scholarly journals Territorial Innovation Patterns in Romania. Future Pathways for Smart Specialization

2021 ◽  
pp. 153-175
Author(s):  
Cristina ȘERBĂNICĂ
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Hierarchical Cluster Analysis ◽  
Structural Characteristics ◽  
Hierarchical Cluster ◽  
Large Heterogeneity ◽  
Knowledge Intensive ◽  
Smart Specialization ◽  
Innovation Patterns ◽  
Step Factor

"This study examines the territorial patterns of innovation in Romania, a country labelled as ‘modest innovator’. Our main assumption is that the large heterogeneity in the sub-national innovation patterns is not captured in the typologies developed for the NUTS2 regions. Consequently, the study proposes a categorization of the Romanian NUTS3 counties according to their innovation performance and structural characteristics, by means of a two-step factor analysis combined with hierarchical cluster analysis. The results point to the existence of five territorial groupings with similar characteristics: knowledge-intensive hubs, technology-intensive platforms, diversified agglomerations, industrial production zones and structurally challenged regions. Taken together, the results suggest the need to prioritize structural transformation and embrace the broad-based innovation concept."

scholarly journals Use of Factorial Analysis of Mixed Data (FAMD) and Hierarchical Cluster Analysis on Principal Component (HCPC) for Multivariate Analysis of Academic Performance of Industrial Engineering Programs

2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Delimiro Visbal-Cadavid ◽  
Adel Mendoza-Mendoza ◽  
Enrique De La Hoz-Dominguez
Keyword(s):  
Higher Education ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Academic Performance ◽  
Hierarchical Cluster Analysis ◽  
Higher Education Institutions ◽  
Hierarchical Cluster ◽  
Industrial Engineering ◽  
Mixed Data ◽  
Engineering Programs

The article describes a new idea about using Factor Analysis, Mixed Data, and Hierarchical Cluster Analysis on Principal Components to study the academic performance in 82 Industrial Engineering Programs in Colombia. For this, we used the data from the results of the standardized test of the Saber Pro.). The authors find that the first three components explain 89.12% of the original data set variability. The quantitative variables associated with the Factor Analysis are the first dimension, while the two qualitative variables are related to the second dimension. The first factor explains 95.83% of the dispersion of the scores in Critical Reading, 94.72% of the variability in Quantitative Reasoning, 94.51% of the variation in Mathematics and Statistics, among others. This study shows a strong positive correlation between the quantitative variables and the first factorial axis. It assumes that the Industrial Engineering Programs of public higher education institutions perform better than private ones. The article stipulates that the higher education institutions belonging to the Andean Region present a better performance, followed by the higher education institutions located in the Pacific Region. In general terms, the results confirm that the best performing universities usually appear in the first places in the different rankings and are located in the big cities.

scholarly journals The organization of taste sensibilities in hamster chorda tympani nerve fibers.

1988 ◽  
Vol 91 (6) ◽  
pp. 861-896 ◽  
Author(s):  
M E Frank ◽  
S L Bieber ◽  
D V Smith
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Hierarchical Cluster Analysis ◽  
Nerve Impulse ◽  
Hierarchical Cluster ◽  
Nerve Fibers ◽  
Chorda Tympani ◽  
Chorda Tympani Nerve ◽  
Activation Patterns ◽  
Response Profiles

Electrophysiological measurements of nerve impulse frequencies were used to explore the organization of taste sensibilities in single fibers of the hamster chorda tympani nerve. Moderately intense taste solutions that are either very similar or easily discriminated were applied to the anterior lingual surface. 40 response profiles or 13 stimulus activation patterns were considered variables and examined with multivariate statistical techniques. Three kinds of response profiles were seen in fibers that varied in their overall sensitivity to taste solutions. One profile (S) showed selectivity for sweeteners, a second (N) showed selectivity for sodium salts, and a third (H) showed sensitivity to salts, acids, and other compounds. Hierarchical cluster analysis indicated that profiles fell into discrete classes. Responses to many pairs of effective stimuli were covariant across profiles within a class, but some acidic stimuli had more idiosyncratic effects. Factor analysis of profiles identified two common factors, accounting for 77% of the variance. A unipolar factor was identified with the N profile, and a bipolar factor was identified with the S profile and its opposite, the H profile. Three stimulus activation patterns were elicited by taste solutions that varied in intensity of effect. Hierarchical cluster analysis indicated that the patterns fell into discrete classes. Factor analysis of patterns identified three common unipolar factors accounting for 82% of the variance. Eight stimuli (MgSO4, NH4Cl, KCl, citric acid, acetic acid, urea, quinine HCl, HCl) selectively activated fibers with H profiles, three stimuli (fructose, Na saccharin, sucrose) selectively activated fibers with S profiles, and two stimuli (NaNO3, NaCl) activated fibers with N profiles more strongly than fibers with H profiles. Stimuli that evoke different patterns taste distinct to hamsters. Stimuli that evoke the same pattern taste more similar. It was concluded that the hundreds of peripheral taste neurons that innervate the anterior tongue play one of three functional roles, providing information about one of three features that are shared by different chemical solutions.

