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A Dynamic and Deadline-Oriented Road Pricing Mechanism for Urban Traffic Management

Tsinghua science and Technology 2022年第1期27卷 91-102页

作者： Jiahui Jin Xiaoxuan Zhu Biwei Wu Jinghui Zhang Yuxiang Wang the School of Computer Science and Engineering Southeast UniversityNanjing 211189China the Department of Computer Science and Engineering Hangzhou Dianzi UniversityHangzhou 310018China

Road pricing is an urban traffic management mechanism to reduce traffic ***,most of the road pricing systems based on predefined charging tolls fail to consider the dynamics of urban traffic flows and travelers’demands on the arrival *** this paper,we propose a method to dynamically adjust online road toll based on traffic conditions and travelers’demands to resolve the above-mentioned *** method,based on deep reinforcement learning,automatically allocates the optimal toll for each road during peak hours and guides vehicles to roads with lower toll ***,it further considers travelers’demands to ensure that more vehicles arrive at their destinations before their estimated arrival *** method can increase the traffic volume effectively,as compared to the existing static mechanisms.

关键词： road pricing traffic congestion al eviation deep reinforcement learning

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User Task Priority Based Resource Allocation with Multi Class Task Scheduling Strategy and Load Balancing in Cloud Environment

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SN computer science 2024年第8期5卷 970页

作者： G, Nida Kousar C, Gopala Krishnan Department of Computer Science and Engineering GITAM School of Technology Bengaluru 561203 India

An effective task scheduling method can accommodate user needs, boost resource usage, and boost cloud computing's overall efficiency. However, the unchanging task needs are generally the focus of grid computing's job scheduling, leading to low resource usage. Distributing the dynamic user tasks fairly among all cloud nodes is the goal of load balancing, a relatively new field of study. The primary difficulty with cloud computing is load balancing. By making better use of available resources, load balancing methods improve cloud performance. Load balancing primary goal is to lessen the burden on the environment by cutting down on energy use and carbon emissions. The most crucial characteristics that can both satisfy user needs and maximize resource utilization are used to determine the order of priorities. Existing systems often ignore user priority suggestions in favor of optimal scheduling to improve load balancing. Scheduling that takes into account user-guided priorities uses a data-driven strategy, which helps improve load balancing. Scheduling algorithms that take user priorities into account can optimize load distribution more effectively. The primary objective of this research is to provide a priority based randomized load balancing technique that assigns tasks to virtual machines in a random fashion based on criteria such as the number of users, the amount of time the task takes to run, the type of software being used, the cost of the software, and the amount of available resources. This method maximizes system performance by decreasing response time and resource consumption while increasing metrics like fault tolerance and scalability. This system for scheduling tasks not only accommodates user needs but also achieves excellent resource usage. This research proposes a User Task Priority based Resource Allocation with Multi Class Task Scheduling Strategy and Load Balancing (UPRA-MCTSS-LB) Model for enhancing the cloud service quality. The proposed method res

关键词： Cloud computing Load balancing Multi class tasks Quality of service Resource utilization Task scheduling User task priority

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An efficient attack detection and prevention approach for secure WSN mobile cloud environment

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Soft Computing 2024年第19期28卷 11279-11293页

作者： Vellela, Sai Srinivas Balamanigandan, R. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai602105 India

Wireless Sensor Network (WSN) is a network with a good organization that provides efficient communication services. However, high energy usage and attack data sometimes become the key challenges that degrade the entire network’s Performance. Therefore, in the present research, a novel Chimp-based Curriculum Learning (CbCL) is created for the WSN mobile cloud environment to reduce energy usage and detect the attack node with the CH selection. Initially, the required nodes are deployed in the network. The attack nodes are monitored and removed based on Chimp's optimal functions;optimal CH is selected for the data transfer. Finally, data is shared between the attack node and normal nodes. The created framework was tested in the Matlab environment, and the network efficiency parameters were calculated. To validate the improvement, the results are related to the existing models. The higher Performance of the CbCL satisfied the network’s efficient energy management and attack detection process. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Sensor nodes

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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with engineering Applications

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computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Efficient Identification of DeepFake Images using CNN 2

Efficient Identification of DeepFake Images using CNN

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Gowda, Naveen Chandra Veena, H.N. Ramani, D Roja School of Computer Science and Engineering REVA University Bengaluru India SJB Institute of Technology Department of Computer Science and Engineering Bengaluru India Newhorizon College of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350327533

The development of Deepfakes has become more prevalent with the rise of Generative Adversarial Networks (GANs). Deepfakes are synthetically created, modified images that have been made to look real;they pose severe social concerns with privacy an d security issues. To solve these issues, this paper offers a novel method to detect Deepfakes in photographs using a Convolutional Neural Network (CNN) architecture. To detect whether a image has been altered or not, the suggested method examines many aspects of the image. The proposed methods are tested using a sizable benchmark dataset of Deepfakes and non-Deepfakes, and were able to identify modified images with high precision. The strategy is resistant to a variety of manipulations, including those intended to trick cutting-edge detection techniques. It is found that proposed strategy will improve digital media's security and credibility while helping mitigate any possible problems of Deepfake images. © 2024 IEEE.

