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Environmental health risks and impacts of PM2.5sub> exposure on human health in residential areas, Bantul, Yogyakarta, Indonesia

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Toxicology Reports 2025年 14卷 101949页

作者： Abidin, Azham Umar Munawaroh, Anisful Lailil Rosinta, Aulia sulistiyani, Arvi Tri Ardianta, Iwan Iresha, Fajri Mulya Department of Environmental Engineering Faculty of Civil Engineering and Planning Universitas Islam Indonesia Indonesia Department of Information and Medical Service Vocational School Applied Master's Program in Occupational Health and Safety Universitas Gadjah Mada Indonesia Department of Community Family and Occupational Medicine Faculty of Medicine Khon Kaen University Thailand Faculty of Medicine Universitas Islam Indonesia Indonesia Laboratory of Air Quality Department of Environmental Engineering Universitas Islam Indonesia Indonesia Laboratory of Solid and Hazardous Wastes Department of Environmental Engineering Universitas Islam Indonesia Indonesia

Air pollution, particularly PM2.5, significantly impacts public health in developing areas. This study evaluates PM2.5 exposure among residents and conducts a health risk assessment within the human community in Bantu... 详细信息

Air pollution, particularly PM2.5sub>, significantly impacts public health in developing areas. This study evaluates PM2.5sub> exposure among residents and conducts a health risk assessment within the human community in Bantul Regency, Indonesia, utilizing a high-volume air sampler (HVAs) over 24 h in a residential area and interviewing 36 respondents. The findings of this study show that PM2.5sub> concentrations varied from 50.7 to 61.9 μg/m³, exceeding the national ambient air quality standards (NAAQs) of 35 μg/m³. The risk hazard quotient (RQ) values of PM2.5sub> were greater than 1, signifying considerable health risk. Epidemiological statistical analysis indicates a significant correlation (p-value < 0.05) between PM2.5sub> exposure, health complaints, and respondent characteristics. Residents report health issues including cough, headache, eye irritation, breathlessness, and wheezing. The findings emphasize the imperative for more rigorous air quality standards and regulations, enhanced public awareness and education regarding preventive practices, and urban planning development strategies incorporating green infrastructure. These measures are crucial for alleviating health hazards and enhancing air quality in impacted areas. © 2025 The Authors

关键词： environmental health health impact health risk assessment PM2.5 exposure

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Development of Real-time Assembly Work Monitoring system Based on 3D skeletal Model of Arms and Fingers

Development of Real-time Assembly Work Monitoring System Bas...

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IEEE International Conference on systems, Man and Cybernetics

作者： Taichi Obinata Hiroaki Kawamoto Yoshiyuki sankai Master’s Program in Intelligent and Mechanical Interaction Systems Univetsity of Tsukuba Ibaraki Japan Faculty of Engineering Information and Systems Center for Cybernics Research University of Tsukuba Ibaraki Japan

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

Decreasing birth rates and an aging population in society often cause labor shortages in the manufacturing industry, making the development of methods to improve productivity based on limited human resources imperative. One way to achieve this is by enhancing product quality via the reduction of product losses and the consequent need for reassembly due to human error. Human error during assembly can arise from specific actions via the arms and fingers. We assumed that these errors can be captured based on the information on human skeletal models. The purpose of this study is to propose and develop a system that acquires information about assembly procedures by using human skeletal models, including the fingers of workers, and notifies them of skipped procedures and errors in part types. Further, we confirm the basic capability of the proposed system via experiments based on simulated assembly work. The proposed system monitors workers' motion based on color and depth images captured by a single RGB-D camera. In addition, we developed a function to detect the process and to point out errors with audible and visual feedbacks when errors were made by workers in assembly processes. In the experiment using simulated assembly work, the proposed system exhibited an accuracy rate of 98.3% with respect to acquisition of assembly processes. In the case of an error in an assembly process, the system was able to point out the error correctly and provide feedback to the worker before he had finished picking up the wrong part. In conclusion, we confirmed that the developed system exhibited the basic capability to acquire work procedures and efficiently point out errors in real time.

关键词： Productivity Visualization Three-dimensional displays Fingers Real-time systems statistics Monitoring

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIs) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIs. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10–3sup> mm2sup>/s were applied. Dice similarity coefficient (DsC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DsC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10–3sup> mm2sup>/s and 0.8 × 10–3sup> mm2sup>/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10–3sup> mm2sup>/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10–3sup> mm2sup>/s achieved the highest DsC in the segmentation of AIs lesion. Conclusions: The segmentation performance of U-Net for AIs varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10–3sup> mm2sup>/s in segmentating AIs lesion with highest DsC. Key Points: • segmentation performance of U-Net for AIs differs among input imaging combos. • segmentation performance of U-Net for AIs differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10–3sup>mm2sup>/s. © 2023, The Author(s), under exclusive licence to European society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic stroke Neural Networks, Computer Retrospective study

