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检索条件"任意字段=5th IEEE International Conference on Distributed Computing in Sensor Systems"

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Enhancing Machine Learning-Based Webpages Phishing Detection with Heterogeneous distributed Ensemble Feature Selection

Enhancing Machine Learning-Based Webpages Phishing Detection...

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

作者： Bamidele M. Olukoya Emmanuel Tunbosun Aderemi Prisca O. Olawoye Taiwo Olatunde Emmanuel Oluwatobi Asani Sodipo Q.B Department of Computing & Information Science Bamidele Olumilua University of Education Science and Technology Ikere Ekiti-State Nigeria Department of Computer Science Landmark University Omu-Aran Kwara State Nigeria Department of Computer Science Landmark University Omu-Aran Nigeria Department of Computer Engineering Bells University of Technology Ota Ogun-State Nigeria

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

the analysis of webpage phishing is a standout computational method used to distinguish phishing from authentic websites through URL examination. In data mining, classification is crucial for constructing machine learning models that facilitate accurate decision-making. Phishing, a significant cyber menace, has recently escalated, inflicting substantial financial damage on individuals, corporations, and the global economy. Phishers typically replicate legitimate websites to trick unsuspecting users and extract vital information. To enhance cybersecurity systems, it's vital to selectively eliminate irrelevant or redundant features, retaining only pertinent attributes to narrow down the search scope. Not all data features are critical for classification, and feature selection can be a complex task. this research introduces a new ensemble feature selection method called Heterogeneous distributed Ensemble Feature Selection (HDEFS). the authors evaluated and contrasted the features derived from each component of the ensemble framework against baseline features in chosen models. Conducted experiments revealed that HDEFS enhanced the performance of both traditional and ensemble models, also simplifying model complexity relative to earlier studies. the boosted_SVM surpassed all other boosted models, achieving a 97.4% accuracy rate followed by boosted_LR with a detection rate of 94%.

关键词： Uniform resource locators Training Humanities Accuracy Biological system modeling Phishing Decision making Machine learning Feature extraction Data mining

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Predictive Maintenance in Electrical Machines: An Edge computing Approach

Predictive Maintenance in Electrical Machines: An Edge Compu...

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Industrial Cyber-Physical systems (ICPS)

作者： Javier De las Morenas Francisco Moya-Ferná ndez Mantis Research Group University of Castilla-La Mancha Almaden-Toledo Spain

Predictive maintenance is one of the premises of the Industry 4.0. A condition monitoring and fault diagnostic never seen before are possible with the new technologies embracing the digitalisation. this paper presents an edge computing approach for the predictive maintenance of electrical machines based on motor current signature analysis (MCSA), using Fast Fourier Transform (FFT) and a Support Vector Machine (SVM) classifier. A broken rotor bars and eccentricity fault detection are implemented on Arduino platform, providing a low-cost solution affordable for small and medium enterprises. the system has been tested in a lathe in one of the laboratories of the Mining and Industrial School of Almaden (UCLM) with satisfactory results.

关键词： Support vector machines Laboratories Rotors sensor systems Fourth Industrial Revolution sensors Prognostics and health management

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Improving Cloud Integrated sensor Network Architecture, Applications Challenges 5

Improving Cloud Integrated Sensor Network Architecture, Appl...

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5th international conference on computing Methodologies and Communication, ICCMC 2021

作者： Patel, Pratik K. Dave, Devangini P. Solanki, Kamini Modi, Kirit Parul Institute of Engineering Technology Parul University Computer Science and Engineering Department Waghodia India Parul Institute of Technology Parul University Computer Science and Engineering Department Waghodia India Parul University Faculty of Computer Science Information Technology Computer Science and Engineering Department Waghodia India

ISBN: (纸本)9781665403603

Wireless sensor network applications are applicable in so many significant areas like human health care observations, defense monitoring, environment observations infrastructure monitoring and so on. there are lots of issues challenges like security, scalability, storage, network lifetime etc. in wireless sensor network. To overcome the issues challenges, sensor Cloud (SC) become significant element of nowadays research era. sensor cloud is the combination of two individual technologies in one form. So, as far as concerned with fabulous data collecting capabilities of wireless sensor networks and because the powerful data storage and process capabilities of cloud computing, sensor Cloud integration is now a days attracting increase focus from both academic purpose and industry purpose. Virtualization is key concept of sensor Cloud in which more than one application simultaneously executes on every sensor device. For monitoring and controlling a number of applications, sensor Cloud provide us open, flexible, and adjustable platform. Here focus on important discussion regarding sensor Cloud Architecture which will give us sensor cloud design, applications, issues challenges. the proposed research work discusses regarding social sensor cloud in which an algorithm is designed for both parameter energy efficiency and security through virtualization. the proposed research work will help academicians as well as industry persons for design and development of sensor cloud. © 2021 ieee.

关键词： Cloud computing

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Analysis of a sensor Switching Approach for State Estimation with Applications to Electrochemical Power Converters and Energy Storage systems

Analysis of a Sensor Switching Approach for State Estimation...

