Edge computing has transformed technology by enabling seamless connections between IoT devices, but it also introduces significant security challenges. EC is crucial for providing minimal latency processing and reduci...
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Cyber-physical swarms represent a paradigm shift in distributedsystems, mirroring characteristics akin to natural swarms, such as self-organization, scalability, and fault tolerance. this paper delves into these comp...
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ISBN:
(纸本)9798350369458;9798350369441
Cyber-physical swarms represent a paradigm shift in distributedsystems, mirroring characteristics akin to natural swarms, such as self-organization, scalability, and fault tolerance. this paper delves into these complex systems, characterized by vast networks of cyber-physical entities with limited environmental awareness, yet capable of exhibiting emergent collective behaviors. these systems encompass a diverse array of scenarios, ranging from swarm robotics to the interconnectivity in smart cities, as well as the collaboration among augmented humans. the engineering of such systems presents unique challenges, primarily due to their intricate complexity and the spontaneous nature of their collective behaviors. this paper aims to dissect these challenges, offering a clear delineation of potential approaches. We present a comprehensive analysis, shedding light on the intricacies of engineering cyberphysical swarms and discussing modern solutions in engineering collective applications for such systems.
this paper presents a distributed learning approach designed to assist physicians in diagnosing diseases based on a patient's current health status, clinical history, and test results. the methodology relies on ne...
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ISBN:
(纸本)9798350369458;9798350369441
this paper presents a distributed learning approach designed to assist physicians in diagnosing diseases based on a patient's current health status, clinical history, and test results. the methodology relies on neural network models and supervised classifiers to identify illnesses. It utilizes word embedding to capture semantic relationships among hospital admissions, symptoms, and diagnoses. Additionally, it introduces a method to evaluate the connection between different diagnoses based on symptom similarity, aiding in prediction tasks. Experimental results on a real-world Electronic Health Records (EHR) dataset showcase the effectiveness and accuracy of the proposed technique, providing clinically relevant interpretations. these findings suggest promising avenues for future enhancements of the framework as a valuable diagnostic tool.
the proceedings contain 6 papers. the topics discussed include: scheduling across multiple applications using task-based programming models;DEMAC: a modular platform for HW-SW co-design;CODIR: towards an MLIR codelet ...
ISBN:
(纸本)9781665422765
the proceedings contain 6 papers. the topics discussed include: scheduling across multiple applications using task-based programming models;DEMAC: a modular platform for HW-SW co-design;CODIR: towards an MLIR codelet model dialect;MENPS: a decentralized distributed shared memory exploiting RDMA;RaDD runtimes: radical and different distributed runtimes with SmartNICs;DEMAC: a modular platform for HW-SW co-design;and CODIR: towards an MLIR Codelet model dialect.
distributed, parallel, and grid computing are all used in a kind of computing known as cloud computing. It serves as a flexible, affordable, and tried-and-true online delivery platform for IT services marketed to busi...
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the Internet of things (IoT) is a breakthrough technology that interconnects and empowers numerous smart devices allowing them to communicate, collect, and exchange data. the most challenging issue in IoT networks is ...
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ISBN:
(纸本)9798350369458;9798350369441
the Internet of things (IoT) is a breakthrough technology that interconnects and empowers numerous smart devices allowing them to communicate, collect, and exchange data. the most challenging issue in IoT networks is securing exchanged data. Virtual Private Networks (VPNs) have a significant impact on ensuring security within IoT systems. So implementing a VPN-based solution can bring multiple security values to IoT systems, especially for exchanged data. However, most VPN-based solutions rely on a single central server responsible for managing all VPN connections. this presents a major problem when the number of managed VPNs increases because it will lead to the performance deterioration of the VPN server and can even lead to a single point of failure problem. We propose in this paper a distributed VPN-based solution that relies on distributed fog nodes playing the role of VPN servers. To determine the VPN server responsible for a specific communication, a fully decentralized and efficient search is guaranteed within the fog nodes through the utilization of the DHT-based Chord protocol. To enforce security and immutability, blockchain is used to verify the different criteria of a new requester to join a specific VPN. the performance evaluations have shown that our solution is efficient in terms of cost, time, and complexity.
the continuous growth in the worldwide demand for medical services pushes the traditional model of hospital care towards a more sustainable one which makes continuous monitoring of health status as well as remote trea...
