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Multi-Speed DVS Algorithms for Periodic Tasks with Non-Preemptible Sections

Multi-Speed DVS Algorithms for Periodic Tasks with Non-Preem...

引用

ieee international conference on Embedded and Real-Time computing systems and Applications (RTCSA)

作者： Jaewoo Lee Kern Koh Chang-Gun Lee School of Computer Science and Engineering Seoul National University Seoul South Korea

Reducing energy consumption is important for mobile embedded systems and one of its solutions is dynamic voltage scaling (DVS). In this paper, we examine how to achieve further energy saving for periodic real-time tasks with non-preemptible sections on EDF algorithm by using DVS. Previous algorithms use two speed levels to deal with run-time blocking situation. However, this paper proposes a multi-speed algorithm that exploits various speed levels depending on specific blocking situation to minimize energy consumption. Moreover, it also presents an enhanced multi-speed algorithm that further reduces the energy dissipation by dropping the speed level early and considering only remaining blocking time to compute a lower speed. We induced feasibility conditions for our algorithms and proved them. the experiments show that proposed algorithms achieve up to 70.8% energy saving compared to previous algorithms.

关键词： Voltage control Energy consumption Dynamic voltage scaling Scheduling algorithm Resource management Medical services Embedded system Runtime Energy efficiency Clocks

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Brain-LEGO Interactive control system Based on SSVEP-BCI

Brain-LEGO Interactive Control System Based on SSVEP-BCI

引用

ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Fangzhou Ru Shiguang Wen Jingying Bi Yongzhao Wen Jing Liu Qi Wu Lu Han Fei Wang Faculty of Robot Science and Engineering Northeastern University Shenyang China College of Information Science and Engineering Northeastern University Shenyang China LiaoNing Disabled Persons' Service Center Shenyang China

To improve the therapeutic effect for children and adolescents with learning disabilities, this paper developed a brain-Legointeractive(BLI) control system. Based on LEGO therapy, the system uses the analysis of EEG signals to control the movement of LEGO robots, enhancing patient engagement and personalized treatment effects. the experiment collects EEG data from four subjects and uses Canonical Correlation Analysis(CCA) to filter the signals spatially. Fast Fourier Transform(FFT) is then used to extract frequency domain features, which are decoded using Fisher Linear Discriminant Analysis (FLDA) to achieve motion control of the LEGO robot. Based on this foundation, this paper conducts an offline analysis to study the influence of the number and location of electrodes and the length of stimulus time on the performance of BLI, with the goal of exploring the low cost and portability of the system. Additionally, an online experiment is conducted to assess its performance in a practical setting. the experimental results showed that using three channels Oz, 01, and O2, and controlling the stimulus duration between 1.5s-2.5s, a good performance was achieved. the accuracy can both reach over 90%, and the information transfer rate can reach over 23 bits/min. the online evaluation results showed an average accuracy of 88.61% and an information transfer rate of 23.29 bits/min, indicating the feasibility of the brain-LEGO interactive control system.

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Optimal Time and Power Allocation in Full-Duplex Wireless-Powered Cognitive Radio Networks

Optimal Time and Power Allocation in Full-Duplex Wireless-Po...

引用

ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Zhenyu Feng Ming Su Meihua Zhou Zhixin Liu School of Electrical Engineering Yanshan University Qinhuangdao China Training Center of Liren College Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao Hebei Province China

In this paper, we integrate wireless powered communication networks (WPCNs) with cognitive radio networks (CRNs) in order to develop wireless powered CRNs (WP-CRNs). the hybrid access point (HAP) is used to broadcast radio-frequency signals to the devices at the downlink stage, and to receive information from these devices. the HAP has two antennas to achieve full-duplex: one is for downlink wireless power transfer and the other is for receiving uplink information transmission from the users simultaneously in the uplink. In the underlay paradigms. the SUs can harvest energy to transmit data when the interference to primary users (PUs) does not exceed a tolerable threshold. To tackle the above network issues, an optimal resource allocation method is proposed to maximize the secondary system uplink throughput. the optimization problem with respect to time and power allocation is formulated including the constraint of energy causality and interference level. the non-convex problem is transformed into an equivalent convex optimization problem, then the joint optimal power and time allocation (JOPTA) algorithm is presented to determine the optimal solutions. the effectiveness of the proposed algorithm is verified in the simulations.

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Dimension Reduction for Dynamic Analysis of Gene Expression Data Using Variational Autoencoder

Dimension Reduction for Dynamic Analysis of Gene Expression ...

