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Towards personalized control of things using Arabic voice commands for elderly and with disabilities people

International Journal of information technology (Singapore) 2023年 1-22页

作者： Salah, Abdelrahman Adel, Ghada Mohamed, Hussein Baghdady, Youssef Moussa, Sherin M. Department of Software Engineering and Information Technology Faculty of Engineering and Technology Egyptian Chinese University Cairo 11351 Egypt Department of Information Systems Faculty of Computer and Information Sciences Ain Shams University Cairo 11566 Egypt Laboratoire Interdisciplinaire de l’Université Française d’Égypte (UFEID Lab) Université Française d’Égypte Cairo 11837 Egypt

Considering recent smart home solutions that automate home appliances through voice commands, elderly people and/or with special needs prefer using their mother-tongue. However, most of current systems adopt the English language, making it harder for non-native English speakers, while personalization is not heavily considered. In this paper, we propose the Arabic Personalized Control of Things (APCoT) system that achieves inhabitant-tailored home automation through Arabic voice commands based on the user’s preferences to control a home device. A new dataset is created for a wider range of Arabic voice commands to interact with home appliances rather than just turning them on/off. Internet of Things, voice and speech recognition are utilized to attain personalization according to the inhabitants' voiceprints, while infrared is adopted to control non-smart devices supporting infrared signals. As a Proof-of-Concept, three home appliances are adopted: TV, Lights and Bluetooth speaker. Machine learning algorithms are customized for Arabic voice recognition, integrating face and hand gestures recognition to provide an additional facility for inhabitant’s identification and sending control commands respectively. The experimental results indicate that the best average accuracies obtained for Arabic voice recognition were 99.63% for a single speaker and 95.4% for multi-speakers, with average response times 0.141s and 14.29s respectively. For speech recognition, Google online API and a customized Vosk offline pretrained model achieved average accuracies of 95% and 90%, average response times 0.7553s and 0.3933s respectively. The face and hand gestures recognition achieved average accuracies of 90% and 98%, average response times 0.5934s and 15.62049s respectively. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Arabic commands Elderly people Home automation People with disabilities Smart home Speech and voice recognition

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Review of Energy Management systems for Small and Medium Enterprises 8

Review of Energy Management Systems for Small and Medium Ent...

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8th Junior Conference on Lighting, Lighting 2023

作者： Vacheva, Gergana Stanchev, Plamen Hinov, Nikolay Technical University of Sofia Faculty of Electronic Engineering and Technologies Departement of Power Electronics Sofia Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Technology in Industry Sofia Bulgaria

ISBN: (纸本)9798350328295

This article provides an overview of systems and methodologies used for energy management in small and medium-sized industrial enterprises. The main goal of the presented development is to examine basic principles in the management of energy flows in industrial enterprises powered by various renewable energy sources and energy storage elements. With the addition of additional energy sources, energy efficiency would significantly increase, which would also lead to a reduction in electricity costs. © 2023 IEEE.

关键词： Energy efficiency

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Novel vision transformer and data augmentation technique for efficient detection of monkeypox disease

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Multimedia Tools and Applications 2024年 1-19页

作者： Alarfaj, Aisha Ahmed Ahmad, Salman Hakeem, Abeer M. Alabdulqader, Ebtisam Abdullah PERO, Chiara Alsubai, Shtwai Innab, Nisreen Ashraf, Imran Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Post Graduate Resident Department of Urology Allama Iqbal Teaching Hospital Dera Ghazi Khan Pakistan Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Information Technology College of Computer and Information Sciences King Saud University P. O. Box 800 Riyadh11421 Saudi Arabia Department of Management & amp Innovation Systems University of Salerno Via Giovanni Paolo II 132 Fisciano Salerno Italy Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj11942 Saudi Arabia Department of Computer Science and Information Systems College of Applied Sciences AlMaarefa University Diriyah Riyadh13713 Saudi Arabia Department of Information and Communication Engineering Yeungnam University Gyeongsan Korea Republic of

