Study on Microstructure Effect of Carbon Black Particles in Filled Rubber Composites by Li Hong Huang, Xiaoxiang Yang, Jianhong Gao

“…The results showed the following. (1) For the random models, if the difference of particle size was larger and particle distance was closer, stress distribution would be denser as well as the stress concentration would become greater. …”
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A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees by Joaquín Abellán, Javier G. Castellano, Carlos J. Mantas

“…As a benchmark point, the known Random Forest (RF) classification method is also used. …”
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A New Type of Eye Movement Model Based on Recurrent Neural Networks for Simulating the Gaze Behavior of Human Reading by Xiaoming Wang, Xinbo Zhao, Jinchang Ren

“…In contrast to conventional psychology-based eye movement models, ours is based on a recurrent neural network (RNN) to generate a gaze point prediction sequence, by using the combination of convolutional neural networks (CNN), bidirectional long short-term memory networks (LSTM), and conditional random fields (CRF). The model uses the eye movement data of a reader reading some texts as training data to predict the eye movements of the same reader reading a previously unseen text. …”
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Enhancing well-being in hybrid work: the crucial role of organizational support for Indonesia’s State Civil Apparatus by Despinur Dara, Susan Febriantina, Suwatno Suwatno

“…Using data from 533 respondents selected through simple random sampling, the analysis employed Structural Equation Modeling with a Generalized Least Squares estimation approach. …”
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Efektivitas Pemanfaatan Cyberspace dalam Penguatan Moderasi Beragama di Kalangan Mahasiswa Perguruan Tinggi Keagamaan Islam Swasta by Efi Tri Astuti

“…Forty students were selected through proportionate stratified random sampling. Data collection utilized tests, observations, and interviews, with analysis conducted using N-Gain Scores and Independent Sample T-Tests. …”
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Flight Delay Classification Prediction Based on Stacking Algorithm by Jia Yi, Honghai Zhang, Hao Liu, Gang Zhong, Guiyi Li

“…There are five supervised machine learning algorithms in the first-level learner of Stacking including KNN, Random Forest, Logistic Regression, Decision Tree, and Gaussian Naive Bayes. …”
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Two Strategies to Improve the Differential Evolution Algorithm for Optimizing Design of Truss Structures by Ching-Yun Kao, Shih-Lin Hung, Budy Setiawan

“…Three mutation strategies (DE/rand/1, DE/best/2, and DE/rand-to-best/1) are combined in the integrated mutation strategy to increase the diversity of random search and avoid premature convergence to a local minimum. …”
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Family Function and Academic Achievement: The Mediating Role of Noble Character by Rahmi Lubis, Lince Kristina Tafonao, Zain Adawiyah, Fonny Dameaty Hutagalung

“…In order to achieve the stated objective, 201 college students were selected using cluster stratified random sampling, which served as the sample in this explanatory quantitative research. …”
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PatCID: an open-access dataset of chemical structures in patent documents by Lucas Morin, Valéry Weber, Gerhard Ingmar Meijer, Fisher Yu, Peter W. J. Staar

“…Here, we compare PatCID with state-of-the-art chemical patent-databases. On a random set, PatCID retrieves 56.0% of molecules, which is higher than automatically-created databases, Google Patents (41.5%) and SureChEMBL (23.5%), as well as manually-created databases, Reaxys (53.5%) and SciFinder (49.5%). …”
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Examination Of Service Quality Levels Perceived By Students Who Participate In Youth Centre Activities by Hacı Ali Çakıcı, Yılmaz Aksoy

“…Population of the study consists of students who are members of Youth Centres within the body of Ministry of Youth and Sports of the Republic of Turkey, while the sample consists of 196 participants who were selected with random sampling method among students who are members of Youth Centres within the body of Ministry of Youth and Sports of the Republic of Turkey. …”
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A Comparative Study of Anomaly Detection Techniques for IoT Security Using Adaptive Machine Learning for IoT Threats by Dheyaaldin Alsalman

