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Publisher: Hindawi   (Total: 330 journals)

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Showing 1 - 200 of 330 Journals sorted alphabetically
Abstract and Applied Analysis     Open Access   (Followers: 3, SJR: 0.343, CiteScore: 1)
Active and Passive Electronic Components     Open Access   (Followers: 7, SJR: 0.136, CiteScore: 0)
Advances in Acoustics and Vibration     Open Access   (Followers: 33, SJR: 0.147, CiteScore: 0)
Advances in Aerospace Engineering     Open Access   (Followers: 52)
Advances in Agriculture     Open Access   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Astronomy     Open Access   (Followers: 36, SJR: 0.257, CiteScore: 1)
Advances in Bioinformatics     Open Access   (Followers: 17, SJR: 0.565, CiteScore: 2)
Advances in Biology     Open Access   (Followers: 8)
Advances in Chemistry     Open Access   (Followers: 21)
Advances in Civil Engineering     Open Access   (Followers: 38, SJR: 0.539, CiteScore: 1)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Condensed Matter Physics     Open Access   (Followers: 10, SJR: 0.315, CiteScore: 1)
Advances in Decision Sciences     Open Access   (Followers: 3, SJR: 0.303, CiteScore: 1)
Advances in Electrical Engineering     Open Access   (Followers: 26)
Advances in Electronics     Open Access   (Followers: 65)
Advances in Emergency Medicine     Open Access   (Followers: 11)
Advances in Endocrinology     Open Access   (Followers: 5)
Advances in Environmental Chemistry     Open Access   (Followers: 5)
Advances in Epidemiology     Open Access   (Followers: 8)
Advances in Fuzzy Systems     Open Access   (Followers: 5, SJR: 0.161, CiteScore: 1)
Advances in Geology     Open Access   (Followers: 14)
Advances in Geriatrics     Open Access   (Followers: 5)
Advances in Hematology     Open Access   (Followers: 11, SJR: 0.661, CiteScore: 2)
Advances in Hepatology     Open Access   (Followers: 2)
Advances in High Energy Physics     Open Access   (Followers: 19, SJR: 0.866, CiteScore: 2)
Advances in Human-Computer Interaction     Open Access   (Followers: 20, SJR: 0.186, CiteScore: 1)
Advances in Materials Science and Engineering     Open Access   (Followers: 30, SJR: 0.315, CiteScore: 1)
Advances in Mathematical Physics     Open Access   (Followers: 4, SJR: 0.218, CiteScore: 1)
Advances in Medicine     Open Access   (Followers: 2)
Advances in Meteorology     Open Access   (Followers: 20, SJR: 0.48, CiteScore: 1)
Advances in Multimedia     Open Access   (Followers: 1, SJR: 0.173, CiteScore: 1)
Advances in Nonlinear Optics     Open Access   (Followers: 6)
Advances in Numerical Analysis     Open Access   (Followers: 5)
Advances in Nursing     Open Access   (Followers: 26)
Advances in Operations Research     Open Access   (Followers: 12, SJR: 0.205, CiteScore: 1)
Advances in Optical Technologies     Open Access   (Followers: 3, SJR: 0.214, CiteScore: 1)
Advances in Optics     Open Access   (Followers: 3)
Advances in OptoElectronics     Open Access   (Followers: 6, SJR: 0.141, CiteScore: 0)
Advances in Orthopedics     Open Access   (Followers: 8, SJR: 0.922, CiteScore: 2)
Advances in Pharmacological Sciences     Open Access   (Followers: 7, SJR: 0.591, CiteScore: 2)
Advances in Physical Chemistry     Open Access   (Followers: 9, SJR: 0.179, CiteScore: 1)
Advances in Power Electronics     Open Access   (Followers: 29, SJR: 0.184, CiteScore: 0)
Advances in Preventive Medicine     Open Access   (Followers: 5)
Advances in Public Health     Open Access   (Followers: 23)
Advances in Software Engineering     Open Access   (Followers: 10)
Advances in Statistics     Open Access   (Followers: 4)
Advances in Toxicology     Open Access   (Followers: 2)
Advances in Tribology     Open Access   (Followers: 12, SJR: 0.265, CiteScore: 1)
Advances in Urology     Open Access   (Followers: 9, SJR: 0.51, CiteScore: 1)
Advances in Virology     Open Access   (Followers: 7, SJR: 0.838, CiteScore: 2)
AIDS Research and Treatment     Open Access   (Followers: 3, SJR: 0.758, CiteScore: 2)
Analytical Cellular Pathology     Open Access   (Followers: 2, SJR: 0.886, CiteScore: 2)
Anatomy Research Intl.     Open Access   (Followers: 2)
Anemia     Open Access   (Followers: 5, SJR: 0.669, CiteScore: 2)
Anesthesiology Research and Practice     Open Access   (Followers: 14, SJR: 0.501, CiteScore: 1)
Applied and Environmental Soil Science     Open Access   (Followers: 16, SJR: 0.451, CiteScore: 1)
Applied Bionics and Biomechanics     Open Access   (Followers: 8, SJR: 0.288, CiteScore: 1)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Archaea     Open Access   (Followers: 3, SJR: 0.852, CiteScore: 2)
Arthritis     Open Access   (Followers: 5, SJR: 0.454, CiteScore: 1)
Autism Research and Treatment     Open Access   (Followers: 25)
Autoimmune Diseases     Open Access   (Followers: 3, SJR: 0.805, CiteScore: 2)
Behavioural Neurology     Open Access   (Followers: 9, SJR: 0.786, CiteScore: 2)
Biochemistry Research Intl.     Open Access   (Followers: 6, SJR: 0.437, CiteScore: 2)
Bioinorganic Chemistry and Applications     Open Access   (Followers: 10, SJR: 0.419, CiteScore: 2)
BioMed Research Intl.     Open Access   (Followers: 4, SJR: 0.935, CiteScore: 3)
Biotechnology Research Intl.     Open Access   (Followers: 1)
Bone Marrow Research     Open Access   (Followers: 2, SJR: 0.531, CiteScore: 1)
Canadian J. of Gastroenterology & Hepatology     Open Access   (Followers: 5, SJR: 0.867, CiteScore: 1)
