A Machine Learning-Based Ransomware Detection Method for Attackers’ Neutralization Techniques Using Format-Preserving Encryption by Jaehyuk Lee, Jinwook Kim, Hanjo Jeong, Kyungroul Lee

“…A newer approach measures file entropy to detect infected files, but attackers counter this by using encoding algorithms like Base64 to bypass detection thresholds. …”
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Mechanical Impedance Control in the Human Arm While Manually Transporting an Open-Top Fluid Filled Dish by Navit Roth, Rami Seliktar, Joseph Mizrahi

“…Redundancies in the numerical solution were eliminated using multicollinearity diagnostic algorithms. The results revealed that the wrist joint was found to have constant stiffness and damping and no regulation of these coefficients was necessary during gait. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…Six machine learning algorithms are utilized: support vector machine (SVM), backpropagation (BP) neural network, gaussian process regression (GPR), extreme gradient boosting (XGBoost), K-nearest neighbor (KNN), and random forest (RF). …”
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DEVELOPMENT OF A METHOD FOR ANALYZING TOMOGRAPHIC IMAGES OF BONE STRUCTURES by Hanna Abramova, Oleh Avrunin

“…In the course of the research, algorithms for processing and analyzing input images were developed, taking into account the modality of the input data. …”
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Sentiment analysis of pilgrims using CNN-LSTM deep learning approach by Aisha Alasmari, Norah Farooqi, Youseef Alotaibi

“…This paper provides a combination of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) algorithms for sentiment analysis of pilgrims using a novel and specialized dataset, namely Catering-Hajj. …”
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Expedited re-design of multi-band passive microwave circuits using orthogonal scaling directions and gradient-based tuning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…Nonetheless, if the intended frequencies are distant from the ones at the starting point, local search procedures tend to fail, whereas global search algorithms are computationally expensive. As recently demonstrated, a combination of large-scale concurrent geometry parameter scaling with intermittent local tuning allows for dependable re-design of high-frequency circuits at low CPU costs. …”
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Opinion Mining on Viet Thanh Nguyen’s The Sympathizer Using Topic Modelling and Sentiment Analysis by Sea Yun Ying, Pantea Keikhosrokiani, Moussa Pourya Asl

“…In addition, Python is used as the analytical tool for this project as it supports two LDA algorithms: Gensim and Mallet. To overcome the limitation that the performance of the model relies on the available libraries in Python, the study employs machine learning approach. …”
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Recent Tools of Software-Defined Networking Traffic Generation and Data Collection by Tabarak Khudhair, Omar Athab

“…Results show success in generating several types of network metrics to be used in the future for training machine or deep learning algorithms. Therefore, when generating data for the purpose of congestion control, iperf3 is the best tool, whilst Ping is useful when generating data for the purpose of detecting distributed denial-of-service attacks. …”
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Identification of stable housekeeping genes for induced pluripotent stem cells and -derived endothelial cells for drug testing by Sheena L. M. Ong, Hans J. Baelde, David G. P. van IJzendoorn, Judith V. M. G. Bovée, Karoly Szuhai

“…This panel was analyzed and ranked based on stability using five algorithms, delta-Ct, bestkeeper, geNorm, Normfinder, and Reffinder. …”
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MODEL OF DATA TRAFFIC QOS FAST REROUTING IN INFOCOMMUNICATION NETWORKS by Oleksandr Lemeshko, Maryna Yevdokymenko, Oleksandra Yeremenko

“…The proposed flow-based model can be used as the basis of the algorithmic software of existing routers and/or controllers of Software-Defined Networks, which are responsible for the calculation of the primary and backup paths in the fast rerouting of data traffic sensitive to such Quality of Service indicators as bandwidth and packet loss probability.…”
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Integrative Role of RNA N7-methylguanosine in epilepsy: Regulation of neuronal oxidative phosphorylation, programmed death and immune microenvironment. by Jiangli Zhao, Qingyuan Sun, Xuchen Liu, Jiwei Wang, Ning Yang, Chao Li, Xinyu Wang

