
      Decision making in early production planning phases is typically based on a rough estimation due to lack of a comprehensive, reliable knowledge base. Virtual planning has been prevailed as a method used to evaluate risks and costs before the concrete realization of production processes. The process of product assembly, which yields a high share in total production costs, gets its particular importance. This paper introduces a new approach and its initial implementation for knowledge-based design for assembly in agile manufacturing by using data mining (DM) methods in the field of series production with high variance. The approach adopts the usage of bulk data with old, successful designs in order to extrapolate its scope for assembly processes. Especially linked product and process data allow the innovative usage of DM methods in order to facilitate the front loading in the product development. The concept presents an affordable assistance potential for development of new products variants along the product emergence process (PEP). With this approach an early cost estimation of assembly processes in series production can be conducted using advanced DM methods as shown in an industrial use case. Furthermore, design and planning processes can be supported effectively.

      PubDate: 2017-01-14T09:16:24Z
      DOI: 10.1016/j.aei.2016.12.006
       
  • A collaborative system for capturing and reusing in-context design
           knowledge with an integrated representation model
    • Authors: Gongzhuang Peng; Hongwei Wang; Heming Zhang; Yanwei Zhao; Aylmer L. Johnson
      Abstract: Publication date: Available online 5 January 2017
      Source:Advanced Engineering Informatics
      Author(s): Gongzhuang Peng, Hongwei Wang, Heming Zhang, Yanwei Zhao, Aylmer L. Johnson
      Current research on design knowledge capture and reuse has predominantly focused on either the codification view of knowledge or the personalisation view of knowledge, resulting in a failure to address designers’ knowledge needs caused by a lack of context of information and insufficient computational support. Precisely motivated by this gap, this work aims to address the integration of these two views into a complete, contextual and trustworthy knowledge management scheme enabled by the emerging collaborative technologies. Specifically, a knowledge model is developed to represent an integrated knowledge space, which can combine geometric model, knowledge-based analysis codes and problem-solving strategies and processes. On this basis, a smart collaborative system is also designed and developed to streamline the design process as well as to facilitate knowledge capture, retrieval and reuse as users with different roles are working on various tasks within this process. An engineering case study is undertaken to demonstrate the idea of collaborative knowledge creation and sharing and evaluate the effectiveness of the knowledge representation model and the collaborative technologies employed. As evidenced in the development and evaluation, the methods proposed are effective for capturing an integrated knowledge space and the collaborative knowledge management system not only facilitates problem-solving using knowledge-based analysis but also supplies in-context tacit knowledge captured from the communications between users throughout the design process.

      PubDate: 2017-01-06T09:02:10Z
      DOI: 10.1016/j.aei.2016.12.007
       
  • An encryption approach for product assembly models
    • Authors: X.T. Cai; S. Wang; X. Lu; W.D. Li
      Abstract: Publication date: Available online 28 December 2016
      Source:Advanced Engineering Informatics
      Author(s): X.T. Cai, S. Wang, X. Lu, W.D. Li
      In a collaboration environment, it is a challenge how to effectively share the information needed for collaboration while protecting other confidential information in a product assembly model. In this paper, an innovative encryption approach for assembly models to support collaboration is presented. This approach is content based encryption and effective for the secure sharing of feature-based assembly models. In the approach, a classification algorithm for features in an assembly model to be shared or protected during collaboration has been first developed. An encryption algorithm for a feature has been then designed to ensure the parameterization, topological and geometrical validity, and self-adaptability of the encrypted feature. An algorithm for parts with multiple encryption features has been developed. Based on the above algorithms, parts are finally assembled and the geometry and topology of the assembling structure are kept un-changed to enhance collaborators’ interoperability. The characteristics and innovations of the approach include: (1) the approach is feature based, integrative into the main-stream commercial Computer Aided Design (CAD) systems, and flexible to meet various users’ needs for encrypting features selected by users during collaboration, (2) in the approach, the topological and geometrical validity of an assembly model after encryption is maintained to ensure effective collaboration on the assembly, and (3) the approach is parametrically controlled through adjusting position and size parameters so as to ensure the user friendliness of using the approach. A case study with complex geometries and assembly structures has been used to validate the effectiveness and robustness of the approach in industrial applications.

