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Hybrid Whale Optimization Algorithm for Resource Optimization in Cloud E-Healthcare Applications

computers, Materials & Continua 2022年第6期71卷 5659-5676页

作者： Punit Gupta Sanjit Bhagat Dinesh Kumar Saini Ashish Kumar Mohammad Alahmadi Prakash Chandra Sharma School of Computing&Information Technology Manipal University JaipurJaipur303007India School of Basic Sciences Manipal University JaipurJaipur303007India Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

In the next generation of computing environment e-health care services depend on cloud *** Cloud computing environment provides a real-time computing environment for e-health care *** these services generate a huge number of computational tasks,real-time computing and comes with a deadline,so conventional cloud optimizationmodels cannot fulfil the task in the least time and within the *** overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization with the least simulation *** order to overcome existing issues,an artificial neural-inspired whale optimization is proposed to provide a reliable solution for healthcare *** this work,two models are proposed one for reliability estimation and the other is based on whale optimization technique and neural network-based binary *** predictive model enhances the quality of service using performance metrics,makespan,least average task completion time,resource usages cost and utilization of the *** as compared to existing algorithms the proposedANN-WHOalgorithms prove to improve the average start time by 29.3%,average finish time by 29.5%and utilization by 11%.

关键词： Cloud computing whale optimization health care resource optimization

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Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

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computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad Khan Abd Jabar Nazimi Mohammad Nazir Ahmad Department of Information Technology The Superior UniversityLahorePakistan Department of Software Engineering The Superior UniversityLahorePakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Computer Science Government College UniversityFaisalabadPakistan Deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3D NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

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HVAdam: A Full-Dimension Adaptive Optimizer 39

HVAdam: A Full-Dimension Adaptive Optimizer

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Yiheng Wu, Shaowu Xu, Yuanzhuo Wu, Jiajun Xu, Shang Drew, Steve Niu, Xiaoguang School of Computer Science Wuhan University China Department of Electrical and Software Engineering University of Calgary Canada Department of Computer Science University College London United Kingdom

ISBN: (纸本)157735897X

Adaptive optimizers such as Adam and RMSProp have gained attraction in complex neural networks, including generative adversarial networks (GANs) and Transformers, thanks to their stable performance and fast convergence compared to non-adaptive optimizers. A frequently overlooked limitation of adaptive optimizers is that adjusting the learning rate of each dimension individually would ignore the knowledge of the whole loss landscape, resulting in slow updates of parameters, invalidating the learning rate adjustment strategy and eventually leading to widespread insufficient convergence of parameters. In this paper, we propose HVAdam, a novel optimizer that associates all dimensions of the parameters to find a new parameter update direction, leading to a refined parameter update strategy for an increased convergence rate. We validated HVAdam in extensive experiments, showing its faster convergence, higher accuracy, and more stable performance on image classification, image generation, and natural language processing tasks. Particularly, HVAdam achieves a significant improvement on GANs compared with other state-of-the-art methods, especially in Wasserstein-GAN (WGAN) and its improved version with gradient penalty (WGAN-GP). Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Generative adversarial networks

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Fruit and Vegetable Detection with Calorie Estimation Built on Mobilenetv2

Fruit and Vegetable Detection with Calorie Estimation Built ...

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International Conference on Advances in Information Technology (ICAIT)

作者： Sengottaiayn N Hamsanandhini S Rajesh Sharma R Akey Sungheetha Monika M Ketema Adare Computer Science & Engineering Alliance University Bengaluru India Department of Computer Technology Kongu Engineering College Erode India MSc Software Systems Kongu Engineering College Erode India Department of Computer Science and Engineering Adama Science and Technology University Adama Ethiopia

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

Fruit and Vegetable Recognition with Calorie Estimation based on Mobilenetv2 is a pioneering research endeavor aimed at leveraging deep learning techniques to enhance dietary monitoring and health management. Building upon the success of neural network models in various domains, this study explores the application of Mobilenetv2 and EfficientNet architecture for accurately identifying fruits and vegetables from images and estimating their respective caloric content. The research dataset comprises meticulously curated images of diverse fruits and vegetables, ensuring comprehensive coverage across different categories. Through rigorous experimentation and evaluation, the proposed model demonstrates remarkable accuracy in fruit and vegetable recognition, achieving an impressive accuracy rate of 97.6%. Moreover, the incorporation of calorie estimation adds a novel dimension to dietary analysis, enabling users to make informed decisions regarding their nutritional intake. The findings of this research not only contribute to the advancement of computer vision techniques but also hold significant implications for personalized nutrition tracking and health- conscious applications.

关键词： Deep learning computer vision Accuracy Architecture Neural networks Buildings Estimation computer architecture Information technology Monitoring

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Transforming Diabetes Care: A Review of IoT-Based Mobile Health Systems 10th

Transforming Diabetes Care: A Review of IoT-Based Mobile He...

