Collaborative filtering based on nonnegative/binary matrix factorization by Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo, Kazue Kudo

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Marine Mammals Classification using Acoustic Binary Patterns by Maheen NADIR, Syed Muhammad ADNAN, Sumair AZIZ, Muhammad Umar KHAN

“…Prior methods for classification focused on spectral features which result in increasing bias for contour base classifiers in automatic detection algorithms. In this study, acoustic marine mammal classification is performed through the fusion of 1D Local Binary Pattern (1D-LBP) and Mel Frequency Cepstral Coefficient (MFCC) based features. …”
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On the modification of bit-flipping decoder of LDPC-codes by S. S. Gurskiy, N. S. Mogilevskaya

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Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel, Hetal Bhavsar

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Decoding Artificial Intelligence: A Tutorial on Neural Networks in Behavioral Research by Javier Martínez-García, Juan José Montaño, Rafael Jiménez, Elena Gervilla, Berta Cajal, Antonio Núñez, Federico Leguizamo, Albert Sesé

“…- Simplifying Complex Concepts: This tutorial helps to demystify ANNs by breaking down the backpropagation algorithm into manageable steps. Readers will gain hands-on experience in Python, empowering them to confidently replicate analyses for regression and classification tasks without feeling overwhelmed…”
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Binary program taint analysis optimization method based on function summary by Pan YANG, Fei KANG, Hui SHU, Yuyao HUANG, Xiaoshao LYU

“…Taint analysis is a popular software analysis method, which has been widely used in the field of information security.Most of the existing binary program dynamic taint analysis frameworks use instruction-level instrumentation analysis methods, which usually generate huge performance overhead and reduce the program execution efficiency by several times or even dozens of times.This limits taint analysis technology’s wide usage in complex malicious samples and commercial software analysis.An optimization method of taint analysis based on function summary was proposed, to improve the efficiency of taint analysis, reduce the performance loss caused by instruction-level instrumentation analysis, and make taint analysis to be more widely used in software analysis.The taint analysis method based on function summary used function taint propagation rules instead of instruction taint propagation rules to reduce the number of data stream propagation analysis and effectively improve the efficiency of taint analysis.For function summary, the definition of function summary was proposed.And the summary generation algorithms of different function structures were studied.Inside the function, a path-sensitive analysis method was designed for acyclic structures.For cyclic structures, a finite iteration method was designed.Moreover, the two analysis methods were combined to solve the function summary generation of mixed structure functions.Based on this research, a general taint analysis framework called FSTaint was designed and implemented, consisting of a function summary generation module, a data flow recording module, and a taint analysis module.The efficiency of FSTaint was evaluated in the analysis of real APT malicious samples, where the taint analysis efficiency of FSTaint was found to be 7.75 times that of libdft, and the analysis efficiency was higher.In terms of accuracy, FSTaint has more accurate and complete propagation rules than libdft.…”
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Fragmentation of young massive clusters in binary components: an application of Griddy Gibbs Sampler by Abisa Sinha Adhikary, Ankita Das

“…Binary masses, fitted to suitable bi-variate distributions, were simulated using Griddy Gibbs sampler, a Markov Chain Monte Carlo (MCMC) algorithm. …”
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A High Performace of Local Binary Pattern on Classify Javanese Character Classification by Ajib Susanto, Daurat Sinaga, Christy Atika Sari, Eko Hari Rachmawanto, De Rosal Ignatius Moses Setiadi

“…In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. …”
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Prediction of Enthalpy of Mixing of Binary Alloys Based on Machine Learning and CALPHAD Assessments by Shuangying Huang, Guangyu Wang, Zhanmin Cao

“…We obtained data for 583 binary alloy systems from the SGTE database, ensuring experimental constraints for accuracy. …”
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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…This study evaluates seven binary classification algorithms, including Random Forests, Logistic Regression, Naive Bayes, K-Nearest Neighbors (kNN), Support Vector Machines, Gradient Boosting, and Artificial Neural Networks, to understand their effectiveness in predicting CVD. …”
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Research on the connectivity reliability analysis and optimization of natural gas pipeline network based on topology by Xiuxuan Yang, Kun Chen, Minghui Liu

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A binary gridding path-planning method for plant-protecting UAVs on irregular fields by Wang-ying XU, Xiao-bing YU, Xin-yu XUE

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Colony Binary Classification Based on Persistent Homology Feature Extraction and Improved EfficientNet by Zumin Wang, Ke Yang, Jie Tang, Jun Gao, Yuhao Zhang, Wei Xu, Chun-Ming Huang

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Efficient Context-Preserving Encoding and Decoding of Compositional Structures Using Sparse Binary Representations by Roman Malits, Avi Mendelson

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Leveraging machine learning and Landsat time series for high-resolution mapping of mining-induced vegetation changes in Ouagadougou, Burkina Faso by Oussama Himmy, Thanh Thi Nguyen, Katharina Salomea Hemmler, Safia Loulad, Hassan Rhinane, Andreas Buerkert

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Choosing the Right Metrics: A Study of Performance Measurement for Binary Classification in Imbalanced and Big Data by Mary Anne Walauskis, Taghi M. Khoshgoftaar

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Employee attendance system using face recognition and GPS using local binary pattern histogram by Narahari Vigraha Prasada, Ikrimach

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Physical Parameters of 12,201 ASAS-SN Contact Binaries Determined by a Neural Network by Kai Li, Li-Heng Wang

“…This paper builds on prior research to present an advanced neural network model combined with the Markov Chain Monte Carlo algorithm and including spot parameters. …”
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An efficient binary spider wasp optimizer for multi-dimensional knapsack instances: experimental validation and analysis by Mohamed Abdel-Basset, Reda Mohamed, Karam M. Sallam, Ibrahim Alrashdi, Ibrahim A. Hameed

“…The classical methods could not achieve acceptable results for this problem in a reasonable amount of time. Therefore, the researchers have recently turned their focus to metaheuristic algorithms to address this problem more accurately and in an acceptable amount of time. …”
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Identification of Papua Cenderawasih Batik Motifs using Local Binary Pattern and K-Nearest Neighbor by Dian Dwi Ariani, Sitti Zuhriyah, Eva Yulia Puspaningrum, Mahabintang Pallawabonang

“…The results of this study show that image processing technology could help protect Papuan batik. Future research could improve model accuracy by utilizing larger data sets and classification algorithms to make the models more accurate.…”
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