Businesses nowadays are increasingly adopting new technologies to obtain competitive advantages. Artificial Intelligence (AI) stands out as an advanced, novel technology that has potential benefits across industries. The fast-food industry is one such industry that is highly competitive, evolving, and requires advanced technologies to cater to modern customers who increasingly demand fast, digitized services. Increased customer engagement has also become a main driving force to adopt technologies since these consumers demand quick, personalized, digitized services. The fast-food industry, compared to other industries, produces food that is perishable, and quick, which demands proper handling before, during, and after preparation, for instant consumption. Services should be quick, fast, and accessible, where adopting advanced technologies has become a necessity for the industry players' survival. Larger organizations have successfully adopted AI and have harnessed a competitive advantage. Conversely, Smaller and Medium Enterprises (SMEs) have successfully adopted digital technologies, assuming it as AI. They have not yet translated to adopt AI, which could threaten their survival and competitiveness in a highly evolving, dynamic industry. On the other hand, AI is a novel technology that has much potential, yet many are unaware of where the technology is heading, specifically, SMEs have a limited understanding and exposure to this technology, demanding more research.  The main purpose of this study is to gain a comprehensive understanding of how fast-food SMEs in Sweden perceive AI, the reasons for non-adoption, and the reasons influencing the behavioral intention to utilize AI for customer engagement within the organization. The study utilizes the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to analyze how performance expectancy, effort expectancy, social influence, and facilitating conditions influence individual SMEs' behavioral intentions towards AI adoption on customer engagement by studying it from an individual, organizational context. Through qualitative interviews with fast-food SME owners, IT managers, and marketing managers, the research explored a nuanced understanding of how AI is being perceived by SMEs, challenges, barriers, and factors influencing their adoption behavior.  The research findings indicated that AI technology itself is immature and the immediate business use case is not apparent for SMEs. It was also revealed that SMEs have a misconception between AI and digital technologies. Though there is enthusiasm and willingness to adopt AI within SMEs, significant challenges remain, such as a lack of understanding about AI, resource constraints, complexity, skills, and influences from competitors and stakeholders. The research identified factors specific to SMEs that contribute to extending the UTAUT framework, such as customized payment plans, establishing technology associations, and new business models suiting SMEs. It was further evidenced that customer engagement is not an impactful mediator that influences AI adoption within SMEs. It was concluded that though SMEs have the potential to improve performance, their adoption is limited due to the immaturity of AI and due to identified challenges.

<p dir="ltr">In network security, the exponential growth of intrusions stimulates research toward developing advanced artificial intelligence (AI) techniques for intrusion detection systems (IDS). However, the reliance on AI for IDS presents challenges, including the performance variability of different AI models and the lack of explainability of their decisions, hindering the comprehension of outputs by human security analysts. Hence, this thesis proposes end-to-end explainable AI (XAI) frameworks tailored to enhance the understandability and performance of AI models in this context.</p><p><br></p><p dir="ltr">The first chapter benchmarks seven black-box AI models across one real-world and two benchmark network intrusion datasets, laying the foundation for subsequent analyses. Subsequent chapters delve into feature selection methods, recognizing their crucial role in enhancing IDS performance by extracting the most significant features for identifying anomalies in network security. Leveraging XAI techniques, novel feature selection methods are proposed, showcasing superior performance compared to traditional approaches.</p><p><br></p><p dir="ltr">Also, this thesis introduces an in-depth evaluation framework for black-box XAI-IDS, encompassing global and local scopes. Six evaluation metrics are analyzed, including descrip tive accuracy, sparsity, stability, efficiency, robustness, and completeness, providing insights into the limitations and strengths of current XAI methods.</p><p><br></p><p dir="ltr">Finally, the thesis addresses the potential of ensemble learning techniques in improving AI-based network intrusion detection by proposing a two-level ensemble learning framework comprising base learners and ensemble methods trained on input datasets to generate evalua tion metrics and new datasets for subsequent analysis. Feature selection is integrated into both levels, leveraging XAI-based and Information Gain-based techniques.</p><p><br></p><p dir="ltr">Holistically, this thesis offers a comprehensive approach to enhancing network intrusion detection through the synergy of AI, XAI, and ensemble learning techniques by providing open-source codes and insights into model performances. Therefore, it contributes to the security advancement of interpretable AI models for network security, empowering security analysts to make informed decisions in safeguarding networked systems.<br></p>

The goal of General Game Playing (GGP) is to develop a system, that is able to automatically play previously unseen games well, solely by being given the rules of the game. In contrast to traditional game playing programs, a general game player cannot be given game specific knowledge. Instead, the program has to discover this knowledge and use it for effectively playing the game well without human intervention. In this thesis, we present a such a program and general methods that solve a variety of knowledge discovery problems in GGP. Our main contributions are methods for the automatic construction of heuristic evaluation functions, the automated discovery of game structures, a system for proving properties of games, and symmetry detection and exploitation for general games.

