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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Hijir Della Wirasti Henki Seta Deden Witarsyah Hamonagan K Prabu Ayu Azzahro Bayu Hananto Faculty of Engineering Industry Telkom University Bandung Indonesia Informatics Study Program Computer Science Faculty Universitas Pembangunan Nasional Veteran Jakarta

Cloud computing has emerged as a transformative technology that offers numerous benefits to various industries, including the music industry. Cloud computing has revolutionized the way businesses operate and has had a significant impact on various industries, including the music industry Cloud computing, with its scalability, flexibility, and cost-effectiveness, presents an opportunity for the music industry to leverage technology to enhance its operations and meet the evolving demands of the digital era. This paper presents a systematic literature review on cloud computing migration strategies specifically tailored for the music industry. The review aims to identify existing research, frameworks, and best practices related to cloud migration in the music industry, as well as highlight the challenges and opportunities associated with such migrations. Through an analysis of relevant literature, this study provides valuable insights to assist music industry stakeholders in developing effective cloud migration strategies.

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An ultra thin,bright,and sensitive interactive tactile display based on organic mechanoluminescence for dual-mode handwriting identification

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InfoMat 2024年第6期6卷 76-87页

作者： Tingting Hou Wenlang Li Haoyu Wang Yuantian Zheng Chaojie Chen Haoran Zhang Kai Chen Huilin Xie Xin Li Shaoshuai He Siwei Zhang Dengfeng Peng Cheng Yang Jacky W.Y.Lam Ben Zhong Tang Yunlong Zi Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong Kongthe People's Republic of China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and TechnologyHong Kongthe People's Republic of China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhenthe People's Republic of China Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)Guangzhouthe People's Republic of China The Hong Kong University of Science and Technology Interdisciplinary Program Office Hong Kong SARthe People's Republic of China Institute of Materials Research Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenthe People's Republic of China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenthe People's Republic of China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhenthe People's Republic of China Guangzhou HKUST Fok Ying Tung Research Institute Guangzhouthe People's Republic of China

Visible light-based human–machine interactive media is capable of transmitting electrical readouts to machines and providing intuitive feedback to users ***,many inorganic mechanoluminescent(ML)materials-based interactive media,typically ZnS-loaded phosphors(ZLPs),have been successfully ***,organic ML materials-based solutions were rarely exploited despite their huge merits of strong structural modification,abundant luminescence property,low cost,easy preparation,and so ***,we propose a novel interactive tactile display(ITD)based on organic ML materials(Cz-A6-dye)and triboelectric nanogenerator,with ultra-brightness(130%enhancement)and ultra-low threshold pressure(57%reduction)as compared to *** proposed ITD achieves the conversion of weak mechanical stimuli into visible light and electrical signals simultaneously,without extra power ***,the relationship between the luminous performance of organic ML materials and mechanical force is quantified,benefiting from the uniform ML layer *** by convolutional neural networks,the high-accuracy recognition(97.1%)for handwriting and identity of users is realized at the same ***,the ITD has great potential for intelligent wearable electronics and classified military applications.

关键词： interactive media organic mechanoluminescence triboelectric nanogenerators

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Enhanced Dye Adsorption and Bacterial Removal of Magnetic Nanoparticle-Functionalized Bacterial Cellulose Acetate Membranes

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Journal of Renewable Materials 2024年第9期12卷 1605-1624页

作者： Heru Suryanto Daimon Syukri Fredy Kurniawan Uun Yanuhar Joseph Selvi Binoj Sahrul Efendi Fajar Nusantara Jibril Maulana Nico Rahman Caesar Komarudin Komarudin Centre of Advanced Material for Renewable Energy(CAMRY) Universitas Negeri MalangMalang65145Indonesia Department of Mechanical and Industrial Engineering Universitas Negeri MalangMalang65145Indonesia Department of Food and Agricultural Product Technology Faculty of Agricultural TechnologyAndalas UniversityPadang25163Indonesia Department of Chemistry Institut Teknologi Sepuluh NopemberSurabaya60111Indonesia Study Program of Aquatic Resources Management Faculty of Fisheries and Marine ScienceBrawijaya UniversityMalang65145Indonesia Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennai602105India Faculty of Vocational Universitas Negeri MalangMalang65145Indonesia

