934 resultados para Symbolic and Algebraic Manipulation
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Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.
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Capacity analysis using simulation is not a new thing in literature. Most of the development process of UMTS standardization have used simulation tools; however, we thing that the use of GIS planning tools and matrix manipulation capacity of MATLAB can show us different scenarios and make a more realistic analysis. Some work is been doing in COST 273 in order to have more realistic scenarios for UMTS planning. Our work initially was centered in uplink analysis, but we are now working in downlink analysis, specifically in two areas: capacity in number of users for RT and NRT services, and Node B power. In this work we will show results for up-link capacity and some results for downlink capacity and BS power consumption.
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The current study examined the frequency and quality of how 3- to 4-year-old children and their parents explore the relations between symbolic and non-symbolic quantities in the context of a playful math experience, as well as the role of both parent and child factors in this exploration. Preschool children’s numerical knowledge was assessed while parents completed a survey about the number-related experiences they share with their children at home, and their math-related beliefs. Parent-child dyads were then videotaped playing a modified version of the card game War. Results suggest that parents and children explored quantity explicitly on only half of the cards and card pairs played, and dyads of young children and those with lower number knowledge tended to be most explicit in their quantity exploration. Dyads with older children, on the other hand, often completed their turns without discussing the numbers at all, likely because they were knowledgeable enough about numbers that they could move through the game with ease. However, when dyads did explore the quantities explicitly, they focused on identifying numbers symbolically, used non-symbolic card information interchangeably with symbolic information to make the quantity comparison judgments, and in some instances, emphasized the connection between the symbolic and non-symbolic number representations on the cards. Parents reported that math experiences such as card game play and quantity comparison occurred relatively infrequently at home compared to activities geared towards more foundational practice of number, such as counting out loud and naming numbers. However, parental beliefs were important in predicting both the frequency of at-home math engagement as well as the quality of these experiences. In particular, parents’ specific beliefs about their children’s abilities and interests were associated with the frequency of home math activities, while parents’ math-related ability beliefs and values along with children’s engagement in the card game were associated with the quality of dyads’ number exploration during the card game. Taken together, these findings suggest that card games can be an engaging context for parent-preschooler exploration of numbers in multiple representations, and suggests that parents’ beliefs and children’s level of engagement are important predictors of this exploration.
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In the context of computer numerical control (CNC) and computer aided manufacturing (CAM), the capabilities of programming languages such as symbolic and intuitive programming, program portability and geometrical portfolio have special importance -- They allow to save time and to avoid errors during part programming and permit code re-usage -- Our updated literature review indicates that the current state of art presents voids in parametric programming, program portability and programming flexibility -- In response to this situation, this article presents a compiler implementation for EGCL (Extended G-code Language), a new, enriched CNC programming language which allows the use of descriptive variable names, geometrical functions and flow-control statements (if-then-else, while) -- Our compiler produces low-level generic, elementary ISO-compliant Gcode, thus allowing for flexibility in the choice of the executing CNC machine and in portability -- Our results show that readable variable names and flow control statements allow a simplified and intuitive part programming and permit re-usage of the programs -- Future work includes allowing the programmer to define own functions in terms of EGCL, in contrast to the current status of having them as library built-in functions
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Let U be a domain in CN that is not a Runge domain. We study the topological and algebraic properties of the family of holomorphic functions on U which cannot be approximated by polynomials.
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The Ukraine crisis and Russia’s contribution to it have raised numerous concerns regarding the possible emergence of a new ‘Cold War’ in Europe. At the same time, Ukraine’s popular choice and enthusiasm for European integration expressed clearly on the streets of Kyiv seem to have caused Russia to adopt a (neo)revisionist attitude. In this context, relations between Russia and the EU (and the West for that matter) have been limited, frozen and directed on path towards conflict. This article analyses how the traditional dichotomy between conflict and cooperation in EU–Russia relations was replaced by conflict in the context of the Ukraine crisis. The article contends that the breakdown of the symbolic and peaceful cohabitation between the EU and Russia has been influenced by the fact that both actors have chosen to ignore key tensions that characterized their post-Cold War interactions. The article identifies three such tensions: the first emphasizes divisions between EU member states and their impact on coagulating a common EU approach towards Russia; the second (geopolitical) tension highlights the almost mutually exclusive way in which the EU and Russia’s security interests have developed in the post-Soviet space; finally, the third contends that a clash of values and worldviews between the EU and Russia makes conflict virtually unavoidable.
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This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach “hybrid”, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both “top-down” structured knowledge and “bottom-up” data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 — i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.
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In this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys- tem can be reified into actual software technology and extended towards many DS-related directions.
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The ability to create hybrid systems that blend different paradigms has now become a requirement for complex AI systems usually made of more than a component. In this way, it is possible to exploit the advantages of each paradigm and exploit the potential of different approaches such as symbolic and non-symbolic approaches. In particular, symbolic approaches are often exploited for their efficiency, effectiveness and ability to manage large amounts of data, while symbolic approaches are exploited to ensure aspects related to explainability, fairness, and trustworthiness in general. The thesis lies in this context, in particular in the design and development of symbolic technologies that can be easily integrated and interoperable with other AI technologies. 2P-Kt is a symbolic ecosystem developed for this purpose, it provides a logic-programming (LP) engine which can be easily extended and customized to deal with specific needs. The aim of this thesis is to extend 2P-Kt to support constraint logic programming (CLP) as one of the main paradigms for solving highly combinatorial problems given a declarative problem description and a general constraint-propagation engine. A real case study concerning school timetabling is described to show a practical usage of the CLP(FD) library implemented. Since CLP represents only a particular scenario for extending LP to domain-specific scenarios, in this thesis we present also a more general framework: Labelled Prolog, extending LP with labelled terms and in particular labelled variables. The designed framework shows how it is possible to frame all variations and extensions of LP under a single language reducing the huge amount of existing languages and libraries and focusing more on how to manage different domain needs using labels which can be associated with every kind of term. Mapping of CLP into Labeled Prolog is also discussed as well as the benefits of the provided approach.
