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Modeling the Percentage of NEET in Indonesia with Spatial Cauchy Regression through the Bayesian Analysis Approach

IAENG International Journal of Applied Mathematics 2024年第7期54卷 1288-1295页

作者： Rantini, Dwi Fakhruzzaman, Muhammad Noor Ningrum, Ratih Ardiati Othman, Fazidah Choir, Achmad Syahrul Ramadan, Arip Alya, Najma Attaqiya Putri, Elfira Rahma Pratama, Muhammad Alfian Engineering Department Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Indonesia Engineering Department Data Science Technology Study Program Faculty of Advanced Technology andMultidiscipline Universitas Airlangga Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia Statistical Computing StudyProgram Politeknik Statistika STIS Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Indonesia

Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors that could contribute to the decline in the NEET percentage are literacy rates and the number of adolescents with computer skills. Increasing these two factors is believed to be able to reduce the percentage of NEET in every province in Indonesia. To find out the relationship between these two factors and how much influence they have on the percentage of NEET, this research is modeled by Cauchy regression and includes spatial effects. The results of the analysis show that the best model is when the spatial effect is modeled by Fernandez Steel Skew Normal conditionally autoregressive (FSSN CAR). This result is seen from the smallest value of the Watanabe Akaike Information Criterion (WAIC) in this model, which is 190.5. The parameter estimated shows that the higher the literacy rate and the number of adolescents with computer skills, the lower the percentage of NEET in each province in Indonesia. The results of this research can be useful for the Indonesian government to increase the number of educational facilities related to these two factors. © (2024), (International Association of Engineers). All rights reserved.

关键词： Bayesian CAR Cauchy Education NEET

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Unassisted photoelectrochemical CO_(2)reduction by employingⅢ-Ⅴphotoelectrode with 15%solar-to-fuel efficiency

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Carbon Energy 2025年第3期7卷 1-10页

作者： Karthik Peramaiah Purushothaman Varadhan Vinoth Ramalingam Bilawal Khan Pradip Kumar Das Hao Huang Hui-Chun Fu Xiulin Yang Vincent Tung Kuo-Wei Huang Jr-Hau He Chemistry Program Center for Renewable Energy and Storage Technologies(CREST)and Division of Physical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia Institute of Sustainability for Chemicals Energyand Environment(ISCE2)Agency for ScienceTechnologyand Research(A*STAR)Singapore School of Computing Engineering and TechnologyRobert Gordon UniversityAberdeenUK Department of Materials Science and Engineering City University of Hong KongKowloonSARHong KongChina Guangxi Key Laboratory of Low Carbon Energy Materials School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilinChina Department of Chemical System and Engineering University of TokyoTokyoJapan

Solar-driven carbon dioxide reduction reaction(CO_(2)RR)provides an oppor tunity to produce value-added chemical feedstocks and ***,achieving efficient and stable photoelectrochemical(PEC)CO_(2)RR into selec tive products is challenging owing to the difficulties associated with the optical and the electrical configuration of PEC devices and electrocatalyst ***,we construct an efficient,concentrated sunlight-driven CO_(2)RR setup consisting of InGaP/GaAs/Ge triple-junction cell as a photoanode and oxide-derived Au(Ox-Au)as a cathode to perform the unassisted PEC CO_(2)*** one-sun illumination,a maximum operating current density of 11.5 mA cm^(-2) with an impressive Faradaic efficiency(FE)of~98%is achieved for carbon monoxide(CO)production,leading to a solar-to-fuel conversion efficiency of~15%.Under concentrated intensity of 10 sun,the photoanode records a maximum current density of~124 mAcm^(-2) and maintains~60%of FE for CO *** results demonstrate crucial advancements in usingⅢ-Ⅴbased photoanodes for concentrated PEC CO_(2)RR.

关键词： 3J photoanode CO_(2)reduction high STF unassisted PEC

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Scaffolding Process-Aware Information systems with the AKIP Platform 1

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18th International Conference on Web Information systems and Technologies, WEBIST 2022

作者： Telemaco Neto, Ulisses Oliveira, Toacy Pillat, Raquel Alencar, Paulo Cowan, Don Melo, Glaucia David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada System Engineering and Computing Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9783031430886

ISBN: (纸本)9783031430879

Business Process Automation (BPA) refers to the automation of business processes through technology, with the goal of improving efficiency, reducing errors, and increasing productivity by eliminating manual and repetitive tasks. Over the past few years, the number of BPA platforms has increased, including both open-source and proprietary solutions. However, some challenges and limitations still exist related to the adoption of these solutions, such as vendor lock-in, limited UI/UX, limited integration, outdated technology stack, and lack of support for non-process features. To address these issues, this paper presents the AKIP platform, an open-source framework for developing process-aware information systems (PAISs) using code generation techniques. AKIP generates functional process-aware web applications from BPMN business process models, making it the only known software tool capable of generating fully functional process-aware web applications. To evaluate the effectiveness of the AKIP platform, a case study was conducted in the industry and six business processes automated into a process-oriented web application were analyzed in this paper. The study showed that the AKIP platform was able to generate a functional web application while supporting the automation of business processes with different model sizes and complexities. Furthermore, this study showed that even a team of professionals with little experience was able to produce such results by using the AKIP platform. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automation

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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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AKIP Process Automation Platform: A Framework for the Development of Process-Aware Web Applications 18

AKIP Process Automation Platform: A Framework for the Develo...

