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检索条件"机构=Dept. of Computer and Elec. Eng. and Computer Science"

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An Enhancement Algorithm for Mobility over Fog Computing 3

An Enhancement Algorithm for Mobility over Fog Computing

引用

3rd IEEE International Conference on elec.ronic eng.neering, ICEEM 2023

作者： Hussien, Doaa Abo El-Sisi, Ashraf El-Bahnasawy, Nirmeen A. Menoufia University Faculty of Electronic Eng. Computer Science & Eng. Dept. El-Menoufia Egypt Menoufia University Faculty of Computers and Information Computer Science Department El-Menoufia Egypt

ISBN: (纸本)9798350323511

Due to the mobility of users and end devices, providing continuous service in Fog Computing (FC) is a difficult challeng.. With fog-assisted IoT healthcare frameworks, dealing with user mobility becomes even more complex because low latency in mobility support and fog node locating is a critical requirement. In this work, we offer a fog computing architecture with hand-over strategy that is tailored to user mobility and that reduces latency for location-sensitive operations and service stability with great data broadcast quality. In our design, it is no longer necessary to either complete a work or send it to the cloud;instead, it is necessary to connect with other FNs to continue with a request for a new job. This reduces average network delay by 30%-40% and increases end-to-end communication by 35%-45%. © 2023 IEEE.

关键词： Fog computing

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An Enhancement Multi-Objective Resource Allocation Algorithm in Fog Environment 3

An Enhancement Multi-Objective Resource Allocation Algorithm...

引用

3rd IEEE International Conference on elec.ronic eng.neering, ICEEM 2023

作者： El-Bahnasawy, Nirmeen A. El-Nattat, Amal El-Sayed, Ayman Elkazzaz, Sahar Menoufia University Faculty of Electronic Eng. Computer Science & Eng. Dept. El-Menoufia Menouf32952 Egypt Sadat City University Faculty of Computing and Artificial Intelligence Computer Science Dept. El-Menoufia Egypt

ISBN: (纸本)9798350323511

For high transmission latency from users, cloud computing (CC) is not the best choice for processing latency sensitive applications that require real time response with minimal delay. To tolerate this issue, a new computing paradigm named fog computing (FC) was introduced to make cloud services closer to the user. It has been proposed to support real-time applications. Resource allocation and Task assignment are important issues for fog environment. Inefficient resource allocation causes poor performance for the system. Some tasks are constrained with a time limit called deadline. In case of real time applications, tasks need to be scheduled in the fog environment without violating its deadline. A new algorithm called Modified Deadline Aware Resource Allocation (MDARA) was proposed in this paper. Its aim is minimizing the completion time of applications, minimizing average response time, augment usage of resources under a constraint of deadline for enhancing the performance of fog environment. The proposed algorithm is compared with one of effective load balancing algorithms as Modified Round Robin algorithm (MRR) and compared with one of the recent algorithms like DRAM algorithm, which focuses on load balancing and resource utilization without taking into consideration the overall completion time and user-defined deadline of tasks. According to the results, the proposed algorithm outperformed both MRR and DRAM algorithms. © 2023 IEEE.

关键词： Resource allocation

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Enhancing Facial Recognition in Visual Prostheses using Region of Interest Magnification and Caricaturing 5

Enhancing Facial Recognition in Visual Prostheses using Regi...

引用

5th International Conference on computer and Applications, ICCA 2023

作者： Moneer, Hesham M. Elnabawy, Reham H. Eldawlatly, Seif German University in Cairo Digital Media Eng. and Technology Dept. Cairo Egypt Ain Shams University Computer and Systems Eng. Dept. Cairo Egypt The American University in Cairo Computer Science and Eng. Depr. Cairo Egypt

ISBN: (纸本)9798350303254

Blindness is a prevalent disability with significant personal and societal consequences. While medical advancements offer treatment options, severe damage to the retina, optic nerve, or brain may remain untreated. Visual prostheses are implantable medical devices that aim at providing limited vision to such individuals. However, such prostheses offer low spatial resolution making activities like reading, facial recognition, and navigation challeng.ng. This work aims to enhance implantees' ability to recognize faces through real-time scene preprocessing, machine learning and computer vision techniques. Virtual-reality visual models simulating prosthetic vision were tested on normally/corrected sighted subjects, investigating the use of histogram equalization for contrast enhancement, facial region magnification, and caricaturing of facial features. Results revealed that histogram equalization with magnification increases facial recognition accuracy by 60%, distinguishability accuracy by 50%, and accuracy of seeing facial details by 90%. In contrast, adding facial caricaturing improved the accuracies by 66.66%, 25%, and 75% for recognizability, distinguishability, and seeing facial details, respectively. Consequently, the combination of visual field histogram equalization, face magnification, and optional caricaturing can be considered as a promising enhancement approach that could enhance the quality of vision perceived through visual prostheses. © 2023 IEEE.

