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14th International Conference on Education technology and computers, ICETC 2022

作者： Souza, Adriana Freitas, Diamantino Bahia Federal Institute of Education Science and Technology Porto Seguro Bahia Brazil Doctoral Program in Digital Media Faculty of Engineering Faculty of Engineering of University of Porto Porto Portugal Department of Electrical and Computer Engineering Faculty of Engineering of University of Porto Porto Portugal

ISBN: (纸本)9781450397766

Voice synthesizers still present several challenges in the speech of mathematical content, as spoken mathematics has quite peculiar rules. In the synthesized speech, pauses help blind and visually impaired students identify the limits of mathematical operators and subexpressions. However, most studies on pauses define them uniformly or use simple punctuation marks to force the synthesizer to introduce pauses in certain parts of the expression. Speech is a dynamic process and pauses in expressions also need to be dynamic to make the synthetic speech of expressions more natural, as this can help in memorizing this type of content. This work proposed a dynamic model of pauses for mathematical expressions. Collected math expressions spoken by teachers were used to create the model. These expressions were useful for identifying patterns and creating a linear regression model. Blind and visually impaired students evaluated the model. Some improvements were observed when we compared the synthesized mathematical expressions with the model and Audiomath, the parameter tool used in this study. © 2022 ACM.

关键词： Dynamic models

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Poultry raising light control system for laying hens and broilers

Poultry raising light control system for laying hens and bro...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Thidarat Pinthong Thittaporn Ganokratanaa Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand

Chicken is an economic animal. one kind At present, it has been raised as a business and has expanded extensively. This is because both domestic and foreign populations have a greater demand for products and processed products from laying hens. which the raising of laying hens must be more attention to the productivity and quality of eggs in order to meet the needs of consumers with high or low temperatures Too low has an effect on the physiological system of laying hens. Reduce egg production or may result in inefficient production. And with the aforementioned problems, technology has been used to help in notifying. Warn whether the temperature in the house is suitable to increase the production of high-quality eggs.

关键词： Productivity Time-frequency analysis Technological innovation Animals Sleep Sociology Morphology

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Towards a Reliable Hierarchical Android Malware Detection Through Image-based CNN

Towards a Reliable Hierarchical Android Malware Detection Th...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Jhonatan Geremias Eduardo K. Viegas Altair O. Santin Alceu Britto Pedro Horchulhack Pontificia Universidade Catolica do Parana (PUCPR) - Graduate Program in Computer Science (PPGIa) Brazil Secure Systems Research Center - Technology Innovation Institute (TII) Abu Dhabi

The number of Android malicious applications keeps growing as time passes, even paving their way to official app markets. In recent years, a promising malware detection approach makes use of the compiled app source codes (dex), through convolutional neural networks (CNN) as an image classification task. Unfortunately, current proposals often rely on unrealistic datasets, focusing their detection on the mal-ware families, while neglecting the detection of malware apps in the first place. In this paper, we propose a reliable and hierarchical Android malware detection through an image-based CNN scheme, implemented twofold. First, Android malware classification is performed in a hierarchically-structured local manner, initially identifying malware apps, then, their related family. Second, to ensure reliability and improve classification accuracy, only highly confident classified apps are reported, in a classification with reject option rationale. Experiments performed in a new dataset with over 26 thousand Android apps, divided into 29 malware families, compounding over 13 GB of app dex images, have shown that current image-based CNN for malware detection is unable to provide high detection accuracies. In contrast, our proposed model is able to reliably detect malware apps, improving the true-negative rates by up to 5.5%, and the average true-positive rate of the malware families of accepted apps by up to 12.7%, while rejecting only 10% of Android apps.

关键词： Source coding Focusing Malware Convolutional neural networks Reliability Proposals Task analysis

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The Deep Learning Approach For American Sign Language Detection

The Deep Learning Approach For American Sign Language Detect...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Gusti Pangestu Yaya Heryadi Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduate Program Computer Science. Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Sign language has importance rule to deal with communication process especially with impairments hearing people. Sign language detection also attract lot of researchers to join the challenge of research to detect and recognize the sign language in the field of computer science. Hence, there is still no any standard approach and method to recognize the meaning in every pose of sign language. This research proposed a mechanism to detect Alphabet American Sign Language by utilizing Convolutional Neural Network (CNN) process. The CNN approach was chosen based on the ability and capability to recognize image. In this research, MNIST dataset is used for traning and testing process. The proposed CNN architecture produced 97% of accuracy that outperform the previous research using the same dataset which made this architecture promising.

关键词： Deep learning computer science Image recognition Gesture recognition computer architecture Auditory system Assistive technologies

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Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Jamalipour, Abbas Mao, Shiwen Kim, Dong In The College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The College of Computing and Data Science Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Auburn University Auburn United States The School of Electrical and Computer Engineering University of Sydney Australia The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However, the evolution of the Metaverse is slowed down by the challenges of content creation, scalability, and dynamic user interaction. Our study investigates an integration of Mixture of Experts (MoE) models with Generative Artificial Intelligence (GAI) for mobile edge computing to revolutionize content creation and interaction in the Metaverse. Specifically, we harness an MoE model's ability to efficiently manage complex data and complex tasks by dynamically selecting the most relevant experts running various sub-models to enhance the capabilities of GAI. We then present a novel framework that improves video content generation quality and consistency, and demonstrate its application through case studies. Our findings underscore the efficacy of MoE and GAI integration to redefine virtual experiences by offering a scalable, efficient pathway to harvest the Metaverse's full potential. © 2024, CC BY.

