Performance Evaluation of Some Selected Classification Algorithms in a Facial Recognition System by Michael Olumuyiwa Adio, Ogunmakinde Jimoh Ogunwuyi, Mayowa Oyedepo Oyediran, Adebimpe Omolayo Esan, Olufikayo Adepoju Adedapo

“…Hence, this work evaluated the performance of the Learning Vector Quantization; Relevance Vector Machine and Support Vector Machine classification algorithms in facial recognition system and Support Vector Machine outwit the other two algorithms in facial recognition in term of specificity, recognition time and recognition accuracy at different threshold. …”
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Improved anticipatory scheduling algorithm based on workload characteristic and service time evaluation by Jin-zhong CHEN, Nian-min YAO, Shao-bin CAI, Mei-ling SUN

“…Anticipatory scheduling (AS) of Linux I/O schedule layer assigns fixed anticipation period length to each process.It will introduce extra delay if I/O request does not arrive in time.The improved anticipatory scheduling (WPCAS) algorithm is proposed which is based on workload characteristic and service time.WPCAS includes process classifier(PC) module and request service time evaluation (STE) module.PC module assigns different anticipation period lengths in terms of workload characteristic.STE module decides whether to anticipate the coming request according to service time.Experimental results show that WPCAS algorithm is superior to 95%-Heuristic and AS in terms of throughput,average waiting time of anticipation success and deceptive idleness.…”
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Evaluating the Minimum Spanning Trees Using Prim's Algorithm with Undirected Neutrosophic Graphs by Sukanta Ghadei, Amaresh Chandra Panada, Surapati Pramanik, Nihar Ranjan Panda, Prasanta Kumar Raut

“…Neutrosophic numbers with components reflecting truth, uncertainty, and Neutrosophic Sets and Systems, Vol. 85, 2025 362 Sukanta Ghadei, Amaresh Chandra Panada,Surapati,Pramanik, Nihar Ranjan Panda, Prasanta Kumar Raut, Evaluating the Minimum Spanning Trees Using Prim's Algorithm with Undirected Neutrosophic Graphs falsehood provide a more sophisticated method of expressing uncertainty in network modeling. …”
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Machine learning for brain tumor classification: evaluating feature extraction and algorithm efficiency by Krishan Kumar, Kiran Jyoti, Krishan Kumar

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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

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Evaluating the Efficiency of Nature-Inspired Algorithms for Finite Element Optimization in the ANSYS Environment by Antonino Cirello, Tommaso Ingrassia, Antonio Mancuso, Giuseppe Marannano, Agostino Igor Mirulla, Vito Ricotta

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Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems by Farshad Taiyari

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Evaluation of polymer viscoelasticity by integrated micro-indentation test with optical flow algorithm by Giyeol Han, Yeongmin Yoon, Hyungyil Lee

“…This study aims to directly evaluate the viscoelastic (creep) parameters of polymer materials by integrating a micro-indentation test with an optical flow (OF) algorithm and an embedded center of dilatation (ECD) model. …”
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Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience by Pratap Khattri, Rachel Sayers, Kunwar K. Singh, Ryan Slapikas, Chet Bahadur Tamang, Dinee Tamang, Brad Sagara, Ariel BenYishay

“…We conducted a geospatial impact evaluation (GIE), which integrated remote sensing data and econometric techniques, including optimal full matching (OFM) and difference-in-differences (DID). …”
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Evaluation of Different Sensor Systems for Classifying the Behavior of Dairy Cows on Pasture by Barbara Pichlbauer, Jose Maria Chapa Gonzalez, Martin Bobal, Christian Guse, Michael Iwersen, Marc Drillich

“…This study aimed to validate several sensor systems for classifying rumination and lying behaviors in cows on pasture under different environmental conditions, compare the sensors’ performance at different time resolutions, and evaluate a correction algorithm for rumination data. …”
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Network security threat warning method based on qualitative differential game by Shirui HUANG, Hengwei ZHANG, Jindong WANG, Ruiyu DOU

