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25th International Conference on Enterprise Information Systems, ICEIS 2023

作者： de Souza, Pedro Lopes de Souza, Wanderley Lopes Pires, Luís Ferreira Moreira, João Luiz Rebelo da Silva Rodrigues, Ronitti Juner Ciferri, Ricardo Rodrigues Semantics Cybersecurity & Services Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente P.O. Box 217 Enschede Netherlands Ubiquitous Computing Group Graduate Program in Computer Science Computing Department Federal University of São Carlos P.O. Box 676 São Carlos Brazil

ISBN: (纸本)9789897586484

Hypertension is a noncommunicable disease (NCD) that causes global concern, high costs and a high number of deaths. Internet of Things, Ubiquitous computing, and Cloud computing enable the development of systems for remote and real-time monitoring of patients affected with NCDs like hypertension. This paper reports on a system for monitoring hypertension patients that was built by employing these techniques. This system allows the vital signs of a patient (blood pressure, heart rate, body temperature) to be captured via sensors built in a wearable device similar to a wristwatch. These signals are transmitted to the patient's mobile device for processing, and the generated clinical data are sent to the cloud to be properly presented and analysed by the health professionals responsible for the patient. To deal with semantic interoperability issues that arise when multiple different devices and system components must interoperate, a semantic model was conceived for this system in terms of ontologies for diseases and devices. This paper also presents the semantic module that we developed and implemented in the cloud to perform reasoning based on this model, demonstrating the potential benefits of incorporating semantic technologies in our system. Copyright © 2023 by SCITEPRESS - science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Ontology

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Prediction of Bankruptcy among Middle 40 per Cent (M40) in Malaysia using Support Vector Machine 22

Prediction of Bankruptcy among Middle 40 per Cent (M40) in M...

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22nd IEEE Student Conference on Research and Development, SCOReD 2024

作者： Sabri, Nurbaity Sahiq, Aqilah Nadiah Md Hamzah, Hazwa Hanim Mohamed Sain, Hartayuni Mangshor, Nur Nabilah Abu Shari, Anis Amilah Universiti Teknologi MARA Cawangan Melaka College of Computing Informatics and Mathematics Kampus Jasin Melaka Malaysia Universiti Teknologi MARA Cawangan Melaka Faculty of Business and Management Kampus Bandaraya Melaka Malaysia Tadulako University Statistics Study Program Mathematics and Natural Science Faculty Palu94118 Indonesia

ISBN: (纸本)9798331510077

The Middle 40 Per Cent (M40) demographic comprises a substantial proportion of Malaysia's consumer base, comprising the median 40% of income earners. This group is a big part of the country's customer base. The rising cost of living, flat wage growth, and rising family debt make this group especially vulnerable to financial instability. Given these economic pressures, predicting the possibility of bankruptcy in this population is becoming increasingly crucial to allow for early intervention and preventive actions. Support Vector Machines (SVM) are recognized for their efficacy in classification tasks, particularly with small or imbalanced datasets. SVM prediction will be utilized using 14694 samples of the Debt Management program (DMP) dataset from 2016 to 2020. Twenty-three (23) features will be implemented on the dataset and Synthetic Minority Oversampling Technique (SMOTE) to improve the imbalanced datasets. The experiment demonstrates that the SVM classifier obtained 91.1% accuracy when implementing PUK kernels. It suggests that SVM is a plausible alternative model for predicting personal bankruptcy in the M40 group. To anticipate personal bankruptcy for M40, additional prediction models will be evaluated in the future. © 2024 IEEE.

关键词： Prediction models

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Adaptive optimal multi key based encryption for digital image security

Adaptive optimal multi key based encryption for digital imag...

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作者： Shankar, K. Lakshmanaprabu, S.K. Gupta, Deepak Khanna, Ashish de Albuquerque, Victor Hugo C. School of Computing Kalasalingam Academy of Research and Education Krishnankoil India B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai India Maharaja Agrasen Institute of Technology Delhi India Graduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil

The security of digital images is an essential and challenging task on shared communication Model. Generally, high secure working environment and data are also secured with an encryption and decryption method by using secret and public keys. In this paper, the innovative encryption technique for image security, ie, Multiple key-based Homomorphic Encryption (MHE) technique is proposed. For increasing the security level of encryption and decryption processes, the optimal key is selected using Adaptive Whale Optimization (AWO) algorithm. Fitness function was considered for optimization as PSNR of plain and cipher images. The original image was transformed into blocks and then rearranged utilizing encryption process, this work achieved maximum security, much better than other encryption techniques. From the outcomes, one can achieve incredible quality of the proposed model, the maximum PSNR, and the minimum MSE contrasted with other encryption schemes. © 2018 John Wiley & Sons, Ltd.