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international conference on systems and Control (ICSC)

作者： Andreas Rauh Marit Lahme Department of Computing Science Group: Distributed Control in Interconnected Systems Carl von Ossietzky Universität Oldenburg Oldenburg Germany

Equivalent circuit models for fuel cell stacks as well as for the series connection of battery cells are characterized by multiple series-connected RC sub-networks. In practical applications, for example, when aiming at the aging detection and monitoring of the individual cells in a fuel cell stack, it is desired to estimate the individual state variables of each of these series-connected cells. the same holds true for battery management systems that are dedicated to the state of charge (resp., voltage) equalization in a series connection of multiple battery cells. However, the pure knowledge of the current through this series connection as well as the sum over all terminal voltages is insufficient to make the overall system model fully observable. To efficiently observe the state variables in each of the series-connected subsystems, we aim at avoiding the measurement of the voltages of each individual fuel (resp., battery) cell. Instead, this paper presents a systematic sensor switching strategy which allows for estimating the individual state variables of all series-connected subsystems in an Unscented Kalman Filter framework. Simulation results are presented to compare the achievable estimation accuracy with a scenario in which all cell (resp., terminal) voltages were measured simultaneously.

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Spectrum Handoff Using Game theory with Hypergraph Scheme in distributed Cognitive Radio Networks 5

Spectrum Handoff Using Game Theory with Hypergraph Scheme in...

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5th international conference on Communication and Information systems, ICCIS 2021

作者： Peng, Yunfei Shao, Wei Lu, Chunlan Li, Shufeng Wang, Chuang Ma, Wenyu Army Engineering University of PLA College of Communications Engineering Nanjing China

ISBN: (纸本)9781665422161

In this paper, a spectrum handoff scheme based on game theory and hypergraph in distributed Cognitive radio networks (CRNs) is proposed. Firstly, the hypergraph model is used to characterize potential spectrum occupation conflicts. By defining the potential cumulative conflict level (PCCL) function, the level of conflicts between secondary users (SUs) is quantified, and the cumulative handoff delay is obtained by combining the data transmission rates of SUs, which is taken as the optimization objective to maximize the CRNs throughput. Secondly, the spectrum handoff problem is characterized as a local altruistic game, which is proved to be an exact potential game (EPG) with at least one Pure Strategy Nash Equilibrium (PNE). thirdly, a spatial adaptive play algorithm based on SUs' transmission rates (BTR-SAP) is proposed, which marks SUs' status with their transmission rates. Lastly, the performance of the proposed scheme is verified by simulation experiments. Simulation results show that the proposed scheme is superior to traditional SAP algorithm in terms of convergence speed and network throughput, and significantly improves spectrum utilization efficiency. © 2021 ieee.

关键词： Cognitive radio

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Multi-sensor Fusion Tracking Algorithm by Square Root Cubature Kalman Filter for Intelligent Vehicle 5

Multi-sensor Fusion Tracking Algorithm by Square Root Cubatu...

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

作者： He, Lin Wang, Yansong Shi, Qin He, Zejia Wei, Yujiang Wang, Mingwei Hefei University of Technology College of Automobile and Traffic Engineering Hefei China

ISBN: (纸本)9781665408462

With the development of unmanned driving technology, the demand for tracking accuracy is increasing. To rely on a single sensor to obtain detection results in complex environments is limited in accuracy, and multi-sensor fusion is an effective method. therefore, the environmental sensing technology based on multi-sensor fusion is one of the present research hotspots. this paper proposes a multi-sensor fusion tracking algorithm based on the square root Cubature Kalman filter (SRCKF) for the purpose of nonlinearity of the vehicle target tracking system. this method establishes the equation of state and the measurement equation using the dynamic model, and utilizes the multi sensor measurement signal. A data fusion method based on cubature Kalman filter (CKF) with nonlinear system to avoid errors caused by linearization of nonlinear systems by extended Kalman filter (EKF). In the filtering process, the covariance square root matrix is used in place of the covariance matrix participating in the iterative operation. It effectively avoids the divergence of the filter and improves the convergence speed and stability of the filtering algorithm. © 2021 ieee.

关键词： Nonlinear systems

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A New Auxiliary Steering Angle sensor for Power-Steering in Four-Wheelers 5

A New Auxiliary Steering Angle Sensor for Power-Steering in ...

