Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

Multi-criteria analysis in the strategic environmental assessment of the sugar and alcohol sector

The Strategic Environmental Assessment (SEA) of the sugar and alcohol sector guides a territorial and sectoral planning that benefits most of the local society and supports this economic activity in all its stages. In this way, the present work aims to determine an index of aggregation of the indicators generated in the baseline of the SEA process, called Index of Sustainability of Expansion of the Sugar and Alcohol Sector (IScana). For this, it was used the normalization of the indicators of each city by the fuzzy logic and attribution of weights by the Analytic Hierarchy Process (AHP). Then, the IScana values had been spatialized in the region of 'Grande Dourados'-Mato Grosso do Sul State. The northern portion concentrated the highest values of IScana, 0.48 and 0.55, referring to the cities of Nova Alvorada do Sul and Rio Brilhante, while, in the central portion, the city of Dourados presented the lowest value, 0.10. The selection of the set of indicators forming the IScana, and their relative importance, was satisfactory for the application of fuzzy logic and AHP techniques. The IScana index supplies objective information regarding the diagnosis of the region for the application of SEA.

Modeling and measuring the spatial relation "along": Regions, contours and fuzzy sets

The analysis of spatial relations among objects in an image is an important vision problem that involves both shape analysis and structural pattern recognition. In this paper, we propose a new approach to characterize the spatial relation along, an important feature of spatial configurations in space that has been overlooked in the literature up to now. We propose a mathematical definition of the degree to which an object A is along an object B, based on the region between A and B and a degree of elongatedness of this region. In order to better fit the perceptual meaning of the relation, distance information is included as well. In order to cover a more wide range of potential applications, both the crisp and fuzzy cases are considered. In the crisp case, the objects are represented in terms of 2D regions or ID contours, and the definition of the alongness between them is derived from a visibility notion and from the region between the objects. However, the computational complexity of this approach leads us to the proposition of a new model to calculate the between region using the convex hull of the contours. On the fuzzy side, the region-based approach is extended. Experimental results obtained using synthetic shapes and brain structures in medical imaging corroborate the proposed model and the derived measures of alongness, thus showing that they agree with the common sense. (C) 2011 Elsevier Ltd. All rights reserved.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

An Analysis of Living Conditions in Rural Villages in China. A New Geography of the Country.

Analysts, politicians and international players from all over the world look at China as one of the most powerful countries on the international scenario, and as a country whose economic development can significantly impact on the economies of the rest of the world. However many aspects of this country have still to be investigated. First the still fundamental role played by Chinese rural areas for the general development of the country from a political, economic and social point of view. In particular, the way in which the rural areas have influenced the social stability of the whole country has been widely discussed due to their strict relationship with the urban areas where most people from the countryside emigrate searching for a job and a better life. In recent years many studies have mostly focused on the urbanization phenomenon with little interest in the living conditions in rural areas and in the deep changes which have occurred in some, mainly agricultural provinces. An analysis of the level of infrastructure is one of the main aspects which highlights the principal differences in terms of living conditions between rural and urban areas. In this thesis, I first carried out the analysis through the multivariate statistics approach (Principal Component Analysis and Cluster Analysis) in order to define the new map of rural areas based on the analysis of living conditions. In the second part I elaborated an index (Living Conditions Index) through the Fuzzy Expert/Inference System. Finally I compared this index (LCI) to the results obtained from the cluster analysis drawing geographic maps. The data source is the second national agricultural census of China carried out in 2006. In particular, I analysed the data refer to villages but aggregated at province level.

Sviluppo di un approccio congiunto fuzzy-Bayesiano per l'analisi e la modellizzazione degli ecosistemi: applicazione ad ecosistemi marini costieri.