关键词： Cryptography

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Crop root bacterial and viral genomes reveal unexplored species and microbiome patterns

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Cell 2025年第9期188卷 2521-2539.e22页

作者： Dai, Rui Zhang, Jingying Liu, Fang Xu, Haoran Qian, Jing-Mei Cheskis, Shani Liu, Weidong Wang, Binglei Zhu, Honghui Pronk, Lotte J.U. Medema, Marnix H. de Jonge, Ronnie Pieterse, Corné M.J. Levy, Asaf Schlaeppi, Klaus Bai, Yang Institute of Genetics and Developmental Biology Chinese Academy of Sciences Beijing 100101 China Peking-Tsinghua Center for Life Sciences State Key Laboratory of Gene Function and Modulation Research Peking-Tsinghua-NIBS Graduate Program School of Life Sciences Peking University Beijing 100871 China CAS-JIC Centre of Excellence for Plant and Microbial Science Institute of Genetics and Developmental Biology Chinese Academy of Sciences Beijing 100101 China College of Advanced Agricultural Sciences University of Chinese Academy of Sciences Beijing 100101 China Department of Plant Pathology and Microbiology Institute of Environmental Science The Faculty of Agriculture Food and Environment The Hebrew University of Jerusalem Rehovot Israel State Key Laboratory of Applied Microbiology Southern China Institute of Microbiology Guangdong Academy of Sciences Guangzhou 510070 China Bioinformatics Group Wageningen University & Research Wageningen 6708 PB Netherlands Plant-Microbe Interactions Department of Biology Science for Life Utrecht University Utrecht 3584 CH Netherlands AI Technology for Life Department of Information and Computing Sciences Science for Life Utrecht University Utrecht 3584 CC Netherlands Department of Environmental Sciences University of Basel Basel 4056 Switzerland

Reference genomes of root microbes are essential for metagenomic analyses and mechanistic studies of crop root microbiomes. By combining high-throughput bacterial cultivation with metagenomic sequencing, we constructed comprehensive bacterial and viral genome collections from the roots of wheat, rice, maize, and Medicago. The crop root bacterial genome collection (CRBC) significantly expands the quantity and phylogenetic diversity of publicly available crop root bacterial genomes, with 6,699 bacterial genomes (68.9% from isolates) and 1,817 undefined species, expanding crop root bacterial diversity by 290.6%. The crop root viral genome collection (CRVC) contains 9,736 non-redundant viral genomes, with 1,572 previously unreported genus-level clusters in crop root microbiomes. From these, we identified conserved bacterial functions enriched in root microbiomes across soils and host species and uncovered previously unexplored bacteria-virus connections in crop root ecosystems. Together, the CRBC and CRVC serve as valuable resources for investigating microbial mechanisms and applications, supporting sustainable agriculture. © 2025 The Authors

关键词： bacteria crop genome genomic resources root microbiome virus

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Implementation of Augmented Reality in Pretend Play Therapy for Children with Autism Spectrum Disorder 3

Implementation of Augmented Reality in Pretend Play Therapy ...

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3rd International Conference on computing and Applied informatics 2018, ICCAI 2018

作者： Syahputra, M.F. Angkasih, A.P. Purnamawati, S. Andayani, U. Abdullah, D. Sriadhi, S. Iskandar, A. Rosida, T.M. Fitriany, J. Sari, I.N. Utama, M.D. Nanuru, R.F. Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Pediatric Universitas Malikussaleh Aceh Utara Indonesia Departement of Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Social and Political Science Universitas Kristen Indonesia Maluku Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia

Autism Spectrum Disorder is a pervasive developmental disorder that will affect children in terms of interpersonal communication, social interaction, and imaginative levels in play. Many therapies to help the motor neuron performance is one of them Pretend Play. Pretend Play is a therapy that invites children in playing to demonstrate something else and tell how to use objects that are considered in the child's imagination. However, in the era of highly developed technology, many fields have used the Augmented Reality method as a visualization of various aspects. With this method researchers will present the therapeutic visualization of the block to 3D transportation tool that is useful for strengthening motor nerves and visual strength of the child. The system can run well during marker detection, marker movement, and 3D object display with the accuracy of precision angle and distance between virtual world with real world reach 100% with angle 0 at distance 31 cm and the maximum distance from the marker is 46 cm and the maximum angle is 30. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Augmented reality

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Local Periodicity-Based Beat Tracking for Expressive Classical Piano Music

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IEEE/ACM Transactions on Audio Speech and Language Processing 2023年 31卷 2824-2835页

