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3rd International Conference on Artificial Intelligence and Data Sciences, AiDAS 2022

作者： Tuh, Moi Hua Kon, Cynthia Mui Lian Chua, Hong Siang Lau, Man Fai Hui Chang, Robin Yee Swinburne University of Technology Faculty of Engineering Computing and Science Sarawak Kuching Malaysia Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Sarawak Kota Samarahan Malaysia School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia Universiti Teknologi Mara Faculty of Applied Sciences Sarawak Kota Samarahan Malaysia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

The Markov chain method has been adopted in this work to evaluate the performance of the synthetic double sampling (SynDS) np chart, which combines the double sampling (DS) np sub-chart and the conforming run length (CRL) sub-chart. In the literature, the performance of the existing SynDS np chart is investigated using average run length (ARL). It is found that the skewness of the run length (RL) distribution varies depending on the size of shift in the process fraction nonconforming, from being significantly right-skewed when the process is in-control (IC) or small shift to being nearly symmetric when the process shift is large. As a result, the true performance of the chart may differ from what the ARL displays. Thus, median run length (MRL) is recommended to represent the central tendency associated with the varying shapes of the RL distribution in accordance to the process shift sizes. This work suggests an optimal design approach for SynDS np chart based on MRL to monitor the process fraction nonconforming, under zero-state and steady-state modes. © 2022 IEEE.

关键词： Control charts

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A Comparative Study of Recent 2D Human Pose Estimation Methods 6

A Comparative Study of Recent 2D Human Pose Estimation Metho...

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6th International Conference on computing and Informatics, ICCI 2024

作者： Elshami, Nada E. Salah, Ahmad Mohsen, Heba Department of Computer Science Faculty of Computers and Information Technology Future University in Egypt New Cairo Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman College of Computers and Informatics Zagazig University Zagazig Egypt

ISBN: (纸本)9798350373875

Human Pose Estimation is a computer vision technique utilized in various fields such as healthcare, security, and sports to detect the pose of single or multi-person utilizing various machine learning and deep learning methodologies. These methodologies can be applied in a variety of ways, including top-down and bottom-up approaches. Furthermore, this technique can be used with images or videos, as well as in 2D or 3D domains. This paper delves into recent advancements in deep learning methods used for estimating the pose, covering commonly employed datasets, evaluation metrics, and the challenges encountered in this field. It aims to assist new researchers in getting familiar with this technique based on work published between 2019 and 2023, with a spotlight on 2D and omitting 3D. © 2024 IEEE.

关键词： Deep learning

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A Robust Model for Translating Arabic Sign Language into Spoken Arabic Using Deep Learning

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Intelligent Automation & Soft computing 2023年第8期37卷 2037-2057页

作者： Khalid M.O.Nahar Ammar Almomani Nahlah Shatnawi Mohammad Alauthman Department of Computer Sciences Faculty of Information Technology and Computer SciencesYarmouk University-Irbid21163Jordan School of Computing Skyline University CollegeSharjahP.O.Box 1797United Arab Emirates IT-Department-Al-Huson University College Al-Balqa Applied UniversityP.O.Box 50IrbidJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan

This study presents a novel and innovative approach to auto-matically translating Arabic Sign Language(ATSL)into spoken *** proposed solution utilizes a deep learning-based classification approach and the transfer learning technique to retrain 12 image recognition *** image-based translation method maps sign language gestures to corre-sponding letters or words using distance measures and classification as a machine learning *** results show that the proposed model is more accurate and faster than traditional image-based models in classifying Arabic-language signs,with a translation accuracy of 93.7%.This research makes a significant contribution to the field of *** offers a practical solution for improving communication for individuals with special needs,such as the deaf and mute *** work demonstrates the potential of deep learning techniques in translating sign language into natural language and highlights the importance of ATSL in facilitating communication for individuals with disabilities.

