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6th international conference on Intelligent computing and Optimization, ICO 2023

6th International Conference on Intelligent Computing and Op...

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6th international conference on Intelligent computing and Optimization, ICO 2023

ISBN: (纸本)9783031503269

the proceedings contain 32 papers. the special focus in this conference is on Intelligent computing and Optimization. the topics include: Machine Learning-Based Predictive Modelling of Spot-Welding Process Parameters;Robust Vehicle Speed Estimation Based on Vision sensor Using YOLOv5 and DeepSORT;automatic Alignment of Aerospace Images Based on the Search for Characteristic Points;method for Plant Leaves Square Area Estimation Based on Digital Image Analysis;digital Revolution through Computational Intelligence: Innovative Applications and Trends;compressive Sensing and Orthogonal Matching Pursuit-Based Approach for Image Compression and Reconstruction;capabilities for Digital Transformation and Sustainability in an Emerging Economy;preface;digitally-Enabled Dynamic Capabilities for Digital Transformation;Non-invasive Glucose Measurement with 940 nm sensor Using Short Wave NIR Technique;managing the Purchase-Sale Process of Digital Currencies Under Fuzzy Conditions;a Comparative Analysis of the Impacts of Traditional and Digital Billing Methods;chest X-ray Image Classification Using Convolutional Neural Network to Identify Tuberculosis;digital Wireless Mini-transduce of Plant thermoregulation;effective Fault Prediction Techniques for the Green Cloud computing Environment Applying Machine Learning to Enhance Network Management;transforming the Financial Industry through Machine and Deep Learning Innovations;MRI-Based Brain Tumor Classification Using Various Deep Learning Convolutional Networks and CNN;deciphering Handwritten Text: A Convolutional Neural Network Framework for Handwritten Character Recognition;applying Machine Learning Techniques to Forecast Demand in a South African Fast-Moving Consumer Goods Company;Digitization of Feeding Processes in Pond Aquaculture Using a Cyber-Physical System for Analyzing Monitoring Data and Transmitting Information Using LoRaWAN Technology;Rice Blast Disease Detection Using CNN Models and DCGAN.

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6th international conference on Intelligent computing and Optimization, ICO 2023

6th International Conference on Intelligent Computing and Op...

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6th international conference on Intelligent computing and Optimization, ICO 2023

ISBN: (纸本)9783031503290

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Detection and Location of Fault in Microgrid using Discrete Wavelet Transform based Technique 6

Detection and Location of Fault in Microgrid using Discrete ...

引用

ieee 6th international conference on Condition Assessment Techniques in Electrical systems (ieee CATCON)

作者： Banerjee, Sannistha Bhowmik, Partha Sarathee Bohre, Aashish Kumar Natl Inst Technol Dept Elect Engn Durgapur India

ISBN: (纸本)9781665473804

In this paper a new wavelet transform based method for detection and identification of fault location has been proposed in microgrid with distributed Generation (DG). Fault detection is challenging for this DG system due to the bi-directional power flow and the issue of fault current which consists of source current and DG current both during fault. the wavelet transform analysis determines the content of frequency with time simultaneously of nonstationary transient signal. the proposed method evaluates the approximate and detail wavelet coefficients at different level of frequency band by Discrete Wavelet Transform (DWT) for detection of the fault reliably. this process starts with tracking the signal of phase voltages at terminal of DG, Point of Common Coupling (PCC) and utility side and by DWT decomposition each signal will be processed. the energy of detail DWT coefficients of each faulty signal considering both the symmetrical and unsymmetrical fault have also been computed. this energy content has been analyzed further to identify the location of the fault. this unique and simple technique has been verified successfully using an existing microgrid network in West Bengal, India for unbalanced and balanced fault detection and location of fault.

关键词： discrete wavelet transform distributed generation fault microgrid protection

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Multi-agent and Reinforcement Learning Schemes for Demand Response Estimation in distributed Microgrids 6

Multi-agent and Reinforcement Learning Schemes for Demand Re...

