878 resultados para USED CARS
Resumo:
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 them in making good decisions about which product to buy from the vast number of product choices available to them. 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 recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.
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Computer games have become a commonplace but engaging activity among students. They enjoy playing computer games as they can perform larger-than-life activities virtually such as jumping from great heights, flying planes, and racing cars; actions that are otherwise not possible in real life. Computer games also offer user interactivity which gives them a certain appeal. Considering this appeal, educators should consider integrating computer games into student learning and to encourage students to author computer games of their own. It is thought that students can be engaged in learning by authoring and using computer games and can also gain essential skills such as collaboration, teamwork, problem solving and deductive reasoning. The research in this study revolves around building student engagement through the task of authoring computer games. The study aims to demonstrate how the creation and sharing of student-authored educational games might facilitate student engagement and how ICT (information and communication technology) plays a supportive role in student learning. Results from this study may lead to the broader integration of computer games into student learning and contribute to similar studies. In this qualitative case study, based in a state school in a low socio-economic area west of Brisbane, Australia, students were selected in both junior and senior secondary classes who have authored computer games as a part of their ICT learning. Senior secondary students (Year 12 ICT) were given the task of programming the games, which were to be based on Mathematics learning topics while the junior secondary students (Year 8 ICT) were given the task of creating multimedia elements for the games. A Mathematics teacher volunteered to assist in the project and provided guidance on the inclusion of suitable Mathematics curricular content into these computer games. The student-authored computer games were then used to support another group of Year 8 Mathematics students to learn the topics of Area, Volume and Time. Data was collected through interviews, classroom observations and artefacts. The teacher researcher, acting in the role of ICT teacher, coordinated with the students and the Mathematics teacher to conduct this study. Instrumental case study was applied as research methodology and Third Generation Activity Theory served as theoretical framework for this study. Data was analysed adopting qualitative coding procedures. Findings of this study indicate that having students author and play computer games promoted student engagement and that ICT played a supportive role in learning and allowed students to gain certain essential skills. Although this study will suggest integrating computer games to support classroom learning, it cannot be presumed that computer games are an immediate solution for promoting student engagement.
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Introduction: Eccentric exercise (EE) is a commonly used treatment for Achilles tendinopathy. While vibrations in the 8–12 Hz frequency range generated during eccentric muscle actions have been put forward as a potential mechanism for the beneficial effect of EE, optimal loading parameters required to expedite recovery are currently unknown. Alfredson's original protocol employed 90 repetitions of eccentric loading, however abbreviated protocols consisting of fewer repetitions (typically 45) have been developed, albeit with less beneficial effect. Given that 8–12 Hz vibrations generated during isometric muscle actions have been previously shown to increase with fatigue, this research evaluated the effect of exercise repetition on motor output vibrations generated during EE by investigating the frequency characteristics of ground reaction force (GRF) recorded throughout the 90 repetitions of Alfredson's protocol. Methods: Nine healthy adult males performed six sets (15 repetitions per set) of eccentric ankle exercise. GRF was recorded at a frequency of 1000 Hz throughout the exercise protocol. The frequency power spectrum of the resultant GRF was calculated and normalized to total power. Relative spectral power was summed over 1 Hz widows within the frequency rage 7.5–11.5 Hz. The effect of each additional exercise set (15 repetitions) on the relative power within each widow was investigated using a general linear modelling approach. Results: The magnitude of peak relative power within the 7.5–11.5 Hz bandwidth increased across the six exercise sets from 0.03 in exercise set one to 0.12 in exercise set six (P < 0.05). Following the 4th set of exercise the frequency at which peak relative power occurred shifted from 9 to 10 Hz. Discussion: This study has demonstrated that successive repetitions of eccentric loading over six exercise sets results in an increase in the amplitude of motor output vibrations in the 7.5–11.5 Hz bandwidth, with an increase in the frequency of these vibrations occurring after the 4th set (60th repetition). These findings are consistent with findings from previous studies of muscle fatigue. Assuming that the magnitude and frequency of these vibrations represent important stimuli for tendon remodelling as hypothesized within the literature, the findings of this study question the role of abbreviated EE protocols and raise the question; can EE protocols for tendinopathy be optimized by performing eccentric loading to fatigue?
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Originally developed in bioinformatics, sequence analysis is being increasingly used in social sciences for the study of life-course processes. The methodology generally employed consists in computing dissimilarities between the trajectories and, if typologies are sought, in clustering the trajectories according to their similarities or dissemblances. The choice of an appropriate dissimilarity measure is a major issue when dealing with sequence analysis for life sequences. Several dissimilarities are available in the literature, but neither of them succeeds to become indisputable. In this paper, instead of deciding upon one dissimilarity measure, we propose to use an optimal convex combination of different dissimilarities. The optimality is automatically determined by the clustering procedure and is defined with respect to the within-class variance.
