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5th ieee international conference on Robotic computing (IRC)

作者： Suzuki, Yoshiyuki Yamaguchi, Akihiko Nojiri, Seita Watanabe, Tetsuyou Hashimoto, Koichi Tohoku Univ Grad Sch Informat Sci Sendai Miyagi Japan Kanazawa Univ Grad Sch Nat Sci & Technol Kanazawa Ishikawa Japan Kanazawa Univ Inst Sci & Engn Kanazawa Ishikawa Japan

ISBN: (纸本)9781665434164

We explore in-hand manipulation, especially pivoting, with a robot hand equipped with a contact area variable surface (CAVS) and a vision-based tactile sensor FingerVision. CAVS is a skin for robots where the surface friction coefficient passively changes according to the external force;during holding objects with a small force, the friction coefficient is low, while the friction coefficient becomes higher when increasing the holding force. FingerVision provides multimodal sensations, including force and slip distributions, and orientation of grasped objects. On our robot hand, CAVS is embedded on the surface of the fingertips, and FingerVision is installed under the CAVS skin. With this hand, we expect a gentle in-hand manipulation of objects where we properly control objects by slipping them on purpose to achieve a desired operation, however an adequate control method for such operations has been unclear. this paper focuses on the control methods of the CAVS+FingerVision hand for pivoting objects as an example of in-hand manipulation. through the empirical comparisons, we found that a vibration control of fingertips achieves the best accuracy and outperforms a simple fuzzy control, and CAVS outperforms a usual flat skin.

关键词： robot hand robotic manipulation pivoting vision-based tactile sensor variable friction

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Analysis and Improvement of Distribution System Reliability by Optimization of distributed Generation

Analysis and Improvement of Distribution System Reliability ...

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ieee international conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Molla Addisu Mossie Sadeq thamer Hlama Hayder Rahm Dakheel Al-Fayyadh Estifanos Abeje Sharew Ayodeji Olalekan Salau Charles Olawale Ogunnigbo School of Electrical and Computer Engineering Woldia Institute of Technology Woldia University Woldia Ethiopia College of Science University of Sumer Iraq Department of Computer Science College of Computer Science and Information Technology University of Sumer Dhi-Qar Iraq Faculty of Electrical and Computer Engineering Bahir Dar Institute of Technology Bahir Dar University Bahir Dar Ethiopia Department of Electrical/ElectronicEngineering Afe Babalola University Ado-Ekiti Nigeria Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Department of Mechanical/Mechatronics Engineering College of Engineering Afe Babalola University Ado-Ekiti Ekiti State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

the three components of a power system are generation, transmission, and distribution. the distribution system, which provides power to meet demand, is the main part of the power system. A measurement of the consistency and reliability of the power supply to consumers is the distribution system reliability assessment. Additionally, it offers details on the system's operation and aids in determining the expenses or losses a power outage will cause the utility and the consumer. this paper uses a variety of EEU data collected to analyze reliability and improve the Woldia distribution system. System reliability indices for the cases show that the system indices (SAIFI = 103.624 in./yr, SAIDI = 891.4559 hr/yr, CAIDI = 8.603 hr/int, ASAI = 0.8982 pu, and EENS = 4904.725 MWhr/yr) of the system is unreliable. A PSO is used to optimize the appropriate location and size for 1.2 MW of DG units, and the effectiveness of the suggested methodology is evaluated on a 15 KV outgoing Woldia University feeder. Following optimal DG allocation, the radial distribution system's reliability over the previous system is increased. the suggested method outperforms the current system, as shown by the test results, which show a 46.097% reduction in EENS, a 47.377% reduction in SAIFI, and a 47.695% reduction in SAIDI. Generally speaking, the findings show that increasing the test system's reliability requires determining the exact size and placement of distributed generation.

关键词： Photovoltaic systems Renewable energy sources Power measurement Power supplies systems operation Power system reliability distributed power generation Reliability Indexes Resource management

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Energy-Efficient Wireless sensor Networks Optimization using Deep Q-Networks for Smart Energy Applications

Energy-Efficient Wireless Sensor Networks Optimization using...

