Multidimensional Ranking Research Articles

New Ranking System for Higher Education Institutions in Oman as a tool for achieving SDGs

This study aims to construct a conceptual framework for ranking Higher Education Institutions in Oman (OHEIs) to achieve country-level Sustainable Development Goals (SDGs). This study utilizes a quantitative research design with focus groups being surveyed in five well-respected universities in Oman. The findings indicate that the newly proposed assessment criteria match and complete the Times Higher Education (THE) Impact Ranking, which overlooks the majority of OHEIs. The practical novelty of this study lies in proposing Oman's first multidimensional ranking system for higher education institutions, which can be applied to other countries’ SDG-monitoring approach modification and improving Oman’s sustainable development. The theoretical novelty of this paper includes a new interpretation of SDGs, with a focus on higher education institutions, which can be used in future similar studies. The significance of this study lies in its proposal of a novel ranking system for OHEIs that is expected to contribute to SDG achievement in Oman.

INVESTMENTS IN THE SYSTEM OF SOCIAL AND ECONOMIC SECURITY FACTORS AND RECOVERY OF THE UKRAINE REGION ECONOMIES

Abstract. The article is devoted to the regional peculiarities of the investment activity in Ukraine as a factor of social and economic security in martial law conditions and in the reconstruction period. The article aims to determine the features of the investment potential of Ukraine regions based on indicators of investment activity in the pre-war period, as well as the need to restore and develop the socio-economic infrastructure that was destroyed during Russian aggression. In preparing the article, methods of desk research, analysis, synthesis, and comparison, statistical methods of dynamic analysis, multidimensional ranking, and integral evaluations were used. Information sources for the investment activity assessment in Ukraine are systematized, considering the regional context and restrictions on disseminating data in wartime conditions. The main sources for statistical analysis of investment activity in Ukraine are state statistical surveys in the form of reporting and questionnaires of enterprises conducted by the State Statistics Service of Ukraine and the National Bank of Ukraine. Additional data producers on Ukraine’s investment climate are state and non-state analytical centers and other institutions, including the Ukrainian Business Association. An analysis of investment activity in the regions of Ukraine in the pre-war period was carried out based on indicators of capital and direct investments. Conclusions are formulated regarding the features of the regional distribution of investment potential indicators, considering the destruction of the socio-economic infrastructure in connection with Russian aggression. Critically important for the socio-economic security of Ukraine is the preservation of the investment potential of the regions that form the country’s industrial potential and can ensure the modernization of the real sector of the country’s economy. To develop regional programs for the recovery of Ukraine and attract investments for their implementation, creating an aggregated database on the scale of destruction and other material damage caused to each region of Ukraine in connection with Russian aggression is of great importance. Keywords: investments, investment activity, socio-economic security, regions of Ukraine, economic recovery, indicators of investment activity

Comparing Multivariate with Wealth-Based Inequity in Vaccination Coverage in 56 Countries: Toward a Better Measure of Equity in Vaccination Coverage.

