Voltage Control Nonlinearity in QZSDMC Fed PMSM Drive System with Grid Filtering by Przemysław Siwek, Konrad Urbanski

“…To enhance voltage control, a tunable controller with optimized parameters was proposed. The conducted studies demonstrated a 16.5% improvement in the IAE index and faster settling time for Quasi-Z-Source voltage control using the proposed controller compared to the reference controller.…”
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Cross-Scene Multi-Object Tracking for Drones: Leveraging Meta-Learning and Onboard Parameters with the New MIDDTD by Chenghang Wang, Xiaochun Shen, Zhaoxiang Zhang, Chengyang Tao, Yuelei Xu

“…Finally, a novel dataset, termed the Multi-Information Drone Detection and Tracking Dataset (MIDDTD), is introduced, containing rich drone-related information and diverse scenes, thereby providing a solid foundation for the validation of cross-scene multi-object tracking algorithms. Experimental results demonstrate that the proposed method improves the IDF1 tracking metric by 1.92% compared to existing state-of-the-art methods, showcasing strong cross-scene adaptability and offering an effective solution for multi-object tracking from a drone’s perspective, thereby advancing theoretical and technical support for related fields.…”
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A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

“…A five-fold cross-validation procedure was applied to estimate the model's performance and hyperparameter tuning was conducted to optimize classifier efficiency. …”
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The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce by Jiwang Yin, Xiaodong Qiu, Ya Wang

“…It offers valuable insights for e-commerce platforms to continuously optimize personalized recommendation algorithms and boost the click conversion rate of online shopping.…”
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Personal health data protection and intelligent healthcare applications under generative adversarial network by Xiaoyuan Gao, Wei Mi, Xirui Feng

“…Additionally, the model’s accuracy gradually improves as the privacy budget increases. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…Abstract Background Artificial intelligence (AI) has transformed medical education through optimized instruction, competency assessment, and personalized learning. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Finally, BiLSTM is applied for temporal modeling, leveraging its bidirectional recurrent structure to capture both forward and backward dependencies in time series, thereby improving forecasting accuracy. …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…The best performing model achieved 99.42% precision, with ablation studies confirming that feedback learning contributes additional improvements from 0.45% to 4.66% across different OCR architectures.…”
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Solving Linear Programming Problems by Reducing to the Form with an Obvious Answer by Gleb D. Stepanov

“…At the third stage the matrix is transformed into a matrix that provides non-negativity and optimality of the basic solution. For the second stage the analog of which in the simplex method uses an artificial basis and is the most time-consuming, two variants without artificial variables are given. …”
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Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

“…Noisy data is a prevalent issue in data mining, significantly impacting the performance of classification algorithms. Mathematical methods are crucial in tackling this obstacle, particularly in optimizing noise detection and data preprocessing. …”
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AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases by Hajar Nasir Tukur, Olivier Uwishema, Hatice Akbay, Dalal Sheikhah, Inês Filipa Silva Correia

“…Future research should focus on refining AI algorithms, integrating multimodal imaging techniques, and developing predictive biomarkers to optimize early intervention strategies for neurodegenerative diseases. …”
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Integrated Ultrasound‐Enrichment and Machine Learning in Colorimetric Lateral Flow Assay for Accurate and Sensitive Clinical Alzheimer's Biomarker Diagnosis by Shuqing Wang, Yan Zhu, Zhongzeng Zhou, Yong Luo, Yan Huang, Yibiao Liu, Tailin Xu

“…The LFA device is integrated with a portable ultrasonic actuator to rapidly enrich microparticles using ultrasound, which is essential for sample pre‐enrichment to improve the sensitivity, followed by ML algorithms to classify and predict the enhanced colorimetric signals. …”
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Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…In IRS-assisted communication systems, accurate channel estimation is crucial for optimizing signal transmission and achieving high spectral efficiency. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…Emerging opportunities for optimizing pest and disease monitoring through advanced algorithms are also emphasized. …”
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Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…This study evaluates several leading multiobjective BO acquisition functions–namely, parallel expected hypervolume improvement (qEHVI), noisy qEHVI, parallel parEGO, and parallel noisy parEGO (qNparEGO)–in optimizing the physical properties of multi-component alloys. …”
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Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systemsMendeley Data by Arjun Upadhyay, Sunil G. C, Maria Villamil Mahecha, Joseph Mettler, Kirk Howatt, William Aderholdt, Michael Ostlie, Xin Sun

“…Effective weed management is crucial for maintaining optimal crop growth and achieve higher yield. Recent advancement in robotic technologies and advanced deep learning (DL) models is shaping the future of robotic weed control systems. …”
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Dual-Path Large Kernel Learning and Its Applications in Single-Image Super-Resolution by Zhen Su, Mang Sun, He Jiang, Xiang Ma, Rui Zhang, Chen Lv, Qiqi Kou, Deqiang Cheng

“…To enhance the performance of super-resolution models, neural networks frequently employ module stacking. …”
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Development of GUI-Driven AI Deep Learning Platform for Predicting Warpage Behavior of Fan-Out Wafer-Level Packaging by Ching-Feng Yu, Jr-Wei Peng, Chih-Cheng Hsiao, Chin-Hung Wang, Wei-Chung Lo

“…Traditional electronic engineers often face difficulties in implementing AI-driven models due to the specialized programming and algorithmic expertise required. …”
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Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Innovative segmentation techniques and multimodal imaging models have further enhanced healthcare efficiency by reducing physician workload and improving diagnostic accuracy. …”
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Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI by J. DiGregorio, A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J.-C. Tardif, P.N. Tyrrell, A.R. Moody, A. Khademi

“…Despite this, most automated biomarker extraction algorithms are designed for T1-weighted or multi-modal inputs. …”
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