Pseudo chaotic pulse position modulation in UWB communications by XIANG Xin1, WANG Jie-ling2, ZENG Zhi-bin2, YI Ke-chu2, CHEN Shun-fang3

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Nutritional and prenatal care factors associated with low birth weight among full-term infants in public hospitals of Addis Ababa, Ethiopia by Berhanu Teshome Woldeamanuel, Merga Abdissa Aga

“…To account for hospital-level variability, a multilevel binary logistic regression model was employed, treating hospitals as random effects, to identify maternal, nutritional and prenatal care factors associated with LBW.Results The prevalence of LBW was 12%. …”
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Genome characterization through dichotomic classes: An analysis of the whole chromosome 1 of A. thaliana by Enrico Properzi, Simone Giannerini, Diego Luis Gonzalez, Rodolfo Rosa

“…In this article we show how dichotomic classes, binary variables naturally derived from a new mathematical model of the genetic code, can be used in order to characterize different parts of the genome. …”
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Evaluating Coastal Wetland Mapping Accuracy with High-Resolution Multi-spectral Imagery and LiDAR Remote Sensing Data by M. Anokye, L. Hashemi-Beni

“…The study also addresses binary classification for wetland and non-wetland classification and a multi-classification for different wetland classes, leveraging on the Random Forest algorithm which significantly improved the overall accuracy of wetland mapping. …”
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Effective breastfeeding practices among mothers exclusively breastfeeding infants in Ethiopia by Yonas Abebe, Beriso Dadi

“…In the multivariable binary logistic analysis, postpartum counselling (AOR = 2.61; 95 % CI 1.27, 5.39), breastfeeding experience (AOR = 6.08; 95 % CI 1.34, 27.39), postpartum breastfeeding demonstration (AOR = 4.14; 95 % CI 1.13, 15.2) and attending four or more antenatal care visits (AOR = 4.41; 95 % CI 2.3, 8.35) were factors significantly associated with effective breastfeeding practice. …”
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Supervised Machine Learning for Real-Time Intrusion Attack Detection in Connected and Autonomous Vehicles: A Security Paradigm Shift by Ahmad Aloqaily, Emad E. Abdallah, Hiba AbuZaid, Alaa E. Abdallah, Malak Al-hassan

“…The selected algorithms encompassed Decision Trees, Random Forests, Naive Bayes, Logistic Regression, XG Boost, LightGBM, and Multi-layer Perceptrons. …”
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A cross-national analysis of childhood predictors of daily smoking in adulthood by Sung Joon Jang, Pedro A. de la Rosa, R. Noah Padgett, Matt Bradshaw, Tyler J. VanderWeele, Byron R. Johnson

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Central obesity is an independent risk factor of poor glycaemic control at Dr George Mukhari Academic Hospital by Tsakani Stanford Mashele, Motetelo Alfred Mogale, Olakunle Adewunmi Towobola, Mmampenani Florence Moshesh

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A Mathematical Approach for Computing the Linear Equivalence of a Periodic Key-Stream Sequence Using Fourier Transform by Baghdad Science Journal

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H∞ Control for Network-Based 2D Systems with Missing Measurements by Bu Xuhui, Wang Hongqi, Zheng Zheng, Qian Wei

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Decoding Lung Cancer Radiogenomics: A Custom Clustering/Classification Methodology to Simultaneously Identify Important Imaging Features and Relevant Genes by Destie Provenzano, John P. Lichtenberger, Sharad Goyal, Yuan James Rao

“…The algorithm was run as follows: (1) genetic clusters were initialized using random clusters, binary matrix factorization, or k-means; (2) image classification was run on CT data for these genetic clusters; (3) misclassified subjects were re-classified based on the image classification algorithm; and (4) the algorithm was run until an accuracy of 90% or no improvement after 10 runs. …”
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Challenges and Opportunities for the Agricultural Producers in Sinana District in Reflection of COVID-19 Pandemic by Meskerem Abebe, Alemayehu Legesse, Fekadu Gadisa, Munira Hussen

“…The data were analyzed using multilevel binary logistic random intercept regression models with maximum-likelihood parameter estimation. …”
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A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing by Md. Alamin Talukder, Md. Ashraf Uddin, Suman Roy, Partho Ghose, Smita Sarker, Ansam Khraisat, Mohsin Kazi, Md Momtazur Rahman, Musawer Hakimi

“…Additionally, to mitigate class imbalance, Random OverSampling (ROS) is employed, leading to significant improvements in model performance. …”
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Fall Detection Using Federated Lightweight CNN Models: A Comparison of Decentralized vs. Centralized Learning by Qasim Mahdi Haref, Jun Long, Zhan Yang

“…The models were trained using three random seeds to ensure result robustness and stability across varying data partitions. …”
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Determinants of household-level food and nutrition security in wheat farmers of Arsi Zone, Ethiopia by Mustefa Bati Geda, Jema Haji Mohammed, Kedir Jemal Ibrahim, Fresenbet Zeleke Abshiro

“…Hence, determining the variables influencing the food and nutrition security of wheat farmers in Arsi Zone of Ethiopia’s was the aim of this study. A random sampling technique was used to collect primary data from 422 households spread over three districts. …”
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Exploring Voice Acoustic Features Associated with Cognitive Status in Korean Speakers: A Preliminary Machine Learning Study by Jiho Lee, Nayeon Kim, Ji-Wan Ha, Kyunghun Kang, Eunhee Park, Janghyeok Yoon, Ki-Su Park

“…Four machine learning models were tested for three binary classification tasks. Voice acoustic features were extracted and analyzed. …”
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Plant leaf classification using the multiscale entropy of curvature and feature aggregation by Raphael G. Pinheiro, José G.F. Lopes, Marcelo M.S. Souza, Fátima N.S. Medeiros

“…The texture descriptor combines the statistics of the local binary pattern and gray-level co-occurrence matrix. …”
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Overweight and obesity among Saudi university students and their relationships with various lifestyle habits: a cross-sectional study by Gamil Ghaleb Alrubaiee, Talal Ali Alqalah, Sameer A Alkubati, Nabil A Al-Rabeei

“…Methods A descriptive cross-sectional study was conducted between January and March 2023. A random sample of 420 students aged 21–26 years was selected with a male-to-female ratio of 0.99:1. …”
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Comparison of extractive distillation flowsheets for methanol–tetrahydrofuran–water mixtures by V. M. Raeva, A. M. Dubrovsky

“…The flowsheets consist of three (schemes I–III) or four (scheme IV) distillation columns operating at atmospheric pressure. …”
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The value of MRI-based radiomics and clinicoradiological data for the detection of forkhead box protein A1 gene mutated prostate cancer by Lin Deng, Ruchuan Chen, Bingni Zhou, Guoqing Hu, Hualei Gan, Ling Zhang, Liangping Zhou, Kefu Liu, Xiaohang Liu

“…Totally 367 prostate cancer patients (109 with FOXA1 mutations and 258 without) from three centers underwent multiparametric MRI. Patients from Center 1 (n = 236) were randomly divided into training and internal validation sets (7:3). …”
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