Wyniki wyszukiwania - Biblioteka Nauki

1

A comparative analysis of economic efficiency of mediumsized manufacturing enterprises in districts of Wielkopolska province using the hybrid approach with metric and interval-valued data

100%

Dehnel G. , Walesiak M.

Statistics in Transition new series

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2019

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tom 20

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nr 2

49-67

EN

The article describes a hybrid approach to evaluating economic efficiency of medium-sized manufacturing enterprises (employing from 50 to 249 people) in districts of Wielkopolska province, using metric and interval-valued data. The hybrid approach combines multidimensional scaling with linear ordering. In the first step, multidimensional scaling is applied to obtain a visual representation of objects in a two-dimensional space. In the next step, a set of objects is ordered linearly based on the distance from the pattern (ideal) object. This approach provides new possibilities for interpreting linearly ordered results of a set of objects. Interval-valued variables characterise the objects of interests more accurately than metric data do. Metric data are atomic, i.e. an observation of each variable is expressed as a single real number. In contrast, an observation of each interval-valued variable is expressed as an interval. The analysis was based on data prepared in a two-stage process. First, a data set of observations was obtained for metric variables describing economic efficiency of medium-sized manufacturing enterprises. These unit-level data were aggregated at district level (LAU 1) and turned into two types of data: metric and interval-valued data. In the analysis of interval-valued data, two approaches are used: symbolic-to-classic, symbolic-to-symbolic. The article describes a comparative analysis of results of the assessment of economic efficiency based on metric and interval-valued data (the results of two approaches). The calculations were made with scripts prepared in the R environment.

2

Multidimensional Scaling in Economic Research

64%

Biela A. , Chair for Decision Analysis C. U. o. L.

Acta Universitatis Lodziensis. Folia Oeconomica

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2004

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tom 175

EN

A relationship between the theoretical terms and the observational ones, called also a perceptual or observational, is essential for scientific research of empirical type, including social sciences and economic sciences. This relationship cannot be clarified in terms of a complete definition but only by a partial definition. This methodological truth is well known since R. Carnap's works. Later on it was developed in methodology of sciences by the Polish logicians: Przełęcki, Poznański and Kamiński. Multivariable techniques are necessary when one wants to define the relationships between variables in economic and social sciences. However, the results obtained in such analysis are often unsatisfactory because the residual variance is too large. Multidimensional scaling proposes quite a different methodological approach for seeking the relationship between the theoretical terms and the observational ones. This paper aims: (1) to show what kind of methodological proposition is multidimensional scaling; (2) to show what are the possible directions of applying multidimensional scaling to social and economic analysis; (3) to define the multidimensional character of decision analysis.

PL

W badaniach naukowych typu empirycznego (do których należą również nauki społeczne i ekonomiczne) istotne znaczenie ma określenie związku pomiędzy terminami teoretycznymi a terminami empirycznymi. Związku tego nie da się ustalić w postaci definicji zupełnych, lecz tylko i wyłącznie przez definicje cząstkowe. Ta prawda znana jest już od czasu prac R. Carnapa, a została utrwalona i rozwinięta w metodologii nauk przez polskich logików: Przełęckiego, Poznańskiego, Kamińskiego. W określaniu związków pomiędzy analizowanymi zmiennymi w naukach społecznych i ekonomicznych konieczne jest stosowanie technik wielozmiennowych. Wyniki uzyskanych analiz nie są jednak zadowalające z uwagi na ich zbyt wielką wariancję resztową. Nieco inne podejście metodologiczne w poszukiwaniu związku między terminami teoretycznymi i empirycznymi proponuje skalowanie wielowymiarowe. Artykuł omawia założenia metodologiczne skalowania wielowymiarowego, teorię danych С. H. Coombsa (1964) jako podstawę logiczną tego skalowania oraz przydatność tej metody w analizie decyzyjnej. Wskazano, iż skalowanie wielowymiarowe może okazać się przydatne w pierwszych etapach pracy badawczej, eksperckiej, analitycznej czy aplikacyjnej, gdy należy usystematyzować zebrane dane i na tej podstawie przystąpić dopiero do formułowania hipotez, sądów, diagnoz, ocen. Istnieje jeszcze jedna możliwość wykorzystania skalowania wielowymiarowego, a jest nią mianowicie integrowanie różnych opinii oraz ekspertyz w przedmiotowej kwestii.

