A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…The particle swarm optimization (PSO) algorithm is used to solve this model. …”
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GBM-Reservoir: Brain tumor (Glioblastoma Multiforme) MRI dataset collection with ground truth segmentation masksfigshare by Naida Solak, André Ferreira, Gijs Luijten, Behrus Puladi, Victor Alves, Jan Egger

“…The first mask is the raw output from the registration process and is provided for all samples, while the second mask, provided particularly for synthetic samples, is a post-processed version of the first, designed to simplify interpretation and optimize it for network training. …”
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DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Second, we develop a Context-Aware Adaptive Threshold Optimization (CA-ATO) algorithm that dynamically determines optimal thresholds by integrating multi-scale contextual information and uncertainty estimates, substantially improving boundary delineation accuracy and fine structure preservation. …”
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MUFFNet: lightweight dynamic underwater image enhancement network based on multi-scale frequency by Dechuan Kong, Dechuan Kong, Yandi Zhang, Xiaohu Zhao, Yanqiang Wang, Lei Cai

“…A Multi-Scale Enhancement Prior algorithm enhances high-frequency and low-frequency features while the Information Flow Interaction module mitigates information stratification and blockage. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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Neural Networks vs. Regression: A Comparative Analysis in Medical Data Processing by Minodora ANDOR, Gheorghe Ioan MIHALAŞ

“…The regression model followed standard statistical guidelines, while the FFNN required optimization of hyperparameters, including the number of layers, activation functions, learning rate, and  optimization algorithms. …”
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Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS by Yanis Hamoudi, Maher G.M. Abdolrasol, Hocine Amimeur, Faycal Hassaini, Pin Jern Ker, Taha Selim Ustun

“…Importantly, this approach does not require reconfiguring the control algorithm while preserving the system’s effective performance. …”
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A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller by Jorge Aráez, Santiago Real, Alvaro Araujo

“…While it is faster than other feature detectors like SIFT (340 times faster) or SURF (15 times faster), it is one of the most computationally expensive algorithms in these types of systems. …”
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Deadbeat-based control for MMC-HVDC power systems by Milovan Majstorović, Vaibhav Nougain, Leposava Ristić, Aleksandra Lekić

“…The designed control algorithm is tested with two real-time simulation platforms, i.e., OPAL-RT and RTDS for thorough power system validation.…”
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LArcNet: Lightweight Neural Network for Real-Time Series AC Arc Fault Detection by Kamal Chandra Paul, Chen Chen, Yao Wang, Tiefu Zhao

“…Detecting series ac arc faults in diverse residential loads is challenging due to variations in load characteristics and noise. While traditional artificial intelligence-based algorithms can be effective, they often involve high computational complexity, limiting their real-time implementation on resource-constrained edge devices. …”
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DMM-YOLO: A high efficiency soil fauna detection model based on an adaptive dynamic shuffle mechanism by Jiehui Ke, Renbo Luo, Guoliang Xu, Yuna Tan, Zhifeng Wu, Liufeng Xiao

“…Therefore, this paper proposes an improved algorithm based on You Only Look Once (YOLO) v9, which enhances feature capture capability while reducing parameters by 33.6%. …”
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Development and application of a generalized fatigue driving monitoring system for open-pit mining vehicles: A case study in a myanmar copper mine by Tao Li, Baomeng Chang, Yan Sun, Yaodong Zhou, Bin Zhou, Lubin Zhang

“…Engineering practices yielding the following outcomes: (1) The Beidou positioning antenna demonstrated superior performance in the S&K mine, ensuring accurate vehicle tracking and minimal signal blind spots in challenging open-pit mining environments. (2) The GFDMS effectively identifies unsafe driving behaviors, including speeding, fatigue driving and irregular operations, providing real-time alerts to enhance safety. (3) A comprehensive analysis of system performance demonstrated its effectiveness, reducing traffic incident rates by over 70 % for mining dump trucks and auxiliary vehicles within a year while improving vehicle utilization and operational reliability. (4) Challenges in improving the GFDMS persist in areas such as environmental adaptability, algorithm generalization, and scalability. …”
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Differential Diagnosis of Peripheral Lung Lesions: Capabilities and Limitations of Current Methods by R. N. Islamov, R. A. Sharipov, M. A. Bagirov, R. K. Tukfatullin, G. V. Chitorelidze, E. V. Pavlova, R. K. Yagafarova

“…VATS proves effective for lesions below 3 cm, while thoracotomy is applied to large lesions. An individualized approach remains essential for optimal diagnosis. …”
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A reversible and robust hybrid image steganography framework using radon transform and integer lifting wavelet transform by B. M. El-den, Walid Raslan

“…Data embedding is performed in the middle bit planes of high-frequency sub-bands (LH, HL, HH) using Arithmetic Coding, optimizing space utilization while preserving visual quality. …”
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From Pixels to Diagnosis: Early Detection of Diabetic Retinopathy Using Optical Images and Deep Neural Networks by Amira J. Zaylaa, Sylva Kourtian

“…The ROC curves of both ResNet-50 and GoogleNet yielded optimal results, followed by SqueezeNet. MobileNet-v2 showed the weakest performance in terms of the ROC, while all networks showed negligible errors in diagnosis and detection. …”
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Integrated impact of urban mixed land use on TOD ridership: A multi-radius comparative analysis by Xinyue Gu, Siyan Lin, Chengfang Wang

“… The global trend toward urbanization has spurred the widespread adoption of transit-oriented development (TOD). While previous research has extensively explored the relationship between land use and TOD ridership, much of it has focused on linear associations at a singular scale. …”
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Prioritising explainable AI-driven recommendations with knowledge graphs and reinforcement learning by Neeraj Tiwary, Shahrul Azman Mohd Noah, Fariza Fauzi

“…By applying optimisation techniques that consider rewards, probabilities, information values, and affinity scores while minimising traversal hops within KG paths, XAIRec learns user preferences from historical data, determines optimal reasoning paths, and enhances recommendation quality by prioritising products with higher relevance. …”
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Force-Driven Model for Automated Clear Aligner Staging Design Based on Stepwise Tooth Displacement and Rotation in 3D Space by Sensen Yang, Yumin Cheng

“…The algorithm was implemented in C++ and incorporated into the WebGL-based SmarteeCheck3.0 software for visualization. …”
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Improving Portfolio Management Using Clustering and Particle Swarm Optimisation by Vivek Bulani, Marija Bezbradica, Martin Crane

“…Particularly, this research examines different approaches for handling missing values and volatility, while examining their effects on optimal portfolios. …”
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