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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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Influencing turnover intention among building information modeling (BIM) Workers in China: A structural equation modeling approach

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Acta Psychologica 2025年 257卷 105121页

作者： Wei, Wei Prasetyo, Yogi Tri Benito, Omar Paolo Cahigas, Maela Madel L. Nadlifatin, Reny Gumasing, Ma. Janice J. School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines 658 Muralla St. Intramuros Manila 1002 Philippines School of Graduate Studies Mapúa University Manila Philippines 658 Muralla St. Intramuros Manila 1002 Philippines Hulunbuir University No. 26 Middle Genghis Khan Road Nei Mongol Hulunbuir China International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Road Chung-Li 32003 Taiwan Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li 32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia Department of Industrial and Systems Engineering Gokongwei College of Engineering De La Salle University Manila 1004 Philippines

Building Information Modeling (BIM) has become integral to modern construction management in China, yet its successful implementation has been hindered by a shortage of skilled BIM personnel and high turnover rates. This study investigates the key factors influencing turnover intention among BIM workers in China through a structural equation modeling (SEM) approach. Survey data were collected from 558 BIM practitioners and researchers across various regions in China. The SEM results revealed that three work-related factors—management and staff cooperation, working hours, and satisfaction with salary and incentives—significantly affected BIM workers' turnover intentions. Notably, the influence of these factors on turnover intention was fully mediated by two pivotal attitudinal variables: job satisfaction and organizational commitment. Among the predictors, excessive working hours emerged as the most salient driver heightening turnover intention, whereas strong team cooperation and competitive, fair rewards reduce the propensity to leave by enhancing worker satisfaction and commitment. The integrated model developed in this research advances understanding of BIM workforce retention and can be generalized to similar project-based contexts. The findings provide an evidence-based foundation for policymakers and industry leaders to devise strategies (e.g., improving working conditions, strengthening organizational support) aimed at increasing job satisfaction and commitment, thereby mitigating turnover intention among BIM workers. © 2025 The Authors

关键词： Chinese Job satisfaction management and staff cooperation Organizational commitment Salary and incentives Turnover Working hours

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Efficacy of rain barrels and rain gardens to reduce urban pluvial flooding in densely built-up residential areas: a case study on Miyahara-Cho in Saitama City, Japan

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City and Built Environment 2023年第1期1卷 1-17页

作者： Lin, Jiajing Uchiyama, Shun Bhattacharya, Yasmin Nakamura, Hitoshi Master student Graduate School of Engineering and Science Shibaura Institute of Technology Saitama City Japan Associate Professor Department of Planning Architecture and Environmental Systems Shibaura Institute of Technology Saitama City Japan Professor Department of Planning Architecture and Environmental Systems Shibaura Institute of Technology Saitama City Japan

In recent years, flooding in densely built-up residential areas has tended to increase because of the increased frequency of heavy rain and climate change. Urban pluvial flooding mitigation is thus needed by reducing the runoff of sewer systems using green infrastructure solutions. In this regard, rain barrels (RBs) and rain gardens (RGs) are considered effective stormwater management methods. This study aimed to verify the effectiveness of RBs and RGs and their combined use in reducing urban pluvial flooding in densely built-up residential areas. This research undertook a case study in Miyahara-Cho, Saitama City, Japan. It involved the analysis of the total runoff of sewer systems and the flood condition in the sewer to verify the rainwater runoff control effect of RBs and RGs through simulations using the US Environmental Protection Agency’s stormwater management model. This study simulates two main types of rainfall events: short duration and long duration. The results of the short duration rainfall showed that the combination of RBs and RGs is highly effective and can reduce the impact of excess runoff. In the case of the long duration rainfall, the volume and speed of stormwater runoff of the first peak rainfall were reduced.

