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检索条件"任意字段=International Conference on Computer Science and Service System"

共 385859 条记录，以下是4901-4910 订阅

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Enhancing IoT-Based Smart Farming Security with a Hybrid GRU Intrusion Detection system

Enhancing IoT-Based Smart Farming Security with a Hybrid GRU...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE conference on

作者： Sivakumar Nagarajan S. Vijay S. Karthi RVS Praveen Ramesh Vijaya Babu K Burri Naresh Technical Architect I & I Software Inc Bethlehem USA Department of Data Science Sacred Heart College (Autonomous) Tamilnadu India Department of Computer Science and Engineering V.S.B. Engineering College Karur Tamilnadu India Director Digital Engineering & Assurance LTIMindtree Limited Hyderabad Telangana India SRKR Engineering College Bhimavaram Andhra Pradesh India Department of CSE - Cyber Security CVR College of Engineering Hyderabad Telangana India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The growing use of IoT devices in smart agriculture makes the industry vulnerable to several cyber risks. This study introduces an innovative hybrid Intrusion Detection system (IDS) utilising Gated Recurrent Units (GRUs) to improve the security of IoT-enabled smart agriculture. compared to current LSTM and CNN-based intrusion detection systems, the proposed model effectively incorporates sequential data dependencies, hence minimising false positives and enhancing detection accuracy. Experimental findings indicate that the suggested model surpasses conventional techniques, with an accuracy of 97.5%, an F1 score of 0.96, and a recall of 0.97. These developments create a strong, efficient, and scalable solution for safeguarding IoT-based agricultural systems from cyber-attacks.

关键词： Smart agriculture Technological innovation Accuracy Computational modeling Scalability Intrusion detection Internet of Things Object recognition Protection Long short term memory

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Look Further: Socially-Compliant Navigation system in Residential Buildings 25

Look Further: Socially-Compliant Navigation System in Reside...

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ACM/IEEE international conference on Human-Robot Interaction (HRI)

作者： Akira Shiba Marina Obata Nathan Kau Zoltan Beck Rishi Shah Michael Sudano Sabrina Lee Woven by Toyota Inc Japan

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

The distance at which a mobile robot reacts to a person strongly impacts various qualities of the human-robot interaction. In this paper, we focus on the navigation of a mobile delivery robot platform in a residential indoor hallway environment. Social navigation methods typically focus on avoiding uncomfortable human-robot interactions, such as when a robot encroaches on someone's personal space. Since personal space has been shown to be in the range of just a few meters, social navigation methods typically focus on deconflicting and resolving these short-range interactions. In this work, however, we demonstrate that by extending the reaction distance to over eight meters, far beyond the typical interaction distance, we can improve the human's perception of the robot's motion. We introduce the Proactive Lane-Changing (PLC) motion pattern and a navigation system that leverages it to react to people at an increased distance. This pattern consists of changing the robot's lateral position as it navigates down the hallway from the center to the side at an eight-meter distance from an oncoming person. We conducted a user study with 42 participants to assess their impressions of the delivery robot based on three service objectives: safety, smoothness, and politeness. In the straight hallway scenario (Frontal Approach), results showed significant improvement in each of these three objectives compared to typical motion patterns found in the literature: slowing down, stopping, and reactive collision avoidance in the proximity of a person. In contrast, in the intersection (Blind Corner) scenarios, none of the approaches performed significantly better than any other, with participants having a diverse range of preferences among robot motion patterns.

关键词： Robot motion Meters Navigation Buildings Human-robot interaction Safety Mobile robots Collision avoidance Logistics

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Transfer Learning Based Deep Learning Model for the Identification of Facial Expression

Transfer Learning Based Deep Learning Model for the Identifi...

引用

Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Gothai Ekambaram Thamilselvan Rakkiannan Natesan P Jayakkavin E Dept of Computer Technology Kongu Engineering College Perundurai Tamilnadu India Dept Computer Science and Engineering Kongu Engineering College Perundurai Tamilnadu India Dept of Artificial Intelligence Kongu Engineering College Perundurai Tamilnadu India Kongu Engineering College Perundurai Tamilnadu India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

The changes that occur on a person's face to communicate their internal emotional states, intentions, or social cues are known as facial expressions. The human face is a crucial tool for communicating with other sand determining their emotional states from their facial expressions. Because it is essential in human interaction, real-time facial expression analysis has become a research topic. Face reading is used in various areas, such as social interaction, emotional intelligence, computer vision, biometric security, and social intelligence. This work focuses on an overview of the various facial expression recognition methods and their advantages and disadvantages. The body's natural response to internal and external stimuli is emotional. Whether it's a common emotion, stress, anger, etc., it can cause serious harm to health. Both psychological and physiological manifestations of these responses emotions and facial expressions appear. The model is used to analyse real-time snapshots of the user's face and detect the existence of stressful information as well as convolutional neural network capable of recognizing emotions, and facial emotions, a proof of concept for the emotion detector was developed. The classification model was developed via transfer learning and fine-tuning. For deep learning process, two classifier designs were taken into account. Following a numberoftests, it was shown that a classifier built using a Separable Conv2D convolutional layer and LeakyReLU as activation method CNN performed the best in categorising emotions. The results are encouraging, and the proposed emotion detection system is minimallyintrusive as it only needs a webcam to monitor the user's facial expressions.

