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Dissertations / Theses on the topic 'Behavioral graph'
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1
Torbey, Elie. "Control/data flow graph synthesis using evolutionary computation and behavioral estimation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ37080.pdf.
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Torbey, Elie Carleton University Dissertation Engineering Electronics. "Control/data flow graph synthesis using evolutionary computation and behavioral estimation." Ottawa, 1999.
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Bodily, Ty Alvin. "A Graph Theoretical Analysis of Functional Brain Networks Related to Memory and Healthy Aging." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7567.
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The cognitive decline associated with healthy aging begins in early adulthood and is important to understand as a precursor of and relative to mild cognitive impairment and Alzheimer disease. Anatomical atrophy, functional compensation, and network reorganization have been observed in populations of older adults. In the current study, we examine functional network correlates of memory performance on the Wechsler Memory Scale IV and the Mnemonic Discrimination Task (MST). We report a lack of association between global graph theory metrics and age or memory performance. In addition, we observed a positive association between lure discrimination scores from the MST and right hippocampus centrality. Upon further investigation, we confirmed that old subjects with poor memory performance had lower right hippocampus centrality scores than young subjects with high average memory performance. These novel results connect the role of the hippocampus in global brain network information flow to cognitive function and have implications for better characterizing and predicting memory decline in aging.
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Mahamadi, Abdelrhman. "Bond Graph Models for Human Behavior." University of Akron / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1479485016074583.
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Janssen, Alisha L. "Physical Activity and Working Memory in Multiple Sclerosis: An Investigation of Neuropsychological and NeuroImaging Associations." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu149788064943423.
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Fleig, John David. "Citationally Enhanced Semantic Literature Based Discovery." Diss., NSUWorks, 2019. https://nsuworks.nova.edu/gscis_etd/1082.
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We are living within the age of information. The ever increasing flow of data and publications poses a monumental bottleneck to scientific progress as despite the amazing abilities of the human mind, it is woefully inadequate in processing such a vast quantity of multidimensional information. The small bits of flotsam and jetsam that we leverage belies the amount of useful information beneath the surface. It is imperative that automated tools exist to better search, retrieve, and summarize this content. Combinations of document indexing and search engines can quickly find you a document whose content best matches your query - if the information is all contained within a single document. But it doesn’t draw connections, make hypotheses, or find knowledge hidden across multiple documents. Literature-based discovery is an approach that can uncover hidden interrelationships between topics by extracting information from existing published scientific literature. The proposed study utilizes a semantic-based approach that builds a graph of related concepts between two user specified sets of topics using semantic predications. In addition, the study includes properties of bibliographically related documents and statistical properties of concepts to further enhance the quality of the proposed intermediate terms. Our results show an improvement in precision-recall when incorporating citations.
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MacKelvie, Erin. "A Comparison of Traditional Aggregated Data to a Comprehensive Second-by-Second Data Depiction in Functional Analysis Graphs." Scholarly Commons, 2021. https://scholarlycommons.pacific.edu/uop_etds/3730.
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Functional analyses (FAs) are an important component of treatment and the data gathered from FAs are often graphed in an aggregate or summary format, such as mean rate per session. Given the prevalence of undifferentiated analyses, it may be that this common method of data depiction is incomplete. In this paper, we compare the traditional aggregate method to a comprehensive second-by-second demonstration of the data including all appropriate and inappropriate responses emitted, as well as programmed and accidental antecedent and consequent variables, which may help further clarify the results of a functional analysis. We compared the functional analysis results of two participants when the data were depicted using the traditional rate aggregate method and depicted using a comprehensive second-by-second method. Although both rate and comprehensive second-by-second data depiction resulted in similar conclusions regarding the maintaining variables for the participants, comprehensive second-by-second data depiction allowed us to draw the conclusions in less time. Additional advantages and disadvantages of each method as it relates to efficiency, therapeutic risk and safety, and practicality are also discussed. Keywords: efficiency, functional analysis, problem behavior, safety, within-session second-by-second analysis.
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Heyman, Susanna. "Visualizing Financial Futures." Doctoral thesis, KTH, Medieteknik och interaktionsdesign, MID, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211657.
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Research on financial decision aids, systems designed to help people make financial decisions, is sparse. Previous research has often focused on the theoretical soundness of the advice that the systems provide.The original contribution of this doctoral thesis is a set of empirical studies of how non-expert people understand the advice provided by financial decision aids. Since every piece of advice must be interpreted by a receiver, the accuracy of the advice can be corrupted along the way if the receiver does not understand complicated terminology, probabilistic reasoning, or abstract concepts.The design concept resulting from the studies visualizes a unique combination of short-term and long-term variables that are usually treated as separate and not interacting with each other; loans and amortizations, insurance, retirement saving, and consumption. The aim is to visualize the consequences of different decisions and possible adverse events in terms of their effect on the user’s future consumption, rather than abstract numbers detached from the user’s lived experience.The design concept was tested and evaluated by personal finance experts and professional financial advisors, as well as students and people without financial education, who represented the target users of the system. Results indicate that the system has a learning curve, but that once users understand how to read the graph, they find it more informative than conventional financial planning tools.<br><p>QC 20170809</p>
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Varga, Adam. "Identifikace a charakterizace škodlivého chování v grafech chování." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442388.
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Za posledné roky je zaznamenaný nárast prác zahrňujúcich komplexnú detekciu malvéru. Pre potreby zachytenia správania je často vhodné pouziť formát grafov. To je prípad antivírusového programu Avast, ktorého behaviorálny štít deteguje škodlivé správanie a ukladá ich vo forme grafov. Keďže sa jedná o proprietárne riešenie a Avast antivirus pracuje s vlastnou sadou charakterizovaného správania bolo nutné navrhnúť vlastnú metódu detekcie, ktorá bude postavená nad týmito grafmi správania. Táto práca analyzuje grafy správania škodlivého softvéru zachytené behavioralnym štítom antivírusového programu Avast pre proces hlbšej detekcie škodlivého softvéru. Detekcia škodlivého správania sa začína analýzou a abstrakciou vzorcov z grafu správania. Izolované vzory môžu efektívnejšie identifikovať dynamicky sa meniaci malware. Grafy správania sú uložené v databáze grafov Neo4j a každý deň sú zachytené tisíce z nich. Cieľom tejto práce bolo navrhnúť algoritmus na identifikáciu správania škodlivého softvéru s dôrazom na rýchlosť skenovania a jasnosť identifikovaných vzorcov správania. Identifikácia škodlivého správania spočíva v nájdení najdôležitejších vlastností natrénovaných klasifikátorov a následnej extrakcie podgrafu pozostávajúceho iba z týchto dôležitých vlastností uzlov a vzťahov medzi nimi. Následne je navrhnuté pravidlo pre hodnotenie extrahovaného podgrafu. Diplomová práca prebehla v spolupráci so spoločnosťou Avast Software s.r.o.