Canadian J. of Infectious Diseases and Medical Microbiology     Open Access   (Followers: 5, SJR: 0.548, CiteScore: 1)
Canadian Respiratory J.     Open Access   (Followers: 1, SJR: 0.474, CiteScore: 1)
Cardiology Research and Practice     Open Access   (Followers: 8, SJR: 1.237, CiteScore: 4)
Case Reports in Anesthesiology     Open Access   (Followers: 10)
Case Reports in Cardiology     Open Access   (Followers: 3, SJR: 0.219, CiteScore: 0)
Case Reports in Critical Care     Open Access   (Followers: 8)
Case Reports in Dentistry     Open Access   (Followers: 5, SJR: 0.229, CiteScore: 0)
Case Reports in Dermatological Medicine     Open Access   (Followers: 2)
Case Reports in Emergency Medicine     Open Access   (Followers: 14)
Case Reports in Endocrinology     Open Access   (Followers: 1, SJR: 0.209, CiteScore: 1)
Case Reports in Gastrointestinal Medicine     Open Access   (Followers: 2)
Case Reports in Genetics     Open Access   (Followers: 1)
Case Reports in Hematology     Open Access   (Followers: 5)
Case Reports in Hepatology     Open Access   (Followers: 1)
Case Reports in Immunology     Open Access   (Followers: 4)
Case Reports in Infectious Diseases     Open Access   (Followers: 5)
Case Reports in Medicine     Open Access   (Followers: 2)
Case Reports in Nephrology     Open Access   (Followers: 4)
Case Reports in Neurological Medicine     Open Access   (Followers: 1)
Case Reports in Obstetrics and Gynecology     Open Access   (Followers: 10)
Case Reports in Oncological Medicine     Open Access   (Followers: 2, SJR: 0.204, CiteScore: 1)
Case Reports in Ophthalmological Medicine     Open Access   (Followers: 3)
Case Reports in Orthopedics     Open Access   (Followers: 5)
Case Reports in Otolaryngology     Open Access   (Followers: 6)
Case Reports in Pathology     Open Access   (Followers: 5)
Case Reports in Pediatrics     Open Access   (Followers: 6)
Case Reports in Psychiatry     Open Access   (Followers: 12)
Case Reports in Pulmonology     Open Access   (Followers: 3)
Case Reports in Radiology     Open Access   (Followers: 8)
Case Reports in Rheumatology     Open Access   (Followers: 5)
Case Reports in Surgery     Open Access   (Followers: 11)
Case Reports in Transplantation     Open Access  
Case Reports in Urology     Open Access   (Followers: 8)
Case Reports in Vascular Medicine     Open Access  
Case Reports in Veterinary Medicine     Open Access   (Followers: 6)
Child Development Research     Open Access   (Followers: 17, SJR: 0.144, CiteScore: 0)
Chinese J. of Engineering     Open Access   (Followers: 2, SJR: 0.114, CiteScore: 0)
Chinese J. of Mathematics     Open Access  
Cholesterol     Open Access   (Followers: 1, SJR: 0.424, CiteScore: 1)
Chromatography Research Intl.     Open Access   (Followers: 6)
Complexity     Hybrid Journal   (Followers: 6, SJR: 0.531, CiteScore: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2, SJR: 0.403, CiteScore: 1)
Computational Intelligence and Neuroscience     Open Access   (Followers: 10, SJR: 0.326, CiteScore: 1)
Contrast Media & Molecular Imaging     Open Access   (Followers: 3, SJR: 0.842, CiteScore: 3)
Critical Care Research and Practice     Open Access   (Followers: 10, SJR: 0.499, CiteScore: 1)
Current Gerontology and Geriatrics Research     Open Access   (Followers: 9, SJR: 0.512, CiteScore: 2)
Depression Research and Treatment     Open Access   (Followers: 13, SJR: 0.816, CiteScore: 2)
Dermatology Research and Practice     Open Access   (Followers: 3, SJR: 0.806, CiteScore: 2)
Diagnostic and Therapeutic Endoscopy     Open Access   (SJR: 0.201, CiteScore: 1)
Discrete Dynamics in Nature and Society     Open Access   (Followers: 5, SJR: 0.279, CiteScore: 1)
Disease Markers     Open Access   (Followers: 1, SJR: 0.9, CiteScore: 2)
Education Research Intl.     Open Access   (Followers: 19)
Emergency Medicine Intl.     Open Access   (Followers: 7, SJR: 0.298, CiteScore: 1)
Enzyme Research     Open Access   (Followers: 3, SJR: 0.653, CiteScore: 3)
Evidence-based Complementary and Alternative Medicine     Open Access   (Followers: 20, SJR: 0.683, CiteScore: 2)
Game Theory     Open Access   (Followers: 1)
Gastroenterology Research and Practice     Open Access   (Followers: 2, SJR: 0.768, CiteScore: 2)
Genetics Research Intl.     Open Access   (Followers: 1, SJR: 0.61, CiteScore: 2)
Geofluids     Open Access   (Followers: 4, SJR: 0.952, CiteScore: 2)
Hepatitis Research and Treatment     Open Access   (Followers: 6, SJR: 0.389, CiteScore: 2)
HPB Surgery     Open Access   (Followers: 5, SJR: 0.824, CiteScore: 2)
Infectious Diseases in Obstetrics and Gynecology     Open Access   (Followers: 5, SJR: 1.27, CiteScore: 2)
Interdisciplinary Perspectives on Infectious Diseases     Open Access   (Followers: 1, SJR: 0.627, CiteScore: 2)
Intl. J. of Aerospace Engineering     Open Access   (Followers: 73, SJR: 0.232, CiteScore: 1)
Intl. J. of Agronomy     Open Access   (Followers: 5, SJR: 0.311, CiteScore: 1)
Intl. J. of Alzheimer's Disease     Open Access   (Followers: 11, SJR: 0.787, CiteScore: 3)
Intl. J. of Analysis     Open Access  
Intl. J. of Analytical Chemistry     Open Access   (Followers: 20, SJR: 0.285, CiteScore: 1)
Intl. J. of Antennas and Propagation     Open Access   (Followers: 11, SJR: 0.233, CiteScore: 1)
Intl. J. of Atmospheric Sciences     Open Access   (Followers: 21)
Intl. J. of Biodiversity     Open Access   (Followers: 4)
Intl. J. of Biomaterials     Open Access   (Followers: 4, SJR: 0.511, CiteScore: 2)
