994 resultados para ranking method


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Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce 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. 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 interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of 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 CFAgQuery technique uses the attributes of 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 CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.

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A novel method was developed for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources. This bacterium is ubiquitous in the natural environment and is an important pathogen known to infect Cystic Fibrosis (CF) patients. The transmission route of strains has not yet been defined; current theories include acquisition from an environmental source or through patient-to-patient spread. A highly discriminatory, bioinformatics based, DNA typing method was developed to investigate the relatedness of clinical and environmental isolates. This study found a similarity between the environmental and several CF clonal strains and also highlighted occurrence of environmental P. aeruginosa strains in CF infections.

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We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.

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Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.

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Scaffolding is an essential issue in tissue engineering and scaffolds should answer certain essential criteria: biocompatibility, high porosity, and important pore interconnectivity to facilitate cell migration and fluid diffusion. In this work, a modified solvent castingparticulate leaching out method is presented to produce scaffolds with spherical and interconnected pores. Sugar particles (200–300 lm and 300–500 lm) were poured through a horizontal Meker burner flame and collected below the flame. While crossing the high temperature zone, the particles melted and adopted a spherical shape. Spherical particles were compressed in plastic mold. Then, poly-L-lactic acid solution was cast in the sugar assembly. After solvent evaporation, the sugar was removed by immersing the structure into distilled water for 3 days. The obtained scaffolds presented highly spherical interconnected pores, with interconnection pathways from 10 to 100 lm. Pore interconnection was obtained without any additional step. Compression tests were carried out to evaluate the scaffold mechanical performances. Moreover, rabbit bone marrow mesenchymal stem cells were found to adhere and to proliferate in vitro in the scaffold over 21 days. This technique produced scaffold with highly spherical and interconnected pores without the use of additional organic solvents to leach out the porogen.

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One limitation of electrospinning stems from the charge build-up that occurs during processing, preventing further fibre deposition and limiting the scaffold overall thickness and hence their end-use in tissue engineering applications targeting large tissue defect repair. To overcome this, we have developed a technique in which thermally induced phase separation (TIPS) and electrospinning are combined. Thick three-dimensional, multilayered composite scaffolds were produced by simply stacking individual polycaprolactone (PCL) microfibrous electrospun discs into a cylindrical holder that was filled with a 3% poly(lactic-co-glycolic acid) (PLGA) solution in dimethylsulfoxide (a good solvent for PLGA but a poor one for PCL). The construct was quenched in liquid nitrogen and the solvent removed by leaching out in cold water. This technique enables the fabrication of scaffolds composed principally of electrospun membranes that have no limit to their thickness. The mechanical properties of these scaffolds were assessed under both quasi-static and dynamic conditions. The multilayered composite scaffolds had similar compressive properties to 5% PCL scaffolds fabricated solely by the TIPS methodology. However, tensile tests demonstrated that the multilayered construct outperformed a scaffold made purely by TIPS, highlighting the contribution of the electrospun component of the composite scaffold to enhancing the overall mechanical property slate. Cell studies revealed cell infiltration principally from the scaffold edges under static seeding conditions. This fabrication methodology permits the rapid construction of thick, strong scaffolds from a range of biodegradable polymers often used in tissue engineering, and will be particularly useful when large dimension electrospun scaffolds are required.

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Review question/objective What is the effect of using the teach-back method for health education to improve adherence to treatment regimen and self-management in chronic disease? Inclusion criteria Types of participants This review will consider all studies that include adult patients (aged 18 years and over) in any healthcare setting, either as inpatients (eg acute care, medical and surgical wards) or those who attend primary health care, family medical practice, general medical practice, clinics, outpatient departments, rehabilitation or community settings. Participants need to have been diagnosed as having one or more chronic diseases including heart failure, diabetes, cardiovascular disease, cancer, respiratory disease, asthma, chronic obstructive pulmonary disease, chronic kidney disease, arthritis, epilepsy or a mental health condition. Studies that include seriously ill patients, and/or those who have impairments in verbal communication and cognitive function will be excluded. Types of intervention This review will consider studies that investigate the use of the teach-back method alone or in combination with other supporting education, either in routine or research intervention education programs; regardless of how long the programs were and whether or not a follow-up was conducted. The intervention could be delivered by any healthcare professional. The comparator will be any health education for chronic disease that does not include the teach-back method. Types of outcomes Primary outcomes of interest are disease-specific knowledge, adherence, and self-management knowledge, behavior and skills measured using patient report, nursing observation or validated measurement scales. Secondary outcomes include knowledge retention, self-efficacy, hospital readmission, hospitalization, and quality of life, also measured using patient report, nursing observation, hospital records or validated measurement scales.

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The measurement of losses in high efficiency / high power converters is difficult. Measuring the losses directly from the difference between the input and output power results in large errors. Calorimetric methods are usually used to bypass this issue but introduce different problems, such as, long measurement times, limited power loss measurement range and/or large set up cost. In this paper the total losses of a converter are measured directly and switching losses are exacted. The measurements can be taken with only three multimeters and a current probe and a standard bench power supply. After acquiring two or three power loss versus output current sweeps, a series of curve fitting processes are applied and the switching losses extracted.

