检索结果-内蒙古大学图书馆

Landscape of sign language research based on smartphone apps: coherent literature analysis, motivations, open challenges, recommendations and future directions for app assessment

引用

Universal Access in the Information Society 2024年第2期23卷 687-702页

作者： David, Dianes Alamoodi, A.H. Albahri, O.S. Zaidan, B.B. Zaidan, A.A. Garfan, Salem Ismail, Amelia Ritahani Albahri, A.S. Alsinglawi, Belal Malik, R.Q. Perak Malaysia Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Faculty of Engineering and IT The British University in Dubai Dubai United Arab Emirates International Islamic University Malaysia Kuala Lumpur Malaysia Baghdad Iraq School of Computer Data and Mathematical Sciences Western Sydney University Sydney Australia Medical Intrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq Computer Techniques Engineering Department Mazaya University College Thi-Qar Nassiriya Iraq

Numerous nations have prioritised the inclusion of citizens with disabilities, such as hearing loss, in all aspects of social life. Sign language is used by this population, yet they still have trouble communicating with others. Many sign language apps are being created to help bridge the communication gap as a result of technology advances enabled by the widespread use of smartphones. These apps are widely used because they are accessible and inexpensive. The services and capabilities they offer and the quality of their content, however, differ greatly. Evaluation of the quality of the content provided by these applications is necessary if they are to have any kind of real effect. A thorough evaluation like this will inspire developers to work hard on new apps, which will lead to improved software development and experience overall. This research used a systematic literature review (SLR) method, which is recognised in gaining a broad understanding of the study whilst offering additional information for future investigations. SLR was adopted in this research for smartphone-based sign language apps to understand the area and main discussion aspects utilised in the assessment. These studies were reviewed on the basis of related work analysis, main issues, discussions and methodological aspects. Results revealed that the evaluation of sign language mobile apps is scarce. Thus, we proposed a future direction for the quality assessment of these apps. The findings will benefit normal-hearing and hearing-impaired users and open up a new area where researchers and developers could work together on sign language mobile apps. The results will help hearing and non-hearing users and will pave the way for future collaboration between academicians and app developers in the field of sign language technology. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

Foundry-fabricated photonic integrated circuit for flex-grid entanglement distribution

Foundry-fabricated photonic integrated circuit for flex-grid...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Miloshevsky, Alexander Lu, Hsuan-Hao Cohen, Lucas M. Myilswamy, Karthik V. Fatema, Saleha Alshowkan, Muneer Weiner, Andrew M. Lukens, Joseph M. Quantum Information Science Section Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Research Technology Office and Quantum Collaborative Arizona State University TempeAZ85287 United States

ISBN: (纸本)9781957171395

We demonstrate a silicon photonic integrated circuit fabricated through the CMOS manufacturing process, which features a bidirectionally pumped microring to achieve over 116 high-fidelity polarization entangled channels covering the entire optical C+L-band for flex-grid entanglement distribution. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Silicon photonics

来源：评论

学校读者我要写书评

暂无评论

Green Leaf Disease Detection Using Raspberry Pi and Random Forest Machine Learning Algorithm: An Automated Approach for Precision Agriculture 10

Green Leaf Disease Detection Using Raspberry Pi and Random F...

引用

10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Ranganathan, Chitra Sabapathy Basha, Amjath Ali Jakul Vijayalakshmi, A. Mohankumar, N. Sujatha, S. Sasikala, C. Mphasis Corporation Tamil Nadu Chennai India University of Technology and Applied Sciences Computer Engineering Electrical and Electronic Section Department of Engineering Ibra Oman Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Maharashtra Nagpur India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India Sri Sai Ranganathan Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350363104

Farm production and food security are affected by green leaf diseases. Modern disease detection technologies may discover plant health issues early. This work uses Raspberry Pi, a cheap and flexible single-board computer, along the advanced Random Forest machine learning technique to identify a green leaf disease. To identify crop diseases, the study uses automated, non-invasive technologies. From labeled images of good and sickly leaves, the algorithm extracts color histograms and texture, and form. It feeds a Random Forest classifier these properties for classifying data with high dimensions. Several green leaf diseased plant species were examined. This method detected plant health concerns with high precision. Movement and low cost make the Raspberry Pi ideal for remote and resource-limited agriculture, increasing farming accuracy. Helping farmers and users identify and develop green leaf diseases improves efficient farming. This methodology has the potential to improve crop management, optimize pesticide usage, and increase agricultural productivity. These results might contribute to the development of advanced automatic disease detection techniques to address green leaf diseases in modern agriculture. © 2024 IEEE.