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ISBN:
(纸本)9798350369458;9798350369441
the continuous growth in the worldwide demand for medical services pushes the traditional model of hospital care towards a more sustainable one which makes continuous monitoring of health status as well as remote treatment of diseases (where possible) feasible. In this context, the synergic exploitation of well-established paradigms such as Internet of things (IoT), Wearable computing and Edge Intelligence (EI) within a single platform can represent a game-changer with respect to the current smart healthcare scenario. In this paper we introduce ENTRUST (usEr ceNtric plaTform foR continoUS healthcare), an innovative solution pivoted around a seamless edge-cloud architecture and a simulation-based approach for the development of next-generation, daily healthcare services. the system desiderata and challenges towards its implementation are hence discussed and a use case reported to exemplify the envisioned ENTRUST approach.
this special issue is dedicated to examining the rapidly evolving fields of artificial intelligence, mathematical modeling, and optimization, with particular emphasis on their growing importance in computational scien...
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this special issue is dedicated to examining the rapidly evolving fields of artificial intelligence, mathematical modeling, and optimization, with particular emphasis on their growing importance in computational science. It features the most notable papers from the "Mathematical Modeling and Problem Solving" workshop at PDPTA'24, the 30thinternationalconference on parallel and distributed Processing Techniques and Applications. the issue showcases pioneering research in areas such as natural language processing, system optimization, and high-performance computing. the nine selected studies include novel AI-driven methods for chemical compound generation, historical text recognition, and music recommendation, along with advancements in hardware optimization through reconfigurable accelerators and vector register sharing. Additionally, evolutionary and hyper-heuristic algorithms are explored for sophisticated problem-solving in engineering design, and innovative techniques are introduced for high-speed numerical methods in large-scale systems. Collectively, these contributions demonstrate the significance of AI, supercomputing, and advanced algorithms in driving the next generation of scientific discovery.
In modern post-disaster rescue missions, the deployment of Multi-Robot systems (MRSs) plays a key role in minimizing injuries and deaths among rescue personnel and civilians involved in the disaster. Achieving optimal...
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ISBN:
(纸本)9798350369458;9798350369441
In modern post-disaster rescue missions, the deployment of Multi-Robot systems (MRSs) plays a key role in minimizing injuries and deaths among rescue personnel and civilians involved in the disaster. Achieving optimal MRS efficiency requires the implementation of a well-suited task allocation mechanism and a highly efficient pathfinding algorithm. However, due to inconsistent communication and low bandwidth, traditional frameworks in the mentioned domains may be impractical or may not work well. To address these problems, a novel Bi-Layer Joint Training Reinforcement (BJoT-RL) framework is proposed where, in the first layer, a Multi-Head Deep Q-Learning (MHDQN) is designed to perform task allocation;whereas, in the second layer, a Condition-Constrained Q-Learning (CCQ) is proposed to perform pathfinding. Noticeably, the output of each layer is used in the training of the other layer to realize a tight coupling, hence the innovative joint training. thorough simulations show that the BJoT-RL framework performs better than state-of-the-art solutions in such applications.
this paper provides a novel solution for developing a virtual keyboard and mouse (VKM) system that is easily manageable and portable. the traditional keyboards and mouse devices take up valuable desk space and are not...
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ISBN:
(纸本)9798350369458;9798350369441
this paper provides a novel solution for developing a virtual keyboard and mouse (VKM) system that is easily manageable and portable. the traditional keyboards and mouse devices take up valuable desk space and are not easily customizable to different languages. On-screen keyboards and 3-D cameras are alternatives, but they also have drawbacks. Our proposed method makes use of computer vision techniques and calls for a mini-projector and a web camera as necessary hardware. the system tracks hand keypoints to detect real-time touch events and uses the Mediapipe tool to detect hands and keystrokes. the mouse functionality is also implemented by monitoring the finger hovering. through experimentation, we show that our VKM solution can provide an accuracy of >90% for detecting the correct keystroke, with a typing speed of similar to 55 letters/min.
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