146 resultados para 222


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The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

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In this paper, we propose three meta-heuristic algorithms for the permutation flowshop (PFS) and the general flowshop (GFS) problems. Two different neighborhood structures are used for these two types of flowshop problem. For the PFS problem, an insertion neighborhood structure is used, while for the GFS problem, a critical-path neighborhood structure is adopted. To evaluate the performance of the proposed algorithms, two sets of problem instances are tested against the algorithms for both types of flowshop problems. The computational results show that the proposed meta-heuristic algorithms with insertion neighborhood for the PFS problem perform slightly better than the corresponding algorithms with critical-path neighborhood for the GFS problem. But in terms of computation time, the GFS algorithms are faster than the corresponding PFS algorithms.

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Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

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Background Scientific research is an essential component in guiding improvements in health systems. There are no studies examining the Sri Lankan medical research output at international level. The present study evaluated the Sri Lankan research performance in medicine as reflected by the research publications output between years 2000-2009. Methods This study was based on Sri Lankan medical research publication data, retrieved from the SciVerse Scopus® from January 2000 to December 2009. The process of article selection was as follows: Affiliation - 'Sri Lanka' or 'Ceylon', Publication year - 'January 2000 to December 2009' and Subject area - 'Life and Health Sciences'. The articles identified were classified according to disease, medical speciality, institutions, major international collaborators, authors and journals. Results Sri Lanka's cumulative medical publications output between years 2000-2009 was 1,740 articles published in 160 different journals. The average annual publication growth rate was 9.1%. Majority of the articles were published in 'International' (n = 950, 54.6%) journals. Most articles were descriptive studies (n = 611, 35.1%), letters (n-345, 19.8%) and case reports (n = 311, 17.9%). The articles were authored by 148 different Sri Lankan authors from 146 different institutions. The three most prolific local institutions were Universities of; Colombo (n = 547), Kelaniya (n = 246) and Peradeniya (n = 222). Eighty four countries were found to have published collaborative papers with Sri Lankan authors during the last decade. UK was the largest collaborating partner (n = 263, 15.1%). Malaria (n = 75), Diabetes Mellitus (n = 55), Dengue (n = 53), Accidental injuries (n = 42) and Lymphatic filariasis (n = 40) were the major diseases studied. The 1,740 publications were cited 9,708 times, with an average citation of 5.6 per paper. The most cited paper had 203 citations, while there were 597 publications with no citations. The Sri Lankan authors' contribution to the global medical research output during the last decade was only 0.086%. Conclusion The Sri Lankan medical research output during the last decade is only a small fraction of the global research output. There it is a necessity to setup an enabling environment for research, with a proper vision, support, funds and training. In addition, collaborations across the region need to be strengthened to face common regional health challenges. Keywords: Sri Lanka, Medical research, Publication, Analysis

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The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

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A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

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Background: During December 2010 and January 2011, torrential rainfall in Queensland resulted in the worst flooding in over 50 years. We carried out a community-based survey to assess the health impacts of this flooding in the city of Brisbane. Methods: A community-based survey was conducted in 12 flood-affected electorates using postal questionnaires. A random sample of residents in these areas was drawn from electoral rolls. Questions examined sociodemographic information, the direct impact of flooding on the household, and perceived flood-related health impacts. Outcome variables included perceived flood-related effects on overall and respiratory health, along with mental health outcomes measured by psychosocial distress, reduced sleep quality and probable post-traumatic stress disorder (PTSD). Multivariable logistic regression was used to examine the association between flooding and health outcome variables, adjusted for current health status and socioeconomic factors. Results: 3000 residents were invited to participate in this survey, with 960 responses (32%). People whose households were directly impacted by flooding had a decrease in perceived overall health (OR 5.3, 95% CI: 2.8–10.2), along with increases in psychological distress (OR 1.9, 1.1–3.5), decreased sleep quality (OR 2.3, 1.2–4.4), and probable PTSD (OR 2.3, 1.2–4.5). Residents were also more likely to increase usage of both tobacco (OR 6.3, 2.4–16.8) and alcohol (OR 7.0, 2.2–22.3) after flooding. Conclusions: There were significant impacts of flood events on residents’ health, in particular psychosocial health. Improved support strategies may need to be integrated into existing disaster management programs to reduce flood‐related health impacts.

