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Publisher: Hindawi   (Total: 338 journals)

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Showing 1 - 200 of 338 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: 35, SJR: 0.147, CiteScore: 0)
Advances in Aerospace Engineering     Open Access   (Followers: 53)
Advances in Agriculture     Open Access   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Astronomy     Open Access   (Followers: 38, 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: 39, 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: 27)
Advances in Electronics     Open Access   (Followers: 69)
Advances in Emergency Medicine     Open Access   (Followers: 12)
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: 15)
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: 3)
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: 30, SJR: 0.184, CiteScore: 0)
Advances in Preventive Medicine     Open Access   (Followers: 6)
Advances in Public Health     Open Access   (Followers: 23)
Advances in Regenerative Medicine     Open Access   (Followers: 2)
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: 17, 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: 26)
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: 13)
Case Reports in Pulmonology     Open Access   (Followers: 3)
Case Reports in Radiology     Open Access   (Followers: 9)
Case Reports in Rheumatology     Open Access   (Followers: 6)
Case Reports in Surgery     Open Access   (Followers: 11)
Case Reports in Transplantation     Open Access  
Case Reports in Urology     Open Access   (Followers: 9)
Case Reports in Vascular Medicine     Open Access  
Case Reports in Veterinary Medicine     Open Access   (Followers: 6)
Child Development Research     Open Access   (Followers: 18, 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: 14, 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)
Economics Research Intl.     Open Access   (Followers: 1)
Education Research Intl.     Open Access   (Followers: 19)
Emergency Medicine Intl.     Open Access   (Followers: 8, 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: 18, 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: 6, 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: 74, SJR: 0.232, CiteScore: 1)
Intl. J. of Agronomy     Open Access   (Followers: 6, 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 Combinatorics     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 Oceanography     Open Access   (Followers: 7)
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 Quality, Statistics, and Reliability     Open Access   (Followers: 15)
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: 7)
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: 5, 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: 189)
ISRN Astronomy and Astrophysics     Open Access   (Followers: 7)
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: 6)

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Complexity
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  [338 journals]
  • Event-Triggered Consensus Control for Leader-Following Multiagent Systems
           Using Output Feedback
    • Abstract: The event-triggered consensus control for leader-following multiagent systems subjected to external disturbances is investigated, by using the output feedback. In particular, a novel distributed event-triggered protocol is proposed by adopting dynamic observers to estimate the internal state information based on the measurable output signal. It is shown that under the developed observer-based event-triggered protocol, multiple agents will reach consensus with the desired disturbance attenuation ability and meanwhile exhibit no Zeno behaviors. Finally, a simulation is presented to verify the obtained results.
      PubDate: Wed, 15 Aug 2018 00:00:00 +000
       
  • Risk Transfer Mechanism for Agricultural Products Supply Chain Based on
           Weather Index Insurance
    • Abstract: The risk management for agricultural products supply chain is more complex than that for typical manufacturing supply chain. Agricultural production is vulnerable to severe weather such as heavy rain, cyclones, and cold wave, which challenges the matching of random output with random demand for agricultural products supply chains. The goal of this paper is to design an effective risk transfer mechanism for managing severe weather risks so as to ensure the stable operation of the agricultural products supply chain. We study the coordination of two-level agricultural products supply chain with a single company and a single farmer under the influence of severe weather. Taking rainstorm weather as an example, this paper designs a risk transfer mechanism based on weather index (rainfall) insurance: “rainfall index insurance + revenue sharing + risk transfer fee.” It is found that this risk transfer mechanism can overcome distortion of the farmer’s agricultural investment level under the influence of severe weather. When the contract parameters meet certain conditions, using the risk transfer mechanism can achieve the supply chain coordination and a win-win situation. More importantly, weather change does not affect the Pareto improvement of the company and the farmer under the risk transfer mechanism. In addition, we also find that the company can incentivize the farmer to purchase weather index insurance and use the insurance market to shift the severe weather risk encountered during the agricultural production to protect the company’s and farmer’s income and the stable operation of the supply chain.
      PubDate: Tue, 14 Aug 2018 04:26:50 +000
       
