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Дисертації з теми "Brain model: artificial intelligence"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Mendeleck, Andre. "Um modelo conexionista para a geração de movimentos voluntarios em ambiente desestruturado." [s.n.], 1995. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263849.

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Orientador: Douglas Eduardo Zampieri<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-07-20T21:35:26Z (GMT). No. of bitstreams: 1 Mendeleck_Andre_D.pdf: 34563816 bytes, checksum: eb6f74befb171f93b3b0ab498352357e (MD5) Previous issue date: 1995<br>Resumo: Neste trabalho apresentamos uma estrutura neuronal artificial com autoaprendizado para o auxílio à geração de trajetórias em um ambiente desestruturado, O objetivo é formar uma sequência de valores de referência que podem auxiliar a definição de um caminho ou uma tr

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2

Kogeyama, Renato. "Who is the cowboy in Washington?: beating google at their own game with neuroscience and cryptography." reponame:Repositório Institucional do FGV, 2014. http://hdl.handle.net/10438/13524.

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Submitted by RENATO Kogeyama (rkogeyama@gmail.com) on 2015-03-06T14:50:01Z No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc2272d6edcdbabe5703b90 (MD5)<br>Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2015-03-10T12:44:03Z (GMT) No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc2272d6edcdbabe5703b90 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2015-03-12T19:58:58Z (GMT) No. of bitstreams: 1 Dissertação final.pdf: 1794273 bytes, checksum: b90c57e65dc227

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3

Gomez, Chloé. "DeepStim Project. Modeling states of consciousness and their modulation by electrical Deep Brain Stimulation : from experimental data to computational models." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASL027.

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Le diagnostic des patients dans le coma est souvent diﬃcile. Les examens cérébraux ren- seignent les médecins sur l’étendue des lésions cérébrales mais ne permettent pas de déterminer avec précision l’état de conscience du patient. De plus, aucune approche thérapeutique ne permet une restauration systématique de la conscience.Des études pionnières menées sur des patients et des Primates Non Humains (PNH) ont montré que la Stimulation Cérébrale Profonde (SCP) des noy- aux intralaminaires du thalamus pouvait restaurer ou améliorer la conscience lorsqu’elle est altérée.Cependant, les conséquences

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4

Voils, Danny. "Scale Invariant Object Recognition Using Cortical Computational Models and a Robotic Platform." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/632.

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This paper proposes an end-to-end, scale invariant, visual object recognition system, composed of computational components that mimic the cortex in the brain. The system uses a two stage process. The first stage is a filter that extracts scale invariant features from the visual field. The second stage uses inference based spacio-temporal analysis of these features to identify objects in the visual field. The proposed model combines Numenta's Hierarchical Temporal Memory (HTM), with HMAX developed by MIT's Brain and Cognitive Science Department. While these two biologically inspired paradigms a

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5

Aitkenhead, Matthew. "Using artificial intelligence to model complex systems." Thesis, University of Aberdeen, 2003. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU602065.

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Two observations underpin this thesis; 1. There is a need for automated pattem-recognition techniques that allow processes requiring skills normally associated with the human brain to be carried out rapidly, reliably and cheaply, and; 2. The current methods applied to solving artificial intelligence (AI) problems are insufficient to the task of creating generalised systems capable of pattem-recognition and environmental interaction. Neural networks (NNs) are a good method of solving AI problems that are difficult or impossible to solve using knowledge-based or symbolic techniques. NNs provide

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6

Machado, Beatriz. "Artificial intelligence to model bedrock depth uncertainty." Thesis, KTH, Jord- och bergmekanik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252317.

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The estimation of bedrock level for soil and rock engineering is a challenge associated to many uncertainties. Nowadays, this estimation is performed by geotechnical or geophysics investigations. These methods are expensive techniques, that normally are not fully used because of limited budget. Hence, the bedrock levels in between investigations are roughly estimated and the uncertainty is almost unknown. Machine learning (ML) is an artificial intelligence technique that uses algorithms and statistical models to predict determined tasks. These mathematical models are built dividing the data be

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7

Coletti, Mark. "An analysis of a model-based evolutionary algorithm| Learnable Evolution Model." Thesis, George Mason University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3625081.