Nell’attuale contesto di aumento degli impatti antropici e di “Global Climate Change” emerge la necessità di comprenderne i possibili effetti di questi sugli ecosistemi inquadrati come fruitori di servizi e funzioni imprescindibili sui quali si basano intere tessiture economiche e sociali. Lo studio previsionale degli ecosistemi si scontra con l’elevata complessità di questi ultimi in luogo di una altrettanto elevata scarsità di osservazioni integrate. L’approccio modellistico appare il più adatto all’analisi delle dinamiche complesse degli ecosistemi ed alla contestualizzazione complessa di risultati sperimentali ed osservazioni empiriche. L’approccio riduzionista-deterministico solitamente utilizzato nell’implementazione di modelli non si è però sin qui dimostrato in grado di raggiungere i livelli di complessità più elevati all’interno della struttura eco sistemica. La componente che meglio descrive la complessità ecosistemica è quella biotica in virtù dell’elevata dipendenza dalle altre componenti e dalle loro interazioni. In questo lavoro di tesi viene proposto un approccio modellistico stocastico basato sull’utilizzo di un compilatore naive Bayes operante in ambiente fuzzy. L’utilizzo congiunto di logica fuzzy e approccio naive Bayes è utile al processa mento del livello di complessità e conseguentemente incertezza insito negli ecosistemi. I modelli generativi ottenuti, chiamati Fuzzy Bayesian Ecological Model(FBEM) appaiono in grado di modellizare gli stati eco sistemici in funzione dell’ elevato numero di interazioni che entrano in gioco nella determinazione degli stati degli ecosistemi. Modelli FBEM sono stati utilizzati per comprendere il rischio ambientale per habitat intertidale di spiagge sabbiose in caso di eventi di flooding costiero previsti nell’arco di tempo 2010-2100. L’applicazione è stata effettuata all’interno del progetto EU “Theseus” per il quale i modelli FBEM sono stati utilizzati anche per una simulazione a lungo termine e per il calcolo dei tipping point specifici dell’habitat secondo eventi di flooding di diversa intensità.

Quantificazione del rischio occupazionale: Indicatori, indici e metodologia fuzzy

La tesi affronta il concetto di esposizione al rischio occupazionale e il suo scopo è quello di indagare l’ambiente di lavoro e il comportamento dei lavoratori, con l'obiettivo di ridurre il tasso di incidenza degli infortuni sul lavoro ed eseguire la riduzione dei rischi. In primo luogo, è proposta una nuova metodologia denominata MIMOSA (Methodology for the Implementation and Monitoring of Occupational SAfety), che quantifica il livello di "salute e sicurezza" di una qualsiasi impresa. Al fine di raggiungere l’obiettivo si è reso necessario un approccio multidisciplinare in cui concetti d’ingegneria e di psicologia sono stati combinati per sviluppare una metodologia di previsione degli incidenti e di miglioramento della sicurezza sul lavoro. I risultati della sperimentazione di MIMOSA hanno spinto all'uso della Logica Fuzzy nel settore della sicurezza occupazionale per migliorare la metodologia stessa e per superare i problemi riscontrati nell’incertezza della raccolta dei dati. La letteratura mostra che i fattori umani, la percezione del rischio e il comportamento dei lavoratori in relazione al rischio percepito, hanno un ruolo molto importante nella comparsa degli incidenti. Questa considerazione ha portato ad un nuovo approccio e ad una seconda metodologia che consiste nella prevenzione di incidenti, non solo sulla base dell'analisi delle loro dinamiche passate. Infatti la metodologia considera la valutazione di un indice basato sui comportamenti proattivi dei lavoratori e sui danni potenziali degli eventi incidentali evitati. L'innovazione consiste nell'applicazione della Logica Fuzzy per tener conto dell’"indeterminatezza" del comportamento umano e del suo linguaggio naturale. In particolare l’applicazione è incentrata sulla proattività dei lavoratori e si prefigge di impedire l'evento "infortunio", grazie alla generazione di una sorta d’indicatore di anticipo. Questa procedura è stata testata su un’azienda petrolchimica italiana.