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Kuhlman, Christopher James. "Generalizations of Threshold Graph Dynamical Systems." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/76765.
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Dynamics of social processes in populations, such as the spread of emotions, influence, language, mass movements, and warfare (often referred to individually and collectively as contagions), are increasingly studied because of their social, political, and economic impacts. Discrete dynamical systems (discrete in time and discrete in agent states) are often used to quantify contagion propagation in populations that are cast as graphs, where vertices represent agents and edges represent agent interactions. We refer to such formulations as graph dynamical systems. For social applications, threshold models are used extensively for agent state transition rules (i.e., for vertex functions). In its simplest form, each agent can be in one of two states (state 0 (1) means that an agent does not (does) possess a contagion), and an agent contracts a contagion if at least a threshold number of its distance-1 neighbors already possess it. The transition to state 0 is not permitted. In this study, we extend threshold models in three ways. First, we allow transitions to states 0 and 1, and we study the long-term dynamics of these bithreshold systems, wherein there are two distinct thresholds for each vertex; one governing each of the transitions to states 0 and 1. Second, we extend the model from a binary vertex state set to an arbitrary number r of states, and allow transitions between every pair of states. Third, we analyze a recent hierarchical model from the literature where inputs to vertex functions take into account subgraphs induced on the distance-1 neighbors of a vertex. We state, prove, and analyze conditions characterizing long-term dynamics of all of these models.<br>Master of Science
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Hu¨ttel, Hans. "Decidability, behavioural equivalences and infinite transition graphs." Thesis, University of Edinburgh, 1991. http://hdl.handle.net/1842/411.
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This thesis studies behavioural equivalences on labelled infinite transition graphs and the role that they can play in the context of modal logics and notions from language theory. A natural class of such infinite graphs is that corresponding to the SnS-definable tree languages first studied by Rabin. We show that a modal mu-calculus with label set {0,...,n - 1} can define these tree languages up to an observational equivalence. Another natural class of infinite transition graphs is that of normed BPA processes, which correspond to the graphs of leftmost derivations in context-free grammars without useless productions. A remarkable result is that strong bisimulation is decidable for these graphs. After an outline of the existing proofs due to Baeten et al. and Caucal we present a much simpler proof using a tableau system closely related to the branching algorithms employed in language theory following Korenjak and Hopcroft. We then present a result due to Colin Stirling, giving a weakly sound and complete sequent-based equational theory for bisimulation equivalence for normed BPA processes from the tableau system. Moreover, we show how to extract a fundamental relation (as in the work of Caucal) from a successful tableau. We then introduce silent actions and consider a class of normed BPA processes with the restriction that processes cannot terminate silently, showing that the decidability result for strong bisimilarity can be extended to van Glabbeek's branching bisimulation equivalence for this class of processes. We complete the picture by establishing that all other known behavioural equivalences and a number of preorders are undecidable for normed BPA processes.
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Ayala-Hoffmann, Jose. "Global behavior of graph dynamics with applications to Markov chains." [Ames, Iowa : Iowa State University], 2008.
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Streib, Kevin. "IMPROVED GRAPH-BASED CLUSTERING WITH APPLICATIONS IN COMPUTER VISION AND BEHAVIOR ANALYSIS." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1331063343.
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Saxton, Valerie Patricia. "Influence of ripening grape compounds on behavioural responses of birds." Phd thesis, Lincoln University. Agriculture and Life Sciences Division, 2004. http://theses.lincoln.ac.nz/public/adt-NZLIU20061207.121738/.
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Vineyards in New Zealand suffer bird damage caused by several avian species, including blackbirds and silvereyes. The introduced European Blackbird takes whole grapes which reduces yield. The self-introduced Australasian Silvereye pecks on grapes, leaving them on the vine to be further attacked by fungi and bacteria, and the subsequent off-odours can cause grapes to be refused by the winery or to suffer a price-reduction. Bird control methods remain primitive and largely ineffective during the long ripening period of wine grapes. An ecologically sound method to manage and reduce bird pressure requires deeper understanding of why some birds eat grapes, especially since grapes are not particularly nutritious.
This work investigated the extent to which blackbirds and silvereyes are attracted by various compounds in ripening grapes. Since in natural grapes these compounds develop and change simultaneously, I developed an artificial grape in which a single parameter could be investigated. Artificial grapes (and sometimes nectar) were presented on a bird feeder table and the responses of birds to hexose sugars, the aromas 2-3-isobutylmethoxypyrazine and geraniol, tartaric and malic acids, grape tannins, and purple and green colour were recorded on timelapse video and analysed.
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Saxton, V. P. "Influence of ripening grape compounds on behavioural responses of birds." Diss., Lincoln University, 2004. http://hdl.handle.net/10182/28.
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Vineyards in New Zealand suffer bird damage caused by several avian species, including blackbirds and silvereyes. The introduced European Blackbird takes whole grapes which reduces yield. The self-introduced Australasian Silvereye pecks on grapes, leaving them on the vine to be further attacked by fungi and bacteria, and the subsequent off-odours can cause grapes to be refused by the winery or to suffer a price-reduction. Bird control methods remain primitive and largely ineffective during the long ripening period of wine grapes. An ecologically sound method to manage and reduce bird pressure requires deeper understanding of why some birds eat grapes, especially since grapes are not particularly nutritious. This work investigated the extent to which blackbirds and silvereyes are attracted by various compounds in ripening grapes. Since in natural grapes these compounds develop and change simultaneously, I developed an artificial grape in which a single parameter could be investigated. Artificial grapes (and sometimes nectar) were presented on a bird feeder table and the responses of birds to hexose sugars, the aromas 2-3-isobutylmethoxypyrazine and geraniol, tartaric and malic acids, grape tannins, and purple and green colour were recorded on timelapse video and analysed.
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Hellmann, Jennifer K. "Neighbor Effects: The Influence of Colony-level Social Structure on Within-group Dynamics in a Social Fish." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1464129648.
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Tamersoy, Acar. "Graph-based algorithms and models for security, healthcare, and finance." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54986.
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Graphs (or networks) are now omnipresent, infusing into many aspects of society. This dissertation contributes unified graph-based algorithms and models to help solve large-scale societal problems affecting millions of individuals' daily lives, from cyber-attacks involving malware to tobacco and alcohol addiction. The main thrusts of our research are: (1) Propagation-based Graph Mining Algorithms: We develop graph mining algorithms to propagate information between the nodes to infer important details about the unknown nodes. We present three examples: AESOP (patented) unearths malware lurking in people's computers with 99.61% true positive rate at 0.01% false positive rate; our application of ADAGE on malware detection (patent-pending) enables to detect malware in a streaming setting; and EDOCS (patent-pending) flags comment spammers among 197 thousand users on a social media platform accurately and preemptively. (2) Graph-induced Behavior Characterization: We derive new insights and knowledge that characterize certain behavior from graphs using statistical and algorithmic techniques. We present two examples: a study on identifying attributes of smoking and drinking abstinence and relapse from an addiction cessation social media community; and an exploratory analysis of how company insiders trade. Our work has already made impact to society: deployed by Symantec, AESOP is protecting over 120 million people worldwide from malware; EDOCS has been deployed by Yahoo and it guards multiple online communities from comment spammers.