  • Modeling and Dynamic Analysis in a Hybrid Stochastic Bioeconomic System
           with Double Time Delays and Lévy Jumps
    • Abstract: A double delayed hybrid stochastic prey-predator bioeconomic system with Lévy jumps is established and analyzed, where commercial harvesting on prey and environmental stochasticity on population dynamics are considered. Two discrete time delays are utilized to represent the maturation delay of prey and gestation delay of predator, respectively. For a deterministic system, positivity of solutions and uniform persistence of system are discussed. Some sufficient conditions associated with double time delays are derived to discuss asymptotic stability of interior equilibrium. For a stochastic system, existence and uniqueness of a global positive solution are studied. By using the invariant measure theory and singular boundary theory of diffusion process, existence of stochastic Hopf bifurcation and stochastic stability are investigated. By constructing appropriate Lyapunov functions, asymptotic dynamic behavior of the proposed hybrid stochastic system with double time delays and Lévy jumps is discussed. Numerical simulations are provided to show consistency with theoretical analysis.
      PubDate: Mon, 13 Aug 2018 09:22:36 +000
       
  • Advances on the Resilience of Complex Networks
    • PubDate: Mon, 13 Aug 2018 00:00:00 +000
       
  • Electromechanical Design of Self-Similar Inspired Surface Electrodes for
           Human-Machine Interaction
    • Abstract: Stable acquisition of electromyography (EMG)/electrocardiograph (ECG) signal is critical and challenging in dynamic human-machine interaction. Here, self-similar inspired configuration is presented to design surface electrodes with high mechanical adaptability (stretchability and conformability with skin) and electrical sensitivity/stability which are usually a pair of paradoxes. Mechanical and electrical coupling optimization strategies are proposed to optimize the surface electrodes with the 2nd-order self-similar serpentine configuration. It is devoted the relationship between the geometric shape parameters (height-space ratio , scale factor , and line width ), the areal coverage , and mechanical adaptability, based on which an open network-shaped electrode is designed to stably collect high signal-to-noise ratio signals. The theoretical and experimental results show that the electrodes can be stretched > 30% and conform with skin wrinkle. The interfacial strength of electrode and skin is measured by homemade peeling test experiment platform. The surface electrodes with different line widths are used to record ECG signals for validating the electrical stability. Conformability reduces background noises and motion artifacts which provides stable recording of ECG/EMG signals. Further, the thin, stretchable electrodes are mounted on the human epidermis for continuous, stable biopotential signal records which suggests the way to high-performance electrodes in human-machine interaction.
      PubDate: Mon, 13 Aug 2018 00:00:00 +000
       
  • Patterns with Equal Values in Permutation Entropy: Do They Really Matter
           for Biosignal Classification'
    • Abstract: Two main weaknesses have been identified for permutation entropy (PE): the neglect of subsequence pattern differences in terms of amplitude and the possible ambiguities introduced by equal values in the subsequences. A number of variations or customizations to the original PE method to address these issues have been proposed in the scientific literature recently. Specifically for ties, methods have tried to remove the ambiguity by assigning different weighted or computed orders to equal values. Although these methods are able to circumvent such ambiguity, they can substantially increase the algorithm costs, and a general characterization of their practical effectiveness is still lacking. This paper analyses the performance of PE using several biomedical datasets (electroencephalogram, heartbeat interval, body temperature, and glucose records) in order to quantify the influence of ties on its signal class segmentation capability. This capability is assessed in terms of statistical significance of the PE differences between classes and classification sensitivity and specificity. Being obvious that ties modify the PE results, we hypothesize that equal values are intrinsic to the acquisition process, and therefore, they impact all the classes more or less equally. The experimental results confirm ties are often not the limiting factor for PE, even they can be beneficial as a sort of stochastic resonance, and it can be far more effective to focus on the embedding dimension instead.
      PubDate: Mon, 13 Aug 2018 00:00:00 +000
       
