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Advancements in computing (ICAC), International Conference on

作者： Aparna Jayawardena Kasuni Ganegoda Sakuni Imbulana Gavin Gunapala Nuwan Kodagoda Thilini Jayasinghe Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

This research was conducted to develop a mobile application that provides expert solutions for the common problems faced by rubber planters in Sri Lanka. The application developed consists of four components, namely, identification of pests in immature rubber plantations and rubber nurseries; leaf disease identification; cover crop identification; and weed identification. Images taken using the mobile phone cameras are recognized using machine learning models developed using several convolutional neural network (CNN) architectures such as mobile net version 2 (MobileNet v2), VGG 16, VGG19, and residual networks (ResNet). After the images were recognized, the application will provide expert solutions and management strategies to the rubber planters. As most of the rubber plantations are located in areas with low network coverage, the application was designed to be operated in offline mode using TensorFlow lite technology.

关键词： Image recognition Crops Machine learning Computer architecture Mobile handsets Mobile applications Rubber

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Sequential Transfer via Clustering-Based Similarity Measurement for Faster Trajectory Optimization

Sequential Transfer via Clustering-Based Similarity Measurem...

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Artificial Intelligence (CAI), IEEE Conference on

作者： Wu Lin Qiuzhen Lin Xiaoming Xue Kay Chen Tan Department of Computing The Hong Kong Polytechnic University Hong Kong SAR China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798350354096

ISBN: (纸本)9798350354102

In evolutionary sequential transfer optimization (ESTO), the precision of similarity measurements between source and target tasks is crucial in selecting useful source solutions to accelerate the optimization of the target task. Despite the success of existing methods in optimizing various numerical functions, their capability to accurately measure the similarity among practical trajectory optimization problems (TOPs) remains limited due to the complex nature of real-world scenarios. To alleviate their limitations, this paper proposes a clustering-based similarity measurement method for ESTO, aiming to accurately select promising source solutions to speed up the evolutionary search in solving TOPs. Specifically, all candidate source TOPs that have been optimized are first categorized into different clusters based on their populations via k-means clustering. Afterward, the populations of source TOPs in the same cluster are employed to compute the similarity of these source TOPs to the target TOP that is being optimized. In this way, the TOPs with the highest similarity can be identified and their optimized solutions will be injected into the population of the target task for faster convergence. The experimental results demonstrate that our proposed method outperforms existing approaches, thereby confirming its capability to improve the optimization performance and efficiency in solving practical TOPs.

关键词： Sociology Search problems Task analysis Statistics Artificial intelligence Trajectory optimization Convergence

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Life on land: An accurate centralized system for ensuring the safety and wellbeing of domestic and wild animals

TechRxiv

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TechRxiv 2023年

作者： Heshan, Adithya B.M. Wickramathilake, Shamilka K.W.D. Gunathilake, Dulmi W.M.P. Herath, Hiruni H.M.S. Samarasekara, Piyumika de Silva, Dilshan Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

The web application described above has the potential to make a significant contribution to the conservation of endangered wildlife and the responsible management of domestic animals. The application addresses a critical issue that has far-reaching implications for the health of ecosystems and the well-being of animals. By providing users with tools to track and manage animal populations, monitor their health and behavior, and implement conservation efforts, the application empowers individuals and organizations to take action and make a positive impact on the environment. In addition to its practical benefits, the web application also includes educational resources and supports community engagement to raise awareness about the importance of preserving biodiversity and protecting animal welfare. This holistic approach recognizes the complex and interconnected nature of conservation and management efforts, and highlights the need for collaboration and cooperation among stakeholders. The user-friendly interface of the application ensures that it is accessible to a wide range of users, including individuals with limited technical expertise. The ability to collaborate and share data also promotes transparency and accountability, which are essential for effective conservation and management efforts. Overall, this web application has the potential to be a valuable tool for those involved in animal conservation and management, and it offers hope for the protection of endangered wildlife and the responsible management of domestic animals. © 2023, CC BY.

关键词： Animals

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Dependency-Aware Hybrid Task Offloading in Mobile Edge computing Networks 27

Dependency-Aware Hybrid Task Offloading in Mobile Edge Compu...