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Knight, Daniel William. "Reactor behavior and its relation to chemical reaction network structure." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1438274630.
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Rijal, Jhalendra P. "Environmental and behavioral factors associated with the infestation of vineyards by larvae of grape root borer." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/46871.
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Grape root borer, Vitacea polistiformis (Harris), is an oligophagous pest of grapevines in the eastern USA. Neonates must burrow into the soil to find grape roots. In Virginia, larvae feed on roots for ~2 years, then pupate just beneath the soil surface. Emerging adults leave an empty pupal exuviae at the soil surface around the vine base. There was no relationship between weekly captures in pheromone traps and pupal exuviae counts, indicating that exuviae sampling is most appropriate to assess infestations. Exuviae sampling in Virginia vineyards revealed infestations that ranged from light to very heavy. Eighteen biotic and abiotic variables were measured and used in analyses that assessed their relative contributions to differences in exuviae density. Water holding capacity and clay/sand ratio were most strongly associated with pupal exuviae density; these variables were used to develop a model for predicting the extent of infestation of individual vineyards. The spatial distribution of pupal exuviae was characterized using non-spatial and geospatial techniques. Although the non-spatial method (Taylor's Power Law) indicated that exuviae showed an aggregated distribution in all blocks, spatial methods (variograms, SADIE) revealed aggregated distributions only in blocks with ≥ 0.5 pupal exuviae per vine. Independent pupal exuviae samples for population assessment in vineyards can be achieved using sampling points separated by >8.8 m. Combined results from geospatial analyses and the temporal distribution of pupal exuviae within years enabled the development of a practical and quantitative sampling protocol. Bioassays used to measure the behavioral response of larvae to host stimuli revealed that neonates were attracted to grape root volatiles. In soil column bioassays, larvae moved vertically and horizontally over distances of up to 120 cm and apparently perceived the presence of grape roots from a distance of 5 cm in soil. Results are discussed in relation to their potential implications for monitoring and managing grape root borer.<br>Ph. D.
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Agharazi, Hanieh. "A Swarm Intelligent Approach To Condition Monitoring of Dynamic Systems." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1457024014.
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Suzuki, Reiji, Masanori Kato, and Takaya Arita. "Cyclic coevolution of cooperative behaviors and network structures." American Physical Society, 2008. http://hdl.handle.net/2237/11274.
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Butler, Steven Kay. "Bounding the Number of Graphs Containing Very Long Induced Paths." Diss., CLICK HERE for online access, 2003. http://contentdm.lib.byu.edu/ETD/image/etd158.pdf.
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Lancaster, Joseph Paul Jr. "Predicting the behavior of robotic swarms in discrete simulation." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/18980.
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Doctor of Philosophy<br>Department of Computing and Information Sciences<br>David Gustafson<br>We use probabilistic graphs to predict the location of swarms over 100 steps in simulations in grid worlds. One graph can be used to make predictions for worlds of different dimensions. The worlds are constructed from a single 5x5 square pattern, each square of which may be either unoccupied or occupied by an obstacle or a target. Simulated robots move through the worlds avoiding the obstacles and tagging the targets. The interactions between the robots and the robots and the environment lead to behavior that, even in deterministic simulations, can be difficult to anticipate. The graphs capture the local rate and direction of swarm movement through the pattern. The graphs are used to create a transition matrix, which along with an occupancy matrix, can be used to predict the occupancy in the patterns in the 100 steps using 100 matrix multiplications. In the future, the graphs could be used to predict the movement of physical swarms though patterned environments such as city blocks in applications such as disaster response search and rescue. The predictions could assist in the design and deployment of such swarms and help rule out undesirable behavior.
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Lorins, Peterson Marthen. "A Comparative Analysis Between Context-Based Reasoning (CxBR) and Contextual Graphs (CxGs)." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2302.
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Context-based Reasoning (CxBR) and Contextual Graphs (CxGs) involve the modeling of human behavior in autonomous and decision-support situations in which optimal human decision-making is of utmost importance. Both formalisms use the notion of contexts to allow the implementation of intelligent agents equipped with a context sensitive knowledge base. However, CxBR uses a set of discrete contexts, implying that models created using CxBR operate within one context at a given time interval. CxGs use a continuous context-based representation for a given problem-solving scenario for decision-support processes. Both formalisms use contexts dynamically by continuously changing between necessary contexts as needed in appropriate instances. This thesis identifies a synergy between these two formalisms by looking into their similarities and differences. It became clear during the research that each paradigm was designed with a very specific family of problems in mind. Thus, CXBR best implements models of autonomous agents in environment, while CxGs is best implemented in a decision support setting that requires the development of decision-making procedures. Cross applications were implemented on each and the results are discussed.<br>M.S.Cp.E.<br>Department of Electrical and Computer Engineering<br>Engineering and Computer Science<br>Computer Engineering
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Laouadi, Rabah. "Analyse du flot de contrôle multivariante : application à la détection de comportements des programmes." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTT255.
