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Machine learning-based analysis on factors influencing blood heavy metal concentrations in the Korean CHildren's ENvironmental health Study (Ko-CHENS)

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Science of the Total Environment 2025年 978卷

作者： Jung, Seowoo Shah, Surabhi Oh, Jongmin Bang, Yoorim Lee, Ji Hyen Kim, Hwan-Cheol Jeong, Kyoung Sook Park, Huibyeol Lee, Eun-Kyung Hong, Yun-Chul Ha, Eunhee Department of Statistics Ewha Womans University Seoul Korea Republic of Department of Environmental Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Department of Human Systems Medicine College of Medicine Seoul National University Seoul Korea Republic of College of Medicine Ewha Womans University Seoul Korea Republic of Institute for Development and Human Security Ewha Womans University Seoul Korea Republic of Department of Pediatrics College of Medicine Ewha Womans University Seoul Korea Republic of Department of Occupational and Environmental Medicine College of Medicine Inha University Hospital Inha University Incheon Korea Republic of Department of Occupational and Environmental Medicine Wonju College of Medicine Wonju Severance Christian Hospital Yonsei University Wonju Korea Republic of Environmental Health Research Division National Institute of Environmental Research Incheon Korea Republic of Institute of Environmental Medicine Medical Research Center Seoul National University Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Ewha Medical Research Institute College of Medicine Seoul Korea Republic of

Heavy metal concentration in pregnant women affects neurocognitive and behavioral development of their infants and children. The majority of existing research focusing on pregnant women's heavy metal concentration has considered individual environmental factor. In this study, we aim to comprehensively consider lifestyle, food, and environmental factors to determine the most influential factor affecting heavy metal concentration in pregnant women. The Ko-CHENS (Korean CHildren health and ENvironmental Study) is a nationwide prospective birth cohort study in South Korea enrolling pregnant women from 2015 to 2020. A total of 5458 eligible pregnant women were included in this study, and 897 variables were included in questionnaire comprising: maternal general information, indoor and living environment, dietary habits, health behavior, exposure to chemicals. Lead, cadmium and mercury concentration on blood were measured in early, late pregnancy and in cord blood at birth. Variables that might be related to heavy metal concentrations were included in machine learning models. Random forest and XGBoost machine learning models were conducted for predictions. Both models had similar but better performance than multiple linear regression. Kimchi (β = 1.55), seaweed (β = 0.40), fatty fish (β = 1.55), intakes respectively affected lead, cadmium, and mercury exposure through early, late pregnancy and cord blood. © 2025

关键词： Obstetrics

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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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Computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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Performance Analysis of Building Integrated Photovoltaic (BIPV): MANOVA Analysis 1

Performance Analysis of Building Integrated Photovoltaic (BI...

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1st Middle East and North Africa Solar Conference, MENA-SC 2023

作者： Alzahmi, Wadhah Alyaarbi, Alyaa Alnaqbi, Tahani Alzaatreh, Ayman Dubai Electricity and Water Authority Dubai United Arab Emirates American University of Sharjah Sharjah Department of Industrial Engineering Engineering Systems Management Program Sharjah26666 United Arab Emirates College of Arts and Sciences American University of Sharjah Sharjah Department of Mathematics and Statistics Sharjah26666 United Arab Emirates

ISBN: (纸本)9781665491464

Global energy consumption has increased over the years due to population growth, economic expansion, and the pursuit of a higher quality of life. The building sector is a critical sector for high consumption, contributing to about 36% of the total global energy consumption in 2020. The global interest in reducing energy consumption allows different sectors to adopt renewable resources such as solar photovoltaics (PV). However, utilizing solar PV in buildings has limitations due to rooftop space constraints in newly designed buildings. Due to this limitation and continuous innovation in solar PV technologies, Building Integrated Photovoltaics (BIPV) have been introduced as a potential alternative for solar PV in buildings. As such, BIPV energy performance and panel temperatures are affected by many factors such as orientation setup and technology type. Therefore, this research aims to analyze the impact of technology type (indium gallium selenide (CIGS) and monocrystalline (MONO) & orientation on BIPV energy production & module temperature. The data used for this study is based on a project completed in Dubai for BIPV in building applications. The results indicate that BIPV type and system orientation during each session significantly affect BIPV energy production and BIPV module temperature. © 2023 IEEE.