  • Complex Modeling of the Effects of Blasting on the Stability of
           Surrounding Rocks and Embankment in Water-Conveyance Tunnels
    • Abstract: Blasting in water-conveyance tunnels that cross rivers is vital for the safety and stability of embankments. In this work, a tunnel project that crosses the Yellow River in the north district of the first-phase Eastern Line of the South-to-North Water Diversion Project was selected as the research object. A complex modeling and numerical simulation on embankment stability with regard to the blasting power of the tunnel was conducted using the professional finite difference software FLAC3D to disclose the relationships between the blasting seismic waves with vibration velocity and embankment displacement under different excavation steps. Calculation results demonstrated that displacement generally attenuated from the tunnel wall to the internal structure of rocks under the effect of blasting seismic waves. The tunnel wall was in tension, and tensile stress gradually transformed into compressive stress with increased depth into the rocks. The curtain-grouting zone was mainly concentrated in the compressive zones. For different excavation steps, the vibration velocity at different feature points was high at the beginning of blasting and then gradually decreased. The resultant displacement was relatively small in the early excavation period and slowly increased as blasting progressed. The effects of different excavation steps on the safety of surrounding rocks and embankment under blasting seismic waves were simulated. We found that the blasting-induced vibration velocity was within the safe range of the code and that the calculated displacement was within the allowed range. Numerical simulation was feasible to assess the safety and stability of engineering projects.
      PubDate: Sun, 12 Aug 2018 06:49:42 +000
       
  • 3D Reconstruction of Pedestrian Trajectory with Moving Direction Learning
           and Optimal Gait Recognition
    • Abstract: An inertial measurement unit-based pedestrian navigation system that relies on the intelligent learning algorithm is useful for various applications, especially under some severe conditions, such as the tracking of firefighters and miners. Due to the complexity of the indoor environment, signal occlusion problems could lead to the failure of certain positioning methods. In complex environments, such as those involving fire rescue and emergency rescue, the barometric altimeter fails because of the influence of air pressure and temperature. This paper used an optimal gait recognition algorithm to improve the accuracy of gait detection. Then a learning-based moving direction determination method was proposed. With the Kalman filter and a zero-velocity update algorithm, different gaits could be accurately recognized, such as going upstairs, downstairs, and walking flat. According to the recognition results, the position change in the vertical direction could be reasonably corrected. The obtained 3D trajectory involving both horizontal and vertical movements has shown that the accuracy is significantly improved in practical complex environments.
      PubDate: Sun, 12 Aug 2018 06:41:28 +000
       
  • Resilience of Complex Systems: State of the Art and Directions for Future
           Research
    • Abstract: This paper reviews the state of the art on the resilience of complex systems by embracing different research areas and using bibliometric tools. The aim is to identify the main intellectual communities and leading scholars and to synthesize key knowledge of each research area. We also carry out a comparison across the research areas, aimed at analyzing how resilience is approached in any field, how the topic evolved starting from the ecological field of study, and the level of cross-fertilization among domains. Our analysis shows that resilience of complex systems is a multidisciplinary concept, which is particularly important in the fields of environmental science, ecology, and engineering. Areas of recent and increasing interest are also operation research, management science, business, and computer science. Except for environmental science and ecology, research is fragmented and carried out by isolated research groups. Integration is not only limited inside each field but also between research areas. In particular, we trace the citation links between different research areas and find a very limited number, revealing a scarce cross-fertilization among domains. We conclude by providing some directions for future research.
      PubDate: Sun, 12 Aug 2018 06:37:45 +000
       