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<p>An evolutionary algorithm (EA) is a biologically inspired metaheuristic that uses mutation, crossover, reproduction, and selection operators to evolve solutions for a given problem. Learnable Evolution Model (LEM) is an EA that has an evolutionary algorithm component that works in tandem with a machine learner to collaboratively create populations of individuals. The machine learner infers rules from best and least fit individuals, and then this knowledge is exploited to improve the quality of offspring. </p><p> Unfortunately, most of the extant work on LEM has been <i>ad hoc </i>, and so

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8

Chang, Spencer J. "Brain Tumor Classification Using Hit-or-Miss Capsule Layers." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2006.

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The job of classifying or annotating brain tumors from MRI images can be time-consuming and difficult, even for radiologists. To increase the survival chances of a patient, medical practitioners desire a means for quick and accurate diagnosis. While datasets like CIFAR, ImageNet, and SVHN have tens of thousands, hundreds of thousands, or millions of samples, an MRI dataset may not have the same luxury of receiving accurate labels for each image containing a tumor. This work covers three models that classify brain tumors using a combination of convolutional neural networks and of the concept of

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9

Golesorkhi, Mehrshad. "The Brain's Intrinsic Spatiotemporal Structure and Its Potential Application in Artificial Intelligence." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42211.

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Neuroscience focuses largely on how the brain mediates perception and cognition. However, this leaves open the basic organization and hierarchies of the brain’s neural activity by itself prior to and independent of its role in cognition. A recent model characterizes the brain’s intrinsic features in terms of temporo- spatial dynamical (rather than cognitive) terms – the brain’s spatiotemporal hierarchies shape what is called ‘brain’s intrinsicality’. The brain’s intrinsicality may provide potential applications in designing artificial intelligence (AI). In this dissertation, I explore ‘intrins

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10

董鵬飛 and Pang-fei Tung. "IntelliMap: a new GIS model with intelligence." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31221804.

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11

Tung, Pang-fei. "IntelliMap : a new GIS model with intelligence /." Hong Kong : University of Hong Kong, 1999. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20793273.

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12

Rouget, Thierry. "Learning explainable concepts in the presence of a qualitative model." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/9762.

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This thesis addresses the problem of learning concept descriptions that are interpretable, or explainable. Explainability is understood as the ability to justify the learned concept in terms of the existing background knowledge. The starting point for the work was an existing system that would induce only fully explainable rules. The system performed well when the model used during induction was complete and correct. In practice, however, models are likely to be imperfect, i.e. incomplete and incorrect. We report here a new approach that achieves explainability with imperfect models. The basis

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13

Treijs, Jonatan. "Artificial Life, A Model." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-25742.

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The model of this thesis simulates a simple artificial eco-system in which evolving and learning agents try to survive by consuming balls of energy and surviving attacks by other agents. The study finds that the model indeed manages to evolve surviving, and in some cases very aggressive, agents. The thesis presents similar conclusions to that of the study of Polyworld by Yaeger [16]; that an evolving population only facilitates a need for complexity set by the world it evolves in and stagnates when the population has reached this level of complexity. If the populations are to evolve further, t

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14

Johnson, Kathy Anne. "Exploiting a functional model of problem solving for error detection in tutoring /." The Ohio State University, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487846354482533.

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15

Browning, Andrew Wilford. "A mathematical model to simulate small boat behaviour." Thesis, Bournemouth University, 1990. http://eprints.bournemouth.ac.uk/9631/.

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The use of mathematical models and associated computer simulation is a well established technique for predicting the behaviour of large marine vessels. For a variety of reasons, mainly related to effects of scale, existing models are unable to adequately predict the manoeuvring characteristics of smaller vessels. The accuracy with which the performance of a boat under autopilot control can be predicted leaves much to be desired. The thesis provides a mathematical model to simulate small boat behaviour and so can assist with the design and testing of marine autopilots. The boat model is present

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16

Abbas, Syed Murtuza. "Advanced Hybrid Simulation Model based on Phenomenology and Artificial Intelligence." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427963095.