关键词： Training Deep learning Emotion recognition Accuracy Face recognition Transfer learning Real-time systems Convolutional neural networks Biomedical monitoring Testing

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The Research of Brain Network Structure Fault Tolerance 24

The Research of Brain Network Structure Fault Tolerance

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Proceedings of the 2024 4th international conference on Big Data, Artificial Intelligence and Risk Management

作者： Qiangwei Xin School of Computer Science Xianyang Normal University Xianyang Shaanxi China

ISBN: (纸本)9798400709753

The brain network has high robustness and fault tolerance, and even if some neurons or connections are damaged, the overall function can still be maintained. Artificial intelligence systems can design systems with similar robustness and fault tolerance by imitating this structure and function. For example, deep learning models can still make effective judgments when dealing with partial input data loss or noise. In the brain network, redundancy and multipath connections are important mechanisms for fault tolerance, allowing information to propagate through different paths, ensuring the stability and continuity of the network's functionality. Artificial intelligence systems also adopt similar fault-tolerant mechanisms, improving system reliability and stability through redundant design, multi-layer structure, and distributed processing.

关键词： Artificial intelligence

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Peer-to-Peer Integrated Smart Gardening Automation Using Cloud Technology with Real-Time Environmental Monitoring and Logging via Blynk Cloud Dashboard

Peer-to-Peer Integrated Smart Gardening Automation Using Clo...

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2025 international conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Malik, Praveen Kumar Bharti, Veena Misra, Neeti Yamsani, Nagendar Mahajan, Anshul Singh, Parulpreet School of Electronics and Electrical Engineering Lovely Professional University Punjab Phagwara India Raj Kumar Goel Institute of Technology Ghaziabad India Uttaranchal Institute of Management Uttaranchal University Department of Management Uttarakhand Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798331527495

The authors of this article discuss the holistic method of automation of gardening operations based on IoT technology that allows real time environmental factors to be monitored, decisions to be made based on data, and those decisions to be executed at a distance. The objective of the system is to minimize the amount of water used, to improve the state of the plants, and ultimately to allow the users of the system to control their gardens from anywhere in the world with as little effort as possible. The concept makes use of the continuously monitored network of sensors to observe important parameters like soil moisture, temperature, humidity, light intensity and rainfall among others. After being received, this information is up to date and the system will use this data to manage irrigation and lighting systems for the plants efficiently. Also, the support of this cloudbased platform is essential today as it allows the users to look up the parameters in their garden remotely and go for manual intervention when required. All the advantages of cloud technology provide remote control of the system but also all the historical data sets which are important trends in future decision making. © 2025 IEEE.

关键词： Green computing

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Leveraging Neural Networks with BiLSTM and CNN Models for Enhanced HR Management Practices

Leveraging Neural Networks with BiLSTM and CNN Models for En...

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Integrated Circuits and Communication systems (ICICACS), IEEE international conference on

作者： Yamini Kalva Anuradha Parasar Rajlaxmi Pramod Pujar K. Balasubramanian Zameer Pasha S. Ramya Department of Computer Science and Engineering Sri Ramachandra Institute of Higher Education and Research Chennai India School of Liberal Education Galgotias University Dankaur India Department of Marketing Indira School of Business Studies PGDM Pune India Department of Computer Applications Kalasalingam Academy of Research and Education- Deemed to be University Krishnankoil India Department of Management St. Claret College (Autonomous) Bengaluru India Department of Artificial Intelligence and Machine Learning M.Kumarasamy College of Engineering Karur India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

The most valuable asset of any business is its employees. Even with technological advances, organizations rely heavily on human resources for system administration. An increasingly competitive sector makes managing and retaining talented workers difficult. An organization's ability to develop, survive, and compete depends on its employees' skills. These challenges can be overcome using preprocessing, feature extraction, and model training. Data preparation for machine learning is necessary yet time-consuming. Features selection is critical since it enhances accuracy and reduces overfitting. CNN-BiLSTM trained the model. The CNN- BiLSTM model outperformed BiLSTM and CNN. The model's 90.62 percent accuracy showed it could handle HR tasks. For effective human resource management, this study recommends sophisticated machine learning models. Today's businesses need reliable tools for managing and keeping people, and the CNN-BiLSTM model helps.

关键词： Training Accuracy Bidirectional long short term memory Machine learning Aging Feature extraction Convolutional neural networks Integrated circuit modeling Retirement Overfitting

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Energy Efficient and SecurityAware Task off Loading for Multi-Tier Edge Cloud Computing systems

Energy Efficient and SecurityAware Task off Loading for Mult...