Intl. J. of Biomedical Imaging     Open Access   (Followers: 3, SJR: 0.501, CiteScore: 2)
Intl. J. of Breast Cancer     Open Access   (Followers: 13, SJR: 1.025, CiteScore: 2)
Intl. J. of Cell Biology     Open Access   (Followers: 3, SJR: 1.887, CiteScore: 4)
Intl. J. of Chemical Engineering     Open Access   (Followers: 7, SJR: 0.327, CiteScore: 1)
Intl. J. of Chronic Diseases     Open Access   (Followers: 1)
Intl. J. of Computer Games Technology     Open Access   (Followers: 9, SJR: 0.287, CiteScore: 2)
Intl. J. of Corrosion     Open Access   (Followers: 10, SJR: 0.194, CiteScore: 1)
Intl. J. of Dentistry     Open Access   (Followers: 6, SJR: 0.649, CiteScore: 2)
Intl. J. of Differential Equations     Open Access   (Followers: 7, SJR: 0.191, CiteScore: 0)
Intl. J. of Digital Multimedia Broadcasting     Open Access   (Followers: 5, SJR: 0.296, CiteScore: 2)
Intl. J. of Electrochemistry     Open Access   (Followers: 8)
Intl. J. of Endocrinology     Open Access   (Followers: 4, SJR: 1.012, CiteScore: 3)
Intl. J. of Engineering Mathematics     Open Access   (Followers: 5)
Intl. J. of Food Science     Open Access   (Followers: 3, SJR: 0.44, CiteScore: 2)
Intl. J. of Forestry Research     Open Access   (Followers: 3, SJR: 0.373, CiteScore: 1)
Intl. J. of Genomics     Open Access   (Followers: 2, SJR: 0.868, CiteScore: 3)
Intl. J. of Geophysics     Open Access   (Followers: 4, SJR: 0.182, CiteScore: 1)
Intl. J. of Hepatology     Open Access   (Followers: 4, SJR: 0.874, CiteScore: 2)
Intl. J. of Hypertension     Open Access   (Followers: 6, SJR: 0.578, CiteScore: 1)
Intl. J. of Inflammation     Open Access   (SJR: 1.264, CiteScore: 3)
Intl. J. of Inorganic Chemistry     Open Access   (Followers: 3)
Intl. J. of Manufacturing Engineering     Open Access   (Followers: 2)
Intl. J. of Mathematics and Mathematical Sciences     Open Access   (Followers: 3, SJR: 0.177, CiteScore: 0)
Intl. J. of Medicinal Chemistry     Open Access   (Followers: 6, SJR: 0.31, CiteScore: 1)
Intl. J. of Metals     Open Access   (Followers: 4)
Intl. J. of Microbiology     Open Access   (Followers: 4, SJR: 0.662, CiteScore: 2)
Intl. J. of Microwave Science and Technology     Open Access   (Followers: 3, SJR: 0.136, CiteScore: 1)
Intl. J. of Navigation and Observation     Open Access   (Followers: 20, SJR: 0.267, CiteScore: 2)
Intl. J. of Nephrology     Open Access   (Followers: 1, SJR: 0.697, CiteScore: 1)
Intl. J. of Optics     Open Access   (Followers: 7, SJR: 0.231, CiteScore: 1)
Intl. J. of Otolaryngology     Open Access   (Followers: 3)
Intl. J. of Partial Differential Equations     Open Access   (Followers: 2)
Intl. J. of Pediatrics     Open Access   (Followers: 6)
Intl. J. of Peptides     Open Access   (Followers: 4, SJR: 0.46, CiteScore: 1)
Intl. J. of Photoenergy     Open Access   (Followers: 2, SJR: 0.341, CiteScore: 1)
Intl. J. of Plant Genomics     Open Access   (Followers: 4, SJR: 0.583, CiteScore: 1)
Intl. J. of Polymer Science     Open Access   (Followers: 24, SJR: 0.298, CiteScore: 1)
Intl. J. of Population Research     Open Access   (Followers: 2)
Intl. J. of Reconfigurable Computing     Open Access   (SJR: 0.123, CiteScore: 1)
Intl. J. of Reproductive Medicine     Open Access   (Followers: 4)
Intl. J. of Rheumatology     Open Access   (Followers: 4, SJR: 0.645, CiteScore: 2)
Intl. J. of Rotating Machinery     Open Access   (Followers: 2, SJR: 0.193, CiteScore: 1)
Intl. J. of Spectroscopy     Open Access   (Followers: 6)
Intl. J. of Stochastic Analysis     Open Access   (Followers: 3, SJR: 0.279, CiteScore: 1)
Intl. J. of Surgical Oncology     Open Access   (Followers: 1, SJR: 0.573, CiteScore: 2)
Intl. J. of Telemedicine and Applications     Open Access   (Followers: 4, SJR: 0.403, CiteScore: 2)
Intl. J. of Vascular Medicine     Open Access   (SJR: 0.782, CiteScore: 2)
Intl. J. of Zoology     Open Access   (Followers: 2, SJR: 0.209, CiteScore: 1)
Intl. Scholarly Research Notices     Open Access   (Followers: 196)
ISRN Astronomy and Astrophysics     Open Access   (Followers: 6)
J. of Addiction     Open Access   (Followers: 12)
J. of Advanced Transportation     Hybrid Journal   (Followers: 13, SJR: 0.581, CiteScore: 1)
J. of Aerodynamics     Open Access   (Followers: 5)
J. of Aging Research     Open Access   (Followers: 6, SJR: 0.573, CiteScore: 2)
J. of Amino Acids     Open Access   (Followers: 2, SJR: 0.474, CiteScore: 2)
J. of Analytical Methods in Chemistry     Open Access   (Followers: 1, SJR: 0.323, CiteScore: 1)
J. of Anthropology     Open Access   (Followers: 19)
J. of Applied Chemistry     Open Access   (Followers: 5)

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Journal Prestige (SJR): 0.531
Citation Impact (citeScore): 2
Number of Followers: 6  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1076-2787 - ISSN (Online) 1099-0526
Published by Hindawi Homepage  [330 journals]
  • Neural Dynamics during Resting State: A Functional Magnetic Resonance
           Imaging Exploration with Reduction and Visualization
