36 results
Search Results
2. Numerical research on the lateral global buckling characteristics of a high temperature and pressure pipeline with two initial imperfections.
- Author
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Liu, Wenbin and Liu, Aimin
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MECHANICAL buckling , *WATER pipelines , *IMPERFECTION , *COMPUTER simulation , *WAVELENGTHS - Abstract
With the exploitation of offshore oil and gas gradually moving to deep water, higher temperature differences and pressure differences are applied to the pipeline system, making the global buckling of the pipeline more serious. For unburied deep-water pipelines, the lateral buckling is the major buckling form. The initial imperfections widely exist in the pipeline system due to manufacture defects or the influence of uneven seabed, and the distribution and geometry features of initial imperfections are random. They can be divided into two kinds based on shape: single-arch imperfections and double-arch imperfections. This paper analyzed the global buckling process of a pipeline with 2 initial imperfections by using a numerical simulation method and revealed how the ratio of the initial imperfection’s space length to the imperfection’s wavelength and the combination of imperfections affects the buckling process. The results show that a pipeline with 2 initial imperfections may suffer the superposition of global buckling. The growth ratios of buckling displacement, axial force and bending moment in the superposition zone are several times larger than no buckling superposition pipeline. The ratio of the initial imperfection’s space length to the imperfection’s wavelength decides whether a pipeline suffers buckling superposition. The potential failure point of pipeline exhibiting buckling superposition is as same as the no buckling superposition pipeline, but the failure risk of pipeline exhibiting buckling superposition is much higher. The shape and direction of two nearby imperfections also affects the failure risk of pipeline exhibiting global buckling superposition. The failure risk of pipeline with two double-arch imperfections is higher than pipeline with two single-arch imperfections. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
3. Correction of failure in linear antenna arrays with greedy sparseness constrained optimization technique.
- Author
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Khan, Shafqat Ullah, Rahim, M. K. A., Aminu-Baba, Murtala, and Murad, N. A.
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LINEAR antenna arrays , *CORRECTION factors , *CONSTRAINED optimization , *ORTHOGONAL matching pursuit , *COMPUTER simulation - Abstract
This paper proposes the correction of faulty sensors using a synthesis of the greedy sparse constrained optimization GSCO) technique. The failure of sensors can damage the radiation power pattern in terms of sidelobes and nulls. The synthesis problem can recover the wanted power pattern with reduced number of sensors into the background of greedy algorithm and solved with orthogonal matching pursuit (OMP) technique. Numerical simulation examples of linear arrays are offered to demonstrate the effectiveness of getting the wanted power pattern with a reduced number of antenna sensors which is compared with the available techniques in terms of sidelobes level and number of nulls. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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4. A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.
- Author
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Hong, Zhiling, Lin, Fan, and Xiao, Bin
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FEATURE extraction , *IPHONE (Smartphone) , *COMPUTER algorithms , *ELECTRONIC information resources , *MICROELECTROMECHANICAL systems , *COMPUTER simulation - Abstract
Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
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5. A multi-domain trust management model for supporting RFID applications of IoT.
- Author
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Wu, Xu and Li, Feng
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RADIO frequency identification systems , *INTERNET of things , *COMPUTER simulation , *MATHEMATICAL models , *HIERARCHICAL clustering (Cluster analysis) - Abstract
The use of RFID technology in complex and distributed environments often leads to a multi-domain RFID system, in which trust establishment among entities from heterogeneous domains without past interaction or prior agreed policy, is a challenge. The current trust management mechanisms in the literature do not meet the specific requirements in multi-domain RFID systems. Therefore, this paper analyzes the special challenges on trust management in multi-domain RFID systems, and identifies the implications and the requirements of the challenges on the solutions to the trust management of multi-domain RFID systems. A multi-domain trust management model is proposed, which provides a hierarchical trust management framework include a diversity of trust evaluation and establishment approaches. The simulation results and analysis show that the proposed method has excellent ability to deal with the trust relationships, better security, and higher accuracy rate. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
6. Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.
- Author
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Kong, Zehui, Zou, Yuan, and Liu, Teng
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HYBRID electric vehicles , *COMPUTER simulation , *AUTOMOTIVE fuel consumption standards , *ENERGY management , *REINFORCEMENT learning , *ENERGY consumption - Abstract
To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM) of power-request is derived. The reinforcement learning (RL) is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions. A facing-forward powertrain model is built in detail, including the engine-generator model, battery model and vehicle dynamical model. The robustness and adaptability of real-time energy management strategy are validated through the comparison with the stationary control strategy based on initial transition probability matrix (TPM) generated from a long naturalistic driving cycle in the simulation. Results indicate that proposed method has better fuel economy than stationary one and is more effective in real-time control. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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7. Comparison of two SVD-based color image compression schemes.
- Author
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Li, Ying, Wei, Musheng, Zhang, Fengxia, and Zhao, Jianli
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COLOR image processing , *IMAGE compression , *COMPARATIVE studies , *QUATERNIONS , *IMAGE quality analysis , *COMPUTER simulation - Abstract
Color image compression is a commonly used process to represent image data as few bits as possible, which removes redundancy in the data while maintaining an appropriate level of quality for the user. Color image compression algorithms based on quaternion are very common in recent years. In this paper, we propose a color image compression scheme, based on the real SVD, named real compression scheme. First, we form a new real rectangular matrix C according to the red, green and blue components of the original color image and perform the real SVD for C. Then we select several largest singular values and the corresponding vectors in the left and right unitary matrices to compress the color image. We compare the real compression scheme with quaternion compression scheme by performing quaternion SVD using the real structure-preserving algorithm. We compare the two schemes in terms of operation amount, assignment number, operation speed, PSNR and CR. The experimental results show that with the same numbers of selected singular values, the real compression scheme offers higher CR, much less operation time, but a little bit smaller PSNR than the quaternion compression scheme. When these two schemes have the same CR, the real compression scheme shows more prominent advantages both on the operation time and PSNR. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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8. Evolutionary Algorithm for RNA Secondary Structure Prediction Based on Simulated SHAPE Data.
- Author
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Montaseri, Soheila, Ganjtabesh, Mohammad, and Zare-Mirakabad, Fatemeh
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MOLECULAR structure of RNA , *BIOLOGICAL evolution , *GENETICS , *NON-coding RNA , *GENETIC algorithms , *THERMODYNAMICS , *COMPUTER simulation - Abstract
Background: Non-coding RNAs perform a wide range of functions inside the living cells that are related to their structures. Several algorithms have been proposed to predict RNA secondary structure based on minimum free energy. Low prediction accuracy of these algorithms indicates that free energy alone is not sufficient to predict the functional secondary structure. Recently, the obtained information from the SHAPE experiment greatly improves the accuracy of RNA secondary structure prediction by adding this information to the thermodynamic free energy as pseudo-free energy. Method: In this paper, a new method is proposed to predict RNA secondary structure based on both free energy and SHAPE pseudo-free energy. For each RNA sequence, a population of secondary structures is constructed and their SHAPE data are simulated. Then, an evolutionary algorithm is used to improve each structure based on both free and pseudo-free energies. Finally, a structure with minimum summation of free and pseudo-free energies is considered as the predicted RNA secondary structure. Results and Conclusions: Computationally simulating the SHAPE data for a given RNA sequence requires its secondary structure. Here, we overcome this limitation by employing a population of secondary structures. This helps us to simulate the SHAPE data for any RNA sequence and consequently improves the accuracy of RNA secondary structure prediction as it is confirmed by our experiments. The source code and web server of our proposed method are freely available at . [ABSTRACT FROM AUTHOR]
- Published
- 2016
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9. Enhancing the Flexibility of TCP in Heterogeneous Network.
