Location-Dependent Query Processing: Semantic Cache for Real-Time Smart City Analytics by Rabia Hasan, Waseem Shehzad, Ejaz Ahmed, Hasan Ali Khattak, Ahmed S. AlGhamdi, Sultan S. Alshamrani

“…In this paper, our novel approach comprise of usage of semantic caches with the Bayesian networks using a prediction algorithm. Our approach is unique and distinct from the traditional query processing system especially in mobile domain for the prediction of future locations of users. …”
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Profiling public perception of emerging technologies: Gene editing, brain chips and exoskeletons. A data-analytics framework by Simona-Vasilica Oprea, Adela Bâra

“…It consists of about 100 questions that are grouped using a prefix code by the 3 above-mentioned human enhancement, science role, concerns and excitements, perceived algorithm fairness and demographics. To investigate this survey and extract insights regarding the general attitude, a data analytics framework is proposed that consists of clustering using DBSCAN and K-means, ANOVA for clusters, PCA, t-SNE and UMAP for graphical visualization, prediction and advanced customers’ profiles analyses. …”
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CNN-GRU Battery SOC Estimation Method Fused with Attention Mechanism for Electric Multiple Units by WANG Shenghui, TIAN Qin, LIU Lihao, FENG Enlai, YU Tianjian

“…To precisely estimate the SOC of small-sample battery cycling data, this paper transforms the continuous regression model into a classification problem, discretizes the battery SOC ranges, and converts the final prediction result into discrete SOC values. The experimental results show that compared with the CNN-GRU algorithm, the proposed approach improves three key metrics — root mean square error, mean absolute error, and mean relative error by 18.90%, 17.92% and 19.78%, respectively, demonstrating impressive prediction accuracy and stability.…”
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Pemodelan Sistem Monitoring Kualitas Udara Pintar Berbasis Internet of Things dengan Pendekatan Machine Learning by Eddy Prasetyo Nugroho, Ani Anisyah, Deva Shofa Al Fathin, Muhammad Nur Yasin Amadudin, Muhammad Satria Ramadhani, Yosafat

“…The combination of the real-time sensor and the LSTM algorithm resulted in an air quality prediction accuracy rate of 88%. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…The samples were divided into two major categories of felsic rocks and mafic rocks using the kNN algorithm, and then six categories were formed by the SVM algorithm. …”
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Characterization of Cuproptosis-Related LncRNAs Prognostic Signature and Identification of LINC02285 as a Novel Biomarker for Ovarian Cancer by Lei H, Zhou Z, Liu C, Chen W, Li Y, Shu G, Wang M, Guo K, Pan Q, Yin G

“…ROC curve analysis further validated the predictive capacity of the signature. Additionally, the low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. …”
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Early Detection of Soil Salinization by Means of Spaceborne Hyperspectral Imagery by Giacomo Lazzeri, Robert Milewski, Saskia Foerster, Sandro Moretti, Sabine Chabrillat

“…The results highlight that the EnMAP-derived dataset produces similar results to those of ASD laboratory spectra, providing evidences regarding EnMAP’s predictive capability to detect early stages of topsoil salinization.…”
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Root-Zone Salinity in Irrigated Arid Farmland: Revealing Driving Mechanisms of Dynamic Changes in China’s Manas River Basin over 20 Years by Guang Yang, Xuejin Qiao, Qiang Zuo, Jianchu Shi, Xun Wu, Alon Ben-Gal

“…The approach demonstrated high predictive accuracy (<i>R</i>² = 0.96 ± 0.01, root mean squared error <i>RMSE</i> = 0.19 ± 0.03 g kg⁻¹, maximum absolute error <i>MAE</i> = 0.14 ± 0.02 g kg⁻¹) in evaluating <i>SSC</i> drivers. …”
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Research on Data-Driven Performance Assessment and Fault Early Warning of Marine Diesel Engine by Haiyan Wang, Zihan Wang, Biao Shi

“…To enable proactive prediction of marine diesel engine failure time and root causes, thereby reserving sufficient time for maintenance, this study proposes a data-driven multi-algorithm integration framework for performance assessment and fault early warning in marine diesel engines. …”
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OBJECT DETECTION IN COMPUTER VISION SYSTEMS: A VISUAL SALIENCY BASED APPROACH by V. A. Kachurka, K. .. Madani, C. .. Sabourin, V. A. Golovko, P. A. Kachurka

