Faculty of Computing, Engineering and Media
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Item Open Access A Climate Emergency Action Plan Toolkit for Community Organisations: Pilot Study Results(2021-09) Kerr, Daniel William; Reeves, Andrew; Hill, Bethan; Alhawamdeh, Aroob; Elmishri, SajaLeicester City Council (LCC) are encouraging businesses and organisations across Leicester to create their own Climate Emergency Action Plans, to play their part in the city’s efforts to achieve carbon neutrality by 2030. To support this, LCC are developing a standalone ‘Climate Emergency Action Plan toolkit’, which can be used by non-business community organisations in the city to develop their own action plans to reduce their carbon footprint (CF), and other negative environmental impacts through measures such as improved energy efficiency in buildings, modal shifts in transport or otherwise. This project aimed to aid development of this toolkit through piloting a small-scale offer of support and eliciting feedback on the draft resources.Item Metadata only AHRC Leicester Outdoor Pursuits Centre Project(De Montfort University, 2022-07-15) Harwood, Tracy; Mohammed, ZainabAHRC funded Design Exchange Partnership (Design Museum/InnovateUK) Design Researcher: Zainab Mohammed Principal Investigator: Prof Tracy Harwood Organization Partner Lead: Stuart Frazer (Centre Manager) This project evaluated passive design concepts that utilise renewable and recyclable sources of materials thereby emitting zero carbon and minimising materials waste. Design concepts proposed maximise use of natural daylight and ventilation creating a healthy built environment for users, and use renewable sources of energy which can be generated on site. The nature of the 15-acres flood plain site requires considerable environmental empathy to be built into its future development scheme. LOPC has 150 years of heritage as a venue for river, target, climbing and adventure educational activities engaging Leicester-based community groups and also has ambition to become a national centre for some activities in the future. The project team, comprising the LOPC manager, Stuart Fraser, Tracy Harwood, Professor of Digital Culture at the Institute of Creative Technologies, De Montfort University and Zainab Mohammed, an architecture postgraduate researcher studying for a PhD in sustainable architecture at De Montfort University, have explored design concepts that address user needs on the complex LOPC site. The way in which stakeholder needs can be integrated into developments of this nature and how they are reflected in design processes are areas that the project team are interested in developing new insight into from the different perspectives of research and practice. The project outcomes are intended to assist LOPC to develop and prioritise plans for incremental redevelopment by identifying short and longer-term actions it may take that deliver its net zero goals. Data included comprises reports from completed project activities. The project includes deliverables (presentations, report, drawings, renders) and instruments used in data collection.Item Metadata only All Change: Equitably Decarbonising India's Transportation Sector(British Academy, 2022-06-01) Mitchell, Andrew; Rowlatt, John; Kerr, Daniel William; Bhattacharyya, Subhes; Ahuja, Nupur; Gautam, Nehal; Agarwal, Naman; Das, Sukanya; Sarangi, Gopal K.Executive summary: Key findings • There is limited focus on just transitions in the transport sector: in both academic literature and policy to date, technical solutions have received policy and research priority, but there is limited focus on how end-users will be affected by transport transitions, and whether these transitions will be equitable, inclusive and just. Several factors should be addressed under this: ensuring that transitions lead to affordable mobility solutions for all users is a key point, as is ensuring that job losses from high-carbon mobility services are compensated for by job creation in low-carbon mobility. From our key informant interviews, policymakers are focused on the supply-side when considering transport transitions, contrasting with users’ concerns of demand-side support and downstream services, particularly for electric vehicles and charging infrastructure. These tensions need to be addressed in policy. • There is potential for significant socio-economic impacts from the transition: this research has investigated the potential pains and gains of the transition to electric mobility, particularly electric road transport, in the Indian transport sector. There is potential for job losses both in the downstream oil sector and the downstream mobility services sector as the EV transition progresses due to reduced petroleum product consumption and a lesser burden of maintenance for electric vehicles compared to ICE vehicles. This also has