Credit Scoring Prediction Using Deep Learning Models in the Financial Sector by Xi Shi, Dingfen Tang, Yike Yu

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Neural responses to peers moderate conversation-drinking associations in daily life by Mia Jovanova, Ovidia Stanoi, Christin Scholz, Bruce Doré, Danielle Cosme, Yoona Kang, Nicole Cooper, Zachary M. Boyd, Dani S. Bassett, Peter J. Mucha, David M. Lydon-Staley, Kevin N. Ochsner, Emily B. Falk

“…Abstract Conversations shape future behaviors, particularly among young adults. However, young adults vary widely in their susceptibility to peer influence. …”
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Time series analysis of radiant heat using 75 hours VIIRS satellite day and night band nightfire data by Jyoti U. Devkota

“…The behavior of this data is also analyzed in frequency domain by study of period, amplitude and the spectrum.…”
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Use of New Technologies to Determine the Locomotion Energy Expenditure and Livestock Activity Patterns of Free-Grazing Sheep in Mountain Pastures by Virginia Larraz, Olivia Barrantes, Ramón Reiné

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A Case Study in China to Determine Whether GPS Data and Derivative Indicator Can Be Used to Identify Risky Drivers by Rui Fu, Tong Liu, Yuxi Guo, Shiwei Zhang, Wendong Cheng

“…This paper presents an investigation of the relationship between driver risk and factors indicating vehicle’s speed and driver’s acceleration behavior. The main objective is to examine whether GPS data and derivative indicator can be used to identify risky drivers by means of factor analysis. …”
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Key Drivers of Live Streaming Adoption: An Empirical Analysis Using the UTAUT Model by Retno Fuji Oktaviani

“…Both performance expectancy and effort expectancy significantly influence behavioral intention, and behavioral intention, in turn, positively affects the actual use of live streaming. …”
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Abnormality detection of sliding surface and exploration suitable sensor data for condition monitoring by calculating contribution using machine learning by Ryo NAKASHIMA, Tomomi HONDA, Tomohiko KON

“…In this paper, we investigated a method to reduce the opacity of anomaly detection using machine learning and explored sensor data useful for condition monitoring of the sliding surface. …”
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On Predictive Modeling for the Al2O3 Data Using a New Statistical Model and Machine Learning Approach by Mahmoud El-Morshedy, Zahra Almaspoor, Gadde Srinivasa Rao, Muhammad Ilyas, Afrah Al-Bossly

“…The importance of statistical methods in various research fields is modeling the real data and predicting the future behavior of data. …”
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A Study on Using Transfer Learning to Utilize Information From Similar Systems for Data-Driven Condition Diagnosis and Prognosis by Marcel Braig, Peter Zeiler

“…A rolling bearing and a filter degradation data set are used to evaluate the diagnostic and prognostic performance. …”
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Capacity Forecasting of Lithium-Ion Batteries Using Empirical Models: Toward Efficient SOH Estimation with Limited Cycle Data by Kanchana Sivalertporn, Piyawong Poopanya, Teeraphon Phophongviwat

“…Among these, the linear and single-exponential models demonstrated strong performance in early-cycle predictions. It was found that using 30 to 40 cycles of data is sufficient for reliable forecasting within a 100-cycle range, reducing the mean absolute error by over 80% compared to using early-cycle data alone. …”
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Understanding the charactersitics and types of single-person households based on food purchase frequencies in Korea: a cross-sectional study using the 2023 Consumer Behavior Survey... by So-Yun Kim, Youngmin Nam, Jong-Youn Rha, Haerang Lee

“…Data were analyzed using Rao-Scott chi-square tests, ANCOVA, ANOVA, and K-modes hierarchical cluster analysis. …”
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Identifying time patterns in Huntington’s disease trajectories using dynamic time warping-based clustering on multi-modal data by Alexia Giannoula, Audrey E. De Paepe, Ferran Sanz, Laura I. Furlong, Estela Camara

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Reduced order data driven framework for computation of the unsteady lid-driven cavity flow using dynamic mode decomposition by Karim Mazaheri, Mohammad Kazem Moayyedi, Mohammad Hadi Dehghan

