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

“…In board examinations, GPT-4 outperformed prior models and junior neurosurgeons in text-based questions but lagged in image-based tasks. …”
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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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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. …”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…The framework utilizes an Island Based Genetic Algorithm flow that optimizes several objectives including performance, area, and power consumption. …”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…This review highlights the significant potential of AI-enhanced qEEG as a non-invasive, cost-effective tool for the diagnosis of AD in its prodromal and dementia stages, while also identifying areas requiring further research to optimize its clinical application. These findings suggest that AI-enhanced qEEG analysis could revolutionize AD diagnosis, enabling earlier intervention and improved patient outcomes.…”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. …”
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Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

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Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…Subsequently, five machine learning algorithms, such as RF and XGBoost, are used in combination with a grid search to find the optimal hyperparameters, and Lasso is used as the meta-learner to integrate the prediction results. …”
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Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…By integrating diverse datasets with advanced algorithms and models, we perform correlation analyses of parameters such as capacity, voltage, temperature, pressure, and strain, enabling precise SOH estimation and RUL prediction. …”
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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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PSO Tuned Super-Twisting Sliding Mode Controller for Trajectory Tracking Control of an Articulated Robot by Zewdalem Abebaw Ayinalem, Abrham Tadesse Kassie

“…This paper introduces a novel method that integrates SolidWorks modeling to create precise digital representations of the robot’s mechanical structure, facilitating easier development and simulation of control algorithms. …”
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Reinforcement learning applications in water resource management: a systematic literature review by Linus Kåge, Vlatko Milić, Vlatko Milić, Maria Andersson, Magnus Wallén

“…Reinforcement learning (RL) has demonstrated promising potential in optimization and planning tasks, as it trains models on historical data or through simulations, allowing them to generate new data by interacting with the simulator. …”
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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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Research on the Virtual Coupling Technology for Urban Rail Transit Trains by YANG Weifeng, LEI Chengjian, HAN Chen, LI Qihe, XIE Xing

“…The paper additionally highlights the technical challenges faced in engineering applications, including the need for improved cooperative control algorithms, enhanced vehicle-to-vehicle communication mechanisms, and optimized safety braking models.…”
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The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease by Mohammed A. Chowdhury, Rodrigue Rizk, Conroy Chiu, Jing J. Zhang, Jamie L. Scholl, Taylor J. Bosch, Arun Singh, Lee A. Baugh, Jeffrey S. McGough, KC Santosh, William C.W. Chen

“…We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. …”
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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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