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Optimizing Service Stipulation Uncertainty with Deep Reinforcement Learning for Internet Vehicle Systems

computers, Materials & Continua 2023年第3期74卷 5705-5721页

作者： Zulqar Nain B.Shahana Shehzad Ashraf Chaudhry P.Viswanathan M.S.Mekala Sung Won Kim Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siKorea Department of Computer Science and Engineering KLEFIndia Department of Computer Engineering Faculty of Engineering and ArchitectureIstanbul Gelisim UniversityIstanbul34310Turkey School of Computer Science and Engineering VIT UniversityVelloreIndia

Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System(CPS)*** devices enable limited computational capacity and energy availability that hamper end user *** designed a novel performance measurement index to gauge a device’s resource *** examination addresses the offloading mechanism issues,where the end user(EU)offloads a part of its workload to a nearby edge server(ES).Sometimes,the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources(such as storage and computation).The manuscript aims to reduce the service offloading rate by selecting a potential device or server to accomplish a low average latency and service completion time to meet the deadline constraints of sub-divided *** this regard,an adaptive online status predictive model design is significant for prognosticating the asset requirement of arrived services to make float ***,the development of a reinforcement learning-based flexible x-scheduling(RFXS)approach resolves the service offloading issues,where x=service/resource for producing the low latency and high performance of the *** approach to the theoretical bound and computational complexity is derived by formulating the system efficiency.A quadratic restraint mechanism is employed to formulate the service optimization issue according to a set ofmeasurements,as well as the behavioural association rate and adulation *** system managed an average 0.89%of the service offloading rate,with 39 ms of delay over complex scenarios(using three servers with a 50%service arrival rate).The simulation outcomes confirm that the proposed scheme attained a low offloading uncertainty,and is suitable for simulating heterogeneous CPS frameworks.

关键词： Fog computing task allocation measurement models feasible node selection methods performance metrics

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Application of machine learning techniques to predict patient’s satisfaction of indoor environmental quality in Jordanian hospitals

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13673-13681页

作者： Ali, Hikmat H. Abdullah, Malak Wedyan, Musab Department of Architecture Jordan University of Science and Technology Irbid Jordan Department of Computer Science Jordan University of Science and Technology Irbid Jordan

The indoor environment is an integral part of the hospital design since it impacts patients’ health, well-being, and healing process. Although the machine learning approach has been widely adopted in many fields, limited studies applied the machine learning approach to indoor environmental quality (IEQ) in hospitals and the impact of the room type on patients’ satisfaction with IEQ. Accordingly, the current study aims to bridge this gap using the machine learning approach. The research used mixed design methods to assess indoor environmental quality. The data was gathered using self-reported data and field monitoring of environmental parameters inside patients’ rooms. King Abdullah University Hospital (KAUH) was used to represent hospitals in Jordan. Machine learning proceeded in several stages, starting from prepossessing, training the algorithms, and testing the results. The experiments were conducted with the same dataset for training and testing and evaluated using the same classification metrics using Python programming language. Besides, the most important features were conducted using Random Forest regardless of room type, in each room type, and each category of IEQ between room types. The present findings confirmed a variation in the essential features. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Hospitals

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HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism

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computers, Materials & Continua 2024年第8期80卷 3351-3377页

作者： TugbaÇelikten Aytug Onan Department of Software Engineering Faculty of TechnologyManisa Celal Bayar UniversityManisa45140Turkey Department of Computer Engineering Faculty of Engineering and ArchitectureIzmir KatipÇelebi UniversityIzmir35620Turkey

Class Title:Radiological imaging method a comprehensive overview *** GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the *** and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed *** recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis ***:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical ***:Radiological imaging is an extremely important tool in modern medicine to assist in medical *** work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.

关键词： Generative artificial intelligence AI-generated text detection attention mechanism hybrid model for text classification

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An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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Design of a Robust IEEE Compliant Floating - Point Divide and Square Root Using Iterative Approximation 16

Design of a Robust IEEE Compliant Floating - Point Divide an...

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16th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2025

作者： Sager, Carson Stine, James E. Oklahoma State University Vlsi Computer Architecture Research Group Electrical and Computer Engineering Department StillwaterOK74078 United States

ISBN: (纸本)9798331522124

In this paper, we discuss an IEEE 754 compliant normalized floating-point divide and square root unit that utilizes iterative approximation. We provide a robust architecture that allows multiple formats and all IEEE 754 rounding modes while still exhibiting high-performance. Moreover, we also adhere to the IEEE 754 2019 standard and demonstrate methods for rounding results to all five rounding modes using iterative approximation. Performance, Power, and Area estimates are determined from physical synthesis using ARM-based standard cells in a TSMC 28nm process. This paper also presents comparisons versus other implementations and demonstrates the efficient of the approach presented here. © 2025 IEEE.