    • Abstract: The brain is a complex high-order system. Body movements or mental activities are both dependent on the transmission of information among billions of neurons. However, potential patterns are hardly discoverable due to the high dimensionality in neural signals. Previous studies have identified rotary trajectories in rhythm and nonrhythm movements when projecting the neural electrical signals into a two-dimensional space. However, it is unclear how well this analogy holds at the resting state. Given the low-frequency fluctuations noted during spontaneous neural activities using functional magnetic resonance imaging (fMRI), it is natural to hypothesize that the neural response at resting state also shows a periodic trajectory. In this study, we explored the potential patterns in resting state fMRI data at four frequency bands (slow 2–slow 5) on two cohorts, one of which consisted of young and elderly adults and the other of patients with Alzheimer’s disease and normal controls (NC). The jPCA algorithm was applied to reduce the high-dimensional BOLD signal into a two-dimensional space for visualization of the trajectory. The results indicated that the “resting state” is a basic state showing an inherent dynamic pattern with a low frequency and long period during normal aging, with changes appearing in the rotary period at the slow 4 frequency band (0.027–0.073 Hz) during the pathological process of Alzheimer’s disease (AD). These findings expand the original understanding that neural signals can rotate themselves and that motor executive signals consist of neural signals. Meanwhile, the rotary period at band slow 4 may be a physiological marker for AD, and studies of this frequency band may be useful for understanding the potential pathophysiology of AD and ultimately facilitate characterization and auxiliary diagnosis of AD.
      PubDate: Tue, 19 Jun 2018 08:26:20 +000
  • Control of Complex Nonlinear Dynamic Rational Systems
    • Abstract: Nonlinear rational systems/models, also known as total nonlinear dynamic systems/models, in an expression of a ratio of two polynomials, have roots in describing general engineering plants and chemical reaction processes. The major challenge issue in the control of such a system is the control input embedded in its denominator polynomials. With extensive searching, it could not find any systematic approach in designing this class of control systems directly from its model structure. This study expands the U-model-based approach to establish a platform for the first layer of feedback control and the second layer of adaptive control of the nonlinear rational systems, which, in principle, separates control system design (without involving a plant model) and controller output determination (with solving inversion of the plant U-model). This procedure makes it possible to achieve closed-loop control of nonlinear systems with linear performance (transient response and steady-state accuracy). For the conditions using the approach, this study presents the associated stability and convergence analyses. Simulation studies are performed to show off the characteristics of the developed procedure in numerical tests and to give the general guidelines for applications.
      PubDate: Thu, 14 Jun 2018 05:47:23 +000
  • Integrating “Hard” and “Soft” Infrastructural Resilience
           Assessment for Water Distribution Systems
    • Abstract: Cities are highly dynamic systems, whose resilience is affected by the interconnectedness between “hard” and “soft” infrastructures. “Hard infrastructures” are the functional networks with physical elements providing goods or services. “Soft infrastructures” (culture, governance, and social patterns) encompass the social networks, make the hard infrastructures work, and are vital for understanding the consequences of disasters and the effectiveness of emergency management. Although the dynamic interactions between such infrastructures are highly complex in the case of the occurrence of hazardous events, it is fundamental to analyze them. The reliability of hard infrastructures during emergency management contributes to keep alive the social capital, while the community, its networks, and its own resilience influence the service provided by infrastructural systems. Resilience-thinking frameworks overcome the limits of the traditional engineering-oriented approaches, accounting for complexity of socio-technical-organizational networks, bridging the static and dynamic components of disasters across pre- and postevent contexts. The present work develops an integrated approach to operatively assess resilience for the hard and soft infrastructural systems, aiming at modeling the complexity of their interaction by adopting a graph theory-based approach and social network analysis. The developed approach has been experimentally implemented for assessing the integrated resilience of the hard/soft infrastructures during the L’Aquila 2009 earthquake.
      PubDate: Thu, 14 Jun 2018 00:00:00 +000
  • Energy and Complexity
    • PubDate: Wed, 13 Jun 2018 09:35:41 +000
  • An RBFNN-Based Direct Inverse Controller for PMSM with Disturbances
    • Abstract: Considering the system uncertainties, such as parameter changes, modeling error, and external uncertainties, a radial basis function neural network (RBFNN) controller using the direct inverse method with the satisfactory stability for improving universal function approximation ability, convergence, and disturbance attenuation capability is advanced in this paper. The weight adaptation rule of the RBFNN is obtained online by Lyapunov stability analysis method to guarantee the identification and tracking performances. The simulation example for the position tracking control of PMSM is studied to illustrate the effectiveness and the applicability of the proposed RBFNN-based direct inverse control method.