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18th International Conference on Web Information systems and Technologies, WEBIST 2022

作者： Neto, Ulisses Telemaco Oliveira, Toacy Pillat, Raquel Alencar, Paulo Cowan, Don Melo, Glaucia David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada System Engineering and Computing Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9789897586132

An increasing number of platforms for Business Process Automation (BPA) have been developed in recent years, including open-source and proprietary solutions. However, there are still some unsolved problems and limitations related to the adoption of these solutions, which include: vendor lock-in, limited UI/UX, limited integration, outdated technology stack, and lack of support for non-process features. The framework presented in this paper addresses these problems and limitations by providing an open-source platform to facilitate the development of process-aware information systems (PAISs) based on code generation techniques. The platform is capable of generating a functional process-aware Web application from a business process model defined in BPMN. To the best of our knowledge, there is no other software tool that generates fully functional process-aware Web applications. The presented framework has been evaluated in the academy and industry and used to develop dozens of non-profit and commercial process-aware applications. Copyright © 2022 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Open systems

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Wearable Technology Application for Banjar Language Translator to Support Ease of Communication: Prototyping and Sustainability Opportunities

Wearable Technology Application for Banjar Language Translat...

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2022 International Conference on Data and Software engineering, ICoDSE 2022

作者： Syahidi, Aulia Akhrian Arai, Kohei Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Graduate School of Science and Engineering Saga University Computing Division Honjo-machi Saga Japan

ISBN: (数字)9798350397055

ISBN: (纸本)9798350397055

Language differences are one of the obstacles to communication. Especially if you use certain regional languages such as Banjar Language. Banjar Language is the mother tongue used by the Banjar tribe in South Kalimantan Province, Indonesia. South Kalimantan is known as an area that has promising tourism potential and is the main gateway of the new nation's capital city. This causes many tourists to visit (overtourism). Tourists will face obstacles when communicating with local residents of Banjar. The purpose of this research is to produce a prototype of a tool in the form of a wearable technology-based translator application, using speech recognition with Python programming, then investigate the usability and sustainability opportunities of the prototype that has been made. A total of 200 respondents have been involved consisting of domestic tourists and local residents of Banjar, these respondents were involved in exploring needs and when evaluating usability. The results show that the prototype that has been made provides usability and is feasible to proceed to the implementation stage, as a means to help tourists from the archipelago and local residents of Banjar to communicate and also transact. © 2022 IEEE.

关键词： Sustainable development

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Model for Anomaly Detection in Reducing Water Losses in the Distribution Network of Peru using Machine Learning Algorithms

Model for Anomaly Detection in Reducing Water Losses in the ...

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Software engineering and Computer science (CSECS), International Conference on

作者： Mayra Rivera Pricila Lucero José Luis Castillo-Sequera Lenis Wong Information Systems Engineering Program Universidad Peruana de Ciencias Aplicadas Lima Peru Department of Computer Science Group: Health Computing and Intelligent System Universidad de Alcalá Alcalá de Henares Spain

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Water leakage in distribution networks is a significant challenge, especially in regions with limited infrastructure like Huancayo, Peru, where losses account for 32.82% of the distributed volume. This study introduces a machine learning-based approach to detect leaks using four algorithms: Autoencoder LSTM, Isolation Forest, One-Class SVM, and K-Nearest Neighbors (KNN). The methodology involved preprocessing historical consumption data (2018–2024) into 12-month temporal sequences per client and evaluating the models based on F1 Score, Precision, and Mean Absolute Error (MAE). Among the algorithms, the Autoencoder LSTM demonstrated superior performance with the highest precision (0.89) and the lowest MAE (0.00402). Its robustness in high-variability contexts enables early and reliable leak detection, providing a cost-effective solution for optimizing water management in resource-constrained environments.

关键词： Support vector machines Machine learning algorithms Autoencoders Distribution networks Forestry Nearest neighbor methods Robustness Leak detection Long short term memory Water resources

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Model for Anomaly Detection in Reducing Water Losses in the Distribution Network of Peru using Machine Learning Algorithms 7

Model for Anomaly Detection in Reducing Water Losses in the ...