“…Most current network security research based on game theory adopts the static game or multi-stage dynamic game model,which does not accord with the real-time change and continuity of the actual network attack-defense process.To make security threats warning more consistent with the attack-defense process,the threat propagation process was analyzed referring to the epidemic model.Then the network attack-defense game model was constructed based on the qualitative differential game theory,by which the evolution of the network security state could be predicted.Based on the model,the qualitative differential game solution method was designed to construct the attack-defense barrier and divide the capture area.Furthermore,the threat severity in different security states were evaluated by introducing multidimensional Euclidean distance.By designing the warning algorithm,the dynamic warning of the network security threat was realized,which had better accuracy and timeliness.Finally,simulation results verify the effectiveness of the proposed algorithm and model.…”
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A Multi-Feature Fusion Algorithm for Fatigue Driving Detection Considering Individual Driver Differences by Meng Zhou, Xiaoyi Zhou, Zhijian Li, Xinyue Liu, Chengming Chen

“…To improve the judging accuracy of the driver’s facial expressions, a personalized threshold is proposed based on the normalization of the driver’s eyes and mouth opening and closing instead of the traditional average threshold, as individual drivers have different eye and mouth sizes. Given the dynamic changes in fatigue level, a sliding window model is designed for further calculating blinking duration ratio (BF), yawning frequency (YF), and nodding frequency (NF), and these evaluation indexes are used in the feature fusion model. …”
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A Modified Multiobjective Self-Adaptive Differential Evolution Algorithm and Its Application on Optimization Design of the Nuclear Power System by Yunjia Yang, Shinian Peng, Li Zhu, Dan Zhang, Zhifang Qiu, Hongsheng Yuan, Lin Xian

“…A modified multiobjective self-adaptive differential evolution algorithm (MMOSADE) is presented in this paper to improve the accuracy of multiobjective optimization design in the nuclear power system. …”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

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Survey on vertical federated learning: algorithm, privacy and security by Jinyin CHEN, Rongchang LI, Guohan HUANG, Tao LIU, Haibin ZHENG, Yao CHENG

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Prediction of strength parameters of concrete containing different additives using optimized neural network algorithm by Behzad Haseli, Gholamreza Nouri, Meysam Mardi, Ehsan Adili, Mohammad Bahari

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Comparative analysis of different algorithms for VAS station land cover classification with limited training points by D. García-Rodríguez, A. Pérez-Hoyos, B. Martínez, Pablo Catret Ruber, J. Javier Samper-Zapater, E. López-Baeza, J.J. Martínez Durá

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A Novel Hybrid Optimizer Based on Coati Optimization Algorithm and Differential Evolution for Global Optimization and Constrained Engineering Problems by Saptadeep Biswas, Binanda Maiti, Gyan Singh, Absalom E. Ezugwu, Kashif Saleem, Laith Abualigah, Aseel Smerat, Uttam Kumar Bera

“…Abstract This paper presents a novel hybrid metaheuristic, the Hybrid Coati Optimization Algorithm with Differential Evolution (HCOADE), developed to address complex global optimization tasks and constrained engineering design problems. …”
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Development of Wearable Wireless Multichannel f-NIRS System to Evaluate Activities by Xiaojie Ma, Tianchao Miao, Fawen Xie, Jieyu Zhang, Lulu Zheng, Xiang Liu, Hangrui Hai

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Parameter Estimation for Three-Phase Induction Motor Based on Performance Curves and Differential Evolution by Marcelo F. Castoldi, Gustavo Henrique Bazan, Wesley A. Souza, Clayton L. Graciola, Rafael M. Silva, Alessandro Goedtel

“…This paper introduces a novel and easy-to-implement offline parameter estimation method that eliminates the need for additional instrumentation by leveraging manufacturer performance curves and differential evolution optimization algorithm. Four equivalent circuit models are analyzed to evaluate the impact of core loss resistance and supplementary losses on estimation accuracy. …”
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