871 resultados para Agent based moduling stimulation


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In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

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Based on provious (Hemelrijk 1998; Puga-González, Hildenbrant & Hemelrijk 2009), we have developed an agent-based model and software, called A-KinGDom, which allows us to simulate the emergence of the social structure in a group of non-human primates. The model includes dominance and affiliative interactions and incorporate s two main innovations (preliminary dominance interactions and a kinship factor), which allow us to define four different attack and affiliative strategies. In accordance with these strategies, we compared the data obtained under four simulation conditions with the results obtained in a provious study (Dolado & Beltran 2012) involving empirical observations of a captive group of mangabeys (Cercocebus torquatus)

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One of the classic research topics in adaptive behavior is the collective displacement of groups of organisms such as flocks of birds, schools of fish, herds of mammals and crowds of people. However, most agent-based simulations of group behavior do not provide a quantitative index for determining the point at which the flock emerges. We have developed an index of the aggregation of moving individuals in a flock and have provided an example of how it can be used to quantify the degree to which a group of moving individuals actually forms a flock.

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Statistical properties of binary complex networks are well understood and recently many attempts have been made to extend this knowledge to weighted ones. There are, however, subtle yet important considerations to be made regarding the nature of the weights used in this generalization. Weights can be either continuous or discrete magnitudes, and in the latter case, they can additionally have undistinguishable or distinguishable nature. This fact has not been addressed in the literature insofar and has deep implications on the network statistics. In this work we face this problem introducing multiedge networks as graphs where multiple (distinguishable) connections between nodes are considered. We develop a statistical mechanics framework where it is possible to get information about the most relevant observables given a large spectrum of linear and nonlinear constraints including those depending both on the number of multiedges per link and their binary projection. The latter case is particularly interesting as we show that binary projections can be understood from multiedge processes. The implications of these results are important as many real-agent-based problems mapped onto graphs require this treatment for a proper characterization of their collective behavior.

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Antibodies play an important role in therapy and investigative biomedical research. The TNF-family member Receptor Activator of NF-κB (RANK) is known for its role in bone homeostasis and is increasingly recognized as a central player in immune regulation and epithelial cell activation. However, the study of RANK biology has been hampered by missing or insufficient characterization of high affinity tools that recognize RANK. Here, we present a careful description and comparison of two antibodies, RANK-02 obtained by phage display (Newa, 2014 [1]) and R12-31 generated by immunization (Kamijo, 2006 [2]). We found that both antibodies recognized mouse RANK with high affinity, while RANK-02 and R12-31 recognized human RANK with high and lower affinities, respectively. Using a cell apoptosis assay based on stimulation of a RANK:Fas fusion protein, and a cellular NF-κB signaling assay, we showed that R12-31 was agonist for both species. R12-31 interfered little or not at all with the binding of RANKL to RANK, in contrast to RANK-02 that efficiently prevented this interaction. Depending on the assay and species, RANK-02 was either a weak agonist or a partial antagonist of RANK. Both antibodies recognized human Langerhans cells, previously shown to express RANK, while dermal dendritic cells were poorly labeled. In vivo R12-31 agonist activity was demonstrated by its ability to induce the formation of intestinal villous microfold cells in mice. This characterization of two monoclonal antibodies should now allow better evaluation of their application as therapeutic reagents and investigative tools.

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Recent studies have demonstrated that the use of paramagnetic hepatobiliary contrast agents in the acquisition of magnetic resonance images remarkably improves the detection and differentiation of focal liver lesions, as compared with extracellular contrast agents. Paramagnetic hepatobiliary contrast agents initially show the perfusion of the lesions, as do extracellular agents, but delayed contrast-enhanced images can demonstrate contrast uptake by functional hepatocytes, providing further information for a better characterization of the lesions. Additionally, this intrinsic characteristic increases the accuracy in the detection of hepatocellular carcinomas and metastases, particularly the small-sized ones. Recently, a hepatobiliary contrast agent called gadolinium ethoxybenzyl dimeglumine, that is simply known as gadoxetic acid, was approved by the National Health Surveillance Agency for use in humans. The authors present a literature review and a practical approach of magnetic resonance imaging utilizing gadoxetic acid as contrast agent, based on patients' images acquired during their initial experiment.

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Plants constitute an excellent ecosystem for microorganisms. The environmental conditions offered differ considerably between the highly variable aerial plant part and the more stable root system. Microbes interact with plant tissues and cells with different degrees of dependence. The most interesting from the microbial ecology point of view, however, are specific interactions developed by plant-beneficial (either non-symbiotic or symbiotic) and pathogenic microorganisms. Plants, like humans and other animals, also become sick, but they have evolved a sophisticated defense response against microbes, based on a combination of constitutive and inducible responses which can be localized or spread throughout plant organs and tissues. The response is mediated by several messenger molecules that activate pathogen-responsive genes coding for enzymes or antimicrobial compounds, and produces less sophisticated and specific compounds than immunoglobulins in animals. However, the response specifically detects intracellularly a type of protein of the pathogen based on a gene-for-gene interaction recognition system, triggering a biochemical attack and programmed cell death. Several implications for the management of plant diseases are derived from knowledge of the basis of the specificity of plant-bacteria interactions. New biotechnological products are currently being developed based on stimulation of the plant defense response, and on the use of plant-beneficial bacteria for biological control of plant diseases (biopesticides) and for plant growth promotion (biofertilizers)