the potential to impact government revenues from fuel taxation and place a higher burden on the government purse from increased electricity subsidy outlay. • Just transition alternatives exist: from the scenarios presented in this research, it is clear the current policy trend does not foreground justice and equity in the low-carbon transport transition, and this will lead to significant negative impacts for disadvantaged sectors of society. Policy alternatives exist to foreground justice in the transport transition, including participatory co-development of policy with end-users, and engendering greater coordination between transport and energy sectors and within the transport sector to ensure users are targeted equally across socio-economic strata with low-carbon mobility solutions.Item Open Access Analysing the Moodle e-learning platform through subgroup discovery algorithms based on evolutionary fuzzy systems(DMU, 2012-09-01) Carmona, C. J.; Elizondo, DavidNowadays, there is a increasing in the use of learning management systems from the universities. This type of systems are also known under other di erent terms as course management systems or learning content management systems. Speci cally, these systems are e-learning platforms o ering di erent facilities for information sharing and communication between the participants in the e-learning process. This contribution presents an experimental study with several subgroup discovery algorithms based on evolutionary fuzzy systems using data from a web-based education system. The main objective of this contribution is to extract unusual subgroups to describe possible relationships between the use of the e-learning platform and marks obtained by the students. The results obtained by the best performing algorithm, NMEEF-SD, are also presented. The most representative results obtained by this algorithm are summarised in order to obtain knowledge that can allow teachers to take actions to improve student performance.Item Metadata only The Aria Project, final report.(De Momtfort University, 2006) Brown, Stephen C.; Ross, R.Item Metadata only The Arts and Humanities Data Service (AHDS) review and user survey final report.(De Montfort University, 2006) Brown, Stephen C.; Ross, R.; Gerrard, D.; Greengrass, Mark, 1949-; Bryson, JaredItem Open Access Benchmark for CEC 2024 Competition on Multiparty Multiobjective Optimization(2024-02) Luo, Wenjian; Xu, Peilan; Yang, Shengxiang; Shi, YuhuiThe competition focuses on Multiparty Multiobjective Optimization Problems (MPMOPs), where multiple decision makers have conflicting objectives, as seen in applications like UAV path planning. Despite their importance, MPMOPs remain understudied in comparison to conventional multiobjective optimization. The competition aims to address this gap by encouraging researchers to explore tailored modeling approaches. The test suite comprises two parts: problems with common Pareto optimal solutions and Biparty Multiobjective UAV Path Planning (BPMO-UAVPP) problems with unknown solutions. Optimization algorithms for the first part are evaluated using Multiparty Inverted Generational Distance (MPIGD), and the second part is evaluated using Multiparty Hypervolume (MPHV) metrics. The average algorithm ranking across all problems serves as a performance benchmark.Item Open Access Benchmark Functions for CEC 2022 Competition on Seeking Multiple Optima in Dynamic Environments(2022-01) Luo, Wenjian; Lin, Xin; Li, Changhe; Yang, Shengxiang; Shi, YuhuiDynamic and multimodal features are two important properties and widely existed in many real-world optimization problems. The former illustrates that the objectives and/or constraints of the problems change over time, while the latter means there is more than one optimal solution (sometimes including the accepted local solutions) in each environment. The dynamic multimodal optimization problems (DMMOPs) have both of these characteristics, which have been studied in the field of evolu tionary computation and swarm intelligence for years, and attract more and more attention. Solving such problems requires optimization algorithms to simultaneously track multiple optima in the changing environments. So that the decision makers can pick out one optimal solution in each environment according to their experiences and preferences, or quickly turn to other solutions when the current one cannot work well. This is very helpful for the decision makers, especially when facing changing environments. In this competition, a test suit about DMMOPs is given, which models the real-world applications. Specifically, this test suit adopts 8 multimodal functions and 8 change modes to construct 24 typical dynamic multimodal optimization problems. Meanwhile, the metric is also given to measure the algorithm performance, which considers the average number of optimal solutions found in all