Secure edge-based smart grid communication using lightweight authentication modeling with autoencoders and real-world data by Omar Abdullah Saleh, Mesut Cevik

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Klasifikasi Multilabel Pada Gaya Belajar Siswa Sekolah Dasar Menggunakan Algoritma Machine Learning by I Kadek Nicko Ananda, Ni Putu Novita Puspa Dewi, Ni Wayan Marti, Luh Joni Erawati Dewi

“…The dataset used in this study is the Data Set of Learning Style Preference. The separation of the dataset was made into three different forms of data sizes, including: Data I: 90% training, 10% testing; Data II: 80% training 20% testing; and Data III: 70% training 30% testing. …”
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Effects of Biochar on Soil Quality in a Maize Soybean Rotation on Mollisols by Likun Hou, Yuchao Wang, Zhipeng Wang, Ruichun Gao, Xin Zhou, Siyu Yang, Xu Luo, Zhenfeng Jiang, Zhihua Liu

“…Principal component analysis was used to establish a minimum data set for the systematic analysis of soil quality and its factors. …”
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Enhancing fraud detection in imbalanced motor insurance datasets using CP-SMOTE and Random Under-Sampling by Pornpawee Komsrimorakot, Thitirat Siriborvornratanakul

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Early-Stage Non-Severe Depression Detection Using a Novel Convolutional Neural Network Approach Based on Resting-State EEG Data by Pascal Penava, Ricardo Buettner

“…With this result, we are setting a new benchmark for resting-state-based early detection. …”
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Data-Driven Fault Diagnosis in Water Pipelines Based on Neuro-Fuzzy Zonotopic Kalman Filters by Esvan-Jesús Pérez-Pérez, Yair González-Baldizón, José-Armando Fragoso-Mandujano, Julio-Alberto Guzmán-Rabasa, Ildeberto Santos-Ruiz

“…The approach involves two key steps: first, identifying the nonlinear pipeline system using an adaptive neuro-fuzzy inference system (ANFIS), resulting in a set of Takagi–Sugeno fuzzy models derived from pressure and flow data, and second, implementing a neuro-fuzzy ZKF bench to detect pipeline leaks and sensor faults with adaptive thresholds. …”
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Neutrosophic Topological Spaces for Lung Cancer Detection in Chest X-Rays: A Novel Approach to Uncertainty Management by A. A. Salama, Doaa E. Mossa, Mahmoud Y. Shams, Huda E. Khalid, Ahmed K. Essa

“…In this work, we propose a novel approach that use a Neutrosophic Topological Spaces (NTS) for the lung cancer detection in the chest X-ray images. Furthermore, the proposed NTS leverage the strengths points of Neutrosophic Sets (NS) which include the degrees of truth (T), indeterminacy (I), and falsity (F). …”
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Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches by T. Anitha Kumari, Sanket Mishra

“…These security breaches are caused by rudimentary and immature security protocols that are implemented on IoT devices. An intrusion detection system is used to detect security threats and system-level applications to detect malicious activities. …”
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PAdaptCD: Progressive Adaptive Thresholding and Bitemporal Image Augmentation for Semisupervised Change Detection by Linlin Wang, Junping Zhang, Dong Chen, Lorenzo Bruzzone

“…In addition, bitemporal image augmentation (BTIA) techniques are developed to better capture the specific properties of bitemporal data. BTIA first introduces a highly random intensity-based augmentation, which sets an appropriate degree of data augmentation. …”
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GA4RF: An Effective Fall Detection System Through Optimizing Random Forest Hyperparameters Using Genetic Algorithm With Mobile Sensor Data by Ha-Nam Nguyen, Hong-Lam Le, Ngo-Thi-Thu-Trang, Duc-Nhan Nguyen

“…However, improving the accuracy of the FDS is a significant challenge, particularly due to the difficulty in collecting comprehensive and accurate fall data which causes imbalance in datasets. In this paper, we introduce a Genetic Algorithm (GA) based Random Forest (RF) method, named GA4RF, to enhance the accuracy of fall detection models by optimizing their hyperparameters. …”
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Evaluation of Prostate Imaging Reporting and the PI-RADS Version 2 Data System for Prostate Cancer Detection: a Retrospective Single-Center Study by Lora Grbanović, Lucija Kovačević, Tomislav Kuliš, Željko Kaštelan, Marko Kralik, Stjepan Ivandić, Maja Prutki

