Advanced Operator Theory for Energy Market Trading: A New Framework by Michele Bufalo, Viviana Fanelli

“…Furthermore, we apply these findings to energy market trading by developing specialized simulation algorithms and forecasting models. These methodologies were tested across all assets comprising the S&P 500 Energy Index, evaluating their predictive accuracy and effectiveness in capturing market dynamics. …”
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Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints by Zhen Zhang, Yifan Luo, Yaohong Qu

“…The distributed virtual controller is based on distributed model predictive control with synchronous update strategy, where the virtual control signals are derived by the optimization simultaneously at each time step for each HGV under directed communication topology. …”
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Enhancing Autonomous Vehicle Safety with Blockchain Technology: Securing Vehicle Communication and AI Systems by Stefan Iordache, Catalina Camelia Patilea, Ciprian Paduraru

“…By integrating blockchain with AI-based predictive algorithms, this approach aims to secure vehicle peer-to-peer communication, reduce traffic congestion, and improve safety for drivers and pedestrians. …”
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Audit Program on Artificial Intelligence (AI)-driven Credit Risk Models by Valeria Anna De Palma, Alessandro Di Maria, Daniele Foschini, Vincenzo Frasca, Dario Girardi

“…While AI enhances predictive performance and accuracy, its inherent lack of transparency and explainability increases the risk of control deficiencies, potentially leading to financial losses, misrepresentation of information, unfair discrimination against debtors, and non compliance with EU regulations. …”
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Identification of Haptic Based Guiding Using Hard Reins. by Anuradha Ranasinghe, Prokar Dasgupta, Kaspar Althoefer, Thrishantha Nanayakkara

“…Based on experimental identification systems on human demonstrations show that the guider and the follower experience learning for an optimal stable state-dependent novel 3rd and 2nd order auto-regressive predictive and reactive control policies respectively. …”
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Real-time locomotion mode detection in individuals with transfemoral amputation and osseointegration by Bahareh Ahkami, Morten B. Kristoffersen, Max Ortiz-Catalan

“…The method was implemented in LocoD, an existing open-source platform, allowing for further development by the community and allowing easy comparison between different classification algorithms. The evaluation of the platform and prediction algorithm relies on quantifying the transition error, signifying instances where the algorithm falls short in predicting shifts between different walking surfaces. …”
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Development of an Intelligent Method for Target Tracking in Radar Systems at the Initial Stage of Operation Under Intentional Jamming Conditions by Serhii Semenov, Olga Wasiuta, Alla Jammine, Justyna Golec, Magdalena Krupska-Klimczak, Yevhen Tarasenko, Vitalii Voronets, Vitalii Breslavets, Serhii Lvov, Artem Moskalenko

“…The problem lies in the lack of a comprehensive approach to tracking air targets in difficult conditions that is able to dynamically adapt filtering parameters, predict signal reliability, and change the processing mode depending on the level of interference. …”
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Construction and analysis of a prognostic risk scoring model for gastric cancer anoikis-related genes based on LASSO regression by Ai CHEN, Xiaowei CHEN, Yanan WANG, Xiaobing SHEN

“…Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. …”
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METHOD OF IMAGE PROCESSING IN THE PROBLEM OF DETECTING MOVING OBJECTS IN OPTICAL-ELECTRONIC SURVEILLANCE SYSTEMS OF THERMAL IMAGING TYPE by E. I. Mikhnionok

“…Moving objects on the observed scene are subject to investigation, so it is advisable to use algorithms based on background subtraction methods to solve the detection problem. …”
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Meta-Learning Amidst Heterogeneity and Ambiguity by Kyeongryeol Go, Mingyu Kim, Seyoung Yun

“…In this paper, we devise a novel meta-learning framework, called Meta-learning Amidst Heterogeneity and Ambiguity (MAHA), that outperforms previous works in prediction based on its ability to task identification. …”
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Edge of excellence: JEC's Scopus achievement, doors 2025 breakthroughs, and Volume 4 Issue 1 (2025) highlights by Serhiy O. Semerikov, Tetiana A. Vakaliuk

“…The paper examines innovative solutions addressing distributed systems challenges, including IoT-based monitoring systems, intelligent traffic prediction algorithms, and security implementations for resource-constrained environments. …”
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An Integrative Computational Approach for Identifying Cotton Host Plant MicroRNAs with Potential to Abate CLCuKoV-Bur Infection by Muhammad Aleem Ashraf, Imran Shahid, Judith K. Brown, Naitong Yu

“…Using this suite of robust algorithms, the predicted repertoire of the cotton microRNA-binding landscape was determined for a CLCuKoV-Bur consensus genome sequence. …”
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Counting workflow satisfiability with exclusion constraints based on backtracking tree-decomposition by Zhinian ZHAI, Weixiang WANG, Yahui LU, Mingwei WU, Zhijun ZHENG, Fahong YU

“…Experiments show that, the proposed optimized algorithm declined in running time, and has well synthetical performance for workflows with low-density constraints compared to the existing #WS（≠）algorithms.…”
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The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis by Gujun Cong, Jingjing Shao, Feng Xiao, Haixia Zhu, Peipei Kang

“…Diagnostic models developed using various machine learning techniques demonstrated the significant predictive capability of these 12 genes in the diagnosis of prostate cancer. …”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…Combining this with the prior yields an accurate prediction for the posterior, measured for DNNs trained with stochastic gradient descent. …”
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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

“…New hydrological insight for the region: Eight AI algorithms (KNN, SVR, RF, ET, Bag, AdaBt, GRB, and CAT) and stacking ensemble models were developed to predict the δ¹ ⁸O and δ²H isotopes of the groundwater using a dataset of physicochemical parameters, ions and elements, and isotopes from 47 wells. …”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The study evaluated two image-deep-learning algorithms’ effectiveness in predicting pregnancy within one year, using AUCs and decision curve analysis. …”
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AI-Driven Advancements in Bioinformatics: Transforming Healthcare and Science by Sunil Namdev Thitame, Ashwini Ashok Aher

“…This review evaluates the fundamental AI enabled bioinformatics approaches with their deployment for genomic and protein structure prediction and drug discovery algorithms and diagnostic solutions. …”
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A Comparison of AutoML Hyperparameter Optimization Tools For Tabular Data by Prativa Pokhrel, Alina Lazar

“…Therefore, finding the optimal values of these hyperparameters is integral in improving the prediction accuracy of an ML algorithm and the model selection. …”
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A multi-chroma format cascaded coding method for full-chroma image in AVS2 by Liping ZHAO, Tao LIN, Kailun ZHOU, Keli HU, Chunmei LIN

“…In the second generation of audio video coding standard (AVS2),a multi-chroma format cascaded coding method (MCFCC) for full-chroma (4:4:4 sampling format) images coding was proposed.The MCFCC algorithm firstly converts the 4:4:4 sampling format image into 4:2:0 sampling format image,then the 4:2:0 sampling format image was processed by 4:2:0 sampling format intra prediction,transform,quantization,inverse quantization,inverse transform,entropy coding and a weighted 4:4:4 sampling format distortion calculation method in the rate-distortion optimization process,finally 4:4:4 sampling format in-loop filtering and offset algorithms were applied to the 4:4:4 sampling format image after up sampling.The experimental results show that,for full-chroma natural images,the MCFCC algorithm achieves higher coding efficiency at very low additional encoding complexity and very low additional design and implementation cost.…”
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