Multilocus sequence analysis and rpoB sequencing of Mycobacterium abscessus (sensu lato) strains

Mycobacterium abscessus, Mycobacterium bolletii, and Mycobacterium massiliense (Mycobacterium abscessus sensu lato) are closely related species that currently are identified by the sequencing of the rpoB gene. However, recent studies show that rpoB sequencing alone is insufficient to discriminate between these species, and some authors have questioned their current taxonomic classification. We studied here a large collection of M. abscessus (sensu lato) strains by partial rpoB sequencing (752 bp) and multilocus sequence analysis (MLSA). The final MLSA scheme developed was based on the partial sequences of eight housekeeping genes: argH, cya, glpK, gnd, murC, pgm, pta, and purH. The strains studied included the three type strains (M. abscessus CIP 104536(T), M. massiliense CIP 108297(T), and M. bolletii CIP 108541(T)) and 120 isolates recovered between 1997 and 2007 in France, Germany, Switzerland, and Brazil. The rpoB phylogenetic tree confirmed the existence of three main clusters, each comprising the type strain of one species. However, divergence values between the M. massiliense and M. bolletii clusters all were below 3% and between the M. abscessus and M. massiliense clusters were from 2.66 to 3.59%. The tree produced using the concatenated MLSA gene sequences (4,071 bp) also showed three main clusters, each comprising the type strain of one species. The M. abscessus cluster had a bootstrap value of 100% and was mostly compact. Bootstrap values for the M. massiliense and M. bolletii branches were much lower (71 and 61%, respectively), with the M. massiliense cluster having a fuzzy aspect. Mean (range) divergence values were 2.17% (1.13 to 2.58%) between the M. abscessus and M. massiliense clusters, 2.37% (1.5 to 2.85%) between the M. abscessus and M. bolletii clusters, and 2.28% (0.86 to 2.68%) between the M. massiliense and M. bolletii clusters. Adding the rpoB sequence to the MLSA-concatenated sequence (total sequence, 4,823 bp) had little effect on the clustering of strains. We found 10/120 (8.3%) isolates for which the concatenated MLSA gene sequence and rpoB sequence were discordant (e.g., M. massiliense MLSA sequence and M. abscessus rpoB sequence), suggesting the intergroup lateral transfers of rpoB. In conclusion, our study strongly supports the recent proposal that M. abscessus, M. massiliense, and M. bolletii should constitute a single species. Our findings also indicate that there has been a horizontal transfer of rpoB sequences between these subgroups, precluding the use of rpoB sequencing alone for the accurate identification of the two proposed M. abscessus subspecies.

Assessing collective defensive performances in football: A Qualitative Comparative Analysis of central back pairs

Ahead of the World Cup in Brazil the crucial question for the Swiss national coach is the nomination of the starting eleven central back pair. A fuzzy set Qualitative Comparative Analysis assesses the defensive performances of different Swiss central back pairs during the World Cup campaign (2011 – 2014). This analysis advises Ottmar Hitzfeld to nominate Steve von Bergen and Johan Djourou as the starting eleven central back pair. The alternative with a substantially weaker empirical validity would be Johan Djourou together with Phillippe Senderos. Furthermore, this paper aims to be a step forward in mainstream football analytics. It analyses the undervalued and understudied defense (Anderson and Sally 2012, Statsbomb 2013) by explaining collective defensive performances instead of assessments of individual player or team performances. However, a qualitatively (better defensive metrics) and quantitatively (more games) improved and extended data set would allow for a more sophisticated analysis of collective defensive performances.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

A fuzzy grassroots ontology for improving social semantic web search

The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.

Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

FORA - A Fuzzy Set Based Framework for Online Reputation Management

The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly exhibit a disastrous influence on the online reputation of organizations. Based on social Web data, this study describes the building of an ontology based on fuzzy sets. At the end of a recurring harvesting of folksonomies by Web agents, the aggregated tags are purified, linked, and transformed to a so-called fuzzy grassroots ontology by means of a fuzzy clustering algorithm. This self-updating ontology is used for online reputation analysis, a crucial task of reputation management, with the goal to follow the online conversation going on around an organization to discover and monitor its reputation. In addition, an application of the Fuzzy Online Reputation Analysis (FORA) framework, lesson learned, and potential extensions are discussed in this article.

