916 resultados para Dynamic Bayesian Networks
Resumo:
We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.
Resumo:
Abstract In social insects, workers perform a multitude of tasks, such as foraging, nest construction, and brood rearing, without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gathered from the environment. Response-threshold models assume that individuals in a colony vary in the stimulus intensity (response threshold) at which they begin to perform the corresponding task. Here we highlight the limitations of these models with respect to colony performance in task allocation. First, we show with analysis and quantitative simulations that the deterministic response-threshold model constrains the workers' behavioral flexibility under some stimulus conditions. Next, we show that the probabilistic response-threshold model fails to explain precise colony responses to varying stimuli. Both of these limitations would be detrimental to colony performance when dynamic and precise task allocation is needed. To address these problems, we propose extensions of the response-threshold model by adding variables that weigh stimuli. We test the extended response-threshold model in a foraging scenario and show in simulations that it results in an efficient task allocation. Finally, we show that response-threshold models can be formulated as artificial neural networks, which consequently provide a comprehensive framework for modeling task allocation in social insects.
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The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.
Resumo:
Emotion regulation is crucial for successfully engaging in social interactions. Yet, little is known about the neural mechanisms controlling behavioral responses to emotional expressions perceived in the face of other people, which constitute a key element of interpersonal communication. Here, we investigated brain systems involved in social emotion perception and regulation, using functional magnetic resonance imaging (fMRI) in 20 healthy participants. The latter saw dynamic facial expressions of either happiness or sadness, and were asked to either imitate the expression or to suppress any expression on their own face (in addition to a gender judgment control task). fMRI results revealed higher activity in regions associated with emotion (e.g., the insula), motor function (e.g., motor cortex), and theory of mind (e.g., [pre]cuneus) during imitation. Activity in dorsal cingulate cortex was also increased during imitation, possibly reflecting greater action monitoring or conflict with own feeling states. In addition, premotor regions were more strongly activated during both imitation and suppression, suggesting a recruitment of motor control for both the production and inhibition of emotion expressions. Expressive suppression (eSUP) produced increases in dorsolateral and lateral prefrontal cortex typically related to cognitive control. These results suggest that voluntary imitation and eSUP modulate brain responses to emotional signals perceived from faces, by up- and down-regulating activity in distributed subcortical and cortical networks that are particularly involved in emotion, action monitoring, and cognitive control.
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The ground-penetrating radar (GPR) geophysical method has the potential to provide valuable information on the hydraulic properties of the vadose zone because of its strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR traveltime data can allow for a significant reduction in uncertainty regarding subsurface van Genuchten-Mualem (VGM) parameters. Much of the previous work on the stochastic estimation of VGM parameters from crosshole GPR data has considered the case of steady-state infiltration conditions, which represent only a small fraction of practically relevant scenarios. We explored in detail the dynamic infiltration case, specifically examining to what extent time-lapse crosshole GPR traveltimes, measured during a forced infiltration experiment at the Arreneas field site in Denmark, could help to quantify VGM parameters and their uncertainties in a layered medium, as well as the corresponding soil hydraulic properties. We used a Bayesian Markov-chain-Monte-Carlo inversion approach. We first explored the advantages and limitations of this approach with regard to a realistic synthetic example before applying it to field measurements. In our analysis, we also considered different degrees of prior information. Our findings indicate that the stochastic inversion of the time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions compared with the corresponding priors, which in turn significantly improves knowledge of soil hydraulic properties. Overall, the results obtained clearly demonstrate the value of the information contained in time-lapse GPR data for characterizing vadose zone dynamics.
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Cognitive radio is a wireless technology aimed at improvingthe efficiency use of the radio-electric spectrum, thus facilitating a reductionin the load on the free frequency bands. Cognitive radio networkscan scan the spectrum and adapt their parameters to operate in the unoccupiedbands. To avoid interfering with licensed users operating on a givenchannel, the networks need to be highly sensitive, which is achieved byusing cooperative sensing methods. Current cooperative sensing methodsare not robust enough against occasional or continuous attacks. This articleoutlines a Group Fusion method that takes into account the behavior ofusers over the short and long term. On fusing the data, the method is basedon giving more weight to user groups that are more unanimous in their decisions.Simulations have been performed in a dynamic environment withinterferences. Results prove that when attackers are present (both reiterativeor sporadic), the proposed Group Fusion method has superior sensingcapability than other methods.
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Multihop ad-hoc networks have a dynamic topology. Retrieving a route towards a remote peer requires the execution of a recipient lookup, which can publicly reveal sensitive information about him. Within this context, we propose an efficient, practical and scalable solution to guaranteethe anonymity of recipients' nodes in ad-hoc networks.
