Childhood violence exposure and its contributing factors in Indonesia: a secondary data analysis of the National Survey on Children and Adolescents’ Life Experience by Dwi Octa Amalia, Sabarinah Sabarinah, Kemal N Siregar, Ella Nurlaella Hadi

“…Future research should explore the practical application of early detection strategies to better support these vulnerable groups.…”
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Prevalence and Factors Associated With Sexually Transmitted Infections Among Women of Reproductive Age in Tanzania: A Cross‐Sectional Analysis of National Data by Fabiola V. Moshi, Jovin R. Tibenderana, Thadei Liganga, Jomo Gimonge, Sanun Ally Kessy

“…In Tanzania, however, data on STIs remains limited. This study seeks to bridge that gap by determining prevalence and factors associated with STIs among WRA in Tanzania. …”
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Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example by Zhefeng Xu, Xiahong Shi, Wei Shu, Yilu Xin, Xuan Zan, Zhaonian Si, Jinping Cheng

“…This study explores the application of machine learning classifiers to analyse Continuous Emission Monitoring Systems data from 107 waste discharge outlets across 31 corporations in a Chinese chemical industrial park. …”
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Estimation of Internal Solitary Waves Propagation Speeds and Occurrence Using Long-Term Sentinel-1 SAR Data in the Lombok Strait, Indonesia by Chonnaniyah, Abd. Rahman As-Syakur, I Made Dharma Raharja, Takahiro Osawa

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Implementasi Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online by Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia

“…This research resulted in a website-based online exam application built using MERN Stack technology. The test results in validating online exam data that has been encrypted using the system and OpenSSL show the same hash value. …”
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Comparing Generative AI Literature Reviews Versus Human-Led Systematic Literature Reviews: A Case Study on Big Data Research by Davide Tosi

“…This study investigates the performance of GPT-4-powered Consensus in conducting an SLR on Big Data research, comparing its results with a manually conducted SLR. …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

“…Motor imagery EEG (MI-EEG) data classification is one of the key applications within brain–computer interface (BCI) systems, utilizing EEG signals from motor imagery tasks. …”
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Addendum: Post-2000 nonlinear optical materials and measurements: data tables and best practices (2023 J. Phys. Photon. 5 035001) by D Ososanya, R Mueller, E T Scheuermann, A Gupta, E Oppong, A Ball, G Boudebs, A S L Gomes, N Vermeulen, N Kinsey

“…Presented in the form of a web-application, users are able to search, filter, and extract information ranging from material and structure information, excitation parameters, measurement technique, and nonlinear coefficients from the data tables presented in Vermeulen et al (2023 J. …”
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A case study on lentil to demonstrate the value of using historic data stored in genebanks to guide the selection of resources for research and development projects by Nadiia Vus, Olha Bezuhla, Hervé Houtin, Florence Naudé, Antonina Vasylenko, Anthony Klein, Oleh Leonov, Nadim Tayeh

“…This exchange was accompanied by the transfer of phenotyping data for multiple traits. Considering that data collected in different environments provide important information on trait stability, the lentil accessions were phenotyped under new conditions through field research. …”
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A nonparametric approach for detecting urban polycentric spatial structure in China using remote sensing nighttime light and point of interest data by Linlin Jiang, Yizhen Wu, Junru Wang, Huiran Han, Kaifang Shi

“…However, existing identification methods have limitations such as subjectivity, poor spatial continuity, and a narrow application scale. Thus, from a morphology perspective, our study proposed a rapid, highly applicable, and spatiotemporally comparable nonparametric approach for detecting morphological urban polycentric spatial structure (MUPS) by integrating remote sensing nighttime light (NTL) and point of interest (POI) data. …”
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Remdesivir associated with reduced mortality in hospitalized COVID-19 patients: treatment effectiveness using real-world data and natural language processing by José Ramón Arribas López, María Pilar Ruiz Seco, Francisco Fanjul, Beatriz Díaz Pollán, Patricia González Ruano Pérez, Adrián Ferre Beltrán, Rosa De Miguel Buckley, Laura Portillo Horcajada, Cristina De Álvaro Pérez, Paulo Jorge Barroso Santos Carvalho, Savana Research Group, Melchor Riera Jaume