Recent technological advancements have paved the way for the optimization of medical processes, particularly automated disease detection. Moreover, the adoption of machine learning (ML) has greatly helped in automating disease detection. Such approaches can detect various diseases early, enabling timely treatment to save countless lives. Early and accurate diagnosis is very important for diseases like monkeypox, to curb its spread. Monkeypox is a viral disease caused by double-stranded DNA and can be transmitted through close contact with infected humans or animals. It’s early identification and accurate lesion diagnosis are critical to contain the disease. This study proposes an automated approach to optimize the diagnosis of monkeypox disease using a novel vision transformer, which is utilized due to its effectiveness for feature extraction. The Proposed approach’s efficiency and accuracy are tested on a public benchmark dataset comprising a variety of skin lesions of different ages and genders. In addition, data augmentation involves rotation, scaling, and flipping thereby enhancing the density of the training data set for better generalization of ML models. Experiments involve binary, as well as, multi-class classification. For the binary class, the proposed model achieves an accuracy of 97.63%, outperforming traditional ML and deep learning (DL) techniques. In the case of multi-class classification with monkeypox, measles, normal, HFMD, cowpox, and chickenpox classes, the proposed model archives an accuracy of 90.61% while precision, recall, and F1 scores are 91.39%, 89.17%, and 90.28%, respectively. Furthermore, the proposed approach shows average accuracy, precision, recall, and F1 scores of 97.54%, 96.19%, 95.16%, and 95.67%, respectively for five-fold cross-validation. Experiments demonstrate that the combination of data augmentation techniques and the vision transformer model significantly optimizes diagnostic performance. In brief, advanced DL architectur

关键词： Medical image processing

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Study of Factors Influencing on Mental Health and Their Relationships, of IT Sector Employees in Colombo District, Sri Lanka 5

Study of Factors Influencing on Mental Health and Their Rela...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Dias, S.P.L. Lokuliyana, S. University of Sabaragamuwa Faculty of Applied Sciences Department of Physical Sciences and Technology Belihuloya Sri Lanka Sri Lanka Institute Information Technology Faculty of Graduate Studies and Research Department of Computer Systems and Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

This study focused on the mental health of IT sector employees in Colombo, using quantitative research methods and data from 300 participants (162 males and 138 females) using the DASS 21 questionnaire and self-administered surveys through convenience sampling. Correlation analysis, chi-square tests, and regression analysis were utilized to examine the data. It found significant correlations between mental health outcomes (stress, anxiety, and depression) and factors like work-life balance, workload, working conditions, and physical fitness. Work-life balance, working environment, and workload were identified as the most significant predictors of mental health outcomes. Physical fitness was associated with stress, depression, and anxiety but had a limited overall impact on mental health. Differences in depression, stress, and anxiety levels were observed based on marital status, age group, work experience, salary, and gender. These findings emphasize the importance of addressing work-life balance and working conditions to enhance the mental health of IT sector employees in Colombo. They provide valuable insights for organizations and policymakers to develop strategies and interventions that promote employee well-being and productivity, underscoring the need to prioritize mental health and create a supportive work environment. © 2023 IEEE.

关键词： Regression analysis

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Realizing Global Citizen Solutions for Sustainable Development Goals: A Collaborative engineering Course Between Thai and Japanese Students 23

Realizing Global Citizen Solutions for Sustainable Developme...

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23rd International Symposium on Communications and information Technologies, ISCIT 2024

作者： Sae-Jia, Thanachot Leelawat, Natt Tang, Jing Murakami, Rie Taoka, Yuki Ota, Eri Punyabukkana, Proadpran Chulalonkorn University Faculty of Engineering Department of Environmental Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan International School of Engineering Chulakongkorn University Faculty of Engineering Bangkok Thailand Global Education Section Center for Entrepreneurship Education Tokyo Institute of Technology Tokyo Japan School of Environment and Society Tokyo Institute of Technology Tokyo Japan Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350353952

One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo Institute of technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.

关键词： Sustainable development goals

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Evaluation and Measures for Improving the Energy Efficiency of Medium-Sized Enterprises 8

Evaluation and Measures for Improving the Energy Efficiency ...

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8th Junior Conference on Lighting, Lighting 2023

作者： Stanchev, Plamen Vacheva, Gergana Hinov, Nikolay Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Technology in Industry Sofia Bulgaria Technical University of Sofia Faculty of Electronic Engineering and Technologies Departement of Power Electronics Sofia Bulgaria

ISBN: (纸本)9798350328295

In the presented article, an assessment and measurements were realized to determine the energy efficiency of a medium-sized industrial enterprise. Real data from a three-shift plant was used. An assessment of the current electricity consumption was made and an energy audit was carried out to reduce electricity costs. The main goal of the current research is to ensure the basic functionality of the buildings, as well as the production-Technological process, ensuring minimum electricity costs and maximum efficiency. © 2023 IEEE.