关键词： Prosthetics

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Hybrid Reinforcement Learning for Data Stream Freshness in Autonomous Vehicle Networks

Hybrid Reinforcement Learning for Data Stream Freshness in A...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Dariush Ebrahimi Pronab Ghosh Fadi Alzhouri Thiago E. Alves De Oliveira Dept. of Computer Science Wilfrid Laurier University Waterloo Canada Dept. of Computer Science Lakehead University Thunder Bay Canada Dept. of Elec. & Computer Eng. Concordia University Montreal Quebec Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Autonomous vehicles (AVs) are poised to become integral components of intelligent transportation systems, particularly within the framework of future smart cities. Traditional performance metrics such as throughput and latency fall short in adequately addressing the temporal relevance and freshness of data in critical applications such as autonomous driving and accident prevention. Consequently, this paper delves into the challeng. of reducing the Age of Information (AoI) for disseminating data streams within AV-assisted vehicular networks. Given the dynamic nature of the environment, the problem is formulated as a Markov decision process and tackled using Q-learning and DDQN, both prominent reinforcement learning (RL) algorithms. Additionally, a heuristic approach is introduced to augment the performance of the RL algorithms, expediting environmental learning convergence. The numerical findings underscore the effectiveness of the proposed methodologies in minimizing the aggregate AoI across all data streams.

关键词： Q-learning Smart cities Shape Heuristic algorithms Transportation Throughput Resource management Vehicle dynamics Streams Autonomous vehicles

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Transitional Frequencies of Fractional-Order Transitional Transfer Functions Using Butterworth and Sync-Tuned Approximations

Transitional Frequencies of Fractional-Order Transitional Tr...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： McGowan, Michael Kubanek, David Herencsar, Norbert Freeborn, Todd J. The University of Alabama Dept. Elec. Computer Eng. Tuscaloosa United States Brno University of Technology Dept. Telecommunications Brno Czech Republic The University of Alabama Dept. Elec. Comp. Eng. Tuscaloosa United States

ISBN: (纸本)9798331504847

In this work, the transitional frequencies of fractional-order transitional transfer functions designed using Butterworth and Sync-Tuned approximations are quantified to advance understanding of which response dominates the magnitude response. Numerical searches identify these frequencies for cases where i) Butterworth order is fixed at 2.54 and Sync-Tuned order is varied from 1 to 4, and ii) Sync-Tuned order is fixed at 2.54 and Butterworth is varied from 1 to 4. LTSpice simulations and measured results of an inverse-follow-the-leader topology designed to realize a transitional response (with Butterworth order of 2.54 and Sync-Tuned of 1.8) using an approximated fractional-order capacitor confirm the characteristics of this transitional design. © 2025 IEEE.

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ForDeen: Towards Formal Design for Ensuring Reliable UAV-Assisted Multi-Access Edge Computing: A Scenario-Based Approach 1

ForDeen: Towards Formal Design for Ensuring Reliable UAV-Ass...

引用

1st IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2023

作者： Wang, Yuxuan Wingate, Charlie Chen, Jingshu Oakland University Computer Science and Engineering Dept. RochesterMI United States Oakland University Computer Science and Eng. Dept. RochesterMI United States

ISBN: (纸本)9798350319958

In this work, we focus on providing reliable design of UAV-assisted MEC systems via a formal way. Specifically, we are currently working on developing ForDeen, a formal framework that assures the reliability for MEC systems using a scenario-based synthesis approach. The framework will first construct a formal model to dynamically adjust the parameters of an UAV-assisted MEC system based on its state, environment, and objectives. To achieve this, we will adopt a combined approach of using Markov-chain Process and temporal logics to capture the behaviors and mission objectives of the target MEC systems. Typical scenarios such as data offloading will be modeled and integrated dynamically to generate the components whose behavior can be specified by a Markov chain. Our preliminary results have demonstrated the feasibility of the proposed framework via a case study. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Natural Language Processing in Environmental Health Research

Natural Language Processing in Environmental Health Research

引用

2024 IEEE MIT Undergraduate Research Technology Conference, URTC 2024

作者： Tiahi, Mouad Kumar, Muskan Feric, Zlatan Kaeli, David Khoury College of Computer Science Northeastern University BostonMA United States Massachusetts Bay Community College Wellesley Dept. of Computer Science MA United States Northeastern University Dept. of Electrical and Computer Eng. BostonMA United States

ISBN: (纸本)9798331531003

Large Language Models (LLMs) are utilized across multiple disciplines for summarizing information and generating domain relevant responses. The Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) Center at Northeastern University aims to address environmental health issues, particularly focusing on the impact of exposure to environmental contaminants on preterm birth rates in Puerto Rico. We explore the application of RAG in creating an AI assistant tailored to the needs of PROTECT for information dissemination and community eng.gement. The virtual assistant is designed to interact with community members, providing them with information about environmental health risks and preventive measures. We assess the performance our model and its efficacy in environmental health research compared to other Large Language Models (LLMs). Our findings suggest that equipping an LLM with a RAG model in the domain of environmental health studies can enhance outreach efforts. © 2024 IEEE.