Following a call from the World Health Organization in 2017 for a methodology to monitor immunization coverage equity in line with the 2030 Agenda for Sustainable Development, this study applies the Vaccine Economics Research for Sustainability and Equity (VERSE) vaccination equity toolkit to measure national-level inequity in immunization coverage using a multidimensional ranking procedure and compares this with traditional wealth-quintile based ranking methods for assessing inequity. The analysis covers 56 countries with a most recent Demographic & Health Survey (DHS) between 2010 and 2022. The vaccines examined include Bacillus Calmette-Guerin (BCG), Diphtheria-Tetanus-Pertussis-containing vaccine doses 1 through 3 (DTP1-3), polio vaccine doses 1-3 (Polio1-3), the measles-containing vaccine first dose (MCV1), and an indicator for being fully immunized for age with each of these vaccines. The VERSE equity toolkit is applied to 56 DHS surveys to rank individuals by multiple disadvantages in vaccination coverage, incorporating place of residence (urban/rural), geographic region, maternal education, household wealth, sex of the child, and health insurance coverage. This rank is used to estimate a concentration index and absolute equity coverage gap (AEG) between the top and bottom quintiles, ranked by multiple disadvantages. The multivariate concentration index and AEG are then compared with traditional concentration index and AEG measures, which use household wealth as the sole criterion for ranking individuals and determining quintiles. We find significant differences between the two sets of measures in almost all settings. For fully-immunized for age status, the inequities captured using the multivariate metric are between 32% and 324% larger than what would be captured examining inequities using traditional metrics. This results in a missed coverage gap of between 1.1 and 46.4 percentage points between the most and least advantaged. The VERSE equity toolkit demonstrated that wealth-based inequity measures systematically underestimate the gap between the most and least advantaged in fully-immunized for age coverage, correlated with maternal education, geography, and sex by 1.1-46.4 percentage points, globally. Closing the coverage gap between the bottom and top wealth quintiles is unlikely to eliminate persistent socio-demographic inequities in either coverage or access to vaccines. The results suggest that pro-poor interventions and programs utilizing needs-based targeting, which reflects poverty only, should expand their targeting criteria to include other dimensions to reduce systemic inequalities, holistically. Additionally, a multivariate metric should be considered when setting targets and measuring progress toward reducing inequities in healthcare coverage.

МЕТОДИ СТАТИСТИЧНОГО МОДЕЛЮВАННЯ ЕКОНОМІЧНИХ ПРОЦЕСІВ: КРИТИЧНИЙ ОГЛЯД

The article discusses various methods of modeling economic processes, in particular methods of multidimensional statistics, such as cluster analysis, multidimensional ranking, taxonomic analysis, multiple regression and correlation, discriminant analysis, multidimensional scaling, etc. Methods of statistical modeling are systematized and visualized. The variety of methods of modeling economic processes requires their systematization and comparative analysis. A critical overview of multidimensional statistical methods and methods used to analyse one-dimensional economic processes helps researchers understand which modeling method to choose and which prerequisites for using the method should be considered. The essence of the methods of multidimensional statistics is briefly described and certain features of these methods, prerequisites for their use, etc. are indicated. An example of the use of one of the methods of statistical modeling, taxonomic analysis at the regional level, is given. The taxonomic indicators of the development of the regions of Ukraine were calculated, as well as the leader regions and outsider regions were selected based on the results of the taxonomic analysis. The article states that taxonomic analysis can also be attributed to the group of classification methods, since in the process of applying the method, elements are not simply ordered, but also search for distances to the standard vector, which is already a sign of clustering. The taxonomic analysis of the regions of Ukraine was carried out according to such indicators as capital investments, foreign trade turnover, the unemployment rate and the number of active business entities. Standardization of indicators was carried out using the range of variation, taking into account stimulating indicators and destimulating indicators. Thus, it can be clearly seen that the leading regions mostly include those regions that are industrially developed, and the outsider regions are those areas that require additional capital investments. The results and recommendations are presented for the year 2021, since in February 2022 a full-scale russian invasion of the territory of Ukraine took place.

Préparation estimée et vulnérabilité des pays face à la pandémie de COVID-19: Elaboration et approbation de l'Index global

La pandémie de COVID-19 et ses conséquences socio-économiques ont provoqué une augmentation notable du rôle de l'estimation de la préparation et la vulnérabilité des pays. Cela s'ajoute aux investigations existantes dans le cadre des ont internationales et des classements multidimensionnels, et présente des résultats d'évaluation complexe au niveau national de la préparation et la vulnérabilité face à la pandémie, à partir des index multidimensionnels proposés par les auteurs. L'objectif de cette recherche était d'estimer le niveau de préparation national et la vulnérabilité d'un point de vue complexe. Un index multidimensionnel global a été calculé et utilisé pour donner un classement des pays à partir de cette méthodologie. L'index a permis aux auteurs de conclure qu'il y a une différence importante dans le niveau de préparation face à une pandémie et une disproportion entre certains éléments du système pour chaque pays. L'analyse des données, les sources et les rapports ont souligné le besoin d'étendre la liste des indicateurs pour évaluer le niveau de vulnérabilité. L'opportunité d'utiliser cet index est prouvée par l'analyse corrélative statistique entre les sous-index et le niveau de morbidité et mortalité due au COVID-19. L'index est utilisé pour former des groupes multidimensionnels et le partitionnement de données permet d'estimer les conséquences économiques de la pandémie. Les résultats du partitionnement de données ont permis de former quatre groupes de pays : (1) très vulnérables avec faible niveau de préparation ; (2) vulnérables avec faible niveau de préparation ; (3) vulnérables avec haut niveau de préparation ; (4) peu vulnérables avec haut niveau de préparation. L'analyse comparative des conséquences économiques (changement annuel PIB en 2020-2019 par rapport à PIB en 2019-2017), taux de chômage et changement de l'inflation ont montré des disproportions de l'influence de la pandémie par groupes de pays.

