WorldWideScience

Sample records for network modeling framework

  1. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection

    Directory of Open Access Journals (Sweden)

    Declan T. Delaney

    2016-12-01

    Full Text Available No single network solution for Internet of Things (IoT networks can provide the required level of Quality of Service (QoS for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  2. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection.

    Science.gov (United States)

    Delaney, Declan T; O'Hare, Gregory M P

    2016-12-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  3. Strategic assessment of capacity consumption in railway networks: Framework and model

    DEFF Research Database (Denmark)

    Jensen, Lars Wittrup; Landex, Alex; Nielsen, Otto Anker

    2017-01-01

    In this paper, we develop a new framework for strategic planning purposes to calculate railway infrastructure occupation and capacity consumption in networks, independent of a timetable. Furthermore, a model implementing the framework is presented. In this model different train sequences...... are obtained efficiently with little input. The case illustrates the model's ability to quantify the capacity gain from infrastructure scenario to infrastructure scenario which can be used to increase the number of trains or improve the robustness of the system....

  4. Models of Coupled Settlement and Habitat Networks for Biodiversity Conservation: Conceptual Framework, Implementation and Potential Applications

    Directory of Open Access Journals (Sweden)

    Maarten J. van Strien

    2018-04-01

    Full Text Available Worldwide, the expansion of settlement and transport infrastructure is one of the most important proximate as well as ultimate causes of biodiversity loss. As much as every modern human society depends on a network of settlements that is well-connected by transport infrastructure (i.e., settlement network, animal and plant species depend on networks of habitats between which they can move (i.e., habitat networks. However, changes to a settlement network in a region often threaten the integrity of the region's habitat networks. Determining plans and policy to prevent these threats is made difficult by the numerous interactions and feedbacks that exist between and within the settlement and habitat networks. Mathematical models of coupled settlement and habitat networks can help us understand the dynamics of this social-ecological system. Yet, few attempts have been made to develop such mathematical models. In this paper, we promote the development of models of coupled settlement and habitat networks for biodiversity conservation. First, we present a conceptual framework of key variables that are ideally considered when operationalizing the coupling of settlement and habitat networks. In this framework, we first describe important network-internal interactions by differentiating between the structural (i.e., relating to purely physical conditions determining the suitability of a location for living or movement and functional (i.e., relating to the actual presence, abundance or movement of people or other organisms properties of either network. We then describe the main one-way influences that a settlement network can exert on the habitat networks and vice versa. Second, we give several recommendations for the mathematical modeling of coupled settlement and habitat networks and present several existing modeling approaches (e.g., habitat network models and land-use transport interaction models that could be used for this purpose. Lastly, we elaborate

  5. Modeling a Large Data Acquisition Network in a Simulation Framework

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00337030; The ATLAS collaboration; Froening, Holger; Garcia, Pedro Javier; Vandelli, Wainer

    2015-01-01

    The ATLAS detector at CERN records particle collision “events” delivered by the Large Hadron Collider. Its data-acquisition system is a distributed software system that identifies, selects, and stores interesting events in near real-time, with an aggregate throughput of several 10 GB/s. It is a distributed software system executed on a farm of roughly 2000 commodity worker nodes communicating via TCP/IP on an Ethernet network. Event data fragments are received from the many detector readout channels and are buffered, collected together, analyzed and either stored permanently or discarded. This system, and data-acquisition systems in general, are sensitive to the latency of the data transfer from the readout buffers to the worker nodes. Challenges affecting this transfer include the many-to-one communication pattern and the inherently bursty nature of the traffic. In this paper we introduce the main performance issues brought about by this workload, focusing in particular on the so-called TCP incast pathol...

  6. Multivariate Multiple Regression Models for a Big Data-Empowered SON Framework in Mobile Wireless Networks

    Directory of Open Access Journals (Sweden)

    Yoonsu Shin

    2016-01-01

    Full Text Available In the 5G era, the operational cost of mobile wireless networks will significantly increase. Further, massive network capacity and zero latency will be needed because everything will be connected to mobile networks. Thus, self-organizing networks (SON are needed, which expedite automatic operation of mobile wireless networks, but have challenges to satisfy the 5G requirements. Therefore, researchers have proposed a framework to empower SON using big data. The recent framework of a big data-empowered SON analyzes the relationship between key performance indicators (KPIs and related network parameters (NPs using machine-learning tools, and it develops regression models using a Gaussian process with those parameters. The problem, however, is that the methods of finding the NPs related to the KPIs differ individually. Moreover, the Gaussian process regression model cannot determine the relationship between a KPI and its various related NPs. In this paper, to solve these problems, we proposed multivariate multiple regression models to determine the relationship between various KPIs and NPs. If we assume one KPI and multiple NPs as one set, the proposed models help us process multiple sets at one time. Also, we can find out whether some KPIs are conflicting or not. We implement the proposed models using MapReduce.

  7. Conceptual Framework for Agent-Based Modeling of Customer-Oriented Supply Networks

    OpenAIRE

    Solano-Vanegas , Clara ,; Carrillo-Ramos , Angela; Montoya-Torres , Jairo ,

    2015-01-01

    Part 3: Collaboration Frameworks; International audience; Supply Networks (SN) are complex systems involving the interaction of different actors, very often, with different objectives and goals. Among the different existing modeling approaches, agent-based systems can properly represent the autonomous behavior of SN links and, simultaneously, observe the general response of the system as a result of individual actions. Most of research using agent-based modeling in SN focuses on production is...

  8. A discrete-time Bayesian network reliability modeling and analysis framework

    International Nuclear Information System (INIS)

    Boudali, H.; Dugan, J.B.

    2005-01-01

    Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis

  9. A mathematical framework for agent based models of complex biological networks.

    Science.gov (United States)

    Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2011-07-01

    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

  10. A mathematical framework for modelling and evaluating natural gas pipeline networks under hydrogen injection

    Energy Technology Data Exchange (ETDEWEB)

    Tabkhi, F.; Azzaro-Pantel, C.; Pibouleau, L.; Domenech, S. [Laboratoire de Genie Chimique, UMR5503 CNRS/INP/UPS, 5 rue Paulin Talabot F-BP1301, 31106 Toulouse Cedex 1 (France)

    2008-11-15

    This article presents the framework of a mathematical formulation for modelling and evaluating natural gas pipeline networks under hydrogen injection. The model development is based on gas transport through pipelines and compressors which compensate for the pressure drops by implying mainly the mass and energy balances on the basic elements of the network. The model was initially implemented for natural gas transport and the principle of extension for hydrogen-natural gas mixtures is presented. The objective is the treatment of the classical fuel minimizing problem in compressor stations. The optimization procedure has been formulated by means of a nonlinear technique within the General Algebraic Modelling System (GAMS) environment. This work deals with the adaptation of the current transmission networks of natural gas to the transport of hydrogen-natural gas mixtures. More precisely, the quantitative amount of hydrogen that can be added to natural gas can be determined. The studied pipeline network, initially proposed in [1] is revisited here for the case of hydrogen-natural gas mixtures. Typical quantitative results are presented, showing that the addition of hydrogen to natural gas decreases significantly the transmitted power: the maximum fraction of hydrogen that can be added to natural gas is around 6 mass% for this example. (author)

  11. A Human Sensor Network Framework in Support of Near Real Time Situational Geophysical Modeling

    Science.gov (United States)

    Aulov, O.; Price, A.; Smith, J. A.; Halem, M.

    2013-12-01

    The area of Disaster Management is well established among Federal Agencies such as FEMA, EPA, NOAA and NASA. These agencies have well formulated frameworks for response and mitigation based on near real time satellite and conventional observing networks for assimilation into geophysical models. Forecasts from these models are used to communicate with emergency responders and the general public. More recently, agencies have started using social media to broadcast warnings and alerts to potentially affected communities. In this presentation, we demonstrate the added benefits of mining and assimilating the vast amounts of social media data available from heterogeneous hand held devices and social networks into established operational geophysical modeling frameworks as they apply to the five cornerstones of disaster management - Prevention, Mitigation, Preparedness, Response and Recovery. Often, in situations of extreme events, social media provide the earliest notification of adverse extreme events. However, various forms of social media data also can provide useful geolocated and time stamped in situ observations, complementary to directly sensed conventional observations. We use the concept of a Human Sensor Network where one views social media users as carrying field deployed "sensors" whose posts are the remotely "sensed instrument measurements.' These measurements can act as 'station data' providing the resolution and coverage needed for extreme event specific modeling and validation. Here, we explore the use of social media through the use of a Human Sensor Network (HSN) approach as another data input source for assimilation into geophysical models. Employing the HSN paradigm can provide useful feedback in near real-time, but presents software challenges for rapid access, quality filtering and transforming massive social media data into formats consistent with the operational models. As a use case scenario, we demonstrate the value of HSN for disaster management

  12. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  13. FRAMEWORK OF TAILORMADE DRIVING SUPPORT SYSTEMS AND NEURAL NETWORK DRIVER MODEL

    Directory of Open Access Journals (Sweden)

    Toshiya HIROSE, M.S.

    2004-01-01

    Nowadays, tailormade medical treatment is receiving much attention in the field of medical care. It is also desirable for driving support systems to reflect the driving characteristics of individuals as much as possible, begin monitoring the driver when a driver starts driving and calculates the driver model, and supports them with a model that makes the driver feel quite normal. That is the construction of Tailormade Driving Support Systems (TDSS. This research proposes a concept and a framework of TDSS, and presents a driver model that uses a neural network to build the system. As for the feasibility of this system, the research selects braking as a typical constituent element, and illustrates and reviews the results of experiments and simulations.

  14. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

    Science.gov (United States)

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

  15. A network model framework for prioritizing wetland conservation in the Great Plains

    Science.gov (United States)

    Albanese, Gene; Haukos, David A.

    2017-01-01

    ContextPlaya wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations.ObjectiveTo develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains.MethodsWe examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation.ResultsWe identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse >2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances (h) >2 km but <5 km and was most sensitive to changes in wetland availability (p) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low (p = 0.2).ConclusionsOur findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.

  16. Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

    Science.gov (United States)

    Karpatne, A.; Kumar, V.

    2017-12-01

    Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

  17. Modelling Framework and the Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks

    DEFF Research Database (Denmark)

    Han, Xue; Sandels, Claes; Zhu, Kun

    2013-01-01

    There has been a large body of statements claiming that the large-scale deployment of Distributed Energy Resources (DERs) could eventually reshape the future distribution grid operation in numerous ways. Thus, it is necessary to introduce a framework to measure to what extent the power system......, comprising distributed generation, active demand and electric vehicles. Subsequently, quantitative analysis was made on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. Simulations are performed in two typical distribution network models for four seasons. The simulation...... results show that in general the DER deployment brings in the possibilities to reduce the power losses and voltage drops by compensating power from the local generation and optimizing the local load profiles....

  18. Multi-agent modelling framework for water, energy and other resource networks

    Science.gov (United States)

    Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

    2015-12-01

    Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be

  19. A decision-making framework to model environmental flow requirements in oasis areas using Bayesian networks

    Science.gov (United States)

    Xue, Jie; Gui, Dongwei; Zhao, Ying; Lei, Jiaqiang; Zeng, Fanjiang; Feng, Xinlong; Mao, Donglei; Shareef, Muhammad

    2016-09-01

    The competition for water resources between agricultural and natural oasis ecosystems has become an increasingly serious problem in oasis areas worldwide. Recently, the intensive extension of oasis farmland has led to excessive exploitation of water discharge, and consequently has resulted in a lack of water supply in natural oasis. To coordinate the conflicts, this paper provides a decision-making framework for modeling environmental flows in oasis areas using Bayesian networks (BNs). Three components are included in the framework: (1) assessment of agricultural economic loss due to meeting environmental flow requirements; (2) decision-making analysis using BNs; and (3) environmental flow decision-making under different water management scenarios. The decision-making criterion is determined based on intersection point analysis between the probability of large-level total agro-economic loss and the ratio of total to maximum agro-economic output by satisfying environmental flows. An application in the Qira oasis area of the Tarim Basin, Northwest China indicates that BNs can model environmental flow decision-making associated with agricultural economic loss effectively, as a powerful tool to coordinate water-use conflicts. In the case study, the environmental flow requirement is determined as 50.24%, 49.71% and 48.73% of the natural river flow in wet, normal and dry years, respectively. Without further agricultural economic loss, 1.93%, 0.66% and 0.43% of more river discharge can be allocated to eco-environmental water demands under the combined strategy in wet, normal and dry years, respectively. This work provides a valuable reference for environmental flow decision-making in any oasis area worldwide.

  20. Reliability Measure Model for Assistive Care Loop Framework Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Venki Balasubramanian

    2010-01-01

    Full Text Available Body area wireless sensor networks (BAWSNs are time-critical systems that rely on the collective data of a group of sensor nodes. Reliable data received at the sink is based on the collective data provided by all the source sensor nodes and not on individual data. Unlike conventional reliability, the definition of retransmission is inapplicable in a BAWSN and would only lead to an elapsed data arrival that is not acceptable for time-critical application. Time-driven applications require high data reliability to maintain detection and responses. Hence, the transmission reliability for the BAWSN should be based on the critical time. In this paper, we develop a theoretical model to measure a BAWSN's transmission reliability, based on the critical time. The proposed model is evaluated through simulation and then compared with the experimental results conducted in our existing Active Care Loop Framework (ACLF. We further show the effect of the sink buffer in transmission reliability after a detailed study of various other co-existing parameters.

  1. Application of a conceptual framework for the modelling and execution of clinical guidelines as networks of concurrent processes

    NARCIS (Netherlands)

    Fung, L.S.N.; Fung, Nick Lik San; Widya, I.A.; Broens, T.H.F.; Larburu Rubio, Nekane; Bults, Richard G.A.; Shalom, Erez; Jones, Valerie M.; Hermens, Hermanus J.

    2014-01-01

    We present a conceptual framework for modelling clinical guidelines as networks of concurrent processes. This enables the guideline to be partitioned and distributed at run-time across a knowledge-based telemedicine system, which is distributed by definition but whose exact physical configuration

  2. A Web Service-based framework model for people-centric sensing applications applied to social networking.

    Science.gov (United States)

    Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

    2012-01-01

    As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

  3. POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

    Energy Technology Data Exchange (ETDEWEB)

    Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

    2016-03-01

    This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

  4. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jisheng Zhang

    2015-06-01

    Full Text Available It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks.

  5. Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

    Science.gov (United States)

    Kriegeskorte, Nikolaus

    2015-11-24

    Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

  6. Spatio-temporal model based optimization framework to design future hydrogen infrastructure networks

    International Nuclear Information System (INIS)

    Konda, N.V.S.; Shah, N.; Brandon, N.P.

    2009-01-01

    A mixed integer programming (MIP) spatio-temporal model was used to design hydrogen infrastructure networks for the Netherlands. The detailed economic analysis was conducted using a multi-echelon model of the entire hydrogen supply chain, including feed, production, storage, and transmission-distribution systems. The study considered various near-future and commercially available technologies. A multi-period model was used to design evolutionary hydrogen supply networks in coherence with growing demand. A scenario-based analysis was conducted in order to account for uncertainties in future demand. The study showed that competitive hydrogen networks can be designed for any conceivable scenario. It was concluded that the multi-period model presented significant advantages in relation to decision-making over long time-horizons

  7. PREDICTING THE EFFECTIVENESS OF WEB INFORMATION SYSTEMS USING NEURAL NETWORKS MODELING: FRAMEWORK & EMPIRICAL TESTING

    Directory of Open Access Journals (Sweden)

    Dr. Kamal Mohammed Alhendawi

    2018-02-01

    Full Text Available The information systems (IS assessment studies have still used the commonly traditional tools such as questionnaires in evaluating the dependent variables and specially effectiveness of systems. Artificial neural networks have been recently accepted as an effective alternative tool for modeling the complicated systems and widely used for forecasting. A very few is known about the employment of Artificial Neural Network (ANN in the prediction IS effectiveness. For this reason, this study is considered as one of the fewest studies to investigate the efficiency and capability of using ANN for forecasting the user perceptions towards IS effectiveness where MATLAB is utilized for building and training the neural network model. A dataset of 175 subjects collected from international organization are utilized for ANN learning where each subject consists of 6 features (5 quality factors as inputs and one Boolean output. A percentage of 75% o subjects are used in the training phase. The results indicate an evidence on the ANN models has a reasonable accuracy in forecasting the IS effectiveness. For prediction, ANN with PURELIN (ANNP and ANN with TANSIG (ANNTS transfer functions are used. It is found that both two models have a reasonable prediction, however, the accuracy of ANNTS model is better than ANNP model (88.6% and 70.4% respectively. As the study proposes a new model for predicting IS dependent variables, it could save the considerably high cost that might be spent in sample data collection in the quantitative studies in the fields science, management, education, arts and others.

