Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks by Rocco Restaino

“…Machine-learning-based algorithms designed for this task require an extensive optimization phase of network parameters, which must be performed using unsupervised learning techniques. …”
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A combined method of formation of a cryptographic key with secret modification of the results of synchronization of artificial neural networks by M. L. Radziukevich

“…The results obtained showed that the combined method of forming a cryptographic key with a secret modification of the synchronization results of artificial neural networks, proposed in this article, provides its high cryptographic strength, commensurate with the cryptographic strength of modern symmetric encryption algorithms, with a relatively simple implementation.…”
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From density functional theory to machine learning predictive models for electrical properties of spinel oxides by Yuval Elbaz, Maytal Caspary Toroker

“…To this end, a new database was developed from first principles, including band structure and conductivity properties of spinel oxides, and machine learning algorithms were trained on this database to predict electronic conductivity and band gaps based solely on the compositions. …”
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RPRep: A Robust and Privacy-Preserving Reputation Management Scheme for Pseudonym-Enabled VANETs by Jin Wang, Yonghui Zhang, Youyuan Wang, Xiang Gu

“…Moreover, we apply the information entropy and the majority rule to the reputation accumulation algorithms to counter false feedback. To defend the reputation link attack during pseudonym changes, we propose hidden-zone strategy and k -anonymity strategy. …”
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Fault Diagnosis of PV Array Based on Time Series and Support Vector Machine by Ying Zhong, Bo Zhang, Xu Ji, Jieping Wu

“…Using the time series values as input data for a “one-to-one” multiclass classifier, we can identify and classify typical operational faults such as random shading, fixed shading, and aging degradation of PV arrays. The developed algorithmic model is trained and tested for different fault conditions using the data sets generated by the PV array simulation device. …”
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Analyzing the Performance of Machine Learning Techniques in Disease Prediction by Khongdet Phasinam, Tamal Mondal, Dony Novaliendry, Cheng-Hong Yang, Chiranjit Dutta, Mohammad Shabaz

“…For the prediction of heart disease, decision trees are used to analyze various training and evaluation datasets. Classification algorithms such as Naive Bayes, ID3, C4.5, and SVM are being investigated. …”
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Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case by Mostafa Ameli, Jean-Patrick Lebacque, Ludovic Leclercq

“…Two different categories of algorithms (heuristic and metaheuristic) are considered in order to solve the discrete dynamic traffic assignment (DTA) problem. …”
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Opening tasks, opening minds – a rediscovery of the open-ended approach by Kalina Jastrzębowska

“…Primary school students in Poland are usually offered algorithmic and rote teaching methods and are thus very often deprived of important elements of successful mathematics learning. …”
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Detecting Latent Topics and Trends in Global Publications on Brucellosis Disease Using Text Mining by Meisam Dastani, Jalal Mardaneh, Omid Pouresmaeil

“…Python programming language has been applied to analyze data and implement text mining algorithms. Results. According to results, eight main topics of “Prevention,” “Clinical symptoms,” “Diagnosis,” “Control,” “Treatment,” “Immunology,” “Structural Features,” and “Pathogenicity” have been identified for brucellosis publications. …”
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Research on Error Propagation Law of Flood Routingby Fourth-order Runge - Kutta Method by ZHOU Bin

“…The fourth-order Runge-Kutta method is one of the commonly used algorithms for solvingordinary differential equations of reservoir flood routing. …”
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The Humoral Theory of Transplantation: Epitope Analysis and the Pathogenicity of HLA Antibodies by Edward J. Filippone, John L. Farber

“…Serologic HLA matching has been the standard for solid organ allocation algorithms in current use. Antibodies do not recognize whole HLA molecules but rather polymorphic residues on the surface, called epitopes, which may be shared by multiple serologic HLA antigens. …”
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The discernibility approach for multi-granulation reduction of generalized neighborhood decision information systems by Yanlan Zhang, Changqing Li

“…Then, the multi-granulation reduction of GNDISs by the discernibility tool provided a theoretical foundation for designing algorithms of multi-granulation reduction of DISs.…”
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Review of the Monograph “LegalTech in the Field of Entrepreneurship” by V. N. Shelmenkov, D. A. Gusev

“…Performing such routine tasks as drafting contracts, document management, issuing licenses, with the help of artificial intelligence, the algorithms of which exclude the possibility of professional error, is no longer a fantasy, but a reality towards which humanity is successfully moving. …”
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Studies on Underwater Image Processing Using Artificial Intelligence Technologies by Sugunapriya A, Markkandan S

“…Our study highlights the significant advances in AI driven underwater image processing technologies with a need for more resilient and flexible algorithms that can manage the intricacies of an undersea environment. …”
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Predicting learning achievement using ensemble learning with result explanation. by Tingting Tong, Zhen Li

“…To overcome these challenges, this research combines the strengths of various machine learning algorithms to design a robust model that performs well across multiple metrics, and uses interpretability analysis to elucidate the prediction results. …”
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Channel model-based multiple layers satellite-ground integrated data allocation strategy by SONG Yujie, CAO Yue, CHEN Nuo, SUN Zhili

“…The simulation results show that the performances of the proposed strategy outperform other baseline algorithms in terms of delivery ratio, average delivery latency, and interruption ratio.…”
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Reliable Service Execution Based on Probabilistic Moving Prediction in Mobile Wireless Sensor Network by Haiyang Hu, Junfeng Zhang, Hua Hu

“…By collaborating with each other，nodes in mobile wireless sensor network（MWSN）can filter，calculate and composite the data so as to provide it in forms of services to different users.However，due to the uncertain moving behavior and the limited wireless transmission，executing services in MWSN has to consider the time needed in nodes executing their services，and the physical region in which two nodes can communicate with each other by wireless channel.Probabilistic methods were used to define and predict the uncertain moving behavior of each node，and then the reliability was measured that two nodes can successfully communicate with each other under their wireless transmission range during a certain time period in the future.An approximate approach based on Monte Carlo simulation was also given to calculate nodes’ motions and the reliabilities of their successful communications.By consider the thresholds of execution time and the reliabilities of nodes’ successful communications，two algorithms were given to make the scheme of selecting nodes executing a group of services provided by the users，one using the approach of completely searching and one adopting the Pareto-dominated local k-th optimized method.Finally，experimented were conducted to evaluate our methods.…”
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A fluid flow model for the software defined wide area networks analysis by Karol Marszałek, Adam Domański

“…This modification allows for the simulation of various networking topologies and can be used to test novel routing and active queue management algorithms in more detail. The obtained numerical analysis demonstrates the model’s advantages over traditional methods, enabling the exploration of new scenarios.…”
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Encoding and Decoding of Secret Messages Using Matrices. by Niwagaba, James

“…It is hoped that this activity of encoding and decoding messages not only offers teachers write great opportunities to either introduce or consolidate certain mathematical concepts and algorithms but also to convince their students that mathematics plays an important role in various walks of life and hence is a useful and meaningful field of study. …”
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Wetland vegetation mapping improved by phenological leveraging of multitemporal nanosatellite images by Lucas T. Fromm, Laurence C. Smith, Ethan D. Kyzivat

“…Maximum Likelihood (MLC), Support Vector Machine (SVM), and Artificial Neural Network (ANN) classification algorithms are tested on individual, monthly- and multi-seasonal composite images. …”
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