关键词： Sign language deep learning transfer learning machine learning automatic translation of sign language natural language processing Arabic sign language

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A stroking device for spatially separated couples 08

A stroking device for spatially separated couples

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10th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2008

作者： Eichhorn, Elisabeth Wettach, Reto Hornecker, Eva Potsdam University of Applied Sciences Faculty of Design Pappelallee 8-9 14469 Potsdam Germany Open University Pervasive Interaction Lab Faculty of Mathematics Computing and Technology Milton Keynes MK7 6AA United Kingdom

ISBN: (纸本)9781595939524

In this paper we present a device to support the communication of couples in long-distance relationships. While a synchronous exchange of factual information over distance is supported by telephone, e-mail and chat-systems, the transmission of nonverbal aspects of communication is still unsatisfactory. Videocalls let us see the partners' facial expression in real time. However, to experience a more intimate conversation physical closeness is needed. Stroking while holding hands is a special and emotional gesture for couples. Hence, we developed a device that enables couples to exchange the physical gesture of stroking regardless of distance and location. The device allows both sending and receiving. A user test supported our concept and provided new insights for future development. © 2008 ACM.

关键词： Interactive computer systems

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A Review of Effectiveness and Efficiency Methodology of Decision Support System for Selecting Suppliers 1

A Review of Effectiveness and Efficiency Methodology of Deci...

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1st International Conference on Computer Science and Emerging Technologies, CSET 2023

作者： Alzoubi, Sharaf Amayreh, Khalid Thaher Farea, Mazen Mohammed Baker El-Ebiary, Yousef A. Ahmad Saany, Syarilla Iryani Bisht, Neeraj Information Technology Department Jordan Irbid National University Faculty of Finance Science and Business Business Administration Department Jordan Al-Madinah International University Faculty of Finance & Administrative Sciences Malaysia UniSZA Faculty of Informatics and Computing Malaysia Birla Institute of Applied Sciences Bhimtal India

ISBN: (纸本)9798350341737

In today's highly competitive global business environment, effective supplier selection plays a crucial role in the success and sustainability of organizations. Decision Support Systems (DSS) have emerged as powerful tools to aid in this complex process by providing valuable insights and data-driven recommendations for selecting suppliers. This research paper presents a comprehensive review of the methodologies used to assess the effectiveness and efficiency of Decision Support Systems employed in supplier selection processes. The primary objective of this study is to evaluate and compare the various methodologies applied in Decision Support Systems, focusing on their effectiveness and efficiency in assisting decision-makers during supplier selection. The research critically analyzes a range of published literature, academic papers, and case studies to highlight the strengths and limitations of different DSS methodologies in this context. The paper commences by elucidating the fundamental concepts of supplier selection and the significance of Decision Support Systems in streamlining this multifaceted process. Subsequently, a systematic review of existing literature is conducted to identify the key methodologies employed in DSS frameworks. Furthermore, the research explores the novel integration of emerging technologies, such as Artificial Intelligence, Machine Learning, and Big Data analytics, within Decision Support Systems for supplier selection. This investigation aims to discern how these advanced techniques contribute to the enhancement of decision-making precision and the overall efficiency of the selection process. By critically analyzing and comparing the effectiveness and efficiency of various Decision Support System methodologies, this research seeks to provide valuable insights for both academics and practitioners in supply chain management. The findings of this study will enable decision-makers to make informed choices regarding the adoption and customiz

关键词： Decision support systems

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A roadmap to data science: Background, future, and trends

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International Journal of Intelligent Information and Database Systems 2021年第3期14卷 277-293页

作者： Khder, Moaiad Ahmad Fujo, Samah Wael Sayfi, Mohammad Adnan Department of Computer Science Applied Science University Bahrain Department of Computing Engineering and Technology Faculty of Applied Sciences University of Sunderland United Kingdom

Data science is a combination of several disciplines that aims to get accurate insights from a bunch of data, develop the technology, and algorithm to solve the complicated problems analytically. Today, data science plays a massive role in our life, and researchers realise how it is essential. Numerous research studies on data science have been published in recent years, but each focus on specific issues, such as data science and its impact on business, manufacturing, academia, and healthcare. This paper will present a roadmap of data science to benefit the readers to know about this field and realise how it is essential in several areas. In addition, it clarifies the mechanism of how data science work and what are the capabilities of the data scientist to be able to work in this field. It also shows the trends and future work of data science. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Big data

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Parametrized Benchmarking: An outline of the idea and a feasibility study 20

Parametrized Benchmarking: An outline of the idea and a feas...

