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An Improved and Efficient Technique for detecting Bengali Fake News using Machine Learning Algorithms 6

An Improved and Efficient Technique for detecting Bengali Fa...

引用

6th international conference on computing, Communication, control and automation, ICCUBEA 2022

作者： Ali, Md. Akkas Matubber, Md. Liakot Sharma, Vandana Balamurugan, B. School of Computing Science and Engineering Galgotias University U.P Greater Noida India Bangabandhu Sheikh Mujibur Rahman Science and Technology University Dept. of Cse Gopalganj Bangladesh

ISBN: (纸本)9781665484510

Fake news is appearing in the news a number of Business, Communities, Political and others reasons and being common in the air world. Humans can be infected it is easy with these false stories of the words which the product has the largest result in a non-Internet environment. thus, interest in research in this area arose. Extensive research done for the discovery of false stories for English News but few in the Bangla language. We have done a job showing the feasibility study of Bangla's false news from the social media still needs lot of attention. We have used a variety of feature extraction methods and Machine Learning Algorithms for detecting Bangla News which are treated as Fake. We have implemented our proposed system by using the Python programming. Finally, we have gained the best result that is 98.08% of accuracy. © 2022 IEEE.

关键词： Learning algorithms

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Robust control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

引用

25th IEEE international conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. this paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Equivalent Impedance Modeling of LCC-HVDC control System Based on Transfer Function Method 6

Equivalent Impedance Modeling of LCC-HVDC Control System Bas...

引用

6th international conference on Energy, electrical and Power engineering, CEEPE 2023

作者： Su, Yinsheng Cao, Runbin Xin, Qingming Xie, Huifan Liu, Hongtao Huang, Weihuang Power Dispatching Control Center China Southern Power Grid Guangzhou510663 China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

ISBN: (纸本)9798350348279

Aiming at the dc side resonance problem of line commutated converter based high-voltage dc transmission (LCC-HVDC) system, considering the effect of DC control system, an impedance modeling method of control system based on transfer function is proposed. the impedance model can be used to analyze the damping effects of constant current controller, constant voltage controller and constant extinction angle controller at different frequencies. Finally, the proposed method is applied to Xing 'an LCC-HVDC project. the results confirm that the constant current control at the rectifier side has resonance risk near a specific frequency, which verifies the effectiveness of the proposed modeling method for the assessment of DC control resonance risk. the influence of different measurement delay and filtering on impedance is analyzed, which can be used for the design and verification of LCC-HVDC control system. © 2023 IEEE.

关键词： Transfer functions

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Exploring the Transformative Convergence of IoT and Fog computing for Healthcare, Agriculture, Urbanization, and Transportation 6

Exploring the Transformative Convergence of IoT and Fog Comp...

引用

6th international conference on Recent Trends in Advance computing, ICRTAC 2023

作者： Suresh, Kotari Humera Khanam, M. S. V. University College of Engineering Department of Computer Science and Engineering Tirupati India

ISBN: (纸本)9798350394702

the integration of IoT and fog computing technologies has the potential to revolutionize a number of sectors, including healthcare, agriculture, urbanization, and transportation. Real-time human health monitoring, sensor-generated bio-signals, and wireless communication protocols enable effective decision-making, medication management, and diagnostics in the healthcare industry while protecting sensitive medical data. Fog computing and Internet of things solutions for agriculture improve production management and pest control using wireless sensor networks, giving farmers the most recent data on the state of the environment, the health of their crops, and pest activity. Fog computing and the IoT provide sustainable growth and better urban services, resource allocation, and citizen experiences in smart city efforts, solving difficulties brought on by expanding urban colonies. Fog computing and the IoT also benefit transportation systems, particularly through the use of vehicular ad hoc networks (VANETs), which improve driving experiences, traffic efficiency, and traffic forecasting, ultimately resulting in increased safety, fewer accidents, and better overall infrastructure for transportation. By utilizing real-time data analytics, connectivity, and intelligent decision-making, the convergence of fog computing and IoT presents a significant opportunity to address pressing issues in healthcare, agriculture, urbanization, and transportation. this will help to create a future that is more effective, sustainable, and interconnected across many industries. © 2023 IEEE.

