An Efficient Deep Learning-Based Framework for Predicting Cyber Violence in Social Networks by Younes Fayand Fathabad, Mohammad Ali Balafar, Amin Golzari Oskouei, Kamal Koohi

“…However, this has also increased the prevalence of cyber violence, necessitating the development of automated detection methods. Deep learning-based algorithms have proven effective in identifying violent content, yet existing models often struggle with understanding contextual nuances and implicit forms of cyber violence. …”
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Driving Cycle for Passenger Cars on Urban Roads in Pristina, Kosovo by Flamur Salihu, Yusuf Kağan Demir

“…The driving cycle was developed by extracting the micro-trips from 53 491 s of data using a “3-sequential points” algorithm, where 780 micro-trips were detected. …”
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A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise. by Wei Zhang, Xiaolong Zhang, Juanjuan Zhao, Yan Qiang, Qi Tian, Xiaoxian Tang

“…However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccurate and inefficient. …”
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Enhanced Transformer Network With High-Dimensional Attention Mechanism for Diabetic Retinopathy Classification by M. Rizvana, Sathiya Narayanan

“…Various deep learning-based detection and classification algorithms have been developed to identify and categorize the disease. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Through empirical and statistical analysis, this study identifies top-performing algorithms. A Hybrid Framework for Real-Time Data Drift and Anomaly Identification Using Hierarchical Temporal Memory and Statistical Tests: This paper introduces a hybrid framework combining Hierarchical Temporal Memory and Sequential Probability Ratio Test for real-time data drift detection and anomaly identification. …”
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Optimal Poisson Cognitive System with Markov Learning Model by A. A. Solodov

“…The research method consists in the application of the simplest Markov learning model of Estes with a stochastic matrix with two states, in which the transition probabilities are calculated in accordance with the optimal Neуman-Pearson algorithm for detecting stimuli affecting the system. …”
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An Assessment of the Use of Visual Odometry in Localization by İ. Yakar, R. A. Kucak, S. Bilgi

“…The process commonly involves detecting and matching key points or features in the images, such as corners or edges, and then using algorithms to calculate the camera's motion. …”
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Convolutional Neural Network for the Classification of the Control Mode of Grid-Connected Power Converters by Rabah Ouali, Martin Legry, Jean-Yves Dieulot, Pascal Yim, Xavier Guillaud, Frédéric Colas

“…This classification poses a challenge as the TSO lacks precise knowledge of the actual control structures and algorithms. This paper introduces a novel classification algorithm based on Convolutional Neural Networks (CNN), capable of detecting patterns in sequential data. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…To maximize system energy efficiency, we propose an optimization method based on sequential convex optimization with linear state-space approximation. …”
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Research on an orchard row centreline multipoint autonomous navigation method based on LiDAR by Chen Zhenyu, Dou Hanjie, Gao Yuanyuan, Zhai Changyuan, Wang Xiu, Zou Wei

“…The method begins by constructing a three-dimensional (3D) point cloud map of the orchard via the LIO_SAM algorithm, and a 3D point cloud-to-two-dimensional (2D) grid map algorithm is designed. …”
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Accuracy Evaluation of Multi-Technique Combination Nonlinear Terrestrial Reference Frame and EOP Based on Singular Spectrum Analysis by Qiuxia Li, Xiaoya Wang, Yabo Li

“…The unlabeled jumps could be detected by the sequential <i>t</i>-test analysis of regime shifts (STARS) combined with the generalized extreme Studentized deviate (GESD) algorithms introduced in our earlier paper. …”
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Carbapenemases Produced by Multidrug-Resistant Strains of <i>Klebsiella Pneumoniae</i> Isolated from Intensive Care Patients by T. V. Chernenkaya, L. A. Borisova, T. Yu. Vorobieva, M. A. Godkov, A. K. Shabanov

“…In 11.3% of carbapenem-resistant strains, the production of KPC, OXA-48, NDM, VIM and IMP genes was not detected. When developing algorithms for antibacterial therapy, it is necessary to take into account that from 25.7% to 60.6% of K. pneumoniae strains in different intensive care units are the producers of metallobetalactamases.…”
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A METHOD OF ELIMINATING MALICIOUS PERTURBATIONS EMBEDDED BY L0-OPTIMIZED ATTACKS by Dmitry A. Yesipov, Nikita S. Sulimenko, Ilya Yu. Popov

“…Transformations such as bilinear interpolation and Telea algorithm were considered to restore modified pixels. …”
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DGM-TOP: automatic identification of the critical boundaries in atrial tachycardia by Robin Van Den Abeele, Sander Hendrickx, Niels Carlier, Eike M. Wülfers, Arthur Santos Bezerra, Bjorn Verstraeten, Sebastiaan Lootens, Karel Desplenter, Arstanbek Okenov, Timur Nezlobinsky, Annika Haas, Armin Luik, Sebastien Knecht, Mattias Duytschaever, Nele Vandersickel

“…The algorithm used analyzes the electroanatomical map of the patient, extracting the nodes at each boundary. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…Using a set of classical machine learning algorithms for predictive modelling (Random Forest, Gradient Boosting, XGBoost, Decision Tree, AdaBoost, Neural Networks, Extra Tree Classifier) and state of art methods such as sequential-attention based Tabent transfer learning, we explore the best performing models which are effective to predict the cognitive status of the subjects given certain clinical and other characteristics. …”
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Orchard: Building large cancer phylogenies using stochastic combinatorial search. by Ethan Kulman, Rui Kuang, Quaid Morris

“…Here, we introduce Orchard, a cancer phylogeny reconstruction algorithm that is fast and accurate using up to 1000 mutations. …”
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Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…Timely and accurate detection of crop diseases is essential for ensuring sustainable agricultural development and effective crop management. …”
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A stratified therapeutic model incorporated with studies on regulatory B cells for elderly patients with newly diagnosed multiple myeloma by Wenjiao Tang, Yan Li, Zhongqing Zou, Jian Cui, Fangfang Wang, Yuhuan Zheng, Li Hou, Ling Pan, Bing Xiang, Hong Chang, Li Zhang, Ting Niu

“…Methods In this open‐label, non‐interventional, prospective study in the real world, 159 newly diagnosed MM (NDMM) patients over 65 years old were sequentially recruited and bone marrow aspirates prior to treatment were obtained to detect the ratios of Bregs by flow cytometry. …”
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A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…Such algorithms provided prediction accuracies of 0.963, 0.739, 0.773, 0.866, and 0.866 sequentially. …”
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