A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batt... by Mehrdad Shoeibi, Anita Ershadi Oskouei, Masoud Kaveh

“…These devices play a pivotal role in next-generation IoT applications by reducing the dependence on conventional batteries and enabling continuous operation through energy harvesting capabilities. …”
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A Structured Dataset for Automated Grading: From Raw Data to Processed Dataset by Ibidapo Dare Dada, Adio T. Akinwale, Ti-Jesu Tunde-Adeleke

“…Future work will focus on enhancing grading consistency and expanding the dataset for broader academic applications.…”
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Validity and reliability of the Chinese version of the Jenkins Sleep Scale among university students in China by Mengyuan Zhao, Garry Kuan, Ke Zhou, Yee Cheng Kueh

“…Background The Chinese version of the Jenkins Sleep Scale (JSS-C) is widely used; however, it lacks formal validation, and its applicability to Chinese university students has not been examined. …”
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A Novel Fuzzy PIDF Enhancing PIDF Controller Tuned in Two Stages by TLBO and PSO Algorithms for Reliable AVR Performance by Mokhtar Shouran, Mohammed Alenezi

“…The tuning process for both stages employs the well-known Integral Time Absolute Error (ITAE) cost function in conjunction with the TLBO and PSO algorithms. …”
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Control of Nonlinear Systems Using Fuzzy Techniques Based on Incremental State Models of the Variable Type Employing the “Extremum Seeking” Optimizer by Basil Mohammed Al-Hadithi, Gilberth André Loja Acuña

“…This makes the approach particularly relevant for control applications in electrical systems, where handling high-order reference signals and disturbances is critical. …”
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Synchronization in Fractional-Order Delayed Non-Autonomous Neural Networks by Dingping Wu, Changyou Wang, Tao Jiang

“…Neural networks, mimicking the structural and functional aspects of the human brain, have found widespread applications in diverse fields such as pattern recognition, control systems, and information processing. …”
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Assessing the accuracy of adherence and sexual behaviour data in the MDP301 vaginal microbicides trial using a mixed methods and triangulation model. by Robert Pool, Catherine M Montgomery, Neetha S Morar, Oliver Mweemba, Agnes Ssali, Mitzy Gafos, Shelley Lees, Jonathan Stadler, Andrew Nunn, Angela Crook, Richard Hayes, Sheena McCormack

“…IDI data on adherence match the applicator-return data more closely than the CRF. The main reasons for inaccuracies are participants forgetting, interviewer error, desirability bias, problems with the definition and delineation of key concepts (e.g. …”
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Explainable deep learning for age and gender estimation in dental CBCT scans using attention mechanisms and multi task learning by Najmeh Pishghadam, Rasool Esmaeilyfard, Maryam Paknahad

“…By incorporating explainable AI techniques, this model provides a computationally efficient and clinically interpretable tool for forensic and medical applications.…”
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Neural Networks vs. Regression: A Comparative Analysis in Medical Data Processing by Minodora ANDOR, Gheorghe Ioan MIHALAŞ

“…The optimization process for NN required extensive trial and error, as no universal guidelines for parameter selection were applicable in this context. …”
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Assimilation of INSAT-3D imager retrieved aerosol optical depth for enhanced dust storm prediction using WRF-Chem model by Aman W Khan, Dilip Ganguly, Sagnik Dey, Atul Kumar Varma, Prashant Kumar

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Machine learning framework for oxytetracycline removal using nanostructured cupric oxide supported on magnetic chitosan alginate biocomposite by Hassan Rasoulzadeh, Hossein Azarpira, Mojtaba Pourakbar, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Consequently, the Tikhonov model outperforms the Yandex Boosting model due to its higher accuracy and lower error rates, whereas Yandex Boosting, despite strong training performance, suffers from overfitting, leading to inferior testing performance. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…However, near the liquid cooling plate, where temperature gradients are more nonlinear, reconstruction error increased slightly. Despite this, the maximum absolute error remains within 0.3 K, highlighting the robustness of the method. …”
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The Dissolved Oxygen Prediction Method Based on Neural Network by Zhong Xiao, Lingxi Peng, Yi Chen, Haohuai Liu, Jiaqing Wang, Yangang Nie

“…Compared with the common prediction models, curve fitting (CF), autoregression (AR), grey model (GM), and support vector machines (SVM), the experimental results show that the prediction accuracy of the neural network is the highest, and all the predicted values are less than 5% of the error limit, which can meet the needs of practical applications, followed by AR, GM, SVM, and CF. …”
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Bayesian Methods for Predicting the Shape of Chinese Yam in Terms of Key Diameters by Mitsunori Kayano, Koki Kyo, Mitsuru Hachiya

“…Shape prediction of yam is applicable to determining optimal cutoff positions of a yam for producing seed yams. …”
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Hybrid Deep–Geometric Approach for Efficient Consistency Assessment of Stereo Images by Michał Kowalczyk, Piotr Napieralski, Dominik Szajerman

“…Experimental results show that our score degrades smoothly with increasing geometric error and achieves high detection rates even at minimal distortion levels, outperforming baseline approaches based on disparity or calibration checks. …”
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Internal model control based sliding mode controller design for unstable second order delayed processes with a case study on CSTR by Mohammed Hasmat Ali, Md Nishat Anwar

“…An objective function is constituted in terms of performance measure (integral absolute error) and control effort measure (total variation of controller output). …”
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Constrained Fuzzy Predictive Control Using Particle Swarm Optimization by Oussama Ait Sahed, Kamel Kara, Mohamed Laid Hadjili

“…The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. …”
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High-accuracy physical property prediction for pure organics via molecular representation learning: bridging data to discovery by Qi Ou, Hongshuai Wang, Minyang Zhuang, Shangqian Chen, Lele Liu, Ning Wang, Zhifeng Gao

“…Traditional trial-and-error methods for discovering highly functional organic compounds are expensive and time-consuming. …”
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A sociotechnical perspective for explicit unfairness mitigation techniques for algorithm fairness by Nimisha Singh, Amita Kapoor, Neha Soni

“…With the increasing use of artificial intelligence (AI) applications in decision making, there are heightened concerns about the fairness of such decisions. …”
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Whispers in End Hopping: High-Robustness Network Covert Channel Based on End Spreading by Zhengwen Wang, Fangxiao Li, Leyi Shi

“…These results confirm the CCES scheme’s strong robustness and practical applicability, outperforming traditional covert channels in both reliability and stealth.…”
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