86 resultados para Clustering evaluation


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Introduction: Cellulite is a complex architectural disorder with multifactorial etiologies that is prevalent in 98% of the women (1). Nowadays several aesthetic treatments are being used: surgical, cosmetic, physical, mechanical, and thermal. (2) Most treatments lack a substantial proof of efficacy. Objective: The purpose of this study was to test and evaluate the efficacy of Ultrasound, Homeopathic Ultrasonophoresis, and Homeopathic Mesotherapy versus control in cellulite in a population of women from ESTSP. Methods: Female volunteers (n=23), Caucasian, aged between 18-31 years, with BMI 19-27 kg/m2 with clinical cellulite gradation on the Cellulite Grading Scale of 1 to 4 were included in a control controlled study. Subjects were assigned in four different groups: Group I (Control, n=6), Group II (Ultrasound, (n=5), Group III (Homeopathic Ultrasonophoresis, n=6), Group IV (Homeopathic Mesotherapy, n=6). Groups II to IV were treated 3 times per week, for a total of 10 sessions. Cellulite gradation was evaluated at the beginning and the end of the trial by means of clinical photography, using a Canon IXUS 65 (6 mega pixels). For homeopathic treatments Dr. Reckeweg® Rekin® 59, 13 and 42 – Dietmed were used. The rating of perceived pain during Homeopathic Mesotherapy was evaluated by a visual analogic scale (VAS). The equipment Sonopuls 692, Enraf-Nonius was used for Ultrasound and Ultrasonophoresis treatments. Results:The higher number of participants with improvement in cellulite graduation occurred in group II (80%), followed group III (50%) and by group IV (33%). The group in which more changes in cellulite gradation occurred was group II, 20% of the individuals improved their score in 2 points. Results were statistically different between Group I and Group II, p=0,015. During the treatments of homeopathic mesotherapy the pain diminished 1 value in VAS scale. Discussion and Conclusion: Although all the three interventions groups were effective in the improvement of cellulite, as expected from previous works described in the literature, (2) only the ultrasound group was statistically different from control. These preliminary results point to the need of a new study using a higher number of participants and the same methodology.

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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

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Signal-to-interference ratio (SIR) performance of a multiband orthogonal frequency division multiplexing ultra-wideband system with residual timing offset is investigated. To do so, an exact mathematical derivation of the SIR of this system is derived. It becomes obvious that, unlike a cyclic prefixing based system, a zero padding based system is sensitive to residual timing offset.

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The nomination of Guimarães to host the 2012 European Capital of Culture (ECC) has put on the agenda of the city the need of measuring the effects that the implementation of this mega event could have in it and in the municipality a whole. The balance of the benefits and costs and an extended community involvement tend to reduce negative impacts and enhance positive ones. This chapter analyzes the involvement of population and local associations in the planning and organization of the 2012 Guimarães European Capital of Culture, using the coverage made during 2011 by local and national press of the mega event. A content analysis of the news published covering the period between January and December 2011 and using three newspapers was conducted. From those, two were local and weekly newspapers and one was a national daily one. Looking to data results, it can be concluded that it was poor the community involvement and, also, the one of the cultural associations in the organizations of the 2012 ECC. A strong negative reaction to the model choose to plan the mega event conducted by official organizers was found, which has cast doubts on the desirable participation of the residents and, consequently, on the success of the mega event, especially in a perspective of a medium and long term effects.

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Presented at IEEE 21st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2015). 19 to 21, Aug, 2015.

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Eight tropical fruit pulps from Brazil were simultaneously characterised in terms of their antioxidant and antimicrobial properties. Antioxidant activity was screened by DPPH radical scavenging activity (126–3987 mg TE/100 g DW) and ferric reduction activity power (368–20819 mg AAE/100 g DW), and complemented with total phenolic content (329–12466 mg GAE/100 g DW) and total flavonoid content measurements (46–672 mg EE /100 g DW), whereas antimicrobial activity was tested against the most frequently found food pathogens. Acerola and açaí presented the highest values for the antioxidant-related measurements. Direct correlations between these measurements could be observed for some of the fruits. Tamarind exhibited the broadest antimicrobial potential, having revealed growth inhibition of Pseudomonas aeruginosa. Escherichia coli, Listeria monocytogenes, Salmonella sp. and Staphylococcus aureus. Açaí and tamarind extracts presented an inverse relationship between antibacterial and antioxidant activities, and therefore, the antibacterial activity cannot be attributed (only) to phenolic compounds.

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O objetivo desta dissertação foi estudar um conjunto de empresas cotadas na bolsa de valores de Lisboa, para identificar aquelas que têm um comportamento semelhante ao longo do tempo. Para isso utilizamos algoritmos de Clustering tais como K-Means, PAM, Modelos hierárquicos, Funny e C-Means tanto com a distância euclidiana como com a distância de Manhattan. Para selecionar o melhor número de clusters identificado por cada um dos algoritmos testados, recorremos a alguns índices de avaliação/validação de clusters como o Davies Bouldin e Calinski-Harabasz entre outros.

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Atualmente, são geradas enormes quantidades de dados que, na maior parte das vezes, não são devidamente analisados. Como tal, existe um fosso cada vez mais significativo entre os dados existentes e a quantidade de dados que é realmente analisada. Esta situação verifica-se com grande frequência na área da saúde. De forma a combater este problema foram criadas técnicas que permitem efetuar uma análise de grandes massas de dados, retirando padrões e conhecimento intrínseco dos dados. A área da saúde é um exemplo de uma área que cria enormes quantidades de dados diariamente, mas que na maior parte das vezes não é retirado conhecimento proveitoso dos mesmos. Este novo conhecimento poderia ajudar os profissionais de saúde a obter resposta para vários problemas. Esta dissertação pretende apresentar todo o processo de descoberta de conhecimento: análise dos dados, preparação dos dados, escolha dos atributos e dos algoritmos, aplicação de técnicas de mineração de dados (classificação, segmentação e regras de associação), escolha dos algoritmos (C5.0, CHAID, Kohonen, TwoSteps, K-means, Apriori) e avaliação dos modelos criados. O projeto baseia-se na metodologia CRISP-DM e foi desenvolvido com a ferramenta Clementine 12.0. O principal intuito deste projeto é retirar padrões e perfis de dadores que possam vir a contrair determinadas doenças (anemia, doenças renais, hepatite, entre outras) ou quais as doenças ou valores anormais de componentes sanguíneos que podem ser comuns entre os dadores.