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7th International Conference on Software engineering and Computer science, CSECS 2025

作者： Rivera, Mayra Lucero, Pricila Castillo-Sequera, Jose Luis Wong, Lenis Universidad Peruana de Ciencias Aplicadas Information Systems Engineering Program Lima Peru Universidad de Alcalá Group: Health Computing and Intelligent System Department of Computer Science Alcalá de Henares Spain

ISBN: (纸本)9798331522216

Water leakage in distribution networks is a significant challenge, especially in regions with limited infrastructure like Huancayo, Peru, where losses account for 32.82% of the distributed volume. This study introduces a machine learning-based approach to detect leaks using four algorithms: Autoencoder LSTM, Isolation Forest, One-Class SVM, and K-Nearest Neighbors (KNN). The methodology involved preprocessing historical consumption data (2018-2024) into 12-month temporal sequences per client and evaluating the models based on F1 Score, Precision, and Mean Absolute Error (MAE). Among the algorithms, the Autoencoder LSTM demonstrated superior performance with the highest precision (0.89) and the lowest MAE (0.00402). Its robustness in high-variability contexts enables early and reliable leak detection, providing a cost-effective solution for optimizing water management in resource-constrained environments. © 2025 IEEE.

关键词： k-nearest neighbors

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Preprocessing Techniques for Enhancing Vision-Based Detection system for Tire Sidewall Extraction 7

Preprocessing Techniques for Enhancing Vision-Based Detectio...

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7th International Seminar on Research of Information Technology and Intelligent systems, ISRITI 2024

作者： Loo, Jia Hao Jauw, Veronica Lestari Lim, Chin Seong Sarmin, Khairul-Rijal Qomariyah, Nunung Nurul Fajar, Ahmad Nurul University of Nottingham Malaysia Department of Mechanical Materials and Manufacturing Engineering Malaysia Continental Tyre Technology Centre Malaysia Petaling Jaya Malaysia Bina Nusantara University School of Computing and Creative Arts Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Information System Management Department Jakarta Indonesia

ISBN: (纸本)9798331519643

This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including Redmi 9T, iPhone 11, and Galaxy S23 Ultra. The captured images are then transferred to a computer for storage. Subsequently, these images were cropped according to the boundaries identified by Hough Circle Transform (HCT). The cropped images were then further pre-processed. During the pre-processing phase, geometrical transformation and image sharpening techniques are applied to enhance the clarity and readability of the text images. The text is then extracted using Google Vision, with the extracted text categorized by size, DOT, brand and pattern. The results indicated that the effectiveness of image pre-processing was constrained by the accuracy of circle detection, which reached a maximum rate of 87.1%. This causes parts of the text to be cut out inaccurately, leading to a suboptimal extraction accuracy of 55.65%. It is also observed that the Redmi 9T camera produced inconsistent results compared to other devices. Specifically, the iPhone 11 and Samsung Galaxy S23 Ultra demonstrated superior extraction accuracies of 69.71% and 66.37%, respectively, whereas the Redmi 9T achieved a lower extraction accuracy of 37.76%. © 2024 IEEE.

关键词： OCR text extraction text identification tire handling tire sidewalls information

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Zema Dataset: A Comprehensive Study of Yaredawi Zema with a Focus on Horologium Chants

arXiv

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arXiv 2024年

作者： Muluneh, Mequanent Argaw Peng, Yan-Tsung Degife, Worku Abebe Tadesse, Nigussie Abate Demeku, Aknachew Mebreku Su, Li Institute of Information Science Academia Sinica Taipei Taiwan Department of Information System University of Gondar Gondar Ethiopia Department of Computer Science National Chengchi University Taipei Taiwan Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Taiwan Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Material Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan

Computational music research plays a critical role in advancing music production, distribution, and understanding across various musical styles in the world. Despite the immense cultural and religious significance, the Ethiopian Orthodox Tewahedo Church (EOTC) chants are relatively underrepresented in computational music research. This paper contributes to this field by introducing a new dataset specifically tailored for the analysis of EOTC chants, also known as Yaredawi Zema. This work provides a comprehensive overview of a 10-hour dataset, 369 instances, creation, and curation process, including rigorous quality assurance measures. Our dataset has a detailed word-level temporal boundary and reading tone annotation along with the corresponding chanting mode label of audios. Moreover, we have also identified the chanting options associated with multiple chanting notations in the manuscript by annotating them accordingly. Our goal in making this dataset available to the public1 is to encourage more research and study of EOTC chants, including lyrics transcription, lyric-to-audio alignment, and music generation tasks. Such research work will advance knowledge and efforts to preserve this distinctive liturgical music, a priceless cultural artifact for the Ethiopian people. © 2024, CC BY.

关键词： Music

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