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27th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2021

作者： Ming, Zhao Li, Xiuhua Sun, Chuan Fan, Qilin Wang, Xiaofei Leung, Victor C. M. School of Big Data and Software Engineering Chongqing University Chongqing China TKLAN College of Intelligence and Computing Tianjin University Tianjin China College of Computer Science and Software Engineering Shenzhen University Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9781665408783

With the rapid increase of data in mobile edge computing (MEC) networks, mobile devices (MDs) have been generating many computation-latency-sensitive tasks. As the MDs are limited by resources in terms of storage, computation, and bandwidth, part of tasks have to be offloaded to the edge of mobile networks or the remote cloud for more efficient processing. Hence, task offloading plays a vital role in this scene. Existing works about task offloading mainly aim at one-shot task offloading and rarely consider the dependencies of tasks. In this paper, we focus on minimizing the maximum delay of processing a series of tasks with dependencies in MEC networks, which supports device-to-device communications. Specifically, we consider task offloading under a hybrid scenario with a small base station (SBS) deployed with an edge server (ES) and several MDs which generate several tasks with dependencies. Then we model the tasks to a weighted directed acyclic graph (DAG) and formulate the optimization problem as minimizing the critical path of the weighted DAG. To tackle this NP-hard problem, we propose a heuristic scheme to iteratively optimize the delay of paths of the weighted DAG under the constraints of the ES. To evaluate the proposed scheme, we perform numerical experiments with different numbers of tasks. Simulation results demonstrate that the proposed scheme outperforms other schemes in terms of reducing the system delay and saving the energy consumption of the MDs. © 2021 IEEE.

关键词： Optimization

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Artificial Intelligence-based Service Chains Scheduling for Medical Emergency in Healthcare 7

Artificial Intelligence-based Service Chains Scheduling for ...

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7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Soni, Mukesh Rusho, Maher Ali Byeon, Haewon Alghamdi, Azzah Hannan, Shaikh Abdul Dave, Parth Rameshchandra Dr. D. Y. Patil School of Science & Technology Tathawade Dr. D. Y. Patil Vidyapeeth Marashtra Pune India University of Colorado Department of Lockheed Martin Engineering Management BoulderCO80309 United States Inje University Department of Ai and Software & Medical Big Data Research Centre Gimhae50834 Korea Republic of Imam Abdalrhman Bin Faisal University College of Computer Science and Information Technology Computer Information Systems Department Khobar Saudi Arabia AlBaha University Faculty of Computing and Information AlBaha Saudi Arabia L. D. College of Engineering Department of Computer Engineering Gujarat Ahmedabad India

ISBN: (纸本)9798350350067

This study analyses the weekly scheduling challenge of health and medical information network service function chains to meet medical emergency categorization and grading needs. Emergency services are divided into four sorts by urgency and service area, with priorities and weights. The health and medical information network architecture, service model, and operation method are built accordingly. To reduce weighted completion time, a service function chain scheduling model is created. The function chain scheduling scheme is solved by matching game and Q -learning reinforcement learning algorithms for different issue scales. Finally, simulation studies demonstrate that this approach can accomplish graded medical emergency service, build health and medical information networks, and progress smart healthcare. © 2024 IEEE.

关键词： Electronic health record

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ChatGPT, Let us Chat Sign Language: Experiments, Architectural Elements, Challenges and Research Directions

arXiv

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arXiv 2024年

作者： Shahin, Nada Ismail, Leila Lab Department of CS and Software Engineering College of IT National Water and Energy Center UAE University Al-Ain United Arab Emirates CLOUDS lab School of Computing and Information Systems The University of Melbourne Melbourne Australia

ChatGPT is a language model based on Generative AI. Existing research work on ChatGPT focused on its use in various domains. However, its potential for Sign Language Translation (SLT) is yet to be explored. This paper addresses this void. Therefore, we present GPT's evolution aiming a retrospective analysis of the improvements to its architecture for SLT. We explore ChatGPT's capabilities in translating different sign languages in paving the way to better accessibility for deaf and hard-of-hearing community. Our experimental results indicate that ChatGPT can accurately translate from English to American (ASL), Australian (AUSLAN), and British (BSL) sign languages and from Arabic Sign Language (ArSL) to English with only one prompt iteration. However, the model failed to translate from Arabic to ArSL and ASL, AUSLAN, and BSL to Arabic. Consequently, we present challenges and derive insights for future research directions. © 2024, CC BY.

关键词： Audition

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Mobile Medical Assistant System for Laboratory Report Analysis and Medical Drug Identification

Mobile Medical Assistant System for Laboratory Report Analys...

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Advancements in computing (ICAC), International Conference on

作者： Deshani Warnakulasuriya Tharushi Dewangi Navodya Sewwandi Minoli Rathnayake Nuwan Kodagoda Kushanra Suriyawansha Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

It is quite common for medical drugs and prescriptions to be misidentified by hospitals and after drugs are being dispensed to the patients. Misidentification of medical drugs is more common among elderly and visually impaired patients. In hospital organizations, the leading medical error is adverse drug events. Another most common issue patients face is keeping track of medical lab reports. Our proposed mobile medical assistant system uses image processing to identify drugs with or without packaging, identifying prescription and medical lab reports. Furthermore, the mobile application will identify the trends of medical lab reports and predict next month’s results of the medical lab report of the patient using machine learning.