关键词： Energy utilization

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Regional Lymph Node Delineation variability and its Dosimetric Impact in Breast Cancer Radiotherapy

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Clinical Oncology 2025年 42卷 103836-103836页

作者： Nabi, Z. Megias, D. Diez, P. Caraman, A. Mir, R. Wheatley, D. Maclennan, M. Bliss, J. Haviland, J. Sydenham, M.A. Spezi, E. Tsang, Y. Brunt, A.M. National Radiotherapy Trials Quality Assurance (RTTQA) Group United Kingdom Mount Vernon Cancer Centre Northwood United Kingdom Glan Clwyd Hospital Betsi Cadwaladr University Health Board. Bodelwyddan Denbighshire Wales United Kingdom Royal Cornwall Hospitals NHS Trust Cornwall United Kingdom Edinburgh Cancer Centre Western General Hospital NHS Lothian Edinburgh United Kingdom Clinical Trials and Statistics Unit (ICR-CTSU) The Institute of Cancer Research London United Kingdom Wolfson Institute of Population Health Queen Mary University of London London United Kingdom School of Engineering Cardiff University Cardiff United Kingdom Radiation Medicine Program Princess Margaret Cancer Center Toronto Canada Department of Radiation Oncology University of Toronto Toronto Canada School of Medicine University of Keele and University Hospitals of North Midlands Staffordshire United Kingdom

Aims: To quantify the interobserver variability of regional lymph node delineation for breast cancer radiotherapy (RT) and establish whether a relationship exists between contouring variations and dosimetry using the FAST-Forward (FF) pre-trial RT quality assurance (QA) benchmark cases. Materials and methods: As part of the pre-trial RT QA, local site principal investigators (PIs) were asked to complete a single outlining QA benchmark case involving the delineation of axillary lymph node clinical target volumes (LNCTVs) levels 1–4. These contours were evaluated for concordance against an expert defined consensus gold standard (GS) volume using various conformity indices (CIs): discordance index (DI), geographical miss index (GMI), Jaccard index (JCI), mean distance to conformity (MDC) for both over- and under- contouring. Descriptive statistics including interquartile range (IQR) was used to evaluate interobserver variation. Wilcoxon signed-rank tests were used to establish if there were any statistically significant differences in the dosimetric parameters between plans conforming to GS volume and the volumes from the individual PI. Results: Pre-trial outlining QA benchmark cases from 29/33 PIs were assessed. The median submitted LNCTV volume was 131.4 cc (IQR: 112.4 – 145.3) compared with the GS volume of 105.46 cc. For conformity indices, the median DI was 0.37 (IQR: 0.31 – 0.40), the median GMI was 0.21 (IQR: 0.13 – 0.28), the median JCI was 0.53 (IQR: 0.49 – 0.56), MDC_under was -0.43 (IQR: -0.64 - -0.32) and MDC_over was 0.46 (IQR: 0.43 – 0.53). A dosimetric analysis showed all plans met the mandatory planning dose constraints but not the optimal objectives for target volumes as required in the trial protocol. Statistically significant differences were found in 7/13 organs at risk dosimetric parameters between plans conformed to individual PI volumes and the GS volume. Conclusion: Analysis of the FF pre-trial QA outlining benchmark case hig

关键词： Breast cancer lymph node contouring interobserver variability quality assurance

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Short-segment heart sound classification using an ensemble of deep convolutional neural networks

arXiv

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arXiv 2018年

作者： Noman, Fuad Ting, Chee-Ming Salleh, Sh-Hussain Ombao, Hernando School of Biomedical Engineering & Health Sciences Universiti Teknologi Malaysia Malaysia Statistics Program King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Statistics Program King Abdullah University of Science and Technology Saudi Arabia