      PubDate: 2017-01-06T09:02:10Z
      DOI: 10.1016/j.aei.2016.12.001
       
  • Reference tag supported RFID tracking using robust support vector
           regression and Kalman filter
    • Authors: Jian Chai; Changzhi Wu; Chuanxin Zhao; Hung-Lin Chi; Xiangyu Wang; Bingo Wing-Kuen Ling; Kok Lay Teo
      Pages: 1 - 10
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): Jian Chai, Changzhi Wu, Chuanxin Zhao, Hung-Lin Chi, Xiangyu Wang, Bingo Wing-Kuen Ling, Kok Lay Teo
      Site operations usually contain potential safety issues and an effective monitoring strategy for operations is essential to predict and prevent risk. Regarding the status monitoring among material, equipment and personnel during site operations, much work is conducted on localization and tracking using Radio Frequency Identification (RFID) technology. However, existing RFID tracking methods suffer from low accuracy and instability, due to severe interference in industrial sites with many metal structures. To improve RFID tracking performance in industrial sites, a RFID tracking method that integrates Multidimensional Support Vector Regression (MSVR) and Kalman filter is developed in this paper. Extensive experiments have been conducted on a Liquefied Natural Gas (LNG) facility site with long range active RFID system to evaluate the performance of this approach. The results demonstrate the effectiveness and stability of the proposed approach with severe noise and outliers. It is feasible to adopt the proposed approach which satisfies intrinsically-safe regulations for monitoring operation status in current practice.

      PubDate: 2016-12-21T08:23:24Z
      DOI: 10.1016/j.aei.2016.11.002
      Issue No: Vol. 32 (2016)
       
  • A real-time automatic pavement crack and pothole recognition system for
           mobile Android-based devices
    • Authors: A. Tedeschi; F. Benedetto
      Pages: 11 - 25
      Abstract: Publication date: April 2017
      Source:Advanced Engineering Informatics, Volume 32
      Author(s): A. Tedeschi, F. Benedetto
      Due to the rapid growth of vehicles and traffic accidents caused by road pavement defects, road safety has become a pressing concern worldwide. For this reason, Countries and Federal States have started focusing their resources on the analysis of civil infrastructures to assess their safety and serviceability. The analyses are performed by specialized teams of inspectors and structural engineers who manually inspect road infrastructures and provide detailed reports about the detected pavement distresses and their magnitudes. This work aims at providing a new system able to detect the framed distress using solely the computational resources provided by a mobile device To reach this goal, an automatic pavement distress recognition system based on the OpenCV library is developed and embedded in a mobile application, enabling the recognition of three common pavement distresses: Pothole, Longitudinal-Transversal Cracks, and Fatigue Cracks. Our method, tested on several Android mobile platforms, is able recognize the pavement distresses of interest reaching more than 0.7 of Precision, Recall, Accuracy, and F-Measure. This application promises to improve the on-site work of inspectors by decreasing the time required to perform inspections while ensuring, at the same time, a higher level of accuracy.

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2016.12.004
      Issue No: Vol. 32 (2016)
       
  • Bridging qualitative spatial constraints and feature-based parametric
           modelling: Expressing visibility and movement constraints
    • Authors: Carl Schultz; Mehul Bhatt; André Borrmann
      Pages: 2 - 17
      Abstract: Publication date: January 2017
      Source:Advanced Engineering Informatics, Volume 31
      Author(s): Carl Schultz, Mehul Bhatt, André Borrmann
      We present a concept for integrating state-of-the-art methods in geometric and qualitative spatial representation and reasoning with feature-based parametric modelling systems. Using a case-study involving a combination of topological, visibility, and movement constraints, we demonstrate the manner in which a parametric model may be constrained by the spatial aspects of conceptual design specifications and higher-level semantic design requirements. We demonstrate the proposed methodology by applying it to architectural floor plan layout design, where a number of spaces with well defined functionalities have to be arranged such that particular functional design constraints are maintained. The case-study is developed by an integration of the declarative spatial reasoning system CLP(QS) (CLP(QS) – a declarative spatial reasoning system. www.spatial-reasoning.com.) with the parametric CAD system FreeCAD.