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17

Tamma, Valentina A. M. "An ontology model supporting multiple ontologies for knowledge sharing." Thesis, University of Liverpool, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250548.

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18

Olien, Leonard. "Analysis of a delay differential equation model of a neural network." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=23927.

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In this thesis I examine a delay differential equation model for an artificial neural network with two neurons. Linear stability analysis is used to determine the stability region of the stationary solutions. They can lose stability through either a pitchfork or a supercritical Hopf bifurcation. It is shown that, for appropriate parameter values, an interaction takes place between the pitchfork and Hopf bifurcations. Conditions are found under which the set of initial conditions that converge to a stable stationary solution is open and dense in the function space. Analytic results are illustra

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19

Stroulia, Eleni. "Failure-driven learning as model-based self-redesign." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/8291.

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20

Ross, Stéphane. "Model-based Bayesian reinforcement learning in complex domains." Thesis, McGill University, 2008. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=21960.

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Reinforcement Learning has emerged as a useful framework for learning to perform a task optimally from experience in unknown systems. A major problem for such learning algorithms is how to balance optimally the exploration of the system, to gather knowledge, and the exploitation of current knowledge, to complete the task. Model-based Bayesian Reinforcement Learning (BRL) methods provide an optimal solution to this problem by formulating it as a planning problem under uncertainty. However, the complexity of these methods has so far limited their applicability to small and simple domains. To

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21

URAS, NICOLA. "Cryptocurrency Price Prediction Improvements Through Artificial Intelligence and Model Features Refinement." Doctoral thesis, Università degli Studi di Cagliari, 2022. http://hdl.handle.net/11584/330469.

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Time series forecasting has always been one of the most investigated scientific areas and this is probably due to the large amount of fields involving a time component including, meteorology, finance, econometric, astronomy, earthquake prediction, just to mention a few. The present work studies the field of financial time series forecasting, mainly focusing on the Cryptocurrency market. This field poses very sophisticated problems for several reasons. Due to its recent birth, this market has a dynamic nature continuously giving rise to new cryptocurrencies leading to frequent and sudden variat

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22

Liao, Kua-ping. "Feedforward neural network forecasting model building evaluation : theory and application in business forecasting." Thesis, Lancaster University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310532.

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23

Mitchell, I. G. "A connectionist model using topological representation of state space graphs for sequence recognition." Thesis, London Metropolitan University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287614.

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24

Wu, Ning. "Artificial intelligence solutions for models of dynamic land use change." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610781.

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25

Goel, Anuj. "Symbolic model checking techniques for BDD-based planning in distributed environments." Full text (PDF) from UMI/Dissertation Abstracts International, 2002. http://wwwlib.umi.com/cr/utexas/fullcit?p3077646.

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26

Turner, Roy Marvin. "A schema-based model of adaptive problem solving." Diss., Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/9156.

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27

MUSUMECI, MARIALESSIA. "ARTIFICIAL INTELLIGENCE APPLIED TO THE STUDY OF CONSCIOUS PERCEPTIVE STATES." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/607650.

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My PhD research consists of the processing of signals from a 14-electrode EEG system, connected to immersive glasses that allow for a realistic visual experience and for the investigation of the brain network in order to identify signal features corresponding to different perceptive and cognitive stimuli. The aim of the research is to implement a procedure that identifies correspondences among EEG signals and chaotic attractors. The chaotic attractors can be defined as a trajectory of a dynamical system, contained in a defined volume of phase space. A dynamical system can have chaotic beha

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28

Kim, Jun-Young. "ANN wave prediction model for winter storms and hurricanes." W&M ScholarWorks, 2003. https://scholarworks.wm.edu/etd/1539616716.