关键词： Fog computing

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Research on Positioning of Permanent Magnet Maglev Trains Based on Weighted Adaptive Kalman Information Fusion 1

引用

6th international conference on electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Xu, Yiwei Fan, Kuangang Hu, Qian School of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou341000 China Key Laboratory of Magnetic Levitation Technology in Jiangxi Province Ganzhou341000 China Ganjiang Innovation Academy Chinese Academy of Sciences Ganzhou341000 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

In this paper, an improved adaptive Kalman fusion method is proposed to solve the problems of low accuracy, poor interference immunity and stability when using a single sensor to localize a suspended permanent magnetic levitation train in a practical situation. the measurement data from three sensors are fused in the first layer by weighted adaptive Kalman filtering (WKF). then, the measurements and the positioning data from the Global Navigation Satellite System (GNSS) are fused in the second layer using recursive weighted least squares (RW) to achieve highly accurate positioning of the levitated permanent magnet maglev train. the experimental results of WKF-RW algorithm improve the positioning accuracy by 51.79% and 32.5% compared with the conventional Kalman (KF) and WKF, respectively, which effectively improves the positioning accuracy and robustness of the permanent magnetically levitated trains and can be better applied to the real environment. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Permanent magnets

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Fault detection method of power user electric energy data acquisition link based on expert system 6

Fault detection method of power user electric energy data ac...

引用

6th IEEE international conference on automation, Electronics and electrical engineering, AUTEEE 2023

作者： Ma, Kun Ding, Jianshun Ji, Aiqiong Li, Shuangshuang Jiang, Xinyue Gu, Li He, Jingsong State Grid Anhui Electric Power Company State Grid Anhui Marketing Service Center Hefei China University of Science and Technology of China School of Microelectronics Hefei China University of Science and Technology of China School of Information Science and Technology Hefei China

ISBN: (纸本)9798350305623

Power user electric energy data acquire system is one of the indispensable key infrastructures in modern society, and its reliability and safety are very important for the normal operation of society. Effective monitoring and data transmission of power user electric energy data are key factors to ensure the stability of data acquire system. In this paper, an expert system based on message detection of power user electric energy data is proposed, which aims to identify errors and locate faults through full link messages, thus improving the reliability and security of power user electric energy data. First of all, we collect the data of power user electric energy data messages from various sources and preprocess the data. then, based on Transformer algorithm, we developed data verification algorithm and anomaly detection technology, and introduced expert rules and logic check to identify unreasonable, wrong or abnormal data points, so as to locate faults. Experiments show that the expert system proposed in this paper can effectively identify errors in message information and locate faults. © 2023 IEEE.

关键词： anomaly detection data verification expert system Power user electric energy data reliability

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Comparative Analysis Between Fuzzy-based Sensored and Back Electromotive Force Observer based Sensorless Methods 6

Comparative Analysis Between Fuzzy-based Sensored and Back E...

引用

6th Parul international conference on engineering and Technology, PICET 2024

作者： Desai, Jigneshkumar P. Electrical Engineering Department of U V Patel College of Engineering Ganpat University Mehsana India

ISBN: (纸本)9798350369748

this paper presents a comparative analysis of two prominent methods for motor control which is the fuzzy-based sensor control method and the current-controlled sensorless control method. the fuzzy-based sensor control method utilizes sensor feedback, commutation logic and fuzzy logic control to achieve precise motor operation. In contrast, sensorless control method estimates the rotor position using motor currents and voltages to eliminates the need for physical sensors, reducing cost and complexity. the analysis delves into the strengths and weaknesses of each approach, comparing their performance in terms of accuracy, robustness, computational complexity, and cost on BLDC motor. Two important case studies, constant speed operation with increasing torque and vice versa is simulated. the findings of this comparative analysis shows that sensorless control have found difficulty in start form standstill while sensorless is not responding satisfactory under constant torque with sudden lower down the speed. In totality, sensorless control is good performer in both the mode of operation requirement with limitation of estimation error at sudden variation. © 2024 IEEE.

关键词： Sensorless control

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Bus Load Forecasting Based on K-means and Long Short-Term Memory Networks 6

Bus Load Forecasting Based on K-means and Long Short-Term Me...