- Author
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Hui, Wang, Peiyu, Li, Zhihui, Fan, Zheqing, Li, and Xuhui, Wei
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TCP/IP , *CHAOS theory , *INITIAL value problems , *CONVERGENCE (Telecommunication) , *COMPUTER simulation - Abstract
Due to a set of constant initial values, the performance of conventional TCP drops significantly encountering heterogeneous network, showing low throughput and unfairness. This paper firstly demonstrates the chaotic character of TCP congestion control in heterogeneous network, especially the sensitivity to initial value. Inspired by merit of nature-inspired algorithm, a novel structure of TCP congestion control (IPPM, Internet Prey-Predator Model) is proposed. Parameters such as available link capacity(C), congestion window (W) and queue length (Q) are collected by IPPM, which calculates the max value of C according to the interacting relationship existing in C, W and Q, and IPPM initiates the TCP ssthresh with the calculated value. Plenty of simulation results show that the modified TCP can effectively avoid network congestion and packet loss. Besides, it holds high resource utilization, convergence speeds, fairness and stability. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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10. Spectral X-Ray CT Image Reconstruction with a Combination of Energy-Integrating and Photon-Counting Detectors.
- Author
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Yang, Qingsong, Cong, Wenxiang, Xi, Yan, and Wang, Ge
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COMPUTED tomography , *IMAGE reconstruction , *PHOTON counting , *COMPUTER simulation , *ALGORITHMS , *FEATURE extraction - Abstract
The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT) which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV). The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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11. Structural Controllability of Complex Networks Based on Preferential Matching.
- Author
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Zhang, Xizhe, Lv, Tianyang, Yang, XueYing, and Zhang, Bin
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CONTROLLABILITY in systems engineering , *STRUCTURAL engineering , *COMPUTER simulation , *APPLICATION software , *COMPUTER networks - Abstract
Minimum driver node sets (MDSs) play an important role in studying the structural controllability of complex networks. Recent research has shown that MDSs tend to avoid high-degree nodes. However, this observation is based on the analysis of a small number of MDSs, because enumerating all of the MDSs of a network is a #P problem. Therefore, past research has not been sufficient to arrive at a convincing conclusion. In this paper, first, we propose a preferential matching algorithm to find MDSs that have a specific degree property. Then, we show that the MDSs obtained by preferential matching can be composed of high- and medium-degree nodes. Moreover, the experimental results also show that the average degree of the MDSs of some networks tends to be greater than that of the overall network, even when the MDSs are obtained using previous research method. Further analysis shows that whether the driver nodes tend to be high-degree nodes or not is closely related to the edge direction of the network. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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12. Gravity Effects on Information Filtering and Network Evolving.
- Author
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Liu, Jin-Hu, Zhang, Zi-Ke, Chen, Lingjiao, Liu, Chuang, Yang, Chengcheng, and Wang, Xueqi
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INFORMATION filtering systems , *COMPUTER algorithms , *ELECTRONIC data processing , *PERFORMANCE evaluation , *COMPUTER simulation , *INFORMATION science - Abstract
In this paper, based on the gravity principle of classical physics, we propose a tunable gravity-based model, which considers tag usage pattern to weigh both the mass and distance of network nodes. We then apply this model in solving the problems of information filtering and network evolving. Experimental results on two real-world data sets, Del.icio.us and MovieLens, show that it can not only enhance the algorithmic performance, but can also better characterize the properties of real networks. This work may shed some light on the in-depth understanding of the effect of gravity model. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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13. Fuzzy jump wavelet neural network based on rule induction for dynamic nonlinear system identification with real data applications
- Author
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Miguel Angel Mañanas, Mohsen Kharazihai Isfahani, Hamid Reza Marateb, Maryam Zekri, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, and Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy
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Computer science ,02 engineering and technology ,Systems Science ,Wavelet ,Informàtica [Àrees temàtiques de la UPC] ,Animal Cells ,0202 electrical engineering, electronic engineering, information engineering ,Neurons ,Multidisciplinary ,Fuzzy rule ,Artificial neural network ,Nonlinear system identification ,Approximation Methods ,Physics ,Linear model ,Classical Mechanics ,Bioassays and Physiological Analysis ,Physical Sciences ,Piecewise ,Medicine ,020201 artificial intelligence & image processing ,Cellular Types ,Cellular Structures and Organelles ,Algorithm ,Muscle Electrophysiology ,Algorithms ,Research Article ,Computer and Information Sciences ,Neural Networks ,Science ,Research and Analysis Methods ,Fuzzy logic ,Neural networks (Computer science) ,Motion ,Fuzzy Logic ,Artificial Intelligence ,Genetic algorithm ,Xarxes neuronals (Informàtica) ,Computer Simulation ,Rule induction ,Electromyography ,020208 electrical & electronic engineering ,Electrophysiological Techniques ,Biology and Life Sciences ,Fuzzy systems ,Cell Biology ,Nonlinear system ,Nonlinear Dynamics ,Torque ,Cell Signaling Structures ,Sistemes borrosos ,Cellular Neuroscience ,Linear Models ,Neural Networks, Computer ,Nonlinear Systems ,Mathematics ,Neuroscience - Abstract
Aim Fuzzy wavelet neural network (FWNN) has proven to be a promising strategy in the identification of nonlinear systems. The network considers both global and local properties, deals with imprecision present in sensory data, leading to desired precisions. In this paper, we proposed a new FWNN model nominated “Fuzzy Jump Wavelet Neural Network” (FJWNN) for identifying dynamic nonlinear-linear systems, especially in practical applications. Methods The proposed FJWNN is a fuzzy neural network model of the Takagi-Sugeno-Kang type whose consequent part of fuzzy rules is a linear combination of input regressors and dominant wavelet neurons as a sub-jump wavelet neural network. Each fuzzy rule can locally model both linear and nonlinear properties of a system. The linear relationship between the inputs and the output is learned by neurons with linear activation functions, whereas the nonlinear relationship is locally modeled by wavelet neurons. Orthogonal least square (OLS) method and genetic algorithm (GA) are respectively used to purify the wavelets for each sub-JWNN. In this paper, fuzzy rule induction improves the structure of the proposed model leading to less fuzzy rules, inputs of each fuzzy rule and model parameters. The real-world gas furnace and the real electromyographic (EMG) signal modeling problem are employed in our study. In the same vein, piecewise single variable function approximation, nonlinear dynamic system modeling, and Mackey–Glass time series prediction, ratify this method superiority. The proposed FJWNN model is compared with the state-of-the-art models based on some performance indices such as RMSE, RRSE, Rel ERR%, and VAF%. Results The proposed FJWNN model yielded the following results: RRSE (mean±std) of 10e-5±6e-5 for piecewise single-variable function approximation, RMSE (mean±std) of 2.6–4±2.6e-4 for the first nonlinear dynamic system modelling, RRSE (mean±std) of 1.59e-3±0.42e-3 for Mackey–Glass time series prediction, RMSE of 0.3421 for gas furnace modelling and VAF% (mean±std) of 98.24±0.71 for the EMG modelling of all trial signals, indicating a significant enhancement over previous methods. Conclusions The FJWNN demonstrated promising accuracy and generalization while moderating network complexity. This improvement is due to applying main useful wavelets in combination with linear regressors and using fuzzy rule induction. Compared to the state-of-the-art models, the proposed FJWNN yielded better performance and, therefore, can be considered a novel tool for nonlinear system identification
