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Engineering and Information Technology Collected Works - Research Publications
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ItemNo Preview AvailablePrefaceSiuly, S ; Huang, Z ; Aickelin, U ; Zhou, R ; Wang, H ; Zhang, Y ; Klimenko, SV ( 2017-01-01)
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ItemTowards the development of a simulator for investigating the impact of people management practices on retail performanceSiebers, PO ; Aickelin, U ; Celia, H ; Clegg, CW ; JE Taylor, S (Palgrave Macmillan, 2014)Models to understand the impact of management practices on retail performance are often simplistic and assume low levels of noise and linearity. Of course, in real life, retail operations are dynamic, nonlinear and complex. To overcome these limitations, we investigate discrete-event and agent-based modeling and simulation approaches. The joint application of both approaches allows us to develop simulation models that are heterogeneous and more life-like, though poses a new research question: When developing such simulation models one still has to abstract from the real world, however, ideally in such a way that the ‘essence’ of the system is still captured. The question is how much detail is needed to capture this essence, as simulation models can be developed at different levels of abstraction. In the literature the appropriate level of abstraction for a particular case study is often more of an art than a science. In this paper, we aim to study this question more systematically by using a retail branch simulation model to investigate which level of model accuracy obtains meaningful results for practitioners. Our results show the effects of adding different levels of detail and we conclude that this type of study is very valuable to gain insight into what is really important in a model.
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ItemTowards the development of a simulator for investigating the impact of people management practices on retail performanceSiebers, PO ; Aickelin, U ; Celia, H ; Clegg, CW ; Taylor, SJE (Palgrave Macmillan UK, 2014)Models to understand the impact of management practices on retail performance are often simplistic and assume low levels of noise and linearity. Of course, in real life, retail operations are dynamic, nonlinear and complex. To overcome these limitations, we investigate discrete-event and agent-based modeling and simulation approaches. The joint application of both approaches allows us to develop simulation models that are heterogeneous and more life-like, though poses a new research question: When developing such simulation models one still has to abstract from the real world, however, ideally in such a way that the ‘essence’ of the system is still captured. The question is how much detail is needed to capture this essence, as simulation models can be developed at different levels of abstraction. In the literature the appropriate level of abstraction for a particular case study is often more of an art than a science. In this paper, we aim to study this question more systematically by using a retail branch simulation model to investigate which level of model accuracy obtains meaningful results for practitioners. Our results show the effects of adding different levels of detail and we conclude that this type of study is very valuable to gain insight into what is really important in a model.
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ItemArtificial immune systemsAickelin, U ; Dasgupta, D ; Gu, F (Springer US, 2014-01-01)The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body asself or nonself substances. It does this with the help of a distributed task force that has theintelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years.
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ItemInvestigating the effectiveness of Variance Reduction Techniques in Manufacturing, Call Center and Cross-docking Discrete Event Simulation ModelsAdewunmi, A ; Aickelin, U ; Bangsow, S (Springer Berlin Heidelberg, 2012)Variance reduction techniques have been shown by others in the past to be a useful tool to reduce variance in Simulation studies. However, their application and success in the past has been mainly domain specific, with relatively little guidelines as to their general applicability, in particular for novices in this area. To facilitate their use, this study aims to investigate the robustness of individual techniques across a set of scenarios from different domains. Experimental results show that Control Variates is the only technique which achieves a reduction in variance across all domains. Furthermore, applied individually, Antithetic Variates and Control Variates perform particularly well in the Cross-docking scenarios, which was previously unknown.
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ItemEvaluating different cost-benefit analysis methods for port security operationsSherman, G ; Siebers, PO ; Menachof, D ; Aickelin, U ; Faulin, J ; Juan, AA ; Grasman, SE ; Fry, MJ (CRC Press, 2012-01-01)
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ItemThe Dendritic Cell Algorithm for Intrusion DetectionGu, F ; Greensmith, J ; Aickelin, U ; Lio, P ; Verma, D (Bio-Inspired Communications and Networking, IGI Global, 2011)As one of the solutions to intrusion detection problems, Artificial Immune Systems (AIS) have shown their advantages. Unlike genetic algorithms, there is no one archetypal AIS, instead there are four major paradigms. Among them, the Dendritic Cell Algorithm (DCA) has produced promising results in various applications. The aim of this chapter is to demonstrate the potential for the DCA as a suitable candidate for intrusion detection problems. We review some of the commonly used AIS paradigms for intrusion detection problems and demonstrate the advantages of one particular algorithm, the DCA. In order to clearly describe the algorithm, the background to its development and a formal definition are given. In addition, improvements to the original DCA are presented and their implications are discussed, including previous work done on an online analysis component with segmentation and ongoing work on automated data pre-processing. Based on preliminary results, both improvements appear to be promising for online anomaly-based intrusion detection.
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ItemSelf-Organizing Maps in Computer SecurityFeyereisl, J ; Aickelin, U ; Hopkins, RD ; Tokere, WP (Computer Security: Intrusion, Detection and Prevention, 2009)Some argue that biologically inspired algorithms are the future of solving difficult problems in computer science. Others strongly believe that the future lies in the exploration of mathematical foundations of problems at hand. The field of computer security tends to accept the latter view as a more appropriate approach due to its more workable validation and verification possibilities. The lack of rigorous scientific practices prevalent in biologically inspired security research does not aid in presenting bio-inspired security approaches as a viable way of dealing with complex security problems. This chapter introduces a biologically inspired algorithm, called the Self- Organising Map (SOM), that was developed by Teuvo Kohonen in 1981. Since the algorithm’s inception it has been scrutinised by the scientific community and analysed in more than 4000 research papers, many of which dealt with various computer security issues, from anomaly detection, analysis of executables all the way to wireless network monitoring. In this chapter a review of security related SOM research undertaken in the past is presented and analysed. The algorithm’s biological analogies are detailed and the author’s view on the future possibilities of this successful bio-inspired approach are given. The SOM algorithm’s close relation to a number of vital functions of the human brain and the emergence of multi-core computer architectures are the two main reasons behind our assumption that the future of the SOM algorithm and its variations is promising, notably in the field of computer security.
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ItemArtificial Immune SystemsGreensmith, J ; Whitbrook, A ; Aickelin, U ; Gendreau, M ; Potvin, JY (Springer Verlag, 2010)
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ItemArtificial Dendritic Cells: Multi-faceted PerspectivesGreensmith, J ; Aickelin, U ; Bargiela, A ; Pedrycz, W (Human-Centric Information Processing Through Granular Modelling, 2009)Dendritic cells are the crime scene investigators of the human immune system. Their function is to correlate potentially anomalous invading entities with observed damage to the body. The detection of such invaders by dendritic cells results in the activation of the adaptive immune system, eventually leading to the removal of the invader from the host body. This mechanism has provided inspiration for the development of a novel bio-inspired algorithm, the Dendritic Cell Algorithm. This algorithm processes information at multiple levels of resolution, resulting in the creation of information granules of variable structure. In this chapter we examine the multi-faceted nature of immunology and how research in this field has shaped the function of the resulting Dendritic Cell Algorithm. A brief overview of the algorithm is given in combination with the details of the processes used for its development. The chapter is concluded with a discussion of the parallels between our understanding of the human immune system and how such knowledge influences the design of artificial immune systems.