979 resultados para Rutgers University.


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This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

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Generating timetables for an institution is a challenging and time consuming task due to different demands on the overall structure of the timetable. In this paper, a new hybrid method which is a combination of a great deluge and artificial bee colony algorithm (INMGD-ABC) is proposed to address the university timetabling problem. Artificial bee colony algorithm (ABC) is a population based method that has been introduced in recent years and has proven successful in solving various optimization problems effectively. However, as with many search based approaches, there exist weaknesses in the exploration and exploitation abilities which tend to induce slow convergence of the overall search process. Therefore, hybridization is proposed to compensate for the identified weaknesses of the ABC. Also, inspired from imperialist competitive algorithms, an assimilation policy is implemented in order to improve the global exploration ability of the ABC algorithm. In addition, Nelder–Mead simplex search method is incorporated within the great deluge algorithm (NMGD) with the aim of enhancing the exploitation ability of the hybrid method in fine-tuning the problem search region. The proposed method is tested on two differing benchmark datasets i.e. examination and course timetabling datasets. A statistical analysis t-test has been conducted and shows the performance of the proposed approach as significantly better than basic ABC algorithm. Finally, the experimental results are compared against state-of-the art methods in the literature, with results obtained that are competitive and in certain cases achieving some of the current best results to those in the literature.

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This paper explores the changing relationship between knowledge creation and city centre spaces, focusing on the relocation of Higher Education Institutions (HEIs) into urban centres and the ensuing economic, social and cultural regeneration. Using the Ulster University's relocation to Belfast city centre, the paper highlights the opportunities a new anchor institution can offer a deprived inner city community. This case study draws attention to the drivers of university relocation and the untapped potential for regeneration in city centres such as Belfast, Northern Ireland. The paper looks to the future and questions whether large-scale city projects, such as the university relocation, can truly form connections with their new neighbouring inner city communities while contending with the mounting pressure of reduced government resources.

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The Library’s Open Access Team has submitted, on behalf of the University, an Article Processing Charges (APCs) expenditure report to Jisc Collections for 2015. In 2015 Queen’s University Belfast had a total APC spend of £138,039 which enabled 123 articles by Queen’s authors to be made open access via the gold route. This is a significant increase in both APC spend and the number of articles made open access in comparison to 2014.

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A new radiocarbon preparation facility was set up in 2010 at the Godwin Laboratory for Palaeoclimate Research, at the University of Cambridge. Samples are graphitized via hydrogen reduction on an iron powder catalyst before being sent to the Chrono Centre, Belfast, or the Australian National University for accelerator mass spectrometry (AMS) analysis. The experimental setup and procedure have recently been developed to investigate the potential for running small samples of foraminiferal carbonate. By analyzing background values of samples ranging from 0.04 to 0.6 mg C along with similar sized secondary standards, the setup and experimental procedures were optimized for small samples. “Background” modern 14C contamination has been minimized through careful selection of iron powder, and graphitization has been optimized through the use of “small volume” reactors, allowing samples containing as little as 0.08 mg C to be graphitized and accurately dated. Graphitization efficiency/fractionation is found not to be the main limitation on the analysis of samples smaller than 0.07 mg C, which rather depends primarily on AMS ion beam optics, suggesting further improvements in small sample analysis might yet be achieved with our methodology.

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From a macro perspective, it is widely acknowledged that University incubation models within a region are important stimulants of economic development through innovation and job creation. With the emergence of quadruple helix innovation ecosystems, universities have had re-evaluate their University incubation activity and models to engage more fully with industry and end users. However, within a given region, the type of University may influence their ability to engage with quadruple helix stakeholders and consequently impact their incubation activity. To date there is a scarcity of research which explores this 'meso' environment and its subsequent impact on University incubation models. Therefore, the aim of this paper is to use a stakeholder lens to explore University Incubation models within unique regional and organisational characteristics and constraints. The research methodology employed was based on a comparative case analysis of incubation of two different Universities within a UK peripheral region. It was found that variances existed in relation to the two universities incubation models which were found to result from both regional (macro environment) and organisational (meso environment) influences (i.e. university type). This research contributes to both regional and national agendas by empirically illustrating the need for appropriate design and tailoring of university incubation models (via acknowledgement of quadruple helix stakeholder influence) to incorporate contextual influences rather than adopting a best practise approach.

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Management control in public university hospitals is a challenging task because of continuous changes due to external pressures (e.g. economic pressures, stakeholder focuses and scientific progress) and internal complexities (top management turnover, shared leadership, technological evolution, and researcher oriented mission). Interactive budgeting contributed to improving vertical and horizontal communication between hospital and stakeholders and between different organizational levels. This paper describes an application of Analytic Hierarchy Process (AHP) to enhance interactive budgeting in one of the biggest public university hospital in Italy. AHP improved budget allocation facilitating elicitation and formalization of units' needs. Furthermore, AHP facilitated vertical communication among manager and stakeholders, as it allowed multilevel hierarchical representation of hospital needs, and horizontal communication among staff of the same hospital, as it allowed units' need prioritization and standardization, with a scientific multi-criteria approach, without using complex mathematics. Finally, AHP allowed traceability of a complex decision making processes (as budget allocation), this aspect being of paramount importance in public sectors, where managers are called to respond to many different stakeholders about their choices.