“…This retrospective study aimed to evaluate the performance of multiparametric MRI (mpMRI) interpreted according to the Prostate Imaging Reporting and Data System (PIRADS) version 2 (v2) in detecting clinically significant prostate cancer (csPCa). …”
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Ability of verbal autopsy data to detect deaths due to uncontrolled hyperglycaemia: testing existing methods and development and validation of a novel weighted score by Justine I Davies, David Beran, Miles D Witham, Alisha N Wade, Amelia Crampin, Sarah Blackstock, Graham D Ogle

“…These diagnoses were also compared with diagnoses produced by a standard computer algorithm (InterVA-4).Setting This study was done using VA data from the Health and Demographic Survey sites in Agincourt in rural South Africa. …”
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Segmentation versus detection: Development and evaluation of deep learning models for prostate imaging reporting and data system lesions localisation on Bi‐parametric prostate magn... by Zhe Min, Fernando J. Bianco, Qianye Yang, Wen Yan, Ziyi Shen, David Cohen, Rachael Rodell, Dean C. Barratt, Yipeng Hu

“…The authors have (1) carefully compared performances of most‐developed segmentation and object detection methods in localising prostate imaging reporting and data system (PIRADS)‐labelled prostate lesions on MRI scans; (2) proposed an additional customised set of lesion‐level localisation sensitivity and precision; (3) proposed efficient ways to ensemble the segmentation and object detection methods for improved performances. …”
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Individual Tree Segmentation Based on Region-Growing and Density-Guided Canopy 3-D Morphology Detection Using UAV LiDAR Data by Shihua Li, Shunda Zhao, Zhilin Tian, Hao Tang, Zhonghua Su

“…This study proposes a novel method that combines the canopy height model (CHM) and point cloud data for segmenting individual trees and employs height and density information for morphological detection of tree canopies. …”
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Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

“…These findings enabled the development of visibility prediction maps, guiding the optimal timing of aerial surveys and minimizing the risk of unsuccessful data acquisition. The results underscore the effectiveness of integrating meteorological data with satellite imagery in archeological research. …”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…The decision fusion-based DCNN model, integrating HSI-EM, HSI-EN, CV-EM, and CV-EN data, achieved the highest accuracy in both training (94.3 %) and validation (93.8 %) sets. …”
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Machine vision model using nail images for non-invasive detection of iron deficiency anemia in university students by Jorge Raul Navarro-Cabrera, Miguel Angel Valles-Coral, María Elena Farro-Roque, Nelly Reátegui-Lozano, Lolita Arévalo-Fasanando

“…Despite the presence of false-negatives, the results showed a positive correlation with Rad-67 readings.ConclusionThe DenseNet169-based model proved to be a promising tool for non-invasive detection of iron deficiency anemia, with potential for application in clinical and educational settings. …”
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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…Looking ahead, the advancement of AML technologies in blockchain systems necessitates progress in several critical areas: the construction of AML datasets capable of addressing data imbalance and annotation uncertainty, development of trusted AML algorithms, design of detection mechanisms for covert financial activities, and formulation of privacy-preserving yet regulation-compliant AML solutions. …”
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DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION by Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

“…Moreover, these models have incomplete interpretation and optimization issues, which do not suit their application in a clinical setting. On this, we propose a novel framework for the detection of cardiovascular diseases and presiding analysis through multimodal data fusion, optimized neural networks, and explainable AI techniques. …”
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Research on Ship Feature Recognition and Tracking Method Based on Long-line Array Single-photon LiDAR by Ziqiang PENG, Han WANG, Ruikai XUE, Xiaokai SHE, Genghua HUANG

“…Owing to the inconsistency between the characteristics of surface ships and ground target, and the lack of relevant data sets, the current commonly used fitting methods cannot effectively perceive surface target characteristics. …”
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