“…Our findings also suggested that active m7G levels could promote oxidative phosphorylation in the neurons of epilepsy patients and decrease neuronal necroptosis activity. Machine learning algorithms were used to identify key m7G regulators (EIF4E3, NUDT3, SNUPN, LSM1, and METTL1), and a nomogram model was constructed based on these findings. …”
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AI in biomedical science: innovations, challenges, and ethical perspectives by Aynur Aliyeva

“…Key technologies such as generative AI platforms, machine learning algorithms, and mobile-based auditory training systems are highlighted. …”
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Threat of technological disruption and turnover intention in Egypt: A moderated mediation model by Mohamed Hossameldin Khalifa, Gamal M. Shehata

“…Orientation: Employee perceived threat of technological disruption (PTTD) is an unavoidable consequence of the increasing prevalence of Smart Technology, Artificial Intelligence, Robotics and Algorithms. Research purpose: This study examined the relationship between PTTD and turnover intention (TI), the mediating role of job insecurity (JI) in this relationship and the moderating effect of age on JI’s mediating role in the Egyptian private sector. …”
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Development of a manipulator kinematic model using Abb Robot Studio by Артем Бронніков, Марія Бендеберя

“… The subject of the research in the article is the application of control technology and algorithms, construction of the trajectory of movements and interaction with the production environment based on Abb Robot Studio. …”
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Physiological Signals as Predictors of Mental Workload: Evaluating Single Classifier and Ensemble Learning Models by Nailul Izzah, Auditya Purwandini Sutarto, Ade Hendi, Maslakhatul Ainiyah, Muhammad Nubli bin Abdul Wahab

“…A comprehensive evaluation was conducted on several ML algorithms, including both single (Support Vector Machine/SVM and Naïve Bayes) and ensemble learning (Gradient Boost and AdaBoost) classifiers and incorporating selected features and validation approaches. …”
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning by Raiyan Jahangir, Muhammad Nazrul Islam, Md. Shofiqul Islam, Md. Motaharul Islam

“…Other conventional machine-learning, bagging, and boosting ensemble algorithms were also explored along with the proposed stack classifiers. …”
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Ship Magnetic Signature Classification Using GRU-Based Recurrent Neural Networks by Kajetan Zielonacki, Jaroslaw Tarnawski, Miroslaw Woloszyn

“…Features, advantages and limitations of developed algorithms are derived strictly from the nature of neural networks.…”
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GALNT6 associated with O-GlcNAcylation contributes to the tumorigenesis of oral squamous cell carcinoma by Junfeng Yan, Xuan Tang, Yingying Zhou, Xin Xiong

“…Four key genes (MUC15, ADAMTS12, GALNT6 and FUT6) were identified with promising prognostic value by three machine learning algorithms. GALNT6 were aberrantly upregulated in OSCC cells and tissues. …”
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Jet substructure probe on scalar leptoquark models via top polarization by Anupam Ghosh, Partha Konar, Tousik Samui, Ritesh K. Singh

“…The analysis has been performed using both fixed radius and dynamic radius jet clustering algorithms. A multivariate analysis using a boosted decision tree (BDT) is performed to isolate signal from the Standard Model background. …”
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An improved multi-strategy equilibrium optimizer for surface marine vehicle path planning by Jianguo Yu, Yanyang Lu, Hamid Reza Karimi, Derong Zhu, Bin Li, Yiming Wang

“…It is verified theoretically from the experimental results that the R $$\mathrm {E^{2}}$$ O is with a significant improvement in performance by comparison between the standard EO and certain frequently-used heuristic optimization algorithms. Finally, the R $$\mathrm {E^{2}}$$ O is successfully applied in path planning for surface marine vehicles under the situations of both dynamic and static obstacles.…”
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