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10th EAI International Conference on IoT Technologies for Health-Care, HealthyIoT 2023, and 4th EAI International Conference on Wearables in Healthcare, HealthWear 2023

作者： Ashfaq, Fiza Ahad, Abdul Hussain, Mudassar Madeira, Filipe Department of Computer Science University of Management and Technology Sialkot51040 Pakistan School of Software Northwestern Polytechnical University Shaanxi Xian China Istanbul34467 Turkey /Pole of Digital Literacy and Social Inclusion Polytechnic Institute of Santarem Santarem2001-904 Portugal Department of Computer Science and Creative Technologies Global College of Engineering and Technology Muscat Oman

ISBN: (纸本)9783031719103

Diabetes, a chronic ailment requiring ongoing care and monitoring, has undergone a healthcare shift thanks to the Internet of Things (IoT). Real-time monitoring, individualized treatment plans, and improved patient-provider communication are all features of IoT-based mobile health solutions. This study explores the components, functionalities, benefits, and disadvantages of IoT-based mobile health systems for the management of diabetes. It investigates wearable sensors, smartphone apps, and linked devices like glucose meter and monitors, placing a focus on their precision, dependability, and usability. The study explores data analytics techniques that allow for customized advice and actions. Patients can effectively control their diabetes with the use of individualized treatments and real-time monitoring. The research also looks into the data analytical methods used in IoT-based mobile health systems for the treatment of diabetes. IoT-based mobile health system issues and implications are also covered. These include issues with data security and privacy, platform and device compatibility, standardization of data formats, and ensuring that all people with diabetes have equal access to technology. Healthcare workers, academics, and policymakers may learn more about the potential of IoT-based mobile health systems to revolutionize diabetes treatment through this thorough assessment. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Electronic health record

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Research on Multi-Blockchain Electronic Archives Sharing Model

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computers, Materials & Continua 2023年第9期76卷 3921-3931页

作者： Fang Yu Wenbin Bi Ning Cao Jun Luo Diantang An Liqiang Ding Russell Higgs School of Information Engineering Qingdao Binhai UniversityQingdao266555China School of Computer and Software Dalian Neusoft University of InformationDalian116023China School of Internet of Things and Software Technology Wuxi Vocational College of Science and TechnologyWuxi214028China Archives Management Department QingdaoWest Coast New Area ArchivesQingdao266427China Editorial Research Department QingdaoWest Coast New Area ArchivesQingdao266427China School of Mathematics and Statistics University College DublinDublinIreland

The purpose of introducing blockchain into electronic archives sharing and utilization is to break the information barrier between electronic archives sharing departments by relying on technologies such as smart contract and asymmetric *** at the problem of dynamic permission management in common access control methods,a new access control method based on smart contract under blockchain is proposed,which improves the intelligence level under blockchain ***,the Internet attribute access control model based on smart contract is *** the dynamic access of heterogeneous devices,the management contract,permission judgment contract and access control contract are designed;Secondly,the access object credit evaluation algorithm based on particle swarm optimization radial basis function(PSO-RBF)neural network is used to dynamically generate the access node credit threshold combined with the access policy,so as to realize the intelligent access right management ***,combined with the abovemodels and algorithms,the workflow of electronic archives sharing and utilization model of multi blockchain is *** experimental results show that the timeconsuming of the process increases linearly with the number of continuous access to electronic archives blocks,and the secure access control of sharing and utilization is feasible,secure and effective.

关键词： Sharing and utilization of electronic archives dynamic permission management PSO-RBF neural network credit evaluation

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A Study of EMG Signals Using QNET Myoelectric Board and LabVIEW software 4

A Study of EMG Signals Using QNET Myoelectric Board and LabV...

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4th International Conference on Applied Automation and Industrial Diagnostics, ICAAID 2022

作者： Alharbi, Hadeel Fahad Patel, Akshet Dasari, Uday Randhawa, Princy University of ha'Il Hail College of Computer Science and Engineering Department of Computer Science and Software Engineering 1234 Saudi Arabia Manipal University Jaipur Department of Mechatronics Engineering Jaipur India Manipal University Jaipur Department of Information Technology Engineering Jaipur India

ISBN: (纸本)9781728189390

This project's aim is to monitor the electrical activity of the user's muscle cells using the QNET Myoelectric Board and NI ELVIS II+ board. An opto-isolated sensor and a grounding strap are included in this electromyograph. The board includes an on-board signal processing and filtering mechanism, as well as a PCI-based data collection system. The board is connected using the LabVIEW application, which stands for Laboratory Virtual Instrument engineering Workbench (LabVIEW). LabVIEW is a graphical programming language and hence a direct connection between the user and the board is possible. The data is acquired, and five assessment criteria are applied to it. Graphs are shown based on time stamps for two participants (male and female), and the analyzed data is compiled to draw crucial conclusions. © 2022 IEEE.

关键词： Machine learning

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Building Personalised XAI Experiences Through iSee: a Case-Based Reasoning-Driven Platform 2

Building Personalised XAI Experiences Through iSee: a Case-B...