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Työssä esitellään käytetyimpiä tuotantofilosofioita. Tuotantofilosofia on hyvin laaja käsite ja sen vuoksi myös jotkin esiteltävistä menetelmistä ovat hyvin kaukana toisistaan. Työ koostuu teoriaosiosta, jossa on esitelty kukin tuotantofilosofia ja lopuksi johtopäätöksiä-osiossa käsitellään sitä, kuinka menetelmät liittyvät toisiinsa. Työssä esitellään JIT/JOT-tuotanto, Lean-tuotanto, Monozukuri, Modulointi, Standardointi, Strategiatyö, Six Sigma, TQM, TPM, QFD, MFD, Simulointi, Digitaalinen valmistus, DFX ja ns. uudet tuotantofilosofiat. Eri menetelmistä löytyvää lähdemateriaalia on tarjolla monipuolisesti, josta johtuen menetelmistä on voitu esitellä vain pääpiirteet. Tuotantofilosofioiden avulla voidaan saavuttaa monia eri asioita. Osa menetelmistä on luotu tuotannon tehostamiseksi ja yksinkertaistamiseksi, osa puolestaan lisää tuotannon tai koko yrityksen laatutasoa ja osa puolestaan helpottaa tuotteiden suunnittelu-työtä. Moni esiteltävistä filosofioista ei istu yksinomaan yhteen edellä mainituista kategorioista vaan kattaa laajempia alueita pitäen sisällään jopa kaikkia kolmea mainittua tulosta. Näiden lisäksi työssä on esitelty lyhyesti uusia tuotantofilosofioita, jotka ovat hieman irrallisia kokonaisuuksia verrattuna muihin työssä esiteltäviin filosofioihin. Työn tarkoituksena on auttaa hahmottamaan suurta kokonaisuutta jonka tuotantofilosofiat tuottavat. On tärkeää osata hahmottaa filosofioiden riippuvuus toisistaan ja se, että otettaessa käyttöön jotain tuotantofilosofiaa, tarkoittaa se myös mahdollisesti monen muunkin asian huomioonottamista. Tätä näkökantaa selvennetään johtopäätöksissä.

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Due to the different dynamics required for organizations to serve the emerging market which contains billions of people at the bottom of the pyramid (BOP) coupled with the increasing desire for organizations to grow and be more multinational, organizations need to continually innovate. However, the tendency for large and established companies to ignore the BOP market and rather focus on existing markets, gives an indication of the existence of a vulnerability that potentially disruptive innovations from the BOP will not be recognized in good time for a counter measure. This can be deduced from the fact that good management practice advocates that managers should learn and listen to their customers. Therefore majority of the large existing companies continually focus on their main customer/market with sustaining innovations which leaves aspiring new entrants with an underserved BOP market to experiment with. With the aid of research interviews and an agent-based model (ABM) simulation, this thesis examines the attributes of BOP innovations that can qualify them as disruptive and the possibilities of tangible disruptive innovations arising from the bottom of the pyramid and their underlying drivers. The thesis Furthermore, examines the associated impact of such innovations on the future sustainability of established large companies that are operating in the developed world, particularly those with a primary focus which is targeted towards the market at the top of the pyramid (TOP). Additionally, with the use of a scenario planning model, the research provides an evaluation of the possible evolution and potential sustainability impacts that could emerge, from the interplay of innovations at the two pyramidal market levels and the chosen market focus of organizations – TOP or BOP. Using four scenario quadrants, the thesis demonstrates the resulting possibilities from the interaction between the rate of innovations and the segment focused on by organizations with disruptive era characterizing the paradigm shift quadrant. Furthermore, a mathematical model and two theoretical propositions are developed for further research. As recommendations, the thesis also extends the ambidextrous organizational theory, business model innovation and portfolio diversification as plausible recommendations to limit a catastrophic impact, resulting from disruptive innovations.