关键词： Convolutional Neural Network (CNN) DeepFake Deeplearning Generative Adversarial Networks (GANs)

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SEED-VII: A Multimodal Dataset of Six Basic Emotions with Continuous Labels for Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第2期16卷 969-985页

作者： Jiang, Wei-Bang Liu, Xuan-Hao Zheng, Wei-Long Lu, Bao-Liang Shanghai Jiao Tong University Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Shanghai200240 China

Recognizing emotions from physiological signals is a topic that has garnered widespread interest, and research continues to develop novel techniques for perceiving emotions. However, the emergence of deep learning has highlighted the need for comprehensive and high-quality emotional datasets that enable the accurate decoding of human emotions. To systematically explore human emotions, we develop a multimodal dataset consisting of six basic (happiness, sadness, fear, disgust, surprise, and anger) emotions and the neutral emotion, named SEED-VII. This multimodal dataset includes electroencephalography (EEG) and eye movement signals. The seven emotions in SEED-VII are elicited by 80 different videos and fully investigated with continuous labels that indicate the intensity levels of the corresponding emotions. Additionally, we propose a novel Multimodal Adaptive Emotion Transformer (MAET), that can flexibly process both unimodal and multimodal inputs. Adversarial training is utilized in the MAET to mitigate subject discrepancies, which enhances domain generalization. Our extensive experiments, encompassing both subject-dependent and cross-subject conditions, demonstrate the superior performance of the MAET in terms of handling various inputs. Continuous labels are used to filter the data with high emotional intensity, and this strategy is proven to be effective for attaining improved emotion recognition performance. Furthermore, complementary properties between the EEG signals and eye movements and stable neural patterns of the seven emotions are observed. © 2010-2012 IEEE.

关键词： Eye movements

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NeuroProbe: A Performance Profiling Feed Forward Neural Network Simulator for Hardware Interaction Analysis

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SN computer science 2025年第5期6卷 1-22页

作者： Ayyappan, Binu Kumar, G. Santhosh Department of Computer Science Cochin University of Science and Technology Kochi India Department of Artificial Intelligence and Data Science Rajagiri School of Engineering & Technology Kochi India

NeuroProbe is a simple neural network simulator designed by authors specifically for educational purposes focusing on simulating inference phase on a computationally capable embedded hardware, aiming to provide a deeper understanding of hardware interactions and performance improvement. This simulator incorporates performance profiling capabilities, allowing students and educators to analyze and optimize the performance of a simulated trained neural network. By simulating the intricate hardware interactions, NeuroProbe enables users to gain insights into how various components impact the overall performance of neural networks. Using this simulator, learners can experiment with different configurations and architectures, identify potential bottlenecks, and explore optimization strategies to enhance neural network performance before deploying the model on an Edge Computing environment. It also enriches computer science education by enabling learners to gain deeper insights into hardware interactions and performance improvement. By identifying performance bottlenecks, learners can refine their understanding of neural networks and develop skills in optimizing their models for enhanced performance. In conclusion, NeuroProbe empowers users to bridge the gap between theoretical knowledge and practical implementation of neural network on an embedded device, fostering a more comprehensive understanding of neural networks and their hardware requirements. Currently, it is focused solely on single-threaded CPU-based computation enabling SSE, AVX. At present, NeuroProbe does not support SIMD extensions such as AVX-FMA, AVX-512, multi-threaded computation, and accelerators such as NPU, TPU, and GPU. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Hardware–software interactions Neural network simulator NeuroProbe Performance bottlenecks Performance profiling Simulations

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Loop Subgraph-Level Greedy Mapping Algorithm for Grid Coarse-Grained Reconfigurable Array

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Tsinghua science and Technology 2023年第2期28卷 330-343页

作者： Naijin Chen Fei Cheng Chenghao Han Jianhui Jiang Xiaoqing Wen School of Computer and Information Science Anhui Polytechnic UniversityWuhu 241000China School of Software Engineering Tongji UniversityShanghai 201804China Department of Computer Science and Networks Kyushu Institute of TechnologyFukuoka 820-8502Japan