  8. A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

    Directory of Open Access Journals (Sweden)

    Jorge Sá Silva

    2012-02-01

    Full Text Available As the Internet evolved, social networks (such as Facebook have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

  9. The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures

    International Nuclear Information System (INIS)

    Eusgeld, Irene; Kroeger, Wolfgang; Sansavini, Giovanni; Schlaepfer, Markus; Zio, Enrico

    2009-01-01

    A framework for the analysis of the vulnerability of critical infrastructures has been proposed by some of the authors. The framework basically consists of two successive stages: (i) a screening analysis for identifying the parts of the critical infrastructure most relevant with respect to its vulnerability and (ii) a detailed modeling of the operational dynamics of the identified parts for gaining insights on the causes and mechanisms responsible for the vulnerability. In this paper, a critical presentation is offered of the results of a set of investigations aimed at evaluating the potentials of (i) using network analysis based on measures of topological interconnection and reliability efficiency, for the screening task; (ii) using object-oriented modeling as the simulation framework to capture the detailed dynamics of the operational scenarios involving the most vulnerable parts of the critical infrastructure as identified by the preceding network analysis. A case study based on the Swiss high-voltage transmission system is considered. The results are cross-compared and evaluated; the needs of further research are defined

  10. A new optimization framework using genetic algorithm and artificial neural network to reduce uncertainties in petroleum reservoir models

    Science.gov (United States)

    Maschio, Célio; José Schiozer, Denis

    2015-01-01

    In this article, a new optimization framework to reduce uncertainties in petroleum reservoir attributes using artificial intelligence techniques (neural network and genetic algorithm) is proposed. Instead of using the deterministic values of the reservoir properties, as in a conventional process, the parameters of the probability density function of each uncertain attribute are set as design variables in an optimization process using a genetic algorithm. The objective function (OF) is based on the misfit of a set of models, sampled from the probability density function, and a symmetry factor (which represents the distribution of curves around the history) is used as weight in the OF. Artificial neural networks are trained to represent the production curves of each well and the proxy models generated are used to evaluate the OF in the optimization process. The proposed method was applied to a reservoir with 16 uncertain attributes and promising results were obtained.

  11. An analytical modeling framework to evaluate converged networks through business-oriented metrics

    International Nuclear Information System (INIS)

    Guimarães, Almir P.; Maciel, Paulo R.M.; Matias, Rivalino

    2013-01-01

    Nowadays, society has increasingly relied on convergent networks as an essential means for individuals, businesses, and governments. Strategies, methods, models and techniques for preventing and handling hardware or software failures as well as avoiding performance degradation are, thus, fundamental for prevailing in business. Issues such as operational costs, revenues and the respective relationship to key performance and dependability metrics are central for defining the required system infrastructure. Our work aims to provide system performance and dependability models for supporting optimization of infrastructure design, aimed at business oriented metrics. In addition, a methodology is also adopted to support both the modeling and the evaluation process. The results showed that the proposed methodology can significantly reduce the complexity of infrastructure design as well as improve the relationship between business and infrastructure aspects

  12. Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

    Science.gov (United States)

    Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

    2018-03-01

    Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

  13. Cluster imaging of multi-brain networks (CIMBN: a general framework for hyperscanning and modeling a group of interacting brains

    Directory of Open Access Journals (Sweden)

    Lian eDuan

    2015-07-01

    Full Text Available Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called Cluster Imaging of Multi-brain Networks (CIMBN. CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network’s properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology.

  14. A framework for online social networking features

    Directory of Open Access Journals (Sweden)

    Mohsen Shafiei Nikabadi

    2014-06-01

    Full Text Available Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable.

  15. A logic model framework for evaluation and planning in a primary care practice-based research network (PBRN)

    Science.gov (United States)

    Hayes, Holly; Parchman, Michael L.; Howard, Ray

    2012-01-01

    Evaluating effective growth and development of a Practice-Based Research Network (PBRN) can be challenging. The purpose of this article is to describe the development of a logic model and how the framework has been used for planning and evaluation in a primary care PBRN. An evaluation team was formed consisting of the PBRN directors, staff and its board members. After the mission and the target audience were determined, facilitated meetings and discussions were held with stakeholders to identify the assumptions, inputs, activities, outputs, outcomes and outcome indicators. The long-term outcomes outlined in the final logic model are two-fold: 1.) Improved health outcomes of patients served by PBRN community clinicians; and 2.) Community clinicians are recognized leaders of quality research projects. The Logic Model proved useful in identifying stakeholder interests and dissemination activities as an area that required more attention in the PBRN. The logic model approach is a useful planning tool and project management resource that increases the probability that the PBRN mission will be successfully implemented. PMID:21900441

  16. Hydrology-oriented forest management trade-offs. A modeling framework coupling field data, simulation results and Bayesian Networks.

    Science.gov (United States)

    Garcia-Prats, Alberto; González-Sanchis, María; Del Campo, Antonio D; Lull, Cristina

    2018-05-23

    Hydrology-oriented forest management sets water as key factor of the forest management for adaptation due to water is the most limiting factor in the Mediterranean forest ecosystems. The aim of this study was to apply Bayesian Network modeling to assess potential indirect effects and trade-offs when hydrology-oriented forest management is applied to a real Mediterranean forest ecosystem. Water, carbon and nitrogen cycles, and forest fire risk were included in the modeling framework. Field data from experimental plots were employed to calibrate and validate the mechanistic Biome-BGCMuSo model that simulates the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere. Many other 50-year long scenarios with different conditions to the ones measured in the field experiment were simulated and the outcomes employed to build the Bayesian Network in a linked chain of models. Hydrology-oriented forest management was very positive insofar as more water was made available to the stand because of an interception reduction. This resource was made available to the stand, which increased the evapotranspiration and its components, the soil water content and a slightly increase of deep percolation. Conversely, Stemflow was drastically reduced. No effect was observed on Runof due to the thinning treatment. The soil organic carbon content was also increased which in turn caused a greater respiration. The long-term effect of the thinning treatment on the LAI was very positive. This was undoubtedly due to the increased vigor generated by the greater availability of water and nutrients for the stand and the reduction of competence between trees. This greater activity resulted in an increase in GPP and vegetation carbon, and therefore, we would expect a higher carbon sequestration. It is worth emphasizing that this extra amount of water and nutrients was taken up by the stand and did not entail any loss of nutrients. Copyright © 2018 Elsevier B.V. All

  17. Building clinical networks: a developmental evaluation framework.

    Science.gov (United States)

    Carswell, Peter; Manning, Benjamin; Long, Janet; Braithwaite, Jeffrey

    2014-05-01

    Clinical networks have been designed as a cross-organisational mechanism to plan and deliver health services. With recent concerns about the effectiveness of these structures, it is timely to consider an evidence-informed approach for how they can be developed and evaluated. To document an evaluation framework for clinical networks by drawing on the network evaluation literature and a 5-year study of clinical networks. We searched literature in three domains: network evaluation, factors that aid or inhibit network development, and on robust methods to measure network characteristics. This material was used to build a framework required for effective developmental evaluation. The framework's architecture identifies three stages of clinical network development; partner selection, network design and network management. Within each stage is evidence about factors that act as facilitators and barriers to network growth. These factors can be used to measure progress via appropriate methods and tools. The framework can provide for network growth and support informed decisions about progress. For the first time in one place a framework incorporating rigorous methods and tools can identify factors known to affect the development of clinical networks. The target user group is internal stakeholders who need to conduct developmental evaluation to inform key decisions along their network's developmental pathway.

  18. Simulation-based Modeling Frameworks for Networked Multi-processor System-on-Chip

    DEFF Research Database (Denmark)

    Mahadevan, Shankar

    2006-01-01

    the requirements to model the application and the architecture properties independent of the NoC, and then use these applications to successfully validate the approach against a reference cycle-true system. The presence of a standard socket at the intellectual property (IP) and the NoC interface in both the ARTS...

  19. Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems

    Science.gov (United States)

    Hunter, Jason M.; Maier, Holger R.; Gibbs, Matthew S.; Foale, Eloise R.; Grosvenor, Naomi A.; Harders, Nathan P.; Kikuchi-Miller, Tahali C.

    2018-05-01

    Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary problem with process-based models is that in many instances, not all of the underlying processes are fully understood or able to be represented mathematically. There are also often insufficient historical data to support model development. The major limitation of data-driven models, such as artificial neural networks (ANNs) in comparison, is that they provide limited system understanding and are generally not able to be used to inform management decisions targeting specific processes, as different processes are generally modelled implicitly. In order to overcome these limitations, a generic framework for developing hybrid process and data-driven models of salinity in river systems is introduced and applied in this paper. As part of the approach, the most suitable sub-models are developed for each sub-process affecting salinity at the location of interest based on consideration of model purpose, the degree of process understanding and data availability, which are then combined to form the hybrid model. The approach is applied to a 46 km reach of the Murray River in South Australia, which is affected by high levels of salinity. In this reach, the major processes affecting salinity include in-stream salt transport, accession of saline groundwater along the length of the reach and the flushing of three waterbodies in the floodplain during overbank flows of various magnitudes. Based on trade-offs between the degree of process understanding and data availability, a process-driven model is developed for in-stream salt transport, an ANN model is used to model saline groundwater accession and three linear regression models are used

  20. Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

    Directory of Open Access Journals (Sweden)

    Daniel J. Garcia

    2015-07-01

    Full Text Available The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water, and maximization of energy output per liter of water consumed (energy efficiency of water. A mixed integer, multiobjective nonlinear fractional programming (MINLFP model is formulated. A mixed integer linear programing (MILP-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline. A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers.

  1. Design of a Message Passing Model for Use in a Heterogeneous CPU-NFP Framework for Network Analytics

    CSIR Research Space (South Africa)

    Pennefather, S

    2017-09-01

    Full Text Available of applications written in the Go programming language to be executed on a Network Flow Processor (NFP) for enhanced performance. This paper explores the need and feasibility of implementing a message passing model for data transmission between the NFP and CPU...

  2. A framework for reactive optimization in mobile ad hoc networks

    DEFF Research Database (Denmark)

    McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

    2008-01-01

    We present a framework to optimize the performance of a mobile ad hoc network over a wide range of operating conditions. It includes screening experiments to quantify the parameters and interactions among parameters influential to throughput. Profile-driven regression is applied to obtain a model....... The predictive accuracy of the model is monitored and used to update the model dynamically. The results indicate the framework may be useful for the optimization of dynamic systems of high dimension....

  3. Hidden Neural Networks: A Framework for HMM/NN Hybrids

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric; Krogh, Anders Stærmose

    1997-01-01

    This paper presents a general framework for hybrids of hidden Markov models (HMM) and neural networks (NN). In the new framework called hidden neural networks (HNN) the usual HMM probability parameters are replaced by neural network outputs. To ensure a probabilistic interpretation the HNN is nor...... HMMs on TIMIT continuous speech recognition benchmarks. On the task of recognizing five broad phoneme classes an accuracy of 84% is obtained compared to 76% for a standard HMM. Additionally, we report a preliminary result of 69% accuracy on the TIMIT 39 phoneme task...

  4. MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

    Directory of Open Access Journals (Sweden)

    Wasserman Wyeth W

    2011-03-01

    Full Text Available Abstract Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs, microRNAs (miRNAs and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs. Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL. In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT, an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http

  5. Entropy Characterization of Random Network Models

    Directory of Open Access Journals (Sweden)

    Pedro J. Zufiria

    2017-06-01

    Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

  6. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    Directory of Open Access Journals (Sweden)

    Kim Hyun

    2011-12-01

    Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  7. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

    Science.gov (United States)

    Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

    2011-01-01

    Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  8. Understanding dynamics of information transmission in Drosophila melanogaster using a statistical modeling framework for longitudinal network data (the RSiena package

    Directory of Open Access Journals (Sweden)

    Cristian ePasquaretta

    2016-04-01

    Full Text Available Social learning – the transmission of behaviors through observation or interaction with conspecifics – can be viewed as a decision-making process driven by interactions among individuals. Animal group structures change over time and interactions among individuals occur in particular orders that may be repeated following specific patterns, change in their nature, or disappear completely. Here we used a stochastic actor-oriented model built using the RSiena package in R to estimate individual behaviors and their changes through time, by analyzing the dynamic of the interaction network of the fruit fly Drosophila melanogaster during social learning experiments. In particular, we re-analyzed an experimental dataset where uninformed flies, left free to interact with informed ones, acquired and later used information about oviposition site choice obtained by social interactions. We estimated the degree to which the uninformed flies had successfully acquired the information carried by informed individuals using the proportion of eggs laid by uninformed flies on the medium their conspecifics had been trained to favor. Regardless of the degree of information acquisition measured in uninformed individuals, they always received and started interactions more frequently than informed ones did. However, information was efficiently transmitted (i.e. uninformed flies predominantly laid eggs on the same medium informed ones had learn to prefer only when the difference in contacts sent between the two fly types was small. Interestingly, we found that the degree of reciprocation, the tendency of individuals to form mutual connections between each other, strongly affected oviposition site choice in uninformed flies. This work highlights the great potential of RSiena and its utility in the studies of interaction networks among non-human animals.

  9. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses

    Directory of Open Access Journals (Sweden)

    Karim El-Laithy

    2011-01-01

    Full Text Available An integration of both the Hebbian-based and reinforcement learning (RL rules is presented for dynamic synapses. The proposed framework permits the Hebbian rule to update the hidden synaptic model parameters regulating the synaptic response rather than the synaptic weights. This is performed using both the value and the sign of the temporal difference in the reward signal after each trial. Applying this framework, a spiking network with spike-timing-dependent synapses is tested to learn the exclusive-OR computation on a temporally coded basis. Reward values are calculated with the distance between the output spike train of the network and a reference target one. Results show that the network is able to capture the required dynamics and that the proposed framework can reveal indeed an integrated version of Hebbian and RL. The proposed framework is tractable and less computationally expensive. The framework is applicable to a wide class of synaptic models and is not restricted to the used neural representation. This generality, along with the reported results, supports adopting the introduced approach to benefit from the biologically plausible synaptic models in a wide range of intuitive signal processing.

  10. Cyber Security Research Frameworks For Coevolutionary Network Defense

    Energy Technology Data Exchange (ETDEWEB)

    Rush, George D. [Missouri Univ. of Science and Technology, Rolla, MO (United States); Tauritz, Daniel Remy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-12-03

    Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation Framework for Experiments (DCAFE) that enables experiment automation and control in a distributed environment. Predictive analysis of adversaries is another thorny issue in cyber security. Game theory can be used to mathematically analyze adversary models, but its scalability limitations restrict its use. Computational game theory allows us to scale classical game theory to larger, more complex systems. In the second paper, we propose a framework termed Coevolutionary Agent-based Network Defense Lightweight Event System (CANDLES) that can coevolve attacker and defender agent strategies and capabilities and evaluate potential solutions with a custom network defense simulation. The third paper is a continuation of the CANDLES project in which we rewrote key parts of the framework. Attackers and defenders have been redesigned to evolve pure strategy, and a new network security simulation is devised which specifies network architecture and adds a temporal aspect. We also add a hill climber algorithm to evaluate the search space and justify the use of a coevolutionary algorithm.

  11. Reasoning and Knowledge Acquisition Framework for 5G Network Analytics

    Science.gov (United States)

    2017-01-01

    Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration. PMID:29065473

  12. Reasoning and Knowledge Acquisition Framework for 5G Network Analytics.

    Science.gov (United States)

    Sotelo Monge, Marco Antonio; Maestre Vidal, Jorge; García Villalba, Luis Javier

    2017-10-21

    Autonomic self-management is a key challenge for next-generation networks. This paper proposes an automated analysis framework to infer knowledge in 5G networks with the aim to understand the network status and to predict potential situations that might disrupt the network operability. The framework is based on the Endsley situational awareness model, and integrates automated capabilities for metrics discovery, pattern recognition, prediction techniques and rule-based reasoning to infer anomalous situations in the current operational context. Those situations should then be mitigated, either proactive or reactively, by a more complex decision-making process. The framework is driven by a use case methodology, where the network administrator is able to customize the knowledge inference rules and operational parameters. The proposal has also been instantiated to prove its adaptability to a real use case. To this end, a reference network traffic dataset was used to identify suspicious patterns and to predict the behavior of the monitored data volume. The preliminary results suggest a good level of accuracy on the inference of anomalous traffic volumes based on a simple configuration.

  13. Social networks a framework of computational intelligence

    CERN Document Server

    Chen, Shyi-Ming

    2014-01-01

    This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

  14. Integrating a flexible modeling framework (FMF) with the network security assessment instrument to reduce software security risk

    Science.gov (United States)

    Gilliam, D. P.; Powell, J. D.

    2002-01-01

    This paper presents a portion of an overall research project on the generation of the network security assessment instrument to aid developers in assessing and assuring the security of software in the development and maintenance lifecycles.

