THE GENRE MODEL OF A SCIENTIFIC PAPER IN THE RUSSIAN AND ENGLISH LANGUAGES by Nataliya I. Kolesnikova, Yuliya V. Ridnaya

“…Since the requirements, recommendations and guidelines on the scientific paper structure presented in scientific and academic literature are mainly miscellaneous and often controversial, the author proposes to solve the problem using an invariant "Intergenre model of scientific text" providing a writer with a universal and basic algorithm for text generating activity.…”
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Reproducing Kernel Method for Solving Nonlinear Fractional Fredholm Integrodifferential Equation by Bothayna S. H. Kashkari, Muhammed I. Syam

“…Numerical results demonstrate the accuracy of the present algorithm. In addition, we prove the existence of the solution of the nonlinear fractional Fredholm integrodifferential equation. …”
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A Conservation Difference Scheme of Generalized Boussinesq Equation by Xiaoli Jiang, Xiaofeng Wang

“…We focus on the algorithm research of a class of six-order generalized Boussinesq equation. …”
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Possibility Intuitionistic Fuzzy Soft Expert Set Theory and Its Application in Decision Making by Ganeshsree Selvachandran, Abdul Razak Salleh

“…Lastly, a generalized algorithm is introduced and applied to the concept of possibility intuitionistic fuzzy soft expert sets in hypothetical decision making problem.…”
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Combinatorics in N = 1 Heterotic Vacua by Seung-Joo Lee

“…We briefly review an algorithmic strategy to explore the landscape of heterotic E 8 × E 8 vacua, in the context of compactifying smooth Calabi-Yau threefolds with vector bundles. …”
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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…To address this problem, a convolutional neural network (CNN) model combining the improved particle swarm optimization (IPSO) algorithm and SHAP analysis, called SHAP-IPSO-CNN, is developed in this study, aiming to reveal the key factors affecting ground-level ozone pollution and their interaction mechanisms. …”
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A segmentation method for LiDAR point clouds of aerial slender targets by Birong Huang, Zilong Wang, Jianhua Chen, Bingyang Zhou, Hao Ma

“…The method introduces an image segmentation algorithm based on a voting mechanism for overhead power lines and designs a calibration algorithm for LiDAR point clouds and images in the scenarios with large depth of field. …”
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A semi-synchronous federated learning framework with chaos-based encryption for enhanced security in medical image sharing by Animesh Roy, Deva Raj Mahanta, Lipi B. Mahanta

“…With its foundation in chaos-based approaches, the encryption algorithm is non-interactive, uses weighted parameters in each aggregation phase, and offers strong privacy protection using semi-synchronous and differential privacy techniques. …”
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Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. This algorithm aims to maximize the profits of network operators and the private sector while minimizing unsupplied energy and its associated penalties. …”
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Statistical Analysis of Medium‐Scale Traveling Ionospheric Disturbances Over Japan Based on Deep Learning Instance Segmentation by Peng Liu, Tatsuhiro Yokoyama, Weizheng Fu, Mamoru Yamamoto

“…Therefore, this research proposes a real‐time processing algorithm for dTEC maps based on Mask Region‐Convolutional Neural Network (R‐CNN) model of deep learning instance segmentation to detect wavelike perturbations intelligently with an accuracy of about 80% and a processing speed of about 8 fps. …”
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Prediction of Orbit Decay for Large-Scale Spacecraft considering Rarefied Aerodynamic Perturbation Effects by Xinglong Gao, Zhihui Li, Qin Chen, Di Ding, Aoping Peng

“…A unified local rapid engineering algorithm for aerodynamic force and moment coefficients covering all flow regimes is proposed. …”
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Color fundus photograph-based diabetic retinopathy grading via label relaxed collaborative learning on deep features and radiomics features by Chao Zhang, Guanglei Sheng, Jie Su, Lian Duan

