HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Genetic variability among sugarcane genotypes based on polymorphisms in sucrose metabolism and drought tolerance genes

Target region amplification polymorphism (TRAP) markers were used to estimate the genetic similarity (GS) among 53 sugarcane varieties and five species of the Saccharum complex. Seven fixed primers designed from candidate genes involved in sucrose metabolism and three from those involved in drought response metabolism were used in combination with three arbitrary primers. The clustering of the genotypes for sucrose metabolism and drought response were similar, but the GS based on Jaccard`s coefficient changed. The GS based on polymorphism in sucrose genes estimated in a set of 46 Brazilian varieties, all of which belong to the three Brazilian breeding programs, ranged from 0.52 to 0.9, and that based on drought data ranged from 0.44 to 0.95. The results suggest that genetic variability in the evaluated genes was lower in the sucrose metabolism genes than in the drought response metabolism ones.

Exposure to contaminated water: perceptions and practices in a neighborhood in the city of Manaus, Brazil

Objective. To investigate the modes of water supply and the perception concerning the problems caused by this water among residents of a neighborhood without public supply of water, settled in an area previously used as a garbage dump in the city of Manaus, Brazil. Methods. One hundred and sixty-two semi-structured household interviews were conducted. In addition, a focal group with teachers from a local public school and a meeting with residents were held. The instruments employed focused on the perception and modes of water use and on the process of exposure to chemical contaminants through water. Results. Untreated well water was used by most families. This water was considered to be ""good"" by 64.8% of the individuals interviewed. Most residents (88.3%) declared knowledge about the garbage dump. Of these, 77.6% stated that the garbage dump caused health and environmental problems. However, qualitative analysis of the responses revealed that the residents were not aware of contamination by chemical elements or of the consequences of such contamination. The activities carried out with teachers revealed that they were partially aware of the problem, but did not design interventions to address the issue. In a meeting with neighborhood residents, the presence of social activism concerning the problem was identified, but it did not extend beyond the neighborhood or reach governmental spheres. Conclusions. The study identified a situation of critical exposure that tends to be maintained as a result of misperceptions and lack of social mobilization. The dissemination of research results to teachers and residents was useful to empower subjects.

The use of complementary and alternative therapies by patients with cancer

The aim of this research was to assess the prevalence and predictors of complementary and alternative therapy (CAT) use among cancer patients in Australia. A total of 1492 cancer patients attending nine major public cancer treatment centers in New South Wales, Australia, were asked to complete the Supportive Care Needs Survey. Of the 1354 consenting patients, 888 (65%) returned a completed survey. This article reports the secondary analyses of the survey data, specifically focusing on CAT use. For all cancers, 17.1% of patients were using at least one CAT. The two main demographic characteristics of CAT users were gender and age, where females were more likely to use CAT than males and that CAT use declined as age increased. Time since diagnosis was identified as the only significant clinical predictor of CAT use, where CAT use increased with time until 5 years since diagnosis. Our research shows that herbal treatments and naturopathy are the most popular CAT used by cancer patients (constituting over 30% of all CAT use recorded). The use of CAT among cancer patients is a significant issue in cancer care, especially considering the potential interactions between CAT and conventional medicines. Given that many cancer patients may not be aware of potential risks associated with these interactions it is important that oncologists and others involved in cancer patient care are informed about CAT and its use amongst their patients.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Compliance aware business process design

Historically, business process design has been driven by business objectives, specifically process improvement. However this cannot come at the price of control objectives which stem from various legislative, standard and business partnership sources. Ensuring the compliance to regulations and industrial standards is an increasingly important issue in the design of business processes. In this paper, we advocate that control objectives should be addressed at an early stage, i.e., design time, so as to minimize the problems of runtime compliance checking and consequent violations and penalties. To this aim, we propose supporting mechanisms for business process designers. This paper specifically presents a support method which allows the process designer to quantitatively measure the compliance degree of a given process model against a set of control objectives. This will allow process designers to comparatively assess the compliance degree of their design as well as be better informed on the cost of non-compliance.

