985 resultados para usage patterns


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Analyzing how software engineers use the Integrated Development Environment (IDE) is essential to better understanding how engineers carry out their daily tasks. Spotter is a code search engine for the Pharo programming language. Since its inception, Spotter has been rapidly and broadly adopted within the Pharo community. However, little is known about how practitioners employ Spotter to search and navigate within the Pharo code base. This paper evaluates how software engineers use Spotter in practice. To achieve this, we remotely gather user actions called events. These events are then visually rendered using an adequate navigation tool chain. Sequences of events are represented using a visual alphabet. We found a number of usage patterns and identified underused Spotter features. Such findings are essential for improving Spotter.

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The spread of bacteria resistant to antimicrobial agents calls for population-wide treatment strategies to delay or reverse the trend toward antibiotic resistance. Here we propose new criteria for the evaluation of the population-wide effects of treatment protocols for directly transmitted bacterial infections and discuss different usage patterns for single and multiple antibiotic therapy. A mathematical model suggests that the long-term benefit of single drug treatment from introduction of the antibiotic until a high frequency of resistance precludes its use is almost independent of the pattern of antibiotic use. When more than one antibiotic is employed, sequential use of different antibiotics in the population (“cycling”) is always inferior to treatment strategies where, at any given time, equal fractions of the population receive different antibiotics. However, treatment of all patients with a combination of antibiotics is in most cases the optimal treatment strategy.

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With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

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Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.

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The aim of the Rural Medicine Rotation (RMR) at the University of Queensland (UQ) is to give all third year medical students exposure to and an understanding of, clinical practice in Australian rural or remote locations. A difficulty in achieving this is the relatively short period of student clinical placements, in only one or two rural or remote locations. A web-based Clinical Discussion Board (CDB) has been introduced to address this problem by allowing students at various rural sites to discuss their rural experiences and clinical issues with each other. The rationale is to encourage an understanding of the breadth and depth of rural medicine through peer-based learning. Students are required to submit a minimum of four contributions over the course of their six week rural placement. Analysis of student usage patterns shows that the majority of students exceeded the minimum submission criteria indicating motivation rather than compulsion to contribute to the CDB. There is clear evidence that contributing or responding to the CDB develops studentâ??s critical thinking skills by giving and receiving assistance from peers, challenging attitudes and beliefs and stimulating reflective thought. This is particularly evident in regard to issues involving ethics or clinical uncertainty, subject areas that are not in the medical undergraduate curriculum, yet are integral to real-world medical practice. The CDB has proved to be a successful way to understand the concerns and interests of third year medical students immersed in their RMR and also in demonstrating how technology can help address the challenge of supporting students across large geographical areas. We have recently broadened this approach by including students from the Rural Program at The Ohio State University College of Medicine. This important international exchange of ideas and approaches to learning is expected to broaden clinical training content and improve understanding of rural issues.

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Objective. To determine whether copper incorporated into hospital ward furnishings and equipment can reduce their surface microbial load. Design. A crossover study. Setting. Acute care medical ward with 19 beds at a large university hospital. Methods. Fourteen types of frequent-touch items made of copper alloy were installed in various locations on an acute care medical ward. These included door handles and push plates, toilet seats and flush handles, grab rails, light switches and pull cord toggles, sockets, overbed tables, dressing trolleys, commodes, taps, and sink fittings. Their surfaces and those of equivalent standard items on the same ward were sampled once weekly for 24 weeks. The copper and standard items were switched over after 12 weeks of sampling to reduce bias in usage patterns. The total aerobic microbial counts and the presence of indicator microorganisms were determined. Results. Eight of the 14 copper item types had microbial counts on their surfaces that were significantly lower than counts on standard materials. The other 6 copper item types had reduced microbial numbers on their surfaces, compared with microbial counts on standard items, but the reduction did not reach statistical significance. Indicator microorganisms were recovered from both types of surfaces; however, significantly fewer copper surfaces were contaminated with vancomycin-resistant enterococci, methicillin-susceptible Staphylococcus aureus, and coliforms, compared with standard surfaces. Conclusions. Copper alloys (greater than or equal to 58% copper), when incorporated into various hospital furnishings and fittings, reduce the surface microorganisms. The use of copper in combination with optimal infection-prevention strategies may therefore further reduce the risk that patients will acquire infection in healthcare environments.

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This paper considers the use of general performance measures in evaluating specific planning and design decisions in higher education and reflects on the students' learning process. Specifically, it concerns the use of the MENTOR multimedia computer aided learning package for helping students learn about OR as part of a general business degree. It includes the transfer of responsibility for a learning module to a new staff member and a change from a single tutor to a system involving multiple tutors. Student satisfaction measures, learning outcome measures and MENTOR usage patterns are examined in monitoring the effects of the changes in course delivery. The results raise some questions about the effectiveness of general performance measures in supporting specific decisions relating to course design and planning.

