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

共 11084 条记录，以下是711-720 订阅

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Secure Vote: AI-powered Fingerprint Authentication for Next-Generation Online Voting 7

Secure Vote: AI-powered Fingerprint Authentication for Next-...

引用

7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Suresh, Anjana Gupthan, Aishwarea Arpitalaxmi Abhishek, S. Anjali, T. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350340600

Democratic societies place significant importance on secure and efficient voting systems as a cornerstone of their governance. Normally, the voting process would follow a traditional ballot system involving tedious paperwork. It all takes a lot of time to manually count the votes, which may lead to human errors in counting or missing votes. However, other concerns surrounding the security and reliability of e-voting systems have initiated the development of more robust approaches. the proposed Secure Vote system presents an AI-enabled voting solution that enhances the security and reliability of the voting process by incorporating dual-factor authentication through a unique identification number and the utilisation of fingerprints. It also has the potential to provide a secure and trustworthy platform for democratic societies to exercise their voting rights. © 2023 IEEE.

关键词： Electronic voting

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An Online Incremental Scheduling Method for Time Sensitive Networks Combined with Routing 7

An Online Incremental Scheduling Method for Time Sensitive N...

引用

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

作者： Yu, Zihan Cao, Suzhi Wang, Xin Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665478571

Time sensitive network is an extension of standard Ethernet network, which meets the delay and jitter requirements of critical traffic in specific fields through various mechanisms. the time sensitive network calculates the traffic schedule that meets the critical traffic requirements by planning the overall network traffic, which is NP-complete. When there is a new flow demand in the network, most of the existing solutions are to resolve the schedule table for all network traffic, which is time-comsuming. To provide a solution on such problem, we propose an incremental scheduling method for time-sensitive network so that the scheduling table corresponding to the new traffic in the network is therefore solved. the method adopts a combination of routing and scheduling, selecting alternative routing paths for traffic via heuristic methods, and then performs incremental scheduling on the gate control list of the devices selected by the routing to solve the feasible scheduling of new flows. the experiment results show that, compared with the traditional static scheduling scheme, the method can greatly speed up the process of scheduling and solving, and is able to solve the problem within seconds, meeting the needs of online incremental scheduling. © 2022 IEEE.

关键词： Scheduling

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Decentralized MISO Cooperative Beamforming Design for Multi-Cell URLLC Network 7

Decentralized MISO Cooperative Beamforming Design for Multi-...

引用

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

作者： Wang, Lihui Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China

ISBN: (纸本)9781665478571

Achieving low-latency for ultra-reliable and low- latency communications (URLLC) is one of the major challenge for the fifth-generation cellular networks. To address this challenge, the cooperation among base stations (BSs) has the potential to reduce latency and improve data speed. However, it requires a great quantity information interaction at cost of magnanimous utilization of the backhaul. In this paper, the author analyzes the duality between virtual uplink and downlink optimization problems. then, we propose an iterative decentralized algorithm to solve a max-min achievable rate problem based on the joint of the alternating direction method of multipliers(ADMMs) and successive convex approximation (SCA) method. Specifically, we can iteratively approximate the nonconvex problem into a convex problem by using the SCA method. In the second step, the ADMM method is used to transform the centralized optimization problem into a decentralized optimization problem that solves the problem locally. Each BS is regarded as a subproblem to work the problem out locally in parallel. By allowing BSs to exchange the required information until ADMM converges, the resulting formulation is optimized. Finally, simulation results show the effectiveness of our proposed algorithm. © 2022 IEEE.

关键词： Optimization

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Intelligent Sorting System 7

Intelligent Sorting System

引用

7th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2022

作者： Mao, Yanghong Chen, Chuixin Pan, Zhengjun Guangzhou Institute of Science and Technology Department of Computer Science and Engineering Guangzhou China Institute of Guangzhou Department of Software Engineering Software Engineering Guangzhou China Department of Software Engineering Software Engineering Institute of Guangzhou Guangzhou China

