Optimizing Location of Car-Sharing Stations Based on Potential Travel Demand and Present Operation Characteristics: The Case of Chengdu by Yu Cheng, Xu Chen, Xiaohua Ding, Linting Zeng

“…We select Chengdu where there are huge amounts of car-sharing travel demand and several large car-sharing operators as the research area and two main operators as the research objects. …”
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Design of a Non-Destructive Seed Counting Instrument for Rapeseed Pods Based on Transmission Imaging by Shengyong Xu, Rongsheng Xu, Pan Ma, Zhenhao Huang, Shaodong Wang, Zhe Yang, Qingxi Liao

“…After enhancing the contrast, the Sauvola algorithm was employed for threshold segmentation to remove the pod skin, followed by thinning and dilation of the binary image to extract and remove the central ridge lines, detecting the number and area of connected domains. …”
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Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

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Crack-Based Estimation of Seismic Damage Level in Confined Masonry Walls in the Lima Metropolitan Area Using Deep Learning Techniques by Miguel Diaz, Luis Lopez, Michel Amancio, Italo Inocente, Jhianpiere Salinas, Sergio Isuhuaylas, Erika Flores, Edisson Moscoso

“…A high-accuracy crack measurement technique was developed, combining a convolutional neural network to generate a binary crack mask and a binary search algorithm to extract polylines and convert them into length measurements, achieving a detection accuracy of 78%. …”
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Unravelling the human taste receptor interactome: machine learning and molecular modelling insights into protein-protein interactions by Harry Zaverdas, Filip Stojceski, Rocío Romero-Zaliz, Lampros Androutsos, Pantelis Makrygiannis, Lorenzo Pallante, Vanessa Martos, Gianvito Grasso, Marco A. Deriu, Konstantinos Theofilatos, Seferina Mavroudi

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A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

“…Utilizing a range of machine learning (ML) algorithms, our research applies multi-classification, data augmentation, and binary classification techniques to evaluate student outcomes effectively. …”
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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…To tackle these issues, our research focused on developing a predictive model for STEM students using advanced ensemble machine learning algorithms. …”
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Enhancing the Accuracy of Image Classification for Degenerative Brain Diseases with CNN Ensemble Models Using Mel-Spectrograms by Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim

“…The proposed ternary classification algorithm integrates the predictions of binary CNN classifiers through a majority voting ensemble strategy. …”
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Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…Abstract In the field of medical imaging, accurately classifying brain tumors remains a significant challenge because of the visual similarities among different tumor types. This research addresses the challenge of multiclass categorization by employing Support Vector Machine (SVM) as the core classification algorithm and analyzing its performance in conjunction with feature extraction techniques such as Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP), as well as the dimensionality reduction technique, Principal Component Analysis (PCA). …”
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NONLINEAR NYBERG CONSTRUCTION TRANSFORMS OVER ISOMORPHIC REPRESENTATIONS OF FIELDS GALOIS by A. V. Sokolov, O. N. Zhdanov

“…Further development of cryptographic algorithms based on the principles of many-valued logic requires more accurate research of non-binary cryptographic primitives – S-boxes. …”
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AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view by Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekani, Ahmad Bitarafan-Rajabi, Kouhyar Geravand, Parham Geramifar

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A model for identifying project sprint tasks based on their description by Marina Grinchenko, Mykyta Rohovyi

“…The article solves the following tasks: analyzing research on the classification and visualization of project tasks, developing an algorithm that can automatically classify text descriptions of sprint tasks, collecting and preparing a training sample of text descriptions of sprint tasks for training and testing the classification model, applying natural language processing methods to improve classification and ensure the accuracy of the results, validating the model on real data to assess the efficiency and accuracy of classification, and analyzing the results. …”
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Energy Demand Response in a Food-Processing Plant: A Deep Reinforcement Learning Approach by Philipp Wohlgenannt, Sebastian Hegenbart, Elias Eder, Mohan Kolhe, Peter Kepplinger

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A model for identifying project sprint tasks based on their description by Марина Гринченко, Микита Роговий

“…The article solves the following tasks: analyzing research on the classification and visualization of project tasks, developing an algorithm that can automatically classify text descriptions of sprint tasks, collecting and preparing a training sample of text descriptions of sprint tasks for training and testing the classification model, applying natural language processing methods to improve classification and ensure the accuracy of the results, validating the model on real data to assess the efficiency and accuracy of classification, and analyzing the results. …”
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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

“…Future research will explore the application of the vein imaging system in robotic venous blood collection to facilitate real-time puncture guidance.…”
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Fault recovery strategy for urban distribution networks using soft open points by Liangsheng Lan, Guangqi Liu, Sitong Zhu, Min Hou, Xinrui Liu

“…Based on the critical role of distributed generation (DG) power supply in fault recovery, this study proposes a method that leverages the synergistic capabilities of SOPs and DG to recover faults in distribution networks. By employing a binary particle swarm optimisation algorithm, this method effectively improves load recovery, reduces the number of switching operations, and minimises network loss. …”
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Finger Vein Recognition Using Optimal Partitioning Uniform Rotation Invariant LBP Descriptor by Bang Chao Liu, Shan Juan Xie, Dong Sun Park

“…Two finger vein databases are taken to test our algorithm performance. Experimental results show that proposed block selection algorithms can reduce the feature vector dimensionality in a large extent.…”
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Neonatal and perinatal mortality in the urban continuum: a geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania by Lenka Benova, Claudia Hanson, Aliki Christou, Aline Semaan, Peter M Macharia, Jessie Pinchoff, Andrea B Pembe

“…A three-category urbanicity measure (core urban, semi-urban and rural) was defined and compared with the binary DHS measure. Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. …”
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An ImmunoSignature test distinguishes Trypanosoma cruzi, hepatitis B, hepatitis C and West Nile virus seropositivity among asymptomatic blood donors. by Michael Rowe, Jonathan Melnick, Robert Gerwien, Joseph B Legutki, Jessica Pfeilsticker, Theodore M Tarasow, Kathryn F Sykes

“…Signals were used to train a single algorithm that distinguished all four disease states. …”
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Enhancing Flexibility of Virtual Power Plants Considering Reconfiguration of District Heating Network by Peinan Fan, Yixun Xue, Haotian Zhao, Xinyue Chang, Jia Su, Ke Wang, Hongbin Sun

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