  15. Geologic Framework Model (GFM2000)

    International Nuclear Information System (INIS)

    T. Vogt

    2004-01-01

    The purpose of this report is to document the geologic framework model, version GFM2000 with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, and the differences between GFM2000 and previous versions. The version number of this model reflects the year during which the model was constructed. This model supersedes the previous model version, documented in Geologic Framework Model (GFM 3.1) (CRWMS M and O 2000 [DIRS 138860]). The geologic framework model represents a three-dimensional interpretation of the geology surrounding the location of the monitored geologic repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain. The geologic framework model encompasses and is limited to an area of 65 square miles (168 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the geologic framework model (shown in Figure 1-1) were chosen to encompass the exploratory boreholes and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The upper surface of the model is made up of the surface topography and the depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The geologic framework model was constructed from geologic map and borehole data. Additional information from measured stratigraphic sections, gravity profiles, and seismic profiles was also considered. The intended use of the geologic framework model is to provide a geologic framework over the area of interest consistent with the level of detailed needed for hydrologic flow and radionuclide transport modeling through the UZ and for repository design. The model is limited by the availability of data and relative amount of geologic complexity found in an area. The geologic framework model is inherently limited by scale and content. The grid spacing used in

  16. Geologic Framework Model (GFM2000)

    Energy Technology Data Exchange (ETDEWEB)

    T. Vogt

    2004-08-26

    The purpose of this report is to document the geologic framework model, version GFM2000 with regard to input data, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, and the differences between GFM2000 and previous versions. The version number of this model reflects the year during which the model was constructed. This model supersedes the previous model version, documented in Geologic Framework Model (GFM 3.1) (CRWMS M&O 2000 [DIRS 138860]). The geologic framework model represents a three-dimensional interpretation of the geology surrounding the location of the monitored geologic repository for spent nuclear fuel and high-level radioactive waste at Yucca Mountain. The geologic framework model encompasses and is limited to an area of 65 square miles (168 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the geologic framework model (shown in Figure 1-1) were chosen to encompass the exploratory boreholes and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The upper surface of the model is made up of the surface topography and the depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The geologic framework model was constructed from geologic map and borehole data. Additional information from measured stratigraphic sections, gravity profiles, and seismic profiles was also considered. The intended use of the geologic framework model is to provide a geologic framework over the area of interest consistent with the level of detailed needed for hydrologic flow and radionuclide transport modeling through the UZ and for repository design. The model is limited by the availability of data and relative amount of geologic complexity found in an area. The geologic framework model is inherently limited by scale and content. The grid spacing used in the

  17. Trust framework for a secured routing in wireless sensor network

    Directory of Open Access Journals (Sweden)

    Ouassila Hoceini

    2015-11-01

    Full Text Available Traditional techniques to eliminate insider attacks developed for wired and wireless ad hoc networks are not well suited for wireless sensors networks due to their resource constraints nature. In order to protect WSNs against malicious and selfish behavior, some trust-based systems have recently been modeled. The resource efficiency and dependability of a trust system are the most fundamental requirements for any wireless sensor network (WSN. In this paper, we propose a Trust Framework for a Secured Routing in Wireless Sensor Network (TSR scheme, which works with clustered networks. This approach can effectively reduce the cost of trust evaluation and guarantee a better selection of safest paths that lead to the base station. Theoretical as well as simulation results show that our scheme requires less communication overheads and consumes less energy as compared to the current typical trust systems for WSNs. Moreover, it detects selfish and defective nodes and prevents us of insider attacks

  18. The AMES network in the 6th Framework Programme

    International Nuclear Information System (INIS)

    Sevini, F.; Debarberis, L.; Taylor, N.; Gerard, R.; English, C.; Brumovsky, M.

    2003-01-01

    The AMES (Ageing Materials European Strategy) European network started its activity in 1993 with the aim of studying ageing mechanisms and remedial procedures for structural materials used for nuclear reactor components. Operated by JRC-IE, it has been supporting the co-ordination of the project cluster throughout the 4th and 5th EURATOM Framework Programs, carrying out projects on with plant life management implications. Among them we can list the development of non-destructive techniques applied to thermal ageing and neutron embrittlement monitoring (AMES-NDT and GRETE), improved surveillance for VVER 440 reactors (COBRA), dosimetry (AMESDOSIMETRY, MADAM and REDOS), chemical composition effects on neutron embrittlement (PISA) and advanced fracture mechanics for integrity assessment (FRAME). Main frame of the network in the 5th Framework Programme is the ATHENA project, which is aimed at summarizing the obtained achievements and edit guidelines on important issues like the Master Curve, Effect of chemical composition on embrittlement rate in RPV steels, Re-embrittlement models validation after VVER-440 annealing and open issues in embrittlement of VVER type reactors. In the 6th EURATOM Framework Programme started in 2003 the network will be part of a broader initiative on PLIM including in a more integrated way NESC, ENIQ, NET and AMALIA networks. This paper shows an overview of the concluded projects, achievements of the running ones and open issues tackled in the 6th EURATOM FWP and a summary of the plans for a new broader network on NPP Plant Life management (SAFELIFE). (author)

  19. AN AUTOMATED NETWORK SECURITYCHECKING AND ALERT SYSTEM: A NEW FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Vivek Kumar Yadav

    2013-09-01

    Full Text Available Network security checking is a vital process to assess and to identify weaknesses in network for management of security. Insecure entry points of a network provide attackers an easy target to access and compromise. Open ports of network components such as firewalls, gateways and end systems are analogues to open gates of a building through which any one can get into. Network scanning is performed to identify insecure entry points in the network components. To find out vulnerabilities on these points vulnerability assessment is performed. So security checking consists of both activities- network scanning as well as vulnerability assessment. A single tool used for the security checking may not give reliable results. This paper presents a framework for assessing the security of a network using multiple Network Scanning and Vulnerability Assessment tools. The proposed framework is an extension of the framework given by Jun Yoon and Wontae Sim [1] which performs vulnerability scanning only. The framework presented here adds network scanning, alerting and reporting system to their framework. Network scanning and vulnerability tools together complement each other and make it amenable for centralized control and management. The reporting system of framework sends an email to the network administrator which contains detailed report (as attachment of security checking process. Alerting system sends a SMS message as an alert to the network administrator in case of severe threats found in the network. Initial results of the framework are encouraging and further work is in progress.

  20. Computer-Aided Modeling Framework

    DEFF Research Database (Denmark)

    Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

    Models are playing important roles in design and analysis of chemicals based products and the processes that manufacture them. Computer-aided methods and tools have the potential to reduce the number of experiments, which can be expensive and time consuming, and there is a benefit of working...... development and application. The proposed work is a part of the project for development of methods and tools that will allow systematic generation, analysis and solution of models for various objectives. It will use the computer-aided modeling framework that is based on a modeling methodology, which combines....... In this contribution, the concept of template-based modeling is presented and application is highlighted for the specific case of catalytic membrane fixed bed models. The modeling template is integrated in a generic computer-aided modeling framework. Furthermore, modeling templates enable the idea of model reuse...

  1. CMAQ Model Evaluation Framework

    Science.gov (United States)

    CMAQ is tested to establish the modeling system’s credibility in predicting pollutants such as ozone and particulate matter. Evaluation of CMAQ has been designed to assess the model’s performance for specific time periods and for specific uses.

  2. OWL Reasoning Framework over Big Biological Knowledge Network

    Science.gov (United States)

    Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

    2014-01-01

    Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

  3. A network Airline Revenue Management Framework Based on Deccomposition by Origins ans Destinations

    NARCIS (Netherlands)

    Birbil, S.I.; Frenk, J.B.G.; Gromicho Dos Santos, J.A.; Zhang, Shuzhong

    2014-01-01

    We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into

  4. Pythoscape: A framework for generation of large protein similarity networks

    OpenAIRE

    Babbitt, Patricia; Barber, AE; Babbitt, PC

    2012-01-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among pr

  5. A Framework for Video Modeling

    NARCIS (Netherlands)

    Petkovic, M.; Jonker, Willem

    In recent years, research in video databases has increased greatly, but relatively little work has been done in the area of semantic content-based retrieval. In this paper, we present a framework for video modelling with emphasis on semantic content of video data. The video data model presented

  6. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  7. Assessing citation networks for dissemination and implementation research frameworks.

    Science.gov (United States)

    Skolarus, Ted A; Lehmann, Todd; Tabak, Rachel G; Harris, Jenine; Lecy, Jesse; Sales, Anne E

    2017-07-28

    A recent review of frameworks used in dissemination and implementation (D&I) science described 61 judged to be related either to dissemination, implementation, or both. The current use of these frameworks and their contributions to D&I science more broadly has yet to be reviewed. For these reasons, our objective was to determine the role of these frameworks in the development of D&I science. We used the Web of Science™ Core Collection and Google Scholar™ to conduct a citation network analysis for the key frameworks described in a recent systematic review of D&I frameworks (Am J Prev Med 43(3):337-350, 2012). From January to August 2016, we collected framework data including title, reference, publication year, and citations per year and conducted descriptive and main path network analyses to identify those most important in holding the current citation network for D&I frameworks together. The source article contained 119 cited references, with 50 published articles and 11 documents identified as a primary framework reference. The average citations per year for the 61 frameworks reviewed ranged from 0.7 to 103.3 among articles published from 1985 to 2012. Citation rates from all frameworks are reported with citation network analyses for the framework review article and ten highly cited framework seed articles. The main path for the D&I framework citation network is presented. We examined citation rates and the main paths through the citation network to delineate the current landscape of D&I framework research, and opportunities for advancing framework development and use. Dissemination and implementation researchers and practitioners may consider frequency of framework citation and our network findings when planning implementation efforts to build upon this foundation and promote systematic advances in D&I science.

  8. E-Services quality assessment framework for collaborative networks

    Science.gov (United States)

    Stegaru, Georgiana; Danila, Cristian; Sacala, Ioan Stefan; Moisescu, Mihnea; Mihai Stanescu, Aurelian

    2015-08-01

    In a globalised networked economy, collaborative networks (CNs) are formed to take advantage of new business opportunities. Collaboration involves shared resources and capabilities, such as e-Services that can be dynamically composed to automate CN participants' business processes. Quality is essential for the success of business process automation. Current approaches mostly focus on quality of service (QoS)-based service selection and ranking algorithms, overlooking the process of service composition which requires interoperable, adaptable and secure e-Services to ensure seamless collaboration, data confidentiality and integrity. Lack of assessment of these quality attributes can result in e-Service composition failure. The quality of e-Service composition relies on the quality of each e-Service and on the quality of the composition process. Therefore, there is the need for a framework that addresses quality from both views: product and process. We propose a quality of e-Service composition (QoESC) framework for quality assessment of e-Service composition for CNs which comprises of a quality model for e-Service evaluation and guidelines for quality of e-Service composition process. We implemented a prototype considering a simplified telemedicine use case which involves a CN in e-Healthcare domain. To validate the proposed quality-driven framework, we analysed service composition reliability with and without using the proposed framework.

  9. SDN Based User-Centric Framework for Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Zhaoming Lu

    2016-01-01

    Full Text Available Due to the rapid growth of mobile data traffic, more and more basestations and access points (APs have been densely deployed to provide users with ubiquitous network access, which make current wireless network a complex heterogeneous network (HetNet. However, traditional wireless networks are designed with network-centric approaches where different networks have different quality of service (QoS strategies and cannot easily cooperate with each other to serve network users. Massive network infrastructures could not assure users perceived network and service quality, which is an indisputable fact. To address this issue, we design a new framework for heterogeneous wireless networks with the principle of user-centricity, refactoring the network from users’ perspective to suffice their requirements and preferences. Different from network-centric approaches, the proposed framework takes advantage of Software Defined Networking (SDN and virtualization technology, which will bring better perceived services quality for wireless network users. In the proposed user-centric framework, control plane and data plane are decoupled to manage the HetNets in a flexible and coadjutant way, and resource virtualization technology is introduced to abstract physical resources of HetNets into unified virtualized resources. Hence, ubiquitous and undifferentiated network connectivity and QoE (quality of experience driven fine-grained resource management could be achieved for wireless network users.

  10. A framework for unsupervised spam detection in social networking sites

    NARCIS (Netherlands)

    Bosma, M.; Meij, E.; Weerkamp, W.

    2012-01-01

    Social networking sites offer users the option to submit user spam reports for a given message, indicating this message is inappropriate. In this paper we present a framework that uses these user spam reports for spam detection. The framework is based on the HITS web link analysis framework and is

  11. Chain and network science: A research framework

    NARCIS (Netherlands)

    Omta, S.W.F.; Trienekens, J.H.; Beers, G.

    2001-01-01

    In this first article of the Journal on Chain and Network Science the base-line is set for a discussion on contents and scope of chain and network theory. Chain and network research is clustered into four main ‘streams’: Network theory, social capital theory, supply chain management and business

  12. Framework for cascade size calculations on random networks

    Science.gov (United States)

    Burkholz, Rebekka; Schweitzer, Frank

    2018-04-01

    We present a framework to calculate the cascade size evolution for a large class of cascade models on random network ensembles in the limit of infinite network size. Our method is exact and applies to network ensembles with almost arbitrary degree distribution, degree-degree correlations, and, in case of threshold models, for arbitrary threshold distribution. With our approach, we shift the perspective from the known branching process approximations to the iterative update of suitable probability distributions. Such distributions are key to capture cascade dynamics that involve possibly continuous quantities and that depend on the cascade history, e.g., if load is accumulated over time. As a proof of concept, we provide two examples: (a) Constant load models that cover many of the analytically tractable casacade models, and, as a highlight, (b) a fiber bundle model that was not tractable by branching process approximations before. Our derivations cover the whole cascade dynamics, not only their steady state. This allows us to include interventions in time or further model complexity in the analysis.

  13. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  14. Port Hamiltonian modeling of Power Networks

    NARCIS (Netherlands)

    van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R

    2012-01-01

    In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all

  15. Power Aware Simulation Framework for Wireless Sensor Networks and Nodes

    Directory of Open Access Journals (Sweden)

    Daniel Weber

    2008-07-01

    Full Text Available The constrained resources of sensor nodes limit analytical techniques and cost-time factors limit test beds to study wireless sensor networks (WSNs. Consequently, simulation becomes an essential tool to evaluate such systems.We present the power aware wireless sensors (PAWiS simulation framework that supports design and simulation of wireless sensor networks and nodes. The framework emphasizes power consumption capturing and hence the identification of inefficiencies in various hardware and software modules of the systems. These modules include all layers of the communication system, the targeted class of application itself, the power supply and energy management, the central processing unit (CPU, and the sensor-actuator interface. The modular design makes it possible to simulate heterogeneous systems. PAWiS is an OMNeT++ based discrete event simulator written in C++. It captures the node internals (modules as well as the node surroundings (network, environment and provides specific features critical to WSNs like capturing power consumption at various levels of granularity, support for mobility, and environmental dynamics as well as the simulation of timing effects. A module library with standardized interfaces and a power analysis tool have been developed to support the design and analysis of simulation models. The performance of the PAWiS simulator is comparable with other simulation environments.

  16. A distributed framework for inter-domain virtual network embedding

    Science.gov (United States)

    Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

    2013-03-01

    Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

  17. A Framework for Security Analysis of Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nanz, Sebastian; Hankin, Chris

    2006-01-01

    processes and the network's connectivity graph, which may change independently from protocol actions. We identify a property characterising an important aspect of security in this setting and express it using behavioural equivalences of the calculus. We complement this approach with a control flow analysis......We present a framework for specification and security analysis of communication protocols for mobile wireless networks. This setting introduces new challenges which are not being addressed by classical protocol analysis techniques. The main complication stems from the fact that the actions...... of intermediate nodes and their connectivity can no longer be abstracted into a single unstructured adversarial environment as they form an inherent part of the system's security. In order to model this scenario faithfully, we present a broadcast calculus which makes a clear distinction between the protocol...

  18. A Scalable Policy and SNMP Based Network Management Framework

    Institute of Scientific and Technical Information of China (English)

    LIU Su-ping; DING Yong-sheng

    2009-01-01

    Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.

  19. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  20. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  1. A Graph Based Framework to Model Virus Integration Sites

    Directory of Open Access Journals (Sweden)

    Raffaele Fronza

    2016-01-01

    Here, we addressed the challenge to: 1 define the notion of CIS on graph models, 2 demonstrate that the structure of CIS enters in the category of scale-free networks and 3 show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD as a testing dataset.

  2. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  3. A general framework for performance guaranteed green data center networking

    OpenAIRE

    Wang, Ting; Xia, Yu; Muppala, Jogesh; Hamdi, Mounir; Foufou, Sebti

    2014-01-01

    From the perspective of resource allocation and routing, this paper aims to save as much energy as possible in data center networks. We present a general framework, based on the blocking island paradigm, to try to maximize the network power conservation and minimize sacrifices of network performance and reliability. The bandwidth allocation mechanism together with power-aware routing algorithm achieve a bandwidth guaranteed tighter network. Besides, our fast efficient heuristics for allocatin...