Individual differences in wild (WWCPS) rat — manifested in the exploration box

2010 ◽  
Vol 41 (1) ◽  
pp. 31-35
Author(s):  
Wojciech Pisula
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Individual Differences ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Dimensional Structure ◽  
Two Dimensional ◽  
Factor Scores ◽  
Laboratory Rats ◽  
Two Factors

Individual differences in wild (WWCPS) rat — manifested in the exploration box Thirty nine WWCPS rats were tested in the exploration box throughout fifteen sessions. Factor analysis was run to extract the main dimensions describing rat behavior. Two factors were extracted, confirming the validity of the concept of two dimensional structure of individual differences in rats. Hierarchical cluster analysis run on factor scores showed that only three out of a possible four types of factor combinations are actually present within observed group of animals. In terms of individual differences structure, the study provide support for the view that laboratory rats are still rats.

scholarly journals Pengelompokan 33 Aksesi Kakao Berdasarkan Karakter Morfologi Komponen Buah

2017 ◽  
Vol 4 (2) ◽  
pp. 67
Author(s):  
Edi Wardiana ◽  
Juniaty Towaha ◽  
Syafaruddin Syafaruddin
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Morphological Character ◽  
Hierarchical Cluster ◽  
Dry Weight ◽  
Morphological Characters ◽  
Fresh Weight ◽  
Experimental Station

<em>Identification and grouping of diverse cacao accessions based on morphological character of pod components is important in breeding activities to generate superior varieties. This study aimed to grouping 33 cocoa accessions based on morphological characters of pod components, conducted at Pakuwon Experimental Station, Sukabumi, West Java, at an altitude of 450 asl with Latosol soil and B type climate (Schmidt and Fergusson), from January until December 2015. Observation was taken on 33 cacao accessions of Kaliwining (KW), planted in 2012 with 3 m x 3 m spacing under 26 years old Genjah Salak coconut trees as shading. Ten mature pods were randomly harvested from 10 cocoa plants of each accession at respective two seasons (February and December 2015). The variables observed were 7 characters of pod components i.e.: (1) fresh weight of pod, (2) number of beans, (3) fresh weight of beans, (4) dry weight of beans, (5) fresh weight of pod husk, (6) number of pod furrow, and (7) fresh weight of pulp. Data were analyzed by factor analysis followed by hierarchical cluster analysis in Ward's method and discriminant analysis. The result showed that 19 accessions were classified as high in bean and pod husk component characters, 9 accessions were classified as high in pulp characters, and 5 accessions i.e. KW 162, KW 528, KW 570, KW 571, and KW 720 were classified as high in all characters of pod components, and potential as parents in generating superior cacao varieties.</em>

scholarly journals Ανάλυση περιβαλλοντικού κινδύνου από βαρέα μέταλλα γεωγενούς και ανθρωπογενούς προέλευσης σε δύο αντιπροσωπευτικές περιοχές του Ελλαδικού χώρου

2016 ◽  
Author(s):  
Δήμητρα Μεγαδούκα
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Hierarchical Cluster Analysis ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Component Analysis ◽  
Η Factor