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Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Satyanarayana Nimmala Nukala Sujata Gupta P Vasanth Sena K Koteswara Chari Md Aleem Pasha Bandi Rambabu Department of CSE (Data Science) CVR College of Engineering Hyderabad India Department of Computer Engineering Technology Chaitanya Bharati Institute of Technology (CBIT) Hyderabad India Department of CSE G. Narayanamma Institute of Technology and Science Hyderabad India Department of CSE Teegala Krishna Reddy Engineering College Hyderabad India Department of Mechanical Engineering Chaitanya Bharati Institute of Technology (CBIT) Hyderabad India Department of CSE CVR College of Engineering Hyderabad India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Energy efficiency poses a significant difficulty in Wireless sensor Networks (WSNs), especially within smart energy applications like smart grids, energy monitoring, and predictive maintenance. this study presents an adaptive optimization approach based on reinforcement learning utilizing Deep Q-Networks (DQN) to improve energy efficiency in Wireless sensor Networks (WSNs) through the dynamic adjustment of transmission power and routing algorithms. the suggested model is trained and assessed utilizing the LEACH (Low-Energy Adaptive Clustering Hierarchy) dataset within a simulated NS-3 and MATLAB environment. the simulation configuration comprises 100 to 500 sensor nodes distributed inside a 100m x 100m region, each with differing energy limitations, utilizing the ieee 802.15.4(Zigbee) communication protocol. the performance evaluation is carried out under varying traffic loads and network density, contrasting the proposed DQN-based optimization with classic LEACH, GA-based clustering, and Q-learning models. the results indicate a 27.5% enhancement in network longevity relative to LEACH, a 21.8% decrease in energy consumption per node, an 18.3% advancement in packet delivery ratio, and a 16.7% reduction in end-to-end latency, hence providing dependable data transfer. the findings underscore the efficacy of reinforcement learning in prolonging the lifespan of wireless sensor networks and enhancing energy efficiency, rendering it exceptionally appropriate for practical smart energy applications, including power grid monitoring, industrial IoT, and renewable energy management. the proposed DQN-based optimization dynamically adjusts transmission power and routing strategies, resulting in significant energy savings and improved network performance

关键词： Wireless sensor networks Adaptive systems Heuristic algorithms Telecommunication traffic Routing Energy efficiency Mathematical models Smart grids Optimization Monitoring

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Field-Based High-throughput Phenotyping Using Newly Developed Proximal sensor Device 5

Field-Based High-Throughput Phenotyping Using Newly Develope...

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5th ieee international conference on Smart systems and Technologies, SST 2022

作者： Šimić, Domagoj Galić, Vlatko Spišić, Josip Mazur, Maja Ledenčan, Tatjana Zdunić, Zvonimir Agricultural Institute Osijek Department of Maize Breeding and Genetics Osijek Croatia Computer Science and Information Technology Faculty of Electrical Engineering Osijek Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

To cope with changing climate and increasing human population, agricultural production requires more data on plant status. High-throughput phenotyping represents new avenue of data collection, increasing throughput in both time and space. We developed a low-cost proximal sensing node retrieving reads at six wavelengths in red (610 and 680 nm), near infra-red (730 and 760 nm) and infrared (810 and 860 nm), intended to capture important plant reflectance indices and fluorescence signals. the reads were collected in fields of maize, barley and wheat and coupled with reads from a commercial multispectral sensing device and a handheld fluorimeter, measuring plant photosynthetic efficiency in a JIP-test framework. Reads of our sensing node were standardized by calculating vegetation indexes (VI). Strong correlations were observed between VIs retrieved from our sensor and NDVI measured by a commercial device, reaching R2 > 0.91$. Correlation analysis also showed strong link between VI810610 and primary electron transport, vanishing between VIs and higher order photosynthetic reactions. Collection of meaningful ecophysiological data facilitates plant state retrieval in scales from seconds to months (temporal throughput) with increasing spatial density (spatial throughput). Proximal sensing nodes combined with novel communication devices (Internet of things), emerging phenotyping technologies and methods (high-throughput phenotyping) and data science frameworks (machine learning) show promise in transition to Agriculture 4.0/5.0. © 2022 ieee.

