Quality Assessment Of Objects Research Articles

DATAMINING CAPABILITIES FOR CLUSTERING CONCRETE MIX FORMULATIONS

The article discusses the possibilities of using DataMining technology for clustering concrete mixtures. In practice, it is often necessary to face tasks in which it is necessary to choose the formulations closest in quality characteristics from a large number of formulations of concrete mixtures. The distribution of formulations of concrete mixtures by classes is provided on the basis of specified criteria such as strength, as well as the composition of the ingredients of the concrete mixture. Earlier in work [1], clustering of concrete mix formulations was carried out with the help of the program "Comprehensive quality assessment and classification of multidimensional objects", which made it possible to distribute formulations into classes with the closest characteristics and collect the highest quality concrete mix formulations into the appropriate classes. The result of using Data Mining technology for clustering concrete mix formulations allowed us to create classes in which the distribution using the DBSCAN algorithm is quite high-quality, however, there is a need for more detailed training of this algorithm, since clustering using the program "Integrated Quality Assessment and classification of multidimensional objects" turned out to be more optimal.

METHODOLOGICAL APPROACHES FOR ASSESSING THE QUALITY OF MULTI-PARAMETER ENERGY FACILITIES

The complex quality assessment of complex multivariate research objects is analyzed. It is emphasized that the current methodology for assessing the quality of multi-parameter objects, despite the heterogeneity of these objects, is based on common principles and methods of qualimetry associated with a particular system or group of systems that are part of this object and carry information on the quantitative parameters of the technological process and properties of the object but does not allow to determine a single integrated criterion for assessing the quality of the object. It has been found that when assessing the quality of a power facility, the main information and measurement systems do not have a process for forming comprehensive and integrated quantitative and qualitative indicators for assessing the quality of the facility. It is proposed to improve the information-measuring system of the software and hardware complex of the automated process control system of a power plant power unit, which, based on the analysis of individual quantitative and qualitative indicators of the quality of control and information flows (signals) on technological parameters, allows to establish and present the relationships between the structural elements of the facility and the process of forming the quality of electricity as the main quantitative and integral indicator of the facility quality assessment. The article substantiates the use of methods for assessing the level of electricity quality, which can be used both separately and in various combinations and allow: to ensure the obtaining of the final economic result, which allows making an economically sound decision in the production of electricity, and to more accurately assess the level of electricity quality when measured by various devices or when calculated are based on formulas that reflect objective laws. The stages of the sequence of work on the organization and conduct of qualimetric assessment of electricity quality are determined, which allows: to determine the purpose of assessing the level of electricity quality; to select the nomenclature of single and basic indicators for assessing the quality of electricity, as well as the choice of a qualimetric method for assessing the level of electricity quality. The application of instrumental (measuring), computational, and static methods of qualimetry, which allow calculations based on the values of quantitative parameters of electricity and can be used in practice when calculating the economic costs of electricity production at a power facility, is considered and substantiated.

System of indicators and the classifier of methods for quality control and evaluation of agricultural products in the structure of multidimensional inter-industry production cooperation

The article deals with the main issues of product quality management and control in multidimensional inter-industry production cooperation. Regulatory requirements and industry methods for assessing the quality of agricultural raw materials and finished industrial products on the example of leather and foot-wear industry are analyzed. The article presents the structural and logical scheme of the integrated classifier of methods for comprehensive quality assessment of objects and processes in multidimensional organizational structure of interindustry production cooperation. The conditions of digital transformation of agro-industrial complex aiming at improving the quality of leather footwear production on the basis of information-organizational inter-branch interaction between industrial and agricultural enterprises are formed int he article.

GRAPH-ANALYTICAL MODELS OF COMPLEX SYSTEMS FOR STATE ASSESSMENT “ORGANISM – ENVIRONMENT”

Practicism in business is generally associated with obtaining high-performance goal-setting solutions. Cost reduction in the case of making a decision requires weight components identification in the object “state (environment)  system processes  system end state” associated with the structure or functionality of systems (processes), which themselves arbitrarily determine the target result. The works aim is to determine model type of a complex structured object of any purpose, which adequately reflects system state and interaction with the environment “(environment – system) – process – (system state – environment)” in a situation of varying degrees uncertainty. Assessment of systemic formation state is due to the grouping of methods, their complex application in the study of the interaction “system – environment”, which is determined by the corporative relations between the components. To solve the problem of quality assessment of such system objects, structural and graphical approach information and methodological support was offered as a set of methods.