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2015.10.004
      Issue No: Vol. 31 (2016)
       
  • Combining visual natural markers and IMU for improved AR based indoor
           navigation
    • Authors: Matthias Neges; Christian Koch; Markus König; Michael Abramovici
      Pages: 18 - 31
      Abstract: Publication date: January 2017
      Source:Advanced Engineering Informatics, Volume 31
      Author(s): Matthias Neges, Christian Koch, Markus König, Michael Abramovici
      The operation and maintenance phase is the longest and most expensive life-cycle period of buildings and facilities. Operators need to carry out activities to maintain equipment to prevent functionality failures. Although some software tools have already been introduced, research studies have concluded that (1) facility handover data is still predominantly dispersed, unformatted and paper-based and (2) hence operators still spend 50% of their on-site work on target localization and navigation. To improve these procedures, the authors previously presented a natural marker-based Augmented Reality (AR) framework that digitally supports facility maintenance operators when navigating indoors. Although previous results showed the practical potential, this framework fails if no visual marker is available, if identical markers are at multiple locations, and if markers are light emitting signs. To overcome these shortcomings, this paper presents an improved method that combines an Inertial Measurement Unit (IMU) based step counter and visual live video feed for AR based indoor navigation support. In addition, the AR based marker detection procedure is improved by learning camera exposure times in case of light emitting markers. A case study and experimental results in a controlled environment reveal the improvements and advantages of the enhanced framework.

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2015.10.005
      Issue No: Vol. 31 (2016)
       
  • Application of clustering for the development of retrofit strategies for
           large building stocks
    • Authors: Philipp Geyer; Arno Schlüter; Sasha Cisar
      Pages: 32 - 47
      Abstract: Publication date: January 2017
      Source:Advanced Engineering Informatics, Volume 31
      Author(s): Philipp Geyer, Arno Schlüter, Sasha Cisar
      In order to reduce energy consumption and emissions from the built environment, it is vital to transform the existing building stock and develop retrofit strategies to achieve energy efficiency and building-integrated renewable energy supply. Compared to developing cost-optimal retrofit strategies for one building, the development of strategies for 100 to up to 10,000 buildings remains a major challenge. This paper presents a method to cluster buildings based on their sensitivity to different retrofit measures, focusing on the cost-effectiveness. Derived from algorithmic clustering and combined with time and cost data, a tailored development of retrofit strategies for large building stocks becomes possible. Improved identification of retrofit measures and strategies, in contrast to the conventional classification based on building type and age, is demonstrated. The method is illustrated, using the data from the case study project ‘Zernez Energia 2020’, which aims to achieve carbon neutrality of a Swiss alpine village.

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2016.02.001
      Issue No: Vol. 31 (2016)
       
  • BIMTag: Concept-based automatic semantic annotation of online BIM product
           resources
    • Authors: Ge Gao; Yu-Shen Liu; Pengpeng Lin; Meng Wang; Ming Gu; Jun-Hai Yong
      Pages: 48 - 61
      Abstract: Publication date: January 2017
      Source:Advanced Engineering Informatics, Volume 31
      Author(s): Ge Gao, Yu-Shen Liu, Pengpeng Lin, Meng Wang, Ming Gu, Jun-Hai Yong
      With the rapid popularity of Building Information Modeling (BIM) technologies, BIM resources such as building product libraries are growing rapidly on the World Wide Web. However, numerous BIM resources are usually from heterogeneous systems or various manufacturers with ambiguous expressions and uncertain categories for product descriptions, which cannot provide effective support for information retrieval and categorization applications. Therefore, there is an increasing need for semantic annotation to reduce the ambiguity and unclearness of natural language in BIM documents. Based on Industry Foundation Classes (IFC) which is a major standard for BIM, this paper presents a concept-based automatic semantic annotation method for the documents of online BIM products. The method mainly consists of the following two stages. Firstly, with reference to the concepts and relationships explicitly defined in IFC, a word-level annotation algorithm is applied to the word-sense disambiguation. Secondly, based on latent semantic analysis technique, a document-level annotation algorithm is proposed to discover the relationships which are not explicitly defined in IFC. Finally, a prototype annotation system, named BIMTag, is developed and combined with a search engine for demonstrating the utility and effectiveness of our method. The BIMTag system is available at http://cgcad.thss.tsinghua.edu.cn/liuyushen/bimtag/.
      Graphical abstract image

