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International Conference on ICT For Smart Society (ICISS)

作者： Fairuz Iqbal Maulana Bambang Kartono Kurniawan Andi Pramono Agung Purnomo Muhamad Ezran Bin Zainal Abdulah Mustafa Mohamed Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Department of Design and Creative Technology Faculty of Creative Technology and Heritage Universiti Malaysia Kelantan Bachok Kelantan School of Technology of the Arts Republic Polytechnic Singapore

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Smart furniture has emerged as a significant area of interest in scientific research over the past decade. This bibliometric analysis aims to explore the trends in scientific research related to smart furniture from 2014 to 2023. By examining a range of scholarly articles, this study delves into the evolution of smart furniture technologies, applications, and implications. The research reveals a growing interest in integrating intelligent systems into furniture design, enabling network connectivity and user-controlled operations. Despite the growing number of studies, the research landscape remains fragmented, necessitating a comprehensive bibliometric analysis to consolidate existing research and identify trends. Data selection from the Scopus database yielded a total of 97 documents from 69 sources, with average citations per doc is 8.041. On the corresponding author's countries, China is the highest country. Moreover, terms like “smart furniture” that expand in size and extend to the right of the chart indicate a growing emphasis in recent literature, signaling potential areas of increased research activity. Smart furniture is characterized as furniture that is connected to a network and equipped with intelligent technologies that make use of user data and energy sources. The study underscores the importance of addressing issues such as ease of use, privacy, security, and affordability in implementing smart furniture solutions. This study provides valuable insights into the current state and future prospects of smart furniture research, guiding further investigation and advancement in this rapidly evolving sector.

关键词： Technological innovation Privacy Bibliometrics User centered design Urban planning Medical services Market research Security Sustainable development Older adults

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Internet of Things for Smart Furniture: A Systematic Review

Internet of Things for Smart Furniture: A Systematic Review

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International Conference on ICT For Smart Society (ICISS)

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

The research entitled “Internet of Things for Smart Furniture: A Systematic Review” explores integrating IoT technology into smart furniture to improve functionality and user experience. By synthesizing existing literature, this research aims to discover how the Internet of Things (IoT) is leveraged to meet specific user needs with smart furniture and what hardware and sensor technologies are proposed for smart furniture design, considering factors such as scalability and need for users. Current research trends in securing user communications and data in the context of IoT-enabled smart furniture. This research involved a literature search which included journal articles and reviews from the Web of science (WOS) and the Scopus database (core collection) from 2014 to 2023, and the final results were 9 documents that would be reviewed. Several impactful means must be used to meet specific user needs, such as health monitoring, enhanced security, enhanced convenience and mobility, integration with smart home systems, and personalization and adaptability. Drawing insights from IoT data quality, machine learning applications in IoT, and smart furniture design for elderly care, this research provides a comprehensive picture of the current IoT-enabled smart furniture landscape. This research can explore existing IoT solutions for smart furniture, with a focus on cutting-edge technologies and design principles that can shape the future of this domain.

关键词： Data privacy Protocols Shape Scalability Data integrity Smart homes Market research User experience Hardware Internet of Things

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Wireless- Powered UAV assisted Communication System in Nakagami-m Fading Channels

Wireless- Powered UAV assisted Communication System in Nakag...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Tharindu D. Ponnimbaduge Perera Dushantha Nalin K. Jayakody Sahil Garg Neeraj Kumar Ling Cheng School of Computer Science and Robotics National Research Tomsk Polytechnic University RUSSIA School of Postgraduate Studies & Research Sri Lanka Technological Campus Padukka SRI LANKA Ecole de technologie supérieure Montreal QC CANADA Thapar Institute of Engineering and Technology INDIA School of Electrical and Information Engineering University of the Witwatersrand SOUTH AFRICA

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138947

Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) cooperative communication system with a source and a destination, where UAV serves as a mobile relay. Here, the transmission power cost is debited to energy harvested using simultaneous wireless information and power transfer (SWIPT) and self-interference energy harvesting (EH) via power-splitting (PS) protocol. In poor channel conditions, UAV uses a soft angular modulation scheme to perceive the soft information. In this proposed system, we present the outage probability over the Nakagami-m fading channels. A closed-form solution for the outage probability is derived. In addition, we formulate an optimization problem to minimize end-to-end outage probability subject of the UAV's power profile. The KKT conditions have been used to obtain a closed-form solution of the proposed optimization problem. Finally, numerical results are provided to evaluate the proposed system under various setups.