GRAPH ANALYTICAL METHOD FOR DETERMINING THE COMPLEX QUALITY INDICATOR OF QUALIMETRY OBJECTS

The subject of research in the article is a method for determining a complex quality indicator of qualimetry objects that have quality indicators with different units of measurement. The purpose of the work is proposing a method for determining a complex quality indicator of multicriteria objects of qualimetry, using integration methods. The article solves the following task: to investigate the possibility of assessing the quality of qualimetry objects by graph analytical method, ie to apply the principle of determining the area and volume under curved surfaces both on the plane and in space, created by combining estimates of unit quality indicators on dimensionless scale. The following methods are used: mathematical statistics; qualimetry. The following results were obtained: the analysis of scientific literature on quality assessment of qualimetry objects in terms of existing mathematical relationships between the measured quality indicators and their assessment on a dimensionless scale was carried out. It was shown that, as a rule, mathematical dependences are nonlinear and their research is reduced to the development of universal methods that could be applied to objects of qualimetry, regardless of their nature, complexity, importance, etc. Research that involves nonlinear relationships between measured quality scores and their estimates on a dimensionless scale should be based on quality ideology and have a physical explanation. Having single quality indicators in a single (dimensionless) rating scale, it is proposed to determine a single comprehensive quality indicator of the object of qualimetry using integration methods. It is proposed to find the area under the broken curve, which is built as a result of combining estimates of quality indicators on a dimensionless scale over a period of observations. Since the calculation of definite integrals by the Newton-Leibniz formula is not always possible, to solve practical problems, it is enough to know the approximate value of a certain integral with a given degree of accuracy, so it is proposed to use methods of numerical integration, methods: rectangles and trapezoids. A method for determining a generalized indicator of the quality of the object of qualimetry, which can be considered universal, as it can be used for multi-criteria assessment of the quality of objects of qualimetry of different nature. Conclusions: To determine the complex quality indicator of multicriteria qualimetry objects, it is proposed to apply integration by the method of average rectangles. The method of definition of a complex indicator of quality of object of qualimetry with application of integration which considers receipt of estimations of unit indicators of quality is proposed.

Multifactorial parametric model for assessing and making organizational decisions to ensure the quality of construction

As noted by a number of experts in the field of the quality of construction of capital construction objects, at present there are no industry-specific methods for assessing the quality of construction and installation works in construction. The quality assessment and acceptance of capital construction objects is carried out according to the criterion of compliance with the requirements established in the project documentation, the working documentation prepared on its basis and the requirements established in the regulatory documents. It should be noted that the more complex the object, the larger the construction volume, the longer the construction period of the object and the harder it is to achieve full compliance of the object with the established requirements due to the lack of a methodology for choosing organizational decisions, as well as changing regulatory requirements, technological variability, errors.The current situation necessitated the development of an assessment model and the adoption of organizational decisions to ensure the quality of construction. This article highlights and discusses the main factors affecting the quality of organizational decisions. A system for assessing the level of quality assurance of construction is proposed, taking into account the quality of organizational decisions and the main factors cited.

IMAGE QUALITY ASSESSMENT OF HIGH-RESOLUTION SATELLITE IMAGES WITH MTF-BASED FUZZY COMPREHENSIVE EVALUATION METHOD

Abstract. A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

INFLUENCE OF THE AVERAGE WEIGHTED ESTIMATION TYPE ON THE DEPENDENCE OF THE COMPLEX QUALITY INDEX ON THE PARAMETERS OF OBJECT

Objects quality is usually assessed by a complex indicator. It includes single quality indicators with their significance factors. The convolution of the corresponding dependencies represents average weighted quantities: arithmetic, geometric, harmonic, quadratic, etc. At the same time, the influence of the convolution type on the level of the complex quality index, the stability of the calculation results and, the reliability of the quality comparison among a number of similar objects is unknown in advance. Therefore, the aim of the study was to assess the influence of the average weighted type on the level and stability of the calculating results of the complex quality index in different objects compressing.For typical private objects compared the values of the complex quality index calculated according to the formulas of various average weighted estimates. Significance of the corresponding unit quality indicators, incompleteness of the object description and control factors influence on the object took into account.The results of the research were got using the method of virtual experiment planning. They showed that the influencing parameters changes, the calculated levels and stability of the complex quality index essentially depend on the type of convolution. It was shown that under the priori uncertainty of the necessary convolution for the best representative choosing of the corresponding class of objects, the arithmetic average weighted estimate is the best for using.The obtained data can serve as a basis for an informed choice of the type of average weighted in the quality assessment of various objects and decision-making on rational levels of controlled factors.