This paper proposes a framework based on deep convolutional neural networks (CNNs) for automatic heart sound classification using short-segments of individual heart beats. We design a 1D-CNN that directly learns features from raw heart-sound signals, and a 2D-CNN that takes inputs of two-dimensional time-frequency feature maps based on Mel-frequency cepstral coefficients (MFCC). We further develop a time-frequency CNN ensemble (TF-ECNN) combining the 1D-CNN and 2D-CNN based on score-level fusion of the class probabilities. On the large PhysioNet CinC challenge 2016 database, the proposed CNN models outperformed traditional classifiers based on support vector machine and hidden Markov models with various hand-crafted time- and frequency-domain features. Best classification scores with 89.22% accuracy and 89.94% sensitivity were achieved by the ECNN, and 91.55% specificity and 88.82% modified accuracy by the 2D-CNN alone on the test set. Copyright © 2018, The Authors. All rights reserved.

关键词： Cardiology

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Assessing alternatives for meeting water demand: A case study of water resource management in the Brazilian Semiarid region

Assessing alternatives for meeting water demand: A case stud...

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作者： de Andrade Santana, Rosinele Marques Bezerra, Saulo de Tarso Melo dos Santos, Sylvana Paiva Coutinho, Artur Lopes Coelho, Isabela Carolina Silva Pessoa, Ruben Vivaldi Postgraduation Program in Civil and Environmental Engineering Universidade Federal de Pernambuco CaruaruPE Brazil Department of Technology Universidade Federal de Pernambuco Avenida Campina Grande S/N CaruaruPE55014-900 Brazil Department of Civil and Environmental Engineering Universidade Federal de Pernambuco RecifePE Brazil Postgraduation Program in Biometry and Applied Statistics Universidade Federal Rural de Pernambuco RecifePE Brazil

Population growth, climate change, and the occurrence of droughts have intensified the water supply crises in the Brazilian Semiarid region. The objective of this study was to identify the most relevant measures for the improvement of the water supply of Caruaru, Brazil. The research involved five steps: the selection of experts, comprehension of variables, application of Delphi research, statistical analyses, and consolidation of results. Projects to expand the system and reduce real losses are the most recommended measures. It is also important to implement an integrated water resources management approach that embraces alternative technological and governance strategies. © 2019 Elsevier Ltd

关键词： Water supply

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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2023 International Conference on Machine Learning and Cybernetics, ICMLC 2023

作者： Yu, Jen-Chien Yang, Chun-Chieh Gilbert, John Reuben Liu, Rou-Jun Oyang, Yen-Jen Yang, Meng-Han National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung City807618 Taiwan National Taiwan University Master Program in Statistics Taipei106216 Taiwan National Taiwan University Department of Computer Science & Information Engineering Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan

ISBN: (纸本)9798350303780

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset. © 2023 IEEE.

关键词： Probability density function

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Fuzzy document retrieval for Portuguese language

Fuzzy document retrieval for Portuguese language

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： B.H. Storb R.S. Wazlawick Production Engineering Graduate Program Department of Informatics and Statistics UFSC-CTC-INE Federal University Florianopolis Santa Catarina Brazil

This paper reports a model of document retrieval for the Portuguese language, developed from a Miyamoto document-retrieval model. The Miyamoto model is based upon semantic similarity detection of descriptors by co-occurrences. The proposed model may be considered an extension of the Miyamoto model because it considers lexical similarities and expression similarities. Hence, descriptors and queries are expressions, i.e. series of words and connectors (prepositions, etc.). The similarity between words is based on the comparison between possible radicals for the detection of words with identical or similar meanings. The expression similarity is determined by comparing words and connectors using an adaptation of a Bruza and van der Weide (1991) model. The proposed Miyamoto model extension considers both: the determination of a fuzzy thesaurus by a fuzzy index, achieved through lexical descriptor similarities; and the possibility of a non-controlled vocabulary use by the determination of similarities between document descriptors and query expressions. A sample document base was created for the comparison between the models. The results show the usefulness of the proposed model for document retrieval in the Portuguese language.