引用

6th Asia conference on Energy and electrical engineering, ACEEE 2023

作者： Zhou, Juan Cheng, Tao Huang, Anping Chao, Zhu Lv, Ji Ding, Min Dongguan Power Supply Bureau Guangdong Power Grid Co. Ltd Dongguan China Guangdong Power Grid Co. Ltd Power Dispatching Control Center Guangzhou China China University of Geosciences School of Automation Wuhan China

ISBN: (纸本)9798350312690

Bus load forecasting is essential for power system generation planning and dispatching operations. To improve the accuracy of bus load prediction, this paper proposes a bus load prediction method based on principal component analysis, K-means clustering, and long short-Term memory networks. Firstly, the bus load is pre-processed by denoising and normalization. then, the load characteristics and the correlation of numerous influencing factors with the daily load are analyzed. Principal component analysis is performed on the multidimensional features to obtain linearly uncorrelated new features. Finally, K-means clustering of historical loads by feature observations is performed, and different LSTM models are constructed for each subset for prediction. the experimental results show that the proposed hybrid prediction method has better performance. © 2023 IEEE.

关键词： Principal component analysis

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Constructing a Medical Domain Functional Knowledge Graph with Large Language Models 6

Constructing a Medical Domain Functional Knowledge Graph wit...

引用

6th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2024

作者： Ji, Lintian Du, Shuxin Qiu, Yi Xu, Hongyi Guo, Xiaorui School of Engineering Huzhou University Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems Huzhou China School of Engineering Huzhou University Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems Huzhou China

ISBN: (纸本)9798350374315

the integration of medicine and artificial intelligence is creating novel opportunities to gather, analyze, and generate groundbreaking medical insights from the vast expanse of medical literature. Although these advancements hold great promise, difficulties including manual annotation and precise data retrieval, and transparency persist. Advanced natural language processing (NLP) techniques and large language models (LLMs) have shown potential in addressing these issues. this paper introduces the Medical Knowledge Graph (MedKG), a comprehensive and multidisciplinary medical knowledge graph. By utilizing advanced NLP algorithms, MedKG extracts millions of entities and converts them into triples from a corpus of superior medical research papers published over the last decade. It categorizes unstructured medical information into nine distinct tags, including disease names, treatments, diagnoses, symptoms, genetics, cellular structures of diseases, patient data, medical procedures, and treatment applications, while seamlessly integrating the digital object identifier (DOI) of each paper. As the latest structured database of medical knowledge, MedKG serves as a powerful tool for accelerating medical research and lays the groundwork for constructing a more extensive medical knowledge graph using full-text medical articles. Moreover, our research establishes a foundation for practical knowledge management systems based on text mining, applicable not only to complex medical systems but also to other professional domains. © 2024 IEEE.

关键词： Knowledge graph

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Design of arc welding robot workstation with dual station detection based on vision 6

Design of arc welding robot workstation with dual station de...

引用

6th international conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2024

作者： Xu, Hongliang Liu, Fukai Liu, Fuqiang Li, Yan College of Electrical Engineering Changchun Technical University of Automobile Changchun China College of Intelligent Manufacturing Industry Changchun Technical University of Automobile Changchun China Institute China Faw Group Corporation Changchun China College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798331541699

At present, commonly used arc welding robot workstations mainly include three working surfaces: loading, welding, and unloading during welding operations. the process flow is as follows: the handling robot clamps the weldment for loading, the fixture fixes the weldment, the arc welding robot welds the weldment, and the handling robot clamps the weldment for unloading. the quality of weld seam is mainly determined by the precision of equipment such as positioner, fixtures, and arc welding robot. the welding quality of the weld seam is determined by the pass rate of the sampling samples. this testing method cannot obtain the true product pass rate, nor can it timely remove unqualified products for necessary repairs. Based on this situation, we have designed a arc welding robot workstation with dual station detection based on vision in this paper, which solves the problems of weld seam tracking and post weld seam quality inspection, synchronization of welding robots and handling robots, and welding and inspection of all welds in the flat welding position, achieving the effect of improving quality and efficiency. © 2024 IEEE.

关键词： Inspection

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