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Sans exécuter une application, est-il possible de prévoir quelle est la méthode cible d’un site d’appel ? Est-il possible de savoir quels sont les types et les valeurs qu’une expression peut contenir ? Est-il possible de déterminer de manière exhaustive l’ensemble de comportements qu’une application peut effectuer ? Dans les trois cas, la réponse est oui, à condition d’accepter une certaine approximation. Il existe une classe d’algorithmes − peu connus à l’extérieur du cercle académique − qui analysent et simulent un programme pour calculer de manière conservatrice l’ensemble des informations qui peuvent être véhiculées dans une expression.Dans cette thèse, nous présentons ces algorithmes appelés CFAs (acronyme de Control Flow Analysis), plus précisément l’algorithme multivariant k-l-CFA. Nous combinons l’algorithme k-l-CFA avec l’analyse de taches (taint analysis),qui consiste à suivre une donnée sensible dans le flot de contrôle, afin de déterminer si elle atteint un puits (un flot sortant du programme). Cet algorithme, en combinaison avec l’interprétation abstraite pour les valeurs, a pour objectif de calculer de manière aussi exhaustive que possible l’ensemble des comportements d’une application. L’un des problèmes de cette approche est le nombre élevé de faux-positifs, qui impose un post-traitement humain. Il est donc essentiel de pouvoir augmenter la précision de l’analyse en augmentant k.k-l-CFA est notoirement connu comme étant très combinatoire, sa complexité étant exponentielle dans la valeur de k. La première contribution de cette thèse est de concevoir un modèle et une implémentation la plus efficace possible, en séparant soigneusement les parties statiques et dynamiques de l’analyse, pour permettre le passage à l’échelle. La seconde contribution de cette thèse est de proposer une nouvelle variante de CFA basée sur k-l-CFA, et appelée *-CFA, qui consiste à faire du paramètre k une propriété de chaque variante, de façon à ne l’augmenter que dans les contextes qui le justifient.Afin d’évaluer l’efficacité de notre implémentation de k-l-CFA, nous avons effectué une comparaison avec le framework Wala. Ensuite, nous validons l’analyse de taches et la détection de comportements avec le Benchmark DroidBench. Enfin, nous présentons les apports de l’algorithme *-CFA par rapport aux algorithmes standards de CFA dans le contexte d’analyse de taches et de détection de comportements<br>Without executing an application, is it possible to predict the target method of a call site? Is it possible to know the types and values that an expression can contain? Is it possible to determine exhaustively the set of behaviors that an application can perform? In all three cases, the answer is yes, as long as a certain approximation is accepted.There is a class of algorithms - little known outside of academia - that can simulate and analyze a program to compute conservatively all information that can be conveyed in an expression. In this thesis, we present these algorithms called CFAs (Control flow analysis), and more specifically the multivariant k-l-CFA algorithm.We combine k-l-CFA algorithm with taint analysis, which consists in following tainted sensitive data inthe control flow to determine if it reaches a sink (an outgoing flow of the program).This combination with the integration of abstract interpretation for the values, aims to identify asexhaustively as possible all behaviors performed by an application.The problem with this approach is the high number of false positives, which requiresa human post-processing treatment.It is therefore essential to increase the accuracy of the analysis by increasing k.k-l-CFA is notoriously known as having a high combinatorial complexity, which is exponential commensurately with the value of k.The first contribution of this thesis is to design a model and most efficient implementationpossible, carefully separating the static and dynamic parts of the analysis, to allow scalability.The second contribution of this thesis is to propose a new CFA variant based on k-l-CFA algorithm -called *-CFA - , which consists in keeping locally for each variant the parameter k, and increasing this parameter in the contexts which justifies it.To evaluate the effectiveness of our implementation of k-l-CFA, we make a comparison with the Wala framework.Then, we do the same with the DroidBench benchmark to validate out taint analysis and behavior detection. Finally , we present the contributions of *-CFA algorithm compared to standard CFA algorithms in the context of taint analysis and behavior detection
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Manglani, Heena R. "A neural network analysis of sedentary behavior and information processing speed in multiple sclerosis." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu15253688510945.
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Vasseur, Baptiste. "Étude de problèmes différentiels elliptiques et paraboliques sur un graphe." Thesis, Littoral, 2014. http://www.theses.fr/2014DUNK0400/document.
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Après une présentation des notations usuelles de la théorie des graphes, on étudie l'ensemble des fonctions harmoniques sur les graphes, c'est à dire des fonctions dont le laplacien est nul. Ces fonctions forment un espace vectoriel et sur un graphe uniformément localement fini, on montre que cet espace vectoriel est soit de dimension un, soit de dimension infinie. Lorsque le graphe comporte une infinité de cycles, ce résultat tombe en défaut et on exhibe des exemples qui montrent qu'il existe un graphe sur lequel les harmoniques forment un espace vectoriel de dimension n, pour tout n. Un exemple de graphe périodique est également traité. Ensuite, toujours pour le laplacien, on étudie plus précisément sur les arbres uniformément localement finis les valeurs propres dont l'espace propre est de dimension infini. Dans ce cas, il est montré que l'espace propre contient un sous-espace isomorphe à l'ensemble des suites réelles bornées. Une inégalité concernant le spectre est donnée dans le cas spécial où les arêtes sont de longueur un. Des exemples montrent que ces inclusions sont optimales. Dans le chapitre suivant, on étudie le comportement asymptotique des valeurs propres pour des opérateurs elliptiques d'ordre 2 quelconques sous des conditions de Kirchhoff dynamiques. Après réécriture du problème sous la forme d'un opérateur de Sturm-Liouville, on écrit le problème de façon matricielle. Puis on trouve une équation caractéristique dont les zéros correspondent aux valeurs propres. On en déduit une formule pour l'asymptotique des valeurs propres. Dans le dernier chapitre, on étudie la stabilité de solutions stationnaires pour certains problèmes de réaction-diffusion où le terme de non linéarité est polynomial<br>After a quick presentation of usual notations for the graph theory, we study the set of harmonic functions on graphs, that is, the functions whose laplacian is zero. These functions form a vectorial space. On a uniformly locally finite tree, we shaw that this space has dimension one or infinity. When the graph has an infinite number of cycles, this result change and we describe some examples showing that there exists a graph on which the harmonic functions form a vectorial space of dimension n, for all n. We also treat the case of a particular periodic graph. Then, we study more precisely the eigenvalues of infinite dimension. In this case, the eigenspace contains a subspace isomorphic to the set of bounded sequences. An inequality concerning the spectral is given when edges length is equal to one. Examples show that these inclusions are optimal. We also study the asymptotic behavior of eigenvalues for elliptic operators under dynamical Kirchhoff node conditions. We write the problem as a Sturm-Liouville operator and we transform it in a matrix problem. Then we find a characteristic equation whose zeroes correspond to eigenvalues. We deduce a formula for the asymptotic behavior. In the last chapter, we study the stability of stationary solutions for some reaction-diffusion problem whose the non-linear term is polynomial
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Visockas, Vilius. "Comparing Expected and Real–Time Spotify Service Topology." Thesis, KTH, Kommunikationssystem, CoS, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-96352.