引用

ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Shuai Yuan Shipeng Chen Yongliang Yang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning China

Single-cell RNA sequencing technology captures gene expression at the whole-genome scale and single-cell level in many cells. thus, the cellular states during a physiological process would be captured in detail. these data provide new opportunities and challenges for systems biology. Previously, the models in systems biology dealt with the dynamics of specific signaling pathways. However, it is almost impossible to directly model the dynamics of the whole genome due to the ultrahigh dimensionality of the data. Here, to model its gene regulatory dynamics, the dimensionality of the whole genome was reduced significantly using the latent space of a variational autoencoder, a generative deep learning model. In the low-dimensional latent space, an ordinary differentiation equation (ODE) system has been established to analyze the dynamic characteristics of the whole genome system. To demonstrate the effectiveness of this method, we generated a low-dimensional representation of a systems biology model we previously developed. the variational autoencoder reduced the dimension from 13 to 2 in latent space. An ODE model was developed to analyze the dynamics of this two-dimensional system. the results indicated that the 2-dimensional model captured the essence of the original systems biology model.

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A Cloud-Edge-Based Multi-Label Learning and Fast Clustering Method for Emerging New PV Faults

A Cloud-Edge-Based Multi-Label Learning and Fast Clustering ...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Qi Liu Bo Yang Yuxiang Liu Kai Ma Xinping Guan Department of Automation Ministry of Education Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Electrical Engineering Yanshan University Qinhuangdao China

Aiming at accurate identification of emerging new faults in PV systems, a novel PV fault diagnosis framework based on cloud-edge collaboration is designed. Model updates are deployed on the cloud servers, while real-time diagnosis is implemented at the edge devices. A multi-label learning model is developed to extract fault features efficiently, and a threshold scheme is further designed for feature enhancement. the obtained features are processed by K-Means clustering and the One-Class Support Vector Machine (OCSVM) methods, which can accurately diagnose existing types and identify unknown faults. For analysis and demonstration, the Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) methods are used for dimensionality reduction and visualization. Numerical results validate the effectiveness of the proposed method.

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Smart Supply Chain Management with Attribute-Based Encryption Access control

Smart Supply Chain Management with Attribute-Based Encryptio...

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ieee Annual computing and Communication Workshop and conference (CCWC)

作者： Habeeb Shittu Mahmoud Nabil Department of Electrical and Computer Engineering University of North Carolina A&T NC USA

the traditional supply chain management process is becoming more automated with the use of cutting-edge blockchain technologies. this helps in reducing the time taken for various processes and also helps in reducing the overall cost. In this paper, we developed a framework for tracking the progress of the supply chain process. the framework uses a variety of technologies to track the status and the progress of products in transit. Raspberry Pi 400 is used to track the progress of products at each chain level using Radio-frequency Identification (RFID) tags as well as other sensors. the tracking data collected by the Raspberry Pi is stored on the blockchain. A decentralized storage network (DSN) is used to store the encryption of Intellectual Property (IP) data (e.g., blueprints, design choices at each production stage, etc). Attribute-based encryption is used to allow access to the data only to authorized stakeholders who have the appropriate attributes. We leverage smart contracts and *** to develop a decentralized application (DApp) for monitoring the supply chain process. the DApp is hosted on the decentralized Ethereum platform, which provides security and transparency for all transactions. Our security analysis demonstrates that the system is secure against data theft and the results obtained from our experiments show that our proposed framework is scalable and efficient.

关键词： Access control Supply chain management Costs Supply chains Smart contracts Sensor phenomena and characterization Decentralized applications

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Mechatronic design and monitoring of a tuned mass damper in structural vibrations

Mechatronic design and monitoring of a tuned mass damper in ...

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ieee Annual computing and Communication Workshop and conference (CCWC)

作者： Jose Luis Nizama-Mallqui Evelin Ruth Mayta-Mercado Ivan Enrique Sarmiento-Ñaupa Albert Jorddy Valenzuela-Inga Juan Gabriel Benito-Zuñiga Lizbett N. Mantari-Ramos Giovene Perez-Campomanes Department of Civil Engineering Universidad Continental Huancayo Peru Department of Mechatronic Engineering Universidad Continental Huancayo Peru

the implementation of passive systems is gaining relevance due to the seismic vulnerability of high-rise buildings in several countries around the world, since they help structures to dissipate external loads, providing stiffness and damping against dynamic earthquake loads. this research aims to improve the dynamic response of the structure by implementing the tuned mass damper (TMD) for 10, 15 and 30-story buildings through engineering software and simulations with a MPU 6050 Gyroscope sensor, to obtain the seismic acceleration over time. An improvement of the inelastic drift in the X direction of up to 22.78% was obtained in the 15-story building, for the basal shear in the X direction was improved by 17.49% in the 10-story building and an improvement of the fundamental period of up to 10.55% in the 30-story building. Finally, the incorporation of the TMD as a seismic dissipator for a passive lateral displacement control system could show the reduction of the inelastic drifts of each floor and basal shear in the buildings, seeking to generate earthquake protection to reduce the damaging impacts produced by the presence of the earthquake, being more favorable for mid-rise buildings; likewise, the gyroscopic sensor yielded efficient results of electronic and mechanical design since the signals received showed that the mid-rise buildings reflect a more stable behavior.