A Multidimensional Ranking of Members of Parliament

A Multidimensional Ranking of Members of Parliament

Multiscale Methods for Signal Selection in Single-Cell Data.

Analysis of single-cell transcriptomics often relies on clustering cells and then performing differential gene expression (DGE) to identify genes that vary between these clusters. These discrete analyses successfully determine cell types and markers; however, continuous variation within and between cell types may not be detected. We propose three topologically motivated mathematical methods for unsupervised feature selection that consider discrete and continuous transcriptional patterns on an equal footing across multiple scales simultaneously. Eigenscores () rank signals or genes based on their correspondence to low-frequency intrinsic patterning in the data using the spectral decomposition of the Laplacian graph. The multiscale Laplacian score (MLS) is an unsupervised method for locating relevant scales in data and selecting the genes that are coherently expressed at these respective scales. The persistent Rayleigh quotient (PRQ) takes data equipped with a filtration, allowing the separation of genes with different roles in a bifurcation process (e.g., pseudo-time). We demonstrate the utility of these techniques by applying them to published single-cell transcriptomics data sets. The methods validate previously identified genes and detect additional biologically meaningful genes with coherent expression patterns. By studying the interaction between gene signals and the geometry of the underlying space, the three methods give multidimensional rankings of the genes and visualisation of relationships between them.

Analysis of Spring Community Structure and Evaluation of Ecological Niche in Tangshan Marine Ranching, China

To investigate the fishery community structure in spring at the early stage of construction of Tangshan Marine Ranching, in China. This study analyzed the relationship between species composition, diversity and community structure of fishery resources in marine ranching using survey data from March, April, and May 2017. The results showed that a total of 53 species of organisms occurred in the spring in the waters inside and outside the reef area of the marine pasture. Among them, 20 species of fish were among the chordates. 16 species of arthropods, including 6 species of shrimps and 8 species of crabs. Ten species of mollusks, including 6 species of snails. 5 species of echinoderms, 1 species of annelids, and 1 species of Cnidaria). The diversity index, evenness index and richness index outside the reef area of marine ranching in spring were greater than those in the reef area. According to cluster analysis and non-metric multidimensional scale ranking analysis, the biological communities inside and outside the reef area can be divided into four groups, with the similarity of the communities in the reef area being greater. The Abundance-Biomass Comparison curves (ABC curve) indicated that the biological communities within and outside of the reef had been moderately disturbed. The relative importance index and niche analysis demonstrated that there had been sufficient bait in the reef area, and the ecological structure of the marine ranching was taking shape.

Економіка підприємства: оновлені підходи до бенчмаркінгу в контексті моделювання результативності діяльності та багатовимірного ранжування

The article is aimed at deepening the theoretical foundations of benchmarking and substantiating applied aspects regarding the feasibility of its use in the activities of enterprises in order to make and implement managerial decisions to increase the competitiveness and effectiveness of the functioning and development of enterprises as systems. The article emphasizes that the main issue of benchmarking is to clarify the factors of more successful and effective activities of some enterprises compared to others. In this context, it is substantiated that the approach proposed in the article is conceptual in terms of the enterprise’s desire to better and improve the effectuality of its functioning and development. Decisive in the use of a certain method is the choice of a number of indicators that characterize the objects and processes allocated when using benchmarking. As such indicators are used the author’s own indicators from the models of the components of the effectiveness of process, characterizing any process both from a qualitative and quantitative point of view. Scientific novelty is the disclosure of the author’s updated methodology for the application of benchmarking on the basis of the results of the studied effectiveness of the processes of functioning of enterprises using the models of components of effectiveness with the above articulated purpose with the implementation of multidimensional ranking and the detection on its basis of a leading enterprise to enable constructive comparative analysis. It is proved that in an unstable external competitive environment, the need to develop vectors of strategic orientation of the enterprise for the best results with the help of the so-called «etalons», such as leading enterprises, are allocated by means of multidimensional ranking. Comparative analysis can facilitate the adaptation of the effectiveness of performance of individual enterprises to best practices.