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Spotify is a music streaming service that allows users to listen to their favourite music. Due to the rapid growth in the number of users, the amount of processing that must be provided by the company’s data centers is also growing. This growth in the data centers is necessary, despite the fact that much of the music content is actually sourced by other users based on a peer-to-peer model. Spotify’s backend (the infrastructure that Spotify operates to provide their music streaming service) consists of a number of different services, such as track search, storage, and others. As this infrastructure grows, some service may behave not as expected. Therefore it is important not only for Spotify’s operations (footnote: Also known as the Service Reliability Engineers Team (SRE)) team, but also for developers, to understand exactly how the various services are actually communicating. The problem is challenging because of the scale of the backend network and its rate of growth. In addition, the company aims to grow and expects to expand both the number of users and the amount of content that is available. A steadily increasing feature-set and support of additional platforms adds to the complexity. Another major challenge is to create tools which are useful to the operations team by providing information in a readily comprehensible way and hopefully integrating these tools into their daily routine. The ultimate goal is to design, develop, implement, and evaluate a tool which would help the operations team (and developers) to understand the behavior of the services that are deployed on Spotify’s backend network. The most critical information is to alert the operations staff when services are not operating as expected. Because different services are deployed on different servers the communication between these services is reflected in the network communication between these servers. In order to understand how the services are behaving when there are potentially many thousands of servers we will look for the patterns in the topology of this communication, rather than looking at the individual servers. This thesis describes the tools that successfully extract these patterns in the topology and compares them to the expected behavior.<br>Spotify är en växande musikströmningstjänst som möjliggör för dess användare att lyssna på sin favoritmusik. Med ett snabbt växande användartal, följer en tillväxt i kapacitet som måste tillhandahållas genom deras datacenter. Denna växande kapacitet är nödvändig trots det faktum att mycket av deras innehåll hämtas från andra användare via en peer-to-peer modell. Spotifys backend (den infrastruktur som kör Spotifys tjänster) består av ett antal distinkta typer som tillhandahåller bl.a. sökning och lagring. I takt med att deras backend växer, ökar risken att tjänster missköter sig. Därför är det inte bara viktigt för Spotifys driftgrupp, utan även för deras utvecklare, att förstå hur dessa kommunicerar. Detta problem är en utmaning p.g.a. deras storskaliga infrastruktur, och blir större i takt med att den växer. Företaget strävar efter tillväxt och förväntar detta i både antalet användare och tillgängligt innehåll. Stadigt ökande funktioner och antalet distinkta plattformar bidrar till komplexitet. Ytterligare en utmaning är att bidra med verktyg som kan användas av driftgrupp för att tillhandahålla information i ett tillgängligt och överskådligt format, och att förhoppningsvis integrera dessa i en daglig arbetsrutin. Det slutgiltiga målet är att designa, utveckla, implementera och utvärdera ett verktyg som låter deras driftgrupp (och utvecklare) förstå beteenden i olika tjänster som finns i Spotifys infrastruktur. Då dessa tjänster är utplacerade på olika servrar, reflekteras kommunikationen mellan dem i deras nätverketskommunikation. För att förstå tjänsternas beteende när det potentiellt kan finnas tusentals servrar bör vi leta efter mönster i topologin, istället för beteenden på individuella servrar.
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Zhang, Don C. "Using Icon Array as a Visual Aid for Communicating Validity Information." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1459517352.
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Avelin, Benny. "Boundary Behavior of p-Laplace Type Equations." Doctoral thesis, Uppsala universitet, Analys och tillämpad matematik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-198008.
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This thesis consists of six scientific papers, an introduction and a summary. All six papers concern the boundary behavior of non-negative solutions to partial differential equations. Paper I concerns solutions to certain p-Laplace type operators with variable coefficients. Suppose that u is a non-negative solution that vanishes on a part Γ of an Ahlfors regular NTA-domain. We prove among other things that the gradient Du of u has non-tangential limits almost everywhere on the boundary piece Γ, and that log|Du| is a BMO function on the boundary. Furthermore, for Ahlfors regular NTA-domains that are uniformly (N,δ,r0)-approximable by Lipschitz graph domains we prove a boundary Harnack inequality provided that δ is small enough. Paper II concerns solutions to a p-Laplace type operator with lower order terms in δ-Reifenberg flat domains. We prove that the ratio of two non-negative solutions vanishing on a part of the boundary is Hölder continuous provided that δ is small enough. Furthermore we solve the Martin boundary problem provided δ is small enough. In Paper III we prove that the boundary type Riesz measure associated to an A-capacitary function in a Reifenberg flat domain with vanishing constant is asymptotically optimal doubling. Paper IV concerns the boundary behavior of solutions to certain parabolic equations of p-Laplace type in Lipschitz cylinders. Among other things, we prove an intrinsic Carleson type estimate for the degenerate case and a weak intrinsic Carleson type estimate in the singular supercritical case. In Paper V we are concerned with equations of p-Laplace type structured on Hörmander vector fields. We prove that the boundary type Riesz measure associated to a non-negative solution that vanishes on a part Γ of an X-NTA-domain, is doubling on Γ. Paper VI concerns a one-phase free boundary problem for linear elliptic equations of non-divergence type. Assume that we know that the positivity set is an NTA-domain and that the free boundary is a graph. Furthermore assume that our solution is monotone in the graph direction and that the coefficients of the equation are constant in the graph direction. We prove that the graph giving the free boundary is Lipschitz continuous.
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Luquette, Allana Duncan. "The effects of graphic display and training in visual inspection on teachers' detection of behavior change." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000584.
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Miller, Eric J. ""Effects of Grape Seed Extract, Lutein, and Omega-3 Fatty Acids on Lens Epithelial Cell Behavior In Vitro and Ex Vivo"." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397743093.
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Zareen, Farhath. "Detecting RTL Trojans Using Artificial Immune Systems and High Level Behavior Classification." Scholar Commons, 2019. https://scholarcommons.usf.edu/etd/7992.
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Security assurance in a computer system can be viewed as distinguishing between self and non-self. Artificial Immune Systems (AIS) are a class of machine learning (ML) techniques inspired by the behavior of innate biological immune systems, which have evolved to accurately classify self-behavior from non-self-behavior. This work aims to leverage AIS-based ML techniques for identifying certain behavioral traits in high level hardware descriptions, including unsafe or undesirable behaviors, whether such behavior exists due to human error during development or due to intentional, malicious circuit modifications, known as hardware Trojans, without the need fora golden reference model. We explore the use of Negative Selection and Clonal Selection Algorithms, which have historically been applied to malware detection on software binaries, to detect potentially unsafe or malicious behavior in hardware. We present a software tool which analyzes Trojan-inserted benchmarks, extracts their control and data-flow graphs (CDFGs), and uses this to train an AIS behavior model, against which new hardware descriptions may be tested.
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Kuhlman, Christopher J. "High Performance Computational Social Science Modeling of Networked Populations." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51175.
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Dynamics of social processes in populations, such as the spread of emotions, influence, opinions, and mass movements (often referred to individually and collectively as contagions), are increasingly studied because of their economic, social, and political impacts. Moreover, multiple contagions may interact and hence studying their simultaneous evolution is important. Within the context of social media, large datasets involving many tens of millions of people are leading to new insights into human behavior, and these datasets continue to grow in size. Through social media, contagions can readily cross national boundaries, as evidenced by the 2011 Arab Spring. These and other observations guide our work. Our goal is to study contagion processes at scale with an approach that permits intricate descriptions of interactions among members of a population. Our contributions are a modeling environment to perform these computations and a set of approaches to predict contagion spread size and to block the spread of contagions. Since we represent populations as networks, we also provide insights into network structure effects, and present and analyze a new model of contagion dynamics that represents a person\'s behavior in repeatedly joining and withdrawing from collective action. We study variants of problems for different classes of social contagions, including those known as simple and complex contagions.<br>Ph. D.