  4. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  5. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling

  6. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  7. Eight challenges for network epidemic models

    Directory of Open Access Journals (Sweden)

    Lorenzo Pellis

    2015-03-01

    Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

  8. Instantiating a Global Network Measurement Framework

    Energy Technology Data Exchange (ETDEWEB)

    Tierney, Brian L.; Boote, Jeff; Boyd, Eric; Brown, Aaron; Grigoriev, Maxim; Metzger, Joe; Swany, Martin; Zekauskas, Matt; Zurawski, Jason

    2008-12-15

    perfSONAR is a web services-based infrastructure for collecting and publishing network performance monitoring. A primary goal of perfSONAR is making it easier to solve end-to-end performance problems on paths crossing several networks. It contains a set of services delivering performance measurements in a federated environment. These services act as an intermediate layer, between the performance measurement tools and the diagnostic or visualization applications. This layer is aimed at making and exchanging performance measurements across multiple networks and multiple user communities, using well-defined protocols. This paper summarizes the key perfSONAR components, and describes how they are deployed by the US-LHC community to monitor the networks distributing LHC data from CERN. All monitoring data described herein is publicly available, and we hope the availability of this data via a standard schema will inspire others to contribute to the effort by building network data analysis applications that use perfSONAR.

  9. Incremental Support Vector Machine Framework for Visual Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yuichi Motai

    2007-01-01

    Full Text Available Motivated by the emerging requirements of surveillance networks, we present in this paper an incremental multiclassification support vector machine (SVM technique as a new framework for action classification based on real-time multivideo collected by homogeneous sites. The technique is based on an adaptation of least square SVM (LS-SVM formulation but extends beyond the static image-based learning of current SVM methodologies. In applying the technique, an initial supervised offline learning phase is followed by a visual behavior data acquisition and an online learning phase during which the cluster head performs an ensemble of model aggregations based on the sensor nodes inputs. The cluster head then selectively switches on designated sensor nodes for future incremental learning. Combining sensor data offers an improvement over single camera sensing especially when the latter has an occluded view of the target object. The optimization involved alleviates the burdens of power consumption and communication bandwidth requirements. The resulting misclassification error rate, the iterative error reduction rate of the proposed incremental learning, and the decision fusion technique prove its validity when applied to visual sensor networks. Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and offers the advantage of reducing both the model training time and the information storage requirements of the overall system which makes it even more attractive for distributed sensor networks communication.

  10. A framework for automated service composition in collaborative networks

    NARCIS (Netherlands)

    Afsarmanesh, H.; Sargolzaei, M.; Shadi, M.

    2012-01-01

    This paper proposes a novel framework for automated software service composition that can significantly support and enhance collaboration among enterprises in service provision industry, such as in tourism insurance and e-commerce collaborative networks (CNs). Our proposed framework is founded on

  11. A versatile framework for cooperative hub network development

    NARCIS (Netherlands)

    Cruijssen, F.C.A.M.; Borm, P.; Dullaert, W.; Hamers, H.

    2010-01-01

    This paper introduces a framework for cooperative hub network development. Building a joint physical hub for the transshipment of goods is expensive and, therefore, involves considerable risks for cooperating companies. In a practical setting, it is unlikely that an entire network will be built at

  12. A versatile framework for cooperative hub network development

    NARCIS (Netherlands)

    Cruijssen, Frans; Borm, Peter; Dullaert, Wout; Hamers, Herbert

    This paper introduces a framework for cooperative hub network development. Building a joint physical hub for the transshipment of goods is expensive and, therefore, involves considerable risks for cooperating companies. In a practical setting, it is unlikely that an entire network will be built at

  13. A Framework for visualization of criminal networks

    DEFF Research Database (Denmark)

    Rasheed, Amer

    networks, network analysis, composites, temporal data visualization, clustering and hierarchical clustering of data but there are a number of areas which are overlooked by the researchers. Moreover there are some issues, for instance, lack of effective filtering techniques, computational overhead......This Ph.D. thesis describes research concerning the application of criminal network visualization in the field of investigative analysis. There are number of way with which the investigative analysis can locate the hidden motive behind any criminal activity. Firstly, the investigative analyst must...... have the ability to understand the criminal plot since a comprehensive plot is a pre-requisite to conduct an organized crime. Secondly, the investigator should understand the organization and structure of criminal network. The knowledge about these two aspects is vital in conducting an investigative...

  14. CoordSS: An Ontology Framework for Heterogeneous Networks Experimentation

    Directory of Open Access Journals (Sweden)

    V. Nejkovic

    2016-11-01

    Full Text Available Experimenting with HetNets environments is of importance because of the role that such environments have in next-generation cellular networks. In this paper, the CoordSS ontology experimentation framework is proposed with an aim to support experimenting with HetNets environments on wireless networking testbeds. In the framework, domain and system ontologies are adopted for formal representation of the knowledge about the context of the problem. This paper outlines implementation details of ontologies in the CoordSS experimentation framework. The synergy between semantic and cognitive computing is introduced as the theoretical foundation of the paper.

  15. A general modeling framework for describing spatially structured population dynamics

    Science.gov (United States)

    Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

    2017-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  16. Neural networks in economic modelling : An empirical study

    NARCIS (Netherlands)

    Verkooijen, W.J.H.

    1996-01-01

    This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a

  17. Geologic Framework Model Analysis Model Report

    Energy Technology Data Exchange (ETDEWEB)

    R. Clayton

    2000-12-19

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M&O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and the

  18. Geologic Framework Model Analysis Model Report

    International Nuclear Information System (INIS)

    Clayton, R.

    2000-01-01

    The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompass the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M and O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models and

  19. A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.

    Science.gov (United States)

    Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao

    2017-06-16

    This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.

  20. Unraveling networked learning initiatives: an analytic framework

    NARCIS (Netherlands)

    Rusman, Ellen; Prinsen, Fleur; Vermeulen, Marjan

    2016-01-01

    Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences

  1. Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

    DEFF Research Database (Denmark)

    Saa, Pedro A.; Nielsen, Lars K.

    2017-01-01

    Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...

  2. Crystallization Kinetics within a Generic Modelling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist

    2013-01-01

    An existing generic modelling framework has been expanded with tools for kinetic model analysis. The analysis of kinetics is carried out within the framework where kinetic constitutive models are collected, analysed and utilized for the simulation of crystallization operations. A modelling...... procedure is proposed to gain the information of crystallization operation kinetic model analysis and utilize this for faster evaluation of crystallization operations....

  3. A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems

    DEFF Research Database (Denmark)

    Han, Pujie; Zhai, Zhengjun; Nielsen, Brian

    2018-01-01

    This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...

  4. A Simulation and Modeling Framework for Space Situational Awareness

    International Nuclear Information System (INIS)

    Olivier, S.S.

    2008-01-01

    This paper describes the development and initial demonstration of a new, integrated modeling and simulation framework, encompassing the space situational awareness enterprise, for quantitatively assessing the benefit of specific sensor systems, technologies and data analysis techniques. The framework is based on a flexible, scalable architecture to enable efficient, physics-based simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel computer systems available, for example, at Lawrence Livermore National Laboratory. The details of the modeling and simulation framework are described, including hydrodynamic models of satellite intercept and debris generation, orbital propagation algorithms, radar cross section calculations, optical brightness calculations, generic radar system models, generic optical system models, specific Space Surveillance Network models, object detection algorithms, orbit determination algorithms, and visualization tools. The use of this integrated simulation and modeling framework on a specific scenario involving space debris is demonstrated

  5. Energy modelling in sensor networks

    Science.gov (United States)

    Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

    2007-06-01

    Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

  6. Handover Framework for Relay Enhanced LTE Networks

    DEFF Research Database (Denmark)

    Teyeb, Oumer Mohammed; Van Phan, Vinh; Raaf, Bernhard

    2009-01-01

    Relaying is one of the proposed technologies for future releases of UTRAN Long Term Evolution (LTE) networks. Introducing relaying is expected to increase the coverage and capacity of LTE networks. In order to enable relaying, the architecture, protocol and radio resource management procedures...... of LTE, such as handover, have to be modified. A user can be handed over not only between two base stations, but also between relays and base stations, and between two relays. With the introduction of relaying, there is a need for a new procedure to hand over a relay and all its associated users...... to another base station, allowing a flexible and dynamic relay deployment. In this paper, we extend the LTE release 8 handover mechanisms so that it can accommodate these new handover functionalities in a flexible manner....

  7. GeoFramework: A Modeling Framework for Solid Earth Geophysics

    Science.gov (United States)

    Gurnis, M.; Aivazis, M.; Tromp, J.; Tan, E.; Thoutireddy, P.; Liu, Q.; Choi, E.; Dicaprio, C.; Chen, M.; Simons, M.; Quenette, S.; Appelbe, B.; Aagaard, B.; Williams, C.; Lavier, L.; Moresi, L.; Law, H.

    2003-12-01

    As data sets in geophysics become larger and of greater relevance to other earth science disciplines, and as earth science becomes more interdisciplinary in general, modeling tools are being driven in new directions. There is now a greater need to link modeling codes to one another, link modeling codes to multiple datasets, and to make modeling software available to non modeling specialists. Coupled with rapid progress in computer hardware (including the computational speed afforded by massively parallel computers), progress in numerical algorithms, and the introduction of software frameworks, these lofty goals of merging software in geophysics are now possible. The GeoFramework project, a collaboration between computer scientists and geoscientists, is a response to these needs and opportunities. GeoFramework is based on and extends Pyre, a Python-based modeling framework, recently developed to link solid (Lagrangian) and fluid (Eulerian) models, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. The utility and generality of Pyre as a general purpose framework in science is now being recognized. Besides its use in engineering and geophysics, it is also being used in particle physics and astronomy. Geology and geophysics impose their own unique requirements on software frameworks which are not generally available in existing frameworks and so there is a need for research in this area. One of the special requirements is the way Lagrangian and Eulerian codes will need to be linked in time and space within a plate tectonics context. GeoFramework has grown beyond its initial goal of linking a limited number of exiting codes together. The following codes are now being reengineered within the context of Pyre: Tecton, 3-D FE Visco-elastic code for lithospheric relaxation; CitComS, a code for spherical mantle convection; SpecFEM3D, a SEM code for global and regional seismic waves; eqsim, a FE code for dynamic

  8. A High-Level Petri Net Framework for Genetic Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Banks Richard

    2007-12-01

    Full Text Available To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.

  9. A Unified Monitoring Framework for Energy Consumption and Network Traffic

    Directory of Open Access Journals (Sweden)

    Florentin Clouet

    2015-08-01

    Full Text Available Providing experimenters with deep insight about the effects of their experiments is a central feature of testbeds. In this paper, we describe Kwapi, a framework designed in the context of the Grid'5000 testbed, that unifies measurements for both energy consumption and network traffic. Because all measurements are taken at the infrastructure level (using sensors in power and network equipment, using this framework has no dependencies on the experiments themselves. Initially designed for OpenStack infrastructures, the Kwapi framework allows monitoring and reporting of energy consumption of distributed platforms. In this article, we present the extension of Kwapi to network monitoring, and outline how we overcame several challenges: scaling to a testbed the size of Grid'5000 while still providing high-frequency measurements; providing long-term loss-less storage of measurements; handling operational issues when deploying such a tool on a real infrastructure.

  10. On effectiveness of network sensor-based defense framework

    Science.gov (United States)

    Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

    2012-06-01

    Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

  11. SDN-Enabled Communication Network Framework for Energy Internet

    Directory of Open Access Journals (Sweden)

    Zhaoming Lu

    2017-01-01

    Full Text Available To support distributed energy generators and improve energy utilization, energy Internet has attracted global research focus. In China, energy Internet has been proposed as an important issue of government and institutes. However, managing a large amount of distributed generators requires smart, low-latency, reliable, and safe networking infrastructure, which cannot be supported by traditional networks in power grids. In order to design and construct smart and flexible energy Internet, we proposed a software defined network framework with both microgrid cluster level and global grid level designed by a hierarchical manner, which will bring flexibility, efficiency, and reliability for power grid networks. Finally, we evaluate and verify the performance of this framework in terms of latency, reliability, and security by both theoretical analysis and real-world experiments.

  12. Maintenance Management in Network Utilities Framework and Practical Implementation

    CERN Document Server

    Gómez Fernández, Juan F

    2012-01-01

    In order to satisfy the needs of their customers, network utilities require specially developed maintenance management capabilities. Maintenance Management information systems are essential to ensure control, gain knowledge and improve-decision making in companies dealing with network infrastructure, such as distribution of gas, water, electricity and telecommunications. Maintenance Management in Network Utilities studies specified characteristics of maintenance management in this sector to offer a practical approach to defining and implementing  the best management practices and suitable frameworks.   Divided into three major sections, Maintenance Management in Network Utilities defines a series of stages which can be followed to manage maintenance frameworks properly. Different case studies provide detailed descriptions which illustrate the experience in real company situations. An introduction to the concepts is followed by main sections including: • A Literature Review: covering the basic concepts an...

  13. Quantifying structural uncertainty on fault networks using a marked point process within a Bayesian framework

    Science.gov (United States)

    Aydin, Orhun; Caers, Jef Karel

    2017-08-01

    Faults are one of the building-blocks for subsurface modeling studies. Incomplete observations of subsurface fault networks lead to uncertainty pertaining to location, geometry and existence of faults. In practice, gaps in incomplete fault network observations are filled based on tectonic knowledge and interpreter's intuition pertaining to fault relationships. Modeling fault network uncertainty with realistic models that represent tectonic knowledge is still a challenge. Although methods that address specific sources of fault network uncertainty and complexities of fault modeling exists, a unifying framework is still lacking. In this paper, we propose a rigorous approach to quantify fault network uncertainty. Fault pattern and intensity information are expressed by means of a marked point process, marked Strauss point process. Fault network information is constrained to fault surface observations (complete or partial) within a Bayesian framework. A structural prior model is defined to quantitatively express fault patterns, geometries and relationships within the Bayesian framework. Structural relationships between faults, in particular fault abutting relations, are represented with a level-set based approach. A Markov Chain Monte Carlo sampler is used to sample posterior fault network realizations that reflect tectonic knowledge and honor fault observations. We apply the methodology to a field study from Nankai Trough & Kumano Basin. The target for uncertainty quantification is a deep site with attenuated seismic data with only partially visible faults and many faults missing from the survey or interpretation. A structural prior model is built from shallow analog sites that are believed to have undergone similar tectonics compared to the site of study. Fault network uncertainty for the field is quantified with fault network realizations that are conditioned to structural rules, tectonic information and partially observed fault surfaces. We show the proposed

  14. PRESS: A Novel Framework of Trajectory Compression in Road Networks

    OpenAIRE

    Song, Renchu; Sun, Weiwei; Zheng, Baihua; Zheng, Yu

    2014-01-01

    Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory Compression), to effectively compress trajectory data under road network constraints. Different from existing work, PRESS proposes a novel representation for trajectories to separate the spatial representation of a trajectory from the temporal representation, and proposes a Hybrid Spatial Compression (HSC) algorithm ...

  15. A framework to find the logic backbone of a biological network.

    Science.gov (United States)

    Maheshwari, Parul; Albert, Réka

    2017-12-06

    Cellular behaviors are governed by interaction networks among biomolecules, for example gene regulatory and signal transduction networks. An often used dynamic modeling framework for these networks, Boolean modeling, can obtain their attractors (which correspond to cell types and behaviors) and their trajectories from an initial state (e.g. a resting state) to the attractors, for example in response to an external signal. The existing methods however do not elucidate the causal relationships between distant nodes in the network. In this work, we propose a simple logic framework, based on categorizing causal relationships as sufficient or necessary, as a complement to Boolean networks. We identify and explore the properties of complex subnetworks that are distillable into a single logic relationship. We also identify cyclic subnetworks that ensure the stabilization of the state of participating nodes regardless of the rest of the network. We identify the logic backbone of biomolecular networks, consisting of external signals, self-sustaining cyclic subnetworks (stable motifs), and output nodes. Furthermore, we use the logic framework to identify crucial nodes whose override can drive the system from one steady state to another. We apply these techniques to two biological networks: the epithelial-to-mesenchymal transition network corresponding to a developmental process exploited in tumor invasion, and the network of abscisic acid induced stomatal closure in plants. We find interesting subnetworks with logical implications in these networks. Using these subgraphs and motifs, we efficiently reduce both networks to succinct backbone structures. The logic representation identifies the causal relationships between distant nodes and subnetworks. This knowledge can form the basis of network control or used in the reverse engineering of networks.

  16. Performance testing framework for smart grid communication network

    International Nuclear Information System (INIS)

    Quang, D N; See, O H; Chee, L L; Xuen, C Y; Karuppiah, S

    2013-01-01

    Smart grid communication network is comprised of different communication mediums and technologies. Performance evaluation is one of the main concerns in smart grid communication system. In any smart grid communication implementation, to determine the performance factor of the network, a testing of an end-to-end process flow is required. Therefore, an effective and coordinated testing procedure plays a crucial role in evaluating the performance of smart grid communications. In this paper, a testing framework is proposed as a guideline to analyze and assess the performance of smart grid communication network.

