Research on Virtual Display of Wetsuit Based on CLO3D

In order to overcome the problems of low signal-to-noise ratio in the information output interface and long time for information synthesis in the traditional virtual display method of clothing, a CLO3D-based virtual display method for wetsuit is designed in this study. The proposed method works as follows. Firstly, it analyzes the categories and functional characteristics of the wetsuit and the virtual display process of the CLO3D software. In the second step, the design of the proposed method for the process of data collection and fusion of the wetsuit design is made. In the subsequent steps, human model is established, designs are made for the style and modeling, simulation is made for the pattern and color of the wetsuit fabric, and dynamic display is made. Experimental results show that the signal-to-noise ratio (SNR) of the information output interface of the proposed method is above 75 dB, and the maximum SNR can reach 80.5 dB, and the information synthesis time varies between 32 min and 47 min, indicating that the proposed method is more efficient and effective.

Information Entropy in Chemistry: An Overview

Basic applications of the information entropy concept to chemical objects are reviewed. These applications deal with quantifying chemical and electronic structures of molecules, signal processing, structural studies on crystals, and molecular ensembles. Recent advances in the mentioned areas make information entropy a central concept in interdisciplinary studies on digitalizing chemical reactions, chemico-information synthesis, crystal engineering, as well as digitally rethinking basic notions of structural chemistry in terms of informatics.

Finding Consensus About the Level of Medication Safety in a Hospital Setting: Development and an Example of Application of a Modified Delphi Method

A version of the Institute for Safe Medication Practices (ISMP) questionnaire adapted to the Austrian inpatient setting was used to sample the estimates of a group of experts regarding the level of medication safety in a level II hospital. To synthesize expert opinions on a group level reproducibly, classical Delphi method elements were combined with an item weight and performance weight decision-maker. This newly developed information synthesis method was applied to the sample dataset to examine method applicability. Method descriptions and flow diagrams were generated. Applicability was then tested by creating a synthesis of individual questionnaires. An estimate of the level of medication safety in an Austrian level II hospital was, thus, generated. Over the past two decades, initiatives regarding patient safety, in general, and medication safety, in particular, have been gaining momentum. Questionnaires are state of the art for assessing medication practice in healthcare facilities. Acquiring consistent data about medication in the complex setting of a hospital, however, has not been standardized. There are no publicly available benchmark datasets and, in particular, there is no published method to reliably synthesize expertise regarding medication safety on an expert group level. The group-level information synthesis method developed in this study has the potential to synthesize information about the level of medication safety in a hospital setting more reliably than unstructured approaches. A medication safety level estimate for a representative Austrian level II hospital was generated. Further studies are needed to establish convergence characteristics and benchmarks for medication safety on a larger scale.

Slice forecast and its accuracy criterion

Subject. This article provides a mathematical formulation of a slice-based forecast technique allowing a comprehensive assessment of future changes in the dynamics and structure of economic systems. The technique is based on an analysis and integration of a set of time series of heterogeneous indicators combined in a system logical algorithm of information synthesis called a slice. A slice forecast accuracy criterion is proposed as well. Objectives. Slice forecasts are designed to improve the quality and efficiency of economic forecasts. Methods. The slice forecast technique is based on a slice technology as a set of methods to collect, process, analyze, and synthesize information and knowledge. Results. The article presents a calculation based on eight series of macroeconomic indicators that characterize the development of the economy of the Russian Federation for the period from 2000 to 2021. It shows new possibilities of analysis and description of economic systems, cycles and crisis phenomena. Conclusions. The results obtained show that the slice technique helps solve a number of urgent problems to improve the quality of foreseeing future changes.

Transformation of Geosystems of the Pre-Baikal Pre-Drift Zone

The results of the work are aimed at solving a fundamental problem related to the forecast of changes in the natural environment of the Russian regions.Modern problems of geographical research are aimed at studying geosystems that develop under the conditions of climatic or geodynamic changes. The territory is characterized by the diversity and contrast of geosystems, which makes the study area unique for identifying the factors of their transformation. The article presents the results of generalization of information obtained in the course of field research, in the analysis of literary and cartographic data in order to identify the specifics of the transformation of plateau geosystems. The features of transformation of geosystems of the research area are revealed. Various blocks of transformation of geosystems are considered, the synthesis of knowledge about which made it possible to create a systematic picture of the transformation of geosystems of the territory. It is shown that the history of the development of geosystems in the research area is largely related to the impact of the Baikal rift zone on the outskirts of the Siberian Platform. The specificity of the spatial organization of geosystems within its boundaries is shown. It is established that at present the most intensive transformations are characteristic of the area of the upper reaches of the Orlinga River, where new young geosystems are being formed. The materials are presented in the form of information synthesis of data and knowledge about the territory, based on the theory of geosystems of Academician V. B. Sochava, the results of long-term ground route research, cartographic information, and the interpretation of satellite images.

Functional Diagnostic System for Multichannel Mine Lifting Machine Working in Factor Cluster Analysis Mode

The primary direction of the increase of reliability of the automated control systems of complex electromechanical machines is the application of intelligent information technologies of the analysis of diagnostic information directly in the operating mode. Therefore, the creation of the basics of information synthesis of a functional diagnosis system (FDS) based on machine learning and pattern recognition is a topical task. In this case, the synthesized FDS must be adaptive to arbitrary initial conditions of the technological process and practically invariant to the multidimensionality of the space of diagnostic features, an alphabet of recognition classes, which characterize the possible technical states of the units and devices of the machine. Besides, an essential feature of FDS is the ability to retrain by increasing the power of the alphabet recognition classes. In the article, information synthesis of FDS is performed within the framework of information-extreme intellectual data analysis technology, which is based on maximizing the information capacity of the system in the process of machine learning. The idea of factor cluster analysis was realized by forming an additional training matrix of unclassified vectors of features of a new recognition class obtained during the operation of the FDS directly in the operating mode. The proposed algorithm allows performing factor cluster analysis in the case of structured feature vectors of several recognition classes. In this case, additional training matrices of the corresponding recognition classes are formed by the agglomerative method of cluster analysis using the k-means procedure. The proposed method of factor cluster analysis is implemented on the example of information synthesis of the FDS of a multi-core mine lifting machine. Keywords: information-extreme intelligent technology, a system of functional diagnostics, multichannel mine lifting machine, machine learning, factor cluster analysis.