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Johnson, Thomas Alex. "Integrating models and simulations of continuous dynamic system behavior into SysML." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24768.
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Tan, Enhua. "Spam Analysis and Detection for User Generated Content in Online Social Networks." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365520334.
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El, Meligy Abdelhamid Sherif Hanie. "Providing High Performance Computing based Models as a Service: Architecture and Services for Modeling Contagions on Large Networked Populations." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/84456.
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Network science emerged as an interdisciplinary field over the last 20 years, and played a central role to address fundamental problems in other fields, e.g., epidemiology, public health, and transportation, and is now part of most university curriculums. Network dynamics is a major area within network science where researchers study different forms of processes in networked populations, such as the spread of emotions, influence, opinions, flu, ebola, and mass movements. These processes often referred to individually and collectively as contagions. Contagions are increasingly studied because of their economic, social, and political impacts. Yet, resources for studying network dynamics are largely dispersed and stand-alone. Furthermore, many researchers interested in the study of networks are not computer scientists. As a result, they do not have easy
access to computing and data resources. Even with the presence of software or tools, it is challenging to install, build, and maintain software. These challenges create a barrier for researchers and domain scientists. The goal of this work is the design and implementation of a research framework for modeling contagions on large networked populations. The framework consists of various systems and services that provide support for researchers and domain scientists at different stages of their research workflow.<br>Ph. D.
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Song, Hyunjin. "A Dynamic Longitudinal Examination of Social Networks and Political Behavior: The Moderating Effect of Local Network Properties and Its Implication for Social Influence Processes." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1427490761.
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Knight, Christopher J. "Hydrogen bond topology order/disorder transitions in ice and the behavior of defects in a disordered ice lattice /." Columbus, Ohio : Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1236788109.
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Siddiqui, Asher. "Capturing JUnit Behavior into Static Programs : Static Testing Framework." Thesis, Linnaeus University, School of Computer Science, Physics and Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-5510.
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<p>In this research paper, it evaluates the benefits achievable from static testing framework by analyzing and transforming the <em>JUnit3.8 </em>source code and static execution of transformed code. Static structure enables us to analyze the code statically during creation and execution of test cases. The concept of research is by now well established in static analysis and testing development. The research approach is also increasingly affecting the static testing process and such research oriented work has proved particularly valuable for those of us who want to understand the reflective behavior of <em>JUnit3.8 Framework</em>.</p><p><em> JUnit3.8 Framework</em> uses <em>Java Reflection API</em> to invoke core functionality (test cases creation and execution) dynamically. However, <em>Java Reflection API</em> allows developers to access and modify structure and behavior of a program. Reflection provides flexible solution for creating test cases and controlling the execution of test cases. Java reflection helps to encapsulate test cases in a single object representing the test suite. It also helps to associate each test method with a test object. Where reflection is a powerful tool to perform potential operations, on the other hand, it limits static analysis. Static analysis tools often cannot work effectively with reflection.</p><p>In order to avoid the reflection, <em>Static Testing Framework</em> provides a static platform to analyze the <em>JUnit3.8</em> source code and transform it into non-reflective version that emulates the dynamic behavior of <em>JUnit3.8</em>. The transformed source code has possible leverage to replace reflection with static code and does same things in an execution environment of <em>Static Testing Framework</em> that reflection does in <em>JUnit3.8</em>. More besides, the transformed code also enables execution environment of <em>Static Testing Framework</em> to run test methods statically. In order to measure the degree of efficiency, the implemented tool is evaluated. The evaluation of <em>Static Testing Framework</em> draws results for different Java projects and these statistical data is compared with <em>JUnit3.8</em> results to measure the effectiveness of <em>Static Testing Framework</em>. As a result of evaluation, <em>STF</em> can be used for static creation and execution of test cases up to <em>JUnit3.8</em> where test cases are not creating within a test class and where real definition of constructors is not required. These problems can be dealt as future work by introducing a middle layer to execute test fixtures for each test method and by generating test classes as per real definition of constructors.</p>
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Yonder, Erkan. "Pricing To Market: An Evaluation For Turkey." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608568/index.pdf.
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This thesis investigates pricing to market behavior in the exports of Turkey, which is a small economy. The investigated sectors are hazelnut, dried grape, dried apricot, dried fig and feldspar. The sectors are selected because Turkey is the leading producer and exporter for these products in the world. We apply pricing to market model for the exports from Turkey to each of the largest importer countries and the world in total for each product to check whether there is monopolistic behavior in the markets. We also check whether there is complete local currency price stability in the investigated markets. The relationship between the import shares of destination markets in the Turkey&<br>#8217<br>s exports and the estimated pricing to market elasticities are compared as well. In general, we find that there is pricing to market in the exports of Turkey for the investigated sectors.
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Costa, Wander Lairson. "Avanços no estudo de complexidade em linguagem regular de autômatos celulares elementares." Universidade Presbiteriana Mackenzie, 2013. http://tede.mackenzie.br/jspui/handle/tede/1431.
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Wander Lairson Costa.pdf: 1957133 bytes, checksum: 6819580d97bb5eaca5ea04352fcda0b8 (MD5)
Previous issue date: 2013-03-15<br>Universidade Presbiteriana Mackenzie<br>Cellular automata are totally discrete systems that act locally in a simple and deterministic way, but whose resulting global behavior can be extremely complex. The set of possible global configurations in one finite time step for a CA can be described by a regular language, which in turn can be represented by a finite automaton, more precisely the so-called process graph, in which all states are initial and final. Here, we study the temporal evolution complexity of the elementary cellular automata (i.e., one-dimensional, binary, with radius 1), and related previous works are revisited and discussed, indicating problems and their consequences. We also start up a novel approach for the problem, substituting the process graph based representation that describes the configuration at each time step by adjacency matrices derived from them. In fact, we extend the classical adjacency matrix notation, as they cannot fully represent process graphs. With this new notation, we show that it is possible to obtain the algorithm to generate a process graph
for an arbitrary finite time step for each of the rules at study. In conclusion, although advancing the limit graph problem, it still remains open, and we provide suggestions for further research.<br>Autômatos celulares são sistemas totalmente discretos que agem localmente de forma simples e determinística, mas cujo comportamento global resultante pode ser extremamente
complexo. O conjunto de possíveis configurações globais em um passo de tempo t finito para um autômato celular pode ser descrito por uma linguagem regular, a qual por sua vez pode ser representada por meio de um autômato finito, mais precisamente, pelo chamado grafo de processo, em que todos os estados são iniciais e finais. Estuda-se aqui a complexidade da evolução temporal dos autômatos celulares elementares (i.e., unidimensionais, binários, de raio 1), e trabalhos anteriores são revisitados e discutidos, no quais apontam-se problemas e suas consequências. Também inicia-se uma nova abordagem para o problema, substituindo a representação dos grafos de processo que descrevem a configuração a cada passo de tempo por matrizes de adjacência deles derivadas. De fato, estende-se a notação clássica de matriz de adjacência, já que ela se mostra insuficiente para descrever completamente os grafos de processo em questão. Com essa nova notação, mostra-se que é possível obter o algoritmo que gere o grafo de processo de tempo t para cada uma das regras estudadas. Conclui-se que, embora houve avanços para o problema do grafo limite, este ainda permanece aberto, e sugestões para continuação da pesquisa são dadas.