3

Geometrical Presentation of Preferences by Using Profit Analysis and R Program

52%

Zaborski A. , Pełka M. , Wroclaw Univeristy of Economics C. o. E. a. C. S. , Wroclaw Univeristy of Economics C. o. E. a. C. S.

Acta Universitatis Lodziensis. Folia Oeconomica

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2013

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tom 285

EN

PROFIT is a kind of external vector analysis of preference mapping. It is a combination of multidimensional scaling and multiple regression analysis. PROFIT takes as input both a configuration of stimulus points and a set of preference rankings of the different properties of the stimuli. For stimulus space obtained by multidimensional scaling multiple regression is performed using the coordinates as independent variables and attribute as the dependent variable. The program locates each property as a vector through the configuration of points, so that it indicates the direction over the space in which the property is increasing. The article presents PROFIT analysis and the R code to carry out the method. The function is illustrated with an example of application in the analysis of consumer preferences.

PL

PROFIT jest przykładem „zewnętrznej” wektorowej metody map preferencji. Jest ona połączeniem skalowania wielowymiarowego i analizy regresji wielorakiej. Danymi wejściowymi w analizie PROFIT są zarówno współrzędne punktów reprezentujących obiekty na mapie percepcyjnej jak również oceny preferencji obiektów ze względu na wybrane zmienne. Dla konfiguracji punktów reprezentujących obiekty otrzymanej za pomocą skalowania wielowymiarowego przeprowadza się analizę regresji wielorakiej, w której zmiennymi objaśniającymi są współrzędne obiektów na mapie percepcyjnej, a zmiennymi zależnymi oceny marek ze względu na poszczególne cechy. Program dokonuje rozmieszczenia na mapie percepcyjnej zmiennych w postaci wektorów wskazujących kierunek maksymalnej preferencji ze względu na daną zmienną. Artykuł jest prezentacją analizy PROFIT oraz składni poleceń programu R, pozwalającej na jej realizację. Sposób użycia funkcji zilustrowano przykładem badania preferencji.

4

Multidimensional comparative analysis of the European Union countries in the field of sustainable development

52%

Bartłomowicz T. , Cheba K.

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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2017

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nr 476

118-126

EN

The subject of the study is a comparative analysis of the level of sustainable development of the European Union. The basis of the study was the data collected in the Eurostat database, which the European Commission uses to monitor the implementation of the objectives of EU Sustainable Development Strategy. In order to determine similarities and differences in the level of development of EU countries in the study area, a method of multidimensional scaling was used. The obtained results allowed to identify similar as well as different countries because of their designated sizes. There were also identified countries whose sustainability is the closest to the object of reference and those whose previous development is similar to antipattern. In the calculations the environment and packages of R program were used.

5

Triads or tetrads? Comparison of two methods for measuring the similarity in preferences under incomplete block design

52%

Zaborski A.

Statistics in Transition new series

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2022

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tom 23

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nr 3

185-198

EN

The measurement of preferences can be based on historical observations of consumer behaviour or on data describing consumer intentions. In the latter case, the measure-ment of preferences is performed using methods which express consumer attitudes at the time of research. However, most of these methods are very laborious, especially when a large number of objects is tested. In such cases incomplete analyses may prove useful. An incomplete analysis involves the division of objects into subgroups, so that each pair of objects appears at exactly the same frequency and all objects are in each subgroup. The purpose of the work is to compare two incomplete methods for measuring the similarity of preferences, i.e. the triad method and the tetrad method. These methods can be used whenever similarities are measured on an ordinal scale. They have been com-pared in terms of their labour intensity and ability to map the known structure of ob-jects, even when all pairs of objects in subgroups cannot be presented equally frequent-ly.

