School of Computer Science and Informatics
Permanent URI for this collection
Browse
Browsing School of Computer Science and Informatics by Type "Book chapter"
Now showing 1 - 20 of 296
Results Per Page
Sort Options
Item Metadata only 3D Sound Simulation over Headphones(Information Science Reference, 2009) Picinali, LorenzoItem Metadata only A Framework of Directed Network Based Influence-Trust Fuzzy Group Decision Making(Springer Nature, 2023-08-17) Kamis, Nor Hanimah; Kilicman, Adem; Kadir, Norhidayah A.; Chiclana, FranciscoDaily life requires individuals or groups of decision-makers to engage in critical decision-making processes. Fuzzy set theory has been integrated into group decision-making (GDM) to address the ambiguity and vagueness of expert preferences. Social Network Group Decision Making (SNGDM) is a newly emerging research area that focuses on the use of social networks to facilitate information exchange and communication among experts in GDM. Moreover, Social Influence Group Decision Making (SIGDM) has been initiated, which considers social influence as a factor that can impact experts’ preferences during interactions or discussions. Studies in this area have proposed innovative measurements of social influence, including the use of trust statements to explicitly influence experts’ opinions. In this study, a new trust index called TrustRank is proposed, which acts as an additional weightage of experts’ importance and is embedded in the influence network measure that represents the strength of the expert’s influence degree. These values are then utilized as the order-inducing variable in the IOWA-based fusion operator to obtain the collective preference and ranking of alternatives. The proposed framework, which is the directed network-based Influence-Trust Fuzzy GDM, is presented along with its implementation, results, and discussion to showcase its applicability.Item Metadata only Accountability and reflective responsibility in information systems.(Springer, 2006) Stahl, Bernd Carsten, 1968-Item Metadata only Activity Recognition: Approaches, Practices and Trends(Atlantis Press, 2011-05-05) Chen, Liming; Khalil, I.Activity recognition has attracted increasing attention as a number of related research areas such as pervasive computing, intelligent environments and robotics converge on this critical issue. It is also driven by growing real-world application needs in such areas as ambient assisted living and security surveillance. This chapter aims to provide an overview on existing approaches, current practices and future trends on activity recognition. It is intended to provide the necessary material to inform relevant research communities of the latest developments in this field in addition to providing a reference for researchers and system developers who are working towards the design and development of activity-based context aware applications. The chapter first reviews the existing approaches and algorithms that have been used for activity recognition in a number of related areas. It then describes the practice and lifecycle of the ontology-based approach to activity recognition that has recently been under vigorous investigation. Finally the chapter presents emerging research on activity recognition by outlining various issues and directions the field will take.Item Metadata only Adaptive Cruise Control Using Fuzzy Logic(Springer, Cham, 2021-05-05) Lloyd, Nathan; Khuman, A. S.Modern transportation undoubtedly provides a plethora of beneficial qualities; qualities that not only dramatically improve the efficiency and speed of travel, but also provide materialistic comforts for the inhabitants of the vehicle. Whilst these advancements have generally improved the quality of life for users, it begs the question: can modern technologies be utilized to augment vehicles further? This chapter will engage intelligent transportation systems (ITS), specifically automatic cruise control (ACC) and the utilization of fuzzy inference systems (FIS), analyzing their successful implementation, posing a bespoke system and how the ITS field can be improved further.Item Metadata only An adaptive multi-mode downloading partitioning algorithm of distributed virtual environment based on grid computing.(IEEE, 2007) Wang, Yuying; Li, Hongmei; Jia, JinyuanWhen users are connected to a Large Scale distributed virtual environment system on internet, downloading speed is a key point to support a life-like world and real time interactions for a large number of avatars in a consistent fashion. We proposed an adaptive multi-node downloading partitioning algorithm to balance the bottleneck problem on multi- node downloading architecture we designed. It facilitates a flexible and scalable downloading large scale DVE. Our method has five major steps: (1) to build up a database by partitioning the ground of a DIE into two-dimensional square regions covered with three-dimensional objects uniformly; (2) to determine statically a region where an avatar's area of interest located according to its spatial coherence; (3) to group the grid nodes located on same region in DVE; (4) to build a downloading servers group within each region and adapt it dynamically; (5) to balance the downloading workload dynamically. A specific multi-node downloading component is devised for supporting remote multi-thread downloading DVE based Globus platform. The downloading speed is proportional to the number of grid nodes participated in the downloading task in each region. Initial experimental results show the feasibility and effectiveness of our approach.Item Embargo Adaptive mutation using statistics mechanism for genetic algorithms(Springer, 2004) Yang, ShengxiangIt has long been recognized that mutation is a key ingredient in genetic algorithms (GAs) and the choice of suitable mutation probability will have a significant effect on the performance of genetic search. In this paper, a statistics-based adaptive non-uniform mutation (SANUM) is presented within which the probability that each gene will subject to mutation is learnt adaptively over time and over the loci. As a search algorithm based on mechanisms abstracted from population genetics, GAs implicitly maintain the statistics about the search space through the population. SANUM explicitly makes use of the statistics information of the allele distribution in each gene locus to adaptively adjust the mutation probability of that locus. To test the performance of SANUM, it is compared to traditional bit mutation operator with a number of “standard” fixed mutation probabilities suggested by other researchers over a range of typical test problems. The results demonstrate that SANUM performs persistently well over the range of test problems while the performance of traditional mutation operators with fixed mutation probabilities greatly depends on the problem under consideration. SANUM represents a robust adaptive mutation operator that needs no prior knowledge about the fitness landscape of the problem being solved.Item Metadata only Agent based evolutionary dynamic optimization.