1,618 research outputs found

    Intelligent interface agents for biometric applications

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    This thesis investigates the benefits of applying the intelligent agent paradigm to biometric identity verification systems. Multimodal biometric systems, despite their additional complexity, hold the promise of providing a higher degree of accuracy and robustness. Multimodal biometric systems are examined in this work leading to the design and implementation of a novel distributed multi-modal identity verification system based on an intelligent agent framework. User interface design issues are also important in the domain of biometric systems and present an exceptional opportunity for employing adaptive interface agents. Through the use of such interface agents, system performance may be improved, leading to an increase in recognition rates over a non-adaptive system while producing a more robust and agreeable user experience. The investigation of such adaptive systems has been a focus of the work reported in this thesis. The research presented in this thesis is divided into two main parts. Firstly, the design, development and testing of a novel distributed multi-modal authentication system employing intelligent agents is presented. The second part details design and implementation of an adaptive interface layer based on interface agent technology and demonstrates its integration with a commercial fingerprint recognition system. The performance of these systems is then evaluated using databases of biometric samples gathered during the research. The results obtained from the experimental evaluation of the multi-modal system demonstrated a clear improvement in the accuracy of the system compared to a unimodal biometric approach. The adoption of the intelligent agent architecture at the interface level resulted in a system where false reject rates were reduced when compared to a system that did not employ an intelligent interface. The results obtained from both systems clearly express the benefits of combining an intelligent agent framework with a biometric system to provide a more robust and flexible application

    Integration of social values in a multi-agent platform running in a supercomputer

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    Agent-based modelling is one of the most suitable ways to simulate and analyse complex problems and scenarios, especially those involving social interactions. Multi-agent systems, consisting of multiple agents in a simulation environment, are widely used to understand emergent behaviour in various fields such as sociology, economics and policy. However, existing multi-agent platforms often face challenges in terms of scalability and reasoning capacity. Some platforms can scale well in terms of computation, but lack sophisticated reasoning mechanisms. On the other hand, some platforms employ complex reasoning systems, but this can compromise their scalability. In this work, we have extended an existing platform developed at UPC that enables scalable, parallel HTN planning for complex agents. Our main goal has been to improve the analysis of social relationships between agents by incorporating moral values. Building on previous work done by David Marín on the implementation of the platform, we have made extensions and modifications both formally and in the implementation. We have formalised the additions to the system model and provided an updated implementation. Finally, we have presented a complex example scenario that demonstrates all the additions we have made. This scenario allows us to show how agents' preferences and moral values influence their decisions and actions in a simulated environment. Through this work, we have sought to improve the existing platform and fulfil the spirit and purpose of the platform

    Machine Learning Algorithm for the Scansion of Old Saxon Poetry

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    Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input verses

    Deconstructing Orthorexia in an Age of Healthism and Social Media

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    Orthorexia, a pathological fixation with healthy eating, has recently emerged as a construct of interest in the field of clinical psychology. Despite its growing recognition, the origin of this construct remains unclear. This dissertation aims to contribute to the understanding of orthorexia by examining its emergence and contextual factors through a constructivist lens. The study found that the cultural, economic, and moralistic landscape of healthism and social medially have played a role in the development of orthorexia. The dominant clinical perspective of orthorexia was also deconstructed, revealing potential biases that may lead to pathologizing the experiences of those who demonstrate orthorexic behaviors. The study highlights the need for careful consideration of the risks and vulnerabilities associated with the integration of orthorexia into diagnostic and clinical models. However, it also acknowledges the reality of individuals expressing suffering in the form of orthorexic behavior and provides treatment considerations to honor their experiences and desire for relief in a clinical setting. This dissertation is available in open access at AURA (https://aura.antioch.edu) and OhioLINK ETD Center (https://etd.ohiolink.edu)

    Contributions of Human Prefrontal Cortex to the Recogitation of Thought

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    Human beings have a unique ability to not only verbally articulate past and present experiences, as well as potential future ones, but also evaluate the mental representations of such things. Some evaluations do little good, in that they poorly reflect facts, create needless emotional distress, and contribute to the obstruction of personal goals, whereas some evaluations are the converse: They are grounded in logic, empiricism, and pragmatism and, therefore, are functional rather than dysfunctional. The aim of non-pharmacological mental health interventions is to revise dysfunctional thoughts into more adaptive, healthier ones; however, the neurocognitive mechanisms driving cognitive change have hitherto remained unclear. Therefore, this thesis examines the role of the prefrontal cortex (PFC) in this aspect of human higher cognition using the relatively new method of functional near-infrared spectroscopy (fNIRS). Chapter 1 advances recogitation as the mental ability on which cognitive restructuring largely depends, concluding that, as a cognitive task, it is a form of open-ended human problem-solving that uses metacognitive and reasoning faculties. Because these faculties share similar executive resources, Chapter 2 discusses the systems in the brain involved in controlled information processing, specifically the nature of executive functions and their neural bases. Chapter 3 builds on these ideas to propose an information-processing model of recogitation, which predicts the roles of different subsystems localized within the PFC and elsewhere in the context of emotion regulation. This chapter also highlights several theoretical and empirical challenges to investigating this neurocognitive theory and proposes some solutions, such as to use experimental designs that are more ecologically valid. Chapter 4 focuses on a neuroimaging method that is best suited to investigating questions of spatial localization in ecological experiments, namely functional near-infrared spectroscopy (fNIRS). Chapter 5 then demonstrates a novel approach to investigating the neural bases of interpersonal interactions in clinical settings using fNIRS. Chapter 6 explores physical activity as a ‘bottom-up’ approach to upregulating the PFC, in that it might help clinical populations with executive deficits to regulate their mental health from the ‘top-down’. Chapter 7 addresses some of the methodological issues of investigating clinical interactions and physical activity in more naturalistic settings by assessing an approach to recovering functional events from observed brain data. Chapter 8 draws several conclusions about the role of the PFC in improving psychological as well as physiological well-being, particularly that rostral PFC is inextricably involved in the cognitive effort to modulate dysfunctional thoughts, and proposes some important future directions for ecological research in cognitive neuroscience; for example, psychotherapy is perhaps too physically stagnant, so integrating exercise into treatment environments might boost the effectiveness of intervention strategies

