The proceedings contain 53 papers. The special focus in this conference is on intelligentsystems in computing and Communications. The topics include: Towards Hands-Free computing: AI Virtual Mouse Interface Powered b...
ISBN:
(纸本)9783031756047
The proceedings contain 53 papers. The special focus in this conference is on intelligentsystems in computing and Communications. The topics include: Towards Hands-Free computing: AI Virtual Mouse Interface Powered by Gestures;smartAgro: Precision Yield Prediction, Crop Insights, and Real-Time Dashboard;Artificial Intelligence with MRI-Guided Radiation Therapy for Cancer Treatment;Software Requirements to UML Class Diagrams Using Machine Learning and Rule-Based Approach;CFALEA_LSTM: Adaptive Lotus Effect Algorithm Enabled Long Short-Term Memory for Rainfall Prediction Using Time Series Data;a Deep Learning Survey on Diseases Prediction and Detection in Health Care;fault Diagnosis in Belts Using Signal Processing Techniques and Machine Learning;machine Learning Techniques Based Chronic Kidney Disease Detection with Performance Analysis of Fuzzy Rough Set and Correlation Attribute Selection;segmentation and Classification of Unharvested Arecanut Bunches Using Deep Learning;enhanced Satellite Image Fusion Using Deep Learning and Feature Extraction Techniques: A Survey;intelligent Aircraft Antiskid Braking systems – A Review;artificial Neural Networks Applied in the Detection of Breast Cancer;supervised and Unsupervised Learning Techniques for Malware Classification Based on Opcode Frequency Features;predictive Analytics for Diagnosing Alzheimer’s Disease Using Artificial Intelligence and Machine Learning Algorithms;A Comprehensive Study on Artificial Intelligence (AI) Driven Internet of Healthcare Things (IOHT);predictive Models for the Early Diagnosis and Prognosis of Knee Osteoarthritis Using Deep Learning Techniques;predicting Salinity Resistance of Rice at the Seedling Stage: An Evaluation of Transfer Learning Methods;Multi-camera HD Pedestrian Dataset for Person Detection and Re-identification;Fire Detection System Using Deep CNN.
The proceedings contain 53 papers. The special focus in this conference is on intelligentsystems in computing and Communications. The topics include: Towards Hands-Free computing: AI Virtual Mouse Interface Powered b...
ISBN:
(纸本)9783031756078
The proceedings contain 53 papers. The special focus in this conference is on intelligentsystems in computing and Communications. The topics include: Towards Hands-Free computing: AI Virtual Mouse Interface Powered by Gestures;smartAgro: Precision Yield Prediction, Crop Insights, and Real-Time Dashboard;Artificial Intelligence with MRI-Guided Radiation Therapy for Cancer Treatment;Software Requirements to UML Class Diagrams Using Machine Learning and Rule-Based Approach;CFALEA_LSTM: Adaptive Lotus Effect Algorithm Enabled Long Short-Term Memory for Rainfall Prediction Using Time Series Data;a Deep Learning Survey on Diseases Prediction and Detection in Health Care;fault Diagnosis in Belts Using Signal Processing Techniques and Machine Learning;machine Learning Techniques Based Chronic Kidney Disease Detection with Performance Analysis of Fuzzy Rough Set and Correlation Attribute Selection;segmentation and Classification of Unharvested Arecanut Bunches Using Deep Learning;enhanced Satellite Image Fusion Using Deep Learning and Feature Extraction Techniques: A Survey;intelligent Aircraft Antiskid Braking systems – A Review;artificial Neural Networks Applied in the Detection of Breast Cancer;supervised and Unsupervised Learning Techniques for Malware Classification Based on Opcode Frequency Features;predictive Analytics for Diagnosing Alzheimer’s Disease Using Artificial Intelligence and Machine Learning Algorithms;A Comprehensive Study on Artificial Intelligence (AI) Driven Internet of Healthcare Things (IOHT);predictive Models for the Early Diagnosis and Prognosis of Knee Osteoarthritis Using Deep Learning Techniques;predicting Salinity Resistance of Rice at the Seedling Stage: An Evaluation of Transfer Learning Methods;Multi-camera HD Pedestrian Dataset for Person Detection and Re-identification;Fire Detection System Using Deep CNN.
Human-centered intelligentsystems (HCIS), which are at the forefront of the AI and HCI fields, are dedicated to enhancing human experiences and interactions with technology. HCIS are designed to be intuitive, respons...
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Human-centered intelligentsystems (HCIS), which are at the forefront of the AI and HCI fields, are dedicated to enhancing human experiences and interactions with technology. HCIS are designed to be intuitive, responsive, and adaptable to human needs and preferences, aiming to empower users and foster positive interactions. By utilizing AI techniques, such as machine learning, natural language processing, and computer vision, HCIS aims to make technology more accessible and beneficial across various industries and domains.
The development of network technology has laid a solid foundation for the network transmission of integrated media. The amount of information in integrated media is large, and it has the characteristics of real-time, ...
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The massive progression of the multi-tier edge cloud computingsystems integration has created the possibility of data orchestration and resource control in edge and cloud layers. However, there are many shortcomings,...
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Over the years, Cloud computing is becoming increasingly popular due to the continually changing technology. The primary goal of the cloud computing network is to offer consumers pay-per-use usage of on-demand process...
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In the cloud computing environment, existing research has mostly focused on improving traditional scheduling algorithms, lacking effective strategies for dealing with dynamic loads and complex workflows, resulting in ...
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In modern avionics system Testing and Verification are very important criteria. With the advantage of Field Programmable Gate Array (FPGA), power sub systems are more intelligent with advance features. Advance power s...
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Vehicular Edge computing (VEC) is an emerging computing paradigm that serves as a specific application of Mobile Edge computing (MEC) in intelligent transportation systems. As a core technology of VEC, task offloading...
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Vehicular Edge computing (VEC) is an emerging computing paradigm that serves as a specific application of Mobile Edge computing (MEC) in intelligent transportation systems. As a core technology of VEC, task offloading improves computing efficiency and service quality by offloading computing tasks from vehicular devices to edge nodes. However, the high mobility of vehicles, heterogeneity of resources, and real-time requirements present significant challenges for task offloading. To address the issue of reducing overall system latency and increasing the offloading success rate in multi-task offloading, we propose a task offloading scheme combining Deep Reinforcement Learning (DRL) and Kuhn-Munkres (KM) Matching algorithm, named the PDQKM offloading scheme. Firstly, to mitigate the delay caused by frequent Roadside Unit (RSU) handovers, we propose a method to detect whether a vehicle is within the coverage area of the RSU. This method filters out unreasonable offloading decisions, avoiding the overhead associated with frequent RSU handovers. Secondly, the combination of DRL and the KM matching algorithm leverages the strengths of both approaches. DRL provides initial offloading strategies in highly dynamic and high-dimensional decision environment. Although DRL may get stuck in local optima, it can quickly adapt to environmental changes. The KM matching algorithm, a classic solution for perfect task-resource matching, performs global optimization on the initial strategies provided by DRL. This integration overcomes the limitations that a single algorithm might have. Finally, to effectively coordinate and manage the heterogeneous resources of RSU, we utilize an improved KM matching algorithm to update computational resources in real time, enhancing matching efficiency. Experimental results demonstrate that PDQKM outperforms comparable offloading schemes in terms of overall system latency and offloading success rate optimization.
Wireless Sensor Networks (WSN) that work hand in hand with IoT are crucial for contemporary smart city solutions. However, as these are dynamic and decentralized, they pose additional issues related to network data an...
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