      PubDate: Wed, 13 Jun 2018 00:00:00 +000
  • Multiple-Model Adaptive Estimation with A New Weighting Algorithm
    • Abstract: The state estimation of a complex dynamic stochastic system is described by a discrete-time state-space model with large parameter (including the covariance matrices of system noises and measurement noises) uncertainties. A new scheme of weighted multiple-model adaptive estimation is presented, in which the classical weighting algorithm is replaced by a new weighting algorithm to reduce the calculation burden and to relax the convergence conditions. Finally, simulation results verified the effectiveness of the proposed MMAE scheme for each possibility of parameter uncertainties.
      PubDate: Wed, 13 Jun 2018 00:00:00 +000
  • Rigorous Solution of Slopes’ Stability considering Hydrostatic
    • Abstract: According to characteristics of soils in failure, a sliding mechanism of slopes in limit state is divided into five parts, for building a slip line field satisfying all possible boundary conditions. An algorithm is built to obtain the rigorous solution approaching upper and lower bound values simultaneously, which satisfies the static boundary and the kinematical boundary based on the slip line field, while stress discontinuity line and velocity discontinuity line are key points. This algorithm is copared with the Spencer method to prove its feasibility with a special example. The variation of rigorous solution, including an ultimate load and a sliding belt the rigid body sliding along rather than a single slip surface for friction-type soils, is achieved considering hydrostatic pressure with soil parameters changing.
      PubDate: Tue, 12 Jun 2018 09:22:10 +000
  • Sparse Gene Coexpression Network Analysis Reveals EIF3J-AS1 as a
           Prognostic Marker for Breast Cancer
    • Abstract: Predictive and prognostic biomarkers facilitate the selection of treatment strategies that can improve the survival of patients. Accumulating evidence indicates that long noncoding RNAs (lncRNAs) play important roles in cancer progression, with diagnostic and prognostic potential. However, few prognostic lncRNAs are reported for breast cancer, and little is known about their functions that contribute to cancer pathogenesis. In this paper, we used weighted correlation network analysis (WGCNA) to construct networks containing noncoding and protein-coding genes based on their expression in 1097 breast cancer patients. The differentially expressed genes were significantly overlapped with gene modules regulating cell cycle and cell adhesion. The cell cycle-related lncRNAs were consistently downregulated in breast cancer. One lncRNA, EIF3J-AS1, is significantly associated with clinicopathological characteristics, including tumor size, lymph node metastasis, estrogen receptor (ER), and progesterone receptor (PR) status. Kaplan–Meier survival analysis revealed that EIF3J-AS1, a downregulated lncRNA in breast tumor, is a potential prognostic marker for breast cancer. EIF3J-AS1 may function in an estrogen-independent manner and could be inhibited by the compound FDI-6. Therefore, integrating sparse gene coexpression network and clinicopathological features can accelerate identification and functional characterization of novel prognostic lncRNAs in breast cancer.
      PubDate: Tue, 12 Jun 2018 07:26:18 +000
  • AIRank: Author Impact Ranking through Positions in Collaboration Networks
    • Abstract: Citation is a universally acknowledged way for scientific impact evaluation. However, due to its easy manipulability, simply relying on citation cannot objectively reflect the actual impact of scholars. Instead of citation, we utilize the academic networks, in virtue of their available and abundant academic information, to evaluate the scientific impact of scholars in this paper. Through the collaboration among scholars in academic networks, we notice an interesting phenomenon that scholars in some special positions can access more kinds of information and connect researchers from different groups to promote the scientific collaborations. However, this important fact is generally ignored by the existing approaches. Motivated by the observations above, we propose the novel method AIRank to evaluate the scientific impact of scholars. Our method not only considers the impact of scholars through the mutual reinforcement process in heterogeneous academic networks, but also integrates the structural holes theory and information entropy theory to depict the benefit that scholars obtain via their positions in the network. The experimental results demonstrate the effectiveness of AIRank in evaluating the impact of scholars more comprehensively and finding more top ranking scholars with interdisciplinary nature.
      PubDate: Mon, 11 Jun 2018 00:00:00 +000
  • Research of Deceptive Review Detection Based on Target Product
           Identification and Metapath Feature Weight Calculation
    • Abstract: It is widespread that the consumers browse relevant reviews for reference before purchasing the products when online shopping. Some stores or users may write deceptive reviews to mislead consumers into making risky purchase decisions. Existing methods of deceptive review detection did not consider the valid product review sets and classification probability of feature weights. In this research, we propose a deceptive review detection algorithm based on the target product identification and the calculation of the Metapath feature weight, noted as TM-DRD. The review dataset of target product is modeled as a heterogeneous review information network with the feature nodes. The classification method of graph is used to detect the deceptive reviews, which can improve the efficiency and accuracy of deceptive review detection due to the sparsity, imbalance of deceptive reviews, and the absence of category probability of feature weight calculation. The TM-DRD algorithm we proposed is validated on the real review dataset Yelp and compared with the SpEagle, NFC, and NetSpam algorithm. The experiment results demonstrate that the TM-DRD algorithm performs better than the other method with regard to the accuracy and efficiency.
      PubDate: Mon, 11 Jun 2018 00:00:00 +000
  • On the Design Complexity of Cyberphysical Production Systems
    • Abstract: Establishing mass-customization practices, in a sustainable way, at a time of increased market uncertainty, is a pressing challenge for modern producing companies and one that traditional automation solutions cannot cope with. Industry 4.0 seeks to mitigate current practice’s limitations. It promotes a vision of a fully interconnected ecosystem of systems, machines, products, and many different stakeholders. In this environment, dynamically interconnected autonomous systems support humans in multifaceted decision-making. Industrial Internet of Things and cyberphysical systems (CPSs) are just two of the emerging concepts that embody the design and behavioral principles of these highly complex technical systems. The research within multiagent systems in manufacturing, by embodying most of the defining principles of industrial CPSs (ICPSs), is often regarded as a precursor for many of today’s emerging ICPS architectures. However, the domain has been fuzzy in specifying clear-cut design objectives and rules. Designs have been proposed with different positioning, creating confusion in concepts and supporting technologies. This paper contributes by providing clear definitions and interpretations of the main functional traits spread across the literature. A characterization of the defining functional requirements of ICPSs follows, in the form of a scale, rating systems according to the degree of implementation of the different functions.