- Published
- 2019
14. New perspective on single-radiator multiple-port antennas for adaptive beamforming applications
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Hosung Choo and Gangil Byun
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Computer science ,Smart antenna ,Information Theory ,lcsh:Medicine ,Reflection ,02 engineering and technology ,Electromagnetic interference ,Radiation properties ,Computer Architecture ,Channel capacity ,0202 electrical engineering, electronic engineering, information engineering ,ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS ,lcsh:Science ,Multidisciplinary ,Physics ,Electromagnetic Radiation ,Channel Capacity ,Classical Mechanics ,Research Design ,Physical Sciences ,Engineering and Technology ,Antenna (radio) ,Adaptive beamformer ,Wireless Technology ,Algorithms ,Research Article ,Beamforming ,Computer and Information Sciences ,Aperture ,Materials Science ,Equipment ,Dielectric ,Data_CODINGANDINFORMATIONTHEORY ,Research and Analysis Methods ,Resonance ,Electronic engineering ,Computer Simulation ,Materials by Attribute ,Computer Science::Information Theory ,Communication Equipment ,WSDMA ,Miniaturization ,Field Tests ,lcsh:R ,020208 electrical & electronic engineering ,ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS ,020206 networking & telecommunications ,Computer Hardware ,Insulators ,Resonance Frequency ,lcsh:Q ,Antennas ,Dielectrics ,Electromagnetic Interference - Abstract
One of the most challenging problems in recent antenna engineering fields is to achieve highly reliable beamforming capabilities in an extremely restricted space of small handheld devices. In this paper, we introduce a new perspective on single-radiator multiple-port (SRMP) antenna to alter the traditional approach of multiple-antenna arrays for improving beamforming performances with reduced aperture sizes. The major contribution of this paper is to demonstrate the beamforming capability of the SRMP antenna for use as an extremely miniaturized front-end component in more sophisticated beamforming applications. To examine the beamforming capability, the radiation properties and the array factor of the SRMP antenna are theoretically formulated for electromagnetic characterization and are used as complex weights to form adaptive array patterns. Then, its fundamental performance limits are rigorously explored through enumerative studies by varying the dielectric constant of the substrate, and field tests are conducted using a beamforming hardware to confirm the feasibility. The results demonstrate that the new perspective of the SRMP antenna allows for improved beamforming performances with the ability of maintaining consistently smaller aperture sizes compared to the traditional multiple-antenna arrays.
- Published
- 2017
15. A Secure Region-Based Geographic Routing Protocol (SRBGR) for Wireless Sensor Networks
- Author
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Zuriati Ahmad Zukarnain, Zurina Mohd Hanapi, Mohamed Othman, and Ali Idarous Adnan
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Dynamic Source Routing ,Computer science ,computer.internet_protocol ,Retransmission ,Enhanced Interior Gateway Routing Protocol ,lcsh:Medicine ,Social Sciences ,Geographic routing ,Astronomical Sciences ,02 engineering and technology ,law.invention ,Routing Information Protocol ,Relay ,law ,Geoinformatics ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:Science ,Hierarchical routing ,Flow Rate ,020203 distributed computing ,Zone Routing Protocol ,Multidisciplinary ,Geography ,Network packet ,Physics ,Classical Mechanics ,Supernetwork ,Ad hoc wireless distribution service ,Celestial Objects ,Semantics ,Aggression ,Interior Gateway Routing Protocol ,Link-state routing protocol ,Physical Sciences ,Telecommunications ,Engineering and Technology ,Hazy Sighted Link State Routing Protocol ,Wireless Technology ,Network Analysis ,Algorithms ,Computer network ,Research Article ,Routing protocol ,Computer and Information Sciences ,Black Holes ,Wireless Routing Protocol ,Geometry ,Fluid Mechanics ,Continuum Mechanics ,Computer Communication Networks ,Mobile wireless sensor network ,Network performance ,Computer Simulation ,Computer Security ,business.industry ,lcsh:R ,ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS ,020206 networking & telecommunications ,Fluid Dynamics ,Linguistics ,Signaling Networks ,Key distribution in wireless sensor networks ,Regional Geography ,Optimized Link State Routing Protocol ,Radii ,Interior gateway protocol ,Geographic Information Systems ,Earth Sciences ,lcsh:Q ,Wireless Sensor Networks ,business ,Wireless sensor network ,computer ,Mathematics ,Software - Abstract
Due to the lack of dependency for routing initiation and an inadequate allocated sextant on responding messages, the secure geographic routing protocols for Wireless Sensor Networks (WSNs) have attracted considerable attention. However, the existing protocols are more likely to drop packets when legitimate nodes fail to respond to the routing initiation messages while attackers in the allocated sextant manage to respond. Furthermore, these protocols are designed with inefficient collection window and inadequate verification criteria which may lead to a high number of attacker selections. To prevent the failure to find an appropriate relay node and undesirable packet retransmission, this paper presents Secure Region-Based Geographic Routing Protocol (SRBGR) to increase the probability of selecting the appropriate relay node. By extending the allocated sextant and applying different message contention priorities more legitimate nodes can be admitted in the routing process. Moreover, the paper also proposed the bound collection window for a sufficient collection time and verification cost for both attacker identification and isolation. Extensive simulation experiments have been performed to evaluate the performance of the proposed protocol in comparison with other existing protocols. The results demonstrate that SRBGR increases network performance in terms of the packet delivery ratio and isolates attacks such as Sybil and Black hole.
- Published
- 2017
16. PSO-Based Smart Grid Application for Sizing and Optimization of Hybrid Renewable Energy Systems
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Abdulrahman I. Alolah, Mohamed A. Mohamed, and Ali M. Eltamaly
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Atmospheric Science ,Computer science ,lcsh:Medicine ,Conservation of Energy Resources ,02 engineering and technology ,Wind ,Automotive engineering ,Geographical locations ,Load management ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:Science ,Wind Power ,Multidisciplinary ,Wind power ,Applied Mathematics ,Simulation and Modeling ,Physics ,Electromagnetic Radiation ,Photovoltaic system ,Particle swarm optimization ,Sizing ,Physical Sciences ,Engineering and Technology ,Solar Radiation ,Diesel generator ,Alternative Energy ,Algorithms ,Research Article ,Optimization ,Asia ,020209 energy ,Materials Science ,Saudi Arabia ,Fuels ,Research and Analysis Methods ,Meteorology ,Electric Power Supplies ,Computer Simulation ,Renewable Energy ,Materials by Attribute ,business.industry ,020208 electrical & electronic engineering ,lcsh:R ,Reproducibility of Results ,Models, Theoretical ,Energy and Power ,Smart grid ,Alternative energy ,Earth Sciences ,lcsh:Q ,People and places ,business ,Mathematics - Abstract
This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers.