Σκοπός της παρούσας μελέτης είναι η έρευνα έξι βαρέων μετάλλων σε δύο περιοχές του Ελλαδικού χώρου. Οι κεντρικοί άξονες της έρευνας αυτής αποτελούνται από τους εξής στόχους: i) να προσδιοριστούν οι συγκεντρώσεις των μετάλλων Pb, Cd, Zn, Co, Ni και Cr που εντοπίζονται σε αδιατάρακτα εδάφη, ii) να προσδιοριστούν οι πηγές προέλευσης των μετάλλων (ανθρωπογενής – γεωγενής) με εργαστηριακές και στατιστικές μεθόδους, iii) να προσδιοριστούν οι γεωχημικές μορφές των μετάλλων που κατανέμονται στα εδάφη, iv) να παρουσιαστούν γεωγραφικοί χάρτες κατανομής των μετάλλων με την χρήση του προγράμματος Γεωγραφικών Πληροφοριακών Συστημάτων, v) να προσδιοριστούν οι υποβόσκουσες σχέσεις μεταξύ των μετάλλων vi) να γίνει εκτίμηση περιβαλλοντικού κινδύνου που σχετίζεται με την ρύπανση εδαφών από βαρέα μέταλλα σε περιοχές επιβαρυμένες από ανθρωπογενή και γεωγενή αίτια.Επιλέχθηκαν δύο περιοχές μελέτης. α) Η Βόρεια Εύβοια επιλέχθηκε ως περίπτωση επιβάρυνσης από βαρέα μέταλλα γεωγενούς προέλευσης λόγω μητρικού υλικού - των βασικών και υπερβασικών πετρωμάτων που χαρακτηρίζουν γεωλογικά την περιοχή. β) Η Λαυρεωτική χερσόνησος επιλέχθηκε ως περίπτωση επιβάρυνσης από βαρέα μέταλλα ανθρωπογενούς προέλευσης από τις παλαιότερες (π.Χ.) αλλά και πρόσφατες μεταλλευτικές και μεταλλουργικές δραστηριότητες.Στην περιοχή της Βόρειας Εύβοιας επιλέχθηκαν 21 θέσεις δειγματοληψίας και στην Λαυρεωτική χερσόνησο επιλέχθηκαν 45 θέσεις δειγματοληψίας. Από κάθε θέση δειγματοληψίας, συλλέχθηκαν δείγματα από δύο διαφορετικά βάθη, 0-10 cm (Α) και 10-30 cm (Β). Σε όλα τα εδαφικά δείγματα προσδιορίστηκαν οι εξής φυσικοχημικές ιδιότητες των εδαφών : η κοκκομετρική σύσταση, το pH, το Eh, η οργανική ουσία και το ισοδύναμο CaCO3. Επίσης προσδιοριστήκαν οι μορφές των μετάλλων με την μέθοδο διαδοχικών εκχυλίσεων τροποποιημένη BCR. Η μέθοδος των διαδοχικών εκχυλίσεων στοχεύει επιλεκτικά και απελευθερώνει τα μέταλλα που είναι συνδεδεμένα σε : α) υδατοδιαλυτές & συνδεδεμένες με ανθρακικά άλατα, β) οξείδια Fe και Mn, γ) οργανική ουσία και δ) πυριτικές μορφές. Επίσης, για να γίνει μία σωστή και αντικειμενική σύγκριση των αποτελεσμάτων και να προσδιοριστούν οι σχέσεις μεταξύ των μετάλλων χρησιμοποιήθηκε το πρόγραμμα Factor Analysis (ανάλυση παραγόντων) και το πρόγραμμα Hierarchical Cluster Analysis. Η Factor Analysis με την μέθοδο της Principal Component Analysis, προσδιορίζει έναν μικρό αριθμό παραγόντων που εξηγούν το μεγαλύτερο μέρος της διακύμανσης που παρατηρείται, σε έναν πολύ μεγαλύτερο όγκο δεδομένων, ενώ η Hierarchical Cluster Analysis προσδιορίζει τις μεταβλητές ή τους παράγοντες, οι οποίοι εξηγούν τον τρόπο που συσχετίζονται τα μέταλλα απεικονιζόμενες σε ένα δενδρόγραμμα.

Factor Analysis of Card Sort Data: An Alternative to Hierarchical Cluster Analysis

2005 ◽  
Vol 49 (5) ◽  
pp. 691-695 ◽  
Author(s):  
Miranda G. Capra
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Statistical Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Common Method ◽  
Card Sorting ◽  
Card Sort ◽  
Formal Statistical Analysis

Software and product designers use card sorting to understand item groups and relationships. In the usability community, a common method of formal statistical analysis for open card sort data is hierarchical cluster analysis, which results in a tree of the items sorted into distinct, nested clusters. Hierarchical cluster analysis is appropriate for highly structured settings, like software menus. However, many situations call for softer clusters, such as designing websites where multiple pages link to the same target page. Factor analysis summarizes the categories created in card sorts and generates clusters that can overlap. This paper explains how to prepare card sort data for statistical analysis, describes the results of factor analysis and how to interpret them, and discusses when hierarchical cluster analysis and factor analysis are appropriate.

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

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