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 (...
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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 learnin...
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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 lea...
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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.
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-sy...
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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 power...
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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
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 p...
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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...
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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 ...
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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.
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 param...
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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 a...
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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.
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