Machine Learning-Based Ransomware Classification of Bitcoin Transactions by Suleiman Ali Alsaif

“…In this article, we propose a high-performance Bitcoin transaction predictive system that investigates Bitcoin payment transactions to learn data patterns that can recognize and classify ransomware payments for heterogeneous bitcoin networks into malicious or benign transactions. …”
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The impact of immune-related adverse events on the outcome of advanced gastric cancer patients with immune checkpoint inhibitor treatment by Tianhang Zhang, Haitao Lv, Jiasong Li, Shasha Zhang, Jingjing Zhang, Siqi Wang, Yingnan Wang, Yingnan Wang, Zhanjun Guo

“…In this study, we investigated individually the impact of the different irAEs on AGC survival as well as the co-occurrence patterns of multi-irAEs.MethodsThe uni-irAE, multi-irAEs, and non-irAE were identified based on National Comprehensive Cancer Network (NCCN) guidelines. …”
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A Multi-Epiphysiological Indicator Dog Emotion Classification System Integrating Skin and Muscle Potential Signals by Wenqi Jia, Yanzhi Hu, Zimeng Wang, Kai Song, Boyan Huang

“…Comprehensive feature extraction (time-domain, frequency-domain, nonlinearity) was conducted for each signal modality, and inter-emotional variance was analyzed to establish discriminative patterns. Four machine learning algorithms—Neural Networks (NN), Support Vector Machines (SVM), Gradient Boosting Decision Trees (GBDT), and XGBoost—were trained and evaluated, with XGBoost achieving the highest classification accuracy of 90.54%. …”
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Coexistence of CN1A autoantibodies in GAD65 encephalitis exacerbates neurodegeneration by Annika Breuer, Delara Kamalizade, Tobias Baumgartner, Juliane L. Berns, Thoralf Opitz, Franziska S. Thaler, Susanne Schoch, Lars Komorowski, Christoph Helmstaedter, Rainer Surges, Albert J. Becker, Julika Pitsch

“…Methods We combined a broad spectrum of approaches ranging from antibody-antigen identification, immunoblotting, immunoprecipitation, mass-spectrometry, cell-based assays, subcellular binding pattern analysis in primary neuronal cultures, and immunohistochemistry to in vitro assays of neuronal uptake, viability, and multi-electrode arrays. …”
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Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…Abstract This paper presents a modular and scalable intrusion detection framework that combines graph-based feature extraction, Transformer-based autoencoding, and contrastive learning to improve detection accuracy in cloud environments. Network flows are modeled as graphs to capture relational patterns among IP addresses and services, and a Graph Neural Network (GNN) is used to extract structured embeddings. …”
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Mapping and assessing the multifunctional demand for agricultural land based on the “P-E-F” framework: A case study of Hangzhou City, China by Qian Yu, Shan He, Chenxia Hu, Shixue You, Lin Lin, Yue Su, Congmou Zhu, Chenhe Zhou

“…However, the methodology for quantifying MAL demand is still exploratory and lacks a comprehensive evaluation system. This study thus proposed the “P-E-F” framework by integrating multi-source datasets (e.g., social network and remote sensing) in Hangzhou, China. …”
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An ECoG-Based Binary Classification of BCI Using Optimized Extreme Learning Machine by Xinman Zhang, Qi Xiong, Yixuan Dai, Xuebin Xu, Guokun Song

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Spatio-Temporal Evolution, Factors, and Enhancement Paths of Ecological Civilization Construction Effectiveness: Empirical Evidence Based on 48 Cities in the Yellow River Basin of... by Haifa Jia, Pengyu Liang, Xiang Chen, Jianxun Zhang, Wanmei Zhao, Shaowen Ma

“…This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. …”
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Multimodal Contrastive Learning for Remote Sensing Image Feature Extraction Based on Relaxed Positive Samples by Zhenshi Zhang, Qiujun Li, Wenxuan Jing, Guangjun He, Lili Zhu, Shijuan Gao

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Characteristics of pore-fracture structure and three-dimensional spatial distribution differences in deep and shallow coal reservoirs: A case study of Junggar Basin by WANG Pengxiang, ZHANG Zhou, YU Wanying, ZOU Qiang, YANG Zhengtao