Which Methods Are Useful to Justify Public Policies? An Analysis of Cost–Benefit Analysis, Multi-Criteria Decision Analysis, and Non-Aggregate Indicator Systems

Science-based methods for assessing the practical rationality of a proposed public policy typically represent assumed future outcomes of policies and values attributed to these outcomes in an idealized, that is, intentionally distorted way and abstracted from aspects that are deemed irrelevant. Different types of methods do so in different ways. As a consequence, they instantiate the properties that result from abstraction and idealization such as conceptual simplicity versus complexity, or comprehensiveness versus selectivity of the values under consideration to different degrees. I hold that none of these methods is best in general. Instead, I opt for the valuation method that is useful for the policy issue in question both in terms of its relevance and in terms of its practicability. Relevance requires that the method can represent and account for what is at stake in the policy issue. Practicability refers to aspects such as easy versus difficult handling of the method. To argue for the claim, I evaluate three types of valuation methods: (1) cost–benefit analysis that rests on unidimensional measurement and ranking, (2) multi-criteria decision analysis that applies multi-dimensional measurement but unidimensional ranking, and (3) non-aggregate indicator systems that operate with multi-dimensional measurement and sometimes also multi-dimensional ranking. Second-order justification indicating whether and how the valuation method chosen is capable of accounting for the substantive value considerations that constitute the real-world policy issue in question renders the conditions on which the results of a proposed policy evaluation rest transparent.

Preparation of Innovative Development Rating of Russian Regions by the Level of University Involvement

The paper presents method of clustering and grouping the university performance indicators to prepare an integral rating of Russian regions by the level of university involvement in innovative development of Russian regions. The following problems that require the management influence of state structures are considered: the role of the research base of regional universities in strengthening the innovative potential of regions, the degree of involvement of universities in the innovative regional space.The aim of the study is to develop a rating system for Russian regions according to the degree of university involvement in innovative development using mathematical tools and an intelligent data processing system. The main hypothesis of the article is the existence of a link between regional innovative development and the effectiveness of university contributions. The mathematical approach involves the consideration and multidimensional ranking of the main groups of university performance indicators in order to obtain cluster classifications within each of the problems posed. The solution to the problems is to build a barometer of innovation activity in the form of a multi-purpose problem-oriented rating.Materials and methods. An approach is applied that includes the assessment and multidimensional ranking of the contribution of universities using groups of integral indices created on the basis of aggregation of several important indicators of the university’s activity. Computational experiments were conducted according to the data of the Ministry of Education and Science for the regions of Russia and regional universities. 16 indicators of Russian regions for 2016 are considered.Results and discussion. The ranking and comparison of universities according to the degree of involvement in the innovative development of the region was performed using an indicator model and aggregation depending on the target problem. Quantitative indicators of the quality of university’s activities by regions are obtained, which allow us to obtain an integral rating of Russian regions by the level of university involvement. Unlike other approaches, the author’s method includes three components, which are independent integral indexes and indicate the level of involvement of universities in regional innovative development. Statistical data on the leading indicators of Russian universities for 2016 were processed. The methodology Science-model with three factors - the model with regrouping, named by the author A-B-C, showed the high potential of Russian universities to balance their regional demand as management research centers.Conclusion. The results of the study are compared with the ratings of the well-known agencies. The author hopes that soon Russia will have a reliable scientometric system at the level of rating universities on their involvement in the innovative development of Russia, such a rating will be an indisputable argument in favor of financing regional universities. The author laid down a high requirement: compliance with the three models, only in this case, regional universities can receive funding from the municipality, after redistribution from the center. At the same time, it is necessary to carefully choose universities in which projects will receive development and perspective. Regional authorities must meet the requirements to receive the necessary investments in promising projects. The scientific potential and demand for theoretical research for their full application at all enterprises, the combination of theoretical science and practical implementation will reduce the cost of stabilizing outdated technologies in all areas of knowledge and use the experience of older generations and the strength of young people for high-tech production growth in Russia. Therefore, the results of the study will be useful to federal authorities and financial and credit organizations that provide financing.

