Design of a Novel Adaptive Weighted Multiview Deep Neural Network for Enhanced Islanding Detection in Smart Distribution Systems by Hani Albalawi, Abdul Wadood, Syed Basit Ali Bukhari, Aadel Mohammed Alatwi

“…This paper develops a novel adaptive weighted multiview deep neural network (AWM-DNN) model for enhanced islanding detection in smart distribution networks. The proposed approach extracts distinct views from three-phase(3-<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>) voltage signal&#x2014;using time-domain (TD), frequency-domain (FD), and time-frequency-domain analysis (TFD). …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…After feature selection, an echo-state network (ESN) classifier is employed for detection and prediction. …”
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Sentiment Analysis and Emotion Detection on Cryptocurrency Related Tweets Using Ensemble LSTM-GRU Model by Naila Aslam, Furqan Rustam, Ernesto Lee, Patrick Bernard Washington, Imran Ashraf

“…In this regard, this study performs both sentiment analysis and emotion detection using the tweets related to the cryptocurrency which are widely used for predicting the market prices of cryptocurrency. …”
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Pig Detection Algorithm Based on Sliding Windows and PCA Convolution by Longqing Sun, Yan Liu, Shuaihua Chen, Bing Luo, Yiyang Li, Chunhong Liu

“…A two-level support vector machine model was trained to calculate the probabilities of sliding windows by using gradient and gray distribution features of pigs. The principal component analysis convolution kernels were trained to extract foreground and background features of pig images. …”
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Optimizing Heart Disease Prediction: A Comparative Analysis of Tree-Based Ensembles With Feature Expansion and Selection by K. Aswini, Kriti Arya

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Analysis of Factors Affecting Random Measurement Error in LiDAR Point Cloud Feature Matching Positioning by Guoliang Liu, Wang Gao, Shuguo Pan

“…Therefore, this work draws on the random measurement error analysis method of GNSS observations to study the impact of factors such as distance, angle, and feature accuracy on the random measurement error of LiDAR. …”
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A discriminant analysis of the P3b wave with electroencephalogram by feature‐electrode pairs in schizophrenia diagnosis by Juan I. Arribas, Luis M. San‐José‐Revuelta

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Winograd Transform-Based Fast Detection of Heart Disease Using ECG Signals and Chest X-Ray Images by Rishabh Anand, Adyasha Rath, Prabodh Kumar Sahoo, Prince Jain, Ganapati Panda, Xinhong Wang, Haipeng Liu

“…These features serve as inputs for AI-based detection models, with six machine learning (ML) and four deep learning (DL) models developed for HD detection. …”
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GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Current research on addressing engineering interference in GB-SAR deformation monitoring remains preliminary, with existing methods exhibiting limitations in interference pattern coverage, feature extraction, and algorithm robustness. To address these challenges, this article proposes a joint processing method integrating amplitude-phase feature analysis and robust regression. …”
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Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques by Azmath Mubeen, Uma N. Dulhare

“…Background/Objectives: Accurate detection and classification of nodules in medical images, particularly rheumatoid nodules, are critical due to the varying nature of these nodules, where their specific type is often unknown before analysis. …”
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One-Class Anomaly Detection for Industrial Applications: A Comparative Survey and Experimental Study by Davide Paolini, Pierpaolo Dini, Ettore Soldaini, Sergio Saponara

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Integrating multiple terrain features for artefact detection in the newly released TanDEM-X 30 m DEM and DCM over the Loess Plateau by Xingang Zhang, Shanchuan Guo, Zilong Xia, Haowei Mu, Bing Wang, Bin Cui, Hong Fang, Peijun Du

“…To address this limitation, a novel artefact detection framework integrating multiple terrain features was proposed. …”
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Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning by Jie Huang, Yanli Zhao, Zhanxiao Tian, Wei Qu, Xia Du, Jie Zhang, Meng Zhang, Yunlong Tan, Zhiren Wang, Shuping Tan

“…The effects of different emotional stimuli and the fusion of demographic information and MFCCs on schizophrenia detection were examined. Results The discriminant analysis results showed superior performance for neutral emotional stimuli compared to positive and negative stimuli. …”
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Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms by Manal Abdullah Alohali, Sultan Alahmari, Mohammed Aljebreen, Mashael M. Asiri, Achraf Ben Miled, Sami Saad Albouq, Othman Alrusaini, Ali Alqazzaz

“…Researchers have proposed numerous malware detection solutions for the past few years. Machine learning (ML) and deep learning (DL)-based detection models can decrease analysis time and increase malware detection accuracy. …”
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Enhanced visibility graph for EEG classification by Asma Belhadi, Pedro G. Lind, Pedro G. Lind, Pedro G. Lind, Youcef Djenouri, Youcef Djenouri, Anis Yazidi, Anis Yazidi

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KICA-DPCA-Based Fault Detection of High-Speed Train Traction Motor Bearings by Yunkai Wu, Yu Tian, Yang Zhou

“…To address the aforementioned issues, this paper proposes a method that combines Kernel Independent Component Analysis and Deep Principal Component Analysis (KICA-DPCA) to improve the accuracy of bearing fault detection. …”
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An Image Processing Approach to Quality Control of Drop-on-Demand Electrohydrodynamic (EHD) Printing by Yahya Tawhari, Charchit Shukla, Juan Ren

“…These stages collectively improve the precision and efficiency of EHD DoD printing analysis in terms of dot size and spacing. Edge and contour detection strategies are implemented to minimize edge discrepancies and accurately delineate droplet perimeters for quality analysis, enhancing measurement precision. …”
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A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture by Nitthita Chirdchoo, Suvimol Mukviboonchai, Weerasak Cheunta

“…Specifically, an automated feed tray captures images of live shrimp, which are then processed using a combination of Detectron2, PyTorch, and CUDA (Compute Unified Device Architecture) for individual shrimp detection. Essential features such as area, perimeter, width, length, and posture are extracted through image analysis, enabling accurate estimation of shrimp weight. …”
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Enhancing Change Point Detection Through Key Actor Identification: A Study in Cryptocurrency Transactions Networks by Ourania Theodosiadou, Andreas Kosmatopoulos, Christos Gkiourtzidis, Taxiarchis Skouras, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris

“…In addition, feature selection is applied to reduce overlapping information among the extracted features and, finally, change point detection is utilized to identify time locations of significant changes in the selected features. …”
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Detection of Geological Structures in the Gol Gohar Mining Iron Ore Area Using Airborne Magnetic Data by Abdullah Ezam Ahmady, Abdolhamid Ansari, Seyyed Hossein Mojtahedzadeh

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