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Currently available wind-wave prediction models require a prohibitive amount of computing time for simulating non-linear wave-wave interactions. Moreover, some parts of wind-wave generation processes are not fully understood yet. For this reason accurate predictions are not always guaranteed. In contrast, Artificial Neural Network (ANN) techniques are designed to recognize the patterns between input and output so that they can save considerable computing time so that real-time wind-wave forecast can be available to the navy and commercial ships. For this reason, this study tries to use ANN tec

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29

Xu, Zhen. "Using Social Dynamics to Make Individual Predictions| Variational Inference with Stochastic Kinetic Model." Thesis, State University of New York at Buffalo, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10253123.

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<p> Social dynamics is concerned with the interactions of individuals and the resulting group behaviors. It models the temporal evolution of social systems via the interactions of the individuals within these systems. The availability of large-scale data in social networks and sensor networks offers an unprecedented opportunity to predict state changing events at the individual level. Examples of such events are disease infection, rumor propagation and opinion transition in elections, etc. Unlike previous research focusing on the collective effects of social systems, we want to make efficient

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30

Bhatta, Sambasiva R. "Model-based analogy in innovative device design." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/8136.

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31

Islam, Md Samsul, Lin Zhou, and Fei Li. "Application of Artificial Intelligence (Artificial Neural Network) to Assess Credit Risk : A Predictive Model For Credit Card Scoring." Thesis, Blekinge Tekniska Högskola, Sektionen för management, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2099.

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Credit Decisions are extremely vital for any type of financial institution because it can stimulate huge financial losses generated from defaulters. A number of banks use judgmental decisions, means credit analysts go through every application separately and other banks use credit scoring system or combination of both. Credit scoring system uses many types of statistical models. But recently, professionals started looking for alternative algorithms that can provide better accuracy regarding classification. Neural network can be a suitable alternative. It is apparent from the classification out

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32

Gill, Gurman. "Building a model for a 3D object classs in a low dimensional space for object detection." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=40739.

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Modeling 3D object classes requires accounting for intra-class variations in an object's appearance under different viewpoints, scale and illumination conditions. Therefore, detecting instances of 3D object classes in the presence of background clutter is difficult. This thesis presents a novel approach to model generic 3D object classes and an algorithm to detect multiple instances of an object class in an arbitrary image. Motivated by the parts-based representation, the proposed approach divides the object into different spatial regions. Each spatial region is associated with an object part

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33

Kalvakolanu, Anjaneya Teja Sarma. "Brain Tumor Detection and Classification from MRI Images." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2267.

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A brain tumor is detected and classified by biopsy that is conducted after the brain surgery. Advancement in technology and machine learning techniques could help radiologists in the diagnosis of tumors without any invasive measures. We utilized a deep learning-based approach to detect and classify the tumor into Meningioma, Glioma, Pituitary tumors. We used registration and segmentation-based skull stripping mechanism to remove the skull from the MRI images and the grab cut method to verify whether the skull stripped MRI masks retained the features of the tumor for accurate classification. In

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34

Lucouw, Alexander. "Distributed fault detection and diagnostics using artificial intelligence techniques / A. Lucouw." Thesis, North-West University, 2009. http://hdl.handle.net/10394/4110.

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With the advancement of automated control systems in the past few years, the focus has also been moved to safer, more reliable systems with less harmful effects on the environment. With increased job mobility, less experienced operators could cause more damage by incorrect identification and handling of plant faults, often causing faults to progress to failures. The development of an automated fault detection and diagnostic system can reduce the number of failures by assisting the operator in making correct decisions. By providing information such as fault type, fault severity, fault location

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35

Ja'bari, Nasser Wahid. "The viable system model (VSM) and organisation theory : a complementary approach to the case of a pharmaceutical manufacturer." Thesis, University of Hull, 1995. http://hydra.hull.ac.uk/resources/hull:3959.

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The primary purpose of this research is to explore the relationships between Beer's viable system model (VSM) and mainstream functionalist organisation theory.The latter is taken to include the classical, behavioural and systems models of organisation. For completeness, we also consider organisation theory situated in the interpretive, radical humanist and radical structuralist paradigms of Burrell and Morgan's (1979) sociological grid. Models of mainstream organisation theory have been used extensively by organisation theorists in the structuring of organisations and the design of information

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36

Middlemiss, Melanie Jane, and n/a. "Aspects of a computational model inspired by immunological principles." University of Otago. Department of Information Science, 2007. http://adt.otago.ac.nz./public/adt-NZDU20071220.150157.

