Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms by S. Jayanthi, Swathi Sowmya Bavirthi, P. Murali, K. Vijaya Kumar, Hend Khalid Alkahtani, Mohamad Khairi Ishak, Samih M. Mostafa

“…Abstract The Distributed Denial of Service (DDoS) attack is uncontrollable and appears in different patterns and shapes; accordingly, it is not easily detected and solved with preceding solutions. …”
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Deciphering the complex links between inflammatory bowel diseases and NAFLD through advanced statistical and machine learning analysis by Deepak Kumar, Brijesh Bakariya, Chaman Verma, Zoltán Illés

“…The study was conducted on collected serum biomaker samples of 81 patients with Inflammatory Bowel Disease (IBD) of Changhua Christian Hospital in China, including 36 with Crohn’s disease (CD) and 45 with Ulcerative Colitis (UC) using Latent Semantic Analysis(LSA) and machine learning (ML) techniques.Machine Learning algorithms Random Forest (RF), Logistic Regression (LR), XGBoost (XGB), and Support Vector Classifier (SVC), were utilized to predict liver risk associated with conditions including Hepatitis, Autoimmune Hepatitis (AIH), Alcoholic Liver Disease (ALD), and Non-Alcoholic Fatty Liver Disease (NAFLD). …”
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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

“…Radiomic features were extracted from intratumoral and peritumoral regions of interest and analyzed using machine learning algorithms to develop a predictive classifier. …”
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Green cover change detection using a modified adaptive ensemble of extreme learning machines for North-Western India by Madhu Khurana, Vikas Saxena

“…The algorithm shows an average accuracy of 97.8% on both the datasets.…”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…To enhance model performance, the slime mould algorithm is employed for parameter optimization. Experimental results demonstrated that the hybrid model achieves excellent predictive accuracy, with crop yield prediction exceeding 99%. …”
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Grassland biome fragmentation analysis using sentinal-2 images and support vector machine learning model in South Africa by Andisani Netsianda, Paidamwoyo Mhangara, Eskinder Gidey

“…Given the paucity of research on the threatened ecosystem, the support vector machine learning algorithm (SVM) is employed to investigate fragmentation from 2016 to 2023. …”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Predictive Archaeological Risk Assessment at Reservoirs with Multitemporal LiDAR and Machine Learning (XGBoost): The Case of Valdecañas Reservoir (Spain) by Enrique Cerrillo-Cuenca, Primitiva Bueno-Ramírez

“…This study assesses the potential of using multitemporal LiDAR data and Machine Learning (ML)—specifically the XGBoost algorithm—to predict erosional and sedimentary processes affecting archaeological sites in the Valdecañas Reservoir (Spain). …”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…Abstract Analysis of small-molecule drug solubility in binary solvents at different temperatures was carried out via several machine learning models and integration of models to optimize. …”
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Multi-Dimensional AE Signal Features in Eccentrically Loaded Concrete Structures: A Machine Learning Classification for Damage Progression by Shilong Ding, Alipujiang Jierula, Abudusaimaiti Kali, Tong Han, Tae-Min Oh

“…This study employed K-means clustering algorithm and Gaussian mixture models (GMMs) to analyze AE signal features from reinforced concrete (RC) columns undergoing failure under the eccentric compression loading of different eccentricity. …”
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Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…This paper proposed a hybrid filter-wrapper algorithm for feature selection based on an index of important features used in the pavement classification task; it takes advantage of two pure methods: the fast speed of the filter and the efficiency of the wrapper method. …”
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A Deep Learning Model Leveraging Time-Series System Call Data to Detect Malware Attacks in Virtual Machines by A. Alfred Raja Melvin, Jaspher W. Kathrine, Andrew Jeyabose, D. Cenitta

“…The CNN model is compared with machine learning algorithms for the results and discussions, and it outperforms ML algorithms in terms of intrusion detection accuracy when utilizing novel time series system call data..…”
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Analisis Visual dan Machine Learning untuk Mengukur Validitas Dokumen Akademik Perpustakaan: Studi pada Data Turnitin by Hesti Ari Wardani, Imam Yuadi

“…Using a data visualization approach and machine learning algorithms, this research explores the relationship between Turnitin scores and document validity status. …”
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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

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Integration of machine learning and bulk sequencing revealed exosome-related gene FOSB was involved in the progression of abdominal aortic aneurysm by Xianlu Ma, Xianlu Ma, Hongjie Zhou, Hongjie Zhou, Ren Wang, Ren Wang

“…The CIBERSORT algorithm was utilized to analyze the correlation between these genes and immune cell infiltration. …”
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Deterministic Light Detection and Ranging (LiDAR)-Based Obstacle Detection in Railways Using Data Fusion by Susana Dias, Pedro J. S. C. P. Sousa, João Nunes, Francisco Afonso, Nuno Viriato, Paulo J. Tavares, Pedro M. G. P. Moreira

“…Using a data fusion approach, pre-existing knowledge about the track topography is incorporated into the LiDAR data processing pipeline in conjunction with the DBSCAN clustering algorithm to identify and classify potential obstacles based on point cloud density patterns. …”
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Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer by Longpeng Li, Longpeng Li, Jinfeng Zhao, Yaxin Wang, Zhibin Zhang, Wanquan Chen, Jirui Wang, Yue Cai

“…The prognostic signature (PCDRS) were constructed by the best combination of 101 machine learning algorithm combinations, and the C-index of PCDRS was compared with 30 published signatures. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…Th1/Th2 cytokines were collected at BSI onset, with LASSO regression and restricted cubic spline analysis used to refine predictors. Seven machine learning(ML) algorithm (XGBoost, Logistic Regression, LightGBM, RandomForest, AdaBoost, GBDT and GNB) were trained using 10-fold cross-validation and model performance was evaluated with the ROC, calibration plots, decision and learning curves and the Shapley Additive Explanations (SHAP) analysis. …”
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Estimating comprehensive growth index for drip-irrigated spring maize in junggar basin via satellite imagery and machine learning by Mingjie Ma, Jinghua Zhao, Tingrui Yang, Feng Liu, Yingying Yuan, Shijiao Ma, Zikang Chang

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