Food security: state Financial support Measures for sustainable Development of Agriculture in Russian Regions

In the context of global economic instability, the problem of ensuring food security and sustainable development of agriculture at the international, national and regional levels becomes urgent. Existing methods for assessing the state of food security and sustainable development of agriculture, as a rule, have two main drawbacks: first, they are often static, and second, they include a scattered list of indicators that are difficult to systematically interpret in the analysis. Therefore, theaimof the study is to develop an adequate methodology for assessing the food security of the constituent entities of the Russian Federation. The construction of a thematic index is carried out in three stages: 1) a system of indicators is formed; 2) the values of indicators are normalized; and 3) sub-indices are calculated. The analysis of domestic and foreign literature on food security provided themethodological basisof the study. The system of indicators was clarified, which were combined into three groups (numerical indicators of the sphere of production, distribution, consumption, and food). The authors extended the retrospective assessment of food security at the meso-level by ranking and clustering Russian regions using hierarchical analysis and a new data filtering algorithm. The hierarchical procedure is based on a system of mathematical filtering of data, which is fundamentally different from existing methods for analyzing hierarchies. The authors replaced the fuzzy “what if” logic with a clear subordination of ranked indicators (subindices). The group of leaders was selected considering the accepted priority of indicators, the rest of the regions were united into a new subgroup, among which leaders and outsiders were singled out. At each new stage, new groups are ranked after excluding leaders and outsiders, they are in the “center of the circular convolution of data”, the procedure for stopping the procedure is the presence of two groups. This is a fundamental feature, scientific novelty, and value of the mathematical apparatus for multidimensional ranking of Russian regions in terms of food security. The authorsconcludedthat in modern Russia the problem of food security has not yet been resolved due to the insufficient use of general economic and special levers to increase the stability of the food system. The results of the study can be applied in the process of updating the state policy in the field of ensuring the sustainability of food systems at the macroand meso-level of management.

RATING ASSESSMENT IN MAKING FINANCIAL DECISIONS BY METHODS OF MULTI-CRITERIA ANALYSIS

The article attempts to reveal the problems of decision support processes by consumers of banking services. Choosing the best financial strategy always requires significant mathematical tools. The comparison of methodological tools for making management decisions has allowed us to identify groups of methods. The most common among them are game theory, multidimensional ranking and multi-criteria analysis, a fairly modern method exploring alternative options using multi-objective optimization without certain shortcomings of the first two methods. The main purpose of the study is to adapt the methods of multi-criteria analysis and to form universal tools to substantiate management decisions on the optimal financial strategy.
 We suggest a methodological approach based on the use of multi-criteria assessment tools, for the rating assessment of possible alternatives in making financial decisions, namely Smart method to determine the weighting factors of the evaluation criteria and TOPSIS method to assess the optimum banking institution from the perspective of bank depositors. The article pays special attention to highlighting and describing the hierarchy of the task of choosing a depository financial institution and the main features of strategic alternatives. To assess the banks’ ratings we set up the system of generalized criteria including three groups, each of which by means of decomposition is divided into 11 partial criteria, which have monotonically increasing target functions (except for "additional associated costs"). Initial data in the form of a constructed "decision matrix" according to certain particular criteria are formed on the basis of statistical and expert information. We have chosen the end of 2020 ‒ beginning of 2021 as the research period for utilizing up-to-date information.
 The research of rating assessment in the article is carried out in the following logical sequence: analysis of existing methods of financial decision-making support and the significance of modern methods of multi-criteria analysis among them, a thorough problem statement from the perspective of the banks’ services consumers, singling out the list of alternatives and their estimation criteria, substantiating the values of the weighting coefficients of generalized and particular criteria by the SMART method, practical application of the TOPSIS method algorithm to select the best alternative and recommendations for making a financial decision. Therefore by means of mathematical calculations the article justifies the choice of the optimum strategy by a consumer of financial services of the banking institution offering the most attractive conditions for opening an account.
 Thus, the study empirically confirms and theoretically proves that the use of modern economic and mathematical methods, in particular the TOPSIS method, helps the consumer of banking services in supporting of making well-considered and optimum management decisions, taking into account the previously set evaluation criteria.