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This paper discusses theoretical results of the research project Linguistic Identity and Identification: A Study of Functions of Second Language in Enunciating Subject Constitution. Non-cognitive factors that have a crucial incidence in the degree of success and ways of accomplishment of second language acquisition process are focused. A transdisciplinary perspective is adopted, mobilising categories from Discourse Analysis and Psychoanalysis. The most relevant ones are: discursive formation, intradiscourse, interdiscourse, forgetting n° 1, forgetting n° 2 (Pêcheux, 1982), identity, identification (Freud, 1966; Lacan, 1977; Nasio, 1995). Revuz s views (1991) are discussed. Her main claim is that during the process of learning a foreign language, the foundations of psychical structure, and consequently first language, are required. After examining how nomination and predication processes work in first and second languages, components of identity and identification processes are focused on, in an attempt to show how second language acquisition strategies depend on them. It is stated that methodological affairs of language teaching, learner s explicit motivation and the like are subordinated to the comprehension of deeper non-cognitive factors that determine the accomplishment of the second language acquisition process. It is also pointed out that those factors are to be approached, questioning the bipolar biological-social conception of subjectivity in the study of language acquisition and use and including in the analysis symbolic and significant dimensions of the discourse constitution process.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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The aim of this work was the development of miniaturized structures useful for retention and/or selection of particles and viscous substances from a liquid flow. The proposed low costs structures are similar to macroscopic wastewater treatment systems, named baffles, and allow disassemble. They were simulated using FEMLAB 3.2b package and manufactured in acrylic with conventional tools. Tests for retention or selection of particles in water or air and viscous fluids in water were carried out. Either in air or water particles with 50 mu m diameter will be retained but not with 13 mu m diameter. In aqueous flow, it is also possible the retention of viscous samples, such as silicone 350 cSt. The simulated results showed good agreement with experimental measurements. These miniaturized structures can be useful in sample pretreatment for chemical analysis and microorganism manipulation. (C) 2007 Elsevier B.V. All rights reserved.
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Methylobacterium mesophilicum, originally isolated as an endophytic bacterium from citrus plants, was genetically transformed to express green fluorescent protein (GFP). The GFP-labeled strain of M. mesophilicum was inoculated into Catharanthus roseus (model plant) seedlings and further observed colonizing its xylem vessels. The transmission of this endophyte by Bucephalogonia xanthophis, one of the insect vectors that transmit Xylella fastidiosa subsp. pauca, was verified by insects feeding from fluids containing the GFP bacterium followed by transmission to plants and isolating the endophyte from C. roseus plants. Forty-five days after inoculation, the plants exhibited endophytic colonization by M. mesophilicum, confirming this bacterium as a nonpathogenic, xylem-associated endophyte. Our data demonstrate that M. mesophilicum not only occupy the same niche of X. fastidiosa subsp. pauca inside plants but also may be transmitted by B. xanthophis. The transmission, colonization, and genetic manipulation of M. mesophilicum is a prerequisite to examining the potential use of symbiotic control to interrupt the transmission of X. fastidiosa subsp. pauca, the bacterial pathogen causing Citrus variegated chlorosis by insect vectors.
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Caloric intake reduction has been considered as the major experimental manipulation able to increase longevity in experimental models. Therefore, its effects upon cognition and mood like behavior are poorly explored. On the other hand, Li(+) is a re-emergent therapeutic drug used to treat mood disorders, mainly bipolar disorder, with antipanic and antidepressant actions. On the hypothesis that lithium treatment could attenuate the negatives effects of stress on Central Nervous Systems (CNS), we evaluated the role of chronic lithium treatment on anxiety-like behaviors in animals submitted to stress by chronic moderated feed restriction (FR). Male wistar rats were divided into four groups (n = 7-8/group) according to dietary and drug manipulation: ad libitum (AL) with unlimited access to standard rat diet, lithium treatment ( AL + Li) which received approximately 50 mg/Kg animal/day of LiCl solved in water and ad libitum diet, FR that were fed with equivalent to 70% of total rat diet consumed by AL group, and FR + Li which received diet corresponding to FR and Li administration. After 12 weeks of drug and FR manipulation, anxiety like behavior was evaluated in elevated plus mazes (EPM). Chronic lithium treatment prevent the anxiogenic like effect of FR ( open time, F(3,30) = 3.588; P = 0.0265; percentage of open entries, F(3,30) = 6.004; P= 0.00029; and open time at the first min, 2.35; F(3,30) = 4.937; P = 0.0073, Duncan test P < 0.05) compared to AL diet. Ours results adding to evidences that moderate feed restriction my increase anxiety-like behavior; also suggest that chronic lithium treatment may be attenuated this effects.
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During a naming task, time pressure and a manipulation of the proportion of related prime-target pairs were used to induce subjects to generate an expectation to the prime. On some trials, the presented target was orthographically and generally phonologically similar to the expected tal-get. The expectancy manipulation was barely detectable in the priming data but was clearly evident on a final recognition test. In addition, the recognition data showed that the nearly simultaneous activation of an expectation and sensory information derived from the orthographically and phonologically similar target produced a false memory. It is argued that this represents a blend memory.