6

Assessment of changes in population aging of Polish provinces in 2002, 2010 and 2017 using the hybrid approach

52%

Walesiak M. , Dehnel G.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2019

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nr vol. 23 no. 4

1-15

EN

The study investigates the variation in population ageing in Polish provinces in 2002, 2010 and 2017. Population ageing was assessed using the median age, proportion of elderly people, double ageing index, ageing index, and old-age dependency ratio. The authors took into account causes that explain changes occurring at the bottom and at the top of the population pyramid. By applying the hybrid approach combining multidimensional scaling with linear ordering (the two-step approach), the authors identified differences in the level of population ageing in a two-dimensional space. The paper applies a new method of automatic data collection from the Local Data Bank using the BDL package and the API interface (Application Programming Interface). The BDL API is a data-sharing service through webservice defining programming interfaces independent of the programming language, whereas the bdl package using this API enables webservice integration with the R statistical environment, eliminating the need for manual data extraction and enabling the automation of recurring activities.

7

Visualization of Differences between Rules' Syntactic and Semantic Similarities using Multidimensional Scaling

52%

Tsumoto S. , Hirano S.

Fundamenta Informaticae

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2007

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tom Vol. 78, nr 4

561-573

EN

One of the most important problems with rule induction methods is that it is very difficult for domain experts to check millions of rules generated from large datasets, although the discovery from these rules requires deep interpretation from domain knowledge. Although several solutions have been proposed in the studies on data mining and knowledge discovery, these studies are not focused on similarities between rules obtained. When one rule r1 has reasonable features and the other rule r2 with high similarity to r1 includes unexpected factors, the relations between these rules will become a trigger to the discovery of knowledge. In this paper, we propose a visualization approach to show the similarity relations between rules based on multidimensional scaling, which assign a two-dimensional cartesian coordinate to each data point from the information about similarities between this data and others data. We evaluated this method on two medical data sets, whose experimental results show that knowledge useful for domain experts can be found.

8

Sustainability Analysis of Domestic Raw Water Supply in Bandung City of Indonesia

52%

Mulyatna L. , Asdak C. , Gunawan B. , Yustiani Y. M.

Geomatics and Environmental Engineering

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2024

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tom Vol. 18, no. 2

5--20

EN

The availability and sustainability of good quantities and qualities of water supplies for human needs and support development should be warranted; therefore, existing water resources should be managed sustainably. A multidisciplinary rapid appraisal method called multidimensional scaling (MDS) is an approach for a comprehensive analysis of the sustainability statuses of domestic water supplies. This study aims to analyze the index and sustainability status of raw water management from three dimensions of sustainability. The results that were obtained from a specific multidimensional scaling analysis method called Rapid Appraisal for Air Baku (Rapaku) are expressed in the form of indices and sustainability statuses. Based on different dimensions of the sustainability status review, the analysis results showed that Bandung’s domestic raw water was “less sustainable” (42.34%). Of the 35 attributes that were analyzed, there were 13 sensitive attributes that affected the index and sustainability status with a very small error at a 95% confidence level.

9

Ascidian diversity (Chordata: Tunicata) from Andaman and Nicobar Islands, India

45%

Murugan R. , Ananthan G.

Oceanological and Hydrobiological Studies

|

2018

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tom Vol. 47, No. 2

107--117

EN

Ascidians are filter-feeding sac-like marine urochordates of great evolutionary, ecological and economic importance. Andaman and Nicobar Islands are one of the most important hot spots of biodiversity in India, while the ascidian diversity of this region is very scanty. Ascidians belonging to 29 species were identified at the Andaman and Nicobar Islands during the field research carried out from March 2014 to April 2015. Eight species (Didemnum granulatum, Didemnum molle, Didemnum psammatodes, Diplosoma listerianum, Lissoclinum fragile, Lissoclinum levitum, Lissoclinum patella, Trididemnum Cyclops) from the Didemnidae family were found and identified. Various diversity indices, such as the Shannon -Wiener index (H’), Margalef’s index (D), Pielou’s index (J’), K-dominance curves, Cluster Analysis and Multidimensional Scaling, were used to analyze the diversity, richness and evenness of species, and to compare the diversity between samples and their resemblance in terms of species composition. The maximum species richness was observed in Campbell Bay (2.424) and the minimum in Haddo Wharf (0.910). This finding shows the rich species diversity of ascidian fauna at Andaman and Nicobar Islands.

10

People’s Evaluations of Income Inequality and the Gini Coefficient Different in Details, Similar in Patterns

45%

Jancewicz B.