“…In this study, we introduce FusionNet, an innovative ensemble model that combines the strengths of multiple machine learning algorithms, namely Random Forest, K-Nearest Neighbors, Support Vector Machine, and Multi-Layer Perceptron, for enhanced anomaly detection. …”
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ANALYSIS ON DYNAMIC CHARACTERISTICS OF CYLINDRICAL ROLLER BEARING UNDER THE CONDITION OF ROTATIONAL SPEED FLUCTUATIONS by TU WenBing, HE HaiBin, LIU LePing, LUO Ya, WANG ChaoBing

“…Based on explicit dynamic LS-DYNA, the dynamic simulations for nonlinear operation process under three different rotational speed fluctuations（rectangular fluctuations, sinusoidal fluctuations and random fluctuations） were made, and the angular speed curve and slipping rate curve of cage and the contact force curve of between roller and inner ring and cage were obtained. …”
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Effect of Electroacupuncture at Baihui Acupoint on Magnetic Resonance Spectroscopy and Spatial Learning and Memory Ability in APP/PS1 Transgenic Mice by Yingzheng ZHANG, Peiyuan ZHUO, Ruhui LIN, Lidian CHEN

“…Objective:To investigate the effects of electroacupuncture (EA) at Baihui (DU20) acupoint on learning and memory ability and¹H magnetic resonance spectroscopy (¹H-MRS) in APP/PS1 transgenic mice.Methods:A male APP/PS1 transgenic mice mated with a wild type female mice and 15 bred APP/PS1 transgenic mice identified by PCR were randomly divided into the model group (<italic>n</italic>=7) and the EA group (<italic>n</italic>=8) according to a random number table, and 8 age-matched littermates were divided into the control group. …”
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PERSPEKTIF REMAJA TENTANG KESEHATAN REPRODUKSI SEBAGAI UPAYA PENCEGAHAN PENYIMPANGAN PERILAKU SEKSUAL DI KABUPATEN BEKASI by Maesaroh Maesaroh, Eka Kartikawati, Devi Anugrah

“…The study population was middle school students in Bekasi Regency, as many as six sample schools were selected using the random sampling technique. The research method used is descriptive quantitative. …”
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Efektivitas konseling kelompok dengan teknik modeling simbolik berbasis TPACK dalam meningkan kecerdasan emosi anak usia dini by Swasti Indrayani, Ni Ketut Suarni, Nyoman Dantes

“…The research sample used random sampling technique. Determination of the experimental class as a sample of this study using lottery technique, the number of samples taken as many as two classes with 8 students from Kindergarten A2 and 11 people from Kindergarten A1. …”
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Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model by Cihan Akyel, Bünyamin Ciylan

“…Artificial intelligence-based classification training using images as input takes a long time and requires high resource requirements such as Random Access Memory (RAM) and Graphics Processing Unit (GPU). …”
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Wireless Sensor Network Coverage Optimization Using a Modified Marine Predator Algorithm by Guohao Wang, Xun Li

“…To solve the coverage problem caused by the random deployment of wireless sensor network nodes in the forest fire-monitoring system, a modified marine predator algorithm (MMPA) is proposed. …”
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RESEARCH ON STIFFNESS-DAMPING FEATURE AND RIDE COMFORT FOR CROSS-ARM DAMPING SEAT OF SPECIAL VEHICLES by LI ZhanLong, ZHAO JunDuo, GAO ShanTie, QIN Yuan, YANG Qiang

“…The results show that the seat vertical acceleration under different speeds has the non-stationary random characteristic. The seat vibration intensifies with the increase of the speed. …”
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Investigating the Relationship between Attachment Styles and Academic Burnout: The Mediating Role of Alexithymia by Zahra Amanat, Majid Barzegar, Azarmidokht Rezaei, Hossein Bagholi

“…The target population comprised all high school students in the 2021 of Firozabad city, with a sample size of 285 individuals selected through multi-stage cluster random sampling. Data collection involved the utilization of Bresso et al.'…”
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Machine Learning-Based Network Detection Research for SDNs by Lai Jiayue

“…Employing a tactical blend of established and cutting-edge machine learning algorithms, including Random Forest, Logistic Regression, and Decision Tree, alongside the advanced XGBoost and LightGBM models, this study conducted an exhaustive investigation to pinpoint the most efficacious methods for swiftly and precisely identifying DoS threats. …”
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