检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

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

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

Mobile Medical Assistant System for Laboratory Report Analys...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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...

引用

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

来源：评论

学校读者我要写书评

暂无评论

A survey of Intel SGX and its applications

引用

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

来源：评论

学校读者我要写书评

暂无评论

A Novel Crypto-Ransomware Family Classification Based on Horizontal Feature Simplification

A Novel Crypto-Ransomware Family Classification Based on Hor...

引用

International Conference on Computer, Communication and Computational Sciences, IC4S 2019

作者： Kakavand, Mohsen Arulsamy, Lingges Mustapha, Aida Dabbagh, Mohammad Department of Computing and Information Systems Sunway University Sunway City Petaling Jaya Malaysia Department of Dept of Software Engineering Universiti Tun Hussein Onn Malaysia Johor Johor Malaysia

ISBN: (纸本)9789811544088

Analytical research on a distinct form of malware otherwise known as crypto-ransomware was studied in this current research. Recent incidents around the globe indicate crypto-ransomware has been an increasing threat due to its nature of encrypting victims, targeted information and keeping the decryption key in the deep Web until a reasonable sum of ransom is paid, usually by cryptocurrency. In addition, current intrusion detection systems (IDSs) are not accurate enough to evade attacks with intelligently written crypto-ransomware features such as polymorphic, environment mapping, and partially encrypting files or saturating the system with low entropy file write operations in order to produce a lower encryption footprint, which can cause inability toward the intrusion detection system (IDS) to detect malicious crypto-ransomware activity. This research has explored diverse data preprocessing technique to depict crypto-ransomware as images. In effort to classify crypto-ransomware images, this research will utilize the existing neural network methods to train a classifier to classify new crypto-ransomware files into their family classes. In a broader context, the concept for this research is to create a crypto-ransomware early detection approach. Nevertheless, the primary contribution is the proof of baselining horizontal feature simplification concept, whereby it provides an accurate real-time detection rate for crypto-ransomware with less system load toward the user device. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

Support Vector Machine for Multiclass Classification of Redundant Instances

Support Vector Machine for Multiclass Classification of Redu...

引用

Intelligent computing and Networking - Proceedings of IC-ICN 2023

作者： Surbakti, Herison Kumar, Athmakuri Naveen Tara, Saikumar Keshta, Ismail khare, Amit Prasad, G.N.R. Faculty of Computing and Digital Technology HELP University Kuala Lumpur Malaysia Senior Software Engineer Glosoft Technologies Pvt Ltd Chennai India Department of ECE BVRIT Hyderabad College of Engineering for Women Hyderabad India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Technology JIET Institute of Design and Technology Rajasthan Jodhpur India Telangana Hyderabad500091 India

ISBN: (纸本)9789819931767

In recent years, support vector machine has become one of the most important classification techniques in pattern recognition, machine learning, and data mining due to its superior classification effect and solid theoretical base. However, its training time will increase dramatically as the number of samples increases, and training will become more sophisticated when dealing with problems involving multiple classifications. A quick training data reduction approach MOIS appropriate for multi-classification tasks is presented as a solution for the aforementioned issues. While eliminating redundant training samples, the boundary samples that play a vital role are chosen in order to considerably reduce training data and the problem of unequal distribution between categories. The experimental results demonstrate that MOIS may maintain or even improve the classification performance of support vector machines while substantially enhancing training efficiency. On the Opt digit dataset, the suggested method improves classification accuracy from 98.94% to 99.05%, while training time is reduced to 15% of the original;in HCL2000, the proposed method improves classification accuracy from 98.94% to 99.05%. When the accuracy rate is marginally increased (from 99.29% to 99.30%) on the first 100 categories dataset, the training time is dramatically reduced to less than 6% of the original. Additionally, MOIS has a high operational efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Success Factors of Requirement Elicitation in the Field of software engineering

Success Factors of Requirement Elicitation in the Field of S...

引用

Advancements in computing (ICAC), International Conference on

作者： Buddhima Attanayaka Dasuni Nawinna Kalpani Manathunga Pradeep K.W. Abeygunawardhana Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka Department of Computer Systems & Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398106

Requirement elicitation (RE) is a cognitively challenging and time-consuming task in software development due to the numerous challenges associated with it including conflicting requirements, unspoken, or assumed requirements, difficulty meeting with relevant stakeholders, stakeholder resistance to change, and not enough time set aside for meetings with all stakeholders. The prime causes of software implementation failure have been identified as inadequacies in the treatment of requirements. Without collecting the quality requirement, cannot achieve the goal of a quality software product. Through identifying the success factors affecting requirement elicitation, the paths to the quality requirements can be identified. The success factors identify through this research are experience, business analyst skills, stakeholder relationship, organizational elicitation process. This study aims to identify the factors affecting requirement elicitation based on the data collected from business analysts and similar positions in the software industry through a survey, interviews, and analyzed data to provide the initial validation for the identified factors. Through the analysis, we identified the main factors affecting successful requirement elicitation with a perfect significance value of less than 0.05 for all factors.

关键词： Resistance Industries software Stakeholders Task analysis Interviews Business

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：