关键词： Vibrations Visualization Displacement control Buildings Earthquakes Shock absorbers Software

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An Efficient Flow control Approach for SDN-Based Network threat Detection and Migration Using Support Vector Machine

An Efficient Flow Control Approach for SDN-Based Network Thr...

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ieee international conference on e-Business engineering (ICEBE)

作者： Ping Wang Kuo-Ming Chao Hsiao-Chung Lin Wen-Hui Lin Chi-Chun Lo Department of Information Management Kun Shan University Tainan Taiwan Professor of Engineering and Computing Coventry University UK Institute of Information Management National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781509061204

Most existing approaches for solving the network threat problems focus on the specific security mechanisms, for example, network intrusion detection system (NIDS) detection, firewall configuration, rather than on flow management approaches to defend network threats with an SDN (Software Defined Networking) architecture. Accordingly, this study proposes an improved behaviour-based SVM (support vector machine) with learning algorithm for use in the security monitoring system (SMS) to categorize network threats for network intrusion detection system. the model also adopted the ID3 decision tree theory to outrank raw features and determine the most qualified features to train support vector classifier (SVC) considering the overall detection precision rate of experiments which speeds up the learning of normal and intrusive patterns and and increases the accuracy of detecting intrusion. By using sFlow collector and analyzer associated with sFlow-RT toolset, the experimental results proved that the SMS enables a defender to classify the network threats with defence strategies and defend network threats.

关键词： Support vector machines Feature extraction Intrusion detection Classification algorithms Decision trees Static VAr compensators

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Transient Frequency Coordination Support Method Considering Multiple HVDC Power Modulations and Flexible Load Regulation

Transient Frequency Coordination Support Method Considering ...

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ieee international conference on Power and Energy systems (ICPES)

作者： Changyong Chen Peng Liu Yanfeng Gou Yi Hu Jinglin Luo China Energy Construction Group International Engineering Co. Ltd. Beijing China China Gezhouba Group Overseas Investment Co. Ltd. Beijing China National Intellectual Property Administration Patent Examination Cooperation Sichuan Center Chengdu China School of Electrical and Electronic Information Xihua University Chengdu China

In response to the modern power grid with multiple HVDC injections, extractions, and flexible loads, this paper proposes a transient frequency coordination support method based on wide-area measurement technology. the method first linearizes the power increment equations for each node in the power grid, establishing a system state equation based on wide-area measurement data after disturbance. then, using this equation, the paper constructs a frequency dynamic analysis model for the power grid, considering both HVDC power modulation and flexible load regulation. By taking into account the impact of different control schemes on the power flow safety, an optimization model for transient frequency coordination control is constructed. Finally, through solving the optimization model, the paper presents a transient frequency coordination support strategy for emergency situations involving both multiple HVDC power modulations and flexible load regulations. the proposed method is validated using the improved ieee 50-generator system, and the results and control effects are compared and analyzed, demonstrating the correctness and effectiveness of the proposed approach.

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Path Tracking control for Helical Microrobots Based on Fusion of Geometric and Model-Free Methods

Path Tracking Control for Helical Microrobots Based on Fusio...

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ieee international conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Shihao Zhong Huaping Wang Qing Shi Yaozhen Hou Yukang Qiu Tao Sun Qiang Huang Toshio Fukuda School of Medical Technology Beijing Institute of Technology Beijing China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

Helical micron-sized robots driven by magnetic fields have garnered significant interest, particularly in the field of tracking control. However, at the microscale, time-varying uncertain perturbations in both the environment and electromagnetic system can cause these robots to deviate from their preset state. Here, we propose a novel control method that combines geometric and model-free controllers in a complementary manner to achieve accurate path-tracking of a helical microrobot on underwater unstructured surfaces. the geometric controller acts as a feedforward controller handling path information and formulating guidance law, while the model-free controller responds directly to the lateral error. To compensate for unmodeled nonlinear dynamics and unknown disturbances and achieve system dynamic linearization, we employ an extended state observer. To validate the proposed method and determine suitable ranges for input parameters of the controllers, simulations were carried out. the effectiveness of our path-tracking control method is validated through experimental results. the control technique provides an initial investigation into addressing the effects of uncertainties and perturbation on the control capabilities of magnetic microrobots.

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