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Background: During December 2010 and January 2011, torrential rainfall in Queensland resulted in the worst flooding in over 50 years. We carried out a community-based survey to assess the health impacts of this flooding in the city of Brisbane. Methods: A community-based survey was conducted in 12 flood-affected electorates using postal questionnaires. A random sample of residents in these areas was drawn from electoral rolls. Questions examined sociodemographic information, the direct impact of flooding on the household, and perceived flood-related health impacts. Outcome variables included perceived flood-related effects on overall and respiratory health, along with mental health outcomes measured by psychosocial distress, reduced sleep quality and probable post-traumatic stress disorder (PTSD). Multivariable logistic regression was used to examine the association between flooding and health outcome variables, adjusted for current health status and socioeconomic factors. Results: 3000 residents were invited to participate in this survey, with 960 responses (32%). People whose households were directly impacted by flooding had a decrease in perceived overall health (OR 5.3, 95% CI: 2.8–10.2), along with increases in psychological distress (OR 1.9, 1.1–3.5), decreased sleep quality (OR 2.3, 1.2–4.4), and probable PTSD (OR 2.3, 1.2–4.5). Residents were also more likely to increase usage of both tobacco (OR 6.3, 2.4–16.8) and alcohol (OR 7.0, 2.2–22.3) after flooding. Conclusions: There were significant impacts of flood events on residents’ health, in particular psychosocial health. Improved support strategies may need to be integrated into existing disaster management programs to reduce flood-related health impacts.

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Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).

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Deprivation is linked to increased incidence in a number of chronic diseases but its relationship to chronic obstructive pulmonary disease (COPD) is uncertain despite suggestions that the socioeconomic gradient seen in COPD is as great, if not greater, than any other disease (Prescott and Vestbo).1 There is also a need to take into account the confounding effects of malnutrition which have been shown to be independently linked to increased mortality (Collins et al).2 The current study investigated the influence of social deprivation on 1-year survival rates in COPD outpatients, independently of malnutrition. 424 outpatients with COPD were routinely screened for malnutrition risk using the ‘Malnutrition Universal Screening Tool’; ‘MUST’ (Elia),3 between July and May 2009; 222 males and 202 females; mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2. Each individual's deprivation was calculated using the index of multiple deprivation (IMD) which was established according to the geographical location of each patient's address (postcode). IMD includes a number of indicators covering economic, housing and social issues (eg, health, education and employment) into a single deprivation score (Nobel et al).4 The lower the IMD score, the lower an individual's deprivation. The IMD was assigned to each outpatient at the time of screening and related to1-year mortality from the date screened. Outpatients who died within 1-year of screening were significantly more likely to reside within a deprived postcode (IMD 19.7±SD 13.1 vs 15.4±SD 10.7; p=0.023, OR 1.03, 95% CI 1.00 to 1.06) than those that did not die. Deprivation remained a significant independent risk factor for 1-year mortality even when adjusted for malnutrition as well as age, gender and disease severity (binary logistic regression; p=0.008, OR 1.04, 95% CI 1.04 to 1.07). Deprivation was not associated with disease-severity (p=0.906) or body mass index, kg/m2 (p=0.921) using ANOVA. This is the first study to show that deprivation, assessed using IMD, is associated with increased 1-year mortality in outpatients with COPD independently of malnutrition, age and disease severity. Deprivation should be considered in the targeted management of these patients.

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OBJECTIVE: To evaluate a healthy lifestyle intervention to reduce adiposity in children aged 5 to 9 years and assess whether adding parenting skills training would enhance this effect. PARTICIPANTS AND METHODS: We conducted a single-blinded randomized controlled trial of prepubertal moderately obese (International Obesity Task Force cut points) children, aged 5 to 9 years. The 6-month program targeted parents as the agents of change for implementing family lifestyle changes. Only parents attended group sessions. We measured BMI and waist z scores and parenting constructs at baseline, 6, 12, 18, 24 months. RESULTS: Participants (n = 169; 56% girls) were randomized to a parenting skills plus healthy lifestyle group (n = 85) or a healthy lifestyle–only group (n = 84). At final 24-month assessment 52 and 54 children remained in the parenting skills plus healthy lifestyle and the healthy lifestyle–only groups respectively. There were reductions (P < .001) in BMI z score (0.26 [95% confidence interval: 0.22–0.30]) and waist z score (0.33 [95% confidence interval: 0.26–0.40]). There was a 10% reduction in z scores from baseline to 6 months that was maintained to 24 months with no additional intervention. Overall, there was no significant group effect. A similar pattern of initial improvement followed by stability was observed for parenting outcomes and no group effect. CONCLUSIONS: Using approaches that specifically target parent behavior, relative weight loss of ∼10% is achievable in moderately obese prepubertal children and can be maintained for 2 years from baseline. These results justify an investment in treatment as an effective secondary obesity-prevention strategy.