Performance Testing and Analysis of a New GNSS Spoofing Detection Method in Different Spoofing Scenarios by Li Junzhi, Wu Haitao, Gao Jinfeng, Liu Fang, Zhang Yu, Li Gangqiang, He Yu

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Distribution Network Fault Risk Assessment Method Considering Difference in Entropy Value of Rare Factors by HUANG Junxian, CHEN Chun, CAO Yijia, QUAN Shaoli, WANG Yi

“…To comprehensively and accurately assess the risk of faults in a distribution network, this paper proposes a fault risk assessment method that considers the difference in entropy value of rare factors. This method uses K-means clustering algorithm to classify failures based on their consequences and an improved association rule mining algorithm to analyze rare environmental factors and evaluate high-risk and low-probability factors, so as to realize the quantitative analysis of the association between rare factors and risk levels. …”
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A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI. by Elizabeth M Sweeney, Joshua T Vogelstein, Jennifer L Cuzzocreo, Peter A Calabresi, Daniel S Reich, Ciprian M Crainiceanu, Russell T Shinohara

“…Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. …”
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Evolution and taxonomic classification of alphapapillomavirus 7 complete genomes: HPV18, HPV39, HPV45, HPV59, HPV68 and HPV70. by Zigui Chen, Mark Schiffman, Rolando Herrero, Rob DeSalle, Kathryn Anastos, Michel Segondy, Vikrant V Sahasrabuddhe, Patti E Gravitt, Ann W Hsing, Robert D Burk

“…To study viral heterogeneity, the complete 8 kb genome of 128 isolates, including 109 sequenced for this analysis, were annotated and analyzed. Viral evolution was characterized by constructing phylogenic trees using maximum-likelihood and Bayesian algorithms. …”
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From Tension to Triumph: Design and Implementation of an Innovative Algorithmic Metric for Quantifying Individual Performance in Women Volleyball’s Critical Moments by Carlos López-Serrano, María Zakynthinaki, Daniel Mon-López, Juan José Molina Martín

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Enhanced Leakage Detection and Estimation via a Hybrid Genetic Algorithm and High-Order Sliding Modes Observer Approach by David Pumaricra-Rojas, Gustavo Perez-Zuniga, Javier Sotomayor-Moriano

“…To find these parameters, it incorporates the Genetic Algorithm to solve an optimization problem that relies on a function cost related to the error norm between measurements and states estimation from HOSMO in order to measure the difference between the model with an assumed leakage and the real leakage. …”
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Research on Arthroscopic Images Bleeding Detection Algorithm Based on ViT-ResNet50 Integrated Model and Transfer Learning by Zewen Liu, Shaoyi Zhou, Jianqiao Chu, Zhiyuan Chai, Dongdong Chang, Yi Yuan, Jinling Qin, Xiancheng Wang

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A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems by Cornelius Rüther, Julia Rieck

“…The parameter tuning is evaluated on five data sets which differ in several structural characteristics and contain 1200 problem instances. …”
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Performance and limitation of machine learning algorithms for diabetic retinopathy screening and its application in health management: a meta-analysis by Mehrsa Moannaei, Faezeh Jadidian, Tahereh Doustmohammadi, Amir Mohammad Kiapasha, Romina Bayani, Mohammadreza Rahmani, Mohammad Reza Jahanbazy, Fereshteh Sohrabivafa, Mahsa Asadi Anar, Amin Magsudy, Seyyed Kiarash Sadat Rafiei, Yaser khakpour

“…This study aimed to evaluate the performance and limitations of machine learning and deep learning algorithms in detecting diabetic retinopathy. …”
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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction by Babu Kumar, Radhakrishnan Soundararajan, Kanimozhi Natesan, Roobini Maridhas Santhi

“…QRS waves, which are time intervals of binary data, can be determined using the suggested technique of determining the ECG signal’s time interval from R-peak levels to the next level using double squared differences in signals. This approach involves many rounds of data sorting for decreasing noise, thresholding an ECG difference signal by examining the time interval between QRS, and then comparing relative magnitudes to identify the area of interval processing to evaluate accuracy results. …”
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Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance by Mahmoud M. Eid, Kamal ElDahshan, Abdelatif H. Abouali, Alaa Tharwat

“…Each experiment compares the proposed method, utilizing the best optimizer from the first set, against leading imputation methods. The experiments evaluate different types of data and various missing-data rates, ensuring that randomness does not introduce bias. …”
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Selection and evaluation of reference genes for qRT-PCR in Inonotus obliquus by Lulu Li, Xiaofan Guo, Shouming Wang

“…Subsequently, we applied GeNorm, NormFinder, and BestKeeper algorithms to evaluate the expression stability of these 11 reference genes. …”
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Evaluation of Transportation Network Reliability under Emergency Based on Reserve Capacity by Xiongfei Zhang, Qi Zhong, Qin Luo

“…There are differences between the requirements for traffic network for traffic demand in daily and emergency situations. …”
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Application of the SARIMA-LSTM model to evaluate the effectiveness of interventions for Visceral Leishmaniasis by Mengchen Han, Chongqi Hao, Zhiyang Zhao, Peijun Zhang, Bin Wu, Lixia Qiu

“… Introduction: This study proposes a combined Seasonal Autoregressive Integrated Moving Average and Long Short-Term Memory (SARIMA-LSTM) model to enhance the accuracy of evaluating the effectiveness of visceral leishmaniasis prevention and control efforts in Yangquan, China. …”
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Application of BP Neural Network Model in Risk Evaluation of Railway Construction by Yang Changwei, Li Zonghao, Guo Xueyan, Yu Wenying, Jin Jing, Zhu Liang

“…Secondly, it establishes two independent BP neural network models by using different training algorithms because of the different political, economic, and cultural elements between the two continents.…”
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RETRACTED: Temporal-Difference Graph-Based Optimization for High-Quality Reconstruction of MODIS NDVI Data by Shengtai Ji, Shuxin Han, Jiaxin Hu, Yuguang Li, Jing-Cheng Han

“…Regarding spatio-temporal NDVI data as a time-varying graph signal, the developed method utilized an optimization algorithm to maximize the spatial smoothness of temporal differences while preserving the spatial NDVI pattern. …”
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An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization by Maria Navarro-Caceres, Pramod Herath, Gabriel Villarrubia, Francisco Prieto-Castrillo, G. Kumar Venyagamoorthy

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Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

“…The experimental results from this study were used to validate a model generated from hybrid adaptive neuro-fuzzy inferences system-particle swarm optimization (ANFIS-PSO) algorithms. The hybrid ANFIS-PSO modelling technique was improvised for a detailed evaluation of corrosion rate of ductile cast iron materials in different environments. …”
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Effects of different wearable sensors and locomotion tasks on machine learning-based joint moment prediction by Jonas Weber, Bernd J. Stetter

“…., 2019). However, comparing different studies investigating various sensors and locomotion tasks can be challenging due to variations in ML algorithms, model evaluation techniques, and reported performance metrics (Gurchiek et al., 2019). …”
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An Aliasing Measure of Factor Effects in Three-Level Regular Designs by Qiuying Chen, Zhiming Li, Zhi Li

“…In this paper, a new three-level aliasing pattern is proposed to evaluate the degree of aliasing among different factors. …”
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