To solve the problem of grid coarse-grained reconfigurable array task mapping under multiple constraints,we propose a Loop Subgraph-Level Greedy Mapping(LSLGM)algorithm using parallelism and processing element *** the constraint of a reconfigurable array,the LSLGM algorithm schedules node from a ready queue to the current reconfigurable cell array *** mapping a node,its successor’s indegree value will be dynamically *** its successor’s indegree is zero,it will be directly scheduled to the ready queue;otherwise,the predecessor must be dynamically *** the predecessor cannot be mapped,it will be scheduled to a blocking *** dynamically adjust the ready node scheduling order,the scheduling function is constructed by exploiting factors,such as node number,node level,and node *** with the loop subgraph-level mapping algorithm,experimental results show that the total cycles of the LSLGM algorithm decreases by an average of 33.0%(PEA44)and 33.9%(PEA_(7×7)).Compared with the epimorphism map algorithm,the total cycles of the LSLGM algorithm decrease by an average of 38.1%(PEA_(4×4))and 39.0%(PEA_(7×7)).The feasibility of LSLGM is verified.

关键词： Grid Coarse-Grained Reconfigurable Array(GCGRA) mapping loop subgraph scheduling

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A Global Medical Data Security and Privacy Preserving Standards Identification Framework for Electronic Healthcare Consumers

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 4379-4387页

作者： Mishra, Vinaytosh Gupta, Kishu Saxena, Deepika Singh, Ashutosh Kumar Thumbay Institute for Ai in Healthcare Gulf Medical University Ajman United Arab Emirates National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan The University of Aizu School of Computer Science and Engineering Aizuwakamatsu965 Japan University of Economics and Human Sciences Department of Computer Science Warsaw01-043 Poland Indian Institute of Information Technology Bhopal Department of Computer Science and Engineering Bhopal462003 India

Electronic Health Records (EHR) are crucial for the success of digital healthcare, with a focus on putting consumers at the center of this transformation. However, the digitalization of healthcare records brings along security and privacy risks for personal data. The major concern is that different countries have varying standards for the security and privacy of medical data. This paper proposed a novel and comprehensive framework to standardize these rules globally, bringing them together on a common platform. To support this proposal, the study reviews existing literature to understand the research interest in this issue. It also examines six key laws and standards related to security and privacy, identifying twenty concepts. The proposed framework utilized K-means clustering to categorize these concepts and identify five key factors. Finally, an Ordinal Priority Approach is applied to determine the preferred implementation of these factors in the context of EHRs. The proposed study provides a descriptive then prescriptive framework for the implementation of privacy and security in the context of electronic health records. Therefore, the findings of the proposed framework are useful for professionals and policymakers in improving the security and privacy associated with EHRs. © 1975-2011 IEEE.

关键词： K-means clustering

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Synthesis of Wideband Bandpass Filter With In-Band Complex Transmission Zeros for Frequency- and Attenuation-Reconfigurable In-Band Notch

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IEEE Transactions on Microwave Theory and Techniques 2024年第2期72卷 1162-1175页

作者： Liu, Bin Li, Kun Chi, Pei-Ling Yang, Tao University of Electronic Science and Technology of China School of Electronic Science and Engineering Chengdu610054 China National Chiao Tung University Department of Electrical and Computer Engineering Hsinchu300 Taiwan

A novel synthesis method for wideband bandpass filter (BPF) with two in-band conjugate complex transmission zeros is proposed for realizing frequency- and attenuation-reconfigurable in-band notch. A new characteristic function with wideband bandpass response is constructed by merging two BPFs with relatively narrow bandwidths. With the newly constructed characteristic function, complex transmission zeros will be introduced in the filter passband, facilitating the generation and control of the in-band notch. Moreover, quasi-Chebyshev filtering response (with quasi-equal ripple level) is also guaranteed in the whole passband. Based on the new characteristic function, a series of filter topologies can be derived using matrix similarity transformations. By only tuning the resonant frequencies of particular resonators, these topologies can exhibit wideband bandpass responses with frequency- and attenuation-reconfigurable in-band notch. To demonstrate the proposed techniques, one prototype of the wideband BPF using waveguide resonators is designed, simulated, and fabricated. The fabricated wideband BPF exhibits a passband frequency from 8.12 to 11.76 GHz with one transmission zero at 13.36 GHz and a reconfigurable in-band notch with frequency tuning from 9.3 to 10.4 GHz and attenuation tuning from 2 to 60 dB. The simulated and measured results are in good agreement, validating the proposed technique. © 1963-2012 IEEE.

关键词： Topology

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