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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11091 条记录，以下是1051-1060 订阅

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Drug Authentication and Counterfeit Drug Detection Using Blockchain 7

Drug Authentication and Counterfeit Drug Detection Using Blo...

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Chandras, Atharva Agrawal, Satyam Chaudhary, Mithil Deshmukh, Anushka Shinde, Shilpa Ramrao Adik Institute of Technology Dept. of Computer Engineering Navi Mumbai India

ISBN: (纸本)9798350304268

Drug counterfeiting is a worldwide phenomenon which affects practically every industry involved with the healthcare sector in both developed and developing countries. this widespread smuggling and usage of counterfeit drugs has serious economic, health, and safety impacts on any country. In addition to this, the credibility of the healthcare system can be questioned and harmed if the counterfeit drugs find a way into the market and harm the public opinion about the pharmaceutical chain. An annual analysis done by the US Trade Representative office on rights protection in 2019 stated that up to 20% of the pharmaceutical supply sold in India were counterfeit and this has only increased since the pandemic. In an estimate done between 2020 to 2021, it was found that incidents of counterfeit and fake drugs had shot up to about 47 percent. Traditional methods of drug authentication have proven to be ineffective in detecting counterfeit drugs. Blockchain technology provides a promising solution to the problem of counterfeit drugs. the proposed system for detecting counterfeit drugs using blockchain technology consists of a blockchain network, a web application, and a database. the proposed system aims to provide an efficient and secure method of detecting counterfeit drugs using blockchain technology, which can enhance trust in the healthcare system and reduce the cost of drug authentication. © 2023 IEEE.

关键词： Blockchain Ganache Node js Solidity Truffle

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Vector Control of an Induction Motor for Speed Regulation 7

Vector Control of an Induction Motor for Speed Regulation

引用

7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Satyanarayana, Gurram Karthikeyan, M. Mahalakshmi, R. Vandarkuzhali, T. Engineering College Telangana Hyderabad India Department of Electrical and Electronics Engineering Veltech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Tamil Nadu Chennai India Department of Electrical and Electronics Engineering Meenakshi Sundarrajan Engineering College Tamil Nadu Chennai India Department of Electrical and Electronics Engineering Hindusthan College of Engineering and Technology Tamil Nadu Coimbatore India

ISBN: (纸本)9781665464086

In electric motor drives, speed regulation plays an essential part in describing the overall performance of the system drive. To control the motor speed of an Induction motor (IM), an indirect vector control method is implemented in this paper. Scalar control is a simple and effective technique, but it responds slowly to transients and is unsatisfactory for regulating motors with dynamic behavior. the currents are controlled via the field-oriented control (FOC) approach, allowing for quick reactions. this approach meets the demands of dynamic drives, wherein quick response is required. the flux location is calculated indirectly in indirect control methods by rotor speed and slip calculation. the indirect control technique has grown in popularity due to the lack of rotor flux position sensors and the capacity to work at low speeds. A PI controlleris utilized in the speed controller to control the motor torque by producing quadrature-axis current reference iq*. the motor's flux is controlled by direct axis current reference id*. the IM is operated by a current-controlled PWM inverter. the designed model is simulated using MATLAB and the results show an accurate speed response of the IM motor. © 2023 IEEE.

关键词： Induction motors

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Welding Robot Follow-Up Control Based on an Advanced UKF Algorithm 7

Welding Robot Follow-Up Control Based on an Advanced UKF Alg...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Xu, Mingzhu Wang, Yu Huang, Zhijun Wu, Guanghai Zhang, Han Song, Zhaozu Zhang, Chengyu Zhao, Yuxuan Gao, Yifan Zheng, Jianbin Wuhan University of Technology School of Information Engineering Wuhan City China Third Construction Co. Ltd. China Construction Third Engineering Bureau Wuhan City China

ISBN: (纸本)9781665478571

the core welding of remote control is the follow-up control of the mechanical arm, and the control accuracy and time delay between the human body motion and the welding process of the mechanical arm are difficult in the problems of the follow-up control. this paper designs a follow-up control algorithm based on the fusion of human motion perception and unscented Kalman Filter to solve the problem between the human body and the follow-up of the mechanical arm, and the nonlinear prediction function are studied. through the improvement of the a1 bove two aspects, the problem of uncoordinated movement of the human body and the mechanical arm during the follow-up control process is solved. Compared with Kalman Filter and unscented Kalman filter, the variance and the mean value of AUKF in prediction accuracy are 6.758 and 1.791 respectively. the mean time delay point of AUKF is 1.8. therefore, the welding quality meets the demands of the industry. © 2022 IEEE.