关键词： Thesauri Boolean functions Information retrieval Connectors Vocabulary Fuzzy logic Production engineering Informatics statistics Natural languages

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A chattering free consensus controller for multiple Lur'e systems with a non-autonomous leader and directed switching topology

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Science China(Technological Sciences) 2023年第4期66卷 1110-1118页

作者： WANG PeiJun YU WenWu WEN GuangHui YU XingHuo HUANG TingWen School of Mathematics and Statistics Anhui Normal UniversityWuhu 241000China Anhui Province Engineering Laboratory of Intelligent Robot's Information Fusion and Control Anhui Normal UniversityWuhu 241000China School of Mathematics Frontiers Science Center for Mobile Information Communication and SecuritySoutheast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 21111lChina Department of Electrical Engineering Nantong UniversityNantong 226019China Department of Systems Science School of MathematicsSoutheast UniversityNanjing 210096China School of Engineering RMIT UniversityMelbourne VIC 3001Australia Science Program Texas A&M University at QatarDoha 23874Qatar

Achieving asymptotical cooperative goal for multi-agent systems(MASs)with non-autonomous leaders(i.e.,leaders with nonzero inputs)is a critical but challenging *** approach is to use discontinuous controllers which may cause chattering phenomenon in practical *** to achieve the asymptotical goal via a chattering free cooperative controller remains to be open so *** this paper,an adaptive continuous controller is designed to achieve zero error consensus tracking in multiple Lur’e systems with a non-autonomous leader under directed switching ***,an unknown input observer(UIO)based on relative outputs is given to estimate the relative full *** an adaptive continuous controller is designed by introducing a decay function which remains positive into the term that plays the role of eliminating the impacts of leader’s nonzero ***,by using multiple Lyapunov functions(MLFs)technique,it is proven that zero error consensus tracking can be achieved if the average dwell time(ADT)is greater than a positive ***,theoretical result is verified by performing simulations on Chua’s *** with existing work,the proposed controller can not only achieve asymptotical consensus,but also is chattering free.

关键词： multi-agent system consensus chattering free non-autonomous leader directed switching topology

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Coarse Grained Molecular Dynamics Simulation of Interaction between Hemagglutinin Fusion Peptides and Lipid Bilayer Membranes

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Advances in Applied Mathematics and Mechanics 2010年第4期2卷 430-450页

作者： Naveen K.Vaidya Huaxiong Huang Shu Takagi Theoretical Biology and Biophysics Group MS K710Los Alamos National LaboratoryLos AlamosNM 87545 USA Department of Mathematics and Statistics York UniversityTorontoM3J 1P3 Canada Organ and Body Scale Team Computational Science Research ProgramRiken Department of Mechanical Engineering The University of TokyoTokyoJapan

Microscopic level interaction between fusion-peptides and lipid bilayer membranes plays a crucial role in membrane fusion,a key step of viral *** this paper,we use coarse-grained molecular dynamics(CGMD)simulations to study the interaction between hemagglutinin fusion-peptides and phospholipid bilayer *** CGMD,we are able to simulate the interaction of fusion peptides with a relatively large piece of membrane for a sufficiently long time period,which is necessary for a detailed understanding of the fusion process.A conformation of the peptide with a kink at the level of phosphate group is obtained,consistent with NMR and EPR *** results show that the N-terminal segment of the peptide inserts more deeply into the membrane bilayer compared to the C-terminal segment,as observed in previous *** simulations also show that the presence of fusion peptides inside the membrane may cause bilayer thinning and lipid molecule ***,our results reveal that peptides tend to aggregate,indicating cluster formation as seen in many experiments.

关键词： Coarse-grained molecular dynamics fusion peptide hemagglutinin protein phospholipid bilayer membrane fusion

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