- Published
- 2016
17. Dependence of Initial Value on Pattern Formation for a Logistic Coupled Map Lattice
- Author
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Li Xu, Haoyue Cui, and Guang Zhang
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Evolutionary Genetics ,lcsh:Medicine ,01 natural sciences ,Systems Science ,010305 fluids & plasmas ,Pattern Recognition, Automated ,Morphogenesis ,Statistical physics ,Pattern Formation ,lcsh:Science ,010301 acoustics ,Mathematics ,Multidisciplinary ,Physics ,Linear model ,Dynamical Systems ,System parameters ,Pattern recognition (psychology) ,Physical Sciences ,Algorithms ,Research Article ,Computer and Information Sciences ,Biophysical Simulations ,Biophysics ,Pattern formation ,Set (abstract data type) ,0103 physical sciences ,Initial value problem ,Animals ,Humans ,Computer Simulation ,Eigenvalues and eigenvectors ,Evolutionary Biology ,Traveling Waves ,lcsh:R ,Biology and Life Sciences ,Computational Biology ,Reproducibility of Results ,Eigenvalues ,Models, Theoretical ,Algebra ,Logistic Models ,Linear Algebra ,Waves ,Linear Models ,lcsh:Q ,Wave Propagation ,Eigenvectors ,Coupled map lattice ,Developmental Biology - Abstract
The logistic coupled map lattices (LCML) have been widely investigated as well as their pattern dynamics. The patterns formation may depend on not only fluctuations of system parameters, but variation of the initial conditions. However, the mathematical discussion is quite few for the effect of initial values so far. The present paper is concerned with the pattern formation for a two-dimensional Logistic coupled map lattice, where any initial value can be linear expressed by corresponding eigenvectors, and patterns formation can be determined by selecting the corresponding eigenvectors. A set of simulations are conducted whose results demonstrate the fact. The method utilized in the present paper could be applied to other discrete systems as well.
- Published
- 2016
18. Size effect of parallel-joint spacing on uniaxial compressive strength of rock
- Author
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Gaojian Hu and Gang Ma
- Subjects
Computer and Information Sciences ,Materials science ,Compressive Strength ,Science ,Materials Science ,Material Properties ,Research and Analysis Methods ,Physics::Geophysics ,Computer Software ,Mathematical and Statistical Techniques ,Computer software ,Materials Testing ,Pressure ,Mechanical Properties ,Computer Simulation ,Composite material ,Damage Mechanics ,Minerals ,Multidisciplinary ,Models, Statistical ,Mathematical model ,Mathematical Models ,Simulation and Modeling ,Physics ,Classical Mechanics ,Software Engineering ,Joint spacing ,Models, Theoretical ,Deformation ,Elasticity ,Curve Fitting ,Compressive strength ,Physical Sciences ,Curve fitting ,Medicine ,Mechanical Stress ,Engineering and Technology ,Stress, Mechanical ,Deformation (engineering) ,Mathematical Functions ,Algorithms ,Research Article - Abstract
The existence of parallel joints has an impact on the size effect of the uniaxial compressive strength of rock, but the relationship is yet to be obtained. In this paper, the influence of parallel-joint spacing on the size effect and characteristic size of rock uniaxial compressive strength is studied by establishing five types of parallel-joint-spacing simulation schemes. The influence of parallel-joint spacing on the size effect of rock uniaxial compressive strength is explored by analyzing the stress–strain curves of rocks with different parallel-joint spacings and rock sizes. The relationship between the uniaxial compressive strength and the size of the rock with parallel joints and its special mathematical model are obtained, and the particular form of the compressive-strength characteristic size and parallel-joint spacing is obtained.
- Published
- 2021
19. Fuzzy adaptive fault diagnosis and compensation for variable structure hypersonic vehicle with multiple faults
- Author
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Wenhao Li, Kaiyu Hu, and Zian Cheng
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Lyapunov function ,Computer and Information Sciences ,Unmanned Aerial Devices ,Observer (quantum physics) ,Aircraft ,Computer science ,Science ,Fault Tolerance ,Transportation ,Control Systems ,Fault (power engineering) ,Research and Analysis Methods ,Stability (probability) ,Fuzzy logic ,Systems Science ,symbols.namesake ,Aerodynamics ,Fuzzy Logic ,Control theory ,Industrial Engineering ,Humans ,Computer Simulation ,Damage Mechanics ,Multidisciplinary ,Models, Statistical ,Physics ,Applied Mathematics ,Simulation and Modeling ,Mechanical Engineering ,Uncertainty ,Classical Mechanics ,Software Engineering ,Fault tolerance ,Control Engineering ,Dynamics ,Variable (computer science) ,Nonlinear system ,Nonlinear Dynamics ,Physical Sciences ,symbols ,Medicine ,Engineering and Technology ,Mathematics ,Algorithms ,Actuators ,Research Article - Abstract
Based on the type-II fuzzy logic, this paper proposes a robust adaptive fault diagnosis and fault-tolerant control (FTC) scheme for multisensor faults in the variable structure hypersonic vehicles with parameter uncertainties. Type-II fuzzy method approximates the original models while eliminating the parameter uncertainties. Hence the sensor faults are detected and isolated by the multiple output residuals and thresholds considering nonlinear approximation errors and disturbance. Based on the fuzzy adaptive augmented observer, the faults and disturbance are all estimated accurately by an improved proportional-differential part. Then a variable structure FTC scheme repairs the faults by the estimation, the fast-varying disturbance is considered in FTC scheme and is compensated by the control parameters designed based on its derivative function, thereby enhancing the output robust tracking accuracy of the variable structure hypersonic vehicles. The Lyapunov theory proves the system robust stability, semi-physical simulation verifies the validity of the proposed method and the superiority compared with the traditional method.
- Published
- 2021
20. Eigenvalue-based entropy in directed complex networks
- Author
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Xiujuan Ma, Jing Liang, Yan Sun, and Haixing Zhao
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Computer and Information Sciences ,Computer science ,Science ,Entropy ,Small World Networks ,Information Theory ,010103 numerical & computational mathematics ,02 engineering and technology ,Topology ,01 natural sciences ,Infographics ,Models, Biological ,0202 electrical engineering, electronic engineering, information engineering ,Entropy (information theory) ,Cluster Analysis ,Computer Simulation ,0101 mathematics ,Network model ,Data Management ,Multidisciplinary ,Small-world network ,Directed Graphs ,Node (networking) ,Physics ,Data Visualization ,Scale-free network ,Eigenvalues ,Directed graph ,Complex network ,Algebra ,Linear Algebra ,Graph Theory ,Physical Sciences ,Medicine ,Thermodynamics ,020201 artificial intelligence & image processing ,Neural Networks, Computer ,Laplacian matrix ,Scale-Free Networks ,Graphs ,Information Entropy ,Network Analysis ,Mathematics ,Algorithms ,Research Article - Abstract
Entropy is an important index for describing the structure, function, and evolution of network. The existing research on entropy is primarily applied to undirected networks. Compared with an undirected network, a directed network involves a special asymmetric transfer. The research on the entropy of directed networks is very significant to effectively quantify the structural information of the whole network. Typical complex network models include nearest-neighbour coupling network, small-world network, scale-free network, and random network. These network models are abstracted as undirected graphs without considering the direction of node connection. For complex networks, modeling through the direction of network nodes is extremely challenging. In this paper, based on these typical models of complex network, a directed network model considering node connection in-direction is proposed, and the eigenvalue entropies of three matrices in the directed network is defined and studied, where the three matrices are adjacency matrix, in-degree Laplacian matrix and in-degree signless Laplacian matrix. The eigenvalue-based entropies of three matrices are calculated in directed nearest-neighbor coupling, directed small world, directed scale-free and directed random networks. Through the simulation experiment on the real directed network, the result shows that the eigenvalue entropy of the real directed network is between the eigenvalue entropy of directed scale-free network and directed small-world network.
