Browsing by Author "Khuman, A. S."
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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 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 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.Item Metadata only Artificial Intelligence in FPS Games: NPC Difficulty Effects on Gameplay(Springer, Cham, 2021-05-05) Hubble, Adam; Moorin, Jack; Khuman, A. S.This report explores the use of fuzzy logic within computer games, with specific respect to their use of Artificial Intelligence (AI) within the games’ enemy Non-Player Characters (NPCs), in order to affect the game’s overall difficulty. The way in which AI is affected varies across different games; games within the same genre often share multiple statistics and values, and these can be applied to an NPC in order to make the game easier or harder. Games within the First-Person Shooter (FPS) genre, for example, can always affect their difficulty by changing an enemy character’s accuracy with weapons or overall damage output as these would all change how likely they are to defeat the player in a combat scenario. In this document, we will be detailing the development and structure of the multiple input Mamdani styled fuzzy inference system (FIS) that we developed in order to rate a given NPC’s difficulty based on the rankings they have been given for these shared statistics.Item Embargo Artificial Intelligence in Healthcare: Recent Applications and Developments(Springer, 2022-10-27) Khuman, A. S.; Chen, Tianhua; Carter, Jenny; Mufti, MahmudRecent advances in artificial intelligence (AI) and machine learning have witnessed many successes in various disciplines including the healthcare sector. Innovations in intelligent medical systems have revolutionized the way in which healthcare services are provided, ranging from making clinical diagnosis, developing personalized treatment and drugs, assisting patient monitoring, to automating administrative tasks and reducing operational costs. In this book, the authors present key applications in the general area of health care, where AI has made significant successes. From the individual chapters, the readers will be provided with a range of examples to illustrate the wide plethora of application domains utilizing state-of-the-art AI techniques, proving credence to the versatility and effectiveness of an AI approach in health care and medicine. We envisage that this book is ideal for individuals new to the notion of AI in health care, equally, early career academics who wish to further expand on their knowledge in AI in medicine. What will be presented is in no means an exhaustive list of applications, but most definitely a varied one.Item Metadata only Automatic Camera Flash Using a Mamdani Type One Fuzzy Inference System(Springer, Cham, 2021-05-05) Hughes, Sophie; Khuman, A. S.Photography is an enjoyable hobby for many people, with many systems having been developed to make it easier for newcomers to begin learning how to take a quality photograph. Features such as automatic aperture and shutter speed allow the user to take a photo without any prior knowledge as to how these two should be manipulated in order to take a good photo. However, a feature that has not currently been explored is an automatic camera flash that will change intensity based on a number of factors, as current automatic flash systems will simply either activate a flash or not based on the perceived light levels of the image. This chapter will utilise a Mamdani type one fuzzy inference system in order to demonstrate how an automatic camera flash could potentially work, justifying each input used as well as discussing any limitations and possible improvements.Item Open Access A commentary on some of the intrinsic differences between grey systems and fuzzy systems(IEEE, 2014-10-05) Khuman, A. S.; Yang, Yingjie; John, Robert, 1955-The aim of this paper is to distinguish between some of the more intrinsic differences that exist between grey system theory (GST) and fuzzy system theory (FST). There are several aspects of both paradigms that are closely related, it is precisely these close relations that will often result in a misunderstanding or misinterpretation. The subtly of the differences in some cases are difficult to perceive, hence why a definitive explanation is needed. This paper discusses the divergences and similarities between the interval-valued fuzzy set and grey set, interval and grey number; for both the standard and the generalised interpretation. A preference based analysis example is also put forward to demonstrate the alternative in perspectives that each approach adopts. It is believed that a better understanding of the differences will ultimately allow for a greater understanding of the ideology and mantras that the concepts themselves are built upon. By proxy, describing the divergences will also put forward the