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Occurrence of antibiotics, hormones and PFAs in surface water from a Nile tilapia aquaculture facility in a Brazilian hydroelectric reservoir

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Chemosphere 2024年 352卷 141444页

作者： Rodrigues, Daniel Aparecido da S. Starling, Maria Clara V.M. Barros, André Luiz C. de Santos, Mônica C. da Silva, Eloísa Stéphanie Viana, Guenther Carlos C. Ribeiro, Lara Fabian da S. Simcik, Matt F. Amorim, Camila C. GruPOA - Research Group on Environmental Applications of Advanced Oxidation Processes Department of Sanitary and Environmental Engineering Universidade Federal de Minas Gerais MG Belo Horizonte Brazil SIMOA - Intelligent Systems for Environmental Monitoring Department of Sanitary and Environmental Engineering Universidade Federal de Minas Gerais MG Belo Horizonte Brazil ProAmb - Graduate Program in Environmental Engineering Department of Environmental Engineering Universidade Federal de Ouro Preto in Memoriam MG Ouro Preto Brazil University of Minnesota School of Public Health 420 Delaware St SE MMC 807 MinneapolisMN55455 United States

This study assessed the occurrence of five antibiotics, three hormones, caffeine, and long and short-chain perfluoroalkyl and polyfluoroalkyl substances (PFASs) in surface water and feedstuff samples obtained from aquaculture cages in Três Marias reservoir in Brazil. This is the first work to evaluate the presence of PFAS in surface water used for aquaculture in Brazil. Solid-phase extraction and low temperature partitioning extraction followed by liquid chromatography coupled to mass spectrometry (LC-MS) were performed to process and analyze surface water samples and feedstuff, respectively. The ecotoxicological risk quotient was calculated for target compounds detected in water. Ciprofloxacin and caffeine were detected in all surface water samples. Pharmaceutical drugs ranged from 0.7 ng L−1 (trimethoprim) to 389.2 ng L −1 (β-estradiol). Estrone (10.24 ng g−1) and β-estradiol (66.20 ng g−1) were also found in feedstuff. Four PFASs (PFOA, PFDoA, PFTeDA, and PFBS) were detected (9.40–15.2 μg L−1) at levels higher than reported in studies conducted worldwide. Ecotoxicological risk assessment indicated high risks for caffeine and PFOA, PFDoA, and PFTeDA with RQ values from 10 to 103. These findings reveal risks to biodiversity, ecosystem integrity and human health considering possible intake of these contaminants by fish consumption due to potential bioaccumulation of these substances. Hence, it is critical to conduct more studies in this direction in Brazil and other low and middle-low-income countries. © 2024

关键词： Water quality

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KMD clustering: robust general-purpose clustering of biological data

Communications Biology

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Communications Biology 2023年第1期6卷 1110页

作者： Zelig, Aviv Kariti, Hagai Kaplan, Noam Data Science & Engineering Program Faculty of Industrial Engineering & Management Technion - Israel Institute of Technology Haifa Israel Department of Physiology Biophysics & Systems Biology Rappaport Faculty of Medicine Technion – Israel Institute of Technology Haifa Israel

The noisy and high-dimensional nature of biological data has spawned advanced clustering algorithms that are tailored for specific biological datatypes. However, the performance of such methods varies greatly between datasets and they require post hoc tuning of cryptic hyperparameters. We present k minimal distance (KMD) clustering, a general-purpose method based on a generalization of single and average linkage hierarchical clustering. We introduce a generalized silhouette-like function to eliminate the cryptic hyperparameter k, and use sampling to enable application to million-object datasets. Rigorous comparisons to general and specialized clustering methods on simulated, mass cytometry and scRNA-seq datasets show consistent high performance of KMD clustering across all datasets. © 2023, The Author(s).

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Importance of surface charge of soot nanoparticles in determining inhalation toxicity in mice

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Environmental Science and Pollution Research 2023年第7期30卷 18985-18997页