  • Analytical Reduction of Nonlinear Metabolic Networks Accounting for
           Dynamics in Enzymatic Reactions
    • Abstract: Metabolic modeling has been particularly efficient to understand the conditions affecting the metabolism of an organism. But so far, metabolic models have mainly considered static situations, assuming balanced growth. Some organisms are always far from equilibrium, and metabolic modeling must account for their dynamics. This leads to high-dimensional models in which metabolic fluxes are no more constant but vary depending on the intracellular concentrations. Such metabolic models must be reduced and simplified so that they can be calibrated and analyzed. Reducing these models of large dimension down to a model of smaller dimension is very challenging, specially, when dealing with nonlinear metabolic rates. Here, we propose a rigorous approach to reduce metabolic models using quasi-steady-state reduction based on Tikhonov’s theorem, with a characterized and bounded reduction error. We assume that the metabolic network can be represented with Michaelis-Menten enzymatic reactions that evolve at different time scales. In this simplest approach, some metabolites can accumulate. We consider the case with a continuous varying input in the model, such as light for microalgae, so that the system is never at a steady state. Furthermore, our analysis proves that metabolites in the slow part of the metabolic system reach higher concentrations (by one order of magnitude) than metabolites in the fast part under some flux conditions. A simple example illustrates our approach and the resulting accuracy of the reduction method.
      PubDate: Sun, 12 Aug 2018 06:34:54 +000
       
  • Fractal Method for Modeling the Peculiar Dynamics of Transient Carbon
           Plasma Generated by Excimer Laser Ablation in Vacuum
    • Abstract: Carbon plasmas generated by excimer laser ablation are often applied for deposition (in vacuum or under controlled atmosphere) of high-technological interest nanostructures and thin films. For specific excimer irradiation conditions, these transient plasmas can exhibit peculiar behaviors when probed by fast time- and space-resolved optical and electrical methods. We propose here a fractal approach to simulate this peculiar dynamics. In our model, the complexity of the interactions between the transient plasma particles (in the Euclidean space) is substituted by the nondifferentiability (fractality) of the motion curves of the same particles, but in a fractal space. For plane symmetry and particular boundary conditions, stationary geodesic equations at a fractal scale resolution give a fractal velocity field with components expressed by means of nonlinear solutions (soliton type, kink type, etc.). The theoretical model successfully reproduces the (surprising) formation of V-like radiating plasma structures (consisting of two lateral arms of high optical emissivity and a fast-expanding central part of low emissivity) experimentally observed.
      PubDate: Sun, 12 Aug 2018 00:00:00 +000
       
  • Corrigendum to “Receding Horizon Control of Type 1 Diabetes Mellitus by
           Using Nonlinear Programming”
    • PubDate: Thu, 09 Aug 2018 00:00:00 +000
       
  • H∞ Optimal Performance Design of an Unstable Plant under Bode
           Integral Constraint
    • Abstract: This paper proposed the H∞ state feedback and H∞ output feedback design methods for unstable plants, which improved the original H∞ state feedback and H∞ output feedback. For the H∞ state feedback design of unstable plants, it presents the complete robustness constraint which is based on solving Riccati equation and Bode integral. For the H∞ output feedback design of unstable plants, the medium-frequency band should be considered in particular. Besides, this paper presents the method to select weight function or coefficients in the H∞ design, which employs Bode integral to optimize the H∞ design. It takes a magnetic levitation system as an example. The simulation results demonstrate that the optimal performance of perturbation suppression is obtained with the design of robustness constraint. The presented method is of benefit to the general H∞ design.
      PubDate: Thu, 09 Aug 2018 00:00:00 +000
       
  • Using Graph Theory to Assess the Interaction between Cerebral Function,
           Brain Hemodynamics, and Systemic Variables in Premature Infants
    • Abstract: Graphs can be used to describe a great variety of real-world situations and have therefore been used extensively in different fields. In the present analysis, we use graphs to study the interaction between cerebral function, brain hemodynamics, and systemic variables in premature neonates. We used data from a propofol dose-finding and pharmacodynamics study as a model in order to evaluate the performance of the graph measures to monitor signal interactions. Concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, regional cerebral oxygen saturation—measured by means of near-infrared spectroscopy—and electroencephalography were performed in 22 neonates undergoing INSURE (intubation, surfactant administration, and extubation). The graphs used to study the interaction between these signal modalities were constructed using the RBF kernel. Results indicate that propofol induces a decrease in the signal interaction up to 90 minutes after propofol administration, which is consistent with clinical observations published previously. The clinical recovery phase is mainly determined by the EEG dynamics, which were observed to recover much slower compared to the other modalities. In addition, we found a more pronounced loss in cerebral-systemic interactions with increasing propofol dose.
      PubDate: Thu, 09 Aug 2018 00:00:00 +000
       