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2015.10.003
      Issue No: Vol. 31 (2016)
       
  • Modularized design-oriented systematic inventive thinking approach
           supporting collaborative service innovations
    • Authors: Yu-Hui Wang; Ching-Hung Lee; Amy J.C. Trappey
      Abstract: Publication date: Available online 24 December 2016
      Source:Advanced Engineering Informatics
      Author(s): Yu-Hui Wang, Ching-Hung Lee, Amy J.C. Trappey
      The rapid evolution of new service systems raises crucial challenges for service design and requires effective methods. This study depicts a conceptual service design framework, called design-oriented systematic inventive thinking (DSIT) approach, which can be applied in different problem contexts. DSIT is presented as a new systematic and collaborative intelligence approach for creating and evaluating complex service systems using multi-criteria data analytics. DSIT synthesizes the current field of TRIZ service-design knowledge system and the emerging area of non-TRIZ service-design knowledge system. DSIT enables integrated development of service offerings at four dimensions and provides the matching integrated service design approach for each dimension. Four types of service design approaches are conceptualized as “human-independent service engineering,” “problem-clarified service engineering,” “solution-converged service engineering,” and “designing for service.” A new service computer-aided design system (service CAD) named DSIT explorer is developed consisting of customization, compatibility, and extensiveness of DSIT modules. A pervasive and smart collaborative service system (i.e., the smart MOS burger service solution) designed using DSIT explorer is illustrated. DSIT is a holistic, interdisciplinary, and collaborative service design concept, which is incorporated into a collaborative and intelligent service CAD framework to enable systematic inventive thinking throughout phases of service design lifecycle from problem definition, problem resolution, to solution evaluation.

      PubDate: 2016-12-28T08:39:14Z
      DOI: 10.1016/j.aei.2016.11.006
       
  • A review of essential standards and patent landscapes for the Internet of
           Things: A key enabler for Industry 4.0
    • Authors: Amy J.C. Trappey; Charles V. Trappey; Usharani Hareesh Govindarajan; Allen C. Chuang; John J. Sun
      Abstract: Publication date: Available online 20 December 2016
      Source:Advanced Engineering Informatics
      Author(s): Amy J.C. Trappey, Charles V. Trappey, Usharani Hareesh Govindarajan, Allen C. Chuang, John J. Sun
      This paper is a formal overview of standards and patents for Internet of Things (IoT) as a key enabler for the next generation advanced manufacturing, referred as Industry 4.0 (I 4.0). IoT at the fundamental level is a means of connecting physical objects to the Internet as a ubiquitous network that enables objects to collect and exchange information. The manufacturing industry is seeking versatile manufacturing service provisions to overcome shortened product life cycles, increased labor costs, and fluctuating customer needs for competitive marketplaces. This paper depicts a systematic approach to review IoT technology standards and patents. The thorough analysis and overview include the essential standard landscape and the patent landscape based on the governing standards organizations for America, Europe and China where most global manufacturing bases are located. The literature of emerging IoT standards from the International Organization for Standardization (ISO), the International Electrotechnical Commission (IEC) and the Guobiao standards (GB), and global patents issued in US, Europe, China and World Intellectual Property Organization (WIPO) are systematically presented in this study.