  17. Information Source Selection and Management Framework in Wireless Sensor Network

    DEFF Research Database (Denmark)

    Tobgay, Sonam; Olsen, Rasmus Løvenstein; Prasad, Ramjee

    2013-01-01

    information source selection and management framework and presents an algorithm which selects the information source based on the information mismatch probability [1]. The sampling rate for every access is decided as per the maximum allowable power consumption limit. Index Terms-wireless sensor network...

  18. An optimisation framework for determination of capacity in railway networks

    DEFF Research Database (Denmark)

    Jensen, Lars Wittrup

    2015-01-01

    network based on a mix of train types, the infrastructure and rolling stock used. The framework consist of two steps. In the first step the maximum number of trains is found according to the predefined mix of train types. In the second step additional trains are added based on weights assigned...

  19. Towards a theoretical framework for analyzing complex linguistic networks

    CERN Document Server

    Lücking, Andy; Banisch, Sven; Blanchard, Philippe; Job, Barbara

    2016-01-01

    The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities.This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statisticalmodels of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information scien...

  20. Pythoscape: a framework for generation of large protein similarity networks.

    Science.gov (United States)

    Barber, Alan E; Babbitt, Patricia C

    2012-11-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

  1. Wireless Sensor Networks Framework for Indoor Temperature Regulation

    DEFF Research Database (Denmark)

    Stojkoska, Biljana; Popovska Avramova, Andrijana

    2013-01-01

    Wireless Sensor Networks take a major part in our everyday lives by enhancing systems for home automation, health-care, temperature control, energy consumption monitoring etc. In this paper we focus on a system used for temperature regulation for homes, educational, industrial, commercial premises...... etc. We propose a framework for indoor regulation and optimization of temperature using wireless sensor networks based on ZigBee. Methods for optimal temperature regulation are suggested and discussed. The framework is based on methods that provide energy savings by reducing the amount of data...... transmissions through prediction methods. Additionally the framework explores techniques for localization, such that the location of the nodes is used for optimization of the temperature settings. Information on node location is used to provide the most optimal tradeo between the time it takes to reach...

  2. An efficient automated parameter tuning framework for spiking neural networks.

    Science.gov (United States)

    Carlson, Kristofor D; Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L

    2014-01-01

    As the desire for biologically realistic spiking neural networks (SNNs) increases, tuning the enormous number of open parameters in these models becomes a difficult challenge. SNNs have been used to successfully model complex neural circuits that explore various neural phenomena such as neural plasticity, vision systems, auditory systems, neural oscillations, and many other important topics of neural function. Additionally, SNNs are particularly well-adapted to run on neuromorphic hardware that will support biological brain-scale architectures. Although the inclusion of realistic plasticity equations, neural dynamics, and recurrent topologies has increased the descriptive power of SNNs, it has also made the task of tuning these biologically realistic SNNs difficult. To meet this challenge, we present an automated parameter tuning framework capable of tuning SNNs quickly and efficiently using evolutionary algorithms (EA) and inexpensive, readily accessible graphics processing units (GPUs). A sample SNN with 4104 neurons was tuned to give V1 simple cell-like tuning curve responses and produce self-organizing receptive fields (SORFs) when presented with a random sequence of counterphase sinusoidal grating stimuli. A performance analysis comparing the GPU-accelerated implementation to a single-threaded central processing unit (CPU) implementation was carried out and showed a speedup of 65× of the GPU implementation over the CPU implementation, or 0.35 h per generation for GPU vs. 23.5 h per generation for CPU. Additionally, the parameter value solutions found in the tuned SNN were studied and found to be stable and repeatable. The automated parameter tuning framework presented here will be of use to both the computational neuroscience and neuromorphic engineering communities, making the process of constructing and tuning large-scale SNNs much quicker and easier.

  3. Cytoview: Development of a cell modelling framework

    Indian Academy of Sciences (India)

    2007-07-06

    Jul 6, 2007 ... The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves ...

  4. Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

    OpenAIRE

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

    2014-01-01

    We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

  5. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  6. A framework for sustainable interorganizational business model

    OpenAIRE

    Neupane, Ganesh Prasad; Haugland, Sven A.

    2016-01-01

    Drawing on literature on business model innovations and sustainability, this paper develops a framework for sustainable interorganizational business models. The aim of the framework is to enhance the sustainability of firms’ business models by enabling firms to create future value by taking into account environmental, social and economic factors. The paper discusses two themes: (1) application of the term sustainability to business model innovation, and (2) implications of integrating sustain...

  7. A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

    Science.gov (United States)

    Kentzoglanakis, Kyriakos; Poole, Matthew

    2012-01-01

    In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.

  8. A permutation testing framework to compare groups of brain networks.

    Science.gov (United States)

    Simpson, Sean L; Lyday, Robert G; Hayasaka, Satoru; Marsh, Anthony P; Laurienti, Paul J

    2013-01-01

    Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

  9. Conceptual Framework for Developing a Diabetes Information Network.

    Science.gov (United States)

    Riazi, Hossein; Langarizadeh, Mostafa; Larijani, Bagher; Shahmoradi, Leila

    2016-06-01

    To provide a conceptual framework for managing diabetic patient care, and creating an information network for clinical research. A wide range of information technology (IT) based interventions such as distance learning, diabetes registries, personal or electronic health record systems, clinical information systems, and clinical decision support systems have so far been used in supporting diabetic care. Previous studies demonstrated that IT could improve diabetes care at its different aspects. There is however no comprehensive conceptual framework that defines how different IT applications can support diverse aspects of this care. Therefore, a conceptual framework that combines different IT solutions into a wide information network for improving care processes and for research purposes is widely lacking. In this study we describe the theoretical underpin of a big project aiming at building a wide diabetic information network namely DIANET. A literature review and a survey of national programs and existing regulations for diabetes management was conducted in order to define different aspects of diabetic care that should be supported by IT solutions. Both qualitative and quantitative research methods were used in this study. In addition to the results of a previous systematic literature review, two brainstorming and three expert panel sessions were conducted to identify requirements of a comprehensive information technology solution. Based on these inputs, the requirements for creating a diabetes information network were identified and used to create a questionnaire based on 9-point Likert scale. The questionnaire was finalized after removing some items based on calculated content validity ratio and content validity index coefficients. Cronbach's alpha reliability coefficient was also calculated (αTotal= 0.98, Pconceptual framework. The questionnaires were returned by 10 clinicians. Each requirement item was labeled as essential, semi-essential, or non

  10. Performance modeling, stochastic networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi R

    2013-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan

  11. Interference Calculus A General Framework for Interference Management and Network Utility Optimization

    CERN Document Server

    Schubert, Martin

    2012-01-01

    This book develops a mathematical framework for modeling and optimizing interference-coupled multiuser systems. At the core of this framework is the concept of general interference functions, which provides a simple means of characterizing interdependencies between users. The entire analysis builds on the two core axioms scale-invariance and monotonicity. The proposed network calculus has its roots in power control theory and wireless communications. It adds theoretical tools for analyzing the typical behavior of interference-coupled networks. In this way it complements existing game-theoretic approaches. The framework should also be viewed in conjunction with optimization theory. There is a fruitful interplay between the theory of interference functions and convex optimization theory. By jointly exploiting the properties of interference functions, it is possible to design algorithms that outperform general-purpose techniques that only exploit convexity. The title “network calculus” refers to the fact tha...

  12. CIMS: A FRAMEWORK FOR INFRASTRUCTURE INTERDEPENDENCY MODELING AND ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Donald D. Dudenhoeffer; May R. Permann; Milos Manic

    2006-12-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, utilities, telecommunication, and even financial networks. While modeling and simulation tools have provided insight into the behavior of individual infrastructure networks, a far less understood area is that of the interrelationships among multiple infrastructure networks including the potential cascading effects that may result due to these interdependencies. This paper first describes infrastructure interdependencies as well as presenting a formalization of interdependency types. Next the paper describes a modeling and simulation framework called CIMS© and the work that is being conducted at the Idaho National Laboratory (INL) to model and simulate infrastructure interdependencies and the complex behaviors that can result.

  13. Crystallization Kinetics within a Generic Modeling Framework

    DEFF Research Database (Denmark)

    Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist V.

    2014-01-01

    of employing a well-structured model library for storage, use/reuse, and analysis of the kinetic models are highlighted. Examples illustrating the application of the modeling framework for kinetic model discrimination related to simulation of specific crystallization scenarios and for kinetic model parameter......A new and extended version of a generic modeling framework for analysis and design of crystallization operations is presented. The new features of this framework are described, with focus on development, implementation, identification, and analysis of crystallization kinetic models. Issues related...... to the modeling of various kinetic phenomena like nucleation, growth, agglomeration, and breakage are discussed in terms of model forms, model parameters, their availability and/or estimation, and their selection and application for specific crystallization operational scenarios under study. The advantages...

  14. A Unified Framework for Systematic Model Improvement

    DEFF Research Database (Denmark)

    Kristensen, Niels Rode; Madsen, Henrik; Jørgensen, Sten Bay

    2003-01-01

    A unified framework for improving the quality of continuous time models of dynamic systems based on experimental data is presented. The framework is based on an interplay between stochastic differential equation (SDE) modelling, statistical tests and multivariate nonparametric regression. This co......-batch bioreactor, where it is illustrated how an incorrectly modelled biomass growth rate can be pinpointed and an estimate provided of the functional relation needed to properly describe it....

  15. Frameworks for understanding and describing business models

    DEFF Research Database (Denmark)

    Nielsen, Christian; Roslender, Robin

    2014-01-01

    This chapter provides in a chronological fashion an introduction to six frameworks that one can apply to describing, understanding and also potentially innovating business models. These six frameworks have been chosen carefully as they represent six very different perspectives on business models...... and in this manner “complement” each other. There are a multitude of varying frameworks that could be chosen from and we urge the reader to search and trial these for themselves. The six chosen models (year of release in parenthesis) are: • Service-Profit Chain (1994) • Strategic Systems Auditing (1997) • Strategy...... Maps (2001) • Intellectual Capital Statements (2003) • Chesbrough’s framework for Open Business Models (2006) • Business Model Canvas (2008)...

  16. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  17. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  18. User Identification Framework in Social Network Services Environment

    Directory of Open Access Journals (Sweden)

    Brijesh BAKARIYA

    2014-01-01

    Full Text Available Social Network Service is a one of the service where people may communicate with one an-other; and may also exchange messages even of any type of audio or video communication. Social Network Service as name suggests a type of network. Such type of web application plays a dominant role in internet technology. In such type of online community, people may share their common interest. Facebook LinkedIn, orkut and many more are the Social Network Service and it is good medium of making link with people having unique or common interest and goals. But the problem of privacy protection is a big issue in today’s world. As social networking sites allows anonymous users to share information of other stuffs. Due to which cybercrime is also increasing to a rapid extent. In this article we preprocessed the web log data of Social Network Services and assemble that data on the basis of image file format like jpg, jpeg, gif, png, bmp etc. and also propose a framework for victim’s identification.

  19. A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

    Science.gov (United States)

    Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan

    2015-01-01

    Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859

  20. A probabilistic computational framework for bridge network optimal maintenance scheduling

    International Nuclear Information System (INIS)

    Bocchini, Paolo; Frangopol, Dan M.

    2011-01-01

    This paper presents a probabilistic computational framework for the Pareto optimization of the preventive maintenance applications to bridges of a highway transportation network. The bridge characteristics are represented by their uncertain reliability index profiles. The in/out of service states of the bridges are simulated taking into account their correlation structure. Multi-objective Genetic Algorithms have been chosen as numerical tool for the solution of the optimization problem. The design variables of the optimization are the preventive maintenance schedules of all the bridges of the network. The two conflicting objectives are the minimization of the total present maintenance cost and the maximization of the network performance indicator. The final result is the Pareto front of optimal solutions among which the managers should chose, depending on engineering and economical factors. A numerical example illustrates the application of the proposed approach.

  1. An Integrated Hydro-Economic Modelling Framework to Evaluate Water Allocation Strategies I: Model Development.

    NARCIS (Netherlands)

    George, B.; Malano, H.; Davidson, B.; Hellegers, P.; Bharati, L.; Sylvain, M.

    2011-01-01

    In this paper an integrated modelling framework for water resources planning and management that can be used to carry out an analysis of alternative policy scenarios for water allocation and use is described. The modelling approach is based on integrating a network allocation model (REALM) and a

  2. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  3. Feature network models for proximity data : statistical inference, model selection, network representations and links with related models

    NARCIS (Netherlands)

    Frank, Laurence Emmanuelle

    2006-01-01

    Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor

  4. Model-based DSL frameworks

    NARCIS (Netherlands)

    Ivanov, Ivan; Bézivin, J.; Jouault, F.; Valduriez, P.

    2006-01-01

    More than five years ago, the OMG proposed the Model Driven Architecture (MDA™) approach to deal with the separation of platform dependent and independent aspects in information systems. Since then, the initial idea of MDA evolved and Model Driven Engineering (MDE) is being increasingly promoted to

  5. Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

    Science.gov (United States)

    Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

    2014-12-01

    Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

  6. A useful framework for optimal replacement models

    International Nuclear Information System (INIS)

    Aven, Terje; Dekker, Rommert

    1997-01-01

    In this note we present a general framework for optimization of replacement times. It covers a number of models, including various age and block replacement models, and allows a uniform analysis for all these models. A relation to the marginal cost concept is described

  7. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  8. A VGI data integration framework based on linked data model

    Science.gov (United States)

    Wan, Lin; Ren, Rongrong

    2015-12-01

    This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

  9. Exploring intellectual capital through social network analysis: a conceptual framework

    Directory of Open Access Journals (Sweden)

    Ivana Tichá

    2011-01-01

    Full Text Available The purpose of this paper is to develop a framework to assess intellectual capital. Intellectual capital is a key element in an organization’s future earning potential. Theoretical and empirical studies show that it is the unique combination of the different elements of intellectual capital and tangible investments that determines an enterprise´s competitive advantage. Intellectual capital has been defined as the combination of an organization´s human, organizational and relational resources and activities. It includes the knowledge, skills, experience and abilities of the employees, its R&D activities, organizational, routines, procedures, systems, databases and its Intellectual Property Rights, as well as all the resources linked to its external relationships, such as with its customers, suppliers, R&D partners, etc. This paper focuses on the relational capital and attempts to suggest a conceptual framework to assess this part of intellectual capital applying social network analysis approach. The SNA approach allows for mapping and measuring of relationships and flows between, people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The conceptual framework is developed for the assessment of collaborative networks in the Czech higher education sector as the representation of its relational capital. It also builds on the previous work aiming at proposal of methodology guiding efforts to report intellectual capital at the Czech public universities.

  10. A Novel Message Scheduling Framework for Delay Tolerant Networks Routing

    KAUST Repository

    Elwhishi, Ahmed

    2013-05-01

    Multicopy routing strategies have been considered the most applicable approaches to achieve message delivery in Delay Tolerant Networks (DTNs). Epidemic routing and two-hop forwarding routing are two well-reported approaches for delay tolerant networks routing which allow multiple message replicas to be launched in order to increase message delivery ratio and/or reduce message delivery delay. This advantage, nonetheless, is at the expense of additional buffer space and bandwidth overhead. Thus, to achieve efficient utilization of network resources, it is important to come up with an effective message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. This paper investigates a new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive simulation results show that the proposed message scheduling framework can achieve better performance than its counterparts.

  11. Developing a Framework for Effective Network Capacity Planning

    Science.gov (United States)

    Yaprak, Ece

    2005-01-01

    As Internet traffic continues to grow exponentially, developing a clearer understanding of, and appropriately measuring, network's performance is becoming ever more critical. An important challenge faced by the Information Resources Directorate (IRD) at the Johnson Space Center in this context remains not only monitoring and maintaining a secure network, but also better understanding the capacity and future growth potential boundaries of its network. This requires capacity planning which involves modeling and simulating different network alternatives, and incorporating changes in design as technologies, components, configurations, and applications change, to determine optimal solutions in light of IRD's goals, objectives and strategies. My primary task this summer was to address this need. I evaluated network-modeling tools from OPNET Technologies Inc. and Compuware Corporation. I generated a baseline model for Building 45 using both tools by importing "real" topology/traffic information using IRD's various network management tools. I compared each tool against the other in terms of the advantages and disadvantages of both tools to accomplish IRD's goals. I also prepared step-by-step "how to design a baseline model" tutorial for both OPNET and Compuware products.

  12. Graphical Model Debugger Framework for Embedded Systems

    DEFF Research Database (Denmark)

    Zeng, Kebin

    2010-01-01

    Model Driven Software Development has offered a faster way to design and implement embedded real-time software by moving the design to a model level, and by transforming models to code. However, the testing of embedded systems has remained at the code level. This paper presents a Graphical Model...... Debugger Framework, providing an auxiliary avenue of analysis of system models at runtime by executing generated code and updating models synchronously, which allows embedded developers to focus on the model level. With the model debugger, embedded developers can graphically test their design model...

