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Predicting Pest Infestation Patterns with Graph Convolutional Networks (GCN) in Precision Farming 3

Predicting Pest Infestation Patterns with Graph Convolutiona...

引用

3rd IEEE international conference on automation and Computation, AUTOCOM 2025

作者： Sireesha, Marri Hussein, Laith Manju, M. Johri, Prashant Kuppuraj, T. Aanandha Saravanan, K. Department of Computer Science and Engineering CMR Technical Campus Hyderabad India College of technical engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Kongu Arts and Science College Department of Computer Science TamilNadu Erode India School of Computing Science and Engineering Galgotias University Greater Noida India Karpagam Academy of Higher Education Department of Computer Applications Coimbatore India Veltech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798331542375

Due to the increases pest impacts on agricultural productivity, effective pest prediction models are required for efficient pest control in precision farming. The framework outlined in this research uses a Graph Convolutional Network (GCN) to estimate pest infestation by exploiting spatial and temporal relationships present in agri-ecosystems. The methodology combines weather, soil, pest, and crop health data into a graph-based representation of spatial units, and the directed connections between them that reflect their proximity and climatic similarity. The GCN converts these graphs to learn such complex relationship as the infestation prediction at various severity levels. The proposed model has produced a better accuracy of 94.8%, better precision of 95.2%, better recall of 94.5% and better F1-score of 94.8% as compared from Random forest, SVM, LSTM, CNN as per the comparison of table 3. Comparing them focuses on graph construction approaches and temporal aspects, mixed P/S and temporal emb has improved the model performance. This framework is practical for further pest management and employing the result without harming the environment. The results show the effectiveness of GCNs for use in pest prediction in precision farming and the opportunity to develop sustainable and scalable data-based agriculture. © 2025 IEEE.

关键词： Weed control

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Integrating Dynamic Access control in Hybrid Cloud Environments for Enhanced Security and Load Balancing

Integrating Dynamic Access Control in Hybrid Cloud Environme...

引用

automation and Computation (AUTOCOM), international conference on

作者： Lakshya Swarup Saritha Srinivasmurthy Raghotham B.P. Singh J Albert Mayan. Aseem Aneja Swadhin Ku. Barisal Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Management - UG Management JAIN (Deemed to be University) Bangalore Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Applications Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Hybrid cloud environments come into play more each month, this service is becoming increasingly important for security and load balancing. Hybrid cloud environments are too fluid to manage with traditional access control methods and load-balancing solutions. This is where dynamic access control integration comes in. Dynamic access control is a process that enables organizations to define and enforce access controls based on the context of the request, not merely user identities. This could be applied in a hybrid cloud environment to implement access controls based on the whereabouts of users, the kind of data, and the threat level. This is intended to add an extra layer of security as we can limit the users who have permission to access specific resources. You can add dynamic access control to your load-balancing solutions for resource efficiency and performance improvements. It also reduces the possibility of service outage, as more accurate granular access control based on lower visibility to higher certain users making fewer requests at a time than another set can simplify algorithms that tombstone or down-replicated out-of-date servers and thus carve their load across racks of machines.

关键词： Access control Cloud computing Fluids Heuristic algorithms process control Organizations Data breach Load management Dynamic scheduling Servers

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Comparative study of Battery Fault Detection using Machine Learning Algorithm

Comparative study of Battery Fault Detection using Machine L...

引用

Advancements in Electrical, Electronics, Communication, computing and automation (ICAECA), international conference on

作者： M. Prasanth P. Viswanath P. Muniswaran G. Anushree Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

This Paper shows comparative study of individual cell fault detection in battery pack by predicting the fault using real time data from parameter of SOC of each cell that is present in the battery pack. Compare the real time data with the predicted dataset using different Machine learning algorithm such as K-Nearest Neighbours and Random Forest algorithm. The NodeMCU acts as a controller which retrieves the data from voltage sensor of individual cell in the battery pack and given to the cloud. The cloud stores pretrained algorithm of Machine Algorithm Model and dataset of predicted *** comparing the real time data from the controller and predicted data from dataset from the confusion matrix which shows the accuracy of the algorithm and also results the faulty cell in the cloud the data is returned to the controller and also displays the faulty cell in the LCD display which is connected to controller.

关键词： Cloud computing Machine learning algorithms Fault detection Voltage Prediction algorithms Real-time systems Batteries Telecommunication computing State of charge Voltage control

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Application of Particle Swarm Optimization Algorithm Based on Adaptive Inertia Adjustment Strategy in Scheduling of the Coking process 26

Application of Particle Swarm Optimization Algorithm Based o...