- Published
- 2021
21. Controlling the pressure of hydrogen-natural gas mixture in an inclined pipeline
- Author
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Sarkhosh Seddighi Chaharborj and Norsarahaida Amin
- Subjects
Fossil Fuels ,Optimization problem ,Pipeline (computing) ,02 engineering and technology ,Polynomials ,Systems Science ,Mathematical and Statistical Techniques ,Natural gas ,0202 electrical engineering, electronic engineering, information engineering ,Fluid dynamics ,Taylor series ,Materials ,Mathematics ,Multidisciplinary ,Physics ,Statistics ,Classical Mechanics ,Mechanics ,Chemistry ,Physical Sciences ,symbols ,Medicine ,Engineering and Technology ,Regression Analysis ,Gases ,Algorithms ,Research Article ,Chemical Elements ,Optimization ,Computer and Information Sciences ,Manometry ,Science ,Flow (psychology) ,Materials Science ,Fluid Mechanics ,Fuels ,Natural Gas ,Research and Analysis Methods ,Continuum Mechanics ,symbols.namesake ,020401 chemical engineering ,Pressure ,Computer Simulation ,0204 chemical engineering ,Statistical Methods ,Fluid Flow ,business.industry ,020208 electrical & electronic engineering ,Fluid Dynamics ,Optimal control ,Energy and Power ,Nonlinear system ,Algebra ,business ,Nonlinear Systems ,Hydrogen ,High Pressure - Abstract
This paper discusses the optimal control of pressure using the zero-gradient control (ZGC) approach. It is applied for the first time in the study to control the optimal pressure of hydrogen natural gas mixture in an inclined pipeline. The solution to the flow problem is first validated with existing results using the Taylor series approximation, regression analysis and the Runge-Kutta method combined. The optimal pressure is then determined using ZGC where the optimal set points are calculated without having to solve the non-linear system of equations associated with the standard optimization problem. It is shown that the mass ratio is the more effective parameter compared to the initial pressure in controlling the maximum variation of pressure in a gas pipeline.
- Published
- 2020
22. A low-loss and compact single-layer butler matrix for a 5G base station antenna
- Author
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Ismahayati Adam, Mohamad Sofian Abu Talip, Intan Izafina Idrus, Mohd Najib Mohd Yasin, Tarik Abdul Latef, Tharek Abd Rahman, Yoshihide Yamada, and Narendra Kumar Aridas
- Subjects
Employment ,Computer and Information Sciences ,Electromagnetics ,Economics ,Acoustics ,Science ,Crossover ,Equipment ,Social Sciences ,02 engineering and technology ,Research and Analysis Methods ,Electricity ,Software Design ,0202 electrical engineering, electronic engineering, information engineering ,Insertion loss ,Computer Simulation ,Computerized Simulations ,Electrodes ,Physics ,Communication Equipment ,Multidisciplinary ,Electromagnetic Radiation ,020208 electrical & electronic engineering ,Software Engineering ,020206 networking & telecommunications ,Electrical element ,Equipment Design ,Optical Lenses ,Quadrature (mathematics) ,Wavelength ,Optical Equipment ,Research Design ,Labor Economics ,Extremely high frequency ,Physical Sciences ,Telecommunications ,Medicine ,Engineering and Technology ,Antennas ,Phase shift module ,Wireless Technology ,Algorithms ,Software ,Research Article - Abstract
Researchers are increasingly showing interest in the application of a Butler matrix for fifth-generation (5G) base station antennas. However, the design of the Butler matrix is challenging at millimeter wave because of the very small wavelength. The literature has reported issues of high insertion losses and incorrect output phases at the output ports of the Butler matrix, which affects the radiation characteristics. To overcome these issues, the circuit elements of the Butler matrix such as the crossover, the quadrature hybrid and the phase shifter must be designed using highly accurate dimensions. This paper presents a low-loss and compact single-layer 8 × 8 Butler matrix operating at 28 GHz. The optimum design of each circuit element is also demonstrated in detail. The designed Butler matrix was fabricated to validate the simulated results. The measured results showed return losses of less than −10 dB at 28 GHz. The proposed Butler matrix achieved a low insertion loss and a low phase error of ± 2 dB and ± 10°, respectively. In sum, this work obtained a good agreement between the simulated and measured results.
- Published
- 2019
23. A Fuzzy Comprehensive CS-SVR Model-based health status evaluation of radar
- Author
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Maohui Zhang, Yifei Yang, and Yuewei Dai
- Subjects
Optimization ,0209 industrial biotechnology ,Computer science ,Science ,Kernel Functions ,Entropy ,Vector Spaces ,Health Status ,Equipment ,02 engineering and technology ,Fault (power engineering) ,computer.software_genre ,Research and Analysis Methods ,Fuzzy logic ,law.invention ,Remote Sensing ,020901 industrial engineering & automation ,Fuzzy Logic ,law ,0202 electrical engineering, electronic engineering, information engineering ,Entropy (information theory) ,Humans ,Computer Simulation ,Radar ,Operator Theory ,Multidisciplinary ,Applied Mathematics ,Simulation and Modeling ,Physics ,Navigation ,Algebra ,Linear Algebra ,Physical Sciences ,Medicine ,Engineering and Technology ,Thermodynamics ,020201 artificial intelligence & image processing ,Enhanced Data Rates for GSM Evolution ,State (computer science) ,Data mining ,computer ,Mathematics ,Algorithms ,Research Article - Abstract
The purpose of Fuzzy Comprehensive CS-SVR Model (FCCS-SVR) is to evaluate and monitor the health status of a radar equipment and then keep its safe operation. Due to reasons such as few samples, slow changes and the nonlinear structure of data of fault monitoring signal, the health status evaluation of a radar system is quite difficult. By establishing the evaluation index system of a radar, the combination of AHP method and Entropy weight method is studied in this paper. In order to evaluate the value of health status, several optimization algorithms including PSO, GA, BA and CS are used for optimizing the parameters of SVR model. Meanwhile, in order to avoid the problem that the system is at the edge of the state, a radar health assessment method based on the combination of Fuzzy Comprehensive Evaluation and Cuckoo Search-Support Vector Regression (CS-SVR), which is named as Fuzzy Comprehensive CS-SVR (FCCS-SVR), is further proposed. The result of case analysis reflects that the state evaluation of the radar system is realized. The system performance analysis shows that the use of FCCS-SVR evaluation method provides a high recognition rate and can accurately assess the health status of the radar system.
- Published
- 2019
24. Numerical simulation of high-temperature thermal contact resistance and its reduction mechanism
- Author
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Jing Zhang and Donghuan Liu
- Subjects
Computer and Information Sciences ,Materials science ,Hot Temperature ,Neural Networks ,Materials by Structure ,Surface Properties ,Finite Element Analysis ,Materials Science ,Material Properties ,lcsh:Medicine ,Aerospace Engineering ,Thermal grease ,02 engineering and technology ,Research and Analysis Methods ,Leading Edges ,Thermal conductivity ,0203 mechanical engineering ,Materials Testing ,Computer Simulation ,Composite material ,lcsh:Science ,Thermal contact conductance ,Damage Mechanics ,Multidisciplinary ,Applied Mathematics ,Simulation and Modeling ,Physics ,lcsh:R ,Biology and Life Sciences ,Classical Mechanics ,Thermal Conductivity ,021001 nanoscience & nanotechnology ,Finite element method ,Deformation ,Superalloy ,Heat pipe ,020303 mechanical engineering & transports ,Thermal radiation ,Physical Sciences ,Engineering and Technology ,Composite Materials ,lcsh:Q ,0210 nano-technology ,Material properties ,Mathematics ,Algorithms ,Research Article ,Neuroscience - Abstract
High-temperature thermal contact resistance (TCR) plays an important role in heat-pipe-cooled thermal protection structures due to the existence of contact interface between the embedded heat pipe and the heat resistive structure, and the reduction mechanism of thermal contact resistance is of special interests in the design of such structures. The present paper proposed a finite element model of the high-temperature thermal contact resistance based on the multi-point contact model with the consideration of temperature-dependent material properties, heat radiation through the cavities at the interface and the effect of thermal interface material (TIM), and the geometry parameters of the finite element model are determined by simple surface roughness test and experimental data fitting. The experimental results of high-temperature thermal contact resistance between superalloy GH600 and C/C composite material are employed to validate the present finite element model. The effect of the crucial parameters on the thermal contact resistance with and without TIM are also investigated with the proposed finite element model.
