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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Yuan, Haitao Wang, Meijia Bi, Jing Zhang, Jia School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing University of Technology Faculty of Information Technology Beijing China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Current mobile edge computing (MEC) owns cloud resources at the network edge, which enables low-latency mobile services. In addition to fixed MEC servers, MEC proxy servers with certain mobility and limited computing, e.g., flying unmanned aerial vehicles (UAVs), and vehicles, have emerged as competitors in providing services. In this work, aiming at a task offloading problem of a UAV-assisted MEC system, a hybrid network environment with multiple mobile devices (MDs) and multiple UAVs is established. A constrained mixed integer nonlinear program of the UAV-assisted hybrid cloud-edge system is formulated. A novel hybrid metaheuristic algorithm called Genetic Simulated annealing-based Particle Swarm Optimization (GSPSO) is presented to solve the program. Then, a task offloading and resource scheduling method is designed to intelligently minimize the total energy consumption of the hybrid system. Simulation results verify superiority of GSPSO over its three benchmark algorithms, thus demonstrating the proposed method significantly improves the energy efficiency of the UAV-enabled hybrid system. © 2023 IEEE.

关键词： computation offloading mobile edge computing particle swarm optimization simulated annealing UAVs

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Joint optimization of sensing period and transmission time for energy-efficient CRSNs 11

Joint optimization of sensing period and transmission time f...

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11th International Conference on Ubiquitous information Management and Communication, IMCOM 2017

作者： Jin, Zilong Jinsung, Cho Kong, Fanhua Kim, Chang-Woo Na, Sangyeob School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Cho Dept. of Computer Science and Engineering Kyung Hee University Yongin17104 Korea Republic of Dept. of Electronics and Radio Engineering Kyung Hee University Yongin17104 Korea Republic of Dept. of Computer Science Namseoul University Cheonan31020 Korea Republic of

ISBN: (纸本)9781450348881

Cognitive radio technology can enable secondary users (SUs) to occupy licensed bands in a non-interference way. SUs perform spectrum sensing to determine the presence of primary user (PU). Spectrum sensing period and transmission time are the critical parameters for the sensing performance and the secondary throughput, respectively. In this paper, a joint optimization of sensing period and transmission time is proposed for cognitive radio sensor network (CRSNs). The joint optimization model is established by taking the network energy efficiency and interference caused by SU's traffic into consideration. By using the optimization model, we try to figure out the optimal sensing period and transmission time which can guarantee the network energy efficiency and maximize the network throughput jointly. The performance of the proposed optimization model is evaluated through a set of simulations, and the existence of the optimal sensing period and transmission time is verified. © 2017 ACM.

关键词： Sensor networks

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Optimal design of lens array for wide-viewing angle multi-view lenticular 3D displays

Optimal design of lens array for wide-viewing angle multi-vi...

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作者： Kim, Hwi Hahn, Joonku Dept. of Electronics and Information Engineering College of Science and Technology Korea University Jochiwon-eup Yeongi-gun Chungnam 339-700 Korea Republic of Dept. of Electrical and Computer Engineering Duke University Durham NC 27708 United States

ISBN: (纸本)9781617827020

In this paper, we investigate the optimal design problem of lenticular lens array show for wide viewing angle lenticular 3D display. It is shown that the use of triplet lens array enables the wide-viewing angle observation with low-cross talk. We propose the optimal design procedure of triplet lens array for lenticular 3D displays using genetic algorithm with specially devised optimization cost function.