引用

26th international conference on Industrial Technology, ICIT 2025

作者： Chen, Yiheng Yin, Fan Chen, Xiaochong Ren, Yi Hu, Jie Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331521950

The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an efficient coke pushing plan. To address this issue, this paper proposes a scheduling method based on the particle swarm optimization algorithm. Firstly, the fuzzy c-means clustering is utilized to categorize actual operating conditions as either normal or abnormal, thereby facilitating the scheduling of pushing plan under disparate conditions. Subsequently, the scheduling problem for the pushing plan is transformed into a traveling salesman problem, and scheduling models under various conditions are established. Finally, to accelerate the convergence and enhance the algorithm's global search capability, an adaptive inertia adjustment strategy is employed to dynamically regulate the velocity and position of particles. The proposed method has been implemented in the coking process. Through the analysis of application results, the completion coefficient of pushing plan has been increased by 4.25%, demonstrating that the proposed has advantages in scheduling the pushing plan during the actual coking process. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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SHWCIM: A Scalable Heterogeneous Workload computing-in-Memory Architecture

SHWCIM: A Scalable Heterogeneous Workload Computing-in-Memor...

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Design, automation and Test in Europe conference and Exhibition

作者： Yanfeng Yang Yi Zou Zhibiao Xue Liuyang Zhang School of Microelectronics South China University of Technology Guangzhou China National Key Laboratory of Spintronics Hungzhou International Innovation Institute Beihang University Hangzhou China

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

This study introduces HWCIM, a SRAM-based computing-In-Memory core, and SHWCIM, a CIM-capable Coarse-Grained Reconfigurable Architecture, to enhance re-source utilization, multi-functionality, and on-chip memory size in SRAM-based CIM designs. Evaluated using the SMIC 55nm process, HWCIM achieves 1.6x lower power, 2.8x higher energy efficiency, and up to 4.1x smaller area compared to previous CIM and CGRA works. Additionally, SHWCIM delivers an average 105.9x speedup over existing CGRAs and consumes 2-5x less energy than the Nvidia A40 GPU on realistic workloads.

关键词： Graphics processing units Europe In-memory computing Common Information Model (computing) Energy efficiency Vectors System-on-chip Reconfigurable architectures Common Information Model (electricity) Resource management

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Biometric and IoT-based Vehicle Security Systems: Advancements and Applications

Biometric and IoT-based Vehicle Security Systems: Advancemen...

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Advancements in Electrical, Electronics, Communication, computing and automation (ICAECA), international conference on

作者： S. Umamaheswari A.G. Mohandas Gandhi V.Jagannath Dept of Electronics and Communication Engineering Kumaraguru College of Technology Coimbatore India Department of Mechanical Engineering RVS Technical Campus Coimbatore

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Biometric authentication is a safe and effective access control method used in today's vehicles. This work discusses an authentication system based on dual-modal verification with face and fingerprint recognition for improved security and convenience to the user. Deep learning is used to train recognition models with a publicly accessible biometric dataset. Preprocessing operations like noise removal, data augmentation, and class balancing are used to make the models robust. Experimental outcomes show that face recognition is found to have more accurate performance than fingerprint recognition, along with a discussion of factors contributing to this performance. To check real-world feasibility, we also test the system's real-time operation, such as time taken for processing and network latency in an IoT-based setup. Security issues, like spoofing attacks, are handled by liveness detection techniques. Comparative study with other biometric modalities, such as iris recognition, shows the efficacy of the presented system.

关键词： Access control Training Accuracy Face recognition Biological system modeling Scalability Authentication Fingerprint recognition Telecommunication computing Reliability

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An IoT-Based Data Logging System to Ensure Consistent Dairy Product Quality Through Monitoring and Cloud Analytics

An IoT-Based Data Logging System to Ensure Consistent Dairy ...

引用

Disruptive Technologies (ICDT), international conference on

作者： Praveen Kumar Malik Jaishanker Prasad Keshari Gaurav Sethi Ashish Singh Chauhan Nagendar Yamsani Shelej Khera School of Electronics and Electrical Engineering Lovely Professional University Phagwara Punjab India Government Engineering College Sheikhpura Bihar Engineering University Patna Bihar India Uttaranchal University Dehradun Uttarakhand India School of Computer Science and Artificial Intelligence SR University Warangal India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Pasteurization is intended to eliminate harmful microorganisms while maintaining the quality of milk and its other crucial constituents. As the consumption of dairy products increases in various regions across the globe, it becomes important to ensure that pasteurization is performed according to the set standards. Currently, the most major limitation of pasteurization processes is that they are overly dependent on the manual supervision and control. Besides the quality of the final product, this is a crucial factor for maintaining safety throughout. Furthermore, because they do not typically provide accurate data relating to the deviation of the process over a period of time. Nowadays having more of an automated solution, as well as computing capabilities of all systems in the cloud, has reduced redundancies across processes. In relation to the dairy sector, having those technologies enable efficiencies with respect to the precision, uniformity, and regulation of the entire pasteurization process. Consequently, the transfer to the automated systems undoubtedly improves operational performance as well as reduces errors related to the manual sanitation of the parameters particularly temperature and flow rate, which are critical and have to be maintained. Also, the factor of timely service is simplified because the machine is able to analyze data instantly, thus increasing productivity by reducing the downtime of operations.