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem. / Address: NaN Mob. +46 - 737 - 40 19 17

Commercial computer gaming is a large growing industry, that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards because of some broad sets of problems. Some of these problems have been solved with the advent of an open real time research platform, named as ORTS. However there still exist some fundamental AI problems that require more research to be better solved for the RTS games. There also exist some AI algorithms that can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems for the RTS games. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for each AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of selected anytime algorithms for an AI problem

The present study is aiming to evaluate the Intelligent Personal Assistants usage motivations, addressing at the same time various privacy issues and concerns related to this emergent technology. To fulfil the purpose of the study I have applied two different research methods. Initially, a web survey conducted gathered 18 respondents answering 24 questions related to the presented topic. Subsequently, was organised a focus group by gathering seven respondents who shared their opinions on the subject of research. Two research questions were developed based on two hypotheses. First research question: “To what extent IPA users agree to personal data collection in order to gratify their sought needs?”; exploring the participants’ opinions when it comes to the degree of acceptance of personal information disclosure to gratify their needs. Moreover, second research question: “What are the motivating criteria that determine the usage of IPA?”. This question develops opinions and experiences on the usage of Intelligent Personal Assistants, as well as the way people perceive this new technology. The finding of this studies reveals that users of new media are concerned and aware of their personal data collection. However, as a result, they feel trapped in the network society by the peer pressure towards the usage of favourite mediums. Therefore, the denial of technology would bring unfavourable consequences from a social perspective. Further researches can be conducted on this topic, addressing in depth the Artificial Intelligence and its societal implications, possible utilities of the Intelligent Personal Assistants as a companion for children, elders and people with disabilities, Artificial Intelligence used in public administration. Consequently, many different aspects can be explored having the topic of this thesis as a starting point.

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Digital transformation is evolving, and it is driving at the helm of the digital evolution. The amount of information accessible to us has revolutionized the way we gather information. Mobile technology and the immediate and ubiquitous access to information has changed how we engage with services including healthcare. Digital technology and digital transformation have afforded people the ability to self-manage in different ways than face-to-face and paper-based methods through different technologies. This study focuses on exploring the use of the most commonly used digital health technologies in the healthcare sector and how it affects physicians’ daily routine practice. The study presents findings from a qualitative methodology involving semi-structured, personal interviews with physicians from Sweden and a physician from Spain. The interviews capture what physicians feel towards digital transformation, digital health technologies and how it affects their work. In a field where a lack of information regarding how physicians work is affected by digital health technologies, this study reveals a general aspect of how reality looks for physicians. A new way of conducting medicine and the changed role of the physician is presented along with the societal implications for physicians and the healthcare sector. The findings demonstrate that physicians’ role, work and the digital transformation in healthcare on a societal level are important in shaping the future for the healthcare industry and the role of the physician in this future. / Den digitala transformationen växer och den drivs vid rodret för den digitala utvecklingen. Mängden information som är tillgänglig för oss har revolutionerat hur vi samlar in information. Mobila tekniker och den omedelbara och allmänt förekommande tillgången till information har förändrat hur vi tillhandahåller oss tjänster inklusive inom vården. Digital teknik och digital transformation har gett människor möjlighet att kontrollera sig själv och sin egen hälsa på olika sätt än ansikte mot ansikte och pappersbaserade metoder genom olika tekniker. Denna studie fokuserar på att utforska användningen av de vanligaste digitala hälsoteknologierna inom hälso- och sjukvårdssektorn och hur det påverkar läkarnas dagliga rutin. Studien presenterar resultat från en kvalitativ metod som involverar semistrukturerade, personliga intervjuer med läkare från Sverige och en läkare från Spanien. Intervjuerna fångar vad läkare tycker om digital transformation, digital hälsoteknik och hur det påverkar deras arbete. I ett fält där brist på information om hur läkare arbetar påverkas av digital hälsoteknik avslöjar denna studie en allmän aspekt av hur verkligheten ser ut för läkare. Ett nytt sätt att bedriva medicin och läkarens förändrade roll presenteras tillsammans med de samhälleliga konsekvenserna för läkare och vårdsektorn. Resultaten visar att läkarnas roll, arbete och den digitala transformationen inom hälso- och sjukvården på samhällsnivå är viktiga för att utforma framtiden för vårdindustrin och läkarens roll i framtiden.