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The existing literature shows driving speed significantly affects levels of safety, emissions, and stress in driving. In addition, drivers who feel tense when driving have been found to drive more slowly than others. These findings were mostly obtained from crash data analyses or field studies, and less is known regarding driver perceptions of the extent to which reducing their driving speed would improve road safety, reduce their car’s emissions, and reduce stress and road rage. This paper uses ordered probit regression models to analyse responses from 3538 Queensland drivers who completed an online RACQ survey. Drivers most strongly agreed that reducing their driving speed would improve road safety, less strongly agreed that reducing their driving speed would reduce their car’s emissions and least strongly agreed that reducing their driving speed would reduce stress and road rage. Younger drivers less strongly agreed that these benefits would occur than older drivers. Drivers of automatic cars and those who are bicycle commuters agreed more to these benefits than other drivers. Female drivers agreed more strongly than males on improving safety and reducing stress and road rage. Type of fuel used, engine size, driving experience, and distance driven per week were also found to be associated with driver perceptions, although these were not found to be significant in all of the regression models. The findings from this study may help in developing targeted training or educational measures to improve drivers’ willingness to reduce their driving speed.
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The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.
Resumo:
To identify potential migraine therapeutics, extracts of eighteen plants were screened to detect plant constituents affecting ADP induced platelet aggregation and [14C]5-hydroxytryptamine (5-HT) release. Extracts of the seven plants exhibiting significant inhibition of platelet function were reanalysed in the presence of polyvinyl pyrrolidone (PVP) to remove polyphenolic tannins that precipitate proteins. Two of these extracts no longer exhibited inhibition of platelet activity after removal of tannins. However, extracts of Crataegus monogyna, Ipomoea pes-caprae, Eremophila freelingii, Eremophila longifolia, and Asteromyrtus symphyocarpa still potently inhibited ADP induced human platelet [14C]5-HT release in vitro, with levels ranging from 62 to 95% inhibition. I. pes-caprae, and C. monogyna also caused significant inhibition of ADP induced platelet aggregation. All of these plants have been previously used as traditional headache treatments, except for C. monogyna which is used primarily for protective effects on the cardiovascular system. Further studies elucidating the compounds that are responsible for these anti-platelet effects are needed to determine their exact mechanism of action.
Resumo:
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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Electrostatic spinning or electrospinning is a fiber spinning technique driven by a high-voltage electric field that produces fibers with diameters in a submicrometer to nanometer range.1 Nanofibers are typical one-dimensional colloidal objects with an increased tensile strength, whose length can achieve a few kilometers and the specific surface area can be 100 m2 g–1 or higher.2 Nano- and microfibers from biocompatible polymers and biopolymers have received much attention in medical applications3 including biomedical structural elements (scaffolding used in tissue engineering,2,4–6 wound dressing,7 artificial organs and vascular grafts8), drug and vaccine delivery,9–11 protective shields in speciality fabrics, multifunctional membranes, etc. Other applications concern superhydrophobic coatings,12 encapsulation of solid materials,13 filter media for submicron particles in separation industry, composite reinforcement and structures for nano-electronic machines.
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We conducted on-road and simulator studies to explore the mechanisms underpinning driver-rider crashes. In Study 1 the verbal protocols of 40 drivers and riders were assessed at intersections as part of a 15km on-road route in Melbourne. Network analysis of the verbal transcripts highlighted key differences in the situation awareness of drivers and riders at intersections. In a further study using a driving simulator we examined in car drivers the influence of acute exposure to motorcyclists. In a 15 min simulated drive, 40 drivers saw either no motorcycles or a high number of motorcycles in the surrounding traffic. In a subsequent 45-60 min drive, drivers were asked to detect motorcycles in traffic. The proportion of motorcycles was manipulated so that there was either a high (120) or low (6) number of motorcycles during the drive. Those drivers exposed to a high number of motorcycles were significantly faster at detecting motorcycles. Fundamentally, the incompatible situation awareness at intersections by drivers and riders underpins the conflicts. Study 2 offers some suggestion for a countermeasure here, although more research around schema and exposure training to support safer interactions is needed.
