Methods for solving the initial value problem with a two-sided estimate of the local error

Numerical methods for solving the initial value problem for ordinary differential equations are proposed. Embedded methods of order of accuracy 2(1), 3(2) and 4(3) are constructed. To estimate the local error, two-sided calculation formulas were used, which give estimates of the main terms of the error without additional calculations of the right-hand side of the differential equation, which favorably distinguishes them from traditional two-sided methods of the Runge- Kutta type.

Informativity assessment and attributes selection in a computer system state identification

The subject of the article is a study of methods of determining the informativeness of attributes. The aim of the article is improvement of the classification quality of a computer system state by selecting the most informative features. Objective: To explore methods for selecting optimal information features to identify a computer system state based on an analysis of the Windows operating system events. The methods used are: machine learning methods, ensemble methods, methods of selecting the optimal information features. The following results were obtained: analysis of the Windows operating system events was performed, methods of selection the optimal information features were investigated: wrapper methods (Wrappers), embedded methods (Embedded) and filter methods (Filters). The informativeness assessment and selection features were performed for identifying a computer system state. An ensemble method for classifying a computer system state based on a bagging and J48 decision tree was developed to evaluate the effectiveness of selected features. The dependency of the classification accuracy of a computer system state on the selected features was investigated, and the attributes set that provides the maximum classification accuracy of a computer system state was determined. Conclusions. The scientific novelty of the results is in the analysis of the Windows operating system events, assessment of their informativeness and selection of features in the identification a computer system state.

Review on Embedded Methods in Parameter Estimation and Auto-tuning of Permanent Magnet Synchronous Servo Machine Driven Industrial Systems

A review on embeddable industrial drive systems

Review on Embedded Methods in Parameter Estimation and Auto-tuning of Permanent Magnet Synchronous Servo Machine Driven Industrial Systems

A review on embeddable industrial drive systems

Feature Selection Stability and Accuracy of Prediction Models for Genomic Prediction of Residual Feed Intake in Pigs Using Machine Learning

Feature selection (FS, i.e., selection of a subset of predictor variables) is essential in high-dimensional datasets to prevent overfitting of prediction/classification models and reduce computation time and resources. In genomics, FS allows identifying relevant markers and designing low-density SNP chips to evaluate selection candidates. In this research, several univariate and multivariate FS algorithms combined with various parametric and non-parametric learners were applied to the prediction of feed efficiency in growing pigs from high-dimensional genomic data. The objective was to find the best combination of feature selector, SNP subset size, and learner leading to accurate and stable (i.e., less sensitive to changes in the training data) prediction models. Genomic best linear unbiased prediction (GBLUP) without SNP pre-selection was the benchmark. Three types of FS methods were implemented: (i) filter methods: univariate (univ.dtree, spearcor) or multivariate (cforest, mrmr), with random selection as benchmark; (ii) embedded methods: elastic net and least absolute shrinkage and selection operator (LASSO) regression; (iii) combination of filter and embedded methods. Ridge regression, support vector machine (SVM), and gradient boosting (GB) were applied after pre-selection performed with the filter methods. Data represented 5,708 individual records of residual feed intake to be predicted from the animal’s own genotype. Accuracy (stability of results) was measured as the median (interquartile range) of the Spearman correlation between observed and predicted data in a 10-fold cross-validation. The best prediction in terms of accuracy and stability was obtained with SVM and GB using 500 or more SNPs [0.28 (0.02) and 0.27 (0.04) for SVM and GB with 1,000 SNPs, respectively]. With larger subset sizes (1,000–1,500 SNPs), the filter method had no influence on prediction quality, which was similar to that attained with a random selection. With 50–250 SNPs, the FS method had a huge impact on prediction quality: it was very poor for tree-based methods combined with any learner, but good and similar to what was obtained with larger SNP subsets when spearcor or mrmr were implemented with or without embedded methods. Those filters also led to very stable results, suggesting their potential use for designing low-density SNP chips for genome-based evaluation of feed efficiency.

Developing Age-Friendly Communities: Comparative Research on the Role of Social Infrastructure and Inclusion

Aging experiences are often framed by the forms in which communities take shape. In turn, the material forms of communities provide the conditions in which aging experiences and processes are produced. These multidirectional pathways of influence between micro-macro contexts comprise an assemblage of networks that usually go unnoticed, except on breakdown. Applying Leigh-Star’s (1999) charge to study these networks as infrastructure, we examine their “invisible work” in the ecological analysis of aging in community. This symposium presents research using community-embedded methods to illuminate how paradoxical forms of transparent and opaque infrastructure facilitate and mediate interactions between people, things, and the environmental shapes that hold these interactions. Yarker’s comparative case analysis of two Manchester neighborhoods highlight the critical importance of social infrastructure in supporting the diversity of relations needed to develop age-friendly communities and new forms of community action amongst older people. Grove’s qualitative and geo-spatial approaches demonstrate how planned and unplanned social interactions, and variety of social infrastructural forms, contribute positively and negatively to ageing well for older people in Dublin. Simon-Rusinowitz’s three-part intervention addresses unmet needs of older Baltimore residents in a low-income community; finding, in part-one, that housing is a platform for providing health and social services needed to age successfully. Yeh compares the conceptual frames undergirding age-friendly community initiatives with expert knowledges and lay perspectives of older San Franciscans, revealing tension between the rational dreams and material realities of aging in the community. These presentations contribute to gerontological discourse, providing new insights for policy and practice considerations.

Tracking of Unmanned Aerial Vehicles Using Computer Vision Methods: A Comparative Analysis

Tracking of small objects in any given airspace is an integral part of modern security systems. In these systems, there are embedded methods that employ the techniques based on either radio waves, or acoustic signals, or light radiation. The computer vision operation, springing from the light radiation-based technique, has prompted interest in its research. This operation has the advantage of being less expensive than radars and acoustic systems. In addition, it can solve complex security problems by detecting and tracking humans, vehicles, and flying objects. Therefore, this article evaluates the usefulness of the varying computer vision algorithms for tracking of small flying objects.

A Rapid Microwave Mediated Polyethyleneglycol Embedding Method Showing Retention of Intracellular Specialized Metabolites in Leaves of Cinnamomum Tamala (Buch-Ham.) T. Nees & Nees

Polyethyleneglycol (PEG) is considered one of the most effective substitutions for paraffin in plant histochemistry as an embedding medium. A rapid and straightforward method of PEG embedding has been developed that resulted in a significant reduction of infiltration time than the traditional method of PEG embedding. The material used for PEG embedding was leaves of Cinnamomum tamala, a member of Lauraceae. Samples were put successively in aqueous solutions of PEG 6000 with increasing concentration for infiltration. A microwave oven was used as a mode of heating medium. The infiltration was completed within 2 h. After the completion of infiltration, the samples were embedded in PEG and solidified. Compared with the existing methods available for PEG infiltration and embedding, this microwave mediated PEG embedding method saves significant time; this also saves the tissue from long-term heat-induced damage. Retention of intracellular metabolites, which was not possible in earlier PEG embedded methods, has also demonstrated in the tissue.