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Reconstructing suspended sediment concentrations in the Mekong River Basin via semi-supervised-based deep neural networks

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science of the Total Environment 2024年 955卷 176758页

作者： Nguyen, Thi Thu Ha Vu, Duc Quang Doan, Ngoc Phu Chi, Huynh Thi Khanh Li, Peixin Binh, Doan Van An, Yimeng Dung, Pham Tuan Hoang, Tuan A. son, Mai Thai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat City Viet Nam

The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but the sediment concentration data in the MRB are extremely sporadic, making analysis challenging. This study focuses on reconstructing long-term suspended sediment concentration (ssC) data using a novel semi-supervised machine learning (ML) model. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on daily hydroclimate and ssC data obtained from 1979 to 2019 at the three main stations (i.e., Chiang saen, Nong Khai, and Mukdahan) are conducted to demonstrate the superior performance of the proposed method compared to the state-of-the-art supervised techniques (i.e., Random Forest, XGBoost, CatBoost, MLP, CNN, and LsTM), and surpasses existing semi-supervised methods (i.e., CoReg, ⊓ Model, ICT, and Mean Teacher). This approach is the first semi-supervised method to reconstruct sediment data in the field and has the potential for broader application in other river systems. © 2024 The Author(s)

关键词： self-supervised learning

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service Oriented Design for Indonesian E-Government system Using sOA 6

Service Oriented Design for Indonesian E-Government System U...

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Joint Conference of the 6th Annual Conference of Industrial and system engineering 2019, ACIsE 2019 and 1st International Conference on Risk Management as an Interdisciplinary Approach 2019, ICRMIA 2019

作者： Fajar, A.N. shofi, I.M. Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Informatics Engineering UIN Syarif Hidayatullah Indonesia

The objective of this study is to create a services design of E-Government system that can help Indonesian government to resolve some problems such as diversity platform and application. It causes the island applications that can make decision support processes is not well happen. In this study, we use literature review as an approach to discuss the phenomenon. It is performed by identifying, evaluating, and combining information from several other studies which relevant with this study's research questions. We use services oriented analysis and design approach to discussing the phenomenon. The ability of service-oriented Architecture to connect multiple services between diversity systems and it can help the enterprise application travelling in Indonesian government. The case in this study is travelling system in Indonesia Government. The results in this study are the conceptual services for Travelling system using sOA approach and EsB Technology. It consists of several services and business services which is can be integrated among of them. © Published under licence by IOP Publishing Ltd.

关键词： information services

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Mapping Tokenomics Arrangements to Expand the Digital Nomad Ecosystem

Mapping Tokenomics Arrangements to Expand the Digital Nomad ...

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International Conference on Computer supported Cooperative Work in Design

作者： Marcos Antonio de Almeida António Correia Jano Moreira de souza Daniel schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal College of Information Science & Technology University of Nebraska at Omaha Omaha NE USA Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

The Massification of remote work, in response to the COVID-19 pandemic, has been causing significant changes in productive and working arrangements, both for individuals, organizations, and society. At the level of personal life philosophy, for example, this transformation can be evidenced in the dissemination of digital nomadism values such as work/leisure balance among corporate workers. On the other hand, at the level of gig/crowd work platforms, the emergence of tensions may indicate the exhaustion of sociotechnical design models adopted by big techs. We show how evidence collected from digital nomads in empirical ethnography studies can inform HCI/CsCWD researchers of design-oriented strands to explore emerging opportunities in new creative digital crypto-economic ecosystems. Finally, we present a proposed research agenda to explore DNs’ activities in the crypto-economic ecosystem.

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Tensions in design and participation processes: An ethnographic approach to the design, building and evaluation of a collective intelligence model

Tensions in design and participation processes: An ethnograp...

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International Conference on Computer supported Cooperative Work in Design

作者： Ramon Chaves Claudia Motta Antonio Correia Jano de souza Daniel schneider Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil 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 UTAD INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal College of Information Science & Technology University of Nebraska at Omaha Omaha NE USA

This paper explores the challenges and strategies used to design, build and evaluate a collective intelligence (CI) model to support discussions about cities. Through an autoethnography of ideas and discussion practices in both online and offline contexts, this work explores the tensions between the chosen methodological approaches, including design science research (DsR) and participatory action research (PAR). Moreover, we also examine the challenges and pitfalls observed during the practical conduction of this research when involving participants in the process of empirically evaluating the proposed model. Finally, aspects related to the autoethnographic process itself as a reflective method are discussed alongside the consequences of desiring and seeking participation in the research process.

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sentiment Analysis of the Indonesian Police Mobile Brigade Corps Based on Twitter Posts Using the sVM and NB Methods

Sentiment Analysis of the Indonesian Police Mobile Brigade C...