  • A Methodology for Evaluating Algorithms That Calculate Social Influence in
           Complex Social Networks
    • Abstract: Online social networks are complex systems often involving millions or even billions of users. Understanding the dynamics of a social network requires analysing characteristics of the network (in its entirety) and the users (as individuals). This paper focuses on calculating user’s social influence, which depends on (i) the user’s positioning in the social network and (ii) interactions between the user and all other users in the social network. Given that data on all users in the social network is required to calculate social influence, something not applicable for today’s social networks, alternative approaches relying on a limited set of data on users are necessary. However, these approaches introduce uncertainty in calculating (i.e., predicting) the value of social influence. Hence, a methodology is proposed for evaluating algorithms that calculate social influence in complex social networks; this is done by identifying the most accurate and precise algorithm. The proposed methodology extends the traditional ground truth approach, often used in descriptive statistics and machine learning. Use of the proposed methodology is demonstrated using a case study incorporating four algorithms for calculating a user’s social influence.
      PubDate: Wed, 08 Aug 2018 00:00:00 +000
       
  • Synchronization Measure Based on a Geometric Approach to Attractor
           Embedding Using Finite Observation Windows
    • Abstract: A simple and effective algorithm for the identification of optimal time delays based on the geometrical properties of the embedded attractor is presented in this paper. A time series synchronization measure based on optimal time delays is derived. The approach is based on the comparison of optimal time delay sequences that are computed for segments of the considered time series. The proposed technique is validated using coupled chaotic Rössler systems.
      PubDate: Wed, 08 Aug 2018 00:00:00 +000
       
  • Research on Supply Chain Stability Driven by Consumer’s Channel
           Preference Based on Complexity Theory
    • Abstract: At present, most of the manufacturers are increasingly laying emphasis on dual-channel selling. The level of consumer’s preference is diverse with different channels. This study discusses a supply chain where one common manufacturer uses two different channels to sell product. The bounded rationality expectation has been applied to explore the decision-making mechanism in finalizing the wholesale prices and sales commissions for the manufacturer and retailers. In addition, the dynamic features of the system are simulated by 2D bifurcation diagram, the largest Lyapunov exponent, attractor variation, and time series. The simulation results suggest that if the adjustment speeds of the wholesale prices and sales commissions change drastically, the system would fall into a chaotic state. If the consumers prefer the online channel, the wholesale prices and sales commissions may be raised and vice versa. However, too strong preference of each channel will make the system appear to have a considerably periodic fluctuation, even chaos. In the meantime, the parameter adjustment method can help make the periodic or chaotic system go back to stability. Therefore, the significance of this study is with a practical meaning to make better pricing strategy for players in dual-channel selling supply chain system.
      PubDate: Tue, 07 Aug 2018 00:00:00 +000
       
  • Solutions to No-Wait Flow Shop Scheduling Problem Using the Flower
           Pollination Algorithm Based on the Hormone Modulation Mechanism
    • Abstract: A flower pollination algorithm is proposed based on the hormone modulation mechanism (HMM-FPA) to solve the no-wait flow shop scheduling problem (NWFSP). This algorithm minimizes the maximum accomplished time. Random keys are encoded based on an ascending sequence of components to make the flower pollination algorithm (FPA) suitable for the no-wait flow shop scheduling problem. The hormone modulation factor is introduced to strengthen information sharing among the flowers and improve FPA cross-pollination to enhance the algorithm global search performance. A variable neighborhood search strategy based on dynamic self-adaptive variable work piece blocks is constructed to improve the local search quality. Three common benchmark instances are applied to test the proposed algorithm. The result verifies that this algorithm is effective.
      PubDate: Mon, 06 Aug 2018 06:27:07 +000
       