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Intelligent systems and Computational Networks (ICISCN), international conference on

作者： S. Divya S. Saranya Department of Computer Science and Engineering Mahendra Engineering College Namakkal India

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529253

The massive progression of the multi-tier edge cloud computing systems integration has created the possibility of data orchestration and resource control in edge and cloud layers. However, there are many shortcomings, including inappropriate methods of scheduling tasks and security breaches that prevent scalability. To solve these problems, we designed an energy-efficient and security-aware task offloading framework for multi-tier edge cloud computing. Firstly, we estimate the energy ratio of tasks using a Fuzzy Logic Energy Management (FL-EM) algorithm and distribute resources according to different layers. Subsequently, the task-offloading parallel squirrel (TO-PS) method is used to effectively extend the task with better energy consumption and computational efficiency. Finally, it is decided to protect the work data using the Provable Energy-Aware Cryptographic Security (PE-ACS) algorithm. The proposed algorithm achieves a 96.7% success rate in protecting high-level data from cybercrime. Additionally, it enhances security and task performance while reducing energy consumption in multi-tier edge cloud computing systems.

关键词： Cloud computing Energy consumption Costs Processor scheduling Scalability Loading system integration Throughput Energy efficiency Resource management

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Content-Aware Dynamic Superpixel Segmentation

Content-Aware Dynamic Superpixel Segmentation

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Tingyu Zhao Bo Peng Zhenguang Zhang Daipeng Yang Xi Wu School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China School of Computer Science Chengdu University of Information Technology Chengdu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In recent years, deep learning-based superpixel segmentation methods derived from SLIC have made significant progress by utilizing uniform grid-based seed initialization. However, due to the unequal pixel space variation rates in natural images, methods based on uniform grid initialization struggle to balance the compactness of superpixels in flat regions with the boundary adherence in non-flat regions. Inspired by the visual attention model based on saliency in the human visual system, we propose a content-aware dynamic superpixel segmentation network. Specifically, we propose a seed initialization strategy guided by geodesic distance transformation and design two segmentation heads for different scales, which are used for joint network training to encourage the network to focus more on areas with texture variations without causing unnecessary segmentation in flat regions. Extensive experiments on BSDS500 and NYUv2 datasets demonstrate that our method achieves state-of-the-art performance.

关键词： Training Image segmentation Visualization Head Visual systems Signal processing Acoustics Speech processing

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Enhancing Data Security and Privacy in Cloud Computing: A Survey of Modern Techniques

Enhancing Data Security and Privacy in Cloud Computing: A Su...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： N. Suganya P. Gouthami R. Sathiya S. Sivaranjani M. Murugesan Department of Computer Science and Business Systems Dr. N.G.P. Institute of Technology Coimbatore India Department of Information Technology Thangavelu Engineering College Chennai India Departement of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India Departement of Electrical and Electronics Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

A computing system that is based on the internet and offers users all resources as on-demand services. Servers, storage, databases, software, and networking are among these on-demand services. Usually, the user must pay for the use of the resources; they are not their property. The number of people using this technology is increasing dramatically as a result of these features. Although it has benefits, cloud computing poses certain security and privacy risks. The authorized user's data can be stolen easily. This current research thoroughly investigates modern strategies to these problems, highlighting identity management protocols, effective encryption and blockchain-based solutions. The article identifies research gaps, focuses attention to the inadequacies of current approaches, and recommends the possible ways to improve the efficiency, scalability and trustworthiness.

关键词： Surveys Cloud computing Data privacy Privacy Reviews Scalability Software Encryption Servers Identity management systems

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Dynamic Climate Hazard Prediction: A Real-time Web Application

Dynamic Climate Hazard Prediction: A Real-time Web Applicati...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE conference on

作者： Diya Dubey Rohit Kumar Nandu C Nair Dept. of Electrical and Electronics Engineering Bengaluru Amrita Vishwa Vidyapeetham Amrita School of Engineering India Dept. of Computer Science Engineering Bengaluru Amrita Vishwa Vidyapeetham Amrita School of Computing India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The model for developing the predictive climate resilience and disaster management in the most vulnerable regions is discussed in the current paper. At its base, the model enhances climate hazard forecasting by real-time data gathered through API. Training on historic and live meteorological and environmental data, the model auto-molds itself to keep pace with the evolving climate pattern and makes reliable prediction. Besides, for distributing warnings and notifications in timely fashion, a user-oriented application based on Flask is developed. This might be a comprehensive system of information at the community level that aids in proactive preparedness with effective response strategies. The proposed model and application enhance big goals of climate resilience and disaster mitigation by proving accurate and real-time forecasting, easily accessible communication regarding potential risks.

关键词： Training Technological innovation Predictive models Real-time systems Hazards Data models Reliability Forecasting Meteorology Resilience

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