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International Conference on Electronics Representation and Algorithm 2019, ICERA 2019

作者： Pratama, Bryan saputra, Dedi Dwi Novianti, Deny Purnamasari, Endah Putri Kuntoro, Antonius Yadi Hermanto Gata, Windu Wardhani, Nia K sfenrianto, sfenrianto Budilaksono, sularso Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Graduate School Master's Degree Computer Science STMIK Nusa Mandiri Jakarta Indonesia Master Faculty of Computer Science-Postgraduate Program Universitas Mercubuana Jakarta Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Graduate School Master's Degree Computer Science Universitas Persada Indonesia YAI. Jakarta Indonesia

The Brimob Corps is a special police force, just like the special military detachments held by the TNI such as Paskhas and so on. At present brigade corps police national is busy being discussed in the real world and cyberspace, especially on social media twitter. Many opinions about the brigade corps police national so there are positive and negative opinions. social media twitter is now one places to spread information about brigade corps police national. This study cases uses text mining techniques with support vector machine (sVM) method which aims to classify public sentiments towards brigade corps police national on twitter. The dataset used is tweet in Indonesian with keyword "Brimob" with a total dataset of 1000 tweets. Text mining, transform, tokenize, stemming, and classification, etc. techniques are useful for building classification and analysis of sentiment. RapidMiner and Gataframework are also used to help create sentiment analysis to measure classification values. Accuracy values obtained with support vector machine (sVM) approach 86,96%, with precision values of 86,96%, and recall values of 86,96%. © Published under licence by IOP Publishing Ltd.

关键词： Law enforcement

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Prediction of Hydrogen Production Rate in Anaerobic Fermentation Using Grey Relation Analysis and Machine Learning

SSRN

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ssRN 2023年

作者： Wang, Yifan Wu, Jinghui Tseng, Yu-Yao Zhao, Chunliang Li, Keqing Wang, Xianze Wang, Ming-Hung Lay, Chyi-How Huo, Mingxin Engineering Research Center of Low-Carbon Treatment Green Development of Polluted Water in Northeast China Ministry of Education Changchun130117 China Science and Technology Innovation Center for Municipal Wastewater Treatment and Water Quality Protection Northeast Normal University Changchun130117 China Key Laboratory of Songliao Aquatic Environment Ministry of Education Jilin Jianzhu University Changchun130118 China Master's Program of Green Energy Science and Technology Feng Chia University Taichung40724 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi County Taiwan

Anaerobic fermentation for hydrogen production has many environmental factors that limit microbial activity, but machine learning has enormous potential in handling the complexity of biological processes. This study explores the potential of machine learning in predicting hydrogen production rates (HPR) from anaerobic fermentation of biomass energy. Grey relation analysis was conducted to determine the correlation between operational parameters and HPR. Five machine learning algorithms, such as decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and K-nearest neighbor (KNN), were then paired with operating conditions and water quality performance as features and HPR as a label, with mean squared error (MsE) and R2 as evaluation indexes. Butyric acid, oxidation-reduction potential (ORP), and volatile suspended solids (Vss) were found to play crucial roles in hydrogen production from sucrose anaerobic fermentation. XGBoost had the highest accuracy with R2 of 0.91 and MsE of 0.0052. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Using Online Grocery Applications during the COVID-19 Pandemic: Their Relationship with Open Innovation

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第2期8卷

作者： Gumasing, Ma. Janice J. Prasetyo, Yogi Tri Persada, satria Fadil Ong, Ardvin Kester s. Young, Michael Nayat Nadlifatin, Reny Redi, Anak Agung Ngurah Perwira School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines School of Graduate Studies Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Malang 65154 Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia Industrial Engineering Department BINUS Graduate Program—Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

This present research examines the behavioral intentions of Filipinos to use online grocery applications during the novel COVID-19 pandemic. The study proposes an integration of the health belief model (HBM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) to identify the factors affecting the acceptance and usage of Filipinos of online grocery applications in terms of the impact of health risk for COVID-19. To accurately measure the factors and their relationship to behavioral intentions and usage behavior, a questionnaire was developed and distributed to 373 residents in the Philippines. Partial least squares structural equation modeling (PLs-sEM) was applied as an analytical method for this study. The results revealed that performance expectancy, perceived benefits, perceived severity, and cues to action significantly influenced the behavioral intentions and usage of online grocery apps during the COVID-19 pandemic. The study’s findings can be utilized as a theoretical framework for future researchers of consumer behavior;e-commerce developers;and grocery industry retailers, to enhance the innovation and services of online grocery applications. The results of this study may also be used and capitalized on by investors and managers to apply in strategizing when developing and marketing online grocery applications among con-sumers. Moreover, the framework of this study may be adopted and utilized by other online markets, even in different counties. Further theoretical and practical aspects are discussed in this paper. © 2022 by the authors. Licensee MDPI, Basel, switzerland.

关键词： health belief model online grocery applications structural equation modeling UTAUT2

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