Utilizing biomass waste as a potential resource for cellulose production holds promise in mitigating environmental *** current study aims to utilize pineapple biowaste extract in producing bacterial cellulose acetate-based membranes with magnetic nanoparticles(Fe_(3)O_(4)nanoparticles)through the fermentation and esterification process and explore its *** bacterial cellulose fibrillation used a high-pressure homogenization procedure,and membranes were developed incorporating 0.25,0.50,0.75,and 1.0 wt.%of Fe3O4 nanoparticles as magnetic nanoparticle for *** membrane characteristics were measured in terms of Scanning Electron Microscope,X-ray diffraction,Fourier Transform Infrared,Vibrating Sample Magnetometer,antibacterial activity,bacterial adhesion and dye adsorption *** results indicated that the surface morphology of membrane changes where the bacterial cellulose acetate surface looks *** crystallinity index of membrane increased from 54.34%to 68.33%,and the functional groups analysis revealed that multiple peak shifts indicated alterations in membrane functional ***,adding Fe_(3)O_(4)-NPs into membrane exhibits paramagnetic behavior,increases tensile strength to 73%,enhances activity against *** and ***,and is successful in removing bacteria from wastewater of the river to 67.4%and increases adsorption for anionic dyes like Congo Red and Acid Orange.

关键词： Bacterial cellulose dye adsorption Fe_(3)O_(4)nanoparticles membrane pineapple waste

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White Bread Mold Detection using K-Means Clustering Based on Grey Level Co-Occurrence Matrix and Region of Interest

White Bread Mold Detection using K-Means Clustering Based on...

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International Seminar on Application for Technology of Information and Communication (ISemantic)

作者： Qori Alfatah Putra Christy Atika Sari Eko Hari Rachmawanto Nur Ryan Dwi Cahyo Edy Mulyanto Mohamed Ayad Alkhafaji Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Informatics Engineering University of Dian Nuswantoro Semarang Indonesia Department of Computer Science National University of Science and Technology DhiQar Iraq

This research paper presents a bread mold identification system that utilizes digital image processing techniques, specifically K-means clustering and thresholding, to accurately detect and classify mold-infected areas on bread. The system aims to provide valuable information regarding the safety of consuming mold-contaminated bread, enabling consumers to make informed decisions and reduce the risk of health issues associated with consuming mold-infested bread. the K-means clustering algorithm for mold classification, considering factors such as the number of iterations and the distance metric within the feature space to determine its accuracy. The GLCM feature extraction technique is employed to extract texture information from bread images, encompassing features such as standard deviation (110.62), contrast (1.46), energy, and homogeneity (0.96 and 0.77, respectively). Experimental results demonstrate that the Euclidean Distance yielded the highest result of 72.73, the Cosine Distance obtained the highest result of 8.25, and the City Block Distance obtained the highest result of 92.11. These findings showcase the effectiveness of the system in accurately detecting and classifying mold-infected areas on bread, thereby aiding in ensuring food safety and reducing health risks for consumers.

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Diabetes Prediction Model for Better Clarification by using Machine Learning 6

Diabetes Prediction Model for Better Clarification by using ...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Eben, J. Lysa Jayasudha, R. Ramya, S. Kaliappan, S. Aswal, Shobha Al-Salehi, Khalid Ali Salem Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Tamilnadu Chennai India Department of Mathematics Dr.N.G.P.Institute of Technology Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Tamilnadu Erode India Division of Research and Development Lovely Professional University Punjab Phagwara144411 India School of Computing Graphic Era Hill University Dehradun India Biomedical Engineering Study Program Faculty of Science and Technology Airlangga University Surabaya Indonesia