Resumo:
This paper describes the state of the art of secure ad hoc routing protocols and presents SEDYMO, a mechanism to secure a dynamic multihop ad hoc routing protocol. The proposed solution defeats internal and external attacks usinga trustworthiness model based on a distributed certification authority. Digital signatures and hash chains are used to ensure the correctness of the protocol. The protocol is compared with other alternatives in terms of security strength, energy efficiency and time delay. Both computational and transmission costs are considered and it is shown that the secure protocol overhead is not a critical factor compared to the high network interface cost.
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Manet security has a lot of open issues. Due to its character-istics, this kind of network needs preventive and corrective protection. Inthis paper, we focus on corrective protection proposing an anomaly IDSmodel for Manet. The design and development of the IDS are consideredin our 3 main stages: normal behavior construction, anomaly detectionand model update. A parametrical mixture model is used for behav-ior modeling from reference data. The associated Bayesian classi¯cationleads to the detection algorithm. MIB variables are used to provide IDSneeded information. Experiments of DoS and scanner attacks validatingthe model are presented as well.
Resumo:
In distributed energy production, permanent magnet synchronous generators (PMSG) are often connected to the grid via frequency converters, such as voltage source line converters. The price of the converter may constitute a large part of the costs of a generating set. Some of the permanent magnet synchronous generators with converters and traditional separately excited synchronous generators couldbe replaced by direct-on-line (DOL) non-controlled PMSGs. Small directly networkconnected generators are likely to have large markets in the area of distributed electric energy generation. Typical prime movers could be windmills, watermills and internal combustion engines. DOL PMSGs could also be applied in island networks, such as ships and oil platforms. Also various back-up power generating systems could be carried out with DOL PMSGs. The benefits would be a lower priceof the generating set and the robustness and easy use of the system. The performance of DOL PMSGs is analyzed. The electricity distribution companies have regulations that constrain the design of the generators being connected to the grid. The general guidelines and recommendations are applied in the analysis. By analyzing the results produced by the simulation model for the permanent magnet machine, the guidelines for efficient damper winding parameters for DOL PMSGs are presented. The simulation model is used to simulate grid connections and load transients. The damper winding parameters are calculated by the finite element method (FEM) and determined from experimental measurements. Three-dimensional finite element analysis (3D FEA) is carried out. The results from the simulation model and 3D FEA are compared with practical measurements from two prototype axial flux permanent magnet generators provided with damper windings. The dimensioning of the damper winding parameters is case specific. The damper winding should be dimensioned based on the moment of inertia of the generating set. It is shown that the damper winding has optimal values to reach synchronous operation in the shortest period of time after transient operation. With optimal dimensioning, interferenceon the grid is minimized.
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Teollisuuden palveluiden on huomattu olevan potentiaalinen lisätulojen lähde. Teollisuuden palveluiden dynaamisessa maailmassa räätälöinti ja kyky toimia nopeasti ovat kriittisiä asiakastyytyväisyyden ja kilpailuedun luomisprosessin osia. Toimitusketjussa käytetyn ajan lyhentämisellä voidaan saavuttaa sekä paremmat vasteajat, että alhaisemmat kokonaiskustannukset. Tutkielman tavoitteena on kuvata teollisuuden palveluiden dynaamista ympäristöä: asiakastarvetta, sekä mahdollisuuksia kaventaa pyydetyn ja saavutetun toimitusajan välistä eroa. Tämä toteutetaan pääosin strategisen toimitusajan hallinnan keinoin. Langattomien tietoliikenneverkkojen operaattorit haluavat vähentää ydinosaamiseensa kuulumatomiin toimintoihin, kuten ylläpitoon sitoutuneita pääomia. Tutkielman case osiossa varaosapalvelujen toimitusketjun kysyntä-, materiaali- ja informaatiovirtoja analysoidaan niin kvalitatiivisten haastatteluiden, sisäisten dokumenttien, kuin kvantitatiivisten tilastollisten menetelmienkin avulla. Löydöksiä peilataan vallitsevaa toimitusketjun ja ajanhallinnan paradigmaa vasten. Tulokset osoittavat, että vahvan palvelukulttuurin omaksuminen ja kokonaisvaltainen toimitusketjun tehokkuuden mittaaminen ovat ajanhallinnan lähtökohtia teollisuuden palveluissa.
