990 resultados para recommendation system


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Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that supports students learning to program. The PHP ITS works by providing exercises for students to solve and then providing feedback based on their solutions. The major challenge here is to be able to identify many semantically equivalent solutions to a single exercise. The PHP ITS achieves this by using theories of Artificial Intelligence (AI) including first-order predicate logic and classical and hierarchical planning to model the subject matter taught by the system. This paper highlights the approach taken by the PHP ITS to analyse students’ programs that include a number of program constructs that are used by beginners of web development. The PHP ITS was built using this model and evaluated in a unit at the Queensland University of Technology. The results showed that it was capable of correctly analysing over 96 % of the solutions to exercises supplied by students.

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Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

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Perhaps no other patient safety intervention depends so acutely on effective interprofessional teamwork for patient survival than the hospital rapid response system (RRS). Yet little is known about nurse-physician relationships when rescuing at-risk patients. This study compared nursing and medical staff perceptions of a mature RRS at a large tertiary hospital. Findings indicate the RRS may be failing to address a hierarchical culture and systems-level barriers to early recognition and response to patient deterioration.

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This thesis utilised mixed-methods study design to understand the factors that influence the translation and implementation of central human resources in health policy at the district and commune health levels. It provided recommendations for changes to enhance governance approaches to human resources for health policy implementation at local and national levels. This thesis has also contributed to the evolution of the theory on health staff motivation and performance through the description and testing of a new model, using data from a survey on 262 health staff and 43 in-depth interviews conducted in two northern mountainous provinces of Vietnam.

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Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

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This study examines the impact of incentives on commuters' travel behavior based upon a questionnaire survey conducted with respect to the Beijing Subway System. Overall, we find that offering incentives to commuters, particularly fast food restaurant-related services and reduced ticket fares, has a positive influence on avoiding the morning rush hour. Furthermore, by using an interaction analysis, we discover that a flexible work schedule has an impact on commuters' behavior and the efficiency of the subway system. Finally, we recommend two possible policies to maximize the utility of the subway system and to reduce congestion at the peak of morning service: (1) a set of incentives that includes free wireless internet service with a coupon for breakfast and a discount on ticket fares before the morning peak, and; (2) the introduction of a flexible work schedule.

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In this paper we discuss the failure of the employee voice system at the Bundaberg Base Hospital (BBH) in Australia. Surgeon Jayant Patel was arrested over the deaths of patients on whom he operated when he was the director of surgery at the hospital. Our interest is in the reasons the established employee voice mechanisms failed when employees attempted to bring serious issues to the attention of managers. Our data is based on an analysis of the sworn testimonies of participants who participated in two inquiries concerning these events. An analysis of the events with a particular focus on the failings of the voice system is presented. We ask the following: how and why did the voice systems in the case of the BBH fail?

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Nursing students used GoSoapBox, a web-based student response system to poll responses to multiple choice questions (MCQs) presented during bioscience lectures. Participation in GoSoapBox appears to have facilitated student engagement, interaction and learning. The majority of students surveyed appreciated the immediate feedback to the student responses and being able to participate anonymously. The use of this tool facilitated collaborative group and class discussion and clarification around any misconceptions or challenging concepts. Information collected using GoSoapBox provided the academic with feedback allowing for reflection, adjustment and improvement in framing of formative and summative MCQs.

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Nursing students used GoSoapBox, a web-based student response system to poll responses to multiple choice questions (MCQs) presented during bioscience lectures. Participation in GoSoapBox appears to have facilitated student engagement, interaction and learning. The majority of students surveyed appreciated the immediate feedback to the student responses and being able to participate anonymously. The use of this tool facilitated collaborative group and class discussion and clarification around any misconceptions or challenging concepts. Information collected using GoSoapBox provided the academic with feedback allowing for reflection, adjustment and improvement in framing of formative and summative MCQs.

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This chapter is focussed on the research and development of an intelligent driver warning system (IDWS) as a means to improve road safety and driving comfort. Two independent IDWS case studies are presented. The first study examines the methodology and implementation for attentive visual tracking and trajectory estimation for dynamic scene segmentation problems. In the second case study, the concept of driver modelling is evaluated which can be used to provide useful feedback to drivers. In both case studies, the quality of IDWS is largely determined by the modelling capability for estimating multiple vehicle trajectories and modelling driving behaviour. A class of modelling techniques based on neural-fuzzy systems, which exhibits provable learning and modelling capability, is proposed. For complex modelling problems where the curse of dimensionality becomes an issue, a network construction algorithm based on Adaptive Spline Modelling of Observation Data (ASMOD) is also proposed.

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There is an increasing demand for Unmanned Aerial Systems (UAS) to carry suspended loads as this can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. The constant variation in operating point induced by the slung load also causes conventional controllers to demand increased control effort. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present a novel controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions. The paper describes a System Dynamics and Control Simulation Toolbox for use with MATLAB/SIMULINK which includes a detailed simulation of the multi-rotor and slung load as well as a predictive controller to manage the nonlinear dynamics whilst accounting for system constraints. It is demonstrated that the controller simultaneously tracks specified waypoints and actively damps large slung load oscillations. A linear-quadratic regulator (LQR) is derived and control performance is compared. Results show the improved performance of the predictive controller for a larger flight envelope, including aggressive manoeuvres and large slung load displacements. The computational cost remains relatively small, amenable to practical implementations.

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Hyperthermia, raised temperature, has been used as a means of treating cancer for centuries. Hippocrates (400 BC) and Galen (200 BC) used red-hot irons to treat small tumours. Much later, after the Renaissance, there are many reports of spontaneous tumour regression in patients with fevers produced by erysipelas, malaria, smallpox, tuberculosis and influenza. These illnesses produce fevers of about 40 °C which last for several days. Temperatures of at least 40 °C were found to be necessary for tumour regression. Towards the end of the nineteenth century pyrogenic bacteria were injected into patients with cancer. In 1896, Coly used a mixture of erysipelas and B. prodigeosus, with some success...

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We propose an architecture for a rule-based online management systems (RuleOMS). Typically, many domain areas face the problem that stakeholders maintain databases of their business core information and they have to take decisions or create reports according to guidelines, policies or regulations. To address this issue we propose the integration of databases, in particular relational databases, with a logic reasoner and rule engine. We argue that defeasible logic is an appropriate formalism to model rules, in particular when the rules are meant to model regulations. The resulting RuleOMS provides an efficient and flexible solution to the problem at hand using defeasible inference. A case study of an online child care management system is used to illustrate the proposed architecture.

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Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.