Agricultural Drought Monitoring Using Climatic, Vegetation and Soil Moisture Data in Hormozgan Province by Mohsen Nouro Pourdargazi, Ommolbanin Bazrafshan, Yahya Esmaelpour

“…For this purpose, soil moisture data at a depth of 0-10 cm was calculated from GLDAS satellite images and standardized soil moisture drought index (SMDI) and standardized normalized difference vegetation index (SNDVI) were used to calculate changes in vegetation cover. …”
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Characterization of within-host Plasmodium falciparum diversity using next-generation sequence data. by Sarah Auburn, Susana Campino, Olivo Miotto, Abdoulaye A Djimde, Issaka Zongo, Magnus Manske, Gareth Maslen, Valentina Mangano, Daniel Alcock, Bronwyn MacInnis, Kirk A Rockett, Taane G Clark, Ogobara K Doumbo, Jean Bosco Ouédraogo, Dominic P Kwiatkowski

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Predictive interpretable analytics models for forecasting healthcare costs using open healthcare data by A. Ravishankar Rao, Raunak Jain, Mrityunjai Singh, Rahul Garg

“…We demonstrate our approach by creating predictive models using recent machine learning techniques. We analyzed anonymous patient data from the New York State Statewide Planning and Research Cooperative System, consisting of 2.34 million records from 2019. …”
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Porosity prediction of tight reservoir rock using well logging data and machine learning by Yawen He, Hongjun Zhang, Zhiyu Wu, Hongbo Zhang, Xin Zhang, Xiaojing Zhuo, Xiaoli Song, Sha Dai, Wei Dang

“…To address these issues, we apply advanced machine learning algorithms—gradient boosting decision tree (GBDT), random forest, XGBoost, and multilayer perceptron—using well logging data, including acoustic time (AC), well logging (CAL), compensating neutrons (CNL), density (DEN), natural gamma (GR), resistivity (RT), and spontaneous potential (SP). …”
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Differences in the Management and Use of Health Services in Australia Using Publicly Available Data: Comparisons between New South Wales and Victoria by Jo M Martins, Godfrey Isouard

“…Design: The study uses data from the Australian Bureau of Statistics (ABS) and the Australian Institute of Health and Welfare (AIHW), focusing on the 2021 census. …”
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A comparative study of forecasting methods using real-life econometric series data by Cláudia Eliane da Matta, Natália Maria Puggina Bianchesi, Milena Silva de Oliveira, Pedro Paulo Balestrassi, Fabiano Leal

“…Research method Two real-life data sets were used to evaluate the forecasting methods proposed in this paper. …”
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An indoor IoT-based LiFi system using LEDs for sensor data transfer by Mostafa A.R. Eltokhy, Mohamed Abdel-Hady, Ayman Haggag, Hisham A. Hamad, Tarek Hosny, Ahmed A. F. Youssef, Ali M. El-Rifaie

“…DHT11 sensor is used to measure the environmental conditions and store collected data via Wi-Fi in the cloud server using HTTP protocol. …”
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Continuous and Discrete Similarity Coefficient for Identifying Essential Proteins Using Gene Expression Data by Jiancheng Zhong, Zuohang Qu, Ying Zhong, Chao Tang, Yi Pan

“…In this work, we discretized gene expression data and used the discrete similarities of the gene expression spectrum to eliminate noise fluctuation. …”
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Research on a PTSD Risk Assessment Model Using Multi-Modal Data Fusion by Youxi Luo, Yucui Shang, Dongfeng Zhu, Tian Zhang, Chaozhu Hu

“…For multi-modal data fusion, two sets of solutions are proposed: the first is to extract EEG features using B-spline basis functions, combined with questionnaire data, to construct a multi-modal Zero-Inflated Poisson regression model; the second is to build a multi-modal deep neural network fusion prediction model to automatically extract and fuse multi-modal data features. …”
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Data Driven Classification of Opioid Patients Using Machine Learning–An Investigation by Lisan Al Amin, Md. Saddam Hossain Mukta, Md. Sezan Mahmud Saikat, Md. Ismail Hossain, Md. Adnanul Islam, Mohiuddin Ahmed, Sami Azam

“…We used structured and unstructured data from the MIMIC-III database to identify intentional and unintentional intake of opioid drugs. …”
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Tools for forecasting regional economic growth using big data and business intelligence technologies by Afanasev Kirill, Kalinin Aleksandr

“…The developed tools were tested on data from 76 Russian regions for 2015–2023 using distributed computing systems. …”
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JailbreakTracer: Explainable Detection of Jailbreaking Prompts in LLMs Using Synthetic Data Generation by Md. Faiyaz Abdullah Sayeedi, Maaz Bin Hossain, Md. Kamrul Hassan, Sabrina Afrin, Molla Md. Sabit Hossain, Md. Shohrab Hossain