  13. Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data

    Science.gov (United States)

    Wong, John-Michael; Stojadinovic, Bozidar

    2005-05-01

    A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

  14. A Stochastic Multiobjective Optimization Framework for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Shibo He

    2010-01-01

    Full Text Available In wireless sensor networks (WSNs, there generally exist many different objective functions to be optimized. In this paper, we propose a stochastic multiobjective optimization approach to solve such kind of problem. We first formulate a general multiobjective optimization problem. We then decompose the optimization formulation through Lagrange dual decomposition and adopt the stochastic quasigradient algorithm to solve the primal-dual problem in a distributed way. We show theoretically that our algorithm converges to the optimal solution of the primal problem by using the knowledge of stochastic programming. Furthermore, the formulation provides a general stochastic multiobjective optimization framework for WSNs. We illustrate how the general framework works by considering an example of the optimal rate allocation problem in multipath WSNs with time-varying channel. Extensive simulation results are given to demonstrate the effectiveness of our algorithm.

  15. A framework for API solubility modelling

    DEFF Research Database (Denmark)

    Conte, Elisa; Gani, Rafiqul; Crafts, Peter

    . In addition, most of the models are not predictive and requires experimental data for the calculation of the needed parameters. This work aims at developing an efficient framework for the solubility modelling of Active Pharmaceutical Ingredients (API) in water and organic solvents. With this framework......-SAFT) are used for solubility calculations when the needed interaction parameters or experimental data are available. The CI-UNIFAC is instead used when the previous models lack interaction parameters or when solubility data are not available. A new GC+ model for APIs solvent selection based...... on the hydrophobicity, hydrophilicity and polarity information of the API and solvent is also developed, for performing fast solvent selection and screening. Eventually, all the previous developments are integrated in a framework for their efficient and integrated use. Two case studies are presented: the first...

  16. A mixed model framework for teratology studies.

    Science.gov (United States)

    Braeken, Johan; Tuerlinckx, Francis

    2009-10-01

    A mixed model framework is presented to model the characteristic multivariate binary anomaly data as provided in some teratology studies. The key features of the model are the incorporation of covariate effects, a flexible random effects distribution by means of a finite mixture, and the application of copula functions to better account for the relation structure of the anomalies. The framework is motivated by data of the Boston Anticonvulsant Teratogenesis study and offers an integrated approach to investigate substantive questions, concerning general and anomaly-specific exposure effects of covariates, interrelations between anomalies, and objective diagnostic measurement.

  17. Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment

    Directory of Open Access Journals (Sweden)

    Anthony Halog

    2011-02-01

    Full Text Available The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA; and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA and sustainability network theory (SNT. The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.

  18. Concurrent enterprise: a conceptual framework for enterprise supply-chain network activities

    Science.gov (United States)

    Addo-Tenkorang, Richard; Helo, Petri T.; Kantola, Jussi

    2017-04-01

    Supply-chain management (SCM) in manufacturing industries has evolved significantly over the years. Recently, a lot more relevant research has picked up on the development of integrated solutions. Thus, seeking a collaborative optimisation of geographical, just-in-time (JIT), quality (customer demand/satisfaction) and return-on-investment (profits), aspects of organisational management and planning through 'best practice' business-process management - concepts and application; employing system tools such as certain applications/aspects of enterprise resource planning (ERP) - SCM systems information technology (IT) enablers to enhance enterprise integrated product development/concurrent engineering principles. This article assumed three main organisation theory applications in positioning its assumptions. Thus, proposing a feasible industry-specific framework not currently included within the SCOR model's level four (4) implementation level, as well as other existing SCM integration reference models such as in the MIT process handbook's - Process Interchange Format (PIF), the TOVE project, etc. which could also be replicated in other SCs. However, the wider focus of this paper's contribution will be concentrated on a complimentary proposed framework to the SCC's SCOR reference model. Quantitative empirical closed-ended questionnaires in addition to the main data collected from a qualitative empirical real-life industrial-based pilot case study were used: To propose a conceptual concurrent enterprise framework for SCM network activities. This research adopts a design structure matrix simulation approach analysis to propose an optimal enterprise SCM-networked value-adding, customised master data-management platform/portal for efficient SCM network information exchange and an effective supply-chain (SC) network systems-design teams' structure. Furthermore, social network theory analysis will be employed in a triangulation approach with statistical correlation analysis

  19. Driver Performance Model: 1. Conceptual Framework

    National Research Council Canada - National Science Library

    Heimerl, Joseph

    2001-01-01

    ...'. At the present time, no such comprehensive model exists. This report discusses a conceptual framework designed to encompass the relationships, conditions, and constraints related to direct, indirect, and remote modes of driving and thus provides a guide or 'road map' for the construction and creation of a comprehensive driver performance model.

  20. A framework for interpreting functional networks in schizophrenia

    Directory of Open Access Journals (Sweden)

    Peter eWilliamson

    2012-06-01

    Full Text Available Some promising genetic correlates of schizophrenia have emerged in recent years but none explain more than a small fraction of cases. The challenge of our time is to characterize the neuronal networks underlying schizophrenia and other neuropsychiatric illnesses. It has been proposed that schizophrenia arises from a uniquely human brain network associated with directed effort including the dorsal anterior and posterior cingulate cortex, auditory cortex, and hippocampus and while mood disorders arise from a different brain network associated with emotional encoding including the ventral anterior cingulate cortex, orbital frontal cortex, and amygdala. Both interact with a representation network including the frontal and temporal poles and the fronto-insular cortex, allowing the representation of the thoughts, feelings and actions of self and others. This paper reviews recent morphological and functional literature in light of the proposed networks underlying these disorders. It is suggested that there is considerable support for the involvement of the directed effort network in schizophrenia from studies of brain structure with voxel-based morphometry (VBM and diffusion tensor imaging (DTI. While early studies of resting brain networks are inconclusive, functional magnetic resonance imaging imaging (fMRI studies of task-related networks clearly implicate these regions. In keeping with the model, functional deficits in regions associated with directed effort and self-monitoring are associated with structural anomalies in action-related regions in schizophrenic patients. VBM, DTI, fMRI studies of mood disordered patients support the involvement of a different network associated with emotional encoding. The distinction between disorders is enhanced by combining structural and functional data. It is concluded that brain networks associated with directed effort are particularly vulnerable to failure in the human brain leading to the symptoms of

  1. Network analysis: An innovative framework for understanding eating disorder psychopathology.

    Science.gov (United States)

    Smith, Kathryn E; Crosby, Ross D; Wonderlich, Stephen A; Forbush, Kelsie T; Mason, Tyler B; Moessner, Markus

    2018-03-01

    Network theory and analysis is an emerging approach in psychopathology research that has received increasing attention across fields of study. In contrast to medical models or latent variable approaches, network theory suggests that psychiatric syndromes result from systems of causal and reciprocal symptom relationships. Despite the promise of this approach to elucidate key mechanisms contributing to the development and maintenance of eating disorders (EDs), thus far, few applications of network analysis have been tested in ED samples. We first present an overview of network theory, review the existing findings in the ED literature, and discuss the limitations of this literature to date. In particular, the reliance on cross-sectional designs, use of single-item self-reports of symptoms, and instability of results have raised concern about the inferences that can be made from network analyses. We outline several areas to address in future ED network analytic research, which include the use of prospective designs and adoption of multimodal assessment methods. Doing so will provide a clearer understanding of whether network analysis can enhance our current understanding of ED psychopathology and inform clinical interventions. © 2018 Wiley Periodicals, Inc.

  2. Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks.

    Science.gov (United States)

    Tejedor, Alejandro; Longjas, Anthony; Zaliapin, Ilya; Ambroj, Samuel; Foufoula-Georgiou, Efi

    2017-08-17

    Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.

  3. A framework for integration of heterogeneous medical imaging networks.

    Science.gov (United States)

    Viana-Ferreira, Carlos; Ribeiro, Luís S; Costa, Carlos

    2014-01-01

    Medical imaging is increasing its importance in matters of medical diagnosis and in treatment support. Much is due to computers that have revolutionized medical imaging not only in acquisition process but also in the way it is visualized, stored, exchanged and managed. Picture Archiving and Communication Systems (PACS) is an example of how medical imaging takes advantage of computers. To solve problems of interoperability of PACS and medical imaging equipment, the Digital Imaging and Communications in Medicine (DICOM) standard was defined and widely implemented in current solutions. More recently, the need to exchange medical data between distinct institutions resulted in Integrating the Healthcare Enterprise (IHE) initiative that contains a content profile especially conceived for medical imaging exchange: Cross Enterprise Document Sharing for imaging (XDS-i). Moreover, due to application requirements, many solutions developed private networks to support their services. For instance, some applications support enhanced query and retrieve over DICOM objects metadata. This paper proposes anintegration framework to medical imaging networks that provides protocols interoperability and data federation services. It is an extensible plugin system that supports standard approaches (DICOM and XDS-I), but is also capable of supporting private protocols. The framework is being used in the Dicoogle Open Source PACS.

  4. A computational framework for the automated construction of glycosylation reaction networks.

    Science.gov (United States)

    Liu, Gang; Neelamegham, Sriram

    2014-01-01

    Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All

  5. A computational framework for the automated construction of glycosylation reaction networks.

    Directory of Open Access Journals (Sweden)

    Gang Liu

    Full Text Available Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS data. The features described above are illustrated using three case studies that examine: i O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii automated N-linked glycosylation pathway construction; and iii the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme

  6. Computational models in physics teaching: a framework

    Directory of Open Access Journals (Sweden)

    Marco Antonio Moreira

    2012-08-01

    Full Text Available The purpose of the present paper is to present a theoretical framework to promote and assist meaningful physics learning through computational models. Our proposal is based on the use of a tool, the AVM diagram, to design educational activities involving modeling and computer simulations. The idea is to provide a starting point for the construction and implementation of didactical approaches grounded in a coherent epistemological view about scientific modeling.

  7. A Framework for Secure Data Delivery in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Leonidas PERLEPES

    2012-03-01

    Full Text Available Typical sensor nodes are resource constrained devices containing user level applications, operating system components, and device drivers in a single address space, with no form of memory protection. A malicious user could easily capture a node and tamper the applications running on it, in order to perform different types of attacks. In this paper, we propose a 3-layer Security Framework composed by physical security schemes, cryptography of communication channels and live forensics protection techniques that allows for secure WSN deployments. Each of the abovementioned techniques maximizes the security levels leading to a tamper proof sensor node. By applying the proposed security framework, secure communication between nodes is guaranteed, identified captured nodes are silenced and their destructive effect on the rest of the network infrastructure is minimized due to the early measures applied. Our main concern is to propose a framework that balances its attributes between robustness, as long as security is concerned and cost effective implementation as far as resources (energy consumption are concerned.

  8. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  9. Building crop models within different crop modelling frameworks

    NARCIS (Netherlands)

    Adam, M.Y.O.; Corbeels, M.; Leffelaar, P.A.; Keulen, van H.; Wery, J.; Ewert, F.

    2012-01-01

    Modular frameworks for crop modelling have evolved through simultaneous progress in crop science and software development but differences among these frameworks exist which are not well understood, resulting in potential misuse for crop modelling. In this paper we review differences and similarities

  10. Developing Personal Network Business Models

    DEFF Research Database (Denmark)

    Saugstrup, Dan; Henten, Anders

    2006-01-01

    The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...

  11. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    Science.gov (United States)

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  12. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  13. Spatial Modeling for Resources Framework (SMRF)

    Science.gov (United States)

    Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed...

  14. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  15. A framework using cluster-based hybrid network architecture for collaborative virtual surgery.

    Science.gov (United States)

    Qin, Jing; Choi, Kup-Sze; Poon, Wai-Sang; Heng, Pheng-Ann

    2009-12-01

    Research on collaborative virtual environments (CVEs) opens the opportunity for simulating the cooperative work in surgical operations. It is however a challenging task to implement a high performance collaborative surgical simulation system because of the difficulty in maintaining state consistency with minimum network latencies, especially when sophisticated deformable models and haptics are involved. In this paper, an integrated framework using cluster-based hybrid network architecture is proposed to support collaborative virtual surgery. Multicast transmission is employed to transmit updated information among participants in order to reduce network latencies, while system consistency is maintained by an administrative server. Reliable multicast is implemented using distributed message acknowledgment based on cluster cooperation and sliding window technique. The robustness of the framework is guaranteed by the failure detection chain which enables smooth transition when participants join and leave the collaboration, including normal and involuntary leaving. Communication overhead is further reduced by implementing a number of management approaches such as computational policies and collaborative mechanisms. The feasibility of the proposed framework is demonstrated by successfully extending an existing standalone orthopedic surgery trainer into a collaborative simulation system. A series of experiments have been conducted to evaluate the system performance. The results demonstrate that the proposed framework is capable of supporting collaborative surgical simulation.

  16. A Model-Driven Framework to Develop Personalized Health Monitoring

    Directory of Open Access Journals (Sweden)

    Algimantas Venčkauskas

    2016-07-01

    Full Text Available Both distributed healthcare systems and the Internet of Things (IoT are currently hot topics. The latter is a new computing paradigm to enable advanced capabilities in engineering various applications, including those for healthcare. For such systems, the core social requirement is the privacy/security of the patient information along with the technical requirements (e.g., energy consumption and capabilities for adaptability and personalization. Typically, the functionality of the systems is predefined by the patient’s data collected using sensor networks along with medical instrumentation; then, the data is transferred through the Internet for treatment and decision-making. Therefore, systems creation is indeed challenging. In this paper, we propose a model-driven framework to develop the IoT-based prototype and its reference architecture for personalized health monitoring (PHM applications. The framework contains a multi-layered structure with feature-based modeling and feature model transformations at the top and the application software generation at the bottom. We have validated the framework using available tools and developed an experimental PHM to test some aspects of the functionality of the reference architecture in real time. The main contribution of the paper is the development of the model-driven computational framework with emphasis on the synergistic effect of security and energy issues.

  17. Phenomenological network models: Lessons for epilepsy surgery.

    Science.gov (United States)

    Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans

    2017-10-01

    The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

  18. A framework for performance measurement in university using extended network data envelopment analysis (DEA) structures

    Science.gov (United States)

    Kashim, Rosmaini; Kasim, Maznah Mat; Rahman, Rosshairy Abd

    2015-12-01

    Measuring university performance is essential for efficient allocation and utilization of educational resources. In most of the previous studies, performance measurement in universities emphasized the operational efficiency and resource utilization without investigating the university's ability to fulfill the needs of its stakeholders and society. Therefore, assessment of the performance of university should be separated into two stages namely efficiency and effectiveness. In conventional DEA analysis, a decision making unit (DMU) or in this context, a university is generally treated as a black-box which ignores the operation and interdependence of the internal processes. When this happens, the results obtained would be misleading. Thus, this paper suggest an alternative framework for measuring the overall performance of a university by incorporating both efficiency and effectiveness and applies network DEA model. The network DEA models are recommended because this approach takes into account the interrelationship between the processes of efficiency and effectiveness in the system. This framework also focuses on the university structure which is expanded from the hierarchical to form a series of horizontal relationship between subordinate units by assuming both intermediate unit and its subordinate units can generate output(s). Three conceptual models are proposed to evaluate the performance of a university. An efficiency model is developed at the first stage by using hierarchical network model. It is followed by an effectiveness model which take output(s) from the hierarchical structure at the first stage as a input(s) at the second stage. As a result, a new overall performance model is proposed by combining both efficiency and effectiveness models. Thus, once this overall model is realized and utilized, the university's top management can determine the overall performance of each unit more accurately and systematically. Besides that, the result from the network

  19. A model of coauthorship networks

    Science.gov (United States)

    Zhou, Guochang; Li, Jianping; Xie, Zonglin

    2017-10-01

    A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property

  20. A model-based risk management framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune

    2002-08-15

    The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

  1. A Generic Context Management Framework for Personal Networking Environments

    DEFF Research Database (Denmark)

    Sanchez, Luis; Olsen, Rasmus Løvenstein; Bauer, Martin

    2006-01-01

    on their computational capabilities and their role within the system. We differentiate between Basic Context Nodes (BCN), Enhanced Context Nodes (ECN) and Context Management Nodes (CMN) within the CMF. CMNs operate on two levels, i.e., local/cluster level and PN level. In the paper we also describe how these entities......In this paper we introduce a high level architecture for a context management system for Personal Networks (PN). The main objective of the Context Management Framework (CMF) described in this paper is to support the interactions between context information sources and context aware components......, services and applications in a generic manner, independently of their nature and operation area. To this end, we propose a structure consisting of a context access module, processing and storage module, and a data source abstraction layer. Nodes provide a certain set of these modules depending...

  2. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    Directory of Open Access Journals (Sweden)

    Jan eHahne

    2015-09-01

    Full Text Available Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy...

  3. An evaluation framework for participatory modelling

    Science.gov (United States)

    Krueger, T.; Inman, A.; Chilvers, J.

