Engineering and Information Technology Collected Works - Research Publications

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    Peter Lilienthal. Von Koffern und Tätern
    Sandberg, C ; Haselberg, L ; Praetorius-Rhein, J ; Riedel, E (Carl Hanser Verlag, 2023)
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    Uncertainty in Selective Bagging: A Dynamic Bi-objective Optimization Model
    Maadi, M ; Khorshidi, HA ; Aickelin, U ; *, (Society for Industrial and Applied Mathematics, 2023-01)
    Bagging is a common approach in ensemble learning that generates a group of classifiers through bootstrapping for classification tasks. Despite its wide applications, generating redundant classifiers remains a central challenge in bagging. In recent years, many selective bagging models have been presented to deal with this challenge. These models mostly focused on the accuracy of classifiers and the diversity among them. Despite the importance of uncertainty in the performance of ensemble classifiers, this criterion has been neglected in selective bagging models. In this paper, we propose a two-stage selective bagging model. In the first stage, we formalize the selective bagging problem as a bi-objective optimization model considering both the uncertainty and accuracy of classifiers. We propose an adaptive evolutionary Two-Arch2 algorithm, named Diverse-Two-Arch2, to solve the bi-objective model. The output of this stage is a subset of classifiers that are diverse, certain about correct predictions, and uncertain about incorrect predictions. While most selective bagging models focus on the selection of a fixed subset of classifiers for all test samples (static approach), our proposed model has a dynamic approach to the selection process. So, in the second stage of the model, we select only certain classifiers to make an ensemble prediction for each test sample. Experimental results on twenty data sets and comparing with two ensemble models, and five state-of-the-art dynamic selective bagging models show the outperformance of the proposed model. We also compare the performance of the proposed Diverse-Two-Arch2 to alternative evolutionary computation methods.
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    Die frühen Fernseharbeiten von Peter Lilienthal. Ein jüdischer Remigrant im Westdeutschland der Nachkriegszeit
    Sandberg, C ; Wohl von Haselberg, L ; Pizaña Pérez, LA (Edition Text + Kritik, 2022)
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    Limitations
    Yang, Y ; Khorshidi, HA ; Aickelin, U (Springer Nature Singapore, 2022-01-01)
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    Preface
    Siuly, S ; Huang, Z ; Aickelin, U ; Zhou, R ; Wang, H ; Zhang, Y ; Klimenko, SV ( 2017-01-01)
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    Towards the development of a simulator for investigating the impact of people management practices on retail performance
    Siebers, 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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    The importance of the socially-conscious engineer
    Cebon, P ; Shaw, J ; Farghaly, Z (GHD Digital, 2020)
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    Towards the development of a simulator for investigating the impact of people management practices on retail performance
    Siebers, 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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    Artificial immune systems
    Aickelin, 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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    Investigating the effectiveness of Variance Reduction Techniques in Manufacturing, Call Center and Cross-docking Discrete Event Simulation Models
    Adewunmi, 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.