  • An Extreme Learning Machine-Based Community Detection Algorithm in Complex
           Networks
    • Abstract: Community structure, one of the most popular properties in complex networks, has long been a cornerstone in the advance of various scientific branches. Over the past few years, a number of tools have been used in the development of community detection algorithms. In this paper, by means of fusing unsupervised extreme learning machines and the -means clustering techniques, we propose a novel community detection method that surpasses traditional -means approaches in terms of precision and stability while adding very few extra computational costs. Furthermore, results of extensive experiments undertaken on computer-generated networks and real-world datasets illustrate acceptable performances of the introduced algorithm in comparison with other typical community detection algorithms.
      PubDate: Mon, 06 Aug 2018 05:11:22 +000
       
  • The Effect of Entropy on the Performance of Modified Genetic Algorithm
           Using Earthquake and Wind Time Series
    • Abstract: The dynamic complexity of time series of natural phenomena allowed to improve the performance of the genetic algorithm to optimize the test mathematical functions. The initial populations of stochastic origin of the genetic algorithm were replaced using the series of time of winds and earthquakes. The determinism of the time series brings in more information in the search of the global optimum of the functions, achieving reductions of time and an improvement of the results. The information of the initial populations was measured using the entropy of Shannon and allowed to establish the importance of the entropy in the initial populations and its relation with getting better results. This research establishes a new methodology for using determinism time series to search the best performance of the models of optimization of genetic algorithms (GA).
      PubDate: Mon, 06 Aug 2018 00:00:00 +000
       
  • Tibetan Weibo User Group Division Based on Semantic Information in the Era
           of Big Data
    • Abstract: In the era of big data, group division in online social network analysis is a basic task. It can be divided into the group division based on static relationship and the group division based on dynamic relationship. Compared with the static group division, users express their semantic information in all kinds of social network behaviors, and they tend to interact with other users who have the same idea and attitude; this is how different groups are formed. In this paper, aimed at the issue that some Tibetan users use Chinese to publish microblogs on social platforms, a group division method based on semantic information of Tibetan users under the big data environment is proposed. When dividing a large number of Tibetan user groups in a social network, a large amount of semantic information of Tibetan users in the social network is first analyzed. Then, based on the semantic similarity between users, we aggregate the Tibetan users with high similarities into one group, thus achieving the final group division. The experimental results illustrate the effectiveness of the method of analyzing Tibetan user semantic information in the context of big data for group partitioning.
      PubDate: Sun, 05 Aug 2018 06:18:32 +000
       
  • Chaos and Symbol Complexity in a Conformable Fractional-Order Memcapacitor
           System
    • Abstract: Application of conformable fractional calculus in nonlinear dynamics is a new topic, and it has received increasing interests in recent years. In this paper, numerical solution of a conformable fractional nonlinear system is obtained based on the conformable differential transform method. Dynamics of a conformable fractional memcapacitor (CFM) system is analyzed by means of bifurcation diagram and Lyapunov characteristic exponents (LCEs). Rich dynamics is found, and coexisting attractors and transient state are observed. Symbol complexity of the CFM system is estimated by employing the symbolic entropy (SybEn) algorithm, symbolic spectral entropy (SybSEn) algorithm, and symbolic C0 (SybC0) algorithm. It shows that pseudorandom sequences generated by the system have high complexity and pass the rigorous NIST test. Results demonstrate that the conformable memcapacitor nonlinear system can also be a good model for real applications.
      PubDate: Sun, 05 Aug 2018 06:03:12 +000
       
  • On Disturbance Rejection for a Class of Nonlinear Systems
    • Abstract: System control techniques have been developing for a long time. For advanced system requirements, sophisticated control algorithms are necessary for the nonlinear systems with uncertainties and disturbances. Disturbance attenuation or rejection control has been attracting an increasing attention from both control theory researchers and control engineering practitioners. In this paper, a new disturbance rejection control is proposed. Controllable canonical form is taken as the standard form of system dynamics, and a disturbance observer is taken to estimate the discrepancy between system dynamics and its standard form. Then the discrepancy could be compensated by control laws. Conditions of the closed-loop stability and ultimate bound of the tracking error have been obtained. Numerical results have also been presented to support the proposed approach.
      PubDate: Sun, 05 Aug 2018 00:00:00 +000
       