“…Subsequently, we design a label relaxation-based collaborative learning algorithm for feature fusion.ResultsWe validate the effectiveness of the proposed method on two fundus image datasets: the DR1 Dataset and the MESSIDOR Dataset. …”
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SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…SAFE-CAST integrates several innovative components: (1) a federated learning approach using Lloyd’s K-means algorithm for secure clustering, (2) a quality diversity optimization algorithm (QDOA) for secure channel selection, (3) a dynamic trust management system utilizing blockchain technology, and (4) an adaptive multi-agent reinforcement learning for context-aware transmission scheme (AMARLCAT) to minimize latency and improve scalability. …”
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Integrating Data Mining, Deep Learning, and Gene Ontology Analysis for Gene Expression-Based Disease Diagnosis Systems by Sergii Babichev, Igor Liakh, Jiri Skvor

“…The research methodology involves initial gene ontology analysis, followed by the application of the Self Organizing Tree Algorithm (SOTA) for clustering gene expression profiles, an ensemble algorithm for data biclustering, and CNN for sample classification. …”
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Magnetic resonance imaging radiomics based on artificial intelligence is helpful to evaluate the prognosis of single hepatocellular carcinoma by Jing Zhou, Daofeng Yang, Hao Tang

“…Results: The clinical model based on linear regression (LR) algorithm (AUC: 0.658, 95%CI: 0.5021–0.8137), the radiomics model and deep transfer learning (DTL) model based on light gradient-boosting machine (Light GBM) algorithm (AUC: 0.761, 95%CI: 0.6326–0.8886 and AUC: 0.784, 95%CI: 0.6587–0.9087, respectively) were the optimal prediction models. …”
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Encrypted and obfuscation WebShell detection for high-speed network traffic by Yihuai CAO, Wei CHEN, Fan ZHANG, Lifa WU

“…With the gradual development of traffic encryption and text obfuscation technologies, it is increasingly difficult to prevent complicated and malicious WebShell attack events in production environment using traditional detection methods based on text content and network flow features, especially for adversarial samples, variant samples and 0Day vulnerability samples.With the established network traffic collection environment, DPDK technology was used to capture network traffic in the high-speed network environment, and a dataset was marked with label.The dataset consisted of more than 24,000 normal traffic and more than 10,000 malicious WebShell traffic under different platforms, different languages, different tools, different encryption and obfuscation methods.Then Asynchronous traffic analysis system framework and lightweight log collection components were used to efficiently parse raw traffic.Expert knowledge was integrated to analyze HTTP data packets during the communication process of several popular WebShell management tools, and the effective feature set for encrypted and obfuscation WebShell was obtained.Support Vector Machine (SVM) algorithm was used to realize offline training and online detection of complicated WebShell malicious traffic based on the effective feature set.Meanwhile, improving the parameter search method with the genetic algorithm promoted the model training efficiency furthermore.The experimental results showed that the detection efficiency can be guaranteed based on the self-built WebShell attack traffic dataset.Besides, the detection model has a precision rate of 97.21% and a recall rate of 98.01%, and it performed well in the comparative experiments of adversarial WebShell attacks.It can be concluded from the results that the proposed method can significantly reduce the risk of WebShell attack, effectively supplement the existing security monitoring system, and be applied in real network environments.…”
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Identifying Ocean Submesoscale Activity From Vertical Density Profiles Using Machine Learning by Leyu Yao, John R. Taylor, Dani C. Jones, Scott D. Bachman

“…In this paper, we propose an unsupervised machine learning algorithm to identify submesoscale activity using vertical density profiles. …”
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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…At the same time, the computational complexity of the algorithm has been reduced to some extent, allowing the estimator to complete the channel estimation faster. …”
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A Simple Visualization Method for Three-Dimensional (3D) Network by Sangkwon Kim, Chaeyoung Lee, Jintae Park, Sungha Yoon, Yongho Choi, Junseok Kim

“…To demonstrate the performance of the proposed algorithm, the relationships of the characters in the two novels are visualized using 3D network diagram.…”
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The Fast and Accurate Method of Tuning of SISO Controllers Using Seven Performance Indexes by Stopakevych A.О., Stopakevych О.A.

“…The goal of the work is the development of an algorithm and corresponding software, which allows the execution of multi-criteria optimization of a control system with PI controller and FOPDT plant. …”
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