In search of the "why" behind campaign professionalisation: explaining the degree and profile of campaign professionalisation by an empirical analysis of 23 Swiss cantonal election campaigns

Die Organisation und die strategische Kommunikation von Wahlkämpfen haben sich in den letzten Jahrzehnten in den meisten westeuropäischen Staaten gewandelt, so auch in der Schweiz. Die Kommunikationswissenschaft hat dafür den Begriff der „Professionalisierung“ geprägt und Eigenschaften zusammengetragen, die zu einem „professionalisierten“ Wahlkampf gehören – wie z.B. die Beauftragung von externen Expertinnen und Experten oder die direkte Ansprache von Wählerinnen und Wählern („narrowcasting“). Welche Hintergründe diese Professionalisierung aber hat und wie das Phänomen nicht nur praktisch zu beschreiben, sondern auch theoretisch zu begründen ist, wurde bisher kaum diskutiert. Hier setzt die vorliegende Dissertation an. Basierend auf einer Analyse von 23 Wahlkämpfen aus den Kantonen Aargau, Appenzell Ausserrhoden, Bern, Neuchâtel und Zürich mithilfe der Methode Fuzzy Set Qualitative Comparative Analysis (fsQCA) kommt sie zum Schluss, dass die Professionalisierung der Wahlkämpfe vor dem theoretischen Hintergrund des soziologischen Neo-Institutionalismus als Anpassung von Wahlkämpfen an sich verändernde Bedingungen, Erwartungen und Anforderungen in den wichtigsten Anspruchsgruppen oder „Umwelten“ für den Wahlkampf (Wählerinnen und Wähler, Mitglieder, Medien, andere Parteien) definiert werden kann. Daraus folgt, dass es nicht nur „die“ Professionalisierung gibt, sondern dass jeder Wahlkampf an jene Umwelten angepasst wird, wo diese Anpassung den Wahlkampfverantwortlichen am dringlichsten erscheint. Daher sollte Professionalisierung mit vier einzelnen Messinstrumenten bzw. Professionalisierungsindices – einem pro Umwelt – gemessen werden. Misst man Professionalisierung wie bisher üblich nur mit einem einzigen Messinstrument, gibt der resultierende Wert nur ein ungenaues Bild vom Grad der Professionalisierung des Wahlkampfs wieder und verschleiert, als Anpassung an welche Umwelt die Professionalisierung geschieht. Hat man ermittelt, wie professionalisiert ein Wahlkampf im Hinblick auf jede der vier relevantesten Umwelten ist, können dann auch zuverlässiger die Gründe analysiert werden, die zur jeweiligen Professionalisierung geführt haben. Die empirische Analyse der kantonalen Wahlkämpfe bestätigte, dass hinter der Professionalisierung in Bezug auf jede der vier Umwelten auch tatsächlich unterschiedliche Gründe stecken. Wahlkämpfe werden in Bezug auf die Ansprache der Wähler angepasst („professionalisiert“), wenn sie in urbanen Kontexten stattfinden. Den Wahlkampf im Hinblick auf die Mitglieder zu professionalisieren ist besonders wichtig, wenn die Konkurrenz zwischen den Parteien gross ist oder wenn eine Ansprache der Gesamtwählerschaft für eine Partei wenig gewinnbringend erscheint. Die Professionalisierung des Wahlkampfes in Bezug auf die Medien erfolgt dann, wenn er eine grosse, regional stark verteilte oder aber eine urbane Wählerschaft ansprechen muss. Für die Professionalisierung der Wahlkämpfe gegenüber anderen Parteien kann kein aussagekräftiger Schluss gezogen werden, da nur wenige der untersuchten Kantonalparteien ihre Wahlkämpfe überhaupt im Hinblick auf andere Parteien professionalisierten, indem sie die gegnerischen Wahlkämpfe beobachteten und den eigenen wenn nötig entsprechend anpassten.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.