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Use of GLOBE observer citizen science data to validate continental-scale canopy height maps derived from ICESat-2 and GEDI by Mei-Kuei Lu, Sorin C. Popescu, Brian A. Campbell, Brian A. Campbell, Brian A. Campbell

“…The Global Learning and Observations to Benefit the Environment (GLOBE) Observer application is a mobile extension of the GLOBE Program that is empowering the public to collect environmental data in support of both scientific research and educational outreach. …”
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An Exploration of Candidate Korean Native Poaceae Plants for Breeding New Varieties as Garden Materials in the New Climate Regime Based on Existing Data by Sang Heon Kim, Wonwoo Cho

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Unraveling regional variability in Dengue outbreaks in Brazil: leveraging the Moving Epidemics Method (MEM) and climate data to optimize vector control strategies. by Ayrton Sena Gouveia, Marcelo Ferreira da Costa Gomes, Iasmim Ferreira de Almeida, Raquel Martins Lana, Leonardo Soares Bastos, Lucas Monteiro Bianchi, Sara de Souza Oliveira, Eduardo Correa Araujo, Danielle Andreza da Cruz Ferreira, Dalila Machado Botelho Oliveira, Vinicius Barbosa Godinho, Luã Bida Vacaro, Thais Irene Souza Riback, Oswaldo Gonçalves Cruz, Flávio Codeço Coelho, Cláudia Torres Codeço

“…This study aimed to characterize Brazilian territory based on epidemiological and climate data to determine the optimal time to guide preventive and control strategies. …”
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Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models by Xingyu Zhang, Yanshan Wang, Yun Jiang, Charissa B. Pacella, Wenbin Zhang

“…Four machine learning models—Logistic Regression, Random Forest, Gradient Boosting, and Extreme Gradient Boosting—were applied to three data configurations: structured data only, unstructured data only, and combined data. …”
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Integrating UAV LiDAR and multispectral data to assess forest status and map disturbance severity in a West African forest patch by Chima J. Iheaturu, Samuel Hepner, Jonathan L. Batchelor, Georges A. Agonvonon, Felicia O. Akinyemi, Vladimir R. Wingate, Chinwe Ifejika Speranza

“…The integration of UAV LiDAR and multispectral data demonstrated here has potential for application across diverse tropical forest patches, providing an effective means to monitor forest health, assess disturbance severity, and support data-driven decision-making in forest conservation and sustainable management.…”
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BO-CNN-BiLSTM deep learning model integrating multisource remote sensing data for improving winter wheat yield estimation by Lei Zhang, Changchun Li, Xifang Wu, Hengmao Xiang, Yinghua Jiao, Huabin Chai

“…Furthermore, the BCBL model exhibited strong stability and generalization across different climatic conditions.ConclusionThus, the BCBL model combined with SIF data can offer reliable winter wheat yield estimates, hold significant potential for application, and provide valuable insights for agricultural policymaking and field management.…”
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Model Analisis Aktivitas Tutor Dalam Learning Management System Berdasarkan Data Log Menggunakan K-Means Dan Deteksi Outlier by Agusriandi Agusriandi, Elihami Elihami, Irman Syarif, Ita Sarmita Samad

“…Therefore, this study aims to (1) describe and monitor the weak performance of tutors in the LMS application based on log data, (2) detect tutors who are included in the outlier category based on the activities in the LMS. …”
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Development of a Predictive Model for Metabolic Syndrome Using Noninvasive Data and its Cardiovascular Disease Risk Assessments: Multicohort Validation Study by Jin-Hyun Park, Inyong Jeong, Gang-Jee Ko, Seogsong Jeong, Hwamin Lee

“…ObjectiveThis study aimed to develop and validate a predictive model for metabolic syndrome using noninvasive body composition data. Additionally, we evaluated the model’s ability to predict long-term CVD risk, supporting its application in clinical and public health settings for early intervention and preventive strategies. …”
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