Global partnership for sustainable development: challenges and perspectives for Ukraine

Research background: The global concept of sustainable development was elaborated in detail by the UN and the Club of Rome. Development Agenda 2030 and 17 Sustainable Development Goals (SDG) were adopted in 2015 with the main priorities of social development of the world. The monitoring and analysis of the 17 SDG and 169 targets of the new agenda will be carried out through a set of global indicators. Purpose of the article is to develop a system of indicators for monitoring the achieving the SDG in Ukraine. This system will use for estimating the current results and developing mid-term forecast. Methods: The classical econometric methods and models, in particular, the exponential smoothing method was used for estimating and forecasting. Also, the multidimensional ranking and the method of expert assessments were used. The research is carried out based on statistical data (from 2008 to 2018 years) of the State Statistics Service of Ukraine, Ministry of Economic Development and Trade of Ukraine, UN reports. Findings & Value added: The article contains an overview of the essence, components, aims, methodology, results and forecast for achieving the 17th Sustainable Development Goal ”Global Partnership” in Ukraine. The system of individual & integrated indicators for the global partnership was built for evaluating the current results and using for forecast modelling. The model of global partnership and mid-term forecast for Ukraine was built for the paper’s aim achieving. The results showed the main challenges for Ukraine in achieving the 17th SDG soon.

Diversification around Europe – performance measuring with regard to different missions

Existing university ranking systems blur differences between Higher Education Institutions because they only focus on research. The increased breadth, diversity and complexity of Higher Education Institutions’ missions are repeatedly overlooked causing a low visibility to a wide audience. This paper demonstrates the possibilities to measure other missions such as international orientation and regional engagement. Therefore, the results of 618 Higher Education Institutions (Effective March 2016) in U-Multirank, an international university ranking, are used. The results show the impressive variety in the higher education systems among European regions. Every region found missions in which they effectively perform thus proving the importance of each mission. The multidimensional ranking takes into account the complexity of Higher Education Institutions’ missions and capturing the relevance of Higher Education Institutions third mission’s activities adequately. Transparency across all missions is the only possibility to make the performances honourable. As research is not the only remarkable mission of Higher Education Institutions, teaching is not the only necessary mission. When other missions are overlooked, the performance measurement systems hinder mission diversity in higher education.

Zarządzanie ryzykiem na rynku metali

The purpose of this paper is to attempt to classify risk which can be observed when one deals with data from the metals market. Usually the general definition of risk includes two dimensions. The first one is the probability of occurrence and the second one are the associated consequences of a set of hazardous scenarios. In this research the authors try to add a new dimension: the source of risk, which can be defined in terms of the level of turnover (volatility of volume) and price (volatility of returns). One can categorize risks in terms of multidimensional ranking based on a comparative evaluation of the consequences, probability, and source of a given risk. Another dimension is the chosen risk measures, in the meaning of the risk model. In risk analysis, some selected quantile risk measures were proposed: VaR, Expected Shortfall, Median Shortfall and GlueVaR. The empirical part presents a multidimensional risk analysis of the metal market

Influence of Urbanization on Improvement of Housing Fund in the Rossiyskaya Federatsiya