      PubDate: 2016-12-21T08:23:24Z
      DOI: 10.1016/j.aei.2016.11.007
       
  • Extracting failure time data from industrial maintenance records using
           text mining
    • Authors: Kazi Arif-Uz-Zaman; Michael E. Cholette; Lin Ma; Azharul Karim
      Abstract: Publication date: Available online 9 December 2016
      Source:Advanced Engineering Informatics
      Author(s): Kazi Arif-Uz-Zaman, Michael E. Cholette, Lin Ma, Azharul Karim
      Reliability modelling requires accurate failure time of an asset. In real industrial cases, such data are often buried in different historical databases which were set up for purposes other than reliability modelling. In particular, two data sets are commonly available: work orders (WOs), which detail maintenance activities on the asset, and downtime data (DD), which details when the asset was taken offline. Each is incomplete from a failure perspective, where one wishes to know whether each downtime event was due to failure or scheduled activities. In this paper, a text mining approach is proposed to extract accurate failure time data from WOs and DD. A keyword dictionary is constructed using WO text descriptions and classifiers are constructed and applied to attribute each of the DD events to one of two classes: failure or nonfailure. The proposed method thus identifies downtime events whose descriptions are consistent with urgent unplanned WOs. The applicability of the methodology is demonstrated on maintenance data sets from an Australian electricity and sugar processing companies. Analysis of the text of the identified failure events seems to confirm the accurate identification of failures in DD. The results are expected to be immediately useful in improving the estimation of failure times (and thus the reliability models) for real-world assets.

      PubDate: 2016-12-14T08:04:25Z
      DOI: 10.1016/j.aei.2016.11.004
       
  • Metamodeling of Smart Environments: from design to implementation
    • Authors: Franco Cicirelli; Giancarlo Fortino; Antonio Guerrieri; Giandomenico Spezzano; Andrea Vinci
      Abstract: Publication date: Available online 3 December 2016
      Source:Advanced Engineering Informatics
      Author(s): Franco Cicirelli, Giancarlo Fortino, Antonio Guerrieri, Giandomenico Spezzano, Andrea Vinci
      A smart environment is a physical environment enriched with sensing, actuation, communication and computation capabilities aiming at acquiring and exploiting knowledge about the environment so as to adapt itself to its inhabitants’ preferences and requirements. In this domain, there is the need of tools supporting the design and analysis of applications. In this paper, the Smart Environment Metamodel (SEM) framework is proposed. The framework allows to model applications by exploiting concepts specific to the smart environment domain. SEM approaches the modeling from two different points of view, namely the functional and data perspectives. The application of the framework is supported by a set of general guidelines to drive the analysis, the design and the implementation of smart environments. The effectiveness of the framework is shown by applying it to the modeling of a real smart office scenario that has been developed, deployed and analyzed.

      PubDate: 2016-12-07T13:56:52Z
      DOI: 10.1016/j.aei.2016.11.005
       
  • Platform as a service gateway for the Fog of Things
    • Authors: Nandor Verba; Kuo-Ming Chao Anne James Daniel Goldsmith Xiang Fei
      Abstract: Publication date: Available online 30 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Nandor Verba, Kuo-Ming Chao, Anne James, Daniel Goldsmith, Xiang Fei, Sergiu-Dan Stan
      Internet of Things (IoT), one of the key research topics in recent years, together with concepts from Fog Computing, brings rapid advancements in Smart City, Monitoring Systems, industrial control, transportation and other fields. These applications require a reconfigurable sensor architecture that can span multiple scenarios, devices and use cases that allow storage, networking and computational resources to be efficiently used on the edge of the network. There are a number of platforms and gateway architectures that have been proposed to manage these components and enable application deployment. These approaches lack horizontal integration between multiple providers as well as higher order functionalities like load balancing and clustering. This is partly due to the strongly coupled nature of the deployed applications, a lack of abstraction of device communication layers as well as a lock-in for communication protocols. This limitation is a major obstacle for the development of a protocol agnostic application environment that allows for single application to be migrated and to work with multiple peripheral devices with varying protocols from different local gateways. This research looks at existing platforms and their shortcomings as well as proposes a messaging based modular gateway platform that enables clustering of gateways and the abstraction of peripheral communication protocol details. These novelties allow applications to send and receive messages regardless of their deployment location and destination device protocol, creating a more uniform development environment. Furthermore, it results in a more streamlined application development and testing while providing more efficient use of the gateway’s resources. Our evaluation of a prototype for the system shows the need for the migration of resources and the QoS advantages of such a system. The examined use case scenarios show that clustering proves to be an advantage in certain use cases as well as presenting the deployment of a larger testing and control environment through the platform.