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With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

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The objective of this research was to develop a methodology for transforming and dynamically segmenting data. Dynamic segmentation enables transportation system attributes and associated data to be stored in separate tables and merged when a specific query requires a particular set of data to be considered. A major benefit of dynamic segmentation is that individual tables can be more easily updated when attributes, performance characteristics, or usage patterns change over time. Applications of a progressive geographic database referencing system in transportation planning are vast. Summaries of system condition and performance can be made, and analyses of specific portions of a road system are facilitated.

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This study deals with the discussions of contemporary interventions in public spaces in areas of heritage value. The product of this dissertation is an Intervention Project to Marechal Deodoro Square located in Teresina/PI center. The starting point for understanding the theme of this study is to investigate the accessibility and vitality of a public space - through relationship between form and uses. The spatial properties of accessibility and visibility as well as the distribution of land use - factors were associated with distinct patterns of vitality - and compared to usage patterns observed in situ and statements from users obtained through the results of the questionnaires. In attention to questions about the building constructed, particularly in historical centers, considers the guidelines to define intervention strategies in the square, consisted in the development of simulations that after evaluation of results of redesign, was chosen the best option to meet the necessary requirements to the performance, considering the spatial properties of integration and visibility that meet these requirements. Therefore, the "Intervention Project" carried out for the Marechal Deodoro Square characterization proposed items are discussed: spatial structure, vegetation, road network, pavements, street furniture and lighting

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Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.

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This study deals with the discussions of contemporary interventions in public spaces in areas of heritage value. The product of this dissertation is an Intervention Project to Marechal Deodoro Square located in Teresina/PI center. The starting point for understanding the theme of this study is to investigate the accessibility and vitality of a public space - through relationship between form and uses. The spatial properties of accessibility and visibility as well as the distribution of land use - factors were associated with distinct patterns of vitality - and compared to usage patterns observed in situ and statements from users obtained through the results of the questionnaires. In attention to questions about the building constructed, particularly in historical centers, considers the guidelines to define intervention strategies in the square, consisted in the development of simulations that after evaluation of results of redesign, was chosen the best option to meet the necessary requirements to the performance, considering the spatial properties of integration and visibility that meet these requirements. Therefore, the "Intervention Project" carried out for the Marechal Deodoro Square characterization proposed items are discussed: spatial structure, vegetation, road network, pavements, street furniture and lighting

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This study examines worldwide usage of over 600,000 e-books from Ebook Library (EBL) and ebrary. Using multiple modes of analysis, the study shows that there are variations in usage by geographic region as well as by subject. The study examines usage in relation to availability of titles, different types of usage per session, usage of the top ten percent of titles, and intensive and extensive use. These patterns can be used for benchmarking and as a model for local e-book studies.

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We contribute to the stated preference literature by addressing scale usage heterogeneity regarding how individuals answer attitudinal questions capturing lack of trust in institutions and fairness issues. Using a latent class model, we conduct a contingent valuation study to elicit the willingness-to-pay to preserve a recreational site. We find evidence that respondents within the same class, that is, with similar preferences and attitudes, interpret the Likert scale differently when answering the attitudinal questions. We identify different patterns of scale usage heterogeneity within and across classes and associate them with individual characteristics. Our approach contributes to better a understanding of individual behavior in the presence of protest attitudes.

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INTRODUCTION : Antimicrobial resistance is an increasing threat in hospitalized patients, and inappropriate empirical antimicrobial therapy is known to adversely affect outcomes in ventilator-associated pneumonia (VAP). The aim of this study was to evaluate antimicrobial usage, incidence, etiology, and antimicrobial resistance trends for prominent nosocomial pathogens causing ventilator-associated pneumonia in a clinical-surgical intensive care unit (ICU). METHODS : Gram-negative bacilli and Staphylococcus aureus causing VAP, as well as their antimicrobial resistance patterns and data on consumption (defined daily dose [DDD] per 1,000 patient days) of glycopeptides, extended-spectrum cephalosporins, and carbapenems in the unit were evaluated in two different periods (A and B). RESULTS: Antimicrobial use was high, mainly of broad-spectrum cephalosporins, with a significant increase in the consumption of glycopeptides (p < 0.0001) and carbapenems (p < 0.007) in period B. For Acinetobacter baumannii and members of the Enterobacteriaceae family, 5.27- and 3.06-fold increases in VAPs, respectively, were noted, and a significant increase in resistance rates was found for imipenem-resistant A. baumannii (p = 0.003) and third-generation cephalosporins-resistant Enterobacteriaceae (p = 0.01) isolates in this same period. CONCLUSIONS: Our results suggest that there is a link between antibiotics usage at institutional levels and resistant bacteria. The use of carbapenems was related to the high rate of resistance in A. baumannii and therefore a high consumption of imipenem/meropenem could play a major role in selective pressure exerted by antibiotics in A. baumannii strains.