Hybrid ML Algorithm for Fault Classification in Transmission Lines Using Multi-Target Ensemble Classifier with Limited Data by Abdallah El Ghaly

“…The proposed algorithm achieved an impressive overall accuracy of 0.829165, outperforming traditional methods, including the K-Nearest Neighbors Classifier, support vector classification, random forest classifier, decision tree classifier, AdaBoost classifier, gradient boosting classifier, and Gaussian NB. …”
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Evaluation of Bus Networks in China: From Topology and Transfer Perspectives by Hui Zhang, Peng Zhao, Yinhai Wang, Xiangming Yao, Chengxiang Zhuge

“…The adding method includes four types among nodes with random choice, large transfer time, degree, and small degree. …”
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The effect of education costs and location on the decision of parents to enroll children in an integrated islamic elementary school through a reference group in tangerang and jakar... by Rahayu Lestari

“…Sampling was based on a purposive sampling method of 100 respondents in Tangerang and South Jakarta using proportional random sampling in Tangerang and South Jakarta. The analytical method used is statistical-partial least square using SEM Lisrel 8.70 analysis software tools. …”
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High order DPA with profiling by Zhen WU, Yi WANG, Guanhao ZHOU

“…In side channel attack,the masking implementation is one of the most popular counter measures again first order DPA.Presently,high order DPA and high order template attack are often used to attack against masking counter measures.High order DPA,however,targets joint leakage of multiple types of information and therefore needs cross combination of powers at corresponding positions,which is the root of the inefficiency of high order DPA.High order template attack,on the other hand,has to know the random mask in each encrypting at its learning phase,which is rarely satisfied for most adversaries.Be aware of these shortcomings and limitations,the algorithm of high order DPA with profiling used neural network to establish the model of fitting the combination of un-masked intermediate values.Attacking was based on the correlation coefficient between the fitted combination intermediate value and the guessing combination intermediate value.This method eliminated the requirement of knowing the masks at the learning phase of template attack and the requirement of cross combination of powers for high order DPA,and therefore lowered the requirement of learning as well as improved attacking efficiency.Experiments have confirmed the feasibility of this algorithm,as well as its efficiency.…”
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The Profit Distribution of Supply Chain under E-Commerce by Jiang-Hua Zhang, Rui-Rui Yin, Jin Zhang, Meng-Jiao Nie

“…The profit function of supply chain under e-commerce is formulated by taking the price of product and the maximum supply amount under certain investment as decision-making variables and taking the expected value of random variables of price as the setting sales quantity. …”
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STUDY ON CONTACT DAMAGE OF WIND POWER GEARS BASED ON CONFIGURATIONAL FORCE THEORY by YE Nan, ZHANG YanHui, WANG Rong, LIU Ran, ZHANG ChuanFen, OUYANG Heng, DUAN ShuYong

“…The gear box of wind turbine is in the complex environment such as random wind load for a long time， and the gear contact fatigue becomes a key factor limiting the stability and reliability of wind turbine equipment. …”
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Classification of Gastrointestinal Diseases Using Hybrid Recurrent Vision Transformers With Wavelet Transform by Biniyam Mulugeta Abuhayi, Yohannes Agegnehu Bezabh, Aleka Melese Ayalew, Miraf Alemayehu Lakew

“…The classification phase employs an ensemble of four classifiers: support vector machines, Bayesian network, random forest, and logistic regression. The system was trained and tested on the Hyper–Kvasir dataset, the largest publicly available GI tract image dataset, achieving an accuracy of 99.13% and an area under the curve of 0.9954. …”
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Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks by Wei Zhao, Zhenmin Tang, Yuwang Yang, Lei Wang, Shaohua Lan

“…Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.…”
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Design and optimization for wireless-powered IRS-aided mobile edge computing system by Dong TANG, Xuwei HUANG, Zhiwei LUO, Sai ZHAO, Gaofei HUANG

“…A new design of intelligent reflecting surface (IRS)-aided mobile edge computing (MEC) system was studied, which consisted of a hybrid access point (HAP) connected with an MEC server, an IRS equipped with radio-frequency (RF) energy harvesting (EH) circuits, and a user side with random task arrival.To reduce energy consumption at the user, a novel protocol was proposed first, in which the system was enabled to select a proper operation mode among an EH mode, an IRS-aided task offloading mode, and an IRS-inactive task offloading mode.Then, based on the proposed protocol, an optimization problem was formulated, which aimed at minimizing the amount of consumed energy at the user by optimizing the selection of system operation mode and the resource allocation in each mode.Lyapunov optimization framework was employed to solve the problem to achieve a low-complexity and efficient optimization algorithm.Simulation results show that the proposed scheme can save 50% to 90% of energy consumption for the MEC system as compared with the existing baseline schemes.…”
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Training of Executive Functions in Children: A meta-analysis of cognitive training interventions by Efsun Birtwistle, Olga Chernikova, Miriam Wünsch, Frank Niklas