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6th international conference on Energy Conservation and Efficiency, ICECE 2023

作者： Ikram, Muhammad Ahmed, Salman Marwat, Safdar Nawaz Khan Nasir, Muhammad University of Engineering and Technology Dept. of Computer Systems Engineering Peshawar Pakistan Allama Iqbal Open University Department of Physics Islamabad Pakistan

ISBN: (纸本)9798350332193

Demand response (DR) is an approach that encourages consumers to shape consumption patterns in peak demands for the reliability of the power system and cost minimization. the optimal DR scheme has not only leverages the distribution system operators (DSOs) but also the consumers in the energy network. this paper introduced a multi-agent coordination control and reinforcement learning approach for optimal DR management. Each microgrid is considered an agent for the state and action estimation in the smart grid and programmed rewards and incentive plans. In this regard, the Multi-agent Markov game (MAMG) is utilized for the state and action. At the same time, the reward is articulated through reinforcement learning deep Q-network (DQN) and deep deterministic policy gradient (DDPG) schemes. the proposed DR model also encourages consumer participation for long-term incentivized benefits through integrating battery energy storage systems (BESS) in the SG network. the reliability of DQN and DDPG schemes is demonstrated and observed that the dynamically changing electricity cost is reduced by 19.86%. Moreover, the controllability of complex microgrids is achieved with limited control information to ensure the integrity and reliability of the network. the proposed schemes were simulated and evaluated in MATLAB and Python (PyCharm IDE) environments. © 2023 ieee.

关键词： Smart power grids

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Batterfly: Battery-Free Daily Living Activity Recognition System through distributed Execution over Energy Harvesting Analog PIR sensors 17

Batterfly: Battery-Free Daily Living Activity Recognition Sy...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Stirapongsasuti, Sopicha Misaki, Shinya Matsui, Tomokazu Suwa, Hirohiko Yasumoto, Keiichi Nara Inst Sci & Technol Ikoma Nara 6300192 Japan

ISBN: (纸本)9781665439299

In recent years, the use of energy harvesting (EH) sensors has led to the proposal of activity sensing systems that are easy to install and do not require maintenance such as battery replacement. In this study, we aim to construct a system that can not only sense but also recognize activities of daily living (ADLs) using only power generated by EH sensors. To achieve this goal, in this paper, we propose a fully EH-based ADL recognition system called Batterfly, which consists of EH analog PIR sensor nodes that can operate with indoor light, continuously senses human movement, and recognizes daily activities through machine learning. We applied the distributed execution method of the activity recognition model with five sensor nodes to five types of activities by five participants, and found that the system could recognize them with an average accuracy of 63.59%, comparable to the performance of the centralized model running on a gateway.

关键词： wireless sensor network energy harvesting distributed computing

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A live context model for semantic reasoning in IoT applications

A live context model for semantic reasoning in IoT applicati...

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20th ieee international conference on Pervasive computing and Communications (ieee PerCom)

作者： Del Gaudio, Daniel Ariguib, Boshra Bartenbach, Arne Solakis, Georgios Univ Stuttgart Inst Parallel & Distributed Syst Stuttgart Germany

ISBN: (纸本)9781665416474

Nowadays, the rapid increase of IoT devices and the corresponding high volume of produced data leads to a higher complexity of data analysis and context reasoning tasks. In the IoT, monitoring the context of an application, i.e., the involved devices sensors and actuators as well as their surroundings, is of vital importance. Ontologies can be used to model such context, nevertheless, they usually do not consider live information like sensor values and monitoring data. Yet, this is necessary to capture the full context of an IoT application. In this paper, we propose a context model that includes the current state of devices, composing their static information, such as device names, and live information gathered from monitoring systems and sensors. We further propose an extendable architecture to enrich the ontology with static and live data. Our approach can be extended by integrating different data sources and extending the context model.

关键词： Internet of things context modeling ontologies

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6th international conference on Intelligent computing and Optimization, ICO 2023

6th International Conference on Intelligent Computing and Op...