关键词： autonomous aerial vehicles cooperative communication energy harvesting minimisation mobile radio Nakagami channels probability protocols radiofrequency interference relay networks (telecommunication) telecommunication network reliability telecommunication Nakagami channels cooperative communication Unmanned Aerial Vehicle telecommunication network reliability Radiofrequency interference Mobile radios energy harvesting Telecommunications drone honey bees Probability protocols COMMUNICATION SYSTEMS Trunk Node Fading channels

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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things

Intrusion Detection using Deep Neural Network Algorithm on t...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Syariful Ikhwan Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia D3 Telecommunication Engineering Institut Teknologi Telkom Purwokerto Banyumas Indonesia Computer Science Informatics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia Statistics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small.

关键词： Deep learning Training Satellites Neural networks Intrusion detection Training data Feature extraction

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H. Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A. Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J.G. Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, H Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierra Sur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen keskus (Centre for Social Data Science) Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Karolinska Institutet (Karolinska Institute) Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics University of Medical Sciences Ondo Ondo Nigeria Department of Veteri

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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Proposal of an integrated decision support system for Tuberculosis based on Semantic Web

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Procedia computer science 2019年 164卷 552-558页

作者： Vinícius Lima Felipe Pellison Filipe Bernardi Isabelle Carvalho Rui Rijo Domingos Alves Bioengineering Postgraduate Program University of Sao Paulo Sao Carlos Brazil Institute of Mathematical and Computer Sciences University of Sao Paulo Sao Carlos Brazil School of Technology and Management Polytechnic Institute of Leiria Leiria Portugal Centre for Research in Health Technologies and Information Systems (CINTESIS) University of Porto Porto Portugal Institute for Systems and Computers Engineering at Coimbra (INESCC) Coimbra Portugal Ribeirão Preto Medical School University of Sao Paulo Ribeirao Preto Brazil

Epidemiological surveillance of Tuberculosis (TB) requires a strong integration of different health services, programs and levels of care. The deepening and broadening of data management techniques must be constantly carried out to increase the integrality of healthcare. Otherwise, knowledge extraction and clinical and administrative decision-making processes are significantly hampered, directly affecting the management and quality of health services. Thus, this work aims to establish a computerized decision support system capable of collecting, integrating and sharing TB health data in Brazilian Unified Public Health System. Also, it will allow the monitoring of infected patients and the visualization of consolidated information of regular TB and its resistant variants for health professionals and managers. The data will be made available from heterogeneous, disconnected and unstructured sources by combining traditional web services, Semantic Web resources and security algorithms. A solid knowledge base applied to epidemiological surveillance, health information governance and clinical support will be enabled to integrate the multiple areas of TB patients care, as well as to support the creation of more accurate operational and diagnostics models.

关键词： Tuberculosis Decision Support System Health Information System Health Information Management Semantic Web

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Predicting complex user behavior from CDR based social networks

arXiv

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arXiv 2019年

作者： Doyle, Casey Herga, Zala Dipple, Stephen Szymanski, Boleslaw K. Korniss, Gyorgy Mladenić, Dunja Network Science and Technology Center Rensselaer Polytechnic Institute 110 8th Street TroyNY12180 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute 110 8th Street TroyNY12180 United States Artificial Intelligence Laboratory Jožef Stefan Institute Jamova 39 Ljubljana Slovenia Jožef Stefan International Postgraduate School Jamova 39 Ljubljana Slovenia Department of Computer Science Rensselaer Polytechnic Institute 110 8th Street TroyNY12180 United States Faculty of Computer Science and Management Wroclaw University of Science and Technology Wroclaw Poland

Call Detail Record (CDR) datasets provide enough information about personal interactions of cell phone service customers to enable building detailed social networks. We take one such dataset and create a realistic social network to predict which customer will default on payments for the phone services, a complex behavior combining social, economic, and legal considerations. After extracting a large feature set from this network, we find that each feature poorly correlates with the default status. Hence, we develop a sophisticated model to enable reliable predictions. Our main contribution is a methodology for building complex behavior models from very large sets of diverse features and using different methods to choose those features that perform best for the final model. This approach enables us to identify the most efficient features for our problem which, unexpectedly, are based on the number of unique users with whom the given user communicates around the Christmas and New Year’s Eve holidays. In general, features based on the number of close ties maintained by a user perform better than others. Our resulting models significantly outperform the methods Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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The utilization of search engines by students of the Library and Information science program at Universitas Padjadjaran