  • Investigation and Optimization of Grounding Grid Based on Lightning
           Response by Using ATP-EMTP and Genetic Algorithm
    • Abstract: A large number of electromagnetic transient studies have been analyzed for finding the overvoltage behavior of power system. A grounding grid of power system is so important for reducing the effect of overvoltage phenomena during a short-circuit event. Two sections are important in grounding system behavior: soil ionization and inductive behavior; this paper focuses on the inductive manner of grounding grid. The grounding grid is considered as a conductor segment; each conductor segment acts as a grounding unit. In this paper, the transient methodology is introduced to investigate the lightning effect on grounding body at each point of grounding grid in normal and optimized conditions. Genetic algorithm is applied for regular and irregular grounding grid to obtain best values of mesh size with the lower ground potential rise (GPR) as compared with the normal condition for more safety. The grounding grid is a combination of inductance, resistance, and capacitance. This model is suitable for practical applications related to fault diagnosis. Several voltages on different positions of grounding grid are described in this paper using ATP-EMTP and genetic algorithm. The computer simulation shows that the proposed scheme is highly feasible and technically attractive.
      PubDate: Sun, 05 Aug 2018 00:00:00 +000
       
  • The Complexity and Simulation of Revenue Sharing Negotiation Based on
           Construction Stakeholders
    • Abstract: This paper focuses on the complexity characteristics of a stakeholder’s revenue sharing for time compression in construction projects, such as adopting a life cycle perspective, the preferences of stakeholders, and the adaptability behaviors in the negotiation process. We build an agent-based model on revenue sharing negotiation. Considering that the agents who are in a weak position not only care about their own benefits but also compare their benefits to others, we design an experimental scenario where a contractor has fairness preference based on China’s reality. According to different sympathy and envy coefficients, we can divide the inequity aversion preference into three typical types, and we research how a contractor’s different types of inequity aversion preferences impact revenue sharing coefficient of agreements, results of successful negotiations, and efficiency in negotiations. Results are as follows: it is advantageous for a contractor to maintain a modest inequity aversion for their own earnings and the degree of sympathy preference in inequity aversion has an important impact on the time to reach consensus while the degree of jealousy preference has no obvious effect. If contractors’ sympathy preference is maintained within a moderate range, it will achieve a higher success rate of negotiations in the negotiation process; the success rate of negotiation is affected largely by the agents’ sympathy preference, though it is also influenced by the jealousy preference, but it is not very sensitive.
      PubDate: Thu, 02 Aug 2018 06:43:29 +000
       
  • Self-Adaptive -Means Based on a Covering Algorithm
    • Abstract: The -means algorithm is one of the ten classic algorithms in the area of data mining and has been studied by researchers in numerous fields for a long time. However, the value of the clustering number in the -means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved -means clustering algorithm called the covering -means algorithm (C--means). The C--means algorithm can not only acquire efficient and accurate clustering results but also self-adaptively provide a reasonable numbers of clusters based on the data features. It includes two phases: the initialization of the covering algorithm (CA) and the Lloyd iteration of the -means. The first phase executes the CA. CA self-organizes and recognizes the number of clusters based on the similarities in the data, and it requires neither the number of clusters to be prespecified nor the initial centers to be manually selected. Therefore, it has a “blind” feature, that is, is not preselected. The second phase performs the Lloyd iteration based on the results of the first phase. The C--means algorithm combines the advantages of CA and -means. Experiments are carried out on the Spark platform, and the results verify the good scalability of the C--means algorithm. This algorithm can effectively solve the problem of large-scale data clustering. Extensive experiments on real data sets show that the accuracy and efficiency of the C--means algorithm outperforms the existing algorithms under both sequential and parallel conditions.
      PubDate: Wed, 01 Aug 2018 10:46:50 +000
       