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Since the pioneering work of Hough in 1902 (1) the term ‘delayed onset muscle soreness (DOMS)’ has dominated the field of athletic recovery. DOMS typically occurs after exercise induced muscle damage (EIMD), particularly if the exercise is unaccustomed or involves a large amount of eccentric (muscle lengthening) contractions. The symptoms of EIMD manifest as a temporary reduction in muscle force, disturbed proprioceptive acuity, increases in inflammatory markers both within the injured muscle and in the blood as well as increased muscle soreness, stiffness and swelling. The intensity of discomfort and soreness associated with DOMS increases within the first 24 hours, peaks between 24 and 72 hours, before subsiding and eventually disappearing 5-7 days after the exercise. Consequently, DOMS may interfere with athletic training or competition and several recovery interventions have been utilised by athletes and coaches in an attempt to offset the negative effects...
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Introduction: Ondansetron is a 5-HT3 receptor antagonist commonly used as an anti-emetic to prevent the nausea and vomiting associated with anti-cancer drugs, cancer radiotherapy, or postoperatively. Recently, the US Food and Drug Administration (FDA) issued a warning for ondansetron due to a potential for prolongation of the QT interval of the electrocardiogram (ECG), a phenomenon that is associated with an increased risk of the potentially fatal arrhythmia torsade de pointes. Areas covered: We undertook a review of the cardiac safety of ondansetron. Our primary sources of information were PubMed (with downloading of full articles), and the internet. Expert opinion: The dose of ondansetron that the FDA has concerns about is 32 mg iv (or several doses that are equivalent to this), which is only used in preventing nausea and vomiting associated with cancer chemotherapy. This suggests that ondansetron may be safe in the lower doses used to prevent the nausea and vomiting in radiation treatment or postoperatively. However, as there is a report that a lower dose of ondansetron prolonged the QT interval in healthy volunteers, this needs to be clarified by the FDA. More research needs to be undertaken of the relationship between QT prolongation and torsades in order that the FDA can produce clear-cut evidence of pro-arrhythmic risk when introducing warnings for this.
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Pilot cars are used in one-lane two-way work zones to guide traffic and keep their speeds within posted limits. While many studies have examined the effectiveness of measures to reduce vehicle speeds in work zones, little is known about the reductions achievable through the use of pilot cars. This paper examines the effectiveness of a pilot car in reducing travel speeds in a rural highway work zone in Queensland, Australia. Analysis of speed data covering a period of five days showed that a pilot car reduced average speeds at the treatment location, but not downstream. The proportion of vehicles speeding through the activity area was also reduced, particularly those traveling at 10 km/h or more above the posted limit. Motorists were more likely to speed during the day, under a 40 kh/h limit, when traffic volumes were higher and when there were fewer vehicles in the traffic stream. Medium vehicles were less likely to speed in the presence of a pilot car than light vehicles. To maximize these benefits, it is necessary to ensure that the pilot car itself is not speeding.
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We write in response to the letter by Liu et al. [1] commenting on our article, ‘‘Mesenchymal Stem Cells Regulate Angiogenesis According to Their Mechanical Environment’’ [2]. The study by Liu et al. demonstrates that the commonly used endogeneous reference gene (ERG), b-actin, is upregulated by mechanical loading, indicating a potential bias in the determined target gene expression when normalizing to b-actin, such as in our report on unchanged vascular endothelial growth factor (VEGF) and hypoxia-inducible factors (HIF)-1a mRNA levels in mechanically loaded mesenchymal stem cells (MSCs).
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In Australia, collaborative contracts, and in particular, project alliances, have been increasingly used to govern infrastructure projects. These contracts use formal and informal governance mechanisms to manage the delivery of infrastructure projects. Formal mechanisms such as financial risk sharing are specified in the contract, while informal mechanisms such as integrated teams are not. Given that the literature contains a multiplicity of often untestable definitions, this paper reports on a review of the literature to operationalize the concepts of formal and informal governance. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operationalize formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; Williamson 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. A previous study by the authors identified that formal governance mechanisms can be classified into seven measurable categories: (1) negotiated cost, (2) competitive cost, (3) commercial framework, (4) risk and reward sharing, (5) qualitative performance, (6) collaborative multi-party agreement, and (7) early contractor involvement. Similarly, informal governance mechanisms can be classified into four measureable categories: (1) leadership structure, (2) integrated team, (3) team workshops, and (4) joint management system. This paper explores and further defines the key operational characteristics of each mechanism category, highlighting its impact on value for money in alliance project delivery. The paper’s contribution is that it provides the basis for future research to compare the impact of a range of individual mechanisms within each category, as a means of improving the performance of construction projects.