关键词： Drugs Hospitals Image processing Organizations Machine learning Packaging Market research

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Multi-feature enhancement based on sparse networks for single-stage 3D object detection

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Alexandria engineering Journal 2025年 111卷 123-135页

作者： Zunwang Ke Chenyu Lin Tao Zhang Tingting Jia Minghua Du Gang Wang Yugui Zhang School of Software Xinjiang University Urumqi 830091 China Department of Stomatology The First Medical Centre Chinese PLA General Hospital Beijing 100853 China School of Computing and Data Engineering NingboTech University Ningbo 315100 China Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China

In the field of autonomous driving, the accuracy and real-time requirements for 3D object detection technology continue to improve, which is directly related to the commercialization process and market popularity of autonomous vehicles. Despite the efficiency of pillar-based coding for onboard systems, it falls short in terms of accuracy and the reduction of incorrect positives. In this paper, we will examine how to solve the problem of high incorrect rate and low accuracy of existing methods. Firstly, a MAP coding module is introduced to optimize previous point cloud feature coding modules, allowing for the efficient extraction of fine-grained features from point cloud data. Then, we introduce an innovative sparse dual attention (SDA) to efficiently filter out irrelevant details in feature extraction, thereby improving the pertinence and efficiency of information extraction. Finally, to address the potential loss of information from single local feature extraction, a local and global fusion module (CTGC) is introduced. Our method has proactively demonstrated its efficiency and accuracy through rigorous experimentation across diverse datasets. Analysis of the results leads to the conclusion that our solutions provide accurate and robust detection results. Code will be available at https://***/lcy199905/*** .

关键词： Point cloud Object detection MAP coding Sparse dual attention Local and global fusion

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Comparative Study of Word Embeddings for Classification of Scientific Article on Human Health Risk of Electromagnetic Fields 11

Comparative Study of Word Embeddings for Classification of S...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Lee, Sang-Woo Kim, Nam Kwon, Jung-Hyok Choi, Hyung Do Lee, Sol-Bee Kim, Eui-Jik Hallym University Division of Software Chuncheon Korea Republic of Chungbuk National University School of Information and Communication Engineering Cheongju Korea Republic of Hallym University Smart Computing Laboratory Chuncheon Korea Republic of Radio Technology Research Department Daejeon Korea Republic of

ISBN: (纸本)9781665492324

This paper presents a comparative study on pre-trained word embeddings for the classification of scientific articles on the human health risk of EMF. In this study, the various neural network (NN) models are trained using the three biomedical pre-trained word embeddings (i.e., PubMed-word2vec, BioWordVec, and PubMed-BERT). Then, the performances of the trained NN models are evaluated to compare the pre-trained word embeddings. The evaluation results show that the NN models using PubMed-BERT outperform the other NN models using PubMed-word2vec and BioWordVec in the classification of scientific articles on the human health risk of EMF. © 2022 IEEE.

关键词： Electromagnetic fields

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A survey of Intel SGX and its applications

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Frontiers of Computer Science 2021年第3期15卷 191-205页

作者： Wei ZHENG Ying WU Xiaoxue WU Chen FENG Yulei SUI Xiapu LUO Yajin ZHOU School of Software and Microelectronics Northwestern Polytechnical UniversityXi'an 710129China Faculty of Engineering and Information Technology University of Technology SydneySydney 2007Australia Department of Computing The Hong Kong Polytechnic UniversityHong Kong 999077China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China

This paper presents a comprehensive survey on the development of Intel SGX(software guard extensions)processors and its *** the advent of SGX in 2013 and its subsequent development,the corresponding research works are also increasing *** order to get a more comprehensive literature review related to SGX,we have made a systematic analysis of the related papers in this *** first search through five large-scale paper retrieval libraries by keywords(i.e.,ACM Digital Library,IEEE/IET Electronic Library,SpringerLink,Web of Science,and Elsevier Science Direct).We read and analyze a total of 128 SGX-related *** first round of extensive study is conducted to classify *** second round of intensive study is carried out to complete a comprehensive analysis of the paper from various *** start with the working environment of SGX and make a conclusive summary of trusted execution environment(TEE).We then focus on the applications of *** also review and study multifarious attack methods to SGX framework and some recent security improvements made on ***,we summarize the advantages and disadvantages of SGX with some future research *** hope this review could help the existing and future research works on SGX and its application for both developers and users.

关键词： Intel SGX cloud computing trusted execution environment TrustZone AMD SEV

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