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Accurate Indoor Home Location Classification through Sound Analysis: The 1D-ILQP Approach by Umut Erman, Türker Tuncer, Nura Abdullahi, Sengul Dogan, Erhan Akbal

“…The final step of our model involves classification, wherein we employed a range of classifiers, including decision trees, linear discriminant analysis, quadratic discriminant analysis, Naive Bayes, support vector machines, k-nearest neighbor, bagged trees, and artificial neural networks. We subjected the results to a comprehensive evaluation, and all classifiers achieved classification accuracies exceeding 80%. …”
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Integrating Fine-Grained Classification and Motion Relation Analysis for Face Anti-Spoofing by Ziyang Cheng, Xiafen Zhang

“…By introducing an attention mechanism, the MCAN uses the RAFT optical flow algorithm to adaptively focus on the direction and intensity of micro-movements in key face regions, distinguishing the natural movement of real faces from the static or repetitive motion patterns in spoofing attacks. Inspired by the latest face recognition research, the Distribution Based Additive Margin softmax-Similarity (DAMS-SIM) loss function is designed in the FGCN network to address the asymmetry between real and spoofed samples, enabling the network to capture the local fine-grained texture differences between real faces and spoofing attacks. …”
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Screening and regulatory mechanism exploration of M1 macrophage polarization and efferocytosis-related biomarkers in coronary heart disease by Hong Gao, Junhua Li, Jianxin Huang, Xiaojie Jiang

“…These biomarkers were subsequently leveraged to explore immune infiltration patterns and to construct a molecular regulatory network. …”
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An Overview of Neutrosophic Graphs by Nihar Ranjan Panda, Prasanta Kumar Raut, Amarendra Baral, Srikanta Kumar Sahoo, Sakya Singh Satapathy, Said Broumi

“…Image processing, social network analysis, pattern recognition, and decision-making in the face of uncertainty all use neutrosophic graphs. …”
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Attention-based multi-scale convolution and conformer for EEG-based depression detection by Ze Yan, Ze Yan, Ze Yan, Yumei Wan, Xin Pu, Xiaolin Han, Mingming Zhao, Haiyan Wu, Wentao Li, Xueying He, Yunshao Zheng

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A spatio-temporal node-place-ridership model for classifying metro station areas: The case of Shenzhen, China by Dejiang Wang, Jiangyue Wu, Zhuolin Tao

“…Using a case study in Shenzhen, China, results show that ridership is more associated with the place values (i.e., land-use pattern) than with the node values (i.e., network accessibility). …”
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Regional landslide hazard assessment using the IV-RF coupling model and critical monthly average rainfall threshold：A case study from Fuling District, Chongqing by Shuangqing PENG, Pengfei LIU, Gang CHEN, Liping WANG, Wei ZHANG, Wenwen LUO, Xiliang JING

“…Taking Fuling District of Chongqing as a case study, the information value model, BP neural network model, random forest model, information value-BP neural network coupled model, and information value-random forest coupled model were used to evaluate regional landslide susceptibility. …”
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MetaTrans-FSTSF: A Transformer-Based Meta-Learning Framework for Few-Shot Time Series Forecasting in Flood Prediction by Jiange Jiang, Chen Chen, Anna Lackinger, Huimin Li, Wan Li, Qingqi Pei, Schahram Dustdar

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A Supervised Approach for Land Use Identification in Trento Using Mobile Phone Data as an Alternative to Unsupervised Clustering Techniques by Manuel Mendoza-Hurtado, Gonzalo Cerruela-García, Domingo Ortiz-Boyer

“…By analyzing spatiotemporal patterns in CDRs, we trained and evaluated several classification algorithms, including k-nearest neighbors (kNN), support vector machines (SVM), and random forests (RF), to map land use categories, such as home, work, and forest. …”
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Similarity Analysis of Upper Extremity’s Trajectories in Activities of Daily Living for Use in an Intelligent Control System of a Rehabilitation Exoskeleton by Piotr Falkowski, Maciej Pikuliński, Tomasz Osiak, Kajetan Jeznach, Krzysztof Zawalski, Piotr Kołodziejski, Andrzej Zakręcki, Jan Oleksiuk, Daniel Śliż, Natalia Osiak

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