关键词： Temperature sensors Temperature measurement Cloud computing Dairy products automation process control Real-time systems Monitoring Standards Business

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19th international Symposium on Visual computing, ISVC 2024

19th International Symposium on Visual Computing, ISVC 2024

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19th international Symposium on Visual computing, ISVC 2024

ISBN: (纸本)9783031773914

The proceedings contain 73 papers. The special focus in this conference is on Visual computing. The topics include: AFIDAF: Alternating Fourier and Image Domain Adaptive Filters as an Efficient Alternative to Attention in ViTs;multi-Actor-Critic Deep Reinforcement Learning with Hindsight Experience Replay;improving Zero-Shot Template-Based 6D Pose Estimation with Geometric Features;contrastive Loss Based on Contextual Similarity for Image Classification;estimation of Global Illumination Using Cycle-Consistent Adversarial Networks;anisotropic Point Synthesis by Example;3D Fluid Shape control by Direct Manipulation;an Epithelium-Inspired Deformation Modeling Framework for 4D Sheets;hybrid Voxel Formats for Efficient Ray Tracing;PIEPredict++: An Improved Pedestrian Intention Estimation Model Incorporating Comprehensive Environment Information;infant Video Interaction Recognition Using Monocular Depth Estimation;real-Time Predictor in Two-Players Fighting Game via Vision Transformer;explainable Action-Recognition Based Approach for Unsupervised Video Anomaly Detection;LORTSAR: Low-Rank Transformer for Skeleton-Based Action Recognition;Pedestrian Tracking Using Ankle-Level 2D-LiDAR Based on ByteTrack;Human Pose Estimation-Based ID Assignment Method in the Wild: A Real-Time Approach;RGB-T-UV Multi-modal Object Tracking Based on Transformer Network;evaluating the Impact of Dehazing Algorithms on Visual Object Tracking Performance;MEM: Mask Enhancement Model for Video Object Segmentation;analysis automation for High Explosive Breakout Symmetry;CLAP: Concave Linear APproximation for Quadratic Graph Matching;generalizing Neural Radiance Fields for Robust 6D Pose Estimation of Unseen Appearances;effectiveness of Residual Noise Based Methods for Single Image Based Morphing Attack Detection: A Comparative Study;black Box Adversarial Face Transformation Network;bi-Feature Selection Deep Learning-Based Techniques for Speech Emotion Recognition;activeConfusion: Efficient Cold-Start

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19th international Symposium on Visual computing, ISVC 2024

19th International Symposium on Visual Computing, ISVC 2024

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19th international Symposium on Visual computing, ISVC 2024

ISBN: (纸本)9783031773884

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Performance Optimization of Double-Tail Dynamic controlled Comparator at 90 nm Technology

Performance Optimization of Double-Tail Dynamic Controlled C...

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Advancements in Electrical, Electronics, Communication, computing and automation (ICAECA), international conference on

作者： Jaspar Vinitha Sundari T Santhosh P Viveksriram A T Jairuban K K. Paramasivam Department of Electronics and Communication Engineering Kumaraguru College of Technology Coimbatore India Department of Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Analog to digital conversion Units with low power consumption and fast speed have long been in demand for efficient conversion systems. With respect to this demand to increase power efficiency and speed, a double tailed dynamic controlled comparator that offers reduced delay is studied. During the meticulous study through various simulations, significant reduction in technology and sizing ratios in comparators offers less power consumption. The comparator under study [11] resimulated in 90 nm CMOS technology offers a power consumption of 3.60 µW, energy efficiency of 10.03 fJ and a delay of 68. 11 ps. process corner and Monte Carlo simulations with a 70.29 ps delay are used to confirm the comparator's resilience.

关键词： Semiconductor device modeling Power demand Monte Carlo methods Telecommunication traffic Energy efficiency Delays Telecommunication computing Analog-digital conversion Optimization Resilience

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