Dual Sequence Simulated Annealing with Round-Robin Approach for University Course Timetabling

The university course timetabling problem involves assigning a given number of events into a limited number of timeslots and rooms under a given set of constraints; the objective is to satisfy the hard constraints (essential requirements) and minimize the violation of soft constraints (desirable requirements). In this study we employed a Dual-sequence Simulated Annealing (DSA) algorithm as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within DSA. The performance of our approach is tested over eleven benchmark datasets. Experimental results show that our approach is able to generate competitive results when compared with other state-of-the-art techniques.

Intellectual Property management in publicly funded R&D centres—A comparison of university-based and company-based research centres

Recent thinking on open innovation and the knowledge-based economy have stressed the importance of external knowledge sources in stimulating innovation. Policy-makers have recognised this, establishing publicly funded Centres of R&D Excellence with the objective of stimulating industry–science links and localised innovation spillovers. Here, we examine the contrasting IP management practices of a group of 18 university- and company-based R&D centres supported by the same regional programme. Our analysis covers all but one of the Centres supported by the programme and suggests marked contrasts between the IP strategies of the university-based and company-based centres. This suggests the potential for very different types of knowledge spillovers from publicly funded R&D centres based in different types of organisations, and a range of alternative policy approaches to the future funding of R&D centres depending on policy-makers’ objectives.

An exploratory study of Principal Investigator roles in UK University Proof-of-Concept processes: an Absorptive capacity perspective

The increasing emphasis on academic entrepreneurship, technology transfer and research commercialisation within UK universities is predicated on basic research being developed by academics into commercial entities such as university spin-off companies or licensing arrangements. However, this process is fraught with challenges and risks, given the degree of uncertainty regarding future returns. In an attempt to minimise such risks, the Proof-of-Concept (PoC) process has been developed within University Science Park Incubators (USIs) to test the technological, business and market potential of embryonic technology. The key or the pivotal stakeholder within the PoC is the Principal Investigator (PI), who is usually the lead academic responsible for the embryonic technology. Within the current literature, there appears to be a lack of research pertaining to the role of the PI in the PoC process. Moreover, Absorptive Capacity (ACAP) has emerged within the literature as a theoretical framework or lens for exploring the development and application of new knowledge and technology, where the USI is the organisation considered in the current study. Therefore, the aim of this paper is to explore the role and influence of the PI in the PoC process within a USI setting using an ACAP perspective. The research involved a multiple case analysis of PoC applications within a UK university USI. The results demonstrate the role of the PI in developing practices and routines within the PoC process. These practices and processes were initially tacit and informal in nature but became more explicit and formal over time so that knowledge was retained within the USI after the PIs had completed the PoC process. © 2010 The Authors. R&D Management © 2010 Blackwell Publishing Ltd.

A hybrid metaheuristic approach to the university course timetabling problem

This paper describes the development of a novel metaheuristic that combines an electromagnetic-like mechanism (EM) and the great deluge algorithm (GD) for the University course timetabling problem. This well-known timetabling problem assigns lectures to specific numbers of timeslots and rooms maximizing the overall quality of the timetable while taking various constraints into account. EM is a population-based stochastic global optimization algorithm that is based on the theory of physics, simulating attraction and repulsion of sample points in moving toward optimality. GD is a local search procedure that allows worse solutions to be accepted based on some given upper boundary or ‘level’. In this paper, the dynamic force calculated from the attraction-repulsion mechanism is used as a decreasing rate to update the ‘level’ within the search process. The proposed method has been applied to a range of benchmark university course timetabling test problems from the literature. Moreover, the viability of the method has been tested by comparing its results with other reported results from the literature, demonstrating that the method is able to produce improved solutions to those currently published. We believe this is due to the combination of both approaches and the ability of the resultant algorithm to converge all solutions at every search process.

UNISTEP (University Students Exercise and Physical Activity) Study: A Pilot Study of the Effects of Accumulating 10,000 Steps on Health and Fitness Among University Students.

BACKGROUND: Recent public health initiatives have promoted accumulating 10,000 steps per day. Little previous research has evaluated its effects in young adults. The aim of this study was to determine the effects of taking 10,000 steps per day on fitness and cardiovascular risk factors in sedentary university students. METHODS: Healthy, sedentary students (mean age 21.16 ± SD 6.17) were randomly allocated to take 10,000 steps per day or to a control group who maintained their habitual activity. Members of the 10,000 step group wore a pedometer and reported daily step count in a diary. Outcome measurements (20-meter multistage shuttle run, BMI, and blood pressure) were measured before and after 6 weeks. RESULTS: There were no significant differences between the groups at baseline. After 6 weeks, the 10,000 steps group were taking significantly more steps (8824.1 ± SD 5379.3 vs. 12635.9 ± SD 6851.3; P = .03).No changes were observed in fitness, or BMI (P > .05). Significant reductions in blood pressure (P = .04) in the 10,000 step group. CONCLUSIONS: A daily target of 10,000 steps may be an appropriate intervention in sedentary university students to increase their physical activity levels. The positive health benefits of simple everyday physical activity should be promoted among health professionals.