关键词： Remote control

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Design of CMOS Based Lc-Voltage Control Oscillator Using Substrate Bias Effect and Low-Voltage Folded-Cascade Current Mirror Circuit 7

Design of CMOS Based Lc-Voltage Control Oscillator Using Sub...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Suresh, N. Ramesh, M. Rosi, A. Periyar Selvam, K. Vaishnavi, T. Nalini, N. AVN Institute of Engineering & Technology Electronics & Communication Engineering Hyderabad501510 India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Electronics & Communication Engineering India GRT Institute of Engineering and Technology Electronics & Communication Engineering Tiruttani India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Electronics & Communication Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Electronics & Communication Engineering Chennai India

ISBN: (纸本)9798350372816

this paper Proposed to design a CMOS Based LC-Voltage Control Oscillator Using Substrate Bias Effect and Low-Voltage Folded-Cascade Current Mirror Circuit using an LC tank circuit at 2.5GHz oscillation Frequency. the paper delves into the substrate-biasing technique, which adjusts the threshold voltage of a CMOS transistor, and the low-voltage folded-cascade current mirror circuit that utilizes CMOS technology to improve the performance of the current mirror circuit. the folded-cascade current mirror circuit comprises of a cascade structure in the input stage and a folded structure in the output stage, which is used to increase the output impedance and provide a more stable output current. the paper concludes that the folded-cascade current mirror circuit is a powerful tool in CMOS circuit design, offering improved performance and accuracy over the traditional current mirror circuit. In this simulation is carried out through cadence virtuoso generic process design kit (GPDK) with 90nm technology. the simulation results exhibits phase noise of -154.92 dBc/Hz @ 1MHz, low power consumption of 4.8mW and the Figure of Merit -216.09 dBc/Hz at 2.5GHz oscillation frequency © 2024 IEEE.

关键词： CMOS integrated circuits

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Network Intrusion Detection using Deep Reinforcement Learning 7

Network Intrusion Detection using Deep Reinforcement Learnin...

引用

7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Sujatha, V. Prasanna, Kodimala Lakshmi Niharika, Kakarla Charishma, Vanukuri Sai, Kamma Bhavya Computer Science and Engineering Vignan's Nirula Institute of Technology and Sciences for Women Guntur India

ISBN: (纸本)9781665464086

the number of internet-connected systems has increased by a huge amount in recent years. these systems are highly vulnerable and increasingly at risk from cyber- attacks. these cyber-attacks need more advanced and intelligent cyber defense systems that include agents that can learn to make judgements on their own without consulting human specialists. Deep learning-based reinforcement learning (DRL) is very good at handling complicated, dynamic, and especially high-dimensional cyber protection problems. this article provides a modern network intrusion detection technology, which employs a deep feed-forward neural network method and reinforcement learning, which is based on Q- learning. In order to detect various sorts of intrusions in the network using an automated trial- and-error method and continually improve its detection skills, the Deep Q-Learning (DQL) model is proposed. the accuracy of the model proposed is 91.4%, while the accuracy of other self-taught learning models is 88.4% and it is a similar case for recall rate and precision as well which are 90.2% and 92.8%. Our experimental findings further demonstrate that our suggested DQL beats other comparable machine learning methods and is very good at identifying various intrusion classifications. © 2023 IEEE.

关键词： Reinforcement learning

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Research on a Portable Gel Physical Properties Analyzer 7

Research on a Portable Gel Physical Properties Analyzer

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yan, Huan Gao, Weixin Yu, Feiyuan Xi'an Shiyou University School of Electronic Engineering Xian China

ISBN: (纸本)9781665478571

Viscosity is an important physical property of gels widely used in the petroleum industry. In this paper, a non-contact and efficient measurement method is proposed. the motion process of the gel in the capillary is captured by a high-speed camera, and the gel image is obtained. Using the advantages of GPU in parallel computing, a corresponding image processing method is proposed. the physical viscosity measurement of four actual batches of gels shows that the method proposed in this paper can accurately obtain the actual physical properties, and the execution time of the method in this paper is significantly faster than the CPU serial method, which ensures the accuracy of the calculation of the physical properties of the analyzer. At the same time, the real-time performance of the calculation is improved. © 2022 IEEE.

关键词： Viscosity

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Parallel LSTM Enhanced Forecasting System for Dependable and Secure Household Energy Consumption 23

Parallel LSTM Enhanced Forecasting System for Dependable and...

