A New Approach Combining RSA and ElGamal Algorithms: Advancements in Encryption and Digital Signatures Using Gaussian Integers by Yahia Awad, Douaa Jomaa, Yousuf Alkhezi, Ramiz Hindi

“…This article introduces a novel approach that integrates the ElGamal and RSA algorithms to advance the security and efficiency of public-key cryptosystems. …”
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Automatic generation control optimization for power system resilience under real world load variations using genetic algorithm by Muhammad Ayaz, Dur-e-Zehra Baig, Syed Muhammad Hur Rizvi, Salah S. Alharbi, Sheeraz Iqbal, Md. Shafiullah

“…This study comprehensively explore the performance of AGC in a two-area interconnected power system, focusing on a wide range load variations that can exists in realistic power systems consisting from 100 to 300 MW in both increments and decrements. The performance of three control strategies-Conventional AGC (CAGC), Tie-Line Bias (TLB) Control, and Genetic Algorithm-Optimized PID (GA-PID)-is assessed across 12 distinct cases, each tested under these three scenarios. …”
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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

“…<i>Methods</i>: To solve the MDPDPTWHV, we present a Grouping Genetic Algorithm (GGA) framework with several operators and population management variants. …”
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Blind Infrared Remote-Sensing Image Deblurring Algorithm via Edge Composite-Gradient Feature Prior and Detail Maintenance by Xiaohang Zhao, Mingxuan Li, Ting Nie, Chengshan Han, Liang Huang

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Mean Field Initialization of the Annealed Importance Sampling Algorithm for an Efficient Evaluation of the Partition Function Using Restricted Boltzmann Machines by Arnau Prat Pou, Enrique Romero, Jordi Martí, Ferran Mazzanti

“…A possible way to tackle this problem is to use the Annealed Importance Sampling (AIS) algorithm, which provides a tool to stochastically estimate the partition function of the system. …”
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A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems by Binaya Kumar Malika, Vivekananda Pattanaik, Subhasis Panda, Binod Kumar Sahu, Pravat Kumar Rout, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

“…Abstract The optimal siting and sizing of DGs are vital for the efficient operation of both radial and microgrid distribution systems. From an operational perspective, minimizing real power loss, reducing voltage deviation, and improving voltage stability index are the three primary objectives considered in this study. …”
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Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms. by Juntu Li, Linfeng Tao, Yanyou Zhou, Yue Zhu, Chao Li, Yiyuan Pan, Ping Yao, Xuefeng Qian, Jun Liu

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Applying blood-derived epigenetic algorithms to saliva: cross-tissue similarity of DNA-methylation indices of aging, physiology, and cognition by Sepideh Zarandooz, Laurel Raffington

“…While the degree of cross-tissue similarity of several MPSs may suffice for some research settings, it may not be suitable in clinical or commercial applications. Collection of both blood and saliva DNAm samples is necessary to validate existing algorithms and to customize MPSs in saliva DNAm.…”
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A Comparative Analysis of Different Algorithms for Estimating Evapotranspiration with Limited Observation Variables: A Case Study in Beijing, China by Di Sun, Hang Zhang, Yanbing Qi, Yanmin Ren, Zhengxian Zhang, Xuemin Li, Yuping Lv, Minghan Cheng

“…The findings can be summarized as follows: (1) Long-term remote sensing data can furnish a more comprehensive background field for the LST-VI space, achieving superior fitting accuracy for wet and dry edges, thereby enabling precise ET estimation with the following metrics: correlation coefficient (r) = 0.68, root mean square error (RMSE) = 0.76 mm/d, mean absolute error (MAE) = 0.49 mm/d, and mean bias error (MBE) = −0.14 mm. (2) ML generally produces more accurate ET estimates, with the Random Forest Regressor (RFR) demonstrating the highest accuracy: r = 0.79, RMSE = 0.61 mm/d, MAE = 0.42 mm/d, and MBE = −0.02 mm. (3) Both ET estimates derived from the LST-VI space and ML exhibit spatial distribution characteristics comparable to those of MOD16 ET data, further attesting to the efficacy of these two algorithms. …”
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Identification of Major Bleeding Events in Postoperative Patients With Malignant Tumors in Chinese Electronic Medical Records: Algorithm Development and Validation by Hui Li, Haiyang Yao, Yuxiang Gao, Hang Luo, Changbin Cai, Zhou Zhou, Muhan Yuan, Wei Jiang

