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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

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.…”
Get full text

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. …”
Get full text

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. …”
Get full text

Visual Identity-Based Earthquake Ground Displacement Testing Method by Chen Su, Zhao Sicheng, Dai Zhijun, Li Xiaojun, Zhou Yue

“…The visual data streams can be quantified to the dynamic relative displacement value automatically, by employing mathematical vision algorithms and then by taking the relative displacement as an intermediate quantity, which is brought into the numerical model for iteration. …”
Get full text

Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept by A. Drosou, D. Ioannidis, K. Moustakas, D. Tzovaras

“…Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. …”
Get full text

Generative ecodesign for mechanical products: A design workflow by Amos Wei Lun Lee, Kevin Kai Wern Seah, Bing Feng Ng, Ee Teng Zhang, Wen Feng Lu, Jonathan Sze Choong Low

“…This workflow combines generative design algorithms, typically used for geometry lightweighting, with life cycle thinking. …”
Get full text

Developing multifactorial dementia prediction models using clinical variables from cohorts in the US and Australia by Caitlin A. Finney, David A. Brown, Artur Shvetcov

“…Tree-based machine learning algorithms and artificial neural networks were used. …”
Get full text

Shipyard Manpower Digital Recruitment: A Data-Driven Approach for Norwegian Stakeholders by Bogdan Florian Socoliuc, Andrei Alexandru Suciu, Mădălina Ecaterina Popescu, Doru Alexandru Plesea, Florin Nicolae

“…The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. …”
Get full text

Separable Nonlinear Least-Squares Parameter Estimation for Complex Dynamic Systems by Itai Dattner, Harold Ship, Eberhard O. Voit

“…Fortunately, many biological systems have embedded linear mathematical features, which may be exploited, thereby improving fits and leading to better convergence of optimization algorithms. In this paper, we explore options of inference for dynamic models using a novel method of separable nonlinear least-squares optimization and compare its performance to the traditional nonlinear least-squares method. …”
Get full text

Quantitative evaluation of intensity fidelity of super-resolution reconstruction for structured illumination microscopy by Yujun Tang, Linbo Wang, Gang Wen, Hui Li

“…Although many SIM reconstruction algorithms have been developed to recover fine cellular structures with high fidelity even from the noisy data, whether the pixel intensities of reconstructed SR images are still proportional to the original fluorescence intensity has been less explored. …”
Get full text

Translation Invariance-Based Deep Learning for Rotating Machinery Diagnosis by Wenliao Du, Shuangyuan Wang, Xiaoyun Gong, Hongchao Wang, Xingyan Yao, Michael Pecht

“…Although deep learning algorithms can automatically learn a good set of features without manual intervention, the lack of domain knowledge greatly limits the performance improvement, especially for nonstationary and nonlinear signals. …”
Get full text

Machine Learning Classifiers and Data Synthesis Techniques to Tackle with Highly Imbalanced COVID-19 Data by Avaz Naghipour, Mohammad Reza Abbaszadeh Bavil Soflaei, mostafa ghader-zefrehei

“…To this end, we demonstrate the capability of two advanced data synthesis algorithms, Conditional Tabular Generative Adversarial Network (CTGAN) and Tabular Variational Autoencoder (TVAE), in addressing the class imbalance inherent in the dataset. …”
Get full text