      PubDate: Sun, 10 Jun 2018 06:53:35 +000
  • An Approach to Interval-Valued Hesitant Fuzzy Multiattribute Group
           Decision Making Based on the Generalized Shapley-Choquet Integral
    • Abstract: The purpose of this paper is to develop an approach to multiattribute group decision making under interval-valued hesitant fuzzy environment. To do this, this paper defines some new operations on interval-valued hesitant fuzzy elements, which eliminate the disadvantages of the existing operations. Considering the fact that elements in a set may be interdependent, two generalized interval-valued hesitant fuzzy operators based on the generalized Shapley function and the Choquet integral are defined. Then, some models for calculating the optimal fuzzy measures on the expert set and the ordered position set are established. Because fuzzy measures are defined on the power set, it makes the problem exponentially complex. To simplify the complexity of solving a fuzzy measure, models for the optimal 2-additive measures are constructed. Finally, an investment problem is offered to show the practicality and efficiency of the new method.
      PubDate: Sun, 10 Jun 2018 00:00:00 +000
  • Loosely Formation-Displaced Geostationary Orbit Optimization with Complex
           Hybrid Sail Propulsion
    • Abstract: To explore the performance of hybrid sail and overcome the congestion of geostationary orbit, this work proposes a method intended to optimize the trajectories of the spacecraft formation and extend the concept of displaced geostationary orbit by loosening the relative distance and introducing a station-keeping box. The multispacecraft formation is a typical complex system with nonlinear dynamics, and the hybrid propulsion system introduces additional complexity. To solve this problem, suboptimal trajectories with constant relative distance constraints are first found with inverse methods, which were referred to as ideal displaced geostationary orbits. Then, the suboptimal trajectories are used as a first guess for a direct optimization algorithm based on Gauss pseudospectral algorithm, which loosens the relative distance constraints and allows the spacecraft to be placed anywhere inside the station-keeping box. The optimization results show that the loosely formation and station-keeping box can create more flexible trajectories and achieve higher efficiency of the hybrid sail propulsion system, which can save about 40% propellant consumption.
      PubDate: Wed, 06 Jun 2018 00:00:00 +000
  • Model-Based ILC with a Modified -Filter for Complex Motion Systems:
           Practical Considerations and Experimental Verification on a Wafer Stage
    • Abstract: Iterative learning control (ILC) is one of the most popular tracking control methods for systems that repeatedly execute the same task. A system model is usually used in the analysis and design of ILC. Model-based ILC results in general in fast convergence and good performance. However, the model uncertainties and nonrepetitive disturbances hamper its practical applications. One of the commonly used solutions is the introduction of a low-pass filter, namely, the -filter. However, it is indicated in this paper that the existing -filter configurations compromise the servo performance, although improving the robustness. Motivated by the combination of performance and robustness, a novel -filter configuration in ILC is presented in this paper. Some practical considerations, such as the configuration of ILC in a feedback control system, the time delay compensation, and the learning coefficient, are provided in the implementation of the proposed ILC algorithm. The effectiveness and superiority of the proposed ILC versus existing -filter ILC are demonstrated by both theoretical analysis and experimental verification on a wafer stage.
      PubDate: Wed, 06 Jun 2018 00:00:00 +000
  • Analysis of Converter Combustion Flame Spectrum Big Data Sets Based on HHT
    • Abstract: The characteristics of the converter combustion flame are one of the key factors in the process control and end-point control of steelmaking. In a big data era, it is significant to carry out high-speed and effective processing on frame spectrum data. By installing data acquisition devices at the converter mouth and separating the spectrum according to the wave length, high-dimensional converter flame spectrum big data sets are achieved. The data of each converter is preprocessed after information fusion. By applying the SM software, the correspondence with the carbon content is obtained. Selecting the relative data of the two peak ratios and the single-peak absolute data as a one-dimensional signal, due to the obvious nonlinear and nonstationary characteristics, using HHT to do empirical mode decomposition and Hilbert spectrum analysis, the variation characteristics after 70% of the converter steelmaking process are obtained. From data acquisition, data preprocessing to data analysis and results, it provides a new perspective and method for the study of similar problems.
      PubDate: Tue, 05 Jun 2018 09:02:00 +000
  • Systematic Approach to Optimization for Protection Against Intentional
           Ultrashort Pulses Based on Multiconductor Modal Filters
    • Abstract: The problem of protecting radio electronic equipment from ultrashort pulses is of utmost importance nowadays since conductive interference poses the biggest danger to its proper functioning. The article considers the issue of protecting equipment by means of modal filters (MFs) and analyzes the structures of multiconductor microstrip MFs. We present the results of a complex study of the possibility to conduct the optimization (both separate and simultaneous) of a multiconductor MF by different criteria and the formulation of the basic (electrical) optimization criteria for MF. We have formulated the amplitude and time criteria for optimizing an MF (with any number of conductors) in an analytical form and obtained a general multicriteria objective function for optimizing an MF by different criteria. As a result, we have formed a hybrid model consisting of heuristic search and GA. The results demonstrated the topicality of further research in this field.