关键词： AI generation LLM processing retrieval

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elec.roencephalographic Biomarkers for Major Depressive Disorder and Alcohol Use Disorder 7

Electroencephalographic Biomarkers for Major Depressive Diso...

引用

7th IEEE International Conference on elec.rical, elec.ronics, and System eng.neering, ICEESE 2024

作者： Maidin, Muhammad Nur Aiman Haja Yahya, Norashikin Saad, Mohamad Naufal Mohamad Khan, Danish M. Kamel, Nidal S. Electrical & Electronics Eng. Dept. Universiti Teknologi PETRONAS Perak Malaysia Dept. of Computing & Information Systems Sunway University Selangor Malaysia College of Eng. & Computer Science VinUniversity Hanoi Viet Nam

ISBN: (纸本)9798350367447

Major Depressive Disorder (MDD) and Alcohol Use Disorder (AUD) are common neurological disorders that significantly impact physical health, family life, and work. Accurate diagnosis is essential for early intervention and treatment. However, conventional DSM-based diagnosis is subjective and susceptible to errors due to patient dishonesty or memory lapses. This study introduces a more reliable and objective diagnostic approach using effective connectivity (EC) from EEG recordings of 30 healthy controls, 30 MDD, and 30 AUD patients. EC, calculated via partial directed coherence, was used as input for an SVM model, achieving a peak classification accuracy of 95.3%, with perfect accuracy in the beta and gamma rhythms. These findings underscore EC’s potential as biomarkers for more accurate diagnosis and early intervention in neurological disorders. © 2024 IEEE.

关键词： elec.roencephalography

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Towards Sustainable Economic Zones with UAV-assisted Real-time Energy Replenishment in Wireless Rechargeable Sensor Networks 17

Towards Sustainable Economic Zones with UAV-assisted Real-ti...

引用

17th IEEE International Conference on Advanced Networks and Telec.mmunications Systems, ANTS 2023

作者： Goyal, Riya Tomar, Abhinav Singal, Gaurav Netaji Subhas University of Technology Dept. of Computer Science and Eng. New Delhi Dwarka India

ISBN: (纸本)9798350307672

An economic zone is bound to have continuous monitoring and control by an autonomous surveillance system for better production competency and security. Wireless Rechargeable Sensor Networks (WRSNs) have gained popularity to provide reliable and sustainable energy supply for continual network operations. In economic zones, numerous sensor nodes are deployed for diverse activities that require continuous energy supply. However, the integration of WRSNs with UAVs has increased the efficiency of recharging the sensor nodes deployed in areas that are difficult to reach by mobile chargers. Nevertheless, UAVs' limited battery life limits their performance and range which requires efficient deployment of charging stations. This paper proposes an integration of the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithms to address the charging scheduling problem through efficient deployment of charging stations and finding the optimal charging scheduling path for UAVs. Simulation results demonstrate that the proposed scheme produces a shorter planning path, leading to a longer network lifespan than alternative approaches. © 2023 IEEE.

关键词： Ant colony optimization

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Replicability Study: Corpora For Understanding Simulink Models & Projects 17

Replicability Study: Corpora For Understanding Simulink Mode...

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17th ACM/IEEE International Symposium on Empirical Software eng.neering and Measurement, ESEM 2023

作者： Shrestha, Sohil Lal Chowdhury, Shafiul Azam Csallner, Christoph University of Texas at Arlington Computer Science & Eng. Dept. ArlingtonTX76019 United States

ISBN: (纸本)9781665452236

Background: Empirical studies on widely used model-based development tools such as MATLAB/Simulink are limited despite the tools' importance in various industries. Aims: The aim of this paper is to investigate the reproducibility of previous empirical studies that used Simulink model corpora and to evaluate the generalizability of their results to a newer and larger corpus, including a comparison with proprietary models. Method: The study reviews methodologies and data sources employed in prior Simulink model studies and replicates the previous analysis using SLNET. In addition, we propose a heuristic for determining code-generating Simulink models and assess the open-source models' similarity to proprietary models. Results: Our analysis of SLNET confirms and contradicts earlier findings and highlights its potential as a valuable resource for model-based development research. We found that open-source Simulink models follow good modeling practices and contain models comparable in size and properties to proprietary models. We also collected and distribute 208 git repositories with over 9k commits, facilitating studies on model evolution. Conclusions: The replication study offers actionable insights and lessons learned from the reproduction process, including valuable information on the generalizability of research findings based on earlier open-source corpora to the newer and larger SLNET corpus. The study sheds light on noteworthy attributes of SLNET, which is self-contained and redistributable. © 2023 IEEE.

关键词： Simulink

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