similarities. We believe that by providing an overview of the facets that each approach employs where confusion may arise, a thorough and more detailed explanation is the result. This paper places particular emphasis on grey system theory, describing the more intrinsic differences that sets it apart from the more established paradigm of fuzzy system theory.Item Metadata only Developing and delivering in block: Reflections one year in(Quality Assurance Agency, 2023-09-21) Allman, Zoe; Coupland, Simon; Attwood, Luke; Fahy, Conor; Hasshu, Salim; Khuman, A. S.; Shell, JethroItem Embargo Fostering Inclusivity Through Dynamic Teaching Practices(Springer, Cham, 2018-09-22) Khuman, A. S.Teaching within the context of Higher Education (HE), often involves interacting with a wide variety of students, who come from, and have varying backgrounds, not just in their capabilities, but also with regards to their understanding. As such, dynamic teaching styles and practices need to be adopted in order to allow for inclusivity. This chapter highlights a particular case study involving the author, and a module that he currently leads—IMAT3406: Fuzzy Logic and Knowledge Based Systems. The teaching style and approaches adopted allow for a better understanding of core concepts, from which better executed applications can be garnered. Making sure that it makes sense to all, ensures that the foundational knowledgebase needed from which to build upon is adequately in place, so that everyone in the cohort is on a level playing field. This can be achieved through dynamic teaching practices, often involving acclimation and assimilation to the cohort. Making sure that a concrete understanding exists before the students are encouraged to undertake their coursework, has proved to cater for exceptional output, not only in terms of detail, but both in quality and substance. Through tried and tested means, the case study used in this chapter sheds light on the attributes of a successful approach; describing how the author’s own accession to harbouring inclusivity is adopted and executed for the module IMAT3406.Item Embargo A Fuzzy Logic Approach to a Hybrid Lexicon-Based Sentiment Analysis Detection Tool Using Healthcare Covid-19 News Articles(Springer Singapore, 2022-10-24) Khuman, A. S.; Morden, JarradThe delivery of unbiased news articles in the healthcare sector is one of the prominent problems in the fight against unvaccinated individuals as Covid-19 causes great skepticism among many groups of people. Companies such as Facebook have already integrated AI models for context to content that is rated by third-party fact-checkers to detect misinformation (“Fonctionnement du programme de vérification tierce de Facebook,” Fonctionnement du programme de vérification tierce de Facebook. https://www.facebook.com/journalismproject/programs/third-party-fact-checking/how-it-works?locale = fr_FR (accessed Sep. 06, 2021)). In this paper we use Natural Language Processing (NLP) and Sentiment Analysis to derive the content of news articles, an API is integrated to gather news articles from various sources using the newsapi (“News API – Search News and Blog Articles on the Web,” News API. https://newsapi.org (accessed Oct. 28, 2021)). Applying VADER, Text Blob, and Flair rule-based lexicons, we create a hybrid approach from the lexicons and combine each method, we then present a novel Fuzzy-Logic Lexicon Mamdani Rule-Base Multi Inference System (FLLMRBMIF) that can generate a final sentiment from each output of polarity, we then classify into a positive, neutral and negative result. The results demonstrate that it is possible to integrate a tool to classify the sources in real-time allowing more insightful information on biased news stories.Item Embargo A Fuzzy Logic Risk Assessment System for Type 2 Diabetes(Springer, 2022-10-24) Khuman, A. S.; Marsh, JaredThis chapter details the design and evolution of a Mamdani fuzzy logic system to allow users to assess their own risk of developing type 2 diabetes. From the research behind the system to its design, conception and testing to refine the system’s accuracy. The system allows users to enter details about their lifestyle and their vital statistics such as height and weight to determine an approximate risk level of developing type 2 diabetes so they can make healthier and more mindful lifestyle choices. Choosing to make better choices will improve their quality of life and save healthcare providers or themselves a vast amount of money in the long run, depending on whether it is a national healthcare service or private provider. This system is not medically tested, and usage of this system without rigorous medical testing and alterations based on that testing is not advised.Item Metadata only Fuzzy Logic: Recent Applications and Developments(Springer International Publishing, 2021-05) Carter, Jenny; Chiclana, Francisco; Khuman, A. S.; Chen, TianhuaSince