      PubDate: Tue, 05 Jun 2018 07:02:59 +000
  • Fuzzy Calculus Theory and Its Applications
    • PubDate: Tue, 05 Jun 2018 00:00:00 +000
  • Active Disturbance Rejection Synchronization of Morris-Lecar Neurons
    • Abstract: Synchronization of biological neurons is not only a hot topic, but also a difficult issue in the field of bioelectrical physiology. Numerous reported synchronization algorithms are designed on the basis of neural model, but they have deficiencies like relatively complex and poor robustness and are difficult to be realized. Morris-Lecar neuron is considered, and linear active disturbance rejection control (LADRC) is designed. Only one control input signal is utilized to synchronize membrane potentials of biological neurons. Meanwhile, in order to verify the robustness of synchronization, sinusoidal signal and parameter perturbations are introduced in numerical simulations. LADRC can still achieve satisfactory synchronization. Both theoretical and numerical simulation results show that LADRC is capable of estimating and cancelling disturbances and uncertainties. Neither accurate neural models nor concrete disturbance signal models are indispensable. A more practical and effective thought is provided to address the synchronization between neurons.
      PubDate: Tue, 05 Jun 2018 00:00:00 +000
  • Research Progress on Monitoring and Separating Suspension Particles for
           Lubricating Oil
    • Abstract: Lubricant failure or irrational lubrication is the root cause of industrial equipment failure. By monitoring the distribution of the suspended particles in lubricants, it is possible to discover hidden lubrication problems. After taking the lubricating oil samples of industrial equipment, the oil monitoring technology is used to analyze the particle size distribution and the type and content of the abrasive particles by electrical, magnetic, and optical monitoring techniques. It is necessary to separate the suspended particles in oils with impurities by some method to eliminate potential safety hazards and ensure the reuse efficiency of the lubricant. In this paper, the principles, advantages, and disadvantages of several important oil monitoring methods are described, and new developments in various methods are analyzed. Several typical methods for separation of the suspended particles in purified oils were introduced. The advantages and disadvantages of each process were summarized. The development direction of lubricant monitoring technology was pointed out, and guidance was provided for the separation and online monitoring of the suspended particles in lubricants. Finally, compared with similar review papers, this paper specifically figured out that ultrasonic separation method has the advantages of real time, high efficiency, and no pollution and has important application value for micron-scale particle separation of large precision machines.
      PubDate: Tue, 05 Jun 2018 00:00:00 +000
  • Multicriteria-Based Location Privacy Preservation in Vehicular Ad Hoc
    • Abstract: Vehicular ad hoc networks (VANETs) are the preferable choice for Intelligent Transportation Systems (ITS) because of its prevailing significance in both safety and nonsafety applications. Information dissemination in a multihop fashion along with privacy preservation of source node is a serious but challenging issue. We have used the idea of the phantom node as the next forwarder for data dissemination. The phantom node (vehicle) hides the identity of actual source node thus preserving the location privacy. The selection of the phantom node among the set of alternatives’ candidate vehicles is considered as a multicriteria-based problem. The phantom node selection problem is solved by using an analytical network process (ANP) by considering different traffic scenarios. The selection is based on different parameters which are distance, speed, trust, acceleration, and direction. The best alternative (target phantom vehicle) is selected through an ANP where all the alternatives are ranked from best to worst. The vehicle having maximum weight is considered to be the best choice as a phantom node. In order to check the stability of the alternatives’ ranking, sensitivity analysis is performed by taking into account different traffic scenarios and interest level of candidate vehicles.
      PubDate: Mon, 04 Jun 2018 00:00:00 +000
  • Intelligent Control Approaches for Modeling and Control of Complex Systems
    • PubDate: Thu, 31 May 2018 00:00:00 +000
  • Contactless Modal Phenomena Based Approach to Detecting, Identifying, and
           Diagnosing of Electrical Connections
    • Abstract: This paper presents a unified description of a new approach for contactless detection, identification, and diagnostics of electrical connections and describes an idea and principles of using modal probing for these tasks. Simulation and experimental results on pulsed signal propagation through flat cables demonstrate the modal decomposition of a pulsed signal, which varies depending on the state of the probed wire. It is shown that the presented tasks can be solved by modal probing. The article also considers the analysis of modal distortions in frequency domain and gives the formula for its practical use. This formula can be useful when the pulse duration time is longer than the minimum of mode delay difference. In conclusion, we present further development ideas of the modal probing.
      PubDate: Wed, 30 May 2018 08:52:35 +000
  • An Improved MOEA/D Based on Reference Distance for Software Project
           Portfolio Optimization
    • Abstract: As it is becoming extremely competitive in software industry, large software companies have to select their project portfolio to gain maximum return with limited resources under many constraints. Project portfolio optimization using multiobjective evolutionary algorithms is promising because they can provide solutions on the Pareto-optimal front that are difficult to be obtained by manual approaches. In this paper, we propose an improved MOEA/D (multiobjective evolutionary algorithm based on decomposition) based on reference distance (MOEA/D_RD) to solve the software project portfolio optimization problems with optimizing 2, 3, and 4 objectives. MOEA/D_RD replaces solutions based on reference distance during evolution process. Experimental comparison and analysis are performed among MOEA/D_RD and several state-of-the-art multiobjective evolutionary algorithms, that is, MOEA/D, nondominated sorting genetic algorithm II (NSGA2), and nondominated sorting genetic algorithm III (NSGA3). The results show that MOEA/D_RD and NSGA2 can solve the software project portfolio optimization problem more effectively. For 4-objective optimization problem, MOEA/D_RD is the most efficient algorithm compared with MOEA/D, NSGA2, and NSGA3 in terms of coverage, distribution, and stability of solutions.