- Published
- 2018
25. A flocking algorithm for multi-agent systems with connectivity preservation under hybrid metric-topological interactions
- Author
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Zhigang Ren, Chenlong He, and Zuren Feng
- Subjects
0209 industrial biotechnology ,Correctness ,Computer science ,Velocity ,lcsh:Medicine ,02 engineering and technology ,01 natural sciences ,Upper and lower bounds ,Systems Science ,Topology ,Database and Informatics Methods ,020901 industrial engineering & automation ,Agent-Based Modeling ,lcsh:Science ,Multidisciplinary ,Behavior, Animal ,Multi-agent system ,Simulation and Modeling ,Applied Mathematics ,Physics ,Classical Mechanics ,Eukaryota ,Graph ,Algebraic Topology ,Physical Sciences ,Vertebrates ,Heuristic Alignment Procedure ,Graph (abstract data type) ,Sequence Analysis ,Algorithms ,Research Article ,Computer and Information Sciences ,Bioinformatics ,Algebraic topology ,Research and Analysis Methods ,Birds ,Motion ,0103 physical sciences ,Animals ,Computer Simulation ,010306 general physics ,Flocking (behavior) ,lcsh:R ,Organisms ,Biology and Life Sciences ,Models, Theoretical ,Computer Science::Multiagent Systems ,Nonlinear system ,Algebra ,Flight, Animal ,Amniotes ,lcsh:Q ,Mathematics - Abstract
In this paper, we propose a connectivity-preserving flocking algorithm for multi-agent systems in which the neighbor set of each agent is determined by the hybrid metric-topological distance so that the interaction topology can be represented as the range-limited Delaunay graph, which combines the properties of the commonly used disk graph and Delaunay graph. As a result, the proposed flocking algorithm has the following advantages over the existing ones. First, range-limited Delaunay graph is sparser than the disk graph so that the information exchange among agents is reduced significantly. Second, some links irrelevant to the connectivity can be dynamically deleted during the evolution of the system. Thus, the proposed flocking algorithm is more flexible than existing algorithms, where links are not allowed to be disconnected once they are created. Finally, the multi-agent system spontaneously generates a regular quasi-lattice formation without imposing the constraint on the ratio of the sensing range of the agent to the desired distance between two adjacent agents. With the interaction topology induced by the hybrid distance, the proposed flocking algorithm can still be implemented in a distributed manner. We prove that the proposed flocking algorithm can steer the multi-agent system to a stable flocking motion, provided the initial interaction topology of multi-agent systems is connected and the hysteresis in link addition is smaller than a derived upper bound. The correctness and effectiveness of the proposed algorithm are verified by extensive numerical simulations, where the flocking algorithms based on the disk and Delaunay graph are compared.
- Published
- 2018
26. Correction of failure in linear antenna arrays with greedy sparseness constrained optimization technique
- Author
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Murtala Aminu-Baba, M. K. A. Rahim, Shafqat Ullah Khan, and Noor Asniza Murad
- Subjects
Optimization ,Computer science ,lcsh:Medicine ,02 engineering and technology ,Research and Analysis Methods ,01 natural sciences ,Computer Communication Networks ,Computational Techniques ,0202 electrical engineering, electronic engineering, information engineering ,Animal Physiology ,Computer Simulation ,Animal Anatomy ,Greedy algorithm ,lcsh:Science ,Damage Mechanics ,Multidisciplinary ,Applied Mathematics ,Simulation and Modeling ,Physics ,Genetic Algorithms ,010401 analytical chemistry ,lcsh:R ,Constrained optimization ,Biology and Life Sciences ,Classical Mechanics ,020206 networking & telecommunications ,Numerical Analysis, Computer-Assisted ,Matching pursuit ,0104 chemical sciences ,Power (physics) ,Physical Sciences ,Telecommunications ,Engineering and Technology ,lcsh:Q ,Antennae (Animal Physiology) ,Evolutionary Algorithms ,Antenna (radio) ,Evolutionary Computation ,Algorithm ,Zoology ,Mathematics ,Algorithms ,Research Article - Abstract
This paper proposes the correction of faulty sensors using a synthesis of the greedy sparse constrained optimization GSCO) technique. The failure of sensors can damage the radiation power pattern in terms of sidelobes and nulls. The synthesis problem can recover the wanted power pattern with reduced number of sensors into the background of greedy algorithm and solved with orthogonal matching pursuit (OMP) technique. Numerical simulation examples of linear arrays are offered to demonstrate the effectiveness of getting the wanted power pattern with a reduced number of antenna sensors which is compared with the available techniques in terms of sidelobes level and number of nulls.
- Published
- 2017
27. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking
- Author
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Yongjie Liu, Xiaoyu Yu, Yunbo Shi, and Yajie Wang
- Subjects
Computer science ,lcsh:Medicine ,02 engineering and technology ,Tracking (particle physics) ,law.invention ,Electronics Engineering ,Electricity ,law ,0202 electrical engineering, electronic engineering, information engineering ,lcsh:Science ,Reliability (statistics) ,Multidisciplinary ,Electric Power Supplies ,Crystallography ,Physics ,Simulation and Modeling ,Applied Mathematics ,Photovoltaic system ,Photoelectric sensor ,Condensed Matter Physics ,Electrical network ,Physical Sciences ,Photovoltaic Power ,Crystal Structure ,Engineering and Technology ,Alternative Energy ,Solar System ,Electrical Engineering ,Algorithms ,Research Article ,Computer and Information Sciences ,020209 energy ,Research and Analysis Methods ,Computer Software ,Control theory ,Solar Energy ,Solid State Physics ,Computer Simulation ,Sunlight ,business.industry ,lcsh:R ,020208 electrical & electronic engineering ,Models, Theoretical ,Solar energy ,Energy and Power ,Logic Circuits ,Alternative energy ,lcsh:Q ,business ,Mathematics ,Software ,Electrical Circuits - Abstract
Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.
