887 resultados para nonparametric demand model


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Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.

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Background The purpose of this study was to identify candidate metastasis suppressor genes from a mouse allograft model of prostate cancer (NE-10). This allograft model originally developed metastases by twelve weeks after implantation in male athymic nude mice, but lost the ability to metastasize after a number of in vivo passages. We performed high resolution array comparative genomic hybridization on the metastasizing and non-metastasizing allografts to identify chromosome imbalances that differed between the two groups of tumors. Results This analysis uncovered a deletion on chromosome 2 that differed between the metastasizing and non-metastasizing tumors. Bioinformatics filters were employed to mine this region of the genome for candidate metastasis suppressor genes. Of the 146 known genes that reside within the region of interest on mouse chromosome 2, four candidate metastasis suppressor genes (Slc27a2, Mall, Snrpb, and Rassf2) were identified. Quantitative expression analysis confirmed decreased expression of these genes in the metastasizing compared to non-metastasizing tumors. Conclusion This study presents combined genomics and bioinformatics approaches for identifying potential metastasis suppressor genes. The genes identified here are candidates for further studies to determine their functional role in inhibiting metastases in the NE-10 allograft model and human prostate cancer.

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This paper presents a travel time prediction model and evaluates its performance and transferability. Advanced Travelers Information Systems (ATIS) are gaining more and more importance, increasing the need for accurate, timely and useful information to the travelers. Travel time information quantifies the traffic condition in an easy to understand way for the users. The proposed travel time prediction model is based on an efficient use of nearest neighbor search. The model is calibrated for optimal performance using Genetic Algorithms. Results indicate better performance by using the proposed model than the presently used naïve model.

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This paper studies the effect of rain on travel demand measured on the Tokyo Metropolitan Expressway (MEX). Rainfall data monitored by the Japan Meteorological Agency's meso-scale network of weather stations are used. This study found that travel demand decreases during rainy days and, in particular, larger reductions occur over the weekend. The effect of rainfall on the number of accidents recorded on 10 routes on the MEX is also analysed. Statistical testing shows that the average frequency of accidents, during periods of rainfall, is significantly different from the average frequency at other times.

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We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.

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A road traffic noise prediction model (ASJ MODEL-1998) has been integrated with a road traffic simulator (AVENUE) to produce the Dynamic areawide Road traffic NoisE simulator-DRONE. This traffic-noise-GIS based integrated tool is upgraded to predict noise levels in built-up areas. The integration of traffic simulation with a noise model provides dynamic access to traffic flow characteristics and hence automated and detailed predictions of traffic noise. The prediction is not only on the spatial scale but also on temporal scale. The linkage with GIS gives a visual representation to noise pollution in the form of dynamic areawide traffic noise contour maps. The application of DRONE on a real world built-up area is also presented.

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This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

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The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.

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The Lane Change Test (LCT) is one of the growing number of methods developed to quantify driving performance degradation brought about by the use of in-vehicle devices. Beyond its validity and reliability, for such a test to be of practical use, it must also be sensitive to the varied demands of individual tasks. The current study evaluated the ability of several recent LCT lateral control and event detection parameters to discriminate between visual-manual and cognitive surrogate In-Vehicle Information System tasks with different levels of demand. Twenty-seven participants (mean age 24.4 years) completed a PC version of the LCT while performing visual search and math problem solving tasks. A number of the lateral control metrics were found to be sensitive to task differences, but the event detection metrics were less able to discriminate between tasks. The mean deviation and lane excursion measures were able to distinguish between the visual and cognitive tasks, but were less sensitive to the different levels of task demand. The other LCT metrics examined were less sensitive to task differences. A major factor influencing the sensitivity of at least some of the LCT metrics could be the type of lane change instructions given to participants. The provision of clear and explicit lane change instructions and further refinement of its metrics will be essential for increasing the utility of the LCT as an evaluation tool.

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One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

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Cell-cell and cell-matrix interactions play a major role in tumor morphogenesis and cancer metastasis. Therefore, it is crucial to create a model with a biomimetic microenvironment that allows such interactions to fully represent the pathophysiology of a disease for an in vitro study. This is achievable by using three-dimensional (3D) models instead of conventional two-dimensional (2D) cultures with the aid of tissue engineering technology. We are now able to better address the complex intercellular interactions underlying prostate cancer (CaP) bone metastasis through such models. In this study, we assessed the interaction of CaP cells and human osteoblasts (hOBs) within a tissue engineered bone (TEB) construct. Consistent with other in vivo studies, our findings show that intercellular and CaP cell-bone matrix interactions lead to elevated levels of matrix metalloproteinases, steroidogenic enzymes and the CaP biomarker, prostate specific antigen (PSA); all associated with CaP metastasis. Hence, it highlights the physiological relevance of this model. We believe that this model will provide new insights for understanding of the previously poorly understood molecular mechanisms of bone metastasis, which will foster further translational studies, and ultimately offer a potential tool for drug screening. © 2010 Landes Bioscience.