Polish Sociological Review

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2019

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tom 207

|

nr 3

289-304

EN

Recent studies suggest that the Gini coefficient’s and people’s evaluations of income inequality differ. Thus, we risk adopting policies that decrease the coefficient but not the inequality people see. This article argues that the coefficient does reflect people’s perception of inequality, at least in relation to the criticised Pigou-Dalton Transfer Principle stating that inequality falls whenever a person with higher income gives a small part of it to a person with lower income. Results from a questionnaire experiment where 105 WUT students evaluated inequality of different income distributions confirm that answers strictly following the principle are rare (around 3% of the sample). However, the average correlation between respondents’ and Gini’s evaluations was relatively high (0.693). Furthermore, when respondents’ evaluations were averaged, the correlation jumped to 0.954. An MDS analysis confirms that while these evaluations differed in details, the pattern common to respondents’ evaluations was in line with the Gini coefficient.

11

Kvalita modelů a volba parametrů počítačové textové analýzy v programu COOA

45%

Čepelák V.

Data a výzkum - SDA Info (Data and Research - SDA Info)

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2013

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tom 7

|

nr 1

7-27

EN

This article examines the reliability of statistical models that use visualization of word distances using computer-assisted text analysis. This study looks at the choice of parameters in the COOA - software for word co-occurrence analysis. The word co-occurrence analysis enables visualization of text structure through the exploration of the number of co-occurrences of words. The data visualization provided by a multi-dimensional scaling (MDS) procedure is susceptible to a particular form of error. The nonlinear relationship between words with significantly different frequencies lies at the root of this problem where words with higher frequencies are placed in the middle of a two-dimensional MDS map visualization. Words with lower frequency, on the other hand, are forced by the MDS estimator to the edge of the two-dimensional map and their estimated spatial positions are unstable. These two processes are potentially a major source of error in making inferences. One solution for reducing this source of error is to (a) reduce the number of words in a model or (b) increase of the number of model dimensions. This article, however, suggests that a detailed investigation of the word structure and a thorough analysis of the error sources and their meaningful interpretation may be a better solution.

12

Visualization of linear ordering results for metric data with the application of multidimensional scaling

45%

Walesiak M.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2016

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nr 2 (52)

9-21

EN

The article discusses the two-step research procedure allowing the visualization of linear ordering results for metric data. In the first step, as a result of the application of multidimensional scaling (see [Borg, Groenen 2005; Mair et al. 2016]) the visualization of objects in two-dimensional space is obtained. In the next step, the linear ordering of a set of objects is carried out based on the Euclidean distance from the pattern (ideal) object. The suggested approach expanded the possibilities for the interpretation of the linear ordering results of a set of objects. The article applies the concept of isoquants and the path of development (the shortest way connecting a pattern and an anti-pattern object) proposed by [Hellwig 1981]. The graphical presentation of the linear ordering results based on this concept was possible for two variables only. The application of multidimensional scaling expanded the applicability of the results of linear ordering visualization for m variables. The suggested approach is illustrated by an empirical example with the application of R environment script.

13

Postawy Polaków wobec służby cywilnej – nadzieje i oczekiwania

45%

Itrich-Drabarek J. , Mider D.

Studia Iuridica

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2022

|

tom 92

30-49

EN

Objective: Multidimensional reconstruction is offered of the Poles’ attitudes towards public service and their diversification in various sociodemographic and psychographic categories. Methods: The approach to data collection included computer-assisted telephone research on a sample of N=1,200 adult Poles (18+) and an analysis using descriptive statistics and selected inductive statistics techniques (regression modeling, intergroup difference tests, multidimensional scaling). Results: Analyzes of aggregate and partial dimensions of the Poles’ attitudes towards the civil service were made, models of positive and negative features of the civil service were developed. Conclusions: The study updates the existing research on the image of the civil service in Polish society, has a diagnostic and comparative value. The proposed models have a practical value, pointing to the strengths and weaknesses of the civil service as perceived by the Polish society, broken down into various groups. The predictive value, implications and model validation procedures were discussed.

14

Psychometric properties of the Polish version of the Job-related Affective Well-being Scale

45%

Basińska B. A. , Gruszczyńska E. , Schaufeli W. B.