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Todeschini, Adrien. "Probabilistic and Bayesian nonparametric approaches for recommender systems and networks." Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0237/document.
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Nous proposons deux nouvelles approches pour les systèmes de recommandation et les réseaux. Dans la première partie, nous donnons d’abord un aperçu sur les systèmes de recommandation avant de nous concentrer sur les approches de rang faible pour la complétion de matrice. En nous appuyant sur une approche probabiliste, nous proposons de nouvelles fonctions de pénalité sur les valeurs singulières de la matrice de rang faible. En exploitant une représentation de modèle de mélange de cette pénalité, nous montrons qu’un ensemble de variables latentes convenablement choisi permet de développer un algorithme espérance-maximisation afin d’obtenir un maximum a posteriori de la matrice de rang faible complétée. L’algorithme résultant est un algorithme à seuillage doux itératif qui adapte de manière itérative les coefficients de réduction associés aux valeurs singulières. L’algorithme est simple à mettre en œuvre et peut s’adapter à de grandes matrices. Nous fournissons des comparaisons numériques entre notre approche et de récentes alternatives montrant l’intérêt de l’approche proposée pour la complétion de matrice à rang faible. Dans la deuxième partie, nous présentons d’abord quelques prérequis sur l’approche bayésienne non paramétrique et en particulier sur les mesures complètement aléatoires et leur extension multivariée, les mesures complètement aléatoires composées. Nous proposons ensuite un nouveau modèle statistique pour les réseaux creux qui se structurent en communautés avec chevauchement. Le modèle est basé sur la représentation du graphe comme un processus ponctuel échangeable, et généralise naturellement des modèles probabilistes existants à structure en blocs avec chevauchement au régime creux. Notre construction s’appuie sur des vecteurs de mesures complètement aléatoires, et possède des paramètres interprétables, chaque nœud étant associé un vecteur représentant son niveau d’affiliation à certaines communautés latentes. Nous développons des méthodes pour simuler cette classe de graphes aléatoires, ainsi que pour effectuer l’inférence a posteriori. Nous montrons que l’approche proposée peut récupérer une structure interprétable à partir de deux réseaux du monde réel et peut gérer des graphes avec des milliers de nœuds et des dizaines de milliers de connections<br>We propose two novel approaches for recommender systems and networks. In the first part, we first give an overview of recommender systems and concentrate on the low-rank approaches for matrix completion. Building on a probabilistic approach, we propose novel penalty functions on the singular values of the low-rank matrix. By exploiting a mixture model representation of this penalty, we show that a suitably chosen set of latent variables enables to derive an expectation-maximization algorithm to obtain a maximum a posteriori estimate of the completed low-rank matrix. The resulting algorithm is an iterative soft-thresholded algorithm which iteratively adapts the shrinkage coefficients associated to the singular values. The algorithm is simple to implement and can scale to large matrices. We provide numerical comparisons between our approach and recent alternatives showing the interest of the proposed approach for low-rank matrix completion. In the second part, we first introduce some background on Bayesian nonparametrics and in particular on completely random measures (CRMs) and their multivariate extension, the compound CRMs. We then propose a novel statistical model for sparse networks with overlapping community structure. The model is based on representing the graph as an exchangeable point process, and naturally generalizes existing probabilistic models with overlapping block-structure to the sparse regime. Our construction builds on vectors of CRMs, and has interpretable parameters, each node being assigned a vector representing its level of affiliation to some latent communities. We develop methods for simulating this class of random graphs, as well as to perform posterior inference. We show that the proposed approach can recover interpretable structure from two real-world networks and can handle graphs with thousands of nodes and tens of thousands of edges
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Hart, M. J. Alexandra. "Action in Chronic Fatigue Syndrome: an Enactive Psycho-phenomenological and Semiotic Analysis of Thirty New Zealand Women's Experiences of Suffering and Recovery." Thesis, University of Canterbury. Social and Political Sciences, 2010. http://hdl.handle.net/10092/5294.
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This research into Chronic Fatigue Syndrome (CFS) presents the results of 60 first-person psycho-phenomenological interviews with 30 New Zealand women. The participants were recruited from the Canterbury and Wellington regions, 10 had recovered. Taking a non-dual, non-reductive embodied approach, the phenomenological data was analysed semiotically, using a graph-theoretical cluster analysis to elucidate the large number of resulting categories, and interpreted through the enactive approach to cognitive science.
The initial result of the analysis is a comprehensive exploration of the experience of CFS which develops subject-specific categories of experience and explores the relation of the illness to universal categories of experience, including self, ‘energy’, action, and being-able-to-do.
Transformations of the self surrounding being-able-to-do and not-being-able-to-do were shown to elucidate the illness process.
It is proposed that the concept ‘energy’ in the participants’ discourse is equivalent to the Mahayana Buddhist concept of ‘contact’. This characterises CFS as a breakdown of contact. Narrative content from the recovered interviewees reflects a reestablishment of contact.
The hypothesis that CFS is a disorder of action is investigated in detail.
A general model for the phenomenology and functional architecture of action is proposed. This model is a recursive loop involving felt meaning, contact, action, and perception and appears to be phenomenologically supported.
It is proposed that the CFS illness process is a dynamical decompensation of the subject’s action loop caused by a breakdown in the process of contact.
On this basis, a new interpretation of neurological findings in relation to CFS becomes possible. A neurological phenomenon that correlates with the illness and involves a brain region that has a similar structure to the action model’s recursive loop is identified in previous research results and compared with the action model and the results of this research. This correspondence may identify the brain regions involved in the illness process, which may provide an objective diagnostic test for the condition and approaches to treatment.
The implications of this model for cognitive science and CFS should be investigated through neurophenomenological research since the model stands to shed considerable light on the nature of consciousness, contact and agency.
Phenomenologically based treatments are proposed, along with suggestions for future research on CFS. The research may clarify the diagnostic criteria for CFS and guide management and treatment programmes, particularly multidimensional and interdisciplinary approaches.
Category theory is proposed as a foundation for a mathematisation of phenomenology.
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Rangel, Guilherme [Verfasser]. "Behavioral congruences and verification of graph transformation systems with applications to model refactoring / vorgelegt von Guilherme Salum Rangel." 2008. http://d-nb.info/991732073/34.