environments. This competition will be very helpful to promote the development of dynamic multimodal optimization algorithms.Item Open Access Benchmark Functions for the CEC'2017 Competition on Many-Objective Optimization(University of Birmingham, U.K., 2017-01) Cheng, Ran; Li, Miqing; Tian, Ye; Zhang, Xingyi; Yang, Shengxiang; Jin, Yaochu; Yao, XinIn the real world, it is not uncommon to face an optimization problem with more than three objectives. Such problems, called many-objective optimization problems (MaOPs), pose great challenges to the area of evolutionary computation. The failure of conventional Pareto-based multi-objective evolutionary algorithms in dealing with MaOPs motivates various new approaches. However, in contrast to the rapid development of algorithm design, performance investigation and comparison of algorithms have received little attention. Several test problem suites which were designed for multi-objective optimization have still been dominantly used in many-objective optimization. In this competition, we carefully selects/designs 15 test problems with diverse properties, aiming to promote the research of evolutionary many-objective optimization (EMaO) via suggesting a set of test problems with a good representation of various real-world scenarios. Also, an open-source software platform with a user-friendly GUI is provided to facilitate the experimental execution and data observation.Item Open Access Benchmark Functions for the CEC'2018 Competition on Dynamic Multiobjective Optimization(Newcastle University, 2018-01) Jiang, Shouyong; Yang, Shengxiang; Yao, Xin; Tan, Kay Chen; Kaiser, Marcus; Krasnogor, NatalioItem Open Access Benchmark Functions for the CEC'2018 Competition on Many-Objective Optimization(2018-01) Cheng, Ran; Li, Miqing; Tian, Ye; Xiang, Xiaoshu; Zhang, Xingyi; Yang, Shengxiang; Jin, Yaochu; Yao, XinItem Open Access Benchmark generator for CEC 2009 competition on dynamic optimization(University of Leicester, U.K., 2008-10) Li, Changhe; Yang, Shengxiang; Nguyen, T. T.; Ling Yu, E.; Yao, Xin; Jin, Yaochu; Beyer, H. -G.; Suganthan, P. N.Item Open Access Benchmark Generator for the IEEE WCCI-2012 Competition on Evolutionary Computation for Dynamic Optimization Problems(Brunel University, U.K., 2011-10) Li, Changhe; Yang, Shengxiang; Pelta, David A.Based on our previous benchmark generator for the IEEE CEC’09 Competition on Dynamic Optimization, this report updates the two benchmark instances where a new change type has been developed as well as a constraint to the benchmark instance of the dynamic rotation peak benchmark generator.Item Metadata only Benchmark generator for the IEEE WCCI-2012 competition on evolutionary computation for dynamic optimization problems. Technical Report 2011.(Department of Information Systems and Computing, Brunel University., 2011) Li, Changhe; Yang, Shengxiang; Pelta, David A.Item Open Access Benchmark Generator for the IEEE WCCI-2014 Competition on Evolutionary Computation for Dynamic Optimization Problems: Dynamic Rotation Peak Benchmark Generator (DRPBG) and Dynamic Composition Benchmark Generator (DCBG)(De Montfort University, UK, 2013-10) Li, Changhe; Mavrovouniotis, Michalis; Yang, Shengxiang; Yao, XinBased on our previous benchmark generator for the IEEE CEC’12 Competition on Dynamic Optimization, this report updates the two benchmark instances where two new features have 1been developed as well as a constraint to the benchmark instance of the dynamic rotation peak benchmark generator. The source code in C++ language for the two benchmark instances is included in the library of EAlib, which is an open platform to test and compare the performances of EAs.Item Open Access Benchmark Generator for the IEEE WCCI-2014 Competition on Evolutionary Computation for Dynamic Optimization Problems: Dynamic Travelling Salesman Problem Benchmark Generator(De Montfort University, U.K., 2013-10) Mavrovouniotis, Michalis; Li, Changhe; Yang, Shengxiang; Yao, XinIn this report, the dynamic benchmark generator for permutation-encoded problems for the travelling salesman problem (DBGPTSP) proposed in is used to convert any static travelling salesman problem benchmark to a dynamic optimization problem, by modifying the encoding of the instance instead of the fitness landscape.Item Open Access Benchmark Problems for CEC2023 Competition on Dynamic Constrained Multiobjective Optimization(2022-12) Gui, Yinan; Chen, Guoyu; Yue, Caitong; Liang, Jing; Wang, Yong; Yang, ShengxiangItem Open Access Benchmark Problems for IEEE WCCI2024 Competition on Dynamic Constrained Multiobjective Optimization(2023-12) Guo, Yinan; Chen, Guoyu; Yue, Caitong; Liang, Jing; Wang, Yong; Yang, ShengxiangItem Metadata only Broadband for schools.(2003) Brown, Stephen C.Item Metadata only Broadband technologies for learning and teaching off-campus.(JISC TechLearn, 2002) Brown, Stephen C.; Bacsich, Paul