The impact of interpersonal and intergroup communication accommodation on perceptions of Chinese students in Australia

Using the framework of communication accommodation theory the authors examined convergence and maintenance on evaluations of Chinese and Australian students. In Study 1, Australian students judged interactions between an Anglo-Australian. and another interactant who either maintained his or converged in speech style. Results indicated that participants were aware of convergence but that speaker ethnicity (Anglo-Australian, Chinese Australian or Chinese national) was a stronger influence on evaluations and future intentions to interact with the speaker In Study 2, Australian students judged Chinese speakers who maintained communication style or converged on interpersonal speech markers, intergroup markers, or both types of markers. Results indicated that the more participants defined themselves in intergroup terms, the more positively they judged intergroup convergence relative to interpersonal convergence and maintenance. This points to the importance of distinguishing between, convergence on interpersonal and intergroup speech markers, and underlines the role of individual differences in the evaluation of convergence.

Molecular characterization of the toxic cyanobacterium Cylindrospermopsis raciborskii and design of a species-specific PCR

Cylindrospermopsis raciborskii is a toxic-bloom-forming cyanobacterium that is commonly found in tropical to subtropical climatic regions worldwide, but it is also recognized as a common component of cyanobacterial communities in temperate climates. Genetic profiles of C. raciborskii were examined in 19 cultured isolates originating from geographically diverse regions of Australia and represented by two distinct morphotypes. A 609-bp region of rpoC1, a DNA-dependent RNA polymerase gene, was amplified by PCR from these isolates with cyanobacterium-specific primers. Sequence analysis revealed that all isolates belonged to the same species, including morphotypes with straight or coiled trichomes. Additional rpoC1 gene sequences obtained for a range of cyanobacteria highlighted clustering of C. raciborskii with other heterocyst-producing cyanobacteria (orders Nostocales and Stigonematales). In contrast, randomly amplified polymorphic DNA and short tandemly repeated repetitive sequence profiles revealed a greater level of genetic heterogeneity among C. raciborskii isolates than did rpoC1 gene analysis, and unique band profiles were also found among each of the cyanobacterial genera examined. A PCR test targeting a region of the rpoC1 gene unique to C. raciborskii was developed for the specific identification of C. raciborskii from both purified genomic DNA and environmental samples. The PCR was evaluated with a number of cyanobacterial isolates, but a PCR-positive result was only achieved with C, raciborskii. This method provides an accurate alternative to traditional morphological identification of C. raciborskii.

MDMA (Ecstasy) neurotoxicity: assessing and communicating the risks

MDMA (3,4-methylenedioxymethamphetamine) is an amphetamine analogue that produces euphoric and stimulant effects and a feeling of closeness towards others.1 and 2 For more than a decade, MDMA (colloquially known as “Ecstasy” or “E”) has been widely used by young adults as a dance-party drug. The usual recreational oral dose is 1-2 tablets (each containing about 60-120 mg of MDMA) a standard oral dose of 0·75–4·00 mg per kg in 60–80 kg people. MDMA is typically used once fortnightly or less because tolerance to the effects of MDMA develops rapidly. More frequent use requires larger doses to achieve the desired effects, but this increases the prevalence of unpleasant side-effects.3 A number of deaths have occurred as a result of malignant hyperthermia or idiosyncractic reactions to the drug, but these have been rare.4 MDMA is perceived by many users to be a safe drug.1 Few report the craving associated with opiates or cocaine3 and most MDMA users are aware of only mild and transient disruptions of functioning.3 and 5 AC Parrott and J Lasky, Ecstasy (MDMA) effects upon mood and cognition: before, during and after a Saturday night dance, Psychopharmacology 139 (1998), pp. 261–268. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (174)5 The perceived safety of MDMA is at odds with animal evidence of MDMA neurotoxicity, an increasing prevalence of hazardous patterns of use among recreational MDMA users, and emerging evidence of neurotoxicity among heavier MDMA users.

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.

Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data

Examples from the Murray-Darling basin in Australia are used to illustrate different methods of disaggregation of reconnaissance-scale maps. One approach for disaggregation revolves around the de-convolution of the soil-landscape paradigm elaborated during a soil survey. The descriptions of soil ma units and block diagrams in a soil survey report detail soil-landscape relationships or soil toposequences that can be used to disaggregate map units into component landscape elements. Toposequences can be visualised on a computer by combining soil maps with digital elevation data. Expert knowledge or statistics can be used to implement the disaggregation. Use of a restructuring element and k-means clustering are illustrated. Another approach to disaggregation uses training areas to develop rules to extrapolate detailed mapping into other, larger areas where detailed mapping is unavailable. A two-level decision tree example is presented. At one level, the decision tree method is used to capture mapping rules from the training area; at another level, it is used to define the domain over which those rules can be extrapolated. (C) 2001 Elsevier Science B.V. All rights reserved.

Polarization vision and its role in biological signaling

Visual pigments, the molecules in photoreceptors that initiate the process of vision, are inherently dichroic, differentially absorbing light according to its axis of polarization. Many animals have taken advantage of this property to build receptor systems capable of analyzing the polarization of incoming light, as polarized light is abundant in natural scenes (commonly being produced by scattering or reflection). Such polarization sensitivity has long been associated with behavioral tasks like orientation or navigation. However, only recently have we become aware that it can be incorporated into a high-level visual perception akin to color vision, permitting segmentation of a viewed scene into regions that differ in their polarization. By analogy to color vision, we call this capacity polarization vision. It is apparently used for tasks like those that color vision specializes in: contrast enhancement, camouflage breaking, object recognition, and signal detection and discrimination. While color is very useful in terrestrial or shallow-water environments, it is an unreliable cue deeper in water due to the spectral modification of light as it travels through water of various depths or of varying optical quality. Here, polarization vision has special utility and consequently has evolved in numerous marine species, as well as at least one terrestrial animal. In this review, we consider recent findings concerning polarization vision and its significance in biological signaling.

A spectral clustering algorithm for manufacturing cell formation

A graph clustering algorithm constructs groups of closely related parts and machines separately. After they are matched for the least intercell moves, a refining process runs on the initial cell formation to decrease the number of intercell moves. A simple modification of this main approach can deal with some practical constraints, such as the popular constraint of bounding the maximum number of machines in a cell. Our approach makes a big improvement in the computational time. More importantly, improvement is seen in the number of intercell moves when the computational results were compared with best known solutions from the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Quality of diabetes care and coronary heart disease absolute risk in patients with type 2 diabetes mellitus in Australian general practice

Objective: To examine the quality of diabetes care and prevention of cardiovascular disease (CVD) in Australian general practice patients with type 2 diabetes and to investigate its relationship with coronary heart disease absolute risk (CHDAR). Methods: A total of 3286 patient records were extracted from registers of patients with type 2 diabetes held by 16 divisions of general practice (250 practices) across Australia for the year 2002. CHDAR was estimated using the United Kingdom Prospective Diabetes Study algorithm with higher CHDAR set at a 10 year risk of >15%. Multivariate multilevel logistic regression investigated the association between CHDAR and diabetes care. Results: 47.9% of diabetic patient records had glycosylated haemoglobin (HbA1c) >7%, 87.6% had total cholesterol >= 4.0 mmol/l, and 73.8% had blood pressure (BP) >= 130/85 mm Hg. 57.6% of patients were at a higher CHDAR, 76.8% of whom were not on lipid modifying medication and 66.2% were not on antihypertensive medication. After adjusting for clustering at the general practice level and age, lipid modifying medication was negatively related to CHDAR (odds ratio (OR) 0.84) and total cholesterol. Antihypertensive medication was positively related to systolic BP but negatively related to CHDAR (OR 0.88). Referral to ophthalmologists/optometrists and attendance at other health professionals were not related to CHDAR. Conclusions: At the time of the study the diabetes and CVD preventive care in Australian general practice was suboptimal, even after a number of national initiatives. The Australian Pharmaceutical Benefits Scheme (PBS) guidelines need to be modified to improve CVD preventive care in patients with type 2 diabetes.