关键词： Augmented reality

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E-Learning Satisfaction: Analysis of the Support Factors

E-Learning Satisfaction: Analysis of the Support Factors

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International Conference on Information technology, computer and Electrical Engineering (ICITACEE)

作者： Boby Siswanto Doni Purnama Alamsyah Doni Morika Norfaridatul Akmaliah Othman Billiam Christofer Wijaya Putri Giyan Adinda Computer Science Study Program School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department BINUS Business School Bina Nusantara University Jakarta Indonesia Interior Design Study Program School of Design Bina Nusantara University Jakarta Indonesia Department of Management Technology Universiti Teknikal Malaysia Melaka Melaka Malaysia

E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e-learning platform, using Big Data technology as the basis for its development.

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Model-Assisted Probabilistic Safe Adaptive Control With Meta-Bayesian Learning

arXiv

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arXiv 2023年

作者： Wang, Shengbo Li, Ke Yang, Yin Cao, Yuting Huang, Tingwen Wen, Shiping College of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Department of Computer Science University of Exeter ExeterEX4 4QF United Kingdom College of Science and Engineering Hamad Bin Khalifa University Doha5855 Qatar Science Program Texas A & M University at Qatar Doha23874 Qatar Australian AI Institute Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

Breaking safety constraints in control systems can lead to potential risks, resulting in unexpected costs or catastrophic damage. Nevertheless, uncertainty is ubiquitous, even among similar tasks. In this paper, we develop a novel adaptive safe control framework that integrates meta learning, Bayesian models, and control barrier function (CBF) method. Specifically, with the help of CBF method, we learn the inherent and external uncertainties by a unified adaptive Bayesian linear regression (ABLR) models, which consists of a forward neural network (NN) and a Bayesian output layer. Meta learning techniques are leveraged to pre-train the NN weights and priors of the ABLR model using data collected from historical similar tasks. For a new control task, we refine the meta-learned models using a few samples, and introduce pessimistic confidence bounds into CBF constraints to ensure safe control. Moreover, we provide theoretical criteria to guarantee probabilistic safety during the control processes. To validate our approach, we conduct comparative experiments in various obstacle avoidance scenarios. The results demonstrate that our algorithm significantly improves the Bayesian model-based CBF method, and is capable for efficient safe exploration even with multiple uncertain constraints. Copyright © 2023, The Authors. All rights reserved.

关键词： Multilayer neural networks

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Home smart alarm system for the visually impaired

Home smart alarm system for the visually impaired

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Cybernetics and Innovations (ICCI), International Conference on

作者： Worawut Yimyam Thittaporn Ganokratanaa Department. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand

This research aims to study the working principles of IOT devices or Internet of Things in order to promote the use of information technology systems, both hardware and software, with visually impaired people. rehabilitation of persons with disabilities, enhancing the capacity or ability of persons with disabilities to improve their condition or or existing capabilities through the advancement of technology so that people with disabilities have the opportunity to work or live in society to the full potential of the researcher The concept of technology acceptance model (technology Acceptance Model or TAM) to help further develop This research shows the importance of information technology systems, both hardware and software, to visually impaired people, which is the basis for product development of healthcare service businesses in the future.

关键词： Technological innovation technology acceptance model Medical services Software Hardware Product development Internet of Things

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Relational database reconstruction from SQL to Entity Relational Diagrams 4

Relational database reconstruction from SQL to Entity Relati...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Hakim Lubis, Juanda Muisa Zamzami, Elviawaty Faculty of Computer Science and Information Technology Doctoral Program of Computer Science Studies Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

The absence of requirement documents or incompatibility of the requirement documents with existing software can be a problem in developing or maintaining software. Without knowing things that become requirements can cause software as a product that fails because it does not meet customer desires. One of the main problems in developing or maintaining software is that developers do not know the entity relational schema of the software. So developers will prefer to rebuild from scratch. This paper discusses database reconstruction from SQL to entity relational diagrams by identifying the primary and foreign keys of SQL sampling. © Published under licence by IOP Publishing Ltd.

关键词： Condensed matter physics

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Mobile Collaborator System Application for E-commerce Drugstore 8

Mobile Collaborator System Application for E-commerce Drugst...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Oktavia, Tanty Michael Gaol, Ford Lumban Hosoda, Takaaki Bina Nusantara University School of Information Systems Information Systems Department Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program-Computer Science Computer Science Department Jakarta11530 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (纸本)9781665416979

Mostly Drugstores do not have any system that exclusively connect to access E-commerce system because the marketing concept of drugstores still use conventional store to sell their products. According to this situation, this study will propose e-commerce that accomodate drugstore service. For this study, the analysis methodology consists of seeing the most recent business processes in the e-commerce system system and the current situation in drugstore, interviewing the drugstore owner, and doing a literature research. Then, for the drugstore mobile application, create the Unified Modeling Language (UML). The system design is accomplished through the creation of Object-Oriented Detailed Designs in the form of diagrams, databases, and user interfaces. The drugstore mobile application, which includes features such as recommendation product menus, best-selling product menus, promo product menus, transaction cart menus, order tracking menus, order letter menus, and item receive confirmation menus, is the result of this study. © 2021 IEEE.

关键词： User interfaces

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