“…Experimental results show viability and efficiency of this approach as compared with state-of-art algorithms, and predict its usability on the broader class of tasks - applied variations of eye fixation problem.…”
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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…The ensemble classifier was designed to predict the presence of TB by fusing DCNNs from the winning combination via weighted averaging. …”
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Genome-wide association between branch point properties and alternative splicing. by André Corvelo, Martina Hallegger, Christopher W J Smith, Eduardo Eyras

“…Using a Support Vector Machine algorithm, we created a model complemented with polypyrimidine tract features, which considerably improves the prediction accuracy over previously published methods. …”
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Big data and data science in global governance: anticipating future needs and applications in the UN and beyond by Lanxin Li, Jiarou Wang, Xi Wang, Peng Peng, Jiaying Shen, Haining Zhu, Ziyang Zhang

“…The research identifies the “4Vs” of big data (Volume, Velocity, Variety, and Veracity) as fundamental characteristics reshaping governance approaches while highlighting innovative applications like UN Global Pulse, SDG tracking systems, and AI-driven predictive analytics in crisis prevention. We assess technical, ethical, and organizational challenges, including data quality inconsistencies, interoperability issues, privacy concerns, algorithmic bias, and resource constraints that impede the full integration of big data into governance systems. …”
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Construction of a prognostic model based on memory CD4+ T cell–associated genes for lung adenocarcinoma and its applications in immunotherapy by Yong Li, Xiangli Ye, Huiqin Huang, Rongxiang Cao, Feijian Huang, Limin Chen

“…The constructed nomogram results demonstrated that the predictive performance of the nomogram was superior to the prognostic model and outperformed individual clinical factors. …”
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From data to nutrition: the impact of computing infrastructure and artificial intelligence by Pierpaolo Di Bitonto, Michele Magarelli, Pierfrancesco Novielli, Donato Romano, Domenico Diacono, Lorenzo de Trizio, Angelo Mariano, Claudia Zoani, Riccardo Ferrero, Alessandra Manzin, Maria De Angelis, Roberto Bellotti, Sabina Tangaro

“…This article explores the significant impact that artificial intelligence (AI) could have on food safety and nutrition, with a specific focus on the use of machine learning and neural networks for disease risk prediction, diet personalization, and food product development. …”
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The diagnostic performance evaluation of the SD BIOLINE HIV/syphilis Duo rapid test in southern Ethiopia: a cross-sectional study by Techalew Shimelis, Endale Tadesse

“…Syphilis serostatus was determined using the Treponema pallidum haemagglutination assay (TPHA).Results The respective sensitivity, specificity, positive predictive value and negative predictive value of the SD BIOLINE HIV/syphilis Duo test were 100, 99.5, 99.5 and 100% for HIV and 97.6, 96, 95.4 and 98% for syphilis testing, respectively. …”
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P-68 LIVGUARD, A DEEP NEURAL NETWORK FOR CIRRHOSIS DETECTION IN LIVER ULTRASOUND (USD) IMAGES by DIEGO ARUFE, Pablo Gomez del Campo, Ezequiel Demirdjian, Carlos Galmarini

“…Sensitivity, specificity, positive (P) and negative (N) predictive values (PV) were 88.8%, 88.5%, 85.5% and 92.2%, respectively. …”
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Innovative Dombi Aggregation Operators in Linguistic Intuitionistic Fuzzy Environments for Optimizing Telecommunication Networks by Dilshad Alghazzawi, Misbah Hayat, Ghaliah Alhamzi, Abdul Wakil Baidar

“…These technologies utilize live and predictive network data to advance the network to its full potential, proactively resolving performance issues prior to the impact on subscribers. …”
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People counting using IR-UWB radar sensors and machine learning techniques by Ange Joel Nounga Njanda, Jocelyn Edinio Zacko Gbadoubissa, Emanuel Radoi, Ado Adamou Abba Ari, Roua Youssef, Aminou Halidou

“…Next, we create features based on statistical and entropic properties of the signal and apply several classification algorithms, including ANN, Random Forest, KNN, XGBOOST, and multiple linear regression, to predict the number of people present. …”
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A multi‐objective feature optimization strategy for developing high‐entropy alloys with optimal strength and ductility by Yan Zhang, Shewei Xin, Wei Zhou, Xiao Wang, Yangyang Xu, Yanjing Su

“…Here, we propose a multi‐objective feature optimization strategy that identifies feature subsets to improve both prediction accuracy and active learning efficiency for iterative experimentation. …”
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