      PubDate: 2016-12-01T14:35:39Z
       
  • Assessment and weighting of meteorological ensemble forecast members based
           on supervised machine learning with application to runoff simulations and
           flood warning
    • Authors: Kristina Doycheva; Gordon Horn; Christian Koch; Andreas Schumann; Markus König
      Abstract: Publication date: Available online 24 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Kristina Doycheva, Gordon Horn, Christian Koch, Andreas Schumann, Markus König
      Numerical weather forecasts, such as meteorological forecasts of precipitation, are inherently uncertain. These uncertainties depend on model physics as well as initial and boundary conditions. Since precipitation forecasts form the input into hydrological models, the uncertainties of the precipitation forecasts result in uncertainties of flood forecasts. In order to consider these uncertainties, ensemble prediction systems are applied. These systems consist of several members simulated by different models or using a single model under varying initial and boundary conditions. However, a too wide uncertainty range obtained as a result of taking into account members with poor prediction skills may lead to underestimation or exaggeration of the risk of hazardous events. Therefore, the uncertainty range of model-based flood forecasts derived from the meteorological ensembles has to be restricted. In this paper, a methodology towards improving flood forecasts by weighting ensemble members according to their skills is presented. The skill of each ensemble member is evaluated by comparing the results of forecasts corresponding to this member with observed values in the past. Since numerous forecasts are required in order to reliably evaluate the skill, the evaluation procedure is time-consuming and tedious. Moreover, the evaluation is highly subjective, because an expert who performs it makes his decision based on his implicit knowledge. Therefore, approaches for the automated evaluation of such forecasts are required. Here, we present a semi-automated approach for the assessment of precipitation forecast ensemble members. The approach is based on supervised machine learning and was tested on ensemble precipitation forecasts for the area of the Mulde river basin in Germany. Based on the evaluation results of the specific ensemble members, weights corresponding to their forecast skill were calculated. These weights were then successfully used to reduce the uncertainties within rainfall-runoff simulations and flood risk predictions.

      PubDate: 2016-12-01T14:35:39Z
      DOI: 10.1016/j.aei.2016.11.001
       
  • A string-wise CRDT algorithm for smart and large-scale collaborative
           editing systems
    • Authors: Xiao Lv; Fazhi He; Weiwei Cai; Yuan Cheng
      Abstract: Publication date: Available online 24 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Xiao Lv, Fazhi He, Weiwei Cai, Yuan Cheng
      With the development of big data and cloud computing, real-time collaborative editing systems have to face new challenges. How to support string-wise operations for smart and large-scale collaborations is one of the key issues in next generation of collaborative editing systems, which is both the core topic of collaborative computing area and the fundamental research of many collaborative systems in science and engineering. However, string-wise operations have troubled the existing collaborative editing algorithms, including Operational Transformation (OT) and Commutative Replicated Data Type (CRDT), for many years. This paper proposes a novel and efficient CRDT algorithm that integrates string-wise operations for smart and massive-scale collaborations. Firstly, the proposed algorithm ensures the convergence and maintains operation intentions of collaborative users under an integrated string-wise framework. Secondly, formal proofs are provided to prove both the correctness of the proposed algorithm and the intentions preserving of string-wise operations. Thirdly, the time complexity of the proposed algorithm has been analyzed in theory to be lower than that of the state of the art OT algorithm and CRDT algorithm. Fourthly, experiment evaluations show that the proposed algorithm outperforms the state of the art OT algorithm and CRDT algorithm.

      PubDate: 2016-12-01T14:35:39Z
      DOI: 10.1016/j.aei.2016.10.005
       
  • Evaluation of quality of service provisioning in large-scale pervasive and
           smart collaborative wireless sensor and actor networks
    • Authors: Goran Horvat; Drago Zagar; Jelena Vlaovic
      Abstract: Publication date: Available online 17 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Goran Horvat, Drago Zagar, Jelena Vlaovic
      With the production of low cost sensors, classical concept of Wireless Sensor Networks (WSNs) evolved into large-scale concept hosting thousands of nodes within a network and generating abundant quantities of data. As these networks are being continuously developed a new class of WSNs are proposed: Wireless Sensor and Actor Networks (WSANs). These networks introduce the actuating component, alongside with the sensing component, where QoS is becoming a very significant factor. The authors of this paper approach the problem of QoS support in large-scale WSAN from a physical layer, where the deployment parameters effects on QoS metrics are demystified. The analysis is formulated on two scenarios: worst case scenario (all nodes transmit data towards the network sink) and best case scenario (a single node transmits a stream of data towards a network sink). For both scenarios two routing protocols were compared, a simple flooding algorithm and a simple distance vector protocol. Also, a new relation between hop count and latency based on transmission power is observed, not reported in the available literature, resulting in a new proposed empirical latency model.