关键词： computer Vision Green Leaf Plant Disease Detection Precision Agriculture raspberry pi

来源：评论

学校读者我要写书评

暂无评论

An ensemble model for predicting dispositions of emergency department patients

引用

BMC Medical Informatics and Decision Making 2024年第1期24卷 1页

作者： Kuo, Kuang-Ming Lin, Yih-Lon Chang, Chao Sheng Kuo, Tin Ju Department of Business Management National United University No.1 Miaoli Lienda 360301 Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology No. 123 University Road Section 3 Yunlin Douliou 64002 Taiwan Department of Emergency Medicine E-Da Hospital Kaohsiung City Taiwan Department of Occupational Therapy I-Shou University Kaohsiung City Taiwan Department of Computer Science and Information Engineering National Taitung University 369 Sec. 2 University Rd Taitung Taiwan

Objective: The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning’s potential to predict ED dispositions, thus leading to promising substantial benefits. This study’s objective is to create a predictive model for ED patient dispositions by employing ensemble learning. It harnesses diverse data types, including structured and unstructured information gathered during ED visits to address the evolving needs of localized healthcare systems. Methods: In this cross-sectional study, 80,073 ED patient records were amassed from a major southern Taiwan hospital in 2018–2019. An ensemble model incorporated structured (demographics, vital signs) and pre-processed unstructured data (chief complaints, preliminary diagnoses) using bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF). Two random forest base-learners for structured and unstructured data were employed and then complemented by a multi-layer perceptron meta-learner. Results: The ensemble model demonstrates strong predictive performance for ED dispositions, achieving an area under the receiver operating characteristic curve of 0.94. The models based on unstructured data encoded with BOW and TF-IDF yield similar performance results. Among the structured features, the top five most crucial factors are age, pulse rate, systolic blood pressure, temperature, and acuity level. In contrast, the top five most important unstructured features are pneumonia, fracture, failure, suspect, and sepsis. Conclusions: Findings indicate that utilizing ensemble learning with a blend of structured and unstructured data proves to be a predictive method for determining ED dispositions. © The Author(s) 2024.

关键词： Base-learner Emergency department disposition Ensemble learning Meta-learner Predictive disposition method

来源：评论

学校读者我要写书评

暂无评论

Research on the Current Situation and Development Strategies of Large-Scale K12 Online Education: A Case Study of a Province in Western China 12

Research on the Current Situation and Development Strategies...

引用

12th International Conference of Educational Innovation through Technology, EITT 2023

作者： Zhang, Le Li, Yun Yang, ShuRan Yuan, XiaoFan School of Computer Science and Engineering North Minzu University Yinchuan China Technical Service Section Ningxia Education Information Management Center Yinchuan China School of Education Ningxia University Yinchuan China

ISBN: (纸本)9798350383362

With the rise of modern information technologies such as computer technology, internet technology (especially 5G), artificial intelligence, big data, cloud computing, and mobile devices, the connotation, manifestation, and functional role of online teaching have undergone certain changes in the field of education. This study focuses on 1,744 primary and secondary school teachers in a province in western China. Through a questionnaire survey, it analyzes and studies the current situation of scaled K12 online teaching, teaching effectiveness, existing problems, and teaching needs. Based on this, it puts forward strategies for the deepening development of scaled K12 online teaching to promote the improvement of teaching quality. © 2023 IEEE.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Frequency Comb of Spectrally Pure Biphotons Using Time-Varying Cavities

Frequency Comb of Spectrally Pure Biphotons Using Time-Varyi...

引用

CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Gaines, Jordan A. Myilswamy, Karthik V. Lukens, Joseph M. Weiner, Andrew M. School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Research Technology Office and Quantum Collaborative Arizona State University TempeAZ85287 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States

We propose and analyze the use of linear, time-variant cavities to spectrally compress broadband frequency-correlated photon pairs into combs of spectrally pure biphotons. Our approach relies on rapid switching of inp... 详细信息

ISBN: (纸本)9781957171395

关键词： Broadband communication Couplings Electro-optical waveguides Photonics Switches Time-frequency analysis

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review of Emerging Approaches in Machine Learning for De Novo PROTAC Design

arXiv

引用

arXiv 2024年

作者： Gharbi, Yossra Mercado, Rocío Department of Computer Science and Engineering Section for Data Science and AI Chalmers University of Technology Chalmersplatsen 4 Gothenburg412 96 Sweden

Targeted protein degradation (TPD) is a rapidly growing field in modern drug discovery that aims to regulate the intracellular levels of proteins by harnessing the cell’s innate degradation pathways to selectively target and degrade disease-related proteins. This strategy creates new opportunities for therapeutic intervention in cases where occupancy-based inhibitors have not been successful. Proteolysis-targeting chimeras (PROTACs) are at the heart of TPD strategies, which leverage the ubiquitin-proteasome system for the selective targeting and proteasomal degradation of pathogenic proteins. This unique mechanism can be particularly useful for dealing with proteins that were once deemed "undruggable" using conventional small-molecule drugs. PROTACs are hetero-bifunctional molecules consisting of two ligands, connected by a chemical linker. As the field evolves, it becomes increasingly apparent that the traditional methodologies for designing such complex molecules have limitations. This has led to the use of machine learning (ML) and generative modeling to improve and accelerate the development process. In this review, we aim to provide a thorough exploration of the impact of ML on de novo PROTAC design — an aspect of molecular design that has not been comprehensively reviewed despite its significance. Initially, we delve into the distinct characteristics of PROTAC linker design, underscoring the complexities required to create effective bifunctional molecules capable of TPD. We then examine how ML in the context of fragment-based drug design (FBDD), honed in the realm of small-molecule drug discovery, is paving the way for PROTAC linker design. Our review provides a critical evaluation of the limitations inherent in applying this method to the complex field of PROTAC development. Moreover, we review existing ML works applied to PROTAC design, highlighting pioneering efforts and, importantly, the limitations these studies face. By offering insights into the current

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

Optimizing Variable-Strength Combinatorial Test Suite Generation via Fuzzy Adaptive Sine Cosine Algorithm (FASCA) 1

Optimizing Variable-Strength Combinatorial Test Suite Genera...

