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Titlebook: Advancement of Science and Technology; AI, Machine Learnin Abeba Birhane,Fekadu Shewarega,Ahunim Abebe Ashete Conference proceedings 2025

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發(fā)表于 2025-3-21 19:45:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advancement of Science and Technology
期刊簡(jiǎn)稱 AI, Machine Learnin
影響因子2023Abeba Birhane,Fekadu Shewarega,Ahunim Abebe Ashete
視頻videohttp://file.papertrans.cn/168/167196/167196.mp4
發(fā)行地址Presents the proceedings of the 11th EAI International Conference on Advancement of Science and Technology.Includes societal developments such as digitization, energy transformation, and impact on eco
學(xué)科分類EAI/Springer Innovations in Communication and Computing
圖書封面Titlebook: Advancement of Science and Technology;  AI, Machine Learnin Abeba Birhane,Fekadu Shewarega,Ahunim Abebe Ashete Conference proceedings 2025
影響因子This proceeding presents the papers from the 11th International Conference on Advancement of Science and Technology (ICAST 2023), which took place in Bahir Dar, Ethiopia, in November 2023. The papers present economic and technologic developments in modern societies related to important issues such digitization, energy transformation, impact on national economy, and its recent advancements. The papers are relevant to researchers, academics, and professionals.
Pindex Conference proceedings 2025
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書目名稱Advancement of Science and Technology影響因子(影響力)




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Bilingual Word-Level Language Identification for Omotic Languagesge, particularly in multilingual communities. Bilingual language identification (BLID) is the task of identifying and distinguishing between two languages in a given text. This paper presents BLID for languages spoken in the southern part of Ethiopia, namely, Wolaita and Gofa. The presence of words’
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ChatGPT in Education: Opportunities and Concerns for Functional English Sentence Structure Analysis ce human-like responses in the education context. To conduct this analysis, the paper includes a comprehensive review of relevant studies and articles on the use of ChatGPT in education. Additionally, the paper presents an experimental model for automatic question generation that focuses on function
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Music Genre Classification Using Deep Neural Network with Feature Selection and Optimization via Evo this study can categorize music correctly into its genre using machine learning techniques. This is accomplished by gleaning useful features from the music and employing an effective classification model. Different datasets, input formats, features taken from datasets, machine learning approaches,
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