its inception, fuzzy logic has attracted an incredible amount of interest, and this interest continues to grow at an exponential rate. As such, scientists, researchers, educators and practitioners of fuzzy logic continue to expand on the applicability of what and how fuzzy can be utilised in the real-world. In this book, the authors present key application areas where fuzzy has had significant success. The chapters cover a plethora of application domains, proving credence to the versatility and robustness of a fuzzy approach. A better understanding of fuzzy will ultimately allow for a better appreciation of fuzzy. This book provides the reader with a varied range of examples to illustrate what fuzzy logic can be capable of and how it can be applied. The text will be ideal for individuals new to the notion of fuzzy, as well as for early career academics who wish to further expand on their knowledge of fuzzy applications. The book is also suitable as a supporting text for advanced undergraduate and graduate-level modules on fuzzy logic, soft computing, and applications of AI.Item Embargo Grey relational analysis and natural language Processing(IEEE, 2015-08-18) Khuman, A. S.; Yang, Yingjie; Liu, SifengThis paper investigates validity of using grey relational analysis (GRA) for natural language processing (NLP). The domain of NLP is one associated with inherent vagueness and abstraction, with many sub-domains all invoking their own associated uncertainties. Regardless of the particularisation, the main objective is understanding and making sense of linguistic lexicon. The inferencing and understanding of sentiment from natural language has been investigated thoroughly, however, the use of grey system theory in conjunction with NLP has yet to be explored in any great detail. Ergo, an introductory investigation into the effectiveness of using GRA on and with regards to NLP. This paper describes the feasibility of using grey system methodologies and tools, specifically the use of grey incidence, to provide a means for analysis of a sequence's geometric curve. The use of GRA provides one with the ability to inspect and infer sequences of data. Using this notion and by having a sequence represented as an input stream, it can be correlated against possible output commands. The use of grey incidence for quantifying and evaluating the correlation between what is inputted, against what output it is most similar to, is novel and should provide an additional facet to grey system theory.Item Open Access Grey Relational Analysis and Natural Language Processing to: Grey Language Processing(RESEARCH INFORMATION LTD, 2016-01-01) Khuman, A. S.; Yang, Yingjie; Liu, SifengThis paper investigates the validity of using grey relational analysis (GRA) for natural language processing (NLP). The domain of NLP is one associated with inherent vagueness and abstraction; with many sub-domains, all invoking their own associated uncertainties. Regardless of the particularisation, the main objective is understanding and making sense of linguistic lexicon. The inferencing and understanding of sentiment from natural language has been investigated thoroughly, however, the use of grey system theory in conjunction with NLP has yet to be explored in any great detail. Ergo, an introductory investigation into the effectiveness of using GRA on and with regards to NLP. This paper describes the feasibility of using grey system methodologies and tools, specifically the use of grey incidence, to provide a means for analysis of a sequence's geometric curve. The use of GRA provides one with the ability to inspect and infer sequences of data. Using this notion and by having a sequence represented as an input stream, it can be correlated against possible output commands. The use of grey incidence for quantifying and evaluating the correlation between what is inputted, against what output it is most similar to, is novel and should provide an additional facet to grey system theory.Item Metadata only Grey systems and uncertainty modelling(Springer, 2023-02-05) Yang, Yingjie; Khuman, A. S.; Liu, SifengInformation can, and often is, rather uncertain; with only partial information initially being made available, from which one would be able to hopefully provide for a solution. The information itself may contain conflicts that have arisen from the possible different sources used to acquire it. In addition, the information may be viewed and interpreted differently by different cohorts, this in itself can be the cause of extenuating circumstances. These are just some of the issues that one can face with uncertain information. These issues can understandably create problems when considering the deployment of applications. Being able to cater for the volatility that is inherently present in uncertainty, becomes an objective with high importance and precedence.Item Embargo The Importance of