Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
Get full text

An Integrated Strategy for Interpretable Fault Diagnosis of UAV EHA DC Drive Circuits Under Early Fault and Imbalanced Data Conditions by Yang Li, Zhen Jia, Jie Liu, Kai Wang, Peng Zhao, Xin Liu, Zhenbao Liu

“…This process effectively saves computational resources while significantly reducing the risk of overfitting. …”
Get full text

Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
Get full text

Prediction of Temperature Distribution on an Aircraft Hot-Air Anti-Icing Surface by ROM and Neural Networks by Ziying Chu, Ji Geng, Qian Yang, Xian Yi, Wei Dong

“…The proposed models not only provide faster predictions of anti-icing surface temperature distributions than traditional numerical simulation methods but also ensure acceptable accuracy, which supports the design of aircraft hot-air anti-icing systems based on optimization methods such as genetic algorithms.…”
Get full text

Towards Economic Sustainability: A Comprehensive Review of Artificial Intelligence and Machine Learning Techniques in Improving the Accuracy of Stock Market Movements by Atoosa Rezaei, Iheb Abdellatif, Amjad Umar

“…Accurately predicting stock market movements remains a critical challenge in finance, driven by the increasing role of algorithmic trading and the centrality of financial markets in economic sustainability. …”
Get full text

Integrating Bayesian Knowledge Tracing and Human Plausible Reasoning in an Adaptive Augmented Reality System for Spatial Skill Development by Christos Papakostas, Christos Troussas, Akrivi Krouska, Cleo Sgouropoulou

“…The use of advanced adaptive algorithms in Augmented Reality (AR) systems works to advance spatial skills with valuable relevance in many professional spheres by providing personalized feedback in an immersive environment. …”
Get full text

The Use of AI in Elementary School Learning: A Systematic Literature Review by Natalina Purba, Desti Pujiati, Partohap Saut Raja Sihombing, Hendra Simanjuntak, Desi Sijabat

“…The study concludes that while AI holds great potential to transform primary education, its successful implementation depends on overcoming these barriers and fostering a culture of innovation within schools. …”
Get full text

Advancing TinyML in IoT: A Holistic System-Level Perspective for Resource-Constrained AI by Leandro Antonio Pazmiño Ortiz, Ivonne Fernanda Maldonado Soliz, Vanessa Katherine Guevara Balarezo

“…We highlight both established and emergent techniques for optimizing resource usage while addressing security, privacy, and ethical concerns. …”
Get full text

Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…Traditional machine learning algorithms perform quite well in general, with SVM giving a best accuracy of around 95% with academic data, while training and testing the model without academic data still gives a good performance of 93%. …”
Get full text

Smart Charging and V2G: Enhancing a Hybrid Energy Storage System with Intelligent and Bidirectional EV Charging by Thomas Franzelin, Sarah Schwarz, Stephan Rinderknecht

“…This environment facilitates comprehensive investigations into EV behavior, charging strategies, control algorithms, and user interactions. It provides a platform for exploring the possibilities, limitations, and optimal use cases for smart charging and hybrid storage systems in practice.…”
Get full text

Battery Management System for Solar Power Plants in Uganda: An IoT-Driven Approach by Ssembalirwa, Denis, Cartland, Richard, Bature, U. I., Kitone, Isaac

“…Intelligent algorithms autonomously regulate charging and discharging cycles to prevent overcharging and deep discharge, optimizing battery performance. …”
Get full text

Urban Air Mobility Vertiport’s Capacity Simulation and Analysis by Antoni Kopyt, Sebastian Dylicki

“…The framework integrates dynamic grid-based spatial management, probabilistic mission duration algorithms, and EASA-compliant operational protocols to address the infrastructural and logistical demands of high-density UAS operations. …”
Get full text

Compact embedded RF sawtooth waveform generator for particle accelerator applications by Ashish Sharma, Subrat Kar, Bhuban Kumar Sahu

“…This paper elaborates on the construction of this instrument, including the design and implementation of multiple feedback controls and complex signal processing algorithms to generate a stable sawtooth waveform. The entire design is space and resource-optimized to be hosted on a single system-on-chip field programmable gate array board, which helped reduce the development effort. …”
Get full text

Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
Get full text

Data-driven decoding of quantum error correcting codes using graph neural networks by Moritz Lange, Pontus Havström, Basudha Srivastava, Isak Bengtsson, Valdemar Bergentall, Karl Hammar, Olivia Heuts, Evert van Nieuwenburg, Mats Granath

“…Accurate, maximum likelihood, decoders are computationally very expensive whereas decoders based on more efficient algorithms give sub-optimal performance. In addition, the accuracy will depend on the quality of models and estimates of error rates for idling qubits, gates, measurements, and resets, and will typically assume symmetric error channels. …”
Get full text

Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…However, implementing accurate and automated object detection algorithms mitigates these challenges, allowing errors or defects to be detected before processing. …”
Get full text

Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…When rolling pins are machining with CNC equipment, a sensor system is installed to collect acoustic data, analyze failure patterns, and apply RUL prediction algorithms. The AI-based predictive maintenance system developed ensures the reliability and operational efficiency of CNC equipment, while also laying the foundation for a smart factory monitoring platform, thus enhancing competitiveness in intelligent manufacturing environments.…”
Get full text

The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…The conclusions from the conducted analyses confirmed that an appropriate strategy of orbital manoeuvres may greatly improve the operational efficiency of the nanosatellite, while, at the same time, continuing to save fuel and energy. …”
Get full text

Leveraging machine learning to predict residential location choice: A comparative analysis by Vahid Noferesti, Hamid Mirzahossein

“…Understanding these decisions is essential for effective urban planning. While discrete choice models have been used to predict residential locations, their limitations in handling complex datasets have hindered their accuracy. …”
Get full text

AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…This commentary aims to clarify how AI is improving the identification of novel biomarkers for optimal early diagnosis, focused treatment, and improved clinical outcomes, while also addressing certain obstacles and ethical issues related to the application of artificial intelligence in oncology. …”
Get full text