“…The results ( N = 57) of a random-effects-model showed that cognitive training was effective with a total effect size of g = 23 The training was more effective for younger compared to older children. …”
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Blind mask template attacks on masked cryptographic algorithm by Yi WANG, Zhen WU, Bing LIN

“…Masking is a countermeasure against differential power analysis (DPA) attacks on cryptographic devices by using random masks to randomize the leaked power of sensitive information.Template attacks (TA) against cryptographic devices with masking countermeasure by far require attackers have knowledge of masks at the profiling phase.This requirement not only increase the prerequisite of template attacking,but also lead to some sort of difference between the experimental encryption codes of the profiling device and the codes of commercial cryptographic devices,which might degrade performance in real world attacking.Blind mask template attack directly learns templates for the combination of no mask intermediate values without the need of knowing the masks of training power traces,and then uses these templates to attack masked cryptographic devices.Both traditional Gaussian distribution and neural network were adopted as the templates in experiments.Experimental results verified the feasibility of this new approach.The success rate of neural network based blind mask template attacking against masked cryptographic devices is very close to that of traditional template attacks against cryptographic devices without masking countermeasure.…”
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Efektivitas pendekatan konseling rational emotif behavioral dengan teknik reframing untuk meningkatkan kecerdasan emosional siswa sekolah menengah pertama by Wayan Winda Yani, Ni Ketut Suarni, I Ketut Dharsana

“…The method used in this study is experimental. Sampling using random sampling technique. Collecting data using emotional intelligence questionnaire. …”
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The estimation of correlation between milk and reproductive traits in holstein by canonical correlation analysis by İsmet Doğan

“…The process ot maximizing the correlation between two linear function ot two sets of random variables is known as Canonical Correlation Analysis, Canonical Correlation Analysis is a statistical method which has been used to describe the re latıonshıp between a set o! …”
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Advancements in Machine Learning and Deep Learning Techniques for Crop Yield Prediction: A Comprehensive Review by V. Ramesh and P. Kumaresan

“…To accomplish this, we have surveyed the optimization algorithms implemented in conjunction with the Random Forest and Cat Boost models. A survey made across multiple databases to determine the effectiveness of crop yield prediction and analysis was performed on the included articles. …”
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Academic progress monitoring through neural network by Ramri Shukla, Bardia Khalilian, Sara Partouvi

“…Students are classified using artificial neural networks and random forests in this article. A private higher education provider provided a dataset of 2000 students. …”
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ADOPTION LEVEL OF GREEN PRACTICES AND ITS EFFECT ON EMPLOYEE’ PERFORMANCE by Ali Erbaşı, Gökhan Akandere

“…The sample of the study is 2,000 employees using simple random sampling method for in the company in 39 province. …”
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A Dynamic Task Scheduling Algorithm for Airborne Device Clouds by Bao Deng, Zhengjun Zhai

“…The task scheduling model based on genetic algorithm and random scheduling algorithm is compared through comparison experiments, which show that the assignment time of the task scheduling model based on genetic algorithm is shortened by 11.82% to 48.51% and the energy consumption is reduced by 22.28% to 47.52% under different load conditions.…”
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Foundation of Voronezh State University by M. D. Karpachev

“…This  relocation was not a random event since Voronezh was an administrative,  economic and cultural centre of Black Earth Region of Russia. …”
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Achieving employee engagement through effective internal communication by Senelisiwe Mbhele, Estelle de Beer

“…To illustrate how employee engagement can be achieved through internal communication, a quantitative research approach was used to obtain data from a sample of 300 respondents identified by means of systematic random sampling from a population of 1 322 employees from the case organisation. …”
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Cloning a Chloroplast Genome in Saccharomyces cerevisiae and Escherichia coli by Emma Walker, Bogumil Karas

“…These methods lack design flexibility as they are reliant upon the random capture of genomic fragments during BAC/YAC library creation; additionally, both demonstrated a low efficiency (≤ 10%) for correct assembly of the genome in yeast. …”
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