作者： Chiu, Ching-Yu Muller, Meinard Davies, Matthew E. P. Su, Alvin Wen-Yu Yang, Yi-Hsuan National Cheng Kung University Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan701401 Taiwan International Audio Laboratories Erlangen Erlangen91058 Germany University of Coimbra Department of Informatics Engineering Centre for Informatics and Systems Coimbra3004-531 Portugal National Cheng Kung University Department of Computer Science and Information Engineering Tainan701401 Taiwan Taiwan AI Labs Yating Music Team Taipei103622 Taiwan Academia Sinica Research Center for IT Innovation Taipei11529 Taiwan

To model the periodicity of beats, state-of-the-art beat tracking systems use 'post-processing trackers' (PPTs) that rely on several empirically determined global assumptions for tempo transition, which work well for music with a steady tempo. For expressive classical music, however, these assumptions can be too rigid. With two large datasets of Western classical piano music, namely the Aligned Scores and Performances (ASAP) dataset and a dataset of Chopin's Mazurkas (Maz-5), we report on experiments showing the failure of existing PPTs to cope with local tempo changes, thus calling for new methods. In this paper, we propose a new local periodicity-based PPT, called predominant local pulse-based dynamic programming (PLPDP) tracking, that allows for more flexible tempo transitions. Specifically, the new PPT incorporates a method called 'predominant local pulses' (PLP) in combination with a dynamic programming (DP) component to jointly consider the locally detected periodicity and beat activation strength at each time instant. Accordingly, PLPDP accounts for the local periodicity, rather than relying on a global tempo assumption. Compared to existing PPTs, PLPDP particularly enhances the recall values at the cost of a lower precision, resulting in an overall improvement of F1-score for beat tracking in ASAP (from 0.473 to 0.493) and Maz-5 (from 0.595 to 0.838). © 2014 IEEE.

关键词： Hidden Markov models

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems 6

Implementation of Face Patterns and Smile Recognition for In...

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6th International Conference on Computer and informatics Engineering, IC2IE 2023

作者： Miftakhurrokhmat Suparyanto, Teddy Elwirehardja, Gregorius Natanael Karimah, Shofiyati Nur Pardamean, Bens Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Department of Informatics Yogyakarta Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350345162

Students 'attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students' attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification. © 2023 IEEE.

关键词： class attendance convolutional neural network deep learning face recognition smile

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Analysis of Shopping Mall Tourist Satisfaction in Bangkok Using Word Cloud of Online Reviews

Analysis of Shopping Mall Tourist Satisfaction in Bangkok Us...

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2023 International Conference on Cyber Management and Engineering, CyMaEn 2023

作者： Ladkoom, Kobthong Tarigan, Emiya Fefayosa Br Yasirandi, Rahmat Suwastika, Novian Anggis Anom, Rahmat Indra Pratama Makky, Muhammad Al Chandrakasem Rajabhat University Faculty of Science Bangkok Thailand Telkom University School of Computing Bandung Indonesia King Mongkut's Institute of Technology Ladkrabang Faculty of Information Technology Bangkok Thailand Universiti Teknologi Malaysia Razak Faculty of Technology and Informatics Kuala Lumpur Malaysia Doctoral Program of Tourism Trisakti School of Tourism Jakarta Indonesia

ISBN: (纸本)9781665493291

The tourism industry is very important to prioritize, especially for developing countries like Thailand. The increase in tourist visits to Bangkok also triggers the potential for a rise in Bangkok tourism during the pandemic. In this study, shopping malls are one of the attractive attractions for a capital city like Bangkok. Tourist expectations of attraction must be realized so that satisfaction can be realized and created revisit. In the digitalization era, the internet's use to find and disseminate information has become commonplace. *** is one of the leading review sites, which already has many reviewers, and is the case study in this research. Using Word Cloud as an analysis technique and clustering of data reviews, several important factors influence tourist satisfaction. Based on the 1186 clustered reviewers, several factors were produced, such as Place Quality, Location Access, Support Facilities, Price, and Seller Attitude. These factors can influence the decision to visit shopping malls in Bangkok because they represent tourist satisfaction. © 2023 IEEE.

关键词： Shopping centers

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach 7

Minimizing the Number of Stunting Prevalence Using the Eucli...

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7th IEEE International Conference of Computer science and Information Technology, ICOSNIKOM 2023

作者： Zarlis, Muhammad Oktavia, Tanty Buaton, Relita Ernawan, Ferda Andrian, Kevin Bina Nusantara University Information System Management Department BINUS Graduate Program - Master of Information System Management Jakarta11480 Indonesia STMIK Kaputama Informatics Engineering Binjai20714 Indonesia Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan26600 Malaysia BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350360752

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city. © 2023 IEEE.

关键词： Classification (of information)

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review 10

Critical Factors of Immersive Learning in Higher Education: ...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Sunardi Meyliana Ramadhan, Arief Rosmansyah, Yusep Bina Nusantara University BINUS Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia School of Information System Bina Nusantara University Information System Departement Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798350339543

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education. © 2023 IEEE.

关键词： E-learning

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