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5th international conference on Condition Assessment Techniques in Electrical systems (CATCON)

作者： Mithun, M. S. Tarafdar, Utpol Sankar, Hemanth P. Natl Inst Technol Calicut Dept Elect Engn Calicut Kerala India

ISBN: (纸本)9780738112916

Electric Power-steering (EPS) has currently become one of the most essential features of a four-wheeler. An EPS module has a Steering Angle sensor (SAS) that detects the angular displacement of the steering wheel made by the driver and produces signals that will in turn trigger the electric motor in the steering assembly to rotate the front wheels of the vehicle as required. When the SAS is faulty or aged, its functionality will be compromised and this can affect the passenger's safety. therefore, it is being proposed to install an auxiliary SAS on all four-wheelers. this auxiliary SAS will be also calibrated just like the built-in SAS of the vehicle. therefore, any the difference between its indication and the actual front-wheel orientation will point to an issue in the EPS. thus, it will act as a condition assessment tool for the EPS. But since this is an add-on system, its output can be also made to serve additional functions such as, data collection, parking assistance etc. the choice of transducer for this auxiliary SAS is a resistive potentiometric transducer as it can he easily coupled with the steering rod, making it a plug & play system. But, resistive transducers too are prone to wear & tear. Hence a new non-contact type transducer has been developed whose details are being presented in this paper. this paper also presents some preliminary evaluation results of this new sensor.

关键词： Power-steering Resistive Transducer Steering Angle sensor

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Installation of Sectionalizers in a Radial Distribution Networks to Create an Emergency Islanded Network Powered by distributed Generators During Outages

Installation of Sectionalizers in a Radial Distribution Netw...

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international conference on Modern Electrical and Energy systems (MEES)

作者： Viacheslav Bezruchko Roman Buinyi Ihor Dikhtyaruk Oleksandr Miroshnyk Denys Myrhorod Dept. Electrical Power Engineering and Information Measuring Technologies Chernihiv Politechnic National University Chennihiv Ukraine Dept. Electricity Supply and Energy Management State Biotechnological University Kharkiv Ukraine Dept. Electricity and Energy Management State Biotechnological University Kharkiv Ukraine

the paper considers the use of sectionalizers to isolate a damaged section of a medium voltage (MV) radial power network of 6-10 kV and create energy islanded network that can be powered by distributed generators (DGs). the configuration of power networks with one and two sectionalizers and a different number of DGs, which are separated over the network zones, is considered. To avoid the use of labor-intensive discrete calculations, the authors propose a simplified method for calculating the reduction of the expected energy not-supplied (EENS) to the consumers due to create energy islanded network. this method suggests replacing discrete load distribution with a standard function. All calculations come down to selecting the load distribution function and obtaining the result from the tables (placement of the sectionalizer and the EENS in this case). the table is easy to use when designing to find the optimal location for installing a sectionalizer in a power network.

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Framework Design of Fault Diagnosis System Based on Improved LSTM Networks

Framework Design of Fault Diagnosis System Based on Improved...

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Power Electronics, Computer Applications (ICPECA), ieee international conference on

作者： Yixin Wang University of Geosciences (Wuhan) Wuhan China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

In the current era of high industrialisation, fault diagnosis of complex industrial systems is facing unprecedented challenges. Traditional fault diagnosis methods based on physical models and signal processing gradually show their limitations, especially when facing nonlinear and nonsmooth signals as well as fusion of multi-source information. In this paper, we propose a framework design of a fault diagnosis system based on a long short-term memory network (LSTM) with improved attention mechanism. the system employs high-precision sensors to collect real-time operating signals from key components, and analyses and diagnoses these signals through a deep learning model to quickly and accurately determine whether there is a fault in the equipment and provide detailed fault type and location information. In particular, an attention mechanism is introduced to enhance the model's focus on key features in the fault signals, thereby improving the accuracy and reliability of fault diagnosis. Experimental results show that the proposed LSTM-Attention network performs well on the bearing fault dataset and achieves high classification accuracy.

关键词： Fault diagnosis Deep learning Attention mechanisms Accuracy Signal processing sensor systems Real-time systems Power electronics sensors Long short term memory

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IoT Enabled Condition Monitoring of Low Voltage Motors using Fuzzy Inference System 5

IoT Enabled Condition Monitoring of Low Voltage Motors using...

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5th international conference on Condition Assessment Techniques in Electrical systems (CATCON)

作者： Prakash, Choudhary Om Jaiswal, Supriya Das, Suchandan Natl Inst Technol Dept Elect Engn Hamirpur India

ISBN: (纸本)9780738112916

In the revolutionized industry 4.0 vision, the predictive maintenance of the machines make the maintenance easy and smart using Internet of things (IoT). It helps to improve the overall machine performance, capacity, sustainability and user safety. IoT serves as a well-planned structure for condition monitoring with the flexibility to integrate more number of devices to be monitored and controlled remotely. In this paper, a real-time condition monitoring prototype of low voltage industrial motor is developed. the prototype majorly monitors three vital parameters, temperature, vibration and speed of the motor using suitable sensors connected to Zigbee module sending data wirelessly to the remote end using IoT. these data are then fed from thingspeak server to the Fuzzy Inference System (FIS) to estimate the health of the motor. the complete devised prototype performs the function of monitoring, processing data, decision making and data storage remotely without any considerable user intervention.

关键词： Industrial motor Internet of things (IoT) condition monitoring (CM) Fuzzy Inference System (FIS) Wireless sensor Network (WSN)

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