Resumo:
The objective of this thesis is to provide a business model framework that connects customer value to firm resources and explains the change logic of the business model. Strategic supply management and especially dynamic value network management as its scope, the dissertation is based on basic economic theories, transaction cost economics and the resource-based view. The main research question is how the changing customer values should be taken into account when planning business in a networked environment. The main question is divided into questions that form the basic research problems for the separate case studies presented in the five Publications. This research adopts the case study strategy, and the constructive research approach within it. The material consists of data from several Delphi panels and expert workshops, software pilot documents, company financial statements and information on investor relations on the companies’ web sites. The cases used in this study are a mobile multi-player game value network, smart phone and “Skype mobile” services, the business models of AOL, eBay, Google, Amazon and a telecom operator, a virtual city portal business system and a multi-play offering. The main contribution of this dissertation is bridging the gap between firm resources and customer value. This has been done by theorizing the business model concept and connecting it to both the resource-based view and customer value. This thesis contributes to the resource-based view, which deals with customer value and firm resources needed to deliver the value but has a gap in explaining how the customer value changes should be connected to the changes in key resources. This dissertation also provides tools and processes for analyzing the customer value preferences of ICT services, constructing and analyzing business models and business concept innovation and conducting resource analysis.
Resumo:
The present study explores relationships between project marketers and their customers in project marketing context. The purpose of the study is to increase the understanding on supplier’s position in project marketing networks. Project marketing is representing a high volume in the international business, and the industrial network approach and the project marketing research cannot fully explain a supplier’s position in project marketing networks. Increased knowledge on project networks can also contribute to industrial marketing research more generally. Data for the present study was collected firstly during the pilot case study from project buyers in the paper and the steel industry in interviews. Secondly an entire project marketing case concerning a steel industry case was used as a data source. The data included interviews, correspondence between the supplier and the buyer, and project documents. The data of the pilot case was analysed with contents analysis, and in the case a deeper analysis based on the developed Stage Dimension framework was used. Supplier’s position in project marketing networks is a hierarchical and dynamic concept including a supplier’s position on the highest level. The dimensions of the position concept are the intermediate level, and the dimensions are based on the underlying components. Supplier’s position is composed from four organization related dimensions, and two individual actor related dimensions. The composition of the supplier’s position varies during the project marketing process, and consequently the relative importance of the dimensions is changing over the process. Supplier’s position in project marketing networks is shaped by incremental and radical changes. Radical changes are initiated by critical events. The study contributes to the research of industrial networks and project marketing. The theoretical contribution of the study is threefold: firstly it proposes a structure of the position concept in project marketing networks, secondly it proposes the Position Stage Dimension Component (PSDC) model for the development of supplier’s position during the project marketing process, and thirdly the study widens the critical event concept to cover the project marketing process both on the organizational and individual level. In addition to the theoretical contributions there are several managerial implications for planning and implementing marketing strategies in the project context.
Resumo:
Technical analysis of Low Voltage Direct Current (LVDC) distribution systems shows that in LVDC transmission the customer voltage quality is higher. One of the problems in LVDC distribution networks that converters both ends of the DC line are required. Because of the converters produce not pure DC voltage, but some fluctuations as well, the huge electrolytic capacitors are required to reduce voltage distortions in the DC-side. This thesis master’s thesis is focused on calculating required DC-link capacitance for LVDC transmission and estimation of the influence of different parameters on the voltage quality. The goal is to investigate the methods of the DC-link capacitance estimation and location in the transmission line.
Resumo:
Cyber security is one of the main topics that are discussed around the world today. The threat is real, and it is unlikely to diminish. People, business, governments, and even armed forces are networked in a way or another. Thus, the cyber threat is also facing military networking. On the other hand, the concept of Network Centric Warfare sets high requirements for military tactical data communications and security. A challenging networking environment and cyber threats force us to consider new approaches to build security on the military communication systems. The purpose of this thesis is to develop a cyber security architecture for military networks, and to evaluate the designed architecture. The architecture is described as a technical functionality. As a new approach, the thesis introduces Cognitive Networks (CN) which are a theoretical concept to build more intelligent, dynamic and even secure communication networks. The cognitive networks are capable of observe the networking environment, make decisions for optimal performance and adapt its system parameter according to the decisions. As a result, the thesis presents a five-layer cyber security architecture that consists of security elements controlled by a cognitive process. The proposed architecture includes the infrastructure, services and application layers that are managed and controlled by the cognitive and management layers. The architecture defines the tasks of the security elements at a functional level without introducing any new protocols or algorithms. For evaluating two separated method were used. The first method is based on the SABSA framework that uses a layered approach to analyze overall security of an organization. The second method was a scenario based method in which a risk severity level is calculated. The evaluation results show that the proposed architecture fulfills the security requirements at least at a high level. However, the evaluation of the proposed architecture proved to be very challenging. Thus, the evaluation results must be considered very critically. The thesis proves the cognitive networks are a promising approach, and they provide lots of benefits when designing a cyber security architecture for the tactical military networks. However, many implementation problems exist, and several details must be considered and studied during the future work.