ISBN: (纸本)9781665487115

In order to achieve the goal that the manipulator can automatically obtain any position within its working range, and can adjust the end actuator for grasping, a machine vision sorting system is designed. the system passes through image processing, target recognition and positioning, and finally realizes the sorting effect through trajectory planning. Aiming at the problem that the deep learning algorithm takes a long time, the traditional image processing algorithm and deep learning target detection algorithm are organically combined to reduce the use delay of image processing in the system. Because the training of deep learning model requires a large number of data sets, but the amount of data in manufacturing factories is small, and data labeling is time-consuming and laborious, YOLO v3 algorithm is used to improve the efficiency of training model under a small number of labeled data sets, SIFT algorithm is used to extract image features, and K-D tree algorithm is used to match image features. In the algorithm of position, the centroid is extracted as the positioning reference coordinate, the kinematics model of the manipulator is established. trajectory planning, straight-line and arc interpolation algorithms are used. the experimental results show that the system meets the design requirements. © 2022 IEEE.

关键词： Deep learning Training Trajectory planning Target recognition Object detection Feature extraction Manipulators

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A High-accessibility Identification technology for Butt Joint Weld Defects 7

A High-accessibility Identification Technology for Butt Join...

引用

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

作者： Wang, Dan Gao, Weixin Xi'an Shiyou University School of Electronic Engineering Xian China

ISBN: (纸本)9781665478571

Aiming at the problem of defect detection of butt joint weld images, this paper proposes to use the distance invariance and angle invariance of Log-Polar transformation to transform the position and shape of the defect into a simple two-dimensional plane translation of a typical defect image. Defect area calibration problem. In addition, in order to improve the detection rate and recognition accuracy of defect identification, a defect identification based on sparse description is proposed, which uses three major knowledges: extracting typical samples from massive data, building non-parametric models, and solving sparse solutions based on the optimal direction method. system to identify the calibrated SDR. On this basis, combined with the 0-norm minimization problem and the OMP algorithm to solve the sparse coefficient, further intelligent determination of defect types is realized. Experiments show that the recognition rate of the dictionary matrix obtained by limited sample training has reached more than 98.5%. © 2022 IEEE.

关键词： Defects

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Improving GAN for Image Super-Resolution by Using Attention Mechanism and Dense Module 7

Improving GAN for Image Super-Resolution by Using Attention ...

引用

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

作者： Zhao, Junhan Zhou, Zhijie Liu, Yu Nanjing Tech University School of Physical and Mathematical Sciences Nanjing China Guangdong University of Foreign Studies College of Computer Science and Technology Guangzhou China Zhejiang University Electrical and Computer Engineering Department Jiaxing China

ISBN: (纸本)9781665478571

With the gradual maturity of the convolutional neural networks (CNN) in image recognition, deep-learning based singe image superresolution (SISR) has shown great promise but also poses a challenge to current researches. Specifically, most SR methods have problems such as failing to reconstruct finer texture details, difficulty in determining the interdependence between each channel of the feature map, to name a few. To solve these problems, we propose a multi-level dense skip network (MDSN) and adapt it into SRGAN. this is a powerful model designed for SISR tasks, which combines confrontation training and extracts abundant local features via the contiguous memory mechanism. We achieve a trade-off between model performance and complexity by introducing the ECA module, which ensures the appropriate cross-channel interaction. the testing results on the public dataset demonstrate richer texture details and better visual effects of superresolution images restored by our model. © 2022 IEEE.

关键词： Textures

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Investigating the Efficacy of Nonlinear Susceptibility Inversion Deep Learning Models in MRI Quantitative Susceptibility Mapping 7

Investigating the Efficacy of Nonlinear Susceptibility Inver...

引用

7th international conference on Biological Information and Biomedical engineering, BIBE 2024

作者： Zhang, Zheng Guo, Hongyu Jing, Yan College of Electrical Engineering Shenyang University of Technology Shenyang110870 China

ISBN: (纸本)9783800762910

Quantitative Susceptibility Mapping (QSM) serves as a crucial tool for assessing tissue susceptibility in various cerebral conditions. Derived from MRI gradient-echo signals, QSM delineates tissue susceptibility distribution by solving a complex dipole inversion problem. However, traditional QSM reconstruction methods often yield images marred by streaking artifacts, excessive smoothing, noise amplification, or underestimated susceptibility values. Moreover, datadriven deep learning-based QSM approaches often lack a data fidelity component within their network architecture, leading to deviations from dipole model-derived magnetic susceptibility values on original phase images. To mitigate these challenges, this paper introduces a novel nonlinear model-driven deep learning method termed NDL-QSM. NDL-QSM incorporates a nonlinear susceptibility inversion model into a deep learning framework and employs the PGD (Projected Gradient Descent) algorithm for systematic optimization. Leveraging the merits of nonlinear modeling and deep learning networks, NDL-QSM delivers more precise susceptibility estimations and produces higher-quality susceptibility maps compared to existing methodologies. © VDE VERLAG GMBH.