关键词： Integrated circuit design

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An integrated framework for the agile development and deployment of low cost remote laboratories

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Multimedia Tools and Applications 2024年 1-21页

作者： Chacón, Jesús Besada-Portas, Eva García-Pérez, Lía López-Orozco, Jose Antonio Department of Computer Architecture and Automation Universidad Complutense de Madrid Plaza de las Ciencias 1 Madrid Madrid28040 Spain

This work proposes a standalone framework, supported by state-of-the-art technologies, to efficiently build Remote Laboratories (RLs) from scratch. Not only does this proposal contribute with a new software infrastructure of RLs, but also with a methodology and an Integrated Development Environment to set up and deploy RLs, to boost developers productivity, and to reduce the RLs time/cost to production. Finally, the new framework, described first in depth from the point of view of its users and later through a study case, can be used as a principle solution for low cost RLs, since its software is completely deployable in single-board computers as the Raspberry Pi. © The Author(s) 2024.

关键词： Remote control

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Dynamic Deep Learning for Enhanced Reliability in Wireless Sensor Networks: The DTLR-Net Approach

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computers, Materials & Continua 2024年第11期81卷 2547-2569页

作者： Gajjala Savithri N.Raghavendra Sai Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh522502India Department of Animation Dr.YSR Architecture and Fine Arts UniversityKadapaAndhra Pradesh516162India

In the world of wireless sensor networks(WSNs),optimizing performance and extending network lifetime are critical *** this paper,we propose a new model called DTLR-Net(Deep Temporal LSTM Regression Network)that employs long-short-term memory and is effective for long-term *** sinks can move in arbitrary patterns,so the model employs long short-term memory(LSTM)networks to handle such *** parameters were initialized iteratively,and each node updated its position,mobility level,and other important metrics at each turn,with key measurements including active or inactive node ratio,energy consumption per cycle,received packets for each node,contact time,and interconnect time between nodes,among *** metrics aid in determining whether the model can remain stable under a variety of ***,in addition to focusing on stability and security,these measurements assist us in predicting future node behaviors as well as how the network *** results show that the proposed model outperformed all other models by achieving a lifetime of 493.5 s for a 400-node WSN that persisted through 750 rounds,whereas other models could not reach this value and were significantly *** research has many implications,and one way to improve network performance dependability and sustainability is to incorporate deep learning approaches into WSN dynamics.

关键词： WSN lifetime nodes mobile sinks energy packets security

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Designing a mockup and refactoring code for HPC geo-electromagnetic applications

Designing a mockup and refactoring code for HPC geo-electrom...

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2024 IEEE International Conference on Engineering Veracruz, ICEV 2024

作者： Castillo-Reyes, Octavio Orihuela, Xavier Garcia Pina Suarez, Xavier Department of Computer Architecture Barcelona08034 Spain Barcelona08034 Spain Barcelona08034 Spain

ISBN: (纸本)9798350391619

This paper presents a comprehensive integration of object-oriented code refactoring within PETGEM, an open-source 3D electromagnetic modeler, aimed at advancing its functionality for geophysical applications in the exascale high-performance computing era. Building upon previous works focusing on PETGEM, our research extends the capabilities of PETGEM by enhancing its codebase organization, design extensibility, and computational efficiency through its integration with the PETSc library. To achieve this goal, we first introduce a mockup design based on PETSc to emulate the PETGEM workflow. Subsequently, we utilize this mockup to implement object-oriented code refactoring techniques. The net result of this effort is an improved code version and better interoperability, portability, and scalability for the solution of real-life geo-electromagnetic surveys in geophysics. © 2024 IEEE.

关键词： Mockups

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SEKM-IoT: Secure and Efficient Key Management for Dynamic Access Control in Smart IoT Systems 21

SEKM-IoT: Secure and Efficient Key Management for Dynamic Ac...

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21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Benmalek, Mourad College of Engineering and Architecture Al Yamamah University Computer Engineering Department Riyadh Saudi Arabia

ISBN: (纸本)9798350378078

In this paper, we focus on the critical challenge of establishing a secure and efficient key management scheme that enables dynamic access control in hierarchical Internet of Things (IoT) systems, particularly linear hierarchies with multiple classes. In the proposed scheme, denoted SEKM-IoT, a key graph technique is used to effectively update class keys when membership changes occur. Moreover, a secure key derivation technique is employed to allow members of higher classes deriving class keys of the lower ones using a one-way hash function. Security analysis shows that SEKM-IoT ensures forward secrecy, backward secrecy, collusion freedom, and resistance against contrary attacks. Furthermore, performance analysis demonstrates that our scheme is lightweight, scalable, and incurs low cost in terms of storage, communication, and computation overheads. © 2024 IEEE.

关键词： Access control

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Improved Shark Smell Optimization Algorithm for Human Action Recognition

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computers, Materials & Continua 2023年第9期76卷 2667-2684页

作者： Inzamam Mashood Nasir Mudassar Raza Jamal Hussain Shah Muhammad Attique Khan Yun-Cheol Nam Yunyoung Nam Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Architecture Joongbu UniversityGoyang10279South Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma *** effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video *** Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature *** accuracy and effectiveness of these models continue to be the biggest challenge in this *** this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted *** proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search *** proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of *** local optimal features are selected,a global search is conducted to further optimize these *** proposed iSSO algorithm is employed on nine(9)selected CNN *** CNN models are selected based on their top-1 and top-5 accuracy in ImageNet *** evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.

关键词： Action recognition improved shark smell optimization convolutional neural networks machine learning

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