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A Three-Dimensional FDTD(2,4) Subgridding Algorithm for the Airborne Ground-Penetrating Radar Detection of Landslide Models by Lifeng Mao, Xuben Wang, Yuelong Chi, Su Pang, Xiangpeng Wang, Qilin Huang

“…This study achieves the first implementation of the high-order FDTD(2,4) method in both coarse- and fine-grid regions, which enables larger grid sizes in both regions. …”
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A Multiobjective Interval Programming Model for Wind-Hydrothermal Power System Dispatching Using 2-Step Optimization Algorithm by Kun Ren, Qu Jihong

“…Thorough experimental results suggest that the proposed method performed reasonably well in terms of both operating efficiency and precision.…”
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A novel fixed-point based two-step inertial algorithm for convex minimization in deep learning data classification by Kobkoon Janngam, Suthep Suantai, Rattanakorn Wattanataweekul

“…In this paper, we present a novel two-step inertial algorithm for finding a common fixed-point of a countable family of nonexpansive mappings. …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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Energy-aware Application Mapping onto 3D Mesh-Based Network-on-Chip using Heuristic Mapping Algorithms by Kiran K A, Jaison Jacob

“…The study&amp;rsquo;s objective is to estimate these algorithms&amp;rsquo; effectiveness in optimizing communication cost, communication energy, and CPU run time in both 2D and 3D mesh NoC architectures. …”
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An Active-Set Algorithm for Convex Quadratic Programming Subject to Box Constraints with Applications in Non-Linear Optimization and Machine Learning by Konstantinos Vogklis, Isaac E. Lagaris

“…The proposed method employs an active-set strategy with Lagrange multipliers, demonstrating rapid convergence. The algorithm, at each iteration, modifies both the minimization parameters in the primal space and the Lagrange multipliers in the dual space. …”
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COPSA: a computation offloading strategy based on PPO algorithm and self-attention mechanism in MEC-empowered smart factories by Yining Chen, Kai Peng, Chengfang Ling

“…A great number of experiments conducted on both simulated and real datasets have verified the superiority of our proposed approach compared to the state-of-the-art baselines.…”
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EVALUATION OF POSSIBILITIES TO IMPROVE ACCURACY CHARACTERISTICS FOR ALGORITHMS OF REFINEMENT ANGULAR VELOCITY OF BALLISTIC AND SPACE OBJECTS IN EARLY WARNING RADARS by Sergei V. Kovbasjuk, Felix M. Andreev, Andrei V. Statkus

“…Therefore, the article deals with the methodology of comparative evaluation accuracy characteristics of algorithms of refinement angular velocity ballistic and space objects and assessing the level of their improvement through the use of different variants of construction algorithm of increasing the accuracy of range higher order derivatives, including information on the third derivative of distance. …”
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Advancing Real-Time Food Inspection: An Improved YOLOv10-Based Lightweight Algorithm for Detecting Tilapia Fillet Residues by Zihao Su, Shuqi Tang, Nan Zhong

“…These residues negatively impact both the processing quality and the economic value of the product. …”
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Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation by Zlata R. Artyukova, Alexey V. Petraikin, Nikita D. Kudryavtsev, Fedor A. Petryaykin, Dmitry S. Semenov, Daria E. Sharova, Zhanna E. Belaya, Anton V. Vladzimirskyy, Yuriy A. Vasilev

“…At all stages, both artificial intelligence algorithms demonstrated sufficient metrics for clinical validation. …”
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