    Multi-Agent Modelling of Industrial Cyber-Physical Systems for IEC 61499 Based Distributed Intelligent Automation

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    Traditional industrial automation systems developed under IEC 61131-3 in centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. Major challenges are that these systems designed under traditional engineering techniques and running on legacy automation platforms are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules, and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. The core objective of this research is to explore the design of multi-layer automation architectures to enable real-time adaptation at the device level and run-time intelligence throughout the whole system under a well-integrated modelling framework. Central to this goal is the research on the integration of multi-agent modelling and IEC 61499 function block modelling to form a new automation infrastructure for industrial cyber-physical systems. Multi-agent modelling uses autonomous and cooperative agents to achieve run-time intelligence in system design and module reconfiguration. IEC 61499 function block modelling applies object-oriented and event-driven function blocks to realize real-time adaption of automation logic and control algorithms. In this thesis, the design focuses on a two-layer self-manageable architecture modelling: a) the high-level cyber module designed as multi-agent computing model consisting of Monitoring Agent, Analysis Agent, Self-Learning Agent, Planning Agent, Execution Agent, and Knowledge Agent; and b) the low-level physical module designed as agent-embedded IEC 61499 function block model with Self-Manageable Service Execution Agent, Self-Configuration Agent, Self-Healing Agent, Self-Optimization Agent, and Self-Protection Agent. The design results in a new computing module for high-level multi-agent based automation architectures and a new design pattern for low-level function block modelled control solutions. The architecture modelling framework is demonstrated through various tests on the multi-agent simulation model developed in the agent modelling environment NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The performance evaluation of regular execution time and adaptation time in two typical conditions for systems designed under three different architectures are also analyzed. The results demonstrate the ability of the proposed architecture to respond to major challenges in Industry 4.0

    New insights on the multidimensionality of fatigue and on its relationship with cognitive impairments in multiple sclerosis

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    Multiple Sclerosis (MS) is an inflammatory disease of the central nervous system (CNS), and it represents the most common cause of irreversible impairment in young adults, affecting about 2.5 million individuals worldwide. In MS, acute attacks of inflammation, leading to demyelination and axonal loss, determine the accumulation of disabilities, varying in number, nature, and severity. Indeed, motor, sensory, cognitive, and behavioral symptoms may manifest at different times during the disease's variable clinical course. Fatigue is a complex and multifaceted phenomenon and one of the most prevalent and disabling symptoms of MS, affecting 75%–90% of patients. Despite its prevalence, MS- related fatigue is still poorly understood. The absence of a well-validated definition and of clear insights into its pathophysiological causes makes fatigue a hybrid symptom, approached within the context of different disciplines, each with their own methods and tools. As a result, the scientific literature abounds with irreconcilable data, leaving fatigue in a dark shadow zone, at the expense of MS patients still lacking adequate therapies and strategies of management. The main topic of this thesis relates to the multidimensional nature of fatigue, to its variability, and its effects on attentional processes, most commonly affected in MS patients. Specifically, studies presented in the current thesis address four research issues: (i) are physical and mental fatigue two distinct constructs? (ii) how do physical and mental fatigue vary within a short (within a day) and long (within a year) period? (iii) how do induced physical and mental fatigue impact the attentional functions of alerting, orienting, and conflict resolution in MS? The main results of the studies are reported: a) A clear distinction between physical and mental fatigue has been psychometrically documented in MS patients. b) MS patients reported experiencing more overall fatigue than Controls. c) A gradual increase in overall fatigue from the morning to the evening was reported by MS participants. d) Across experiments physical fatigue was significantly more pronounced in MS patients as compared to Controls. e) Both MS patients and Controls reported having experienced more overall fatigue in the past (one year ago) than in the present (the last 24 hours). f) MS patients were slower as compared to Controls in performing attentional tasks; however, inconclusive results have emerged regarding the effects of physical and mental fatigue on attentional processes. g) Sleep quality and depression were both associated with fatigue across the experiments. The relationship between self-efficacy, general cognitive functioning, functional deterioration, and physical and mental fatigue is fragmented, thus preventing a clear conclusion
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