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Operating in business-to-business markets requires an in-depth understanding on business networks. Actions and reactions made to compete in markets are fundamentally based on managers‘ subjective perceptions of the network. However, an amalgamation of these individual perceptions, termed a network picture, to a common company level shared understanding on that network, known as network insight, is found to be a substantial challenge for companies. A company‘s capability to enhance common network insight is even argued to lead competitive advantage. Especially companies with value creating logics that require wide comprehension of and collaborating in networks, such as solution business, are necessitated to develop advanced network insight. According to the extant literature, dispersed pieces of atomized network pictures can be unified to a common network insight through a process of amalgamation that comprises barriers/drivers of multilateral exchange, manifold rationality, and recursive time. However, the extant body of literature appears to lack an understanding on the role of internal communication in the development of network insight. Nonetheless, the extant understanding on the amalgamation process indicates that internal communication plays a substantial role in the development of company level network insight. The purpose of the present thesis is to enhance understanding on internal communication in the amalgamation of network pictures to develop network insight in the solution business setting, which was chosen to represent business-to-business value creating logic that emphasizes the capability to understand and utilize networks. Thus, in solution business the role of succeeding in the amalgamation process is expected to emphasize. The study combines qualitative and quantitative research by means of various analytical methods including multiple case analysis, simulation, and social network analysis. Approaching the nascent research topic with differing perspectives and means provides a broader insight on the phenomenon. The study provides empirical evidence from Finnish business-to-business companies which operate globally. The empirical data comprise interviews (n=28) with managers of three case companies. In addition the data includes a questionnaire (n=23) collected mainly for the purpose of social network analysis. In addition, the thesis includes a simulation study more specifically achieved by means of agent based modeling. The findings of the thesis shed light on the role of internal communication in the amalgamation process, contributing to the emergent discussion of network insights and thus to the industrial marketing research. In addition, the thesis increases understanding on internal communication in the change process to solution business, a supplier‘s internal communication in its matrix organization structure during a project sales process, key barriers and drivers that influence internal communication in project sales networks, perceived power within industrial project sales, and the revisioning of network pictures. According to the findings, internal communication is found to play a substantial role in the amalgamation process. First, it is suggested that internal communication is a base of multilateral exchange. Second, it is suggested that internal communication intensifies and maintains manifold rationality. Third, internal communication is needed to explicate the usually differing time perspectives of others and thus it is suggested that internal communication has role as the explicator of recursive time. Furthermore, the role of an efficient amalgamation process is found to be emphasized in solutions business as it requires a more advanced network insight for cross-functional collaboration. Finally, the thesis offers several managerial implications for industrial suppliers to enhance the amalgamation process when operating in solution business.

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In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.

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In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

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The last two decades have provided a vast opportunity to live and explore the compulsive imaginary world or virtual world through massively multiplayer online role-playing games (MMORPGs). MMORPG gives a wide range of opportunities to its users to participate with multi-players on the same platform, to communicate and to do real time actions. There is a virtual economy in these games which is largely player-driven. In-game currency provides its users to build up their Avatars, to buy or sell the necessary goods to play, survive in the games and so on. As a part of virtual economies generated through EVE Online, this thesis mainly focuses on how the prices of the minerals in EVE Online behave by applying the Jabłonska- Capasso-Morale (JCM) mathematical simulation model. It is to verify up to what degree the model can reproduce the virtual economy behavior. The model is applied to buy and sell prices of two minerals namely, isogen and morphite. The simulation results demonstrate that JCM model ts reasonably well to the mineral prices, which lets us conclude that virtual economies behave similarly to the real ones.

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The aim of this research is to develop a tool that could allow to organize coopetitional relationships between organizations on the basis of two-sided Internet platform. The main result of current master thesis is a detailed description of the concept of the lead generating internet platform-based coopetition. With the tools of agent-based modelling and simulation, there were obtained results that could be used as a base for suggestion that the developed concept is able to cause a positive effect on some particular industries (e.g. web-design studios market) and potentially can bring some benefits and extra profitability for most companies that operate on this particular industry. Also on the basis of the results it can be assumed that the developed instrument is also able to increase the degree of transparency of the market to which it is applied.

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The work presented in this thesis is regarding the development and evaluation of new bonding agents for short polyester fiber - polyurethane elastomer composites. The conventional bonding system based on hexamethylenetetramine, resorcinol and hydrated silica was not effective as a bonding agent for the composite, as the water eliminated during the formation of the RF resin hydrolysed the urethane linkages. Four bonding agents based on MDI/'I‘DI and polypropyleneglycol, propyleneglycol and glycerol were prepared and the composite recipe was optimised with respect to the cure characteristics and mechanical properties. The flow properties, stress relaxation pattern and the thermal degradation characteristics of the composites containing different bonding agents were then studied in detail to evaluate the new bonding systems. The optimum loading of resin was 5 phr and the ratio of the -01 to isocyanate was 1:1. The cure characteristics showed that the optimum combination of cure rate and processability was given by the composite with the resin based on polypropyleneglycol/ glycerol/ 4,4’diphenylmethanediisocynate (PPG/GL/MDI). From the rheological studies of the composites with and without bonding agents it was observed that all the composites showed pseudoplastic nature and the activation energy of flow of the composite was not altered by the presence of bonding agents. Mechanical properties such as tensile strength, modulus, tear resistance and abrasion resistance were improved in the presence of bonding agents and the effect was more pronounced in the case of abrasion resistance. The composites based on MDI/GL showed better initial properties while composites with resins based on MDI/PPG showed better aging resistance. Stress relaxation showed a multistage relaxation behaviour for the composite. Within the-strain levels studied, the initial rate of relaxation was higher and the cross over time was lesser for the composite containing bonding agents. The bonding agent based on MDI/PPG/GL was found to be a better choice for improving stress relaxation characteristics with better interfacial bonding. Thennogravimetirc analysis showed that the presence of fiber and bonding agents improved the thennal stability of the polyurethane elastomer marginally and it was maximum in the case of MDI / GL based bonding agents. The kinetics of degradation was not altered by the presence of bonding agents