关键词： Design

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Adaptive Predictive control using GOBF-ARX Models: An Experimental Case Study

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IFAC Proceedings Volumes 2013年第32期46卷 99-104页

作者： Muddu Madakyaru Sachin C Patwardhan Systems and Control Engineering Indian Institute of Technology Bombay Dept. of Chemical Engineering Indian Institute of Technology Bombay Powai Mumbai - 400076 India

Industrial applications of model predictive control rely mostly on linear empirical models obtained by employing time series analysis approaches. These models can quickly become obsolete and require maintenance when the operating conditions become significantly different from the design conditions. The need to generate good predictions in the face of changing operating conditions and / or plant characteristics can be fulfilled through updating the linear model parameters online. This work is aimed at the development of adaptive MPC (AMPC) scheme based on ARX models, which are parameterized using generalized orthonormal basis filters (GOBF). The proposed model structure, in addition to capturing the dynamics with respect to the manipulated inputs, facilitates modeling of stationary as well as non-stationary components of the unmeasured disturbances. The feasibility of using the proposed AMPC scheme is established by conducting experimental studies on a benchmark Heater-Mixer setup.

关键词： Orthonormal Basis Filters ARX Models Model Predictive control Adaptive control

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Indian composites industry makes progress

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Reinforced Plastics 2008年第4期52卷 26-28,30-31页

作者： Jacob, Amanda Neogi, Swati Baksi, Sangeeta Biswas, Soumitra Department of Chemical Engineering Indian Institute of Technology (IIT) Khargpur India Advanced Composites Programme Technology Information Forecasting and Assessment Council (TIFAC) Dept. of Science and Technology (Govt. of India) New Delhi India Soumitra Biswas TIFAC New Delhi India

India's biggest composites event, the International Conference and Exhibition on Reinforced Plastics (ICERP), was held in Mumbai, India, in February. The fourth in the series, this event demonstrated a big step up for the country's composites industry. Amanda Jacob reports. © 2008 Elsevier Ltd. All rights reserved.

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F-M II Model Realization of 2D Radar Based on Graph Theory Method

F-M II Model Realization of 2D Radar Based on Graph Theory M...

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International Conference on Computer and Communications (ICCC)

作者： Sheng Daoqing Wu Xudongzi Cheng Hua Liu Chang Dept. of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Dept. of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

In this paper, a new method of solving the system realization matrix based on the given transfer matrix of two-dimensional hybrid linear system is proposed. According to the two-dimensional block diagram theory and the relation between Roesser model and F-M II model, the realization matrix of F-M II model can be directly obtained from the realization matrix of Roesser state space model, which greatly simplifies the calculation of the F-M II model and makes the solution of the system matrix more flexible and conducive to the analysis and design of the system. This method is applied to radar system, and the analysis efficiency of the system will be greatly improved.

关键词： Mathematical model Radar Analytical models Numerical models Transfer functions Matrix converters Two dimensional displays

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Feeling Awareness in Interactive Differential Evolution Based Facial Image Generation

Feeling Awareness in Interactive Differential Evolution Base...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Qiangfu Zhao Cheng-Hsiung Hsieh Dept. of Computer and Information Systems The University of Aizu Dept. of Computer Science and Information Engineering Chaoyang University of Technology

ISBN: (纸本)9781467317139

In our earlier studies, we have proposed an image morphing based steganography. The basic idea is to embed a secrete image into a stego image through morphing. The stego image is a morphed image obtained from the secrete image and some other reference images. To make this method more practically useful, it is essential to make the stego image as natural as possible. For this purpose, we should define a proper feature point set (FPS) for morphing. To find a good FPS efficiently, we use interactive differential evolution (IDE) in this paper. One problem in using IDE is that, in the evolution process the human user may change his/her evaluation criterion subconsciously. This is not desirable for finding an objective evaluation function based on the generated images. To solve this problem, we investigate the effectiveness of k-NN based feeling awareness, and propose a reminder for stabilizing the "user feeling" in the evolution process. Experimental results show that the reminder is useful for reducing the chance of criterion shift. Results also show that increasing k alone may not improve the performance of the reminder for user feeling modeling.

关键词： information hiding Steganography Image morphing Interactive differential evolution Criterion shift User feeling awareness Reminder Image generation images image morphing Imagery (Psychotherapy) IDE IDE gene Feelings Image Feature Points FES gene evolution Evolution evolution evolution

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Development of new soft actuator using magnetic intelligent fluids for flexible walking robot

Development of new soft actuator using magnetic intelligent ...