ISBN: (纸本)9798350398496

Diabetes mellitus is one of the most pressing health concerns because so many people are afflicted by its disabling symptoms. Factors such as age, excess body fat, insufficient physical activity, a history of diabetes in one's family, a sedentary lifestyle, an unhealthy diet, hypertension, etc., all increase the likelihood of developing diabetes mellitus. Health complications are more common in people with diabetes, including cardiovascular disease, renal failure, stroke, blindness, and nerve injury. To validate a diagnosis of diabetes, hospitals typically perform a battery of procedures on the patient. Big data analytics has many vital applications in the healthcare sector. Numerous large computer systems are used in the healthcare sector. With the help of big data analytics, researchers can sift through mountains of data in search of previously unseen patterns and insights. Current techniques have a poor degree of precision in classification and forecast. While previous research has focused on factors such as glucose, body mass index, age, insulin, etc., the proposed model takes these into account and also the other factors that may be more relevant to the development of diabetes. The newer sample is superior to the older one based on categorization accuracy. A workflow algorithm for diabetes prognosis is also required to improve the accuracy. © 2023 IEEE.

关键词： Forecasting

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Mapping the Literature of Artificial Intelligence in Medical Education: A Scientometric Analysis 7th

Mapping the Literature of Artificial Intelligence in Medical...

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7th International Conference on Inventive Communication and Computaional Technologies, ICICCT 2023

作者： Maulana, Fairuz Iqbal Zaın, Muhammad Yasır Lestari, Dian Purnomo, Agung Adi, Puput Dani Prasetyo Computer Science Department Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Jakarta11480 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia

ISBN: (纸本)9789819951659

This study aims to investigate the use of artificial intelligence in health education in the last ten years from 2012 to 2022 using the Scopus database. Researchers use bibliometric analysis combined with the quantification method of Vosviewer and Rstudio software used for literature analysis. The results of the article that were flushed showed data such as the year of publication, journal, country, keywords, and authors, to the highest number of citations. The general keywords used by researchers are artificial intelligence, medical, and education. Researchers limit findings through keywords as in the last ten years and English only so that 1681 articles were obtained. According to the study's findings, McGill University affiliation had the greatest number of papers, with 69 pieces, and medicine had a proportion of 39.7% (n = 1067). This bibliometric study will be useful for other researchers to examine the development of research on artificial intelligence in health education in the last ten years. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Medical education

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Digital Technology in Health Education Trend Mapping through Bibliometrics Analysis 4

Digital Technology in Health Education Trend Mapping through...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Maulana, Fairuz Iqbal Lestari, Dian Widartha, Vandha Pradwiyasma Haidar, Nirwana Dirgantara, Wahyu School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Airlangga University Faculty of Medicine Surabaya60132 Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia University of Madura Informatics Engineering Study Program Pamekasan Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia

ISBN: (纸本)9781665473279

This study examines the mapping of research data on digital technology in the field of health education using bibliometric analysis method. Data was collected by identifying keywords in the Scopus database and sorting them out to sort the studies from the last 10 years (2012-2021). Through this step, a total of 1482 documents were obtained (articles, journals, proceedings, books, and others). The data is then processed using the VOSViewer instrument to obtain a visualization of the mapping analysis. This study also analyzes the network types of authors and co-authors through the VOSViewer instrument. The result of this study indicates that the most document types published within ten years are Articles (66.5%), Review (22.9%), Conference Paper (4.2%), and others. The most studied subjects are Medicine (55.7%), Nursing (9.0%), Health Professions (8.2%), Social sciences (7.8%), engineering (3.9%), Computer science (2.6%), Environmental science (2.6%), Biochemistry-Genetics and Molecular Biology (2.2%), Psychology (1.6%), and Dentistry (1.3%). This study offers a written communication process and the nature and direction of developing descriptive means of counting and analyzing the various phases of communication as well as recognizing the authorship and direction of its symptoms in documents on the subject of digital technology in the health sector. © 2022 IEEE.