关键词： Energy efficiency

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Arabic Sentiment Analysis of Mobile Banking Services Reviews 10

Arabic Sentiment Analysis of Mobile Banking Services Reviews

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10th International Conference on Social Networks Analysis, Management and Security, SNAMS 2023

作者： Khabour, Safaa M. Mustafa, Dheya Althebyan, Qutaibah Yarmouk University Faculty of Information Technology and Computer Sciences Dept. of Information Systems Irbid21163 Jordan The Hashemite University Faculty of Engineering Dept. of Computer Engineering Zarqa13133 Jordan Al Ain University Dept. of Cybersecurity Al Ain United Arab Emirates Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9798350318906

Online customer reviews have developed into a significant source of information about a business's performance. Due to shifting consumer expectations and growing internet penetration, the Middle East, especially Jordan, is seeing an increase in the usage of online banking. This propensity toward digital transition has been accelerated by the COVID-19 pandemic. Mobile banking service companies aim to effectively use customers' feedback to identify areas for improvement in customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on mobile banking reviews in Arabic, exploiting machine learning, natural language processing, and resampling methods to obtain subjective feedback, determine polarity, and identify customers' feelings in the banking domain. This work walks the reader through detailed steps of cleaning and preprocessing a manually annotated dataset of online banking reviews in Arabic, followed by features extraction and modeling, dataset splitting, and balancing training data. Finally, we examined classification algorithms including Decision Tree (DT), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Random Forest (RF). Ensemble hard and soft voting ML methods were also evaluated. We achieved a maximum accuracy of about 94% using the LR classifier and a maximum precision of 94% using the LR and hard voting methods. Our methodology will enable banks to acquire insights on how to develop their online presence and meet the demands of customers and stakeholders. © 2023 IEEE.

关键词： Sentiment analysis

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Smart Advertising Based on Customer Preferences and Manage the Supermarket 4

Smart Advertising Based on Customer Preferences and Manage t...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Eishan Dinuka, W.H.A. Wickramasinghe, A.Y.S.W. Weerasinghe, W.S.H. Karunaratne, K.P.G. Liyanapathirana, Chethana Rupasinghe, Lakmal Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users' feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users' preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly. © 2022 IEEE.

关键词： Sales

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7th International Conference of computer and Informatics engineering, IC2IE 2024

作者： Wandy, Wandy Adi, Kusworo Ayu, Media Anugerah Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Sampoerna University Faculty of Engineering and Technology Department of Computer Science South Jakarta Indonesia

ISBN: (纸本)9798331505530

Full-marathon and Half-marathon distances are categorized as road running. Full-marathon running is becoming increasingly popular, and Half-marathon is increasing worldwide in both sexes and all age groups. Some aspects might relate to Full-marathon and Half-marathon running performance during training and races. technology also plays an essential role in supporting runners and running races. technology like artificial intelligence (AI) now supports the running athlete, not only predicting performance and results. It can also be used later to help the coach generate training programs for the athlete. This research aimed to find many aspects of marathons and performance and analyze them to see if artificial intelligence could later support them. It used secondary data and a systematic literature review proposed by Kitchenham. Out of the 58 articles, 21 of them (36.21%) received a score of 1 from Q1. Additionally, 19 articles (32.76%) received a score of 1 from both Q2 and Q3. Among the 58 articles, 9 (15.52%) received a total score of 3, with all three Q1, Q2, and Q3 scores being 1. This indicates that artificial intelligence will likely support the content of these nine articles. Several factors were also discovered to be connected to marathons and athletic performance. These findings suggested that additional investigation into marathons and performance, later backed by artificial intelligence, remained pertinent and essential. © 2024 IEEE.

关键词： artificial intelligence aspects marathon performance

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A Model for a Mobile-enabled e-Health System in Saudi Arabia for the Self-management of Diabetes 38

A Model for a Mobile-enabled e-Health System in Saudi Arabia...

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38th information systems Education Conference, ISECON 2022

作者： Alanazi, Fuhid Gay, Valerie Alturki, Ryan Faculty of Engineering and Information Technology University of Technology Sydney Australia Department of Information Sciences College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia

This paper prescribes the design requirements for a mobile-enabled e-health system for the self-management of diabetes by Saudi diabetes patients. The findings from a survey and a focus group were integrated to achieve this. The requirements, challenges and problems were identified and were supported by published works on the topic. The findings showed that since a variety of stakeholders are involved in such an ecosystem, it is imperative to ensure smooth coordination and an improvement in the outreach of public health campaigns. The findings thus far have highlighted the demographic groups to be targeted for designing and implementing targeted interventions to tackle diabetes in Saudi Arabia. Doing this would require interventions in the healthcare system, hospital and home-based management, and targeted patient interventions. The finer aspects of the system design need to be determined based on similar successful models and expert opinions. Some comments on the boundaries of this research are also provided. © ISECON 2022. All Rights Reserved.

关键词： Patient treatment

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