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Nature and biological systems have provided the basis for many computational models and systems, such as neural computing and evolutionary computation. This thesis examines the vertebrate immune system which formed the original basis for Artificial Immune Systems (AIS). The vertebrate immune system is highly complex and, for the most part, is successful at providing us with protection from harmful stimuli. Such a system is attractive as a model to inspire a computational system as it exhibits many desirable behaviours: adaptability, diversity, robustness, efficiency and multiple layers of dete

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37

Dukkipati, Ambedkar. "ACE-Model: A Conceptual Evolutionary Model For Evolutionary Computation And Artificial Life." Thesis, Indian Institute of Science, 2002. https://etd.iisc.ac.in/handle/2005/3920.

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Darwinian Evolutionary system - a system satisfying the abstract conditions: reproduction with heritable variation, in a finite world, giving rise to Natural Selection encompasses a complex and subtle system of interrelated theories, whose substantive transplantation to any artificial medium let it be mathematical model or computational model - will be very far from easy. There are two motives in bringing Darwinian evolution into computational frameworks: one to understand the Darwinian evolution, and the other is to view Darwinian evolution - that carries out controlled adaptive-stochastic se

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38

Dukkipati, Ambedkar. "ACE-Model: A Conceptual Evolutionary Model For Evolutionary Computation And Artificial Life." Thesis, Indian Institute of Science, 2002. http://hdl.handle.net/2005/47.

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Darwinian Evolutionary system - a system satisfying the abstract conditions: reproduction with heritable variation, in a finite world, giving rise to Natural Selection encompasses a complex and subtle system of interrelated theories, whose substantive transplantation to any artificial medium let it be mathematical model or computational model - will be very far from easy. There are two motives in bringing Darwinian evolution into computational frameworks: one to understand the Darwinian evolution, and the other is to view Darwinian evolution - that carries out controlled adaptive-stochastic se

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39

Jones, Brian Edward. "A computer graphics based target detection model." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FJones_Brian.pdf.

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Thesis (M.S. in Modeling, Virtual Environments and Simulations)--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Christian J. Darken. "September 2006." Includes bibliographical references (p. 85). Also available in print.

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40

Shafer, Micheal E. "Traumatic Brain Injury in Children and Adolescents: An Evaluation of the WISC-III Four Factor Model and Individual Cluster Profiles." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc9033/.

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Traumatic brain injury (TBI) is the leading cause of death and disability among children and adolescents in the US. Children and adolescents who sustain moderate and severe head injuries are much more likely to evidence significant deficits in neuropsychological functioning when compared with children with mild head injuries. Information about the recovery process and functional sequelae associated with moderate and severe head injuries remains limited, despite clear indications that children who experience such injuries typically exhibit notable deficits in intellectual functioning, particula

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41

Frassineti, Lorenzo. "Development of multimodal systems for monitoring paediatric brain disorders." Doctoral thesis, Università di Siena, 2023. https://hdl.handle.net/11365/1227514.

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In the last years, artificial intelligence (AI) methods are extensively applied in several fields, including healthcare, with several applications to support diagnostic approaches or treatments. The research activities carried on during my PhD work have been devoted to the development of AI methods to support neonatologists and paediatric neurologists in the detection, characterization, and monitoring of brain disorders in paediatric subjects. Specifically, the PhD work was focused on the development of multimodal systems for: neonatal and absence seizure detection; quantitative characterizati

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42

Cha, Dea Ho. "Prediction of Wave-Induced Seabed Maximum Liquefaction Depth Using Artificial Neural Network Model." Thesis, Griffith University, 2010. http://hdl.handle.net/10072/367451.