“…Validation of CFD computation was assessed, and independence of the DMD modes from the data collection process was investigated. A data set of 400 snapshots of the flow field at three different Reynolds numbers were used to identify the DMD modal structure. …”
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Dynamic AI-Enhanced Therapeutic Framework for Precision Medicine Using Multi-Modal Data and Patient-Centric Reinforcement Learning by R. Gayathri, S. K. B. Sangeetha, R. Sangeetha, G. Leena Rosalind Mary, Sandeep Kumar Mathivanan, Usha Moorthy

“…Here, genomic data integrated with EHR coupled with the metering from wearable devices are combined using an adaptive temporal-fusion mechanism to ensure it is context-aware and timely. …”
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Investigating Catching Hotspots of Fishing Boats: A Framework Using BeiDou Big Data and Deep Learning Algorithms by Fen Wang, Xingyu Liu, Tanxue Chen, Hongxiang Feng, Qin Lin

“…This contribution presents the efficacy of China’s summer fishing moratorium using BeiDou vessel monitoring system (VMS) data from 2805 fishing vessels in the East China Sea and Yellow Sea, integrated with a deep learning framework for spatiotemporal analysis. …”
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Uncovering the Uncertainties and Variability of Travel Time and Fuel Consumption Using Floating Car Data: A Case Study in Wuhan by Wenxin Teng, Fei Liu, Jianbing Yang, Chaoyang Shi, Yunfei Zhang, Fuqiang Wang

“…While previous studies have extensively examined travel time distributions, the joint distributional patterns of fuel consumption remain underexplored, limiting the effectiveness of green routing strategies. A novel data-driven framework, integrating map-matching, second-by-second trajectory interpolation, and microscopic fuel consumption estimation (CMEM), is developed for jointly analyzing the distributions and spatiotemporal variability characteristics of link-level travel time and fuel consumption using floating car data (FCD) in Wuhan, China. …”
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Assessing pedestrian safety at urban signalized intersections across various land use types: insights from a mid-sized Indian city by Dipanjan Mukherjee

“…Abstract Pedestrian fatalities and injuries have emerged as significant concerns in Indian cities, particularly in mid-sized urban areas where obtaining consistent and reliable crash data remains a major challenge. Addressing this gap, the present study proposes and demonstrates a novel approach to proactively evaluate pedestrian safety across varying land use patterns in an Indian mid-sized city. …”
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Multi-layer retrieval of aerosol optical depth in the troposphere using SEVIRI data: a case study of the European continent by M. Pashayi, M. Satari, M. Momeni Shahraki

“…We employed machine learning models – XGBoost (XGB) and random forest (RF) – trained on SEVIRI data from 2017 to 2018 for the estimations. Validation using CALIOP AOD retrievals in 2019 confirmed the reliability of our findings, emphasizing the importance of wind speed (Ws) and wind direction (Wd) in improving AOD estimation accuracy. …”
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Adherence as a predictor of sexual behaviors in people living with HIV/AIDS during the first year of antiretroviral therapy in rural Cameroon: data from Stratall ANRS 12110/ESTHER... by Gilbert Ndziessi, Sylvie Boyer, Charles Kouanfack, Julien Cohen, Fabienne Marcellin, Jean-Paul Moatti, Eric Delaporte, Bruno Spire, Christian Laurent, Maria Patrizia Carrieri, Stratall ANRS 12110/ESTHER Study Group

“…<h4>Methods</h4>Data collection was nested within a longitudinal trial on HIV treatment. …”
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Exploring focal adhesion data: dynamic parameter extraction from FRAP and FLAP experiments using chemical master equation by Luciana Renata de Oliveira, Matheus Gimenez Fernandes, José Salvatore Leister Patane, Jean-Marc Schwartz, José Eduardo Krieger, Christoph Ballestrem, Ayumi Aurea Miyakawa

“…The dynamic behavior of proteins within cellular structures can be studied using fluorescence recovery after photobleaching (FRAP) and fluorescence loss after photobleaching (FLAP) experiments. …”
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