  • Ensemble Prediction Algorithm of Anomaly Monitoring Based on Big Data
           Analysis Platform of Open-Pit Mine Slope
    • Abstract: With the diversification of pit mine slope monitoring and the development of new technologies such as multisource data flow monitoring, normal alert log processing system cannot fulfil the log analysis expectation at the scale of big data. In order to make up this disadvantage, this research will provide an ensemble prediction algorithm of anomalous system data based on time series and an evaluation system for the algorithm. This algorithm integrates multiple classifier prediction algorithms and proceeds classified forecast for data collected, which can optimize the accuracy in predicting the anomaly data in the system. The algorithm and evaluation system is tested by using the microseismic monitoring data of an open-pit mine slope over 6 months. Testing results illustrate prediction algorithm provided by this research can successfully integrate the advantage of multiple algorithms to increase the accuracy of prediction. In addition, the evaluation system greatly supports the algorithm, which enhances the stability of log analysis platform.
      PubDate: Wed, 01 Aug 2018 10:06:10 +000
       
  • Artificial Neural Network Classification of Motor-Related EEG: An Increase
           in Classification Accuracy by Reducing Signal Complexity
    • Abstract: We apply artificial neural network (ANN) for recognition and classification of electroencephalographic (EEG) patterns associated with motor imagery in untrained subjects. Classification accuracy is optimized by reducing complexity of input experimental data. From multichannel EEG recorded by the set of 31 electrodes arranged according to extended international 10-10 system, we select an appropriate type of ANN which reaches 80 ± 10% accuracy for single trial classification. Then, we reduce the number of the EEG channels and obtain an appropriate recognition quality (up to 73 ± 15%) using only 8 electrodes located in frontal lobe. Finally, we analyze the time-frequency structure of EEG signals and find that motor-related features associated with left and right leg motor imagery are more pronounced in the mu (8–13 Hz) and delta (1–5 Hz) brainwaves than in the high-frequency beta brainwave (15–30 Hz). Based on the obtained results, we propose further ANN optimization by preprocessing the EEG signals with a low-pass filter with different cutoffs. We demonstrate that the filtration of high-frequency spectral components significantly enhances the classification performance (up to 90 ± 5% accuracy using 8 electrodes only). The obtained results are of particular interest for the development of brain-computer interfaces for untrained subjects.
      PubDate: Wed, 01 Aug 2018 09:54:09 +000
       
  • Modeling Cell-to-Cell Spread of HIV-1 with Nonlocal Infections
    • Abstract: This paper is devoted to develop a nonlocal and time-delayed reaction-diffusion model for HIV infection within host cell-to-cell viral transmissions. In a bounded spatial domain, we study threshold dynamics in terms of basic reproduction number for the heterogeneous model. Our results show that if , the infection-free steady state is globally attractive, implying infection becomes extinct, while if , virus will persist in the host environment.
      PubDate: Wed, 01 Aug 2018 00:00:00 +000
       
  • Forecasting Crude Oil Consumption in China Using a Grey Prediction Model
           with an Optimal Fractional-Order Accumulating Operator
    • Abstract: Crude oil, which is an important part of energy consumption, can drive or hinder economic development based on its production and consumption. Reasonable predictions of crude oil consumption in China are meaningful. In this paper, we study the grey-extended SIGM model, which is directly estimated with differential equations. This model has high simulation and prediction accuracies and is one of the important models in grey theory. However, to achieve the desired modeling effect, the raw data must conform to a class ratio check. Unfortunately, the characteristics of the Chinese crude oil consumption data are not suitable for SIGM modeling. Therefore, in this paper, we use a least squares estimation to study the parametric operation properties of the SIGM model, and the gamma function is used to extend the integer order accumulation sequence to the fractional-order accumulation generation sequence. The first-order SIGM model is extended to the fractional-order FSIGM model. According to the particle swarm optimization (PSO) mechanism and the properties of the gamma function of the fractional-order cumulative generation operator, the optimal fractional-order particle swarm optimization algorithm of the FSIGM model is obtained. Finally, the data concerning China’s crude oil consumption from 2002 to 2014 are used as experimental data. The results are better than those of the classical grey GM, DGM, and NDGM models as well as those of the grey-extended SIGM model. At the same time, according to the FSIGM model, this paper predicts China’s crude oil consumption for 2015–2020.
      PubDate: Wed, 01 Aug 2018 00:00:00 +000
       
 
 
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