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In the last few decades, considerable effort has been devoted to the phenomenon of wave-induced liquefaction. In deed, it is one of the most important factors used in analysing the seabed stability and in designing marine structures. As waves propagate and fluctuate over the ocean surface, energy is carried within the medium of the water particles. When this energy is transmitted into the seabed, the results are a rather complex mechanism of soil behaviours that significantly affect the stability of the seabed. The prediction of wave-induced seabed liquefaction has been recognised by coastal g

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O'Neill, Brian. "A computational model of suspense for the augmentation of intelligent story generation." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50416.

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In this dissertation, I present Dramatis, a computational human behavior model of suspense based on Gerrig and Bernardo's de nition of suspense. In this model, readers traverse a search space on behalf of the protagonist, searching for an escape from some oncoming negative outcome. As the quality or quantity of escapes available to the protagonist decreases, the level of suspense felt by the audience increases. The major components of Dramatis are a model of reader salience, used to determine what elements of the story are foregrounded in the reader's mind, and an algorithm for determining the

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44

Cohen, Sally M. "A model of troubleshooting in electronics assembly manufacturing." Thesis, Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/25803.

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Sayers, William Keith Paul. "Artificial intelligence techniques for flood risk management in urban environments." Thesis, University of Exeter, 2015. http://hdl.handle.net/10871/21030.

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Flooding is an important concern for the UK, as evidenced by the many extreme flooding events in the last decade. Improved flood risk intervention strategies are therefore highly desirable. The application of hydroinformatics tools, and optimisation algorithms in particular, which could provide guidance towards improved intervention strategies, is hindered by the necessity of performing flood modelling in the process of evaluating solutions. Flood modelling is a computationally demanding task; reducing its impact upon the optimisation process would therefore be a significant achievement and of

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Coon, William MacDowell. "A Computational Model for Building Relationships Between Humans and Virtual Agents." Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-theses/942.

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"As artificially intelligent agents become more advanced, they will require corresponding advances in social capability. In particular, they will require an understanding of the development of relationships. This work is intended to aid in addressing this need. We have developed a model of the development of relationships, designed and implemented a planning module based on this model, and performed an evaluation study verifying the functionality of the model and implementation. This should provide a foundation for future work in developing artificially intelligent agents capable of appropriat

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Clark, Matthew C. "Knowledge-Guided Processing of Magnetic Resonance Images of the Brain." Scholar Commons, 1998. http://purl.fcla.edu/fcla/etd/SFE0000001.

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Oliveira, Aline de. "Variáveis que influenciam o consumidor em relação ao uso dos chatbots." Master's thesis, Instituto Superior de Economia e Gestão, 2018. http://hdl.handle.net/10400.5/18164.

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Mestrado em Marketing<br>As empresas frequentemente buscam moldar a evolução das aplicações tecnológicas e estão cada vez mais utilizando chatbots e inteligência artificial para se comunicar com os clientes, resolver dúvidas, problemas de atendimento, procurar informações, comprar produtos e serviços, reservar hotéis, fazer perguntas às empresas, entre outros. Sendo assim, o objetivo desta pesquisa consiste em explorar diferentes variáveis externas e do Modelo TAM para ver se influenciam o consumidor em relação ao uso dos chatbots pelas empresas. Para coletar os dados quantitativos foi realiza

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Khader, Michael. "A fuzzy hierarchical decision model and its application in networking datacenters and in infrastructure acquisitions and design." ScholarWorks, 2009. https://scholarworks.waldenu.edu/dissertations/657.

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According to several studies, an inordinate number of major business decisions to acquire, design, plan, and implement networking infrastructures fail. A networking infrastructure is a collaborative group of telecommunications systems providing services needed for a firm's operations and business growth. The analytical hierarchy process (AHP) is a well established decision-making process used to analyze decisions related to networking infrastructures. AHP is concerned with decomposing complex decisions into a set of factors and solutions. However, AHP has difficulties in handling uncertainty i

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Shafer, Micheal E. Neumann Craig Stephen. "Traumatic brain injury in children and adolescents an evaluation of the WISC-III four factor model and individual cluster profiles /." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9033.

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