- Published
- 2016
28. A Method for Automated Classification of Parkinson’s Disease Diagnosis Using an Ensemble Average Propagator Template Brain Map Estimated from Diffusion MRI
- Author
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Baba C. Vemuri, Michael S. Okun, David E. Vaillancourt, and Monami Banerjee
- Subjects
Pathology ,Parkinson's disease ,Computer science ,lcsh:Medicine ,computer.software_genre ,Brain mapping ,Biochemistry ,030218 nuclear medicine & medical imaging ,Diagnostic Radiology ,Pattern Recognition, Automated ,0302 clinical medicine ,Voxel ,Medicine and Health Sciences ,lcsh:Science ,Brain Mapping ,Multidisciplinary ,Movement Disorders ,medicine.diagnostic_test ,Orientation (computer vision) ,Radiology and Imaging ,Physics ,Classical Mechanics ,Brain ,Neurodegenerative Diseases ,Parkinson Disease ,Condensed Matter Physics ,Magnetic Resonance Imaging ,Deformation ,Diffusion Tensor Imaging ,Neurology ,Feature (computer vision) ,Physical Sciences ,Algorithms ,Research Article ,medicine.medical_specialty ,Imaging Techniques ,Brain Morphometry ,Materials Science ,Material Properties ,Neuroimaging ,Research and Analysis Methods ,Parkinsonian syndromes ,03 medical and health sciences ,Diagnostic Medicine ,Image Interpretation, Computer-Assisted ,Medical imaging ,medicine ,Humans ,Computer Simulation ,Damage Mechanics ,business.industry ,lcsh:R ,Biology and Life Sciences ,Pattern recognition ,Magnetic resonance imaging ,medicine.disease ,Diffusion Magnetic Resonance Imaging ,Case-Control Studies ,Anisotropy ,lcsh:Q ,Artificial intelligence ,business ,computer ,030217 neurology & neurosurgery ,Biomarkers ,Diffusion MRI ,Neuroscience - Abstract
Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder that affects patients in all countries and of all nationalities. Magnetic resonance imaging (MRI) is currently one of the most widely used diagnostic imaging techniques utilized for detection of neurologic diseases. Changes in structural biomarkers will likely play an important future role in assessing progression of many neurological diseases inclusive of PD. In this paper, we derived structural biomarkers from diffusion MRI (dMRI), a structural modality that allows for non-invasive inference of neuronal fiber connectivity patterns. The structural biomarker we use is the ensemble average propagator (EAP), a probability density function fully characterizing the diffusion locally at a voxel level. To assess changes with respect to a normal anatomy, we construct an unbiased template brain map from the EAP fields of a control population. Use of an EAP captures both orientation and shape information of the diffusion process at each voxel in the dMRI data, and this feature can be a powerful representation to achieve enhanced PD brain mapping. This template brain map construction method is applicable to small animal models as well as to human brains. The differences between the control template brain map and novel patient data can then be assessed via a nonrigid warping algorithm that transforms the novel data into correspondence with the template brain map, thereby capturing the amount of elastic deformation needed to achieve this correspondence. We present the use of a manifold-valued feature called the Cauchy deformation tensor (CDT), which facilitates morphometric analysis and automated classification of a PD versus a control population. Finally, we present preliminary results of automated discrimination between a group of 22 controls and 46 PD patients using CDT. This method may be possibly applied to larger population sizes and other parkinsonian syndromes in the near future.
- Published
- 2016
29. Ringed Seal Search for Global Optimization via a Sensitive Search Model
- Author
-
Younes Saadi, Haruna Chiroma, Tutut Herawan, Iwan Tri Riyadi Yanto, Vimala Balakrishnan, and Anhar Risnumawan
- Subjects
Seals, Earless ,RSS ,lcsh:Medicine ,Social Sciences ,02 engineering and technology ,Mathematical and Statistical Techniques ,0202 electrical engineering, electronic engineering, information engineering ,Psychology ,lcsh:Science ,Cuckoo search ,Physics ,Mammals ,Multidisciplinary ,Animal Behavior ,Behavior, Animal ,Mathematical Models ,Applied Mathematics ,Simulation and Modeling ,Swarm behaviour ,computer.file_format ,Random walk ,Habitats ,Smell ,Physical Sciences ,Vertebrates ,Benchmark (computing) ,020201 artificial intelligence & image processing ,Sensory Perception ,Imitation ,Algorithm ,Algorithms ,Research Article ,Optimization ,Death Rates ,Bears ,Research and Analysis Methods ,Population Metrics ,020204 information systems ,Genetic algorithm ,Animals ,Computer Simulation ,Global optimization ,Metaheuristic ,Demography ,Behavior ,Population Biology ,lcsh:R ,Ecology and Environmental Sciences ,Organisms ,Biology and Life Sciences ,Models, Theoretical ,Random Walk ,People and Places ,lcsh:Q ,computer ,Zoology ,Mathematics ,Neuroscience - Abstract
The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global optimization problems.
- Published
- 2016
30. Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms
- Author
-
Laura-Nicoleta Ivanciu and Gabriel Oltean
- Subjects
Mean squared error ,Knowledge Bases ,Wavelet Analysis ,lcsh:Medicine ,Computational intelligence ,02 engineering and technology ,Bioinformatics ,0202 electrical engineering, electronic engineering, information engineering ,Waveform ,Computer Simulation ,lcsh:Science ,Physics ,Multidisciplinary ,Artificial neural network ,Models, Genetic ,lcsh:R ,020208 electrical & electronic engineering ,Wavelet transform ,Function (mathematics) ,Metamodeling ,Range (mathematics) ,Linear Models ,lcsh:Q ,020201 artificial intelligence & image processing ,Neural Networks, Computer ,Algorithm ,Algorithms ,Research Article - Abstract
The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the output waveform).
- Published
- 2016
31. The Continual Reassessment Method for Multiple Toxicity Grades: A Bayesian Model Selection Approach
- Author
-
Ling Wang, Feng Zhang, Chanjuan Li, Ying Yuan, Wenhong Zhang, Haitao Pan, Shemin Zhang, Jielai Xia, and Cailin Zhu
- Subjects
Maximum Tolerated Dose ,Clinical Research Design ,Predictive Toxicology ,Cancer Treatment ,lcsh:Medicine ,Antineoplastic Agents ,Machine learning ,computer.software_genre ,Bioinformatics ,Bayesian inference ,Toxicology ,Research and Analysis Methods ,Continual reassessment method ,Bayes' theorem ,Clinical trials ,Neoplasms ,Humans ,Computer Simulation ,Theoretical Pharmacology ,lcsh:Science ,Selection (genetic algorithm) ,Physics ,Medicine and health sciences ,Pharmacology ,Multidisciplinary ,Models, Statistical ,Clinical Trials, Phase I as Topic ,business.industry ,Phase I clinical investigation ,lcsh:R ,Clinical Pharmacology ,Biology and Life Sciences ,Phase i trials ,Bayes Theorem ,Probability Theory ,Oncology ,Research Design ,Maximum tolerated dose ,Clinical medicine ,Physical Sciences ,Probability distribution ,lcsh:Q ,Artificial intelligence ,business ,computer ,Mathematics ,Algorithms ,Research Article - Abstract
Grade information has been considered in Yuan et al. (2007) wherein they proposed a Quasi-CRM method to incorporate the grade toxicity information in phase I trials. A potential problem with the Quasi-CRM model is that the choice of skeleton may dramatically vary the performance of the CRM model, which results in similar consequences for the Quasi-CRM model. In this paper, we propose a new model by utilizing bayesian model selection approach – Robust Quasi-CRM model – to tackle the above-mentioned pitfall with the Quasi-CRM model. The Robust Quasi-CRM model literally inherits the BMA-CRM model proposed by Yin and Yuan (2009) to consider a parallel of skeletons for Quasi-CRM. The superior performance of Robust Quasi-CRM model was demonstrated by extensive simulation studies. We conclude that the proposed method can be freely used in real practice.