关键词： Mapping

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Testing the Inference Accuracy of Accelerator-Friendly Approximate Phylogeny Tracking

Testing the Inference Accuracy of Accelerator-Friendly Appro...

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2025 IEEE Symposium on Computational Intelligence in Artificial Life and Cooperative Intelligent Systems, ALIFE-CIS 2025

作者： Moreno, Matthew Andres Ranjan, Anika Dolson, Emily Zaman, Luis University of Michigan Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data and Ai in Society University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Michigan State University Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

ISBN: (纸本)9798331508371

Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Such phylogenies can provide insight into evolutionary dynamics within these simulations. Previous work generally tracks lineages directly, yielding an exact phylogenetic record of evolutionary history. However, challenges exist in scaling direct ancestrytracking approaches to highly-distributed, many-processor evolution in silico. An alternative approach is to estimate phylogenetic history via noncoding annotations on digital genomes, akin to how bioinformaticians build phylogenies by assessing genetic similarities between organisms. Recent work has extended this 'hereditary stratigraphy' approach to support powerful hardware accelerator platforms, such as the Cerebras Wafer-Scale Engine. Although these second-generation 'surface'-based hereditary stratigraphy algorithms have demonstrated order-ofmagnitude speedups over first-generation 'column'-based algorithms, it remains unknown how they impact the accuracy of reconstructed phylogenies. To address this question, we assessed reconstruction accuracy under alternative configurations across a matrix of evolutionary conditions varying in selection pressure, spatial structure, and ecological dynamics. Encouragingly, we find that the second-generation approaches provide higher reconstruction quality across most surveyed conditions. © 2025 IEEE.

关键词： Biostratigraphy

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Development of High Temperature Lead-free Solders in the Al-95Zn + xSn Systems

Development of High Temperature Lead-free Solders in the Al-...

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International Conference on Electronics Packaging (ICEP)

作者： Andromeda Dwi Laksono Yee-Wen Yen Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan R.O.C Study Program of Materials and Metallurgical Engineering Institut Teknologi Kalimantan Balikpapan East Kalimantan Indonesia

The high-temperature lead-free solder alloys of Al-95Zn with the modification of the addition of Sn have been investigated. Its proportion is used to adjust the metallographic microstructure, solidified precipitate phase, and liquidus temperature of the solder alloy. The characterization results, such as scanning electron microscope (SEM), energy dispersive spectrometer (EDS), X-ray diffraction (XRD), and differential scanning calorimeter (DSC), will be discussed in this study. The study results show that the Al-Sn-Zn-based alloy has (Zn)+β- Sn+(Al) precipitates when heat-treated at 900°C for 36 h. Its liquidus temperature of Al-95Zn + xSn is between 342-385°C, and increased Sn content will decrease its liquidus temperature.

关键词： Heating systems Scanning electron microscopy X-ray scattering Lead X-ray diffraction Microstructure Dispersion

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Vibration problem due to railway loading 1

Vibration problem due to railway loading

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1st Universitas Lampung International Conference on science, Technology and Environment, ULICOSTE 2020

作者： Alami, F. Afriani, L. Faculty of Engineering University of Lampung Bandar Lampung Indonesia Postgraduated Student of Study Program of Environmental Science University of Lampung Bandar Lampung Indonesia

Train is one of transportation mode is increasingly polular in Indonesia nowdays, although in developed countries this transportation has long been a very advanced mode of mass transportation. Problems due to railroad tracks adjacent to densely populated settlements cannot be avoided. Problems such as noise levels can interfere with the health and comfort of the environment, vibrations in the surrounding environment due to passing trains cause some damage to civilian buildings such as residents' houses and high rise buildings as well. This field study shows the potential problem due to mass train loading (Babaranjang) in Bandar Lampung. © Published under licence by IOP Publishing Ltd.

关键词： Mass transportation

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