ТИПОЛОГИЧЕСКИЙ ПОДХОД К ОПРЕДЕЛЕНИЮ УРОВНЯ КАЧЕСТВА ОБЪЕКТОВ И ПРОЦЕССОВ В УПРАВЛЕНИИ ОРГАНИЗАЦИОННЫМИ СИСТЕМАМИ

The purpose of this work consists in the presentation of the results of the theoretical generalization of the problem in the quality level definition in processes and objects of arbitrary origin with the use of a typological approach as a basis of control in organization systems.
 In the investigation there were used methods of a system analysis, a mathematical modeling of multi-parametric social objects, methods of a structural anal-ysis and also a methodology of a universal quality management (UQM).
 Investigation results. A multidimensional information object space of matrices of groups of quality indices is considered, a generalized model of a twodimensional matrix of relations of quality indices parameters in Cartesian coordinates is presented, quality indices are shown and their application for adaptive marketing control is shown, a procedure for the quality assessment of objects with the aid of models of a neuro-network typification is offered, and the expediency of basic directions realization in strategy of quality control regarding the set of objects and processes of an organization system under analysis is also substantiated. As an example there is considered a neuro-network approach at the typification of engineering positions in modern mechanical engineering and procedures on the basis of a competence approach of the identification process of young specialists with available vacant seats.
 Conclusions. The quality parameters are a com-plex category in control of objects/processes and can be considered as a general methodological approach to the control of different organization systems. At the same time there can be used simulators of quality me-tering and typification, and also clusterization and grouping quality indices with the aid of which it is possible to ensure efficiently enough the realization of the identification procedure of objects/processes on quality indices with the application of neuro-network models.

A QUALITY ASSESSMENT METHOD FOR 3D ROAD POLYGON OBJECTS

Abstract. With the development of the economy, the fast and accurate extraction of the city road is significant for GIS data collection and update, remote sensing images interpretation, mapping and spatial database updating etc. 3D GIS has attracted more and more attentions from academics, industries and governments with the increase of requirements for interoperability and integration of different sources of data. The quality of 3D geographic objects is very important for spatial analysis and decision-making. This paper presents a method for the quality assessment of the 3D road polygon objects which is created by integrating 2D Road Polygon data with LiDAR point cloud and other height information such as Spot Height data in Hong Kong Island. The quality of the created 3D road polygon data set is evaluated by the vertical accuracy, geometric and attribute accuracy, connectivity error, undulation error and completeness error and the final results are presented.

Complex ecological estimation of natural and manmade complexes which basis on MIPS- and risk analysis

The article provides an algorithmic support which determines the ecological level of systems of natural environment and processes in it. The given algorithmic support allows identifying negative factors disturbing the homeostasis of man-made complexes, and provides complex ecological quality assessment of man-made objects. Using the proposed algorithm of the quality assessment of a complicated system-systematic formation based on MIPS-numbers, risk-characteristic as to the conditions of objects and processes connected with ecological state disturbance, we have received a complex assessment of the studied territory (hard domestic waste landfill (HDWL) in Kharkiv region (the town of Dergachi) and Rivne city(Ukraine), with the pressure indices and ecological security destabilization processes being estimated. The calculations at the given territories have shown the following results: by the activity of chemical influence on the water systems according to the standards of conditions, the environmental risk on Dergachi and Rivne HDWL was determined as acceptable; chlorides were recognised as a destabilizing factor. The investigation involving the complex ecological assessment methodology on the level of system objects allows taking into account the transformation processes of ecological safety destabilization when determining the situation safety level based on the results of monitoring the balance violation factors, which gives the grounds for creating a complex mechanism for quality management of anthropogenic territories.