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Introduction: The purpose of this study was to assess the capacity of a written intervention, in this case a patient information brochure, to improve patient satisfaction during an Emergency Department (ED) visit. For the purpose of measuring the effect of the intervention the ED journey was conceptualised as a series of distinct areas of service comprising waiting time, service by the triage nurse, care from doctors and nurses and information giving Background of study: Research into patient satisfaction has become a widespread activity endorsed by both governments and hospital administrations. The literature on ED patient satisfaction has consistently indicated three primary areas of patient dissatisfaction: waiting time, nursing care and communication. Recent developments in the literature on patient satisfaction studies however have highlighted the relationship between patients. expectations of a service encounter and their consequent assessment of the experience as dissatisfying or satisfying. Disconfirmation theory posits that the degree to which expectations are confirmed will affect subsequent levels of satisfaction. The conceptual framework utilised in this study is Coye.s (2004) model of disconfirmation. Coye while reiterating satisfaction is a consequence of the degree expectations are either confirmed or disconfirmed also posits that expectations can be modified by interventions. Coye.s work conceptualises these interventions as intra encounter experiences (cues) which function to adjust expectations. Coye suggests some cues are unintended and may have a negative impact which also reinforces the value of planned cues intended to meet or exceed consumer expectations. Consequently the brochure can be characterized as a potentially positive cue, encouraging the patient to understand processes and to orient them in what can be a confronting environment. Only a limited number of studies have examined the effect of written interventions within an ED. No studies could be located which have tested the effect of ED interventions using a conceptual framework which relates the effect of the degree to which expectations are confirmed or disconfirmed in terms of satisfaction with services. Method: Two studies were conducted. Study One used qualitative methods to explore patients. expectations of the ED from the perspective of both patients and health care professionals. Study One was used in part to direct the development of the intervention (brochure) in Study Two. The brochure was an intervention designed to modify patients. expectations thus increasing their satisfaction with the provision of ED service. As there was no existing tools to measure ED patients. expectations and satisfaction a new tool was also developed based on the findings and the literature of Study One. Study Two used a non-randomised, quasi-experimental approach using a non-equivalent post-test only comparison group design used to investigate the effect of the patient education brochure (Stommel and Wills, 2004). The brochure was disseminated to one of two study groups (the intervention group). The effect of the brochure was assessed by comparing the data obtained from both the intervention and control group. These two groups consisted of 150 participants each. It was expected that any differences in the relevant domains selected for examination would indicate the effect of the brochure both on expectation and potentially satisfaction. Results: Study One revealed several areas of common ground between patients and nurses in terms of relevant content for the written intervention, including the need for information on the triage system and waiting times. Areas of difference were also found with patients emphasizing communication issues, whereas focus group members expressed concern that patients were often unable to assimilate verbal information. The findings suggested the potential utility of written material to reinforce verbal communication particularly in terms of the triage process and other ED protocols. This material was synthesized within the final version of the written intervention. Overall the results of Study Two indicated no significant differences between the two groups. The intervention group did indicate a significant number of participants who viewed the brochure of having changed their expectations. The effect of the brochure may have been obscured by a lack of parity between the two groups as the control group presented with statistically significantly higher levels of acuity and experienced significantly shorter waiting times. In terms of disconfirmation theory this would suggest expectations that had been met or exceeded. The results confirmed the correlation of expectations with satisfaction. Several domains also indicated age as a significant predictor with older patients tending to score higher satisfaction results. Other significant predictors of satisfaction established were waiting time and care from nurses, reinforcing the combination of efficient service and positive interpersonal experiences as being valued by patients. Conclusions: Information presented in written form appears to benefit a significant number of ED users in terms of orientation and explaining systems and procedures. The degree to which these effects may interact with other dimensions of satisfaction however is likely to be limited. Waiting time and interpersonal behaviours from staff also provide influential cues in determining satisfaction. Written material is likely to be one element in a series of coordinated strategies to improve patient satisfaction during periods of peak demand.

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The high levels of end-stage renal disease among Indigenous Australians, particularly in remote areas of the country, are a serious public health concern. The magnitude of the problem is reflected in figures from the Australian and New Zealand Transplant and Dialysis Registry that show that Indigenous Australians experience end-stage renal disease at a rate almost 9–10 times higher than other non-Indigenous Australians. A majority of Indigenous Australians have to relocate to receive appropriate renal dialysis treatment. In some Australian states, renal treatment is based on self-care dialysis which allows those Indigenous Australians to be treated back in their community. Evidence clearly shows that reuniting renal patients with community and family improves overall health and well-being for those Indigenous Australians. With the appropriate resources, training, and support, self-care management of renal dialysis treatment is an effective way for Indigenous people with end-stage renal failure to be treated at home. In this context, the study was used to gain insight and further understanding of the impact that end-stage renal disease and renal dialysis treatment has had on the lives of Indigenous community members. The study findings are from 14 individually interviewed people from South East Queensland. Data from the interviews were analysed using a combination of thematic and content analysis. The study methodology was based on qualitative data principles where the Indigenous community members were able to share their experiences and journeys living with end-stage renal disease. Many of the experiences and understanding closely relate to the renal disease pattern and the treatment with other outside influences, such as social, cultural, and environmental influences, all having an equal impact. Each community member’s experience with end-stage renal disease is unique; some manage with family and medical support, while others try to manage independently. From the study, community members who managed their renal dialysis treatment independently were much more aware of their renal health status. The study provides recommendations towards a model of care to improve the health and well-being is based on self-care and self-determination principles.