    2012-04-01

    Strong arguments for participatory modelling in hydrology can be made on substantive, instrumental and normative grounds. These arguments have led to increasingly diverse groups of stakeholders (here anyone affecting or affected by an issue) getting involved in hydrological research and the management of water resources. In fact, participation has become a requirement of many research grants, programs, plans and policies. However, evidence of beneficial outcomes of participation as suggested by the arguments is difficult to generate and therefore rare. This is because outcomes are diverse, distributed, often tacit, and take time to emerge. In this paper we develop an evaluation framework for participatory modelling focussed on learning outcomes. Learning encompasses many of the potential benefits of participation, such as better models through diversity of knowledge and scrutiny, stakeholder empowerment, greater trust in models and ownership of subsequent decisions, individual moral development, reflexivity, relationships, social capital, institutional change, resilience and sustainability. Based on the theories of experiential, transformative and social learning, complemented by practitioner experience our framework examines if, when and how learning has occurred. Special emphasis is placed on the role of models as learning catalysts. We map the distribution of learning between stakeholders, scientists (as a subgroup of stakeholders) and models. And we analyse what type of learning has occurred: instrumental learning (broadly cognitive enhancement) and/or communicative learning (change in interpreting meanings, intentions and values associated with actions and activities; group dynamics). We demonstrate how our framework can be translated into a questionnaire-based survey conducted with stakeholders and scientists at key stages of the participatory process, and show preliminary insights from applying the framework within a rural pollution management situation in

  4. A framework for benchmarking land models

    Directory of Open Access Journals (Sweden)

    Y. Q. Luo

    2012-10-01

    Full Text Available Land models, which have been developed by the modeling community in the past few decades to predict future states of ecosystems and climate, have to be critically evaluated for their performance skills of simulating ecosystem responses and feedback to climate change. Benchmarking is an emerging procedure to measure performance of models against a set of defined standards. This paper proposes a benchmarking framework for evaluation of land model performances and, meanwhile, highlights major challenges at this infant stage of benchmark analysis. The framework includes (1 targeted aspects of model performance to be evaluated, (2 a set of benchmarks as defined references to test model performance, (3 metrics to measure and compare performance skills among models so as to identify model strengths and deficiencies, and (4 model improvement. Land models are required to simulate exchange of water, energy, carbon and sometimes other trace gases between the atmosphere and land surface, and should be evaluated for their simulations of biophysical processes, biogeochemical cycles, and vegetation dynamics in response to climate change across broad temporal and spatial scales. Thus, one major challenge is to select and define a limited number of benchmarks to effectively evaluate land model performance. The second challenge is to develop metrics of measuring mismatches between models and benchmarks. The metrics may include (1 a priori thresholds of acceptable model performance and (2 a scoring system to combine data–model mismatches for various processes at different temporal and spatial scales. The benchmark analyses should identify clues of weak model performance to guide future development, thus enabling improved predictions of future states of ecosystems and climate. The near-future research effort should be on development of a set of widely acceptable benchmarks that can be used to objectively, effectively, and reliably evaluate fundamental properties

  5. A Hybrid Energy Sharing Framework for Green Cellular Networks

    KAUST Repository

    Farooq, Muhammad Junaid

    2016-12-09

    Cellular operators are increasingly turning towards renewable energy (RE) as an alternative to using traditional electricity in order to reduce operational expenditure and carbon footprint. Due to the randomness in both RE generation and mobile traffic at each base station (BS), a surplus or shortfall of energy may occur at any given time. To increase energy selfreliance and minimize the network’s energy cost, the operator needs to efficiently exploit the RE generated across all BSs. In this paper, a hybrid energy sharing framework for cellular network is proposed, where a combination of physical power lines and energy trading with other BSs using smart grid is used. Algorithms for physical power lines deployment between BSs, based on average and complete statistics of the net RE available, are developed. Afterwards, an energy management framework is formulated to optimally determine the quantities of electricity and RE to be procured and exchanged among BSs, respectively, while considering battery capacities and real-time energy pricing. Three cases are investigated where RE generation is unknown, perfectly known, and partially known ahead of time. Results investigate the time varying energy management of BSs and demonstrate considerable reduction in average energy cost thanks to the hybrid energy sharing scheme.

  6. Constitutive modelling of composite biopolymer networks.

    Science.gov (United States)

    Fallqvist, B; Kroon, M

    2016-04-21

    The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Telecommunications network modelling, planning and design

    CERN Document Server

    Evans, Sharon

    2003-01-01

    Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

  8. Talking Cure Models: A Framework of Analysis

    Directory of Open Access Journals (Sweden)

    Christopher Marx

    2017-09-01

    Full Text Available Psychotherapy is commonly described as a “talking cure,” a treatment method that operates through linguistic action and interaction. The operative specifics of therapeutic language use, however, are insufficiently understood, mainly due to a multitude of disparate approaches that advance different notions of what “talking” means and what “cure” implies in the respective context. Accordingly, a clarification of the basic theoretical structure of “talking cure models,” i.e., models that describe therapeutic processes with a focus on language use, is a desideratum of language-oriented psychotherapy research. Against this background the present paper suggests a theoretical framework of analysis which distinguishes four basic components of “talking cure models”: (1 a foundational theory (which suggests how linguistic activity can affect and transform human experience, (2 an experiential problem state (which defines the problem or pathology of the patient, (3 a curative linguistic activity (which defines linguistic activities that are supposed to effectuate a curative transformation of the experiential problem state, and (4 a change mechanism (which defines the processes and effects involved in such transformations. The purpose of the framework is to establish a terminological foundation that allows for systematically reconstructing basic properties and operative mechanisms of “talking cure models.” To demonstrate the applicability and utility of the framework, five distinct “talking cure models” which spell out the details of curative “talking” processes in terms of (1 catharsis, (2 symbolization, (3 narrative, (4 metaphor, and (5 neurocognitive inhibition are introduced and discussed in terms of the framework components. In summary, we hope that our framework will prove useful for the objective of clarifying the theoretical underpinnings of language-oriented psychotherapy research and help to establish a more

  9. Developing a Framework and Implementing User-Driven Innovation in Supply and Value Network

    DEFF Research Database (Denmark)

    Jacobsen, Alexia; Lassen, Astrid Heidemann; Wandahl, Søren

    2011-01-01

    This paper serves to create a framework for and, subsequently, implementing user-driven innovation in a construction material industry network. The research has its outset in Project InnoDoors that consists of a Danish university and a construction material network. The framework and the implemen......This paper serves to create a framework for and, subsequently, implementing user-driven innovation in a construction material industry network. The research has its outset in Project InnoDoors that consists of a Danish university and a construction material network. The framework...

  10. RUASN: A Robust User Authentication Framework for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Hoon-Jae Lee

    2011-05-01

    Full Text Available In recent years, wireless sensor networks (WSNs have been considered as a potential solution for real-time monitoring applications and these WSNs have potential practical impact on next generation technology too. However, WSNs could become a threat if suitable security is not considered before the deployment and if there are any loopholes in their security, which might open the door for an attacker and hence, endanger the application. User authentication is one of the most important security services to protect WSN data access from unauthorized users; it should provide both mutual authentication and session key establishment services. This paper proposes a robust user authentication framework for wireless sensor networks, based on a two-factor (password and smart card concept. This scheme facilitates many services to the users such as user anonymity, mutual authentication, secure session key establishment and it allows users to choose/update their password regularly, whenever needed. Furthermore, we have provided the formal verification using Rubin logic and compare RUASN with many existing schemes. As a result, we found that the proposed scheme possesses many advantages against popular attacks, and achieves better efficiency at low computation cost.

  11. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  12. AGAMA: Action-based galaxy modeling framework

    Science.gov (United States)

    Vasiliev, Eugene

    2018-05-01

    The AGAMA library models galaxies. It computes gravitational potential and forces, performs orbit integration and analysis, and can convert between position/velocity and action/angle coordinates. It offers a framework for finding best-fit parameters of a model from data and self-consistent multi-component galaxy models, and contains useful auxiliary utilities such as various mathematical routines. The core of the library is written in C++, and there are Python and Fortran interfaces. AGAMA may be used as a plugin for the stellar-dynamical software packages galpy (ascl:1411.008), AMUSE (ascl:1107.007), and NEMO (ascl:1010.051).

  13. A Framework for Understanding Physics Students' Computational Modeling Practices

    Science.gov (United States)

    Lunk, Brandon Robert

    With the growing push to include computational modeling in the physics classroom, we are faced with the need to better understand students' computational modeling practices. While existing research on programming comprehension explores how novices and experts generate programming algorithms, little of this discusses how domain content knowledge, and physics knowledge in particular, can influence students' programming practices. In an effort to better understand this issue, I have developed a framework for modeling these practices based on a resource stance towards student knowledge. A resource framework models knowledge as the activation of vast networks of elements called "resources." Much like neurons in the brain, resources that become active can trigger cascading events of activation throughout the broader network. This model emphasizes the connectivity between knowledge elements and provides a description of students' knowledge base. Together with resources resources, the concepts of "epistemic games" and "frames" provide a means for addressing the interaction between content knowledge and practices. Although this framework has generally been limited to describing conceptual and mathematical understanding, it also provides a means for addressing students' programming practices. In this dissertation, I will demonstrate this facet of a resource framework as well as fill in an important missing piece: a set of epistemic games that can describe students' computational modeling strategies. The development of this theoretical framework emerged from the analysis of video data of students generating computational models during the laboratory component of a Matter & Interactions: Modern Mechanics course. Student participants across two semesters were recorded as they worked in groups to fix pre-written computational models that were initially missing key lines of code. Analysis of this video data showed that the students' programming practices were highly influenced by

  14. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework.

    Directory of Open Access Journals (Sweden)

    H Francis Song

    2016-02-01

    Full Text Available The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, "trained" networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale's principle, which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural

  15. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

    Science.gov (United States)

    Wang, Xiao-Jing

    2016-01-01

    The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity

  16. A scalable computational framework for establishing long-term behavior of stochastic reaction networks.

    Directory of Open Access Journals (Sweden)

    Ankit Gupta

    2014-06-01

    Full Text Available Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed.

  17. A framework for detecting communities of unbalanced sizes in networks

    Science.gov (United States)

    Žalik, Krista Rizman; Žalik, Borut

    2018-01-01

    Community detection in large networks has been a focus of recent research in many of fields, including biology, physics, social sciences, and computer science. Most community detection methods partition the entire network into communities, groups of nodes that have many connections within communities and few connections between them and do not identify different roles that nodes can have in communities. We propose a community detection model that integrates more different measures that can fast identify communities of different sizes and densities. We use node degree centrality, strong similarity with one node from community, maximal similarity of node to community, compactness of communities and separation between communities. Each measure has its own strength and weakness. Thus, combining different measures can benefit from the strengths of each one and eliminate encountered problems of using an individual measure. We present a fast local expansion algorithm for uncovering communities of different sizes and densities and reveals rich information on input networks. Experimental results show that the proposed algorithm is better or as effective as the other community detection algorithms for both real-world and synthetic networks while it requires less time.

  18. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  19. Role models for complex networks

    Science.gov (United States)

    Reichardt, J.; White, D. R.

    2007-11-01

    We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

  20. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  1. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  2. Conceptualising Business Models: Definitions, Frameworks and Classifications

    Directory of Open Access Journals (Sweden)

    Erwin Fielt

    2013-12-01

    Full Text Available The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1 explicitly including the customer value concept in the business model definition and focussing on value creation, (2 presenting four core dimensions that business model elements need to cover, (3 arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy (4 stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5 suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

  3. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  4. Model-based version management system framework

    International Nuclear Information System (INIS)

    Mehmood, W.

    2016-01-01

    In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

  5. Modelling framework for groundwater flow at Sellafield

    International Nuclear Information System (INIS)

    Hooper, A.J.; Billington, D.E.; Herbert, A.W.

    1995-01-01

    The principal objective of Nirex is to develop a single deep geological repository for the safe disposal of low- and intermediate-level radioactive waste. In safety assessment, use is made of a variety of conceptual models that form the basis for modelling of the pathways by which radionuclides might return to the environment. In this paper, the development of a conceptual model for groundwater flow and transport through fractured rock on the various scales of interest is discussed. The approach is illustrated by considering how some aspects of the conceptual model are developed in particular numerical models. These representations of the conceptual model use fracture network geometries based on realistic rock properties. (author). refs., figs., tabs

  6. Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

    International Nuclear Information System (INIS)

    Hargrave, C; Deegan, T; Gibbs, A; Poulsen, M; Moores, M; Harden, F; Mengersen, K

    2014-01-01

    A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

  7. Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

    Science.gov (United States)

    Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.

    2014-03-01

    A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

  8. An entropic framework for modeling economies

    Science.gov (United States)

    Caticha, Ariel; Golan, Amos

    2014-08-01

    We develop an information-theoretic framework for economic modeling. This framework is based on principles of entropic inference that are designed for reasoning on the basis of incomplete information. We take the point of view of an external observer who has access to limited information about broad macroscopic economic features. We view this framework as complementary to more traditional methods. The economy is modeled as a collection of agents about whom we make no assumptions of rationality (in the sense of maximizing utility or profit). States of statistical equilibrium are introduced as those macrostates that maximize entropy subject to the relevant information codified into constraints. The basic assumption is that this information refers to supply and demand and is expressed in the form of the expected values of certain quantities (such as inputs, resources, goods, production functions, utility functions and budgets). The notion of economic entropy is introduced. It provides a measure of the uniformity of the distribution of goods and resources. It captures both the welfare state of the economy as well as the characteristics of the market (say, monopolistic, concentrated or competitive). Prices, which turn out to be the Lagrange multipliers, are endogenously generated by the economy. Further studies include the equilibrium between two economies and the conditions for stability. As an example, the case of the nonlinear economy that arises from linear production and utility functions is treated in some detail.

  9. Geotube: a network based framework for Goescience dissemination

    Science.gov (United States)

    Grieco, Giovanni; Porta, Marina; Merlini, Anna Elisabetta; Caironi, Valeria; Reggiori, Donatella

    2016-04-01

    Geotube is a project promoted by Il Geco cultural association for the dissemination of Geoscience education in schools by open multimedia environments. The approach is based on the following keystones: • A deep and permanent epistemological reflection supported by confrontation within the International Scientific Community • A close link with the territory • A local to global inductive approach to basic concepts in Geosciences • The construction of an open framework to stimulate creativity The project has been developed as an educational activity for secondary schools (11 to 18 years old students). It provides for the creation of a network of institutions to be involved in order to ensure the required diversified expertise. They can comprise: Universities, Natural Parks, Mountain Communities, Municipalities, schools, private companies working in the sector, and so on. A single project lasts for one school year (October to June) and requires 8-12 work hours at school, one or two half day or full day excursions and a final event of presentation of outputs. The possible outputs comprise a pdf or ppt guidebook, a script and a video completely shooted and edited by the students. The framework is open in order to adapt to the single class or workgroup needs, the level and type of school, the time available and different subjects in Geosciences. In the last two years the two parts of the project have been successfully tested separately, while the full project will be presented at schools in in its full form in April 2016, in collaboration with University of Milan, Campo dei Fiori Natural Park, Piambello Mountain Community and Cunardo Municipality. The production of geotube outputs has been tested in a high school for three consecutive years. Students produced scripts and videos on the following subjects: geologic hazards, volcanoes and earthquakes, and climate change. The excursions have been tested with two different high schools. Firstly two areas have been

  10. Computational modeling of Metal-Organic Frameworks

    Science.gov (United States)

    Sung, Jeffrey Chuen-Fai

    In this work, the metal-organic frameworks MIL-53(Cr), DMOF-2,3-NH 2Cl, DMOF-2,5-NH2Cl, and HKUST-1 were modeled using molecular mechanics and electronic structure. The effect of electronic polarization on the adsorption of water in MIL-53(Cr) was studied using molecular dynamics simulations of water-loaded MIL-53 systems with both polarizable and non-polarizable force fields. Molecular dynamics simulations of the full systems and DFT calculations on representative framework clusters were utilized to study the difference in nitrogen adsorption between DMOF-2,3-NH2Cl and DMOF-2,5-NH 2Cl. Finally, the control of proton conduction in HKUST-1 by complexation of molecules to the Cu open metal site was investigated using the MS-EVB methodology.

  11. Systems and methods for modeling and analyzing networks

    Science.gov (United States)

    Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

    2013-10-29

    The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

  12. Modeling Geomagnetic Variations using a Machine Learning Framework

    Science.gov (United States)

    Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

    2017-12-01

    We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

  13. System-level Modeling of Wireless Integrated Sensor Networks

    DEFF Research Database (Denmark)

    Virk, Kashif M.; Hansen, Knud; Madsen, Jan

    2005-01-01

    Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

  14. Computer-aided modeling framework – a generic modeling template

    DEFF Research Database (Denmark)

    Fedorova, Marina; Sin, Gürkan; Gani, Rafiqul

    and test models systematically, efficiently and reliably. In this way, development of products and processes can be made faster, cheaper and more efficient. In this contribution, as part of the framework, a generic modeling template for the systematic derivation of problem specific models is presented....... The application of the modeling template is highlighted with a case study related to the modeling of a catalytic membrane reactor coupling dehydrogenation of ethylbenzene with hydrogenation of nitrobenzene...

