Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics by Syeda Faiza Nasim, Umm-e-Kulsoom, Syeda Alishba Fatima, Salka Naushad

“…The research highlights the significance of data-driven decision-making for event planners, as it empowers them to execute efficient backup plans The main objective of this research is to improve the sports environment for both players and spectators while tackling the urgent problems caused by climate variability. …”
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Multiverse Analysis for Dynamic Network Models: Investigating the Influence of Plausible Alternative Modeling Choices by Björn S. Siepe, Daniel W. Heck

“…However, researchers typically perform and report only a single, preferred analysis while ignoring alternatives that could yield different conclusions. …”
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Adaptively Implicit Advection for Atmospheric Flows by Hilary Weller, Christian Kühnlein, Piotr K. Smolarkiewicz

“…This adaptively implicit advection scheme facilitates efficient and robust integrations with long time‐steps while having negligible impact on the overall accuracy, and achieving monotonicity and local conservation on general meshes. …”
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Enabling disaggregation of Asian American subgroups: a dataset of Wikidata names for disparity estimation by Qiwei Lin, Derek Ouyang, Cameron Guage, Isabel O. Gallegos, Jacob Goldin, Daniel E. Ho

“…Recent U.S. federal regulations have required increasingly disaggregated race reporting, but major implementation barriers mean that, in practice, reported race data continues to remain inadequate. While imputation methods have enabled disparity assessments in many research and policy settings lacking reported race, the leading name algorithms cannot recover disaggregated categories, given the same lack of disaggregated data from administrative sources to inform algorithm design. …”
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An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…The model integrates the Gaussian mutation and shrink mechanism-based moth flame optimization (GMSMFO) algorithm with an extreme learning machine (ELM). GMSMFO enhances population diversity and avoids local optima through Gaussian mutation (GM), while the shrink mechanism (SM) improves exploration–exploitation balance. …”
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Optimal scheduling of BIES with multi-energy flow coupling based on deep RL by XIA Xuhua, YANG Jiandi, SHI Yongtao

“…Building integrated energy systems （BIESs） can enhance energy efficiency ratio （EER） and reduce carbon emissions while meeting diverse user-side load demands. To further improve the energy dispatch capability of BIES， this paper proposes a low-carbon economic and optimal dispatch method for BIES with multi-energy flow coupling based on deep reinforcement learning （deep RL）. …”
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Demand Forecasting in Data-Scarce and Resource-Restricted Environments by David Gogelein, Marianne von Schwerin, Thomas Walter

“…This approach divides each day into evenly spaced time intervals and various average user demands, while forecasts are made and refined based on on-site data to account for short-term fluctuations. …”
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Comprehensive empirical evaluation of feature extractors in computer vision by Murat ISIK

“…ORB is notably effective on affine-transformed and brightened images, while AKAZE excels in conditions involving blurring, fisheye distortion, image rotation, and perspective distortions. …”
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GPU-Accelerated CNN Inference for Onboard DQN-Based Routing in Dynamic LEO Satellite Networks by Changgeun Yu, Daeyeon Kim, Heoncheol Lee, Myonghun Han

“…This paper addresses the issue of onboard inference for AI-based routing algorithms in dynamic LEO (Low Earth Orbit) satellite networks. …”
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Bayesian linkage analysis of categorical traits for arbitrary pedigree designs. by Abra Brisbin, Myrna M Weissman, Abby J Fyer, Steven P Hamilton, James A Knowles, Carlos D Bustamante, Jason G Mezey

“…LOCate uses a Gibbs sampling approach to assess linkage, incorporating a simulated tempering algorithm for fast mixing. While our treatment is Bayesian, we develop a LOD (log of odds) score estimator for assessing linkage from Gibbs sampling that is highly accurate for simulated data. …”
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RFM Model and K-Means Clustering Analysis of Transit Traveller Profiles: A Case Study by Angela H. L. Chen, Yun-Chia Liang, Wan-Ju Chang, Hsuan-Yuan Siauw, Vanny Minanda

“…Based on big data smart card information, this paper proposes using the RFM and K-means clustering algorithm to analyze and construct mode-switching traveller profiles on MRT and YouBike riders. …”
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Inter-satellite link connection strategy for large-scale low earth orbit satellite networks by YAN Feng, NIE Haojian, XIA Weiwei, SHEN Lianfeng

“…The Grid+ connection strategy, while retaining the Grid connection strategy, allowed satellites to establish cross-satellite connections with satellites in the same orbit or the cross-adjacent orbits. …”
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Efficient RANSAC in 4D Plane Space for Point Cloud Registration by Chang Liu, Chao Liu, Yuming Zhang, Zhongqi Wu, Jianwei Guo

“…3D registration methods based on point-level information struggle in situations with noise, density variation, large-scale points, and small overlaps, while existing primitive-based methods are usually sensitive to tiny errors in the primitive extraction process. …”
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Tent–PSO-Based Unmanned Aerial Vehicle Path Planning for Cooperative Relay Networks in Dynamic User Environments by Shuyue Liu, Wenmao Zhou, Mingwei Qin, Xin Peng

“…The proper planning of UAV paths can improve user coverage while maintaining communication quality. The traditional particle swarm optimization (PSO) algorithm exhibits strong global search capabilities; however, it suffers from challenges such as uneven search coverage owing to the random distribution of the initial particle positions. …”
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Insect Detection Using mm-Waves: Integrated Communication and Biodiversity Sensing Based on Micro-Doppler Effects by Linta Antony, Nicola Marchetti, Ian Donohue, Adam Narbudowicz

“…We use experiments to capture reflected signals from live insects, and introduce a semi-supervised algorithm that automatically detects signal portions exhibiting micro-Doppler effects of wing flapping. …”
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College Student Social Dynamic Analysis and Educational Mechanism Using Big Data Technology by Jing Bai

“…With the advancement of the “big data” technology, college students inadvertently purchase personal advice while taking advantage of the exciting Internet to access information quickly and easily. …”
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Community Clustering and Recommendation Toward Elderly Health Records: Probabilistic Representation Learning and Large Graph Search by Huijiong Ding

“…This approach enables more precise, efficient, and personalized healthcare interventions, wherein the key steps include: 1) Geometry-based feature selection from high-dimensional health data-This effectively reduces dimensionality while preserving discriminative health patterns. 2) Probabilistic multi-topic representations of individual health profiles-These latent space embeddings capture complex health-need interactions. 3) Graph-based community detection via shared clinical/behavioral traits-The algorithm identifies natural clusters with medical relevance. 4) Personalized intervention ranking by community relevance-This ensures tailored care plan recommendations for each subgroup. …”
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Improving Performance of QoS Applications for Wireless Networks by Pingping Dong, Jianxin Wang, Jiawei Huang, Haodong Wang, Yi Pan

“…The problem exacerbates when the traffic asymmetry between the uplink and the downlink is present. While prior research works proposed various mechanisms to alleviate the issue, little was done to specifically address the appropriate parameter setting in a real world network. …”
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A Robust Hybrid MRAPID Controller Design for an Underactuated Nonlinear System With Parametric Uncertainty by Ahmed Abduljabbar Mahmood, Mohamed Abderrahim

“…Optimal performance is achieved through parameter tuning via the social spider optimization (SSO) algorithm, and MIT (Massachusetts Institute of Technology) rule criteria are employed to ensure system stability. …”
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Research on Default Prediction for Credit Card Users Based on XGBoost-LSTM Model by Jing Gao, Wenjun Sun, Xin Sui

“…The accuracy of the XGBoost model depends on the degree of expertise in feature extraction, while the LSTM algorithm can achieve higher accuracy without feature extraction. …”
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