作者： Hsiao, Ta-Chih Han, Chia-Li Yang, Tzu-Ting Lee, Yueh-Lun Shen, Yu-Fang Jheng, Yu-Teng Lee, Chii-Hong Chang, Jer-Hwa Chung, Kian Fan Kuo, Han-Pin Chuang, Hsiao-Chi Graduate Institute of Environmental Engineering National Taiwan University Taipei Taiwan Master Program in Clinical Genomics and Proteomics College of Pharmacy Taipei Medical University Taipei Taiwan Department of Environmental Engineering and Health Yuanpei University of Medical Technology Hsin Chu City Taiwan Department of Microbiology and Immunology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Environmental Engineering National Center University Tauyoun Taiwan Genome and Systems Biology Degree Program Academia Sinica and National Taiwan University Taipei Taiwan Department of Pathology Taipei City Hospital Heping Fuyou Branch Taipei Taiwan School of Respiratory Therapy College of Medicine Taipei Medical University Taipei Taiwan Division of Pulmonary Medicine Department of Internal Medicine Wan Fang Hospital Taipei Medical University Taipei Taiwan National Heart and Lung Institute Imperial College London London United Kingdom Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei Taiwan

Physicochemical properties of nanoparticles are important in regulating nanoparticle toxicity;however, the contribution of nanoparticle charge remains unclear. The objective of this study was to investigate the pulmonary effects of inhalation of charged soot nanoparticles. We established a stably charged nanoparticle generation system for whole-body exposure in BALB/c mice, which produced positively charged, negatively charged, and neutral soot nanoparticles in a wide range of concentrations. After a 7-day exposure, pulmonary toxicity was assessed, together with proteomics analysis. The charged soot nanoparticles on average carried 1.17–1.35 electric charges, and the sizes for nanoparticles under different charging conditions were all fixed at 69 ~ 72 nm. We observed that charged soot nanoparticles induced cytotoxic LDH and increased lung permeability, with the release of 8-isoprostane and caspase-3 and systemic IL-6 in mice, especially for positively charged soot nanoparticles. Next, we observed that positive-charged soot nanoparticles upregulated Eif2, Eif4, sirtuin, mammalian target of rapamycin (mTOR), peroxisome proliferator-activated receptors (PPAR), and HIPPO-related signaling pathways in the lungs compared with negatively charged soot nanoparticles. HIF1α, sirt1, E-cadherin, and Yap were increased in mice’s lungs by positively charged soot nanoparticle exposure. In conclusion, carbonaceous nanoparticles carrying electric ions, especially positive-charged, are particularly toxic when inhaled and should be of concern in terms of pulmonary health protection. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Nanoparticles

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Deep-Net:Fine-Tuned Deep Neural Network Multi-Features Fusion for Brain Tumor Recognition

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Computers, Materials & Continua 2023年第9期76卷 3029-3047页

作者： Muhammad Attique Khan Reham R.Mostafa Yu-Dong Zhang Jamel Baili Majed Alhaisoni Usman Tariq Junaid Ali Khan Ye Jin Kim Jaehyuk Cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Informatics University of LeicesterLeicesterUK Information Systems Department Faculty of Computers and Information SciencesMansoura UniversityMansouraEgypt Department of Computer Engineering College of Computer ScienceKing Khalid UniversityAbha61413Saudi Arabia Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Management Information System Department College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Manual diagnosis of brain tumors usingmagnetic resonance images(MRI)is a hectic process and ***,it always requires an expert person for the ***,many computer-controlled methods for diagnosing and classifying brain tumors have been introduced in the *** paper proposes a novel multimodal brain tumor classification framework based on two-way deep learning feature extraction and a hybrid feature optimization ***-Mobile,a pre-trained deep learning model,has been fine-tuned and twoway trained on original and enhancedMRI *** haze-convolutional neural network(haze-CNN)approach is developed and employed on the original images for contrast ***,transfer learning(TL)is utilized for training two-way fine-tuned models and extracting feature vectors from the global average pooling ***,using a multiset canonical correlation analysis(CCA)method,features of both deep learning models are fused into a single feature matrix—this technique aims to enhance the information in terms of features for better *** the information was increased,computational time also *** issue is resolved using a hybrid feature optimization algorithm that chooses the best classification *** experiments were done on two publicly available datasets—BraTs2018 and BraTs2019—and yielded accuracy rates of 94.8%and 95.7%,*** proposedmethod is comparedwith several recent studies andoutperformed *** addition,we analyze the performance of each middle step of the proposed approach and find the selection technique strengthens the proposed framework.