  15. A Framework for Joint Optical-Wireless Resource Management in Multi-RAT, Heterogeneous Mobile Networks

    DEFF Research Database (Denmark)

    Zakrzewska, Anna; Popovska Avramova, Andrijana; Christiansen, Henrik Lehrmann

    2013-01-01

    Mobile networks are constantly evolving: new Radio Access Technologies (RATs) are being introduced, and backhaul architectures like Cloud-RAN (C-RAN) and distributed base stations are being proposed. Furthermore, small cells are being deployed to enhance network capacity. The end-users wish...... to be always connected to a high-quality service (high bit rates, low latency), thus causing a very complex network control task from an operator’s point of view. We thus propose a framework allowing joint overall network resource management. This scheme covers different types of network heterogeneity (multi......-RAT, multi-layer, multi-architecture) by introducing a novel, hierarchical approach to network resource management. Self-Organizing Networks (SON) and cognitive network behaviors are covered as well as more traditional mobile network features. The framework is applicable to all phases of network operation...

  16. International Voluntary Health Networks (IVHNs). A social-geographical framework.

    Science.gov (United States)

    Reid, Benet; Laurie, Nina; Smith, Matt Baillie

    2018-03-01

    Trans-national medicine, historically associated with colonial politics, is now central to discourses of global health and development, thrust into mainstream media by catastrophic events (earthquakes, disease epidemics), and enshrined in the 2015 Sustainable Development Goals. Volunteer human-resource is an important contributor to international health-development work. International Voluntary Health Networks (IVHNs, that connect richer and poorer countries through healthcare) are situated at a meeting-point between geographies and sociologies of health. More fully developed social-geographic understandings will illuminate this area, currently dominated by instrumental health-professional perspectives. The challenge we address is to produce a geographically and sociologically-robust conceptual framework that appropriately recognises IVHNs' potentials for valuable impacts, while also unlocking spaces of constructive critique. We examine the importance of the social in health geography, and geographical potentials in health sociology (focusing on professional knowledge construction, inequality and capital, and power), to highlight the mutual interests of these two fields in relation to IVHNs. We propose some socio-geographical theories of IVHNs that do not naturalise inequality, that understand health as a form of capital, prioritise explorations of power and ethical practice, and acknowledge the more-than-human properties of place. This sets an agenda for theoretically-supported empirical work on IVHNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. A computational framework for modeling targets as complex adaptive systems

    Science.gov (United States)

    Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

    2017-05-01

    Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

  18. Network model of security system

    Directory of Open Access Journals (Sweden)

    Adamczyk Piotr

    2016-01-01

    Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.

  19. How democratic are Networks?- A framework for Assessing the Democratic Effects of Networks

    DEFF Research Database (Denmark)

    Agger, Annika; Löfgren, Karl

    : How can we assess the democratic effects of formal network mobilisation?  The article will present a tentative framework deriving criteria from both traditional democratic theory, as well as new theories on democratic governance and collaborative planning, which can be deployed for empirical studies......There has, since the end of the 1980s, been a growing interest in western democracies for formally involving citizens in various local planning activities through network governance. The overarching goal has been to increase efficiency in local planning. Equally, it has also been accompanied...... by an underlying idea of enhancing public participation and mobilising the citizens, thereby strengthening local democracy. Even though much is written about these initiatives, the actual democratic effects of these activities have been notably overlooked in the literature. Both among scholars, as well...

  20. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  1. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. COSMO: a conceptual framework for service modelling and refinement

    NARCIS (Netherlands)

    Quartel, Dick; Steen, Maarten W.A.; Pokraev, S.; van Sinderen, Marten J.

    This paper presents a conceptual framework for service modelling and refinement, called the COSMO (COnceptual Service MOdelling) framework. This framework provides concepts to model and reason about services, and to support operations, such as composition and discovery, which are performed on them

  3. Target-Centric Network Modeling

    DEFF Research Database (Denmark)

    Mitchell, Dr. William L.; Clark, Dr. Robert M.

    In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

  4. Multi-Agent Framework in Visual Sensor Networks

    Directory of Open Access Journals (Sweden)

    J. M. Molina

    2007-01-01

    Full Text Available The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination.

  5. Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks

    Science.gov (United States)

    Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa

    In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.

  6. A system-level multiprocessor system-on-chip modeling framework

    DEFF Research Database (Denmark)

    Virk, Kashif Munir; Madsen, Jan

    2004-01-01

    We present a system-level modeling framework to model system-on-chips (SoC) consisting of heterogeneous multiprocessors and network-on-chip communication structures in order to enable the developers of today's SoC designs to take advantage of the flexibility and scalability of network-on-chip and...... SoC design. We show how a hand-held multimedia terminal, consisting of JPEG, MP3 and GSM applications, can be modeled as a multiprocessor SoC in our framework....

  7. Business Model Innovation: An Integrative Conceptual Framework

    Directory of Open Access Journals (Sweden)

    Bernd Wirtz

    2017-01-01

    Full Text Available Purpose: The point of departure of this exploratory study is the gap between the increasing importance of business model innovation (BMI in science and management and the limited conceptual assistance available. Therefore, the study identi es and explores scattered BMI insights and deduces them into an integrative framework to enhance our understanding about this phenomenon and to present a helpful guidance for researchers and practitioners. Design/Methodology/Approach: The study identi es BMI insights through a literature-based investigation and consolidates them into an integrative BMI framework that presents the key elements and dimensions of BMI as well as their presumed relationships. Findings: The study enhances our understanding about the key elements and dimensions of BMI, presents further conceptual insights into the BMI phenomenon, supplies implications for science and management, and may serve as a helpful guidance for future research. Practical Implications: The presented framework provides managers with a tool to identify critical BMI issues and can serve as a conceptual BMI guideline. Research limitations: Given the vast amount of academic journals, it is unlikely that every applicable scienti c publication is included in the analysis. The illustrative examples are descriptive in nature, and thus do not provide empirical validity. Several implications for future research are provided. Originality/Value: The study’s main contribution lies in the unifying approach of the dispersed BMI knowledge. Since our understanding of BMI is still limited, this study should provide the necessary insights and conceptual assistance to further develop the concept and guide its practical application.

  8. Novel Framework for Data Collection in Wireless Sensor Networks Using Flying Sensors

    DEFF Research Database (Denmark)

    Mathur, Prateek; Nielsen, Rasmus Hjorth; Prasad, Neeli R.

    2014-01-01

    This paper proposes a novel framework for data collection from a sensor network using flying sensor nodes. Efficient data communication within the network is a necessity as sensor nodes are usually energy constrained. The proposed framework utilizes the various entities forming the network...... for a different utility compared to their usual role in sensor networks. Use of flying sensor nodes is usually considered for conventional purpose of sensing and monitoring. Flying sensing nodes are usually utilized collectively in the form of an aerial sensor network, they are not expected to function as a data...... collection entity, as proposed in this framework. Similarly, cluster heads (CHs) are usually expected to transfer the aggregated data to an adjoining CH or to the base station (BS) directly. In the proposed framework the CH transfers data directly to the flying sensor node, averting the need for energy...

  9. A Procurement Performance Model for Construction Frameworks

    Directory of Open Access Journals (Sweden)

    Terence Y M Lam

    2015-07-01

    Full Text Available Collaborative construction frameworks have been developed in the United Kingdom (UK to create longer term relationships between clients and suppliers in order to improve project outcomes. Research undertaken into highways maintenance set within a major county council has confirmed that such collaborative procurement methods can improve time, cost and quality of construction projects. Building upon this and examining the same single case, this research aims to develop a performance model through identification of performance drivers in the whole project delivery process including pre and post contract phases. A priori performance model based on operational and sociological constructs was proposed and then checked by a pilot study. Factor analysis and central tendency statistics from the questionnaires as well as content analysis from the interview transcripts were conducted. It was confirmed that long term relationships, financial and non-financial incentives and stronger communication are the sociological behaviour factors driving performance. The interviews also established that key performance indicators (KPIs can be used as an operational measure to improve performance. With the posteriori performance model, client project managers can effectively collaboratively manage contractor performance through procurement measures including use of longer term and KPIs for the contract so that the expected project outcomes can be achieved. The findings also make significant contribution to construction framework procurement theory by identifying the interrelated sociological and operational performance drivers. This study is set predominantly in the field of highways civil engineering. It is suggested that building based projects or other projects that share characteristics are grouped together and used for further research of the phenomena discovered.

  10. Framework for path finding in multi-layer transport networks

    NARCIS (Netherlands)

    Dijkstra, F.

    2009-01-01

    In only a few decades the use of computer networks has dramatically increased. Today, networks are ubiquitous in society: they are used for surfing, email and financial transactions. The capacity of the network has increased so much, that it is now possible to transfer massive data sets that

  11. Picasso: A Modular Framework for Visualizing the Learning Process of Neural Network Image Classifiers

    Directory of Open Access Journals (Sweden)

    Ryan Henderson

    2017-09-01

    Full Text Available Picasso is a free open-source (Eclipse Public License web application written in Python for rendering standard visualizations useful for analyzing convolutional neural networks. Picasso ships with occlusion maps and saliency maps, two visualizations which help reveal issues that evaluation metrics like loss and accuracy might hide: for example, learning a proxy classification task. Picasso works with the Tensorflow deep learning framework, and Keras (when the model can be loaded into the Tensorflow backend. Picasso can be used with minimal configuration by deep learning researchers and engineers alike across various neural network architectures. Adding new visualizations is simple: the user can specify their visualization code and HTML template separately from the application code.

  12. Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

    Science.gov (United States)

    2015-03-03

    based whole-cell models of E. coli [6]. Conversely , highly abstracted kinetic frameworks, such as the cybernetic framework, represented a paradigm shift...metabolic objective function has been the optimization of biomass formation [18], although other metabolic objectives have also been estimated [19...experimental data. Toward these questions, we explored five hypothetical cell-free networks. Each network shared the same enzymatic connectivity, but

  13. FERN - a Java framework for stochastic simulation and evaluation of reaction networks.

    Science.gov (United States)

    Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

    2008-08-29

    Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand-alone program and within new

  14. Traffic Steering Framework for Mobile-Assisted Resource Management in Heterogeneous Networks

    DEFF Research Database (Denmark)

    Dogadaev, Anton Konstantinovich; Checko, Aleksandra; Popovska Avramova, Andrijana

    2013-01-01

    With the expected growth of mobile data traffic it is essential to manage the network resources efficiently. In order to undertake this challenge, we propose a framework for network-centric, mobile-assisted resource management, which facilitates traffic offloading from mobile network to Wi-Fi...... to the network backbone. What is more, we give an overview of existing standardization activities on offloading the mobile traffic through Wi-Fi....

  15. Conceptual Frameworks in the Doctoral Research Process: A Pedagogical Model

    Science.gov (United States)

    Berman, Jeanette; Smyth, Robyn

    2015-01-01

    This paper contributes to consideration of the role of conceptual frameworks in the doctoral research process. Through reflection on the two authors' own conceptual frameworks for their doctoral studies, a pedagogical model has been developed. The model posits the development of a conceptual framework as a core element of the doctoral…

  16. LQCD workflow execution framework: Models, provenance and fault-tolerance

    International Nuclear Information System (INIS)

    Piccoli, Luciano; Simone, James N; Kowalkowlski, James B; Dubey, Abhishek

    2010-01-01

    Large computing clusters used for scientific processing suffer from systemic failures when operated over long continuous periods for executing workflows. Diagnosing job problems and faults leading to eventual failures in this complex environment is difficult, specifically when the success of an entire workflow might be affected by a single job failure. In this paper, we introduce a model-based, hierarchical, reliable execution framework that encompass workflow specification, data provenance, execution tracking and online monitoring of each workflow task, also referred to as participants. The sequence of participants is described in an abstract parameterized view, which is translated into a concrete data dependency based sequence of participants with defined arguments. As participants belonging to a workflow are mapped onto machines and executed, periodic and on-demand monitoring of vital health parameters on allocated nodes is enabled according to pre-specified rules. These rules specify conditions that must be true pre-execution, during execution and post-execution. Monitoring information for each participant is propagated upwards through the reflex and healing architecture, which consists of a hierarchical network of decentralized fault management entities, called reflex engines. They are instantiated as state machines or timed automatons that change state and initiate reflexive mitigation action(s) upon occurrence of certain faults. We describe how this cluster reliability framework is combined with the workflow execution framework using formal rules and actions specified within a structure of first order predicate logic that enables a dynamic management design that reduces manual administrative workload, and increases cluster-productivity.

  17. Continuum Model for River Networks

    Science.gov (United States)

    Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.

    1995-07-01

    The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.

  18. Next generation framework for aquatic modeling of the Earth System

    Science.gov (United States)

    Fekete, B. M.; Wollheim, W. M.; Wisser, D.; Vörösmarty, C. J.

    2009-03-01

    Earth System model development is becoming an increasingly complex task. As scientists attempt to represent the physical and bio-geochemical processes and various feedback mechanisms in unprecedented detail, the models themselves are becoming increasingly complex. At the same time, the complexity of the surrounding IT infrastructure is growing as well. Earth System models must manage a vast amount of data in heterogeneous computing environments. Numerous development efforts are on the way to ease that burden and offer model development platforms that reduce IT challenges and allow scientists to focus on their science. While these new modeling frameworks (e.g. FMS, ESMF, CCA, OpenMI) do provide solutions to many IT challenges (performing input/output, managing space and time, establishing model coupling, etc.), they are still considerably complex and often have steep learning curves. The Next generation Framework for Aquatic Modeling of the Earth System (NextFrAMES, a revised version of FrAMES) have numerous similarities to those developed by other teams, but represents a novel model development paradigm. NextFrAMES is built around a modeling XML that lets modelers to express the overall model structure and provides an API for dynamically linked plugins to represent the processes. The model XML is executed by the NextFrAMES run-time engine that parses the model definition, loads the module plugins, performs the model I/O and executes the model calculations. NextFrAMES has a minimalistic view representing spatial domains and treats every domain (regardless of its layout such as grid, network tree, individual points, polygons, etc.) as vector of objects. NextFrAMES performs computations on multiple domains and interactions between different spatial domains are carried out through couplers. NextFrAMES allows processes to operate at different frequencies by providing rudimentary aggregation and disaggregation facilities. NextFrAMES was designed primarily for

  19. A Framework for the Specification of Acquisition Models

    National Research Council Canada - National Science Library

    Meyers, B

    2001-01-01

    .... The timing properties associated with the items receives special treatment. The value of a framework is that one can develop specifications of various acquisition models, such as waterfall, spiral, or incremental, as instances of that framework...

  20. A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Ebenezer Out-Nyarko

    2009-11-01

    Full Text Available Using Hidden Markov Models (HMMs as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks.

  1. A hybrid framework for reservoir characterization using fuzzy ranking and an artificial neural network

    Science.gov (United States)

    Wang, Baijie; Wang, Xin; Chen, Zhangxin

    2013-08-01

    Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization problems dealing with the complex underlying relationships inherent in well log data. Despite the utility of ANNs, the current limitation is that most existing applications simply focus on directly implementing existing ANN models instead of improving/customizing them to fit the specific reservoir characterization tasks at hand. In this paper, we propose a novel intelligent framework that integrates fuzzy ranking (FR) and multilayer perceptron (MLP) neural networks for reservoir characterization. FR can automatically identify a minimum subset of well log data as neural inputs, and the MLP is trained to learn the complex correlations from the selected well log data to a target reservoir property. FR guarantees the selection of the optimal subset of representative data from the overall well log data set for the characterization of a specific reservoir property; and, this implicitly improves the modeling and predication accuracy of the MLP. In addition, a growing number of industrial agencies are implementing geographic information systems (GIS) in field data management; and, we have designed the GFAR solution (GIS-based FR ANN Reservoir characterization solution) system, which integrates the proposed framework into a GIS system that provides an efficient characterization solution. Three separate petroleum wells from southwestern Alberta, Canada, were used in the presented case study of reservoir porosity characterization. Our experiments demonstrate that our method can generate reliable results.

  2. Model based risk assessment - the CORAS framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

    2004-04-15

    Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

  3. Web-based networking within the framework of ANENT

    International Nuclear Information System (INIS)

    Han, K.W.; Lee, E.J.; Kim, Y.T.; Nam, Y.M.; Kim, H.K.

    2004-01-01

    The Korea Atomic Energy Research Institute (KAERI) is actively participating in the Asian Network for Education in Nuclear Technology (ANENT), which is an IAEA activity to promote nuclear knowledge management. This has led KAERI to conduct a web-based networking for nuclear education and training in Asia. The networking encompasses the establishment of