International Journal of Occupational Medicine and Environmental Health

|

2014

|

tom 27

|

nr 6

993-1004

EN

Objectives: The aim of this study was to verify psychometric properties of the Polish version of the Job-related Affective Well-being Scale (JAWS). Specifically, theoretical 4-factor structure (based on the dimensions of pleasure and arousal) and reliability of the original - 20-item JAWS (van Katwyk et al., 2000) and the shortened - 12-item (Schaufeli and Van Rhenen, 2006) versions were tested. Material and Methods: Two independent samples were analyzed (police officers, N = 395, and police recruits, N = 202). The Polish version of the original, 20-item, JAWS was used to measure job-related affective states across the past month (van Katwyk et al., 2000). This version of JAWS includes 2 dimensions: valence and arousal, which allow to assess 4 categories of emotions: low-arousal positive emotions, high-arousal positive emotions, lowarousal negative emotions and high-arousal negative emotions. Results: The results of multidimensional scaling analysis showed that the theoretical circumplex model of emotions underlining JAWS was satisfactorily reproduced. Also the hypothesized 4-factor structure of the Polish version of JAWS was confirmed. The 12-item version had better fit with the data than the original, 20-item, version, but the best fit was obtained for the even shorter, 8-item version. This version emerged from a multidimensional scaling of the 12-item version. Reliabilities of the 20- and 12-item versions were good, with lower values for the 8-item JAWS version. Conclusions: The findings confirmed satisfactory psychometric properties of both Polish versions of the Job-related Affective Well-being Scale. Thus, when both psychometric properties and relevance for cross-cultural comparisons are considered, the 12-item JAWS is recommended as a version of choice.

15

Maintenance and Discovery of Domain Knowledge for Nursing Care using Data in Hospital Information System

39%

Iwata H. , Hirano S. , Tsumoto S.

Fundamenta Informaticae

|

2015

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tom Vol. 137, nr 2

237--252

EN

[Introduction] Schedule management of hospitalization is important to maintain or improve the quality of medical care and application of a clinical pathway is one of the important solutions for the management. Although several kinds of deductive methods for construction for a clinical pathway have been proposed, the customization is one of the important problems. This research proposed an inductive approach to support the customization of existing clinical pathways by using data on nursing actions stored in a hospital information system. [Method] The number of each nursing action applied to a given disease during the hospitalization was counted for each day as a temporal sequence. Temporal sequences were compared by using clustering and multidimensional scaling method in order to visualize the similarities between temporal patterns of clinical actions. [Results] Clustering and multidimensional scaling analysis classified these orders to one group necessary for the treatment for this DPC and the other specific to the status of a patient. The method was evaluated on data sets of ten frequent diseases extracted from hospital information system in Shimane University Hospital. Cataracta and Glaucoma were selected. Removing routine and poorly documented nursing actions, 46 items were selected for analysis. [Discussion] Counting data on executed nursing orders were analyzed as temporal sequences by using similarity-based analysis methods. The analysis classified the nursing actions into the two major groups: one consisted of orders necessary for the treatment and the other consisted of orders dependent on the status of admitted patients, including complicated diseases, such as DM or heart diseases. The method enabled us to inductive construction of standardized schedule management and detection of the conditions of patients difficult to apply the existing or induced clinical pathway.

16

Qualimetrical measurements: methodology based on relationship between qualimetry and metrology

39%

Motalo V. , Stadnyk B. , Mykyjchuk M. , Motalo A.

|

17

Dekompozycja modeli diagnostycznych

39%

Cholewa W.

Pomiary Automatyka Kontrola

|

2005

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tom R. 51, nr 9 bis

19--21

PL

Opracowanie dotyczy konstruowania klasyfikatorów diagnostycznych. Jego celem jest zwrócenie uwagi na celowość dekompozycji złożonych modeli diagnostycznych oraz pokazanie oryginalnego sposobu identyfikacji cech relewantnych, na podstawie danych uczących występujących w postaci zbioru przykładów. Wskazano możliwość zastosowania kryterium bazującego na zgodności wyników grupowania w nowej ograniczonej przestrzeni z wynikami klasyfikacji wzorcowej.