“…The emergence of Large Language Models (LLMs) has revolutionized natural language processing (NLP), enabling remarkable advancements across various applications. …”
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Wind Turbine Fault Diagnosis with Imbalanced SCADA Data Using Generative Adversarial Networks by Hong Wang, Taikun Li, Mingyang Xie, Wenfang Tian, Wei Han

“…Specifically, the long short-term memory network that can handle time series data well is used in the generator network to learn the temporal correlations from SCADA data and thus generate samples with temporal dependencies. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Firstly, the data are sourced from the HIPAA database, encompassing various data types, such as medical records, patient personal information, and treatment costs. …”
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Modeling GIC in the Southern South Island of Aotearoa New Zealand Using Magnetotelluric Data by K. M. Pratscher, M. Ingham, D. H. Mac Manus, M. Kruglyakov, W. Heise, C. J. Rodger, T. Divett, E. Bertrand, M. Dalzell, J. Brundell

“…This study compares modeled and measured GIC using specifically measured MT impedance data.…”
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Predicting the infecting dengue serotype from antibody titre data using machine learning. by Bethan Cracknell Daniels, Darunee Buddhari, Taweewun Hunsawong, Sopon Iamsirithaworn, Aaron R Farmer, Derek A T Cummings, Kathryn B Anderson, Ilaria Dorigatti

“…We applied four machine learning classifiers and multinomial logistic regression to the titre data to predict the infecting serotype. The models were validated against the true infecting serotype, identified using RT-PCR. …”
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Systematic assessment of COVID-19 host genetics using whole genome sequencing data. by Axel Schmidt, Nicolas Casadei, Fabian Brand, German Demidov, Elaheh Vojgani, Ayda Abolhassani, Rana Aldisi, Guillaume Butler-Laporte, DeCOI host genetics group, T Madhusankha Alawathurage, Max Augustin, Robert Bals, Carla Bellinghausen, Marc Moritz Berger, Michael Bitzer, Christian Bode, Jannik Boos, Thorsten Brenner, Oliver A Cornely, Thomas Eggermann, Johanna Erber, Torsten Feldt, Christian Fuchsberger, Julien Gagneur, Siri Göpel, Tobias Haack, Helene Häberle, Frank Hanses, Julia Heggemann, Ute Hehr, Johannes C Hellmuth, Christian Herr, Anke Hinney, Per Hoffmann, Thomas Illig, Björn-Erik Ole Jensen, Verena Keitel, Sarah Kim-Hellmuth, Philipp Koehler, Ingo Kurth, Anna-Lisa Lanz, Eicke Latz, Clara Lehmann, Tom Luedde, Carlo Maj, Michael Mian, Abigail Miller, Maximilian Muenchhoff, Isabell Pink, Ulrike Protzer, Hana Rohn, Jan Rybniker, Federica Scaggiante, Anna Schaffeldt, Clemens Scherer, Maximilian Schieck, Susanne V Schmidt, Philipp Schommers, Christoph D Spinner, Maria J G T Vehreschild, Thirumalaisamy P Velavan, Sonja Volland, Sibylle Wilfling, Christof Winter, J Brent Richards, DeCOI, André Heimbach, Kerstin Becker, Stephan Ossowski, Joachim L Schultze, Peter Nürnberg, Markus M Nöthen, Susanne Motameny, Michael Nothnagel, Olaf Riess, Eva C Schulte, Kerstin U Ludwig

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The use of big data on the labor market in HR business processes of organizations in the Republic of Belarus by Alena V. Vankevich, Iryna N. Kalinouskaya

“…The study was conducted within the framework of the research work “Theoretical approaches and methodological support for the analysis of the labor market in the Republic of Belarus using big data” with the financial support of the Belarusian Foundation for Basic Research under the agreement G24-013.…”
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Deep learning model using continuous skin temperature data predicts labor onset by Chinmai Basavaraj, Azure D. Grant, Shravan G. Aras, Elise N. Erickson

“…Methods We evaluated patterns in continuous skin temperature data in 91 (n = 54 spontaneous labors) pregnant women using a wearable smart ring. …”
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A framework for conducting GWAS using repeated measures data with an application to childhood BMI by Kimberley Burrows, Anni Heiskala, Jonathan P. Bradfield, Zhanna Balkhiyarova, Lijiao Ning, Mathilde Boissel, Yee-Ming Chan, Philippe Froguel, Amelie Bonnefond, Hakon Hakonarson, Alexessander Couto Alves, Deborah A. Lawlor, Marika Kaakinen, Marjo-Riitta Järvelin, Struan F. A. Grant, Kate Tilling, Inga Prokopenko, Sylvain Sebert, Mickaël Canouil, Nicole M. Warrington

“…We propose a framework that enables data quality control, implements mixed models to evaluate trajectories of change in traits, and estimates phenotypes to identify age-varying genetic effects in GWAS. …”
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