The Object of the Study. Housing. The Subject of the Study. Housing improvement.The Purpose of the Study is to reveal the dependence of the degree of housing improvement on the level of urbanization.The Main Provisions of the Article. The quality of services provided to the population by the housing and communal services sector has a significant impact on the quality of life of the population. Therefore, monitoring the effectiveness of the reforms carried out both in the economy as a whole and in the housing and communal services of the Russiyskaya Federatsiya can be carried out by indicators of the dynamics of the quality of life of the population. At the same time, an important task is to identify factors that affect the indicators of the quality of life of the population in order to ensure appropriate conditions for achieving the goals. This work substantiates the solution of the problem of assessing factors affecting indicators of the level of improvement of the housing stock of the Russiyskaya Federatsiya. As one of such factors, the proportion of the urban population is used.A hypothesis of the dependence of the indicators of improvement of the housing stock on the level of urbanization of the Federal Okrugs has been put forward as a working one. In the process of the study, the task was set - to check this hypothesis and, if confirmed, to assess the level and direction of the identified relationship.As indicators of improvement in the work, we used official statistical data for 2017 for the Federal Okrugs of the Russiyskaya Federatsiya and data on the proportion of the urban population.The authors propose an algorithm for solving that problem, including ranking procedures of the Federal Okrugs by the level of improvement of the housing stock, as well as by the proportion of the urban population. Subsequently, the comparison of the obtained ranking results is performed using one of the statistical criteria, the Spearman rank correlation coefficient being proposed as such.The statement of the problem of multidimensional ranking of the Federal Okrugs by indicators of improvement of the housing stock has been formulated. Since in this case vectors of the same size are used for ranking, the multidimensional average method is used for that.To test the hypothesis put forward, the Spearman rank correlation coefficient was calculated, the value of which indicates the presence of a strong statistical relationship. Checking the statistical significance of the coefficient showed that the identified relationship is not random.The analysis of statistical data has allowed us to conclude that there is a strong statistical relationship between the integral level of improving housing and the level of urbanization of regions.

Towards Automatic Blocking of Shapes using Evolutionary Algorithm

This work focuses on the use of evolutionary algorithm to perform automatic blocking of a 2D manifold. The goal of such a blocking process is to completely partition a 2D region into a set of conforming and non-intersecting quadrilaterals to facilitate the generation of an all-quadrilateral, or more preferably an ideal quadrilateral mesh configuration covering the closed 2D region. However, depending on the input shape, the optimal blocking strategy is often unclear and can be very user-dependent. In this work, a novel approach based on evolutionary algorithm is adapted to search for a potential set of such ideal configurations. Based on a selection within a set of candidate vertices from a pre-computed pool, blocking configurations can be derived and ranked based on the collective quality of its blocks. The quality of a block is computed based on objective functions relating to its interior angles and opposite length ratios. Using multi-dimensional ranking criteria, inferior solutions can be slowly filtered away with each successive generation. Based on observations on a range of turbomachinery test cases, it is possible to derive and improve near-optimal blocking configurations by utilizing a large number of generations.

Item Selection and Exposure Control Methods for Computerized Adaptive Testing with Multidimensional Ranking Items

AbstractThe use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across items). To address these issues, we introduce subpool partition strategies for item selection and within‐person statement exposure control procedures. Simulations showed that the multinomial method reduces computation time while maintaining measurement precision. Both the freeze and revised Sympson‐Hetter online (RSHO) methods controlled the statement exposure rate; RSHO sacrificed some measurement precision but increased pool use. Furthermore, preventing a statement's repetition on consecutive items neither hindered the effectiveness of the freeze or RSHO method nor reduced measurement precision.

VASEM: visual analytics system for electron microscopy data bank

Electron Microscopy Data Bank (EMDB) provides biological researchers with a platform for uploading and downloading data obtained mainly by electron microscopy. With the continuous expansion of the total amount of data stored in EMDB in recent years, its influence has also been continuously improved. In order to make it easier for domain scientists to make better use of these data, we analyzed the EMDB meta-information structure and developed a visual analytics system, called VASEM, to provide convenient data exploration, searching, and analysis tools. Domain scientists can use our system to interactively filter massive EMDB data into relatively small subset for analysis and obtain subset depiction from visualization results. A modified parallel coordinates plot suitable for large-scale multi-dimensional ranking data visualization is also proposed for EM data subset depiction tasks. We present two usage scenarios to describe how the proposed system achieves the design goals.