引用

1st International Conference on Cyber Security and Computing, CyberComp 2024

作者： Zabidi, Nur Syabila Ibrahim, Noraini Rejab, Mazidah Mat Mamat, MasrulEhsan Nazir, Sumaira Mat Tuselim, Nurul Hawani Faculty of Computer Science and Information Technology Parit Raja Batu Pahat Malaysia National University of Modern Languages Department of Software Engineering Islamabad Pakistan Industrial Research Management Centre SIRIM Berhad Business Intelligence Section Shah Alam Malaysia

ISBN: (纸本)9798350387728

Combinatorial test suite generation is a critical aspect of software testing, particularly for systems with variable-strength interactions. Traditional optimization algorithms often struggle to efficiently generate minimal test suites while maintaining coverage. This research introduces the Fuzzy Adaptive Sine Cosine Algorithm (FASCA), a variant of the Sine Cosine Algorithm (SCA), tailored specifically for optimizing variable-strength combinatorial test suite generation. FASCA incorporates fuzzy adaptation mechanisms to dynamically balance exploration and exploitation, addressing the limitations of standard SCA in handling diverse interaction strengths. Experimental evaluations demonstrate that FASCA significantly reduces test suite size and execution time compared to the original SCA, offering a more efficient solution for combinatorial test optimization. These results highlight FASCA's potential as a robust tool for enhancing the efficiency of software testing processes. © 2024 IEEE.

关键词： Software testing

来源：评论

学校读者我要写书评

暂无评论

Advancing Blackboard Framework: Responsive Trigger Mechanisms and Dynamic Feasibility Conditions for Optimal Knowledge Source Selection 19

Advancing Blackboard Framework: Responsive Trigger Mechanism...

引用

19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Muhd Mukhtar, Hana Munira Husin, Husna Sarirah Ismail, Suriana Rahmat, Azizah Ismail, Roslan Software Engineering Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia School of Computer Science Taylor’s University Kuala Lumpur Malaysia Centre of Innovative Digital Education & Emerging Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (纸本)9798331507817

Expert systems (ES) rely heavily on effective control mechanisms to navigate complex problem-solving tasks. These mechanisms govern how ES utilizes knowledge and data to make decisions and execute actions. Optimizing these mechanisms, or addressing the "control problem," remains a central challenge. Blackboard architectures, with their separation of knowledge and control processes, offer a promising approach. This study introduces an improved control mechanism for blackboard architectures. It focuses on a critical aspect—trigger mechanisms and feasible conditions—for optimal knowledge source selection to participate in the problem-solving process. By leveraging these features, this study aims to enhance decision-making and problem-solving capabilities within complex domains. This paper focuses on the technical details of exploring how it manages the flow of rule activation and execution throughout the problem-solving process. © 2025 IEEE.

关键词： Expert systems

来源：评论

学校读者我要写书评

暂无评论

MPI Allgather Utilizing CXL Shared Memory Pool in Multi-Node Computing Systems

MPI Allgather Utilizing CXL Shared Memory Pool in Multi-Node...

引用

IEEE International Conference on Big Data

作者： Hooyoung Ahn Seonyoung Kim Yoomi Park Woojong Han Shinyoung Ahn Tu Tran Bharath Ramesh Hari Subramoni Dhabaleswar K. Panda Supercomputing System Research Section Electronics and Telecommunications Research Institute Department of Computer Science and Engineering The Ohio State University

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In Artificial Intelligence (AI) and high-performance computing (HPC), growing data and model sizes require distributed processing across multiple nodes due to single-node limitations, increasing inter-node communication. To address these challenges, we propose a novel MPI allgather method leveraging CXL technology, which supports composable architectures and dynamic resource allocation in data centers and HPC systems. Notably, CXL 3.1 facilitates cache coherence among nodes. The proposed allgather method uses the CXL shared memory pool as a communication buffer, outperforming existing algorithms for two reasons: First, CXL provides lower latency than Ethernet and IB, and second, by using the CXL shared memory pool as a shared communication buffer across multiple nodes, it significantly reduces the number of communications. To the best of our knowledge, this work is the first to explore combining MPI collective communication with CXL technology to optimize MPI allgather. Our proposed allgather method significantly reduces communication latency compared to traditional allgather methods by up to 42.14x, with a minimum improvement of 2.91x, as measured using the OSU Micro-Benchmark (OMB), a standard MPI benchmarking suite.

关键词： High performance computing Heuristic algorithms Memory management Ethernet Dynamic scheduling Hardware Topology Resource management Artificial intelligence Standards

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：