MULTITEMPORAL QUALITY ASSESSMENT OF GRASSLAND AND CROPLAND OBJECTS OF A TOPOGRAPHIC DATASET

Abstract. As a consequence of the wide-spread application of digital geo-data in geographic information systems (GIS), quality control has become increasingly important to enhance the usefulness of the data. For economic reasons a high degree of automation is required for the quality control process. This goal can be achieved by automatic image analysis techniques. An example of how this can be achieved in the context of quality assessment of cropland and grassland GIS objects is given in this paper. The quality assessment of these objects of a topographic dataset is carried out based on multi-temporal information. The multi-temporal approach combines the channels of all available images as a multilayer image and applies a pixel-based SVM-classification. In this way multispectral as well as multi-temporal information is processed in parallel. The features used for the classification consist of spectral, textural (Haralick features) and structural (features derived from a semi-variogram) features. After the SVM-classification, the pixel-based result is mapped to the GIS-objects. Finally, a simple ruled-based approach is used in order to verify the objects of a GIS database. The approach was tested using a multi-temporal data set consisting of one 5-channel RapidEye image (GSD 5 m) and two 3-channel Disaster Monitoring Constellation (DMC) images (GSD 32 m). All images were taken within one year. The results show that by using our approach, quality control of GIS- cropland and grassland objects is possible and the human operator saves time using our approach compared to a completely manual quality assessment.

ANALYSIS OF QUANTITATIVE EVALUATION PROBLEM OF QUALITY IN HIGHER EDUCATION

In the article the existing principles and approaches the quality assessment of various objects and features of education quality are considered, the task of synthesis of quality assessment model for educational systems is set, the choice of network model of complex evaluation is substantiated.

Statistical profiles of highly-rated learning objects

The continuously growth of learning resources available in on-line repositories has raised the concern for the development of automated methods for quality assessment. The current existence of on-line evaluations in such repositories has opened the possibility of searching for statistical profiles of highly-rated resources that can be used as priori indicators of quality. In this paper, we analyzed 35 metrics in learning objects refereed inside the MERLOT repository and elaborated profiles for these resources regarding the different categories of disciplines and material types available. We found that some of the intrinsic metrics presented significant differences between highly rated and poorly-rated resources and that those differences are dependent on the category of discipline to which the resource belongs and on the type of the resource. Moreover, we found that different profiles should be identified according to the type of rating (peer-review or user) under evaluation. At last, we developed an initial model using linear discriminant analysis to evaluate the strength of relevant metrics when performing an automated quality classification task. The initial results of this work are promising and will be used as the foundations for the further development of an automated tool for contextualized quality assessment of learning objects inside repositories.

Building a software experience factory using granular-based models

Software quality is one of the most important practical features of software development. Project managers and developers look for methods and tools supporting software development processes and ensuring a required level of quality. To make such tools relevant, they should provide the designer/manager with some quantitative input useful for purposes of interpretation of the results. Knowledge provided by the tools leads to better understanding of the investigated phenomena. In this paper, we propose a comprehensive development methodology of logic-based models represented by fuzzy neural networks. A process of model development is performed in the stages of structural and parametric optimization. The structural optimization framework utilizes mechanisms of evolutionary computing, which become especially attractive in light of the structural optimization of the models. The parametric optimization is performed using the gradient-base method. The study comprises two detailed case studies dealing with existing software data. The first one deals with the quality assessment of software objects in an exploratory biomedical data analysis and visualization system. The second case is concerned with the model of software development effort discussed in the setting of some medical information system.

Software quality analysis with the use of computational intelligence

Quality of individual objects composing a software system is one of the important factors that determine quality of this system. Quality of objects, on the other hand, can be related to a number of attributes, such as extensibility, reusability, clarity and efficiency. These attributes do not have representations suitable for automatic processing. There is a need to find a way to support quality related activities using data gathered during quality assurance processes, which involve humans. This paper proposes an approach, which can be used to support quality assessment of individual objects. The approach exploits techniques of Computational Intelligence that are treated as a consortium of granular computing, neural networks and evolutionary techniques. In particular, self-organizing maps and evolutionary-based developed decision trees are used to gain a better insight into the software data and to support a process of classification of software objects. Genetic classifiers—a novel algorithmic framework—serve as ‘filters’ for software objects. These classifiers are built on data representing subjective evaluation of software objects done by humans. Using these classifiers, a system manager can predict quality of software objects and identify low quality objects for review and possible revision. The approach is applied to analyze an object-oriented visualization-based software system for biomedical data analysis.