Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…ObjectiveThis study aims to evaluate the accuracy of LLMs in RoB2 assessments to explore their potential as research assistants for bias evaluation. …”
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KERF: a knowledge-enhanced relearning framework for tailings pond detection from high-resolution remote sensing images by Bingjie Liu, Wei Wu, Hao Wu, Ailong Ma, Shaohua Hu, Nianchun Du, Xuan Cui, Junyang Xie

“…An augmented feature pyramid network and multi-stage detectors are introduced to generate proposals with feature enhancement and location optimization. …”
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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

“…Prior to applying machine learning models, preprocessing steps were performed, including normalization using Min–Max Scaling to confine all features within the [0,1] range, outlier detection and removal of anomalous values, correlation analysis to avoid redundancy and multicollinearity, and data splitting into training and testing sets at an 80:20 ratio, along with K-fold cross-validation (k = 5) for robust model evaluation. The study assesses the accurate predictions of specific models, including Tikhonov Regularization, Yandex Boosting, and Particle Swarm Optimization (PSO), to improve removal efficiency and provide analysis of the components influencing the method. …”
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Self-Supervised Neural Networks for Precoding in MIMO Rate Splitting Multiple Access Systems by Dheeraj Raja Kumar, Carles Anton-Haro, Xavier Mestre

“…The intention is to explore several alternatives to conventional iterative precoding benchmarks like Weighted Minimum Mean Square Error (WMMSE) which are computationally intensive algorithms. We evaluate the different precoding policies learnt by the neural network architectures by closely studying the respective radiation patterns. …”
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Cytotoxicity and Exposure Assessment of PM2.5 in a Residential Home during COVID-19 Lockdown by Ummi Sabariah Mahamud, Armania Nurdin, Eliani Ezani

“…Due to the limited yield of indoor and outdoor PM2.5, further optimization on the extraction of PM2.5 should be carried out to evaluate further the mechanism of cytotoxicity of indoor PM2.5 on the lung cells.…”
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Machine Learning Models for Predicting Seismic Response of a Novel Two-Stage Friction Pendulum Isolated Bridge Structure by Hanzlah Akhlaq, Tianbo Peng, Kawsu Jitteh, Muhammad Salman Khan

“…Utilizing this extensive dataset, seven ML models were trained and evaluated using statistical key performance indicators (KPIs). …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…The generated flight paths are optimized in terms of both stability and efficiency, making the algorithm suitable for complex mission scenarios.…”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid by Yanming Cheng, Jinqi Zhang, Mahmoud Al Shurafa, Dejun Liu, Yulian Zhao, Chao Ding, Jing Niu

“…Abstract Microgrid (MG) is basically composed of different distribution generators (DGs) connected in parallel for supplying a specific set of loads managed by an Energy management system (EMS). …”
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A New Heuristic Procedure for Quadratic Assignment Problems by Najla Al-Saati

“…Three different tests are carried out in this work including 26 randomly generated problems, each is represented by a distance and a volume flow matrix with different matrix dimensions, to be employed in the process of evaluating the efficiency of the improved heuristic procedure in terms of solution accuracy and processing time consumption. …”
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Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm by Xiaoxia Ma

“…Finally, according to different evaluation indexes, a systematic visualization scheme is designed to generate students’ classroom learning evaluation report and teachers' classroom teaching evaluation report, respectively, and visualize them on the web.…”
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Whole-body tumor segmentation from FDG-PET/CT: Leveraging a segmentation prior from tissue-wise projections by Sambit Tarai, Elin Lundström, Nouman Ahmad, Robin Strand, Håkan Ahlström, Joel Kullberg

“…Background:Accurate tumor detection and quantification are important for optimized therapy planning and evaluation. Total tumor burden is also an appealing biomarker for clinical trials. …”
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Research progress of catalyst for hydrogen precipitation reaction (HER) in hydrogen production by electrolytic water by Song Yiming

“…However, the large-scale application of water electrolysis technology is still limited by the activity, stability and cost of the cathode hydrogen evolution reaction (HER) catalyst. In this paper, the reaction mechanism, material system and optimization strategy of HER catalyst were systematically reviewed, focusing on the structure-activity relationship of platinum-based catalyst, transition metal sulfide and metal-carrier composite catalyst, and the differences in their activity were revealed based on the theory of hydrogen adsorption free energy ( ΔGH), in order to provide references for rational design of high-performance catalysts and industrial promotion of water electrolytic technology.…”
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Defining a Novel Meaning of the New Organic Architecture by Jia-Rey Chang

“…This discussion will be categorized into three major divisions: “Morphological”, “Material”, and “Behavioral” owing to the different focus of computational applications within each one of them. …”
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Study on Synergistic Effect of Directional Chemical Reaction⁃Assisted SAGD under Three⁃Dimensional Physical Simulationon by Tao LIN, Qiaobo WANG, Hongzhi SONG, Zhongtao YUAN, Tianliang LI

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A multi objective collaborative reinforcement learning algorithm for flexible job shop scheduling by Jian Li, Shifa Li, Pengbo He, Huankun Li

“…Using hypervolume, set coverage and inverted generational distance as evaluation metrics, the algorithm is compared with those proposed in other studies on standard instances. …”
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Image Super-Resolution via Adaptive Regularization Term of Compressed Sensing by Yintao Liu, Chao Ren, Hongjuan Shao, Qirui Liu, Yan Zhang

“…By generating a suitable coefficient, it can adaptively reconcile the relationship between sparsity and correlation. …”
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Polynomial Modeling of Noise Figure in Erbium-Doped Fiber Amplifiers by Rocco D’Ingillo, Alberto Castronovo, Stefano Straullu, Vittorio Curri

“…Accurate noise figure estimation is critical for optimizing link budgets, monitoring optical Signal-to-Noise Ratio (OSNR), and enabling real-time network optimization. …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…To address these limitations, we construct a pseudo-surrogate model with adjustable prediction accuracy, enabling fair comparisons across different strategies. We evaluate three representative strategies — pre-selection (PS), individual-based (IB), and generation-based (GB) — using a common pseudo-surrogate model on six benchmark problems in 10 and 30 dimensions from the CEC2015 competition. …”
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Embedded feature selection using dual-network architecture by Abderrahim Abbassi, Arved Dörpinghaus, Niklas Römgens, Tanja Grießmann, Raimund Rolfes

“…Simultaneously, the selection model aims to minimize the cumulative value of the mask, thus selecting the most relevant features with minimal impact on the task model’s performance.The method is evaluated using benchmark and synthetic datasets across different supervised tasks. …”
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Deep learning models for detection of explosive ordnance using autonomous robotic systems: trade-off between accuracy and real-time processing speed by Vadym Mishchuk, Herman Fesenko, Vyacheslav Kharchenko

“…The main contribution of this study is the results of a detailed evaluation of the YOLOv8 and RT-DETR models for real-time EO detection, helping to find trade-offs between the speed and accuracy of each model and emphasizing the need for special datasets and algorithm optimization to improve the reliability of EO detection in autonomous systems.…”
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