关键词： Brain tumor haze contrast enhancement deep learning transfer learning features optimization

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An LMI adaptive-barrier function global sliding mode control of uncertain nonlinear systems with input saturation

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Ain Shams engineering Journal 2024年第2期15卷

作者： Rahimpour, Rahim Sepestanaki, Mohammadreza Askari Mobayen, Saleh Mokhtare, Zahra Fekih, Afef Assawinchaichote, Wudhichai Zhilenkov, Anton Electrical Engineering Department University of Zanjan Zanjan Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan Department of Electrical and Computer Engineering University of Louisiana at Lafayette Lafayette United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok10140 Thailand Department of Cyber-Physical Systems St. Petersburg State Marine Technical University Saint-Petersburg190121 Russia

This paper proposes a barrier function-based adaptive control strategy with a nonlinear sliding surface for a class of uncertain dynamic systems with input saturation. Its main objectives are to ensure robustness to parametric and non-parametric uncertainties whilst eliminating the reaching phase. A global nonlinear switching surface is defined and an adaptive barrier function sliding mode control approach is derived. The barrier strategy is adopted to ensure the convergence of the states to the desired values without overestimating the control gains. System stability is analyzed using the Lyapunov stability theory. The control parameters are obtained using the linear matrix inequality (LMI) approach. The control law is designed to remove the reaching phase. The effectiveness of the proposed approach was validated using a simulation study. The proposed control approach can easily be implemented to various nonlinear uncertain systems. © 2023 THE AUTHORS

关键词： Linear matrix inequalities

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Improvement of Spatial Ambiguity in Multi-Channel Speech Separation Using Channel Attention

Improvement of Spatial Ambiguity in Multi-Channel Speech Sep...

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2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021

作者： Hong, Qian-Bei Wu, Chung-Hsien Nguyen, Thanh Binh Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9789881476890

Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel signal captured by a structured microphone array and leveraging the inner difference between channels to enhance the speech separation performance. The spatial feature has been widely used in recent speech separation research. This feature appears to be insufficient when the location information becomes ambiguous. This is known as the spatial ambiguity problem. In order to deal with the spatial ambiguity problem, this study proposes an attention mechanism for the Temporal-Spatial Neural Filter (TSNF), in which the channel attention on merged features and the feature map of 1D convolution block in the temporal convolution network is proposed. The proposed method is evaluated on the multi-channel reverberant dataset which is built based on the WSJ0-2mix dataset. The dataset is simulated in the real-environment room by using the Room Impulse Response generator. In the experimental results, the proposed methods produced the SI -SNR improvement of about 1.2dB in close speakers' case, while a small decrease of 0.1dB in other cases. © 2021 APSIPA.

关键词： Convolution

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Investigating the dynamic memory effect of human drivers via ON-LSTM

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Science China(Information Sciences) 2020年第9期63卷 83-93页

作者： Shengzhe DAI Zhiheng LI Li LI Dongpu CAO Xingyuan DAI Yilun LIN Department of Automation Tsinghua University Shenzhen International Graduate School Tsinghua University Department of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

It is a widely accepted view that considering the memory effects of historical information(driving operations) is beneficial for vehicle trajectory prediction models to improve prediction accuracy. However,many commonly used models(e.g., long short-term memory, LSTM) can only implicitly simulate memory effects, but lack effective mechanisms to capture memory effects from sequence data and estimate their effective time range(ETR). This shortage makes it hard to dynamically configure the most suitable length of used historical information according to the current driving behavior, which harms the good understanding of vehicle motion. To address this problem, we propose a modified trajectory prediction model based on ordered neuron LSTM(ON-LSTM). We demonstrate the feasibility of ETR estimation based on ON-LSTM and propose an ETR estimation method. We estimate the ETR of driving fluctuations and lane change operations on the NGSIM I-80 dataset. The experiment results prove that the proposed method can well capture the memory effects during trajectory prediction. Moreover, the estimated ETR values are in agreement with our intuitions.

关键词： driving behavior memory effect trajectory prediction historical information ON-LSTM

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