The utilization of search engines by students of the Library...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Kurniasih, Nuning Kurniawati, Nanik Yulianti, Y. Rahim, Robbi Sujito, S. Ikhwan, Afiful Aimang, Hasrat A. Haluti, Farid Putri, Lusi Dwi Napitupulu, Darmawan Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Jakarta Indonesia Sekolah Dasar Negeri 3 Rajapolah Tasikmalaya Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Department of English Language Education IAIN Surakarta Surakarta Indonesia Postgraduate Universitas Muhammadiyah Ponorogo Ponorogo Indonesia Universitas Muhammadiyah Luwuk Luwuk Banggai Indonesia Universitas Lancang Kuning Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia

Search engines have become an integral part of student learning activities. This study aims to see how the use of search engines by students, especially by students of the Library and Information science program, Faculty of Communication sciences, Universitas Padjadjaran. This study uses the mixed method. The research data was obtained through questionnaires, in-depth interviews, observations and literature studies. The results of the study showed that in learning activities, the respondents used search engines to find the references for college assignments and thesis writing material. The students also use search engines to meet daily information needs, solve problems, increase knowledge, reduce doubts, clarify things, entertain, fulfill curiosity about others, etc. The retrieval technique used by students is by using keywords/queries, Boolean logic, query strategies in the form of a brief search and using the advanced search feature. This research is expected to contribute to the university in supporting online-based learning facilities for students. © Published under licence by IOP Publishing Ltd.

关键词： Search engines

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Using Bipartite Graphs for 3D Cardiac Model Retrieval

Using Bipartite Graphs for 3D Cardiac Model Retrieval

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Leila C.C. Bergamasco Hellyan Oliveira Helton Bíscaro Harry Wechsler Fátima L.S. Nunes Polytechnic School - Graduate Program in Electrical Engineering University of Sao Paulo São Paulo SP Brasil Laboratory of Health Informatics Applications University of Sao Paulo São Paulo SP Brasil Department of Computer Science George Mason University Fairfax VA USA

Three-dimensional models have been used to aid medical diagnoses, using images generated by modalities like Magnetic Resonance Imaging. They can provide a more complete vision of objects since their depth is taken into account. Content-based Image Retrieval (CBIR) has also been used to aid the diagnosis. One important step in Three-dimensional CBIR (Model Retrieva) systems is the comparison between two models by using a set of features extracted and stored in a database. In this paper we present a novel method to compare two models, using the Bipartite graphs technique, with the aim to improve the retrieval precision. This technique retrieves 3D medical models of the left ventricle in order to aid the diagnosis of Congestive Heart Failure. Results showed that the novel method improved the precision by 10% when compared to the Similarity Function of Euclidean and Manhattan distance. These results confirmed that bipartite graph techniques can be used to improve the accuracy of Model Retrieval systems.

关键词： Solid modeling Three-dimensional displays Computational modeling Medical diagnostic imaging Feature extraction Bipartite graph

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Determinants and Predictors of Intentionality and Perceived Reliability in Human-AI Interaction as a Means for Innovative Scientific Discovery

Determinants and Predictors of Intentionality and Perceived ...

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IEEE International Conference on Big Data

作者： António Correia Benjamim Fonseca Hugo Paredes Ramon Chaves Daniel Schneider Shoaib Jameel INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research (NCE) Federal University of Rio de Janeiro Brazil School of Computer Science and Electronic Engineering Colchester Campus University of Essex UK

ISBN: (纸本)9781665445993

With the increasing development of human-AI teaming structures within and across geographies, the time is ripe for a continuous and objective look at the predictors, barriers, and facilitators of human-AI scientific collaboration from a multidisciplinary point of view. This paper aims at contributing to this end by exploiting a set of factors affecting attitudes towards the adoption of human-AI interaction into scientific work settings. In particular, we are interested in identifying the determinants of trust and acceptability when considering the combination of hybrid human-AI approaches for improving research practices. This includes the way as researchers assume human-centered artificial intelligence (AI) and crowdsourcing as valid mechanisms for aiding their tasks. Through the lens of a unified theory of acceptance and use of technology (UTAUT) combined with an extended technology acceptance model (TAM), we pursue insights on the perceived usefulness, potential blockers, and adoption drivers that may be representative of the intention to use hybrid intelligence systems as a way of unveiling unknown patterns from large amounts of data and thus enabling novel scientific discoveries.

关键词： Geography Crowdsourcing Technology acceptance model Big Data Predictive models Data models Reliability

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