关键词： Agriculture

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Object Detection and State Estimation of Autonomous Vehicles with Multi-sensor Information Fusion 5

Object Detection and State Estimation of Autonomous Vehicles...

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5th CAA international conference on Vehicular Control and Intelligence, CVCI 2021

作者： Li, Zheng Wang, Yijing Zuo, Zhiqiang School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (纸本)9781665408462

An accurate object detection and state estimation is the keystone for realizing motion decision of autonomous vehicles. Multi-sensor fusion is a reliable way to obtain sufficient object information compared with detection by only a single sensor. In this paper a two-stage fusion scheme is proposed to deal with object detection and state estimation simultaneously. three typical sensors, radar, camera and LiDAR, are studied as the data sources. Compared with the existing work, not only detection results but also state estimation accuracy are analyzed. A simulation in PanoSim is performed to verify the effectiveness of our method. the test results illustrate the output of fusion can meet the requirement of motion decision, where both overtaking and adaptive following tasks are conducted as expected. © 2021 ieee.

关键词： State estimation

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Deep Fusion of a Skewed Redundant Magnetic and Inertial sensor for Heading State Estimation in a Saturated Indoor Environment

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international JOURNAL OF SEMANTIC computing 2021年第3期15卷 313-335页

作者： Karimi, Mojtaba Babaians, Edwin Oelsch, Martin Steinbach, Eckehard Tech Univ Munich Dept Elect & Comp Engn D-80333 Munich Germany

Robust attitude and heading estimation in an indoor environment with respect to a known reference are essential components for various robotic applications. Affordable Attitude and Heading Reference systems (AHRS) are typically using low-cost solid-state MEMS-based sensors. the precision of heading estimation on such a system is typically degraded due to the encountered drift from the gyro measurements and distortions of the Earth's magnetic field sensing. this paper presents a novel approach for robust indoor heading estimation based on skewed redundant inertial and magnetic sensors. Recurrent Neural Network-based (RNN) fusion is used to perform robust heading estimation with the ability to compensate for the external magnetic field anomalies. We use our previously described correlation-based filter model for preprocessing the data and for empowering perturbation mitigation. Our experimental results show that the proposed scheme is able to successfully mitigate the anomalies in the saturated indoor environment and achieve a Root-Mean-Square Error of less than 2.5 degrees for long-term use.

关键词： Heading estimation skewed redundant RNN magnetic and inertial sensor

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Synchronous execution of program instructions in a distributed data transmission network based on FPGA

Synchronous execution of program instructions in a distribut...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Alexander A. Deev Andrei A. Kalshchikov Department of Fundamentals of Radio Engineering National Research University "MPEI" Moscow Russian Federation

the widespread use of synchronous data networks today is driving the rapid development of precision time synchronization systems such as PTP (ieee 1588). this paper describes implementations that allow to perform synchronous execution of program instructions with subnanosecond accuracy on spatially separated devices. Such solutions make it possible to implement real-time applications based on synthesizable processors such as Nios II from Intel (Altera), MicroBlaze from Xilinx (AMD), SoC (System on a Chip) integrated into FPGA chips, or even classic processors. Using of a single time scale, which synchronized with subnanosecond accuracy on all devices in network is the basis for the synchronous execution of program instructions. this paper describes in detail how to integrate a single time scale into the instruction set of microprocessors, SoCs, and processors. Finally, potential applications and options for using a single time scale for synchronous execution of instructions are discussed.

关键词： Performance evaluation Optical fibers Power engineering Service robots Real-time systems System-on-chip Synchronization

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Enhancing Wireless Network Performance with Deep Learning Based Routing Protocols

Enhancing Wireless Network Performance with Deep Learning Ba...