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2020 Genetic and Evolutionary Computation Conference, GECCO 2020

作者： Opara, Karol R. Hadi, Anas A. Mohamed, Ali W. Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia School of Engineering and Applied Sciences Nile University Giza Egypt

ISBN: (纸本)9781450371278

Performance of real-parameter global optimization algorithms is typically evaluated using sets of test problems. We propose a new methodology of extending these benchmarks to obtain a more balanced experimental design. This can be done by selectively removing some of the transformations originally used in the definitions of the test problems such as rotation, scaling, or translation. In this way, we obtain several variants of each problem parametrized by interpretable, high-level characteristics. These binary parameters are used as predictors in a multiple regression model explaining the algorithmic performance. Linear models allow for the attribution of strength and direction of performance changes to particular characteristics of the optimization problems and thus provide insight into the underlying mechanics of the investigated algorithms. The proposed ideas are illustrated with an application example showing the feasibility of the new benchmark. Parametrized benchmarking is a step towards obtaining multi-faceted insight into algorithmic performance and the optimization problems. The overall goal is to systematize a method of matching problems to algorithms and in this way constructively address the limitations imposed by the no free lunch theorem. © 2020 Owner/Author.

关键词： Benchmarking

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The development of online trust among construction teams in Finland

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Electronic Journal of Information technology in Construction 2007年 12卷 305-321页

作者： Uden, Lorna Naaranoja, Marja Faculty of Computing Engineering and Technology Staffordshire University United Kingdom Vaasan Ammattikorkeakoulu University of Applied Sciences Finland

Construction is a complex process involving many different stakeholders. It is important that information among these stakeholders flows smoothly. A crucial aspect of the success of a project depends on the effective sharing of knowledge among the different people. Trust is important for knowledge transfer especially for online applications. There are different types of trust that have implications for knowledge sharing among the construction teams. This paper describes the importance of trust that we have identified during knowledge sharing among four construction projects in Finland. It begins with identification of the needs of online technology among construction teams. It is followed by a brief review of the different types of online trust. Section Three describes the case study methodology. In Section Four the implications of the online trust among construction teams are then discussed. Section Five concludes with suggestions for promoting trust among construction teams for knowledge sharing.

关键词： Online systems

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Research on complex system fault prediction method for massive data 4

Research on complex system fault prediction method for massi...

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4th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2021

作者： Niu, Wei Cheng, Juan Song, Xiaogang Xi'An Aeronautics Computing Technique Research Institute AVIC Xi'an China Xi'An Institute of Applied Optics Xi'an China Xi'an China Faculty of Computer Science and Engineering Xi'An University of Technology Xi an China

ISBN: (纸本)9781665415965

Fault prediction is a challenging problem of complex system. Furthermore, fault prediction plays a critical role in aircraft engines and the performance of their control systems. Using the robustness analysis of parametric uncertain systems, an improved algorithm is proposed for massive data. The algorithm takes the parametric uncertainties into consideration which can distinguish an actual fault from the model uncertainties. Application to an aircraft engine clearly illustrates the improved performance of the proposed method, the results show that the proposed method helps the system accommodate parametric uncertainties in the model and reduce false alarms and missed detection. © 2021 IEEE.

关键词： Aircraft engines

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A plausible ancestor generator an experiment with heuristics, screen scraping and geolocs

A plausible ancestor generator an experiment with heuristics...

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International Conference on the Current Trends in Information technology (CTIT)

作者： Ken Newman Faculty of Computing Information Systems and Applied Communications Higher Colleges of Technology Dubai UAE

This paper demonstrates methods for creating a server application with the task of generating a plausible family tree based on the user. The application does not try to be factual, merely plausible. In creating this app a number of server based techniques are employed to solve the various problems. 1 - Heuristics were defined to simulate plausible birth and death dates, and also the parent's age at the birth of the each generation. 2 - Screen scraping techniques were employed to harvest names from name databases which did not offer an api. 3 - Google places api was used to select a plausible birthplace for each ancestors. 4 - Wikibots were used to retrieve a plausible occupation plausible for each ancestor. The purpose of this study is to investigate how a variety of servers-based methods can be employed within a single application to provide a complex result which appears intelligent, has a certain level of semantic credibility, is fun, engaging for the user and appears entirely plausible.

关键词： Geology Generators Google Semantics Feeds History

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