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The key to reducing cost of electric vehicles is integration. All too often systems such as the motor, motor controller, batteries and vehicle chassis/body are considered as separate problems. The truth is that a lot of trade-offs can be made between these systems, causing an overall improvement in many areas including total cost. Motor controller and battery cost have a relatively simple relationship; the less energy lost in the motor controller the less energy that has to be carried in the batteries, hence the lower the battery cost. A motor controller’s cost is primarily influenced by the cost of the switches. This paper will therefore present a method of assessing the optimal switch selection on the premise that the optimal switch is the one that produces the lowest system cost, where system cost is the cost of batteries + switches.

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This paper elaborates the approach used by the Applied Data Mining Research Group (ADMRG) for the Social Event Detection (SED) Tasks of the 2013 MediaEval Benchmark. We extended the constrained clustering algorithm to apply to the first semi-supervised clustering task, and we compared several classifiers with Latent Dirichlet Allocation as feature selector in the second event classification task. The proposed approach focuses on scalability and efficient memory allocation when applied to a high dimensional data with large clusters. Results of the first task show the effectiveness of the proposed method. Results from task 2 indicate that attention on the imbalance categories distributions is needed.

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Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.

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This study aimed to identify new peptide antigens from Chlamydia (C.) trachomatis in a proof of concept approach which could be used to develop an epitope-based serological diagnostic for C. trachomatis related infertility in women. A bioinformatics analysis was conducted examining several immunodominant proteins from C. trachomatis to identify predicted immunoglobulin epitopes unique to C. trachomatis. A peptide array of these epitopes was screened against participant sera. The participants (all female) were categorized into the following cohorts based on their infection and gynecological history; acute (single treated infection with C. trachomatis), multiple (more than one C. trachomatis infection, all treated), sequelae (PID or tubal infertility with a history of C. trachomatis infection), and infertile (no history of C. trachomatis infection and no detected tubal damage). The bioinformatics strategy identified several promising epitopes. Participants who reacted positively in the peptide 11 ELISA were found to have an increased likelihood of being in the sequelae cohort compared to the infertile cohort with an odds ratio of 16.3 (95% c.i. 1.65 – 160), with 95% specificity and 46% sensitivity (0.19-0.74). The peptide 11 ELISA has the potential to be further developed as a screening tool for use during the early IVF work up and provides proof of concept that there may be further peptide antigens which could be identified using bioinformatics and screening approaches.

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An HPLC with SPE method has been developed for analysis of constituents in rat blood after oral administration of the extract of Acanthopanax senticosus (ASE). The plasma sample was prepared by SPE method equipped with Oasis HLB cartridge (3cc, 60 mg). The analysis was performed on a Dikma Diamonsil RP(18) column (4.6 mmx150 mm, 5 microm) with the gradient elution of solvent A (ACN) and solvent B (0.1% aqueous phosphoric acid, v/v) and the detection wavelength was set at 270 nm. The calibration curve was linear over the range of 0.156-15.625 microg/mL. The LOD was 60 ng/mL. The intraday precision was less than 5.80%, and the interday precision was less than 6.0%. The recovery was (87.30 +/- 1.73)%. As a result, 19 constituents were detected in rat plasma after oral administration of the ASE, including 11 original compounds in ASE and eight metabolites, and three of the metabolites originated from syringin in ASE. Six constituents were identified by comparing with the corresponding reference compounds.

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Isofraxidin is one of the main bioactive constituents in the root of Acanthopanax senticosus, which has antifatigue, antistress, and immuno-accommondating effects. In this study, an ultraperformance LC (UPLC)-ESI MS method was developed for analyzing isofraxidin and its metabolites in rat plasma. The analysis was performed on a UPLC coupled with ESI MS (quadropole MS tandem TOF MS). The lower LOD (LLOD) for isofraxidin was 0.25 ng/mL, the intraday precision was less than 10%, the interday precision was less than 10%, and the extraction recovery was more than 80%. Isofraxidin and two metabolites (M1 and M2) were detected in rat plasma after oral administration of isofraxidin, and the molecular polarities of M1 and M2 were both increased compared to isofraxidin. The metabolites were identified as 5,6-dihydroxyl-7-methoxycoumarin and 5-hydroxyl-6,7-dimethoxycoumarin when subjected to parent ion spectra, product ion spectra, and extract mass and element composition analyses.

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Railway Bridges deteriorate over time due to different critical factors including, flood, wind, earthquake, collision, and environment factors, such as corrosion, wear, termite attack, etc. In current practice, the contributions of the critical factors, towards the deterioration of railway bridges, which show their criticalities, are not appropriately taken into account. In this paper, a new method for quantifying the criticality of these factors will be introduced. The available knowledge as well as risk analyses conducted in different Australian standards and developed for bridge-design will be adopted. The analytic hierarchy process (AHP) is utilized for prioritising the factors. The method is used for synthetic rating of railway bridges developed by the authors of this paper. Enhancing the reliability of predicting the vulnerability of railway bridges to the critical factors, will be the significant achievement of this research.