      PubDate: Wed, 30 May 2018 07:15:13 +000
  • Urban Road Infrastructure Maintenance Planning with Application of Neural
    • Abstract: The maintenance planning within the urban road infrastructure management is a complex problem from both the management and technoeconomic aspects. The focus of this research is on decision-making processes related to the planning phase during management of urban road infrastructure projects. The goal of this research is to design and develop an ANN model in order to achieve a successful prediction of road deterioration as a tool for maintenance planning activities. Such a model is part of the proposed decision support concept for urban road infrastructure management and a decision support tool in planning activities. The input data were obtained from Circly 6.0 Pavement Design Software and used to determine the stress values (560 testing combinations). It was found that it is possible and desirable to apply such a model in the decision support concept in order to improve urban road infrastructure maintenance planning processes.
      PubDate: Tue, 29 May 2018 00:00:00 +000
  • Fractional-Order Memristor Emulator Circuits
    • Abstract: This brief leads the synthesis of fractional-order memristor (FOM) emulator circuits. To do so, a novel fractional-order integrator (FOI) topology based on current-feedback operational amplifier and integer-order capacitors is proposed. Then, the FOI is substituting the integer-order integrator inside flux- or charge-controlled memristor emulator circuits previously reported in the literature and in both versions: floating and grounded. This demonstrates that FOM emulator circuits can also be configured at incremental or decremental mode and the main fingerprints of an integer-order memristor are also holding up for FOMs. Theoretical results are validated through HSPICE simulations and the synthesized FOM emulator circuits can easily be reproducible. Moreover, the FOM emulator circuits can be used for improving future applications such as cellular neural networks, modulators, sensors, chaotic systems, relaxation oscillators, nonvolatile memory devices, and programmable analog circuits.
      PubDate: Mon, 28 May 2018 09:54:04 +000
  • GA Based Adaptive Singularity-Robust Path Planning of Space Robot for
           On-Orbit Detection
    • Abstract: As a new on-orbit detection platform, the space robot could ensure stable and reliable operation of spacecraft in complex space environments. The tracking accuracy of the space manipulator end-effector is crucial to the detection precision. In this paper, the Cartesian path planning method of velocity level inverse kinematics based on generalized Jacobian matrix (GJM) is proposed. The GJM will come across singularity issue in path planning, which leads to the infinite or incalculable joint velocity. To solve this issue, firstly, the singular value decomposition (SVD) is used for exposition of the singularity avoidance principle of the damped least squares (DLS) method. After that, the DLS method is improved by introducing an adaptive damping factor which changes with the singularity. Finally, in order to improve the tracking accuracy of the singularity-robust algorithm, the objective function is established, and two adaptive parameters are optimized by genetic algorithm (GA). The simulation of a 6-DOF free-floating space robot is carried out, and the results show that, compared with DLS method, the proposed method could improve the tracking accuracy of space manipulator end-effector.
      PubDate: Mon, 28 May 2018 08:05:22 +000
  • New Methods for Analyzing Complex Biomedical Systems and Signals
    • PubDate: Thu, 24 May 2018 09:07:57 +000
  • Approximately Nearest Neighborhood Image Search Using Unsupervised Hashing
           via Homogeneous Kernels
    • Abstract: We propose an approximation search algorithm that uses additive homogeneous kernel mapping to search for an image approximation based on kernelized locality-sensitive hashing. To address problems related to the unstable search accuracy of an unsupervised image hashing function and degradation of the search-time performance with increases in the number of hashing bits, we propose a method that combines additive explicit homogeneous kernel mapping and image feature histograms to construct a search algorithm based on a locality-sensitive hashing function. Moreover, to address the problem of semantic gaps caused by using image data that lack type information in semantic modeling, we describe an approximation searching algorithm based on the homogeneous kernel mapping of similarities between pairs of images and dissimilar constraint relationships. Our image search experiments confirmed that the proposed algorithm can construct a locality-sensitive hash function more accurately, thereby effectively improving the similarity search performance.
      PubDate: Wed, 23 May 2018 00:00:00 +000
  • Inversion of Thermal Conductivity in Two-Dimensional Unsteady-State Heat
           Transfer System Based on Boundary Element Method and Decentralized Fuzzy
    • Abstract: Based on the boundary element method and the decentralized fuzzy inference algorithm, the thermal conductivity in the two-dimensional unsteady-state heat transfer system changing with the temperature is deduced. The more accurate inversion results are obtained by introducing the variable universe method. The concrete method is as follows: using experimental means to obtain the instantaneous temperature in the material or on the boundary, to determine the thermal conductivity of the material by solving the inversion problem. The boundary element method is used to calculate the regional boundary and internal temperature in the direct problem. With the inversion problem, the decentralized fuzzy inference algorithm is used to compensate for the initial guess of the thermal conductivity by using the difference between the temperature measurement and the temperature calculation. In the inversion problem, the influence of the initial guess of different thermal conductivities, different numbers of measuring points, and the existence of measurement errors on the results is discussed. The example calculation and analysis prove that, with different initial guesses, existence of measurement errors, and the number of boundary measurements decrease, the methods adopted in this paper still maintain good validity and accuracy.
      PubDate: Tue, 22 May 2018 00:00:00 +000
  • Credit Card Fraud Detection through Parenclitic Network Analysis
    • Abstract: The detection of frauds in credit card transactions is a major topic in financial research, of profound economic implications. While this has hitherto been tackled through data analysis techniques, the resemblances between this and other problems, like the design of recommendation systems and of diagnostic/prognostic medical tools, suggest that a complex network approach may yield important benefits. In this paper we present a first hybrid data mining/complex network classification algorithm, able to detect illegal instances in a real card transaction data set. It is based on a recently proposed network reconstruction algorithm that allows creating representations of the deviation of one instance from a reference group. We show how the inclusion of features extracted from the network data representation improves the score obtained by a standard, neural network-based classification algorithm and additionally how this combined approach can outperform a commercial fraud detection system in specific operation niches. Beyond these specific results, this contribution represents a new example on how complex networks and data mining can be integrated as complementary tools, with the former providing a view to data beyond the capabilities of the latter.
      PubDate: Tue, 22 May 2018 00:00:00 +000
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