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作者： Taniguchi, Hironari Miyake, Masaki Suzumori, Koichi Dept. of Electronics and Control Engineering Tsuyama National College of Tech. Okayama Japan Graduate of National Science and Technology Okayama University Okayama Japan

ISBN: (纸本)9781424474530

The purpose of my work is to develop a new soft actuator with magnetic intelligent fluids such as a magnetic fluid and a magneto-rheological fluid for flexible walking robots. For this purpose, the authors have produced two types of soft magnetic materials. One is called the magnetic fluid rubber that consists of an isoparaffin-based magnetic fluid and elastic silicone rubber. The other is called the magneto-rheological fluid rubber that consists of a polyalphaolefin-based magneto-rheological fluid and elastic silicone rubber. We have developed four types of cylindrical soft actuators using proposed soft magnetic materials. An experimental system was constructed and a response test was made using it. A Laser displacement sensor was employed to find the relationships between the magnetic flux density and the displacement of soft actuator. The experiment showed that the responsibility of soft actuator with the magnetic fluid rubber indicated the best performance. In addition, we operated four electromagnetic coils to control the direction and the displacement of soft actuator. As a result, we have succeeded in moving the tip of soft actuator like drawing a circle. We represented a first possible step towards the development of soft actuator with magnetic functional fluids for flexible walking robots. ©ICROS.

关键词： Silicones

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Sparsity-Smoothness-Aware Power Spectral Density Estimation with Application to Phased Array Weather Radar 48

Sparsity-Smoothness-Aware Power Spectral Density Estimation ...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Kuroda, Hiroki Kitahara, Daichi Yoshikawa, Eiichi Kikuchi, Hiroshi Ushio, Tomoo Nagaoka University of Technology Dept. of Information and Management Systems Engineering Japan Osaka University Division of Electrical Electronic and Infocommunications Engineering Japan Japan Aerospace Exploration Agency Aeronautical Technology Japan The University of Electro-Communications Center for Space Science and Radio Engineering Japan

ISBN: (纸本)9781728163277

In this paper, we propose a sparsity and smoothness regularized model for the estimation of nonnegative power spectral densities (PSDs) of complex-valued random processes from mixtures of realizations. The proposed model is designed to jointly estimate frequency components of the realizations and the PSDs. The PSDs are estimated by the nonnegative variable in the proposed model, which enables that the sparsity and the smoothness can be exploited via convex optimization. Numerical experiments on the phased array weather radar, which is an advanced weather radar system, show that the proposed approach achieves superior performance to the existing sparse estimation models combined with post-smoothing. © 2023 IEEE.

关键词： Power spectral density random process regularized estimation smoothness sparsity weather radar

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Deep and Spatio-Temporal Detection for Abnormal Traffic in Cloud Data Centers

Deep and Spatio-Temporal Detection for Abnormal Traffic in C...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Yuan, Haitao Wang, Shen Bi, Jing Zhang, Jia School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing University of Technology Faculty of Information Technology Beijing China Lyle School of Engineering at Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9798350337020

Current interactions of network traffic through cloud data centers have become an important process of network services. Precise and real-time detection and prediction of network traffic can assist system operators in effectively allocating resources, and assessing network performance based on actual service requirements, and analyzing network health. However, sources and distribution of network traffic are different, which makes accurate warnings of network attack traffic become a difficult problem. In recent years, neural networks have been proven to be effective in predicting time series data, particularly long short-term memory networks for capturing temporal features and convolutional methods for capturing spatial features. This work proposes a Deep Hybrid Spatio-Temporal (DHST) network method for abnormal traffic detection in cloud data centers, which combines a cooperative temporal convolutional network, an attention mechanism and a random inactivation method to capture the network traffic data's spatio-temporal features. It improves accuracy of abnormal traffic detection, and realizes classification of normal traffic and abnormal one. It achieves higher accuracy than typical detection methods when applied to a real-life dataset collected from Yahoo Webscope S5. © 2023 IEEE.

关键词： anomaly detection Deep learning network traffic spatio-temporal modeling temporal convolutional networks

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