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6th international conference on Intelligent computing and Optimization, ICO 2023

ISBN: (纸本)9783031362453

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Design of Cable Temperature Monitoring System Based on RFID 6

Design of Cable Temperature Monitoring System Based on RFID

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6th international conference on HVDC, HVDC 2024

作者： Zhumabieke, Abai Lan, Chenglong New Power System Technology Research Institute State Grid Xinjiang Electric Power Research Institute Urumqi China

ISBN: (纸本)9798350387759

For the stable operation of the power grid, temperature is one of the important criteria for considering its working performance. Moreover, accidents often occur in the joints of transmission lines, cables, busbars and other equipment. these parts are in a high-voltage working environment for a long time. the joint resistance is large, and the degree of heating will be more serious than other operating parts of the power grid, which will bring huge impact and economic losses to residents ' lives and normal work of the factory. With the continuous improvement of the construction and automation level of the new intelligent power network, the traditional manual temperature measurement operation has not adapted to the development and construction of the new power network. therefore, it is necessary to introduce more advanced and reliable technology to realize automatic monitoring, which also plays an important role in the development of the smart grid. Considering that most of the actual power grid cable temperature measurement points are laid with active sensors, higher requirements are put forward for the insulation performance of the equipment, and the cable transmission temperature measurement method cannot cope with the more complex, dense and narrow working environment. In order to deal with the above problems, this paper proposes a design of cable temperature monitoring system based on RFID technology, which can realize the transmission and reception of wireless radio frequency signals. the overall design is to attach the temperature sensor tag to the cable joint and the key temperature measurement point. the temperature data measured by the tag in real time is transmitted back to the reader system through wireless transmission. this paper focuses on the introduction of readers and electronic tags, and explores the feasibility and working stability of this technology in cable temperature measurement through experimental methods. © 2024 ieee.

关键词： electronic tag online temperature measurement reader RFID temperature sensor

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the Parallelized Cuckoo Filter for Cold Data Representation 23

The Parallelized Cuckoo Filter for Cold Data Representation

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23rd ieee international conference on High Performance computing and Communications, 7th ieee international conference on Data Science and systems, 19th ieee international conference on Smart City and 7th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Sun, Bowen Luo, Lailong Li, Shangsen Chen, Yingwen Guo, Deke College of Computer National University of Defense Technology China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China College of Computer National University of Defense Technology National Lab for Parallel and Distributed Processing China

ISBN: (纸本)9781665494571

Cold data contributes a large portion of the big data today and is usually stored in secondary storage. Various sketch data structures are implemented to represent the stored elements and provide constant-time membership queries. Considering the large volume and infrequent access of cold data, we envision three rationales of cold data representation: 1) parallelized insertion, 2) accurate representation, and 3) constant-time query/deletion. the existing sketches, however, fail to achieve these rationales simultaneously. To this end, we propose a novel sketch named Parallelized cuckoo Filter (PCF) in this paper. PCF divides the standard cuckoo filter into multiple homogenous segments. An additional hash function is introduced to assign an element to a segment. the element will be inserted into the selected segment. With such a design, element insertions in PCF can be naturally parallelized. Besides, as a variant of the cuckoo filter, PCF naturally realizes the accurate representation and constant-time query/deletion requirements. Comprehensive experiments further indicate that PCF achieves the three rationales simultaneously. © 2021 ieee.

关键词： Hash functions Smart cities Big Data Data structures Standards

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2023 19th international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

2023 19th International Conference on Wireless and Mobile Co...

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19th ieee international conference on Wireless and Mobile computing, Networking and Communications, WiMob 2023

ISBN: (纸本)9798350336672

the proceedings contain 81 papers. the topics discussed include: outage performance of IRS-assisted underwater optical wireless communication systems over combined channel model;sensor-based wastewater monitoring framework to detect COVID-19;deep learning assisted channel estimation for cell-free distributed MIMO networks;multi-agent Q-learning for drone base stations;RF fingerprint-based identity verification in the presence of an sei mimicking adversary;analyzing the feasibility of privacy-respecting automated tracking of devices fleeing a burglary;security implications of a satellite communication device on wireless networks using Pentesting;deep learning assisted quality ranking for list decoding of videos subject to transmission errors;robotaxis as computing clusters: a stochastic modeling approach;chained estimation for data reduction-driven routing in wireless sensor networks;lightweight group pre-handover authentication scheme for aviation 5g air-to-ground networks;learning to detect wireless spectrum occupancy using clustering approaches;smartphone camera as a diagnostic tool for detection of pulse rate and blood oxygen concentration;density-aware reinforcement learning to optimize energy efficiency in UAV-assisted networks;area under time series transformation for home appliance classification;and a novel single grant-based uplink scheme for high throughput and reliable low latency communication.

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