Enhancing cybersecurity through autonomous knowledge graph construction by integrating heterogeneous data sources by Hatoon Alharbi, Ali Hur, Hasan Alkahtani, Hafiz Farooq Ahmad

“…To evaluate the effectiveness of our proposed CKG, we formulate a set of queries as questions to validate the logical rules. …”
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New prospects of uranium mineralisation of the Trans-Urals based on regional geochemical survey data by L. A. Krinochkin, O. K. Krinochkina, V. I. Blokov

“…Besides the known Dolmatovsky and Khokhlovsky uranium ore regions, 31 AGAs with uranium specialisation were identified based on the geochemical data obtained in a well-developed and accessible site. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Multiple Imputations by Chained Equations (MICE) were applied separately to the training and testing sets to handle missing data. Borderline-SMOTE (Synthetic Minority Over-sampling Technique) was used on the training set to balance the dataset. …”
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Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

“…Data augmentation allows researchers to expand the dataset, providing a larger and more diverse set of examples for model training. …”
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Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning by Jungpil Shin, Abu Saleh Musa Miah, Koki Hirooka, Md. Al Mehedi Hasan, Md. Maniruzzaman

“…Many researchers analyzing handwriting data for PD detection typically rely on computing statistical features over the entirety of the handwriting task. …”
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A Deep Neural Network Approach for Drogue Detection Using Laboratory-Chroma Key Images by Dillon Miller, Sean Mccormick, Violet Mwaffo, Donald H. Costello

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Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach by Hadas Biran, Tamar Hashimshony, Tamar Lahav, Or Efrat, Yael Mandel-Gutfreund, Zohar Yakhini

“…SPIRAL is based on Gaussian statistics to detect all statistically significant biological processes in single cell, bulk and spatial transcriptomics data. …”
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Fault detection and classification of bipolar DC system with dedicated metallic return based on TF-ENSR by Bo Ren, Niancheng Zhou, Qianggang Wang

“…To address this, this paper proposes a data-driven protection method based on feature learning. …”
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An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method by Deepa Devasenapathy, Kathiravan Kannan

“…The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.…”
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Use of individual Google Location History data to identify consumer encounters with food outlets by Olufunso Oje, Ofer Amram, Perry Hystad, Assefaw Gebremedhin, Pablo Monsivais

“…Methods We leveraged GLH data previously collected from a sub-set of participants in the Washington State Twin Registry (WSTR). …”
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Automated detection and de novo structure modeling of nucleic acids from cryo-EM maps by Tao Li, Hong Cao, Jiahua He, Sheng-You Huang

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Impact of Phenological and Lighting Conditions on Early Detection of Grapevine Inflorescences and Bunches Using Deep Learning by Rubén Íñiguez, Carlos Poblete-Echeverría, Ignacio Barrio, Inés Hernández, Salvador Gutiérrez, Eduardo Martínez-Cámara, Javier Tardáguila

“…These findings define optimal scenarios for early-stage organ detection and support the integration of automated detection models into vineyard management systems. …”
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Nonlinear Model for Condition Monitoring and Fault Detection Based on Nonlocal Kernel Orthogonal Preserving Embedding by Bo She, Fuqing Tian, Weige Liang, Gang Zhang

“…Compared with KONPE and KPCA, NLKOPE combines both the advantages of KONPE and KPCA, and NLKOPE is also more powerful in extracting potential useful features in nonlinear data set than NLOPE. For the purpose of condition monitoring and fault detection, monitoring statistics are constructed in feature space. …”
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A digital twin framework with MobileNetV2 for damage detection in slab structures by Duong Huong Nguyen, Huan Nguyen, Xiaohong Gao

“…The defection of the damaged slab under static loads is analyzed with two-dimensional discrete wavelet theory (DWT), whereas the diagonal wavelets are used to extract images data set used to train the convolutional neural network (CNN). …”
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4D trajectory prediction and conflict detection in terminal areas based on an improved convolutional network. by Xin Ma, Linxin Zheng, Xikang Lu

“…The simulation experiment shows that the simulation experiment is carried out by introducing the real automatic dependent surveillance-broadcast (ADS-B) historical track data in the terminal area of the busy airport. The experimental results are compared with the experimental results of the single long short-term memory (LSTM) model and the gated recurrent unit (GRU) model in the same data set. …”
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A novel similarity-constrained feature selection method for epilepsy detection via EEG signals by Chunlei Shi, Jun Gao, Jian Yu, Lingzhi Zhao, Faxian Jia

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Non-Invasive Detection of Breast Cancer by Low-Coverage Whole-Genome Sequencing from Plasma by Li Peng, Ru Yao, Sihang Gao, Yang Qu, Li Qu, Jingbo Zhang, Yidong Zhou

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K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“…Additionally, the performance across four clusters demonstrates the positive impact of K-Means clustering in improving classification accuracy for specific data groups. As proven by the obtained results, integrating feature selection with ensemble learning is effective for phishing detection; moreover, the scalability and efficiency of such a solution in real-world applications are demonstrated. …”
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Automated detection of broiler vocalizations a machine learning approach for broiler chicken vocalization monitoring by Patricia de Carvalho Soster, Tomasz Grzywalski, Yuanbo Hou, Pieter Thomas, Annelike Dedeurwaerder, Maarten De Gussem, Frank Tuyttens, Paul Devos, Dick Botteldooren, Gunther Antonissen

“…An extension with a subset of the AudioSet dataset was made to include background sounds. …”
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Predicting Deep Venous Thrombosis Using Artificial Intelligence: A Clinical Data Approach by Aurelian-Dumitrache Anghele, Virginia Marina, Liliana Dragomir, Cosmina Alina Moscu, Mihaela Anghele, Catalin Anghel

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