- Published
- 2014
32. Optimizing Online Social Networks for Information Propagation
- Author
-
Yan Fu, Yi-Cheng Zhang, An Zeng, Duanbing Chen, and Guan-Nan Wang
- Subjects
Information propagation ,Computer and Information Sciences ,Uniform distribution (continuous) ,Informatics ,lcsh:Medicine ,Similarity measure ,Recommender system ,Bioinformatics ,Social Networking ,Medicine ,Humans ,Computer Simulation ,lcsh:Science ,Social influence ,Numerical Analysis ,Internet ,Multidisciplinary ,Information retrieval ,business.industry ,Information Dissemination ,Physics ,lcsh:R ,Reproducibility of Results ,Models, Theoretical ,Internet Standard ,Information overload ,Social research ,Physical Sciences ,Interdisciplinary Physics ,lcsh:Q ,business ,Mathematics ,Algorithms ,Research Article - Abstract
Online users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their leaders. Validation of such adaptive social recommendation methods in the literature assumes uniform distribution of users' activity frequency. In this paper, our empirical analysis shows that the distribution of online users' activity is actually heterogenous. Accordingly, we propose a more realistic multi-agent model in which users' activity frequency are drawn from a power-law distribution. We find that previous social recommendation methods lead to serious delay of information propagation since many users are connected to inactive leaders. To solve this problem, we design a new similarity measure which takes into account users' activity frequencies. With this similarity measure, the average delay is significantly shortened and the recommendation accuracy is largely improved.
- Published
- 2014
33. Refractory Period Modulates the Spatiotemporal Evolution of Cortical Spreading Depression: A Computational Study
- Author
-
Bing Li, Shangbin Chen, Qingming Luo, Pengcheng Li, and Hui Gong
- Subjects
Circuit Models ,Central Nervous System ,Anatomy and Physiology ,Wave propagation ,Refractory period ,Models, Neurological ,Biophysics ,lcsh:Medicine ,Neurophysiology ,Biochemistry ,Neurological System ,Biophysics Theory ,Recovery rate ,Diagnostic Medicine ,Cortex (anatomy) ,medicine ,Pathology ,Humans ,Computer Simulation ,lcsh:Science ,Biology ,Theoretical Biology ,Neuropathology ,Physics ,Computational Neuroscience ,Cerebral Cortex ,Multidisciplinary ,Neuromodulation ,Systems Biology ,lcsh:R ,Cortical Spreading Depression ,Computational Biology ,Neurochemistry ,medicine.anatomical_structure ,Cerebral cortex ,Anatomical Pathology ,Cortical spreading depression ,Ischemic stroke ,Medicine ,lcsh:Q ,Biophysic Al Simulations ,Neuroscience ,Algorithms ,Research Article - Abstract
Cortical spreading depression (CSD) is a pathophysiological phenomenon, which underlies some neurological disorders, such as migraine and stroke, but its mechanisms are still not completely understood. One of the striking facts is that the spatiotemporal evolution of CSD wave is varying. Observations in experiments reveal that a CSD wave may propagate through the entire cortex, or just bypass some areas of the cortex. In this paper, we have applied a 2D reaction-diffusion equation with recovery term to study the spatiotemporal evolution of CSD. By modulating the recovery rate from CSD in the modeled cortex, CSD waves with different spatiotemporal evolutions, either bypassing some areas or propagating slowly in these areas, were present. Moreover, spiral CSD waves could also be induced in case of the transiently altered recovery rate, i.e. block release from the absolute refractory period. These results suggest that the refractory period contributes to the different propagation patterns of CSD, which may help to interpret the mechanisms of CSD propagation.
- Published
- 2014
34. On the Encoding of Proteins for Disordered Regions Prediction
- Author
-
Julien Becker, Louis Wehenkel, and Francis Maes
- Subjects
Physics ,Protein structure and function ,Models, Molecular ,Multidisciplinary ,Protein Conformation ,lcsh:R ,Protein Data Bank (RCSB PDB) ,Disulfide bond ,Inference ,lcsh:Medicine ,Feature selection ,Computational biology ,Bioinformatics ,Protein structure ,Sequence Analysis, Protein ,lcsh:Q ,Computer Simulation ,Evolutionary information ,CASP ,lcsh:Science ,Algorithms ,Software ,Research Article - Abstract
Disordered regions, i.e., regions of proteins that do not adopt a stable three-dimensional structure, have been shown to play various and critical roles in many biological processes. Predicting and understanding their formation is therefore a key sub-problem of protein structure and function inference. A wide range of machine learning approaches have been developed to automatically predict disordered regions of proteins. One key factor of the success of these methods is the way in which protein information is encoded into features. Recently, we have proposed a systematic methodology to study the relevance of various feature encodings in the context of disulfide connectivity pattern prediction. In the present paper, we adapt this methodology to the problem of predicting disordered regions and assess it on proteins from the 10th CASP competition, as well as on a very large subset of proteins extracted from PDB. Our results, obtained with ensembles of extremely randomized trees, highlight a novel feature function encoding the proximity of residues according to their accessibility to the solvent, which is playing the second most important role in the prediction of disordered regions, just after evolutionary information. Furthermore, even though our approach treats each residue independently, our results are very competitive in terms of accuracy with respect to the state-of-the-art. A web-application is available at http://m24.giga.ulg.ac.be:81/x3Disorder.
- Published
- 2013
35. Quid Pro Quo: A Mechanism for Fair Collaboration in Networked Systems
- Author
-
Luis López Fernández, Agustín Santos, and Antonio Fernández Anta
- Subjects
FOS: Computer and information sciences ,Distributed computing ,lcsh:Medicine ,Models, Psychological ,Communications system ,computer.software_genre ,Community Networks ,Task (project management) ,System model ,Computer Science - Networking and Internet Architecture ,Game Theory ,Computer Science - Computer Science and Game Theory ,Humans ,Computer Simulation ,Cooperative Behavior ,lcsh:Science ,Networking and Internet Architecture (cs.NI) ,Physics ,Internet ,Multidisciplinary ,business.industry ,Node (networking) ,lcsh:R ,Context (computing) ,Computer Science - Distributed, Parallel, and Cluster Computing ,lcsh:Q ,The Internet ,Collaboration ,Distributed, Parallel, and Cluster Computing (cs.DC) ,business ,computer ,Game theory ,Algorithms ,Computer Science and Game Theory (cs.GT) ,Research Article - Abstract
Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust event in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet)., Comment: 23 pages, 5 figures, 3 algorithms
- Published
- 2013
36. Structural Discrimination of Networks by Using Distance, Degree and Eigenvalue-Based Measures
- Author
-
Matthias Dehmer, Boris Furtula, and Martin Grabner
- Subjects
Theoretical computer science ,Mathematical properties ,lcsh:Medicine ,Bioinformatics ,Computer Graphics ,Computer Simulation ,Uniqueness ,lcsh:Science ,Theoretical Chemistry ,Biology ,Mathematical Computing ,Eigenvalues and eigenvectors ,Real number ,Physics ,Multidisciplinary ,Discrete Mathematics ,Applied Mathematics ,lcsh:R ,Empirical modelling ,Computational Biology ,Graph theory ,Complex Systems ,Models, Theoretical ,Graph ,Chemistry ,Computer Science ,lcsh:Q ,Biological network ,Algorithms ,Mathematics ,Research Article - Abstract
In chemistry and computational biology, structural graph descriptors have been proven essential for characterizing the structure of chemical and biological networks. It has also been demonstrated that they are useful to derive empirical models for structure-oriented drug design. However, from a more general (complex network-oriented) point of view, investigating mathematical properties of structural descriptors, such as their uniqueness and structural interpretation, is also important for an in-depth understanding of the underlying methods. In this paper, we emphasize the evaluation of the uniqueness of distance, degree and eigenvalue-based measures. Among these are measures that have been recently investigated extensively. We report numerical results using chemical and exhaustively generated graphs and also investigate correlations between the measures.
- Published
- 2012
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