关键词： Deep learning

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Adaptive Neural approximated Inverse Control for Heliostat in Tower Solar plant 7

Adaptive Neural approximated Inverse Control for Heliostat i...

引用

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

作者： He, Huan Gao, Yiming Yu, Bo Jia, Yilin Zhu, Guoqiang Zhang, Xiuyu Anshan Power Supply Company State Grid Liaoning Electiric Power Co. Ltd Anshan China Northeast Electric Power University School of Automation Engineering Jilin China

ISBN: (纸本)9781665478571

A full state constrained decentralized adaptive robust dynamic surface sliding mode approximated inverse control scheme is proposed to address the consensus attitude tracking problem of heliostat in solar power tower plant. By introducing the Barrier Lyapunov function into the dynamic surface technique, the full states of the systems satisfy the constraints, which will keep the system working in a safe range. the RBFNNS was used to approximate the unknown parameters and uncertainties in the system, and the output feedback control law is designed by using sliding mode method to satisfy the attitude tracking accuracy and improve the robust of the system. We using the approximated inverse compensator approach to address the problem of hysteresis in the serve motor, which will affect the control accuracy and stability. It is proved that all the signals are semi-globally uniformly ultimately bounded, and the tracking errors converge can be made arbitrarily small. © 2022 IEEE.

关键词： Sliding mode control

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Software Effort Estimation using ANN (Back Propagation) 7

Software Effort Estimation using ANN (Back Propagation)

引用

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

作者： Ravi Kumar, B.N. Suresh, Yeresime Dept. of Computer Science and Engineering BMS Institute of Technology and Management Bangalore India Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari India

ISBN: (纸本)9781665464086

Project managers often use Effort Estimating strategies to manage the human resources of current or upcoming software projects. Prior to project implementation, cost, time, and personnel estimation are basically necessary. For every project of software, getting an accuracy in Effort Estimation has always been difficult. In case of this study, estimating the labor involved in developing software determined using a Back Propagation Model. this model's goal is to investigate the capabilities and potential uses of utilizing Artificial Neural Networks (ANN) as a tool for forecasting the effort required for software development. In order to estimate the software work, we are attempting to implement a machine learning technique in this research. Out of all machine learning methods, we are applying an algorithm based on Artificial Neural Networks that is Back propagation. the Desharnais dataset, a well-known publicly available dataset for estimation of software effort, is used to test the approach. the performance and accuracy of the tested model have been evaluated using three metrics: MMRE, MRE, and Pred (0.25). In the sections below that follows, I explain the algorithm and its results. © 2023 IEEE.

关键词： Neural networks

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Experimental and numerical study on free-running tests of a 7m KVLCC2 model 7

Experimental and numerical study on free-running tests of a ...

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7th IEEE international conference on Transportation Information and Safety, ICTIS 2023

作者： Tao, Jiabin Liu, Jialun Wuhan University of Technology School of Naval Architecture Ocean and Energy Power Engineering Wuhan China State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan China Wuhan University of Technology Intelligent Transportation Systems Research Center Wuhan China National Engineering Research Center for Water Transport Safety Wuhan China

ISBN: (纸本)9798350308532

Ship maneuverability is very important for navigation safety of seagoing and inland vessels. A lot of studies have been conducted to investigate the maneuvering performance of ships in calm water or waves, including model experiments, theoretical methods based on potential flow theory and numerical simulations. this paper presents an investigation on mathematical modelling of a 7 m long KVLCC2 model-scale ship. the model is validated with free running tests, which provides a hint for relevant research. © 2023 IEEE.

关键词： Numerical methods

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