(Springer-Verlag., 2010) Yan, Yang; Yang, Shengxiang; Wang, Dazhi; Wang, DingweiItem Metadata only Agent-based modelling in grey economic systems(Springer, 2023-02-05) Delcea, Camelia; Yang, Yingjie; Liu, Sifeng; Cotfas, Liviu-AdrianThe economic systems are basically grey systems due to their components and to their interactions which enable the occurrence of uncertainty. First, the human component plays an important role as a consequence of its usually unpredictable and sometimes irrational behavior, a situation strictly related to the way the humans are thinking and acting. From here, it can easily be demonstrated that when analyzing a system, we are facing grey knowledge. This kind of knowledge exists and it represents that small piece of puzzle needed to successfully fill the gap separating the explicit knowledge form the tacit one, also conducting to uncertainty.Item Open Access Agile Incident Response in Industrial Control Environments(CRC press, 2021) Janicke, Helge; Smith, Richard; Maglaras, Leandros; Cook, Allan; He, Ying; Ferra, FeniaICS incident response differs from traditional IT incident response. Whilst there is some crossover many IR practices in IT cannot be directly applied in ICS. Because of this, a new approach is required, one that can adapt quickly and promotes communication between stakeholders. The interview responses of industry professionals have been thematically analyzed with key themes emerging such as the criticality of communication and situational awareness. The four Agile values have been mapped into the context if ICS incident response to meet those requirements along with a number of tools to aid IR teams in the field. Proper incident response can improve technical attribution in relation to ICSItem Embargo AI in Healthcare: Malignant or Benign?(Springer Singapore, 2022-10-24) Khuman, A. S.; Lloyd, NathanDespite a slightly tumultuous past, the popularity and growth of Artificial intelligence are observable in every nook and cranny. AI has engrained itself within a multitude of industries as a principal tool for success, all whilst being a fledgling domain itself.Item Metadata only Alterity ex Machina: The Encounter with Technology as an Epistemological-Ethical Drama(Rowman & Littlefield International, 2016) Coeckelbergh, MarkItem Metadata only Analysis and testing of the m-RDP neural network.(Springer, 2009-11) Elizondo, David; Ortiz-de-Lazcano-Lobato, Juan; Birkenhead, Ralph, 1955-Item Metadata only Analysis of cellular and molecular markers by statistical, artificial neural networks and fuzzy logic-based approaches as an aid in intelligent prognostic decision making in oncology(2004) Seker, H.; Sherbet, G. V.; Naguib, R. N. G.Item Embargo Analysis of structural bias in Differential Evolution configurations(Springer, 2022-01-01) Vermetten, Diederick; van Stein, Bas; Kononova, Anna V.; Caraffini, FabioDifferential Evolution is a popular optimisation method with a small number of parameters. However, different hyper-parameters and Differential Evolution variants such as different mutation operators and the F and Cr parameter may introduce structural bias. Structural bias is a form of bias where artefacts in the algorithm lead to a preference to particular regions in the search space regardless of the objective function. Many algorithm configurations suffer from structural bias but it is very hard to automatically detect it and even harder to detect what kind of structural bias is involved and what component might be the cause of it. A comprehensive study of the occurrence and type of structural bias in Differential Evolution configurations has not yet been carried out till now. In this chapter we systematically evaluate 10980 Differential Evolution configurations on structural bias with the open source BIAS toolbox. Using this toolbox we identify which configurations cause bias and what type of bias it is. In addition, we analyse the results to make clear recommendations on which components and parameters can be used in Differential Evolution to ensure unbiased behaviour within reasonable computational budget.Item Metadata only Analyzing evolutionary algorithms for dynamic optimization problems based on the dynamical system.(Springer-Verlag., 2013) Tinos, Renato; Yang, ShengxiangItem Metadata only Ant colony optimization algorithms with immigrants schemes for the dynamic travelling salesman problem.(Springer-Verlag, 2013) Mavrovouniotis, Michalis; Yang, ShengxiangItem Embargo Ant colony optimization for dynamic combinatorial optimization problems(The Institution of Engineering and Technology, 2018-02) Mavrovouniotis, Michalis; Yang, ShengxiangThe ant colony optimization (ACO) metaheuristic was inspired from the foraging behaviour of real ant colonies. In particular, real ants communicate indirectly via pheromone trails and find the shortest path. Although real ants proved that they can find the shortest path when the available paths are known a prior; they may face serious challenges when some paths are made available after the colony has converged to a path. This is because the colony may continue to follow the current path rather than exploring the new paths in case a shorter path is available. For the ACO metaheuristic, the challenges are similar when applied to dynamic optimization problems (DOPs). Once the algorithm converges, it loses its adaptation capabilities and may have poor performance in DOPs. Several strategies have been integrated with ACO to address difficult combinatorial DOPs. Their performance proved that ACO is a powerful computational technique for combinatorial DOPs once enhanced. This chapter investigates the applications of ACO for combinatorial DOPs.Item Metadata only Application of fuzzy logic in computer security and forensics.(Springer, 2012) Al Amro, S.; Chiclana, Francisco; Elizondo, DavidItem Metadata only The Application of Fuzzy Logic in Determining Outcomes of eSports Events(Springer, Cham, 2021-05-05) Deane, Spencer; Khuman, A. S.As eSports skyrocket in popularity, the saturation of top talent intensifies. Hundreds of millions of dollars in prize money are distributed amongst this talent, resulting in fierce competition. To get ahead, players go to extreme measures to gain marginal performance increases. Besides intense training and performance enhancing drugs, athletes seek intelligent analytical tools which can provide useful insights into a player’s strengths and weaknesses. This report showcases a fuzzy system which uses real-world data and determines a player’s percentage chance of winning a duel in the online first-person shooter video game Counter-Strike Global Offensive, one of the leading eSports.