An Integer Erasure Correction Coding and Its Application for Security Enhancement of Encryption by Miodrag J. Mihaljevic, Aleksandar Radonjic, Nevena Mijajlovic, Lianhai Wang, Shujiang Xu

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A comparison of modeling approaches for static and dynamic prediction of central line-associated bloodstream infections using electronic health records (part 2): random forest mode... by Elena Albu, Shan Gao, Pieter Stijnen, Frank E Rademakers, Christel Janssens, Veerle Cossey, Yves Debaveye, Laure Wynants, Ben Van Calster

“…Models including multiple outcome events (multinomial and competing risks) display a different internal structure compared to binary and survival models, choosing different variables for early splits in trees. …”
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Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

“…The first phase utilized J48, Classification and Regression Tree (CART), and Decision Stump (DS) to create a random forest model. …”
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Developing a hybrid feature selection method to detect botnet attacks in IoT devices by Alshaeaa H.Y., Ghadhban Z.M., Ministry of Education, Iraq

“…Several classification models including decision tree (DT), random forest (RF), k-nearest neighbors (KNN), adaptive boosting (AdaBoost), and bagging are utilized for the classification purpose. …”
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Using a 3D Chaotic Dynamic System as a Random Key Generator for Image Steganography by Mohammed Abod Husain, Saad Al-Momen

“…Furthermore, an algorithm is suggested to generate a random binary key, serving as the controller for the embedding process. …”
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Heavy Tailed Distribution of Binary Classification Model by Damilare Oladimeji, Emmanuel Oguntade, Samuel Olanrewaju

“…The proposed research incorporates the utilization of a heavy-tailed skewed distribution referred to as the inverse Weibull as a link function in the context of a binary classification model. This selection is motivated by the need to address the existence of rare or extreme events in random processes. …”
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Development of a Predictive Model for N-Dealkylation of Amine Contaminants Based on Machine Learning Methods by Shiyang Cheng, Qihang Zhang, Hao Min, Wenhui Jiang, Jueting Liu, Chunsheng Liu, Zehua Wang

“…Then, we applied four machine learning methods—random forest, gradient boosting decision tree, extreme gradient boosting, and multi-layer perceptron—to develop binary classification models for N-dealkylation. …”
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Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

“…Moreover, the features extracted with a histogram of oriented gradients (HOG), local binary pattern (LBP), and KAZE bands were integrated to evaluate using random forest, extreme gradient boosting, extra trees, and support vector classifier algorithms. …”
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Quasars Can Signpost Supermassive Black Hole Binaries by J. Andrew Casey-Clyde, Chiara M. F. Mingarelli, Jenny E. Greene, Andy D. Goulding, Siyuan Chen, Jonathan R. Trump

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Patient, Physician, and Assessor Blinding in Phase III Randomized Trials in Oncology: A Meta‐Epidemiological Analysis by Gabrielle Brown, Pavlos Msaouel, Avital M. Miller, Ramez Kouzy, Timothy A. Lin, Joseph Abi Jaoude, Ethan B. Ludmir, Alexander D. Sherry

“…ABSTRACT Background Blinding mitigates bias in randomized trials and may be especially crucial for surrogate endpoints, such as progression‐free survival (PFS). …”
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Optimal Coherence Length Control in Interferometric Fiber Optic Hydrophones via PRBS Modulation: Theory and Experiment by Wujie Wang, Qihao Hu, Lina Ma, Fan Shang, Hongze Leng, Junqiang Song

“…In this study, we propose a pseudo-random binary sequence (PRBS) phase modulation method for laser coherence length control, establishing the first theoretical model that quantitatively links PRBS parameter to coherence length, elucidating the mechanism underlying its suppression of parasitic interference noise. …”
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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The research evaluates and compares the performance of five algorithms - Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting - on a dataset containing clinical features of patients. …”
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Fundamental Parameters for Totally Eclipsing Contact Binaries Observed by TESS by Xu Ding, KaiFan Ji, ZhiMing Song, XueFen Tian, JinLiang Wang, ChuanJun Wang, QiYuan Cheng, JianPing Xiong

“…Our analysis identified 96 targets with mass ratios below 0.25, all of which were not listed in any previous catalog, thus signifying the discovery of new LMR system candidates. Assuming all 143 binary systems are affected by a third light during parameter estimation, we train a neural network (NN _l _3 ) model considering the third light. …”
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Applying binary mixed model to predict knee osteoarthritis pain. by Helal El-Zaatari, Liubov Arbeeva, Amanda E Nelson

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Short Paper - The Binary Linearization Complexity of Pseudo-Boolean Functions by Walter, Matthias

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Magnetic activities of two contact binaries in quadruple stellar systems by Yuangui Yang, Shuang Wang

“…Given the third light of $$\ell _3\sim 4.0\%$$ for HT Vir, we estimate the mass of the third body to be $$M_3=0.66(2)~\textrm{M}_{\odot }$$ . …”
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Distance-based target tracking algorithm in binary sensor network by SUN Xiao-yan1, LI Jian-dong1, HUANG Peng-yu1, ZHANG Wen-zhu1

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Integrated Imager and 3.22 <italic>&#x03BC;</italic>s/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing by Ruizhi Wang, Cheng-Hsuan Wu, Makoto Takamiya

“…This new approach employs a global-parallel processing concept, which enables multiply-and-accumulate operations (MACs) to be executed simultaneously within the imager array in a 2D manner, eliminating the additional latency associated with row-by-row processing and data access from random access memories (RAMs). In this design, convolution and subsampling operations using a <inline-formula> <tex-math notation="LaTeX">$3\times $ </tex-math></inline-formula> 3 kernel are completed within just nine steps of global-parallel processing, regardless of image size. …”
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Chaotic Binary Firefly Spectrum Allocation Strategy Based on Logistic Mapping by TENG Zhi-jun, ZHANG Hua, ZHANG Ai-ling, HAN Zhong-ting, ZHANG Heng-jia

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Efficient Phase Retrieval via Improved Binary Amplitude Modulation Masks by Chao Yang, Cheng Xu, Hui Pang, Jun Lan, Lixin Zhao, Song Hu, Wei Yan, Xianchang Zhu

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