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Electronics and Sustainable Communication systems (ICESC), 2020 international conference on

作者： C. S. Gayathri Rajeswari Nallathambi J. Sophia Rajasekaran Eswarnn Brindha T Department of Electronics and Communication Engineering Mother Teresa college of Engineering and Technology Pudukkottai Tamil Nadu India Department of Electrical and Electronics Engineering Sri Raaja Raajan college of Engineering and Technology Karaikudi Tamil Nadu India Department of Electrical and Electronics Engineering St. Michael College of Engineering and Technology Kalayarkoil Sivagangai India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

Wireless routing plays a major role in efficiently directing the data packets from the source to destination in a distributed network environment. Since the sensor node are widely distributed often wireless networks struggle to establish an effective routing mechanism due to the challenges such as mobility of nodes, energy constraints, limited bandwidth, and signal interference. Since the nodes in WSN networks are limitedly programmed, the nodes lack to respond efficiently. To overcome these constraints, recently deep learning-based routing mechanisms are introduced to make the network respond appropriately according to the situation. Deep learning helps to program and reprogram the wireless networks based on the network traffic patterns and correlations, topology. Deep learning also plays a major role in providing valuable insights for routing decisions by extracting the relevant features from the network data. this study presents a review on the different deep learning techniques implemented in wireless network routing and how the algorithms have contributed to enhance the wireless networks' mobility, scalability, complexity, energy efficiency, security and its real-time adaptability. Finally, this study compares the accuracy of the existing deep learning algorithms and finally states the advantages, limitations and open issues.

关键词： Deep learning Wireless sensor networks Wireless networks Scalability Neural networks Routing Feature extraction Routing protocols Real-time systems Mathematical models

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Research on curve braking based on sensor fusion 5

Research on curve braking based on sensor fusion

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5th CAA international conference on Vehicular Control and Intelligence, CVCI 2021

作者： Li, Linhui Liang, Ruitian Zhang, Yifan Lian, Jing Guan, Xiaowei School of Automotive Engineering Dalian University of Technology Dalian China Hualu Zhida Technology Co. Ltd Dalian China

ISBN: (纸本)9781665408462

the stability of the braking process of the intelligent vehicle is mainly divided into two parts: the accurate selection of the braking target and the stability during a braking on curve. For the selection of braking targets, this paper uses sensor fusion to identify and fit lane lines, and establishes a road curvature estimation model, which is used to identify the target vehicle in front of the lane, thereby effectively reducing vehicle mis-braking. the emergency braking of a vehicle in a curve is prone to instability. To solve this problem, a sliding-mode controller is worked out based on the joint control of the yaw rate and the side slip angle, in order to calculate the additional yaw moment. then the additional yaw moment is converted into the braking moment of the wheels, so as to realize that the actual yaw rate and the side slip angle of the center of mass can follow the ideal value well. Finally, using Prescan, Carsim and MATLAB/Simulink for joint simulation, the results show that the proposed target vehicle recognition strategy based on sensor fusion can effectively reduce the vehicle's mis-braking on curve, and after the torque is distributed through the designed sliding mode controller, it can effectively improve the braking stability of the vehicle. © 2021 ieee.

关键词： Vehicles

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Investigation of Attacks and Methods of Protection of Wireless Networks During Authorization Using the ieee 802.1x Protocol 5

Investigation of Attacks and Methods of Protection of Wirele...

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5th international conference on Future Networks and distributed systems: the Premier conference on Smart Next Generation Networking Technologies, ICFNDS 2021

作者： Kovtsur, Maxim Minyaev, Andrey Khramtsov, Dmitrii Abramenko, Georgii Bonch-Bruevich Saint Petersburg State University of Telecommunications Saint Petersburg Russia

ISBN: (纸本)9781450387347

this article discusses the principles of the ieee 802.1x standard and presents four DoS attacks in accordance with the enterprise matrix MITRE ATT&CK for corporate networks of companies. the methods of protection against the presented attacks are determined and the ways of their implementation on the equipment of various manufacturers, such as TP-LINK, ASUS, MikroTik are investigated. © 2021 ACM.

关键词： Wi-Fi

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