Transnational Education and International Engagement for Future Collaborations(Springer International Publishing, 2019) Khuman, A. S.Many universities and higher educational institutes throughout the world have had a long and distinguished history with the involvement of international students, and international collaboration efforts and partnerships. International student recruitment for UK based institutes has now become, and continues to be, somewhat very competitive, as these students pay considerably more for their chosen programmes of study, when compared to their institute’s native population. Therefore, international student recruitment is factored into the business models of many UK based Higher Education (HE) institutions. Due to the competitive nature of student recruitment and the need to diversify income generation of universities from relying on native student populations, one should also consider more extensive recruiting of international students, and in doing so, establishing more international collaborations. This chapter will highlight the efforts adopted by De Montfort University (DMU) as its case study, in expanding its outreach into emerging and developing Asian markets, due to its recent (2018) Gold award in the Government’s Teaching Excellence Framework (TEF). From this engagement, several opportunities have arisen in conjunction with Asia Pacific University (APU). The author’s own experience in dealing with this particular tour of Malaysia is commented on, as too are the benefits of such engagements to that of Transnational Education (TNE) with regards to computing related subjects.Item Metadata only A Mamdani Fuzzy Logic Inference System to Estimate Project Cost(Springer, Cham, 2021-05-05) Maia, Daniel Helder; Khuman, A. S.The precision and reliability of estimations of project costs are essential, especially in significant cooperation. The level of uncertainty when estimating projects can cause issues down the line during a project. For generations, humans are more often than always in a predicament where estimation for a project size or cost appears to be complicated. The methodology adopted in this research included using the literature to review the topic of project estimation and explore the use of fuzzy logic in order to define an initial fuzzy system. The development of a system to estimate project costs is based on findings from the literature. This work seeks to demonstrate the benefits of using fuzzy logic in estimating the cost for business. Analysis of the results attained during testing and research shows that the system could be beneficial for estimating the cost of projects. The results show that the system can produce an appropriate result when estimating project cost. The study concludes that there is still room for improvement and that further development and testing could lead to improvements; however, the current system gives a foundation for further development such that the system can be put to use in a real-world situation. Whether it is for business or personal circumstances where any or most cases, cost estimation is required.Item Metadata only A new approach to improve the overall accuracy and the filter value accuracy of the GM(1,1) new-information and GM(1,1) metabolic models(IEEE, 2013) Khuman, A. S.; Yang, Yingjie; John, Robert, 1955-Item Metadata only Pathfinding in partially explored games environments: The application of the A∗ Algorithm with occupancy grids in Unity3D(IEEE, 2014) Stamford, J.; Khuman, A. S.; Carter, J.; Ahmadi, SamadItem Open Access Predicting Social Engineering Security Threats Using Fuzzy Logic(2020-12-13) Morden, Jarrad; Khuman, A. S.; Fasanmade, Alex; Lakoju, MikeSmall and large businesses are increasingly using new technology to store important resources, such as records, financial reports, personal and sensitive data. This paper investigates cybercriminals who use email-based social engineering to influence human behavior and consequently, the authors put forward a framework for mitigating such attacks. Recent findings highlight the heightened levels of cyber-attacks and poor condition of information security systems globally. The complexity of social engineering attacks calls for more attention and methods for mitigation. To this end, using Fuzzy Logic theory, the authors propose a Mamdani Fuzzy Inference Model (FIS) to produce risk mitigation of a company's security level deduced from the email social engineering attacks, since they are often focused on human subjective interpretation of ambiguity. Results show that centroid, bisector and MOM (Middle of Maxima) defuzzification methods produces a predicted accuracy of 90% for the company security level prediction, whilst the other more extreme defuzzification methods LOM (Largest of Maxima), SOM (Smallest of Maxima) achieves a negative result of ~75%, thus Centroid, MOM and Bisector provide the best accuracy.