A fast calculation approach for thermal distribution of aircraft piston pumps based on finite difference method by Jiming MA, Haolun NING

“…Compared with conventional finite element approaches, the proposed method reduces the simulation duration to approximately 10 % of that required by traditional algorithms under identical operational conditions.The developed methodology enables efficient and accurate simulation of critical heat generation mechanisms in piston pumps, including frictional heating and fluid leakage phenomena, while simultaneously providing comprehensive temperature distributions across pump components. …”
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Overcoming barriers and ethical challenges in implementing intelligent tutoring systems in Ghanaian higher education by Moses Kumi Asamoah, Jessica Amarteifio

“…In addition, the study highlights several ethical concerns, including ensuring equitable access to ITS, addressing algorithmic biases, and preserving academic integrity. …”
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ESTIMATION OF SATELLITE ALTIMETER ECHO-SIGNAL PARAMETERS BY STATISTICAL FITTING METHODS IN THE COURSE OF RETRACKING by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…The results obtained are compared to the potential attainable and show that while LS fitting yields noticeably to the potential, experimental accuracy of ML-fitting practically coincides with the potential one.…”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…Efficient supply chain management (SCM) is essential for enterprises seeking to enhance operational efficiency, reduce costs, and mitigate risks while ensuring product quality and customer satisfaction. …”
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Dry sliding tribological characteristics evaluation and prediction of TiB2-CDA/Al6061 hybrid composites exercising machine learning methods by Amit Aherwar, Anamika Ahirwar, Vimal Kumar Pathak

“…The models were trained and validated using experimental data, demonstrating the efficacy of machine learning in accurately predicting tribological performance while minimizing extensive experimental trials. Among the models, GPR exhibited the highest predictive accuracy, surpassing other algorithms in forecasting wear behaviour.…”
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Robust multisynchrosqueezing transform time frequency technologies with application to fault diagnosis by Haibin Wang, Junbo Long, Changshou Deng, Youxue Zhou

“…They effectively mitigate the interference of strong impulsive noise while maintaining high time–frequency concentration. …”
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High-Radix Taylor-Optimized Tone Mapping Processor for Adaptive 4K HDR Video at 30 FPS by Xianglong Wang, Zhiyong Lai, Lei Chen, Fengwei An

“…However, real-time processing of HDR content remains challenging due to the computational complexity of tone mapping algorithms and the inherent limitations of Low Dynamic Range (LDR) capture systems. …”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…This paper focuses on forecasting models using T-SFIS, GBMBoost, and Decision Tree, combined with metaheuristic algorithms (GWO, QPSO) in hybrid and ensemble frameworks. …”
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A multi-modality ground-to-air cross-view pose estimation dataset for field robots by Xia Yuan, Kaiyang Wang, Riyu Qin, Jiachen Xu

“…Abstract High-precision localization is critical for intelligent robotics in autonomous driving, smart agriculture, and military operations. While Global Navigation Satellite System (GNSS) provides global positioning, its reliability deteriorates severely in signal degraded environments like urban canyons. …”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…Additionally, advanced signal processing algorithms are necessary for accurately determining the location and nature of detected events. …”
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Performance Evaluation of Triple Play Services Delivery with E2E QoS Provisioning by Nikolaos Zotos, Evangelos Pallis, Anastasios Kourtis

“…The evaluation will prove that this combination made feasible the E2E QoS provisioning while keeping the initial constrains as well as the services delivered over a wireless network.…”
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Privacy, ethics, transparency, and accountability in AI systems for wearable devices by Petar Radanliev, Petar Radanliev

“…However, the fast advancement of these technologies has raised critical ethical and regulatory concerns, particularly around data privacy, algorithmic bias, informed consent, and the opacity of automated decision-making. …”
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More than a chatbot: a practical framework to harness artificial intelligence across key components to boost digital therapeutics quality by Amit Baumel

“…This framework provides a structured method to integrate AI-driven improvements, while also enabling to focus on a specific component during the optimization process.…”
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Machine learning evidence towards eradication of malaria burden: A scoping review by Idara JAMES, Veronica OSUBOR

“…In conclusion, there is a clear need to utilize machine learning algorithms through real-time data collection, model development, and deployment for evidence-based recommendations in effective malaria control and diagnosis. …”
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Explaining distortions in metacognition with an attractor network model of decision uncertainty. by Nadim A A Atiya, Quentin J M Huys, Raymond J Dolan, Stephen M Fleming

“…One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. …”
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Increasing the noise immunity of radio receiving paths with automatic sensitivity control by Р. V. Zayats, I. Y. Malevich

“…Studies of various possible ASC structures have shown that with a proportional exchange of the transmission coefficient for the DR, an improvement in the noise immunity of the RRP is provided while maintaining a high sensitivity of the system. …”
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Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI by Elie Neghawi, Yan Liu

“…By unifying and standardizing computational models and algorithms, UMAC ensures adaptability across different data types and computational environments while incorporating state-of-the-art methodologies. …”
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Towards a new Contextualized Annotation Schema for Unacceptable and Extreme Speech (CUES) to Unleash Generalization Capability of ML models by Dimitra Niaouri, Michele Linardi, Julien Longhi

“…Through our approach, we highlight the significance of context in enhancing the effectiveness of ML algorithms for detecting extreme online content.…”
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CTSS in the tumor microenvironment links immune escape and immunotherapy sensitivity in kidney renal clear cell carcinoma by Hanjing Zhou, Jun Ying, Xuchun Xu, Jian Huang

“…Employing advanced machine learning (ML) algorithms, we identified Cathepsin S (CTSS) as the most pivotal tumor suppressor, with elevated CTSS expression consistently predicting improved survival across multiple independent cohorts. …”
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DEEP LEARNING-BASED SUPER-RESOLUTION TECHNIQUES: A COMPARATIVE ANALYSIS WITH RECENT INSIGHTS by Renuka Sambhaji Sindge, Maitreyee Dutta, Jagriti Saini

“…Furthermore, this paper presents future directions for future researchers to follow SR trends with potential DL-based algorithms.…”
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