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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： Yan, Ke Yang, Fan Zhou, Xiaokang Liang, Wei College of Design and Engineering National University of Singapore Singapore Singapore College of Information Engineering China Jiliang University Hangzhou China Shiga University Faculty of Data Science Hikone Japan Riken Center for Advanced Intelligence Project Tokyo Japan School of Frontier Crossover Studies Hunan University of Technology and Business Changsha China

ISBN: (纸本)9781665494571

A dependable and secure energy consumption forecasting system is proposed with parallel long short term memory neural networks and singular spectrum analysis (SSA). the input data is a time series dataset collected by an energy loading sensor installed for a particular household. the energy consumption patterns of in total five households in the UK were investigated. the SSA is employed for feature extraction by decomposing the original time series data into a series of constitutive sub-signals. A Parallel LSTM (PLSTM) learning model is then conducted to predict the energy consumption patterns for each SSA sub-signal. the decomposition and signal merging processes enhance the resilience for sensor faulty and errors, i.e., improve the security and dependability levels. Experiment results demonstrate that the proposed hybrid model significantly improves the prediction precision compared with benchmark models. the pressure of power load and maintenance cost of the grid can be drastically reduced. In addition, the training time of our proposed model is much faster than the benchmark model. the shortening of model training time can greatly advance the research on household power consumption. © 2021 IEEE.

关键词： Training Energy consumption Time series analysis Predictive models Data models Reliability Forecasting

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Multi-Facial Automated Attendance System using Haar Cascade, LBPH, and OpenCV-Based Face Detection and Recognition 7

Multi-Facial Automated Attendance System using Haar Cascade,...

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Rathi, Snehal Kapadnis, Snehal Sonar, Gayatri Sonar, Gaurav Vispute, Sushma R. Vishwakarma Institute of Information Technology Pune India Vishwakarma Institute of Technology Pune India Aress Software Nashik India Pimpri Chinchwad College of Engineering Pune India

ISBN: (纸本)9798350304268

In the 21st century, everything around us is dependent upon technology to make our lives much easier. Daily tasks are increasingly being computerized. Nowadays more people prefer to do their work electronically. To the extent of our knowledge, students' attendance at some universities is manual. the attendance management system computerizes the traditional attendance process. Utilizing OpenCV (Open-source Computer Vision) and some face detection and recognition algorithms, we propose a system to measure student attendance in classes. By using face detection algorithms and face recognition algorithms, we will keep track of how many people are present in the class and attendance of each one. this project intends to provide a system that automates and streamlines the process of collecting and monitoring student attendance using facial recognition technology. To find, identify, and validate collected faces, preprocessing methods like the Haar Cascade approach will be used. To make the attendance process quicker and more accurate, we aim to offer a method. © 2023 IEEE.

关键词： attendance management system computer vision face detection face recognition Haar Cascade approach

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UCloudStack - A Private Cloud Platform for Lightweight Delivery 7

UCloudStack - A Private Cloud Platform for Lightweight Deliv...

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7th IEEE international conference on Smart Cloud, SmartCloud 2022

作者： Peng, Xingyu Song, Yilun Yuan, Kangjian Guo, Xu Lu, Zhihui Liu, Jie UCloud Technology Co. Ltd Shanghai China Fudan University School of Computer Science Shanghai China

ISBN: (数字)9781665451796

ISBN: (纸本)9781665451796

Cloud computing is a relatively mature business computing model, which is gradually developed from technologies such as distributed computing, parallel processing, and grid computing. Similarly, with the continuous emergence of cloud computing applications, people's understanding of cloud computing is also constantly changing. this paper designs a private cloud platform called 'UCloudStack' based on cloud computing technology. the platform can provide a complete set of cloud resource management capabilities such as unified management of core services such as virtualization, SDN network, and distributed storage, resource scheduling, monitoring logs, and operation and maintenance, helping the digital transformation of government and enterprises. © 2022 IEEE.

关键词： Grid computing

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Experience-based Pickup Area Recommendation on Taxi's GPS Trajectories 23

Experience-based Pickup Area Recommendation on Taxi's GPS Tr...

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作者： Liao, Zhuhua Zhang, Jian Yi, Aiping Liu, Yizhi Zhao, Yijiang Liu, Silin School of Computer Science & Engineering Hunan University of Science & Technology Xiangtan China

ISBN: (纸本)9781665494571

Experienced drivers can generally earn high income and save more energy and time with their effective experiences. So the behaviors of experienced drivers are important for pickup area recommendation to ordinary drivers. In this paper, we proposed a pickup area recommendation model that considering the behaviors mining of experienced drivers and recommending directions where clustering high profit pickup areas by using taxi's GPS trajectories. Although this is a strategically important task in passenger seeking for taxi drivers, the problem has not been solved due to two major challenges. the one is data sparsity. the other is how to fuse the experiences of professional drivers to recommender. To address these challenges, we firstly fuse the geographic information into the process of filling up the absence data. then, we make driving direction decision and pickup areas recommendation at any place according to the experiences of experienced drivers. We evaluate our method by using GPS trajectories generated by more than 13000 taxis over a period of one month. the results demonstrate the efficiency of pickup area recommendation for ordinary drivers. © 2021 IEEE.

关键词： Training Fuses Social networking (online) Telecommunication traffic Trajectory Behavioral sciences Data mining

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