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Hsu, Chun-Hsien, and 許峻舷. "Behaviors of the Colin de Verdière graph invariant under some graph operations." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/xn9q7y.
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Lee, Fong-Ruei, and 李豐瑞. "Graph-Based Behavior Analysis for User Verification." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/09716758079271523860.
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碩士<br>國立臺灣科技大學<br>資訊工程系<br>98<br>Part of our lives exist in an electronic community. Many of our
activities rely on web services like searching for coffee shops, paying money
to banks, even scheduling our daily activities. Many of the services need a
veri cation process to confirm our identity and user privilege. In network,
unlawful users may issue attacks to steal information through the Internet.
The verification step can help us to distinguish between the lawful users
and intruders. In a host, user without enough privilege may gain access
to data they are not supposed to see. We propose a mechanism to allow
automatic verification given nothing but user computer usage profile.
We discuss two types of computer usages: network usage and host
usage. The proposed method can monitor the network or host data for
user profiling and to decide the user identity. In network environment,
the user may use web to obtain valuable information. To avoid network
attacks, we usually adopt Intrusion detection systems (IDS) to enhance
network security. More specifically, given alert sequences generated by
IDS, we would like to spot the subsequences with malicious behavior. The
challenge in this case is to filter out the false alarms in the alert sequences.
In a host, users may run processes for their tasks like compiling Java codes,
surfing the web, or playing online games. In this case, the input is process
sequence and our goal is to distinguish user identities with different user
profiles.
The input like alert sequences or process sequences is one kind of
sequential data. Different from other sequential data, to deal with the
network or host sequential data, we may encounter some difficulties. The
subsequences generated from different users with different intentions may
interleave with each other. Also, the data may be noisy so that the typical
user profile is hard to describe. Here, we propose an approach for verification
based on the behaviors extracted from the event sequence like alert
sequence or process sequence.
We use graph to describe a subsequence with certain intention. The
graph is built by a Markov Chain model with sliding window to describe
the behavior from the sequence. To distinguish between two behaviors, we
propose a graph-based dissimilarity measure. Finally, we use the manifold
learning to represent the behaviors and to detect the malicious behavior or
the unauthorized access. The experiment results show that the proposed
method can reach high detection accuracy while maintaining low false
positives.
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Rose, Daniel John. "Asymptotic behavior of combinatorial optimization and proximity graphs on random point sets /." Diss., 2000. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:9982856.
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SHAN-YUNTENG and 鄧善云. "Learning Spatial-Temporal User Behaviors with Symbolic Graphs." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/e23ujd.
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博士<br>國立成功大學<br>資訊工程學系<br>107<br>Recently, interesting user behaviors have been found in different fields. Therefore, many research focuses on understanding user behaviors, needs, and motivations through observation techniques, data analysis, and machine learning methodologies. By learning different user behaviors, the prediction of user behaviors can lead to applications for indispensable services such as trajectory patterns mining, social links prediction, and personalized recommender systems. Due to the high penetration rate of cost-effective mobile devices, it becomes possible to continuously collect user behavior records with temporal and spatial information. As such, many spatial-temporal learning methodologies have been proposed to figure out the hidden information of user behaviors with the spatial or temporal sense. In my dissertation, we attempt to learn spatial-temporal user behaviors which are left unexplored thus far in different scenarios such as indoor spaces, social networks, and E-learning systems. More specifically, we investigated the following three kinds of user behaviors, spatial-temporal stop-by behaviors in indoor spaces, temporal worship behaviors in celebrity-dived networks, and temporal rating behaviors in E-learning systems.
Learning Spatial-Temporal Stop-by Behaviors with Uncertain Symbolic Graphs in Indoor Spaces:
In this work, we explore a new mining paradigm, called Indoor Stop-by Patterns (ISP), to discover user stop-by behavior in mall-like indoor environments. The discovery of ISPs enables new marketing collaborations, such as a joint coupon promotion, among stores in indoor spaces (e.g., shopping malls). Moreover, it can also help in eliminating the overcrowding situation. To pursue better practicability, we consider the cost-effective wireless sensor-based environment and conduct the analysis of indoor stop-by behaviors on real data. The proposed Probabilistic Top-k Indoor Stop-by Patterns Discovery (PTkISP) framework incorporates the probabilistic model to identify top-k ISPs over uncertain data collected from sensing logs. Moreover, we develop an uncertain symbolic model and devise an Index 1-itemset (IIS) algorithm to enhance the accuracy and efficiency. Our experimental studies on one synthetic data and one real data show that the proposed PTkISP framework can efficiently discover high-quality ISPs and can provide insightful observations for marketing collaborations.
Learning Temporal Worship Behaviors with Heterogeneous Symbolic Graph in Celebrity-Dived Networks:
We in this work explore a new link prediction paradigm, called ‘worship’ prediction, to discover worship links between users and celebrities on celebrity-dived networks. The prediction of ‘worship’ links enables valuable social services, such as viral marketing, popularity estimation, and celebrity recommendation. However, as the concern of business security and personal privacy, only public-accessible statistical social properties, instead of the detailed information of users, can be utilized to predict the ‘worship’ labels.
To address these issues, a novel learning framework is devised, including a heterogeneous factor graph with new discovered statistical properties and a Gaussian estimation based learning algorithm with active learning. Our experimental studies on real data, including Instagram, Twitter, and DBLP, show that the proposed learning framework can overcome the problem of missing labels and efficiently discover worship links.
Learning Temporal Rating Behaviors with Dependent Symbolic Graphs in E-Learning Systems:
In this work, we address an important issue on the exploration of user rating behaviors from an interactive question-answering process in E-learning systems. A novel interactive learning system, called CagMab, is devised to interactively recommend questions with a round-by-round strategy, which contributes to applications such as a conversational bot for self-evaluation. The flow enables users to discover their weakness and further helps them to progress. Even though formulating the problem with the multi-armed bandit framework provides a solution, it often leads to suboptimal results for interactive unknowns recommendation as it simply relies on the contextual features of answered questions. To address this issue, we develop a novel interactive learning framework by borrowing strengths from the dependency of concept-aware graphs for learning user ratings. Our experimental studies on real data show that the proposed framework can effectively predict user ratings in an interactive fashion for the recommendation in E-learning systems.
In summary, we in my dissertation focus on learning spatial-temporal user behaviors with symbolic graphs in indoor spaces, social networks, and E-learning systems. The experimental results of learning the proposed user behaviors show that incorporating symbolic graphs with machine learning algorithms can significantly improve the accuracy performances.
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Agarwal, Manish. "Viewing Behavior Model Graphs (VBMG) for characterizing user viewing behavior in program visualizations." 2007. http://purl.galileo.usg.edu/uga%5Fetd/agarwal%5Fmanish%5F%5F200705%5Fms.
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