EN

The paper deals with design of diagnostic classifiers. The main goal is to present the usefulness of diagnostic model decomposition and to illustrate an original way of identification of useful signal features on the basis of learning data prepared as a set of examples. One indicated some possibilities of application of a criterion based on the expectation that results of unsupervised clustering in a new limited space should be compatible with results of classification of learning data.

18

Exploring the Structure of Volunteer Activities in Hospital Settings Using Multidimensional Scaling: A Preliminary Study

39%

Raveepatarakul J. , Ngamake S. T. , Srichaisawat C. , Bovornusvakool W. , Suttiwan P. , Monkong N. , Areekit P.

Polish Psychological Bulletin

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2020

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tom 51

|

nr 4

19

Analysis of Components for Generalization using Multidimensional Scaling

39%

Damaševičius R.

Fundamenta Informaticae

|

2009

|

tom Vol. 91, nr 3-4

507-522

EN

To achieve better software quality, to shorten software development time and to lower development costs, software engineers are adopting generative reuse as a software design process. The usage of generic components allows increasing reuse and design productivity in software engineering. Generic component design requires systematic domain analysis to identify similar components as candidates for generalization. However, component feature analysis and identification of components for generalization usually is done ad hoc. In this paper, we propose to apply a data visualization method, called Multidimensional Scaling (MDS), to analyze software components in the multidimensional feature space. Multidimensional data that represent syntactical and semantic features of source code components are mapped to 2D space. The results of MDS are used to partition an initial set of components into groups of similar source code components that can be further used as candidates for generalization. STRESS value is used to estimate the generalizability of a given set of components. Case studies for Java Buffer and Geom class libraries are presented.

20

Multidimensional scaling (MDS): sustainability assessment model of community economic empowerment

39%

Fadilah S. , Rosidana Y. , Maemunah M. , Hernawati N. , Sukarmanto E. , Hartanto R.

Polish Journal of Management Studies

|

2021

|

tom Vol. 24, No. 2

119--135

EN

The purpose of this research is to determine a sustainability assessment model of community economic empowerment program using Multidimensional Scaling (MDS). Multidimensional scaling is a multivariate statistical analysis used as a variable to determine the position of the object based on the similarity/dissimilarity. The research method used is descriptive research. Data collection techniques used are observation questionnaires, depth interview; and documentation. The population of this research are 573 beneficiaries of zakat and 236 samples (Slovin formula). Respondents are members of the BAZNAS (Badan Amil Zakat Nasional) business group in West Java Province. The results show that all Zakat Community Development’s (ZCD) have sufficient sustainability values from an economic perspective. The Squared Correlation (RSQ) value is 91.85 percent, and therefore, it suggests that the results of the Multidimensional Scaling analysis on the Zakat Community Development from an economic perspective can be explained as very good. The factor of income level becomes a decisive factor that is the most influential in the increase of economic sustainability.

PL

Celem tego badania jest określenie modelu oceny zrównoważenia programu wzmocnienia ekonomicznego społeczności przy użyciu skalowania wielowymiarowego (MDS). Skalowanie wielowymiarowe to wielowymiarowa analiza statystyczna wykorzystywana jako zmienna do określenia położenia obiektu na podstawie podobieństwa/niepodobieństwa. Zastosowaną metodą badawczą są badania opisowe. Stosowane techniki zbierania danych to kwestionariusze obserwacyjne, wywiad pogłębiony; i dokumentacja. Populacja tego badania to 573 beneficjentów zakatu i 236 próbek (formuła Slovina). Respondenci są członkami grupy biznesowej BAZNAS (Badan Amil Zakat Nasional) w prowincji Jawa Zachodnia. Wyniki pokazują, że wszystkie projekty Zakat Community Development (ZCD) mają wystarczające wartości zrównoważenia w perspektywie ekonomicznej. Wartość korelacji kwadratów (RSQ) wynosi 91,85 procent, a zatem sugeruje, że wyniki analizy wielowymiarowego skalowania rozwoju społeczności Zakat w perspektywie ekonomicznej można uznać za bardzo dobre. Czynnik poziomu dochodów staje się decydującym czynnikiem, który ma największy wpływ na wzrost zrównoważenia gospodarczego.