[ES] La presente tesis aborda el problema del encaminamiento en las redes definidas por software (SDN). Específicamente, aborda el problema del diseño de un protocolo de encaminamiento basado en inteligencia artificial (AI) para garantizar la calidad de servicio (QoS) en transmisiones multimedia. En la primera parte del trabajo, el concepto de SDN es introducido. Su arquitectura, protocolos y ventajas son comentados. A continuación, el estado del arte es presentado, donde diversos trabajos acerca de QoS, encaminamiento, SDN y AI son detallados. En el siguiente capítulo, el controlador SDN, el cual juega un papel central en la arquitectura propuesta, es presentado. Se detalla el diseño del controlador y se compara su rendimiento con otro controlador comúnmente utilizado. Más tarde, se describe las propuestas de encaminamiento. Primero, se aborda la modificación de un protocolo de encaminamiento tradicional. Esta modificación tiene como objetivo adaptar el protocolo de encaminamiento tradicional a las redes SDN, centrado en las transmisiones multimedia. A continuación, la propuesta final es descrita. Sus mensajes, arquitectura y algoritmos son mostrados. Referente a la AI, el capítulo 5 detalla el módulo de la arquitectura que la implementa, junto con los métodos inteligentes usados en la propuesta de encaminamiento. Además, el algoritmo inteligente de decisión de rutas es descrito y la propuesta es comparada con el protocolo de encaminamiento tradicional y con su adaptación a las redes SDN, mostrando un incremento de la calidad final de la transmisión. Finalmente, se muestra y se describe algunas aplicaciones basadas en la propuesta. Las aplicaciones son presentadas para demostrar que la solución presentada en la tesis está diseñada para trabajar en redes heterogéneas. / [CA] La present tesi tracta el problema de l'encaminament en les xarxes definides per programari (SDN). Específicament, tracta el problema del disseny d'un protocol d'encaminament basat en intel·ligència artificial (AI) per a garantir la qualitat de servici (QoS) en les transmissions multimèdia. En la primera part del treball, s'introdueix les xarxes SDN. Es comenten la seva arquitectura, els protocols i els avantatges. A continuació, l'estat de l'art és presentat, on es detellen els diversos treballs al voltant de QoS, encaminament, SDN i AI. Al següent capítol, el controlador SDN, el qual juga un paper central a l'arquitectura proposta, és presentat. Es detalla el disseny del controlador i es compara el seu rendiment amb altre controlador utilitzat comunament. Més endavant, es descriuen les propostes d'encaminament. Primer, s'aborda la modificació d'un protocol d'encaminament tradicional. Aquesta modificació té com a objectiu adaptar el protocol d'encaminament tradicional a les xarxes SDN, centrat a les transmissions multimèdia. A continuació, la proposta final és descrita. Els seus missatges, arquitectura i algoritmes són mostrats. Pel que fa a l'AI, el capítol 5 detalla el mòdul de l'arquitectura que la implementa, junt amb els mètodes intel·ligents usats en la proposta d'encaminament. A més a més, l'algoritme intel·ligent de decisió de rutes és descrit i la proposta és comparada amb el protocol d'encaminament tradicional i amb la seva adaptació a les xarxes SDN, mostrant un increment de la qualitat final de la transmissió. Finalment, es mostra i es descriuen algunes aplicacions basades en la proposta. Les aplicacions són presentades per a demostrar que la solució presentada en la tesi és dissenyada per a treballar en xarxes heterogènies. / [EN] This thesis addresses the problem of routing in Software Defined Networks (SDN). Specifically, the problem of designing a routing protocol based on Artificial Intelligence (AI) for ensuring Quality of Service (QoS) in multimedia transmissions. In the first part of the work, SDN is introduced. Its architecture, protocols and advantages are discussed. Then, the state of the art is presented, where several works regarding QoS, routing, SDN and AI are detailed. In the next chapter, the SDN controller, which plays the central role in the proposed architecture, is presented. The design of the controller is detailed and its performance compared to another common controller. Later, the routing proposals are described. First, a modification of a traditional routing protocol is discussed. This modification intends to adapt a traditional routing protocol to SDN, focused on multimedia transmissions. Then, the final proposal is described. Its messages, architecture and algorithms are depicted. As regards AI, chapter 5 details the module of the architecture that implements it, along with all the intelligent methods used in the routing proposal. Furthermore, the intelligent route decision algorithm is described and the final proposal is compared to the traditional routing protocol and its adaptation to SDN, showing an increment of the end quality of the transmission. Finally, some applications based on the routing proposal are described. The applications are presented to demonstrate that the proposed solution can work with heterogeneous networks. / Rego Máñez, A. (2020). Intelligent multimedia flow transmission through heterogeneous networks using cognitive software defined networks [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/160483 / TESIS

The goal of General Game Playing (GGP) is to develop a system, that is able to automatically play previously unseen games well, solely by being given the rules of the game. In contrast to traditional game playing programs, a general game player cannot be given game specific knowledge. Instead, the program has to discover this knowledge and use it for effectively playing the game well without human intervention. In this thesis, we present a such a program and general methods that solve a variety of knowledge discovery problems in GGP. Our main contributions are methods for the automatic construction of heuristic evaluation functions, the automated discovery of game structures, a system for proving properties of games, and symmetry detection and exploitation for general games.:1. Introduction 2. Preliminaries 3. Components of Fluxplayer 4. Game Tree Search 5. Generating State Evaluation Functions 6. Distance Estimates for Fluents and States 7. Proving Properties of Games 8. Symmetry Detection 9. Related Work 10. Discussion