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Joint of the 2nd World Conference on eXplainable Artificial Intelligence Late-Breaking Work, Demos and Doctoral Consortium, xAI-2024:LB/D/DC

作者： Caro-Martínez, Marta Liret, Anne Díaz-Agudo, Belén Recio-García, Juan A. Darias, Jesús Wiratunga, Nirmalie Wijekoon, Anjana Martin, Kyle Nkisi-Orji, Ikechukwu Corsar, David Palihawadana, Chamath Pirie, Craig Bridge, Derek Pradeep, Preeja Fleisch, Bruno Department of Software Engineering and Artificial Intelligence Universidad Complutense de Madrid Spain School of Computing Robert Gordon University Aberdeen United Kingdom School of Computer Science & IT University College Cork Ireland British Telecommunications United Kingdom

Nowadays, eXplainable Artificial Intelligence (XAI) is well-known as an important field in computer science due to the necessity of understanding the increasing complexity of Artificial Intelligence (AI) systems or algorithms. This is the reason why we can find a wide variety of explanation techniques (explainers) in the literature, on top of some XAI libraries. The challenge faced by XAI designers here is deciding what explainers are the most suitable for each scenario, taking into account the AI model, task to explain, user preferences, needs and knowledge, and overall, fitting into the explanation requirements. With the aim of addressing this problem, the iSee project was conceived to provide XAI design users with supporting tools to build their own explanation experiences. As a result, we have developed iSee, a Case-Based Reasoning-driven platform that allows users to create personalised explanation experiences. With the iSee platform, users add their explanation experience requirements, and get the most suitable XAI strategies to explain their own situation, taking advantage of XAI strategies previously used with success in similar context. The iSee platform is composed of different tools and modules: the ontology, the cockpit, the explainer library, the Explanation Experiences Editor (iSeeE3), the chatbot, and the analytics dashboard. This paper introduces these tools as a demo and tutorial for current and future users and for the XAI community. © 2024 Copyright for this paper by its authors.

关键词： Case based reasoning

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A Multi-Criteria Decision-Making Framework for software Project Management Tool Selection 23

A Multi-Criteria Decision-Making Framework for Software Proj...

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9th International Conference on computer Technology Applications, ICCTA 2023

作者： Akbar, Saeed Ullah, Rahmat Khan, Rizwan Asghar, Ikram Zubair, Muhammad Zheng, Zhonglong College of Computer Science and Technology Zhejiang Normal University Jinhua321004 China Cemet University of South Wales Pontypridd United Kingdom Department of Software Engineering Lahore Garrison University Pakistan

ISBN: (纸本)9781450399579

Project management tools are critical for managing software projects, decreasing costs, accelerating timelines, and using available resources effectively. However, project managers find it very tedious to choose a suitable software project management (SPM) tool from available tools in the market. The appropriateness of the SPM tool depends on the nature of the software project being developed - an SPM tool suitable for a large-scale software project may not be appropriate for small-scale projects. However, due to the complexities of the software projects and the development conditions, the selection of an SPM tool is often biased by personal preferences or marketing publicities which may lead to inefficiencies in SPM and consequently, lead to higher cost and lower quality of end product. In this work, we present a decision support framework for SPM tool selection. The proposed system develops a set of selection criteria based on an analytic network process (ANP). To demonstrate the internal working of the proposed framework, we put forward an example of the tool selection problem using the proposed system. Furthermore, the proposed system can be used as is for SPM tool selection for other than software projects. © 2023 ACM.

关键词： Decision making

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Collaborative Streaming and Super Resolution Adaptation for Mobile Immersive Videos 42

Collaborative Streaming and Super Resolution Adaptation for ...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Zhang, Lei Guo, Haotian Dong, Yanjie Wang, Fangxin Cui, Laizhong Leung, Victor C. M. Shenzhen University College of Computer Science and Software Engineering Shenzhen China The Chinese University of HongKong Sse and FNii Shenzhen China Peng Cheng Laboratory Shenzhen China Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798350334142

Tile-based streaming and super resolution are two representative technologies adopted to improve bandwidth efficiency of immersive video steaming. The former allows selective download of contents in the user viewport by splitting the video into multiple independently decodable tiles. The latter leverages client-side computation to reconstruct the received video into higher quality using advanced neural network models. In this work, we propose CASE, a collaborated adaptive streaming and enhancement framework for mobile immersive videos, which integrates super resolution with tile-based streaming to optimize user experience with dynamic bandwidth and limited computing capability. To coordinate the video transmission and reconstruction in CASE, we identify and address several key design issues including unified video quality assessment, computation complexity model for super resolution, and buffer analysis considering the interplay between transmission and reconstruction. We further formulate the quality-of-experience (QoE) maximization problem for mobile immersive video streaming and propose a rate adaptation algorithm to make the best decisions for download and for reconstruction based on the Lyapunov optimization theory. Extensive evaluation results validate the superiority of our proposed approach, which presents stable performance with considerable QoE improvement, while enabling trade-off between playback smoothness and video quality. © 2023 IEEE.

关键词： Video streaming

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