      PubDate: 2016-11-19T02:18:35Z
      DOI: 10.1016/j.aei.2016.10.003
       
  • Integrating affective features with engineering features to seek the
           optimal product varieties with respect to the niche segments
    • Authors: Chih-Hsuan Wang; Hsin-Tze Chin
      Abstract: Publication date: Available online 12 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Chih-Hsuan Wang, Hsin-Tze Chin
      In recent years, the popularity of smart phones substantially leads to poor sales of the low-end digital cameras. One of the most astounding industry news is Kodak’s bankruptcy in 2011 although Kodak was a pioneer in the field of digital still cameras. In reality, not only functional capability but also affective design can influence user purchase intentions on consumer electronics. In this paper, both affective features (AFs), and engineering features (EFs) are considered to achieve successful product planning. In particular, two critical issues are addressed: (1) market partitioning and (2) product differentiation. Initially, Kansei engineering is employed to capture user attitude toward AFs. Then, a classification tree is constructed to carry out effective market partitioning. Secondly, correspondence analysis is applied to capture user perceptions of EFs for identifying the core features that best characterize distinct market segments. Finally, VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) ranking is conducted to prioritize various product portfolios to accomplish product differentiation. In summary, the presented framework can help industrial practitioners transform diverse customer requirements into attractive alternatives while keep controllable manufacturing costs.
      Graphical abstract image

      PubDate: 2016-11-19T02:18:35Z
      DOI: 10.1016/j.aei.2016.10.002
       
  • A collaborative web-based platform for the prescription of Custom-Made
           Insoles
    • Authors: Marco Mandolini; Agnese Brunzini; Michele Germani
      Abstract: Publication date: Available online 4 November 2016
      Source:Advanced Engineering Informatics
      Author(s): Marco Mandolini, Agnese Brunzini, Michele Germani
      Many foot pathologies are prevented or treated with Custom Made Insoles (CMIs). Although a strong computerization has characterized the shoe development process during the last decade, the CMI sector still lacks a software platform integrating the design and diagnosis tools used by the stakeholders of this area. Moreover, the prescription of CMIs is only based on the experience of skilled podiatrists rather than on a common and shared knowledge (e.g. guidelines, best practices, rules, etc.). This paper presents a multi-users and knowledge-based platform, called Smart Prescription Platform (SPP), covering the whole CMI development phases, from foot diagnosis to the production, involving clinicians, patients, manufacturers and controllers. The web-based platform is fully integrated with the technologies available in the orthopaedic sector, which are 3D/4D scanners, baropodometric platforms, footwear virtual catalogues, plantar pressure simulators, Augmented Reality devices and 3D CAD systems. The use of standard file formats (e.g. .stl, .bmp, .xml) allows an electronic dataflow among the tools. The main module of the platform, called Prescription System (PS), is used for prescribing custom-made insoles for patients with different health conditions, satisfying the needs of all actors and optimizing the data exchange. PS is a knowledge-based prescription system integrating the best practices related to the prescription of CMIs. The PS output is a XML file representing the electronic order, used to exchange data with the other tools of the SPP. The proposed platform has been tested with a twofold aim: to validate the usability of the Prescription System and the inter-operability of the platform tools. The positive results gathered during the validation, led the experts to start using the web platform for their daily work.

      PubDate: 2016-11-06T08:07:27Z
      DOI: 10.1016/j.aei.2016.10.004
       
  • Computing advances applied for building design, operation, retrofit and
           supply chain information processing
    • Authors: Haijiang Li; Timo Hartmann
      Abstract: Publication date: Available online 3 August 2016
      Source:Advanced Engineering Informatics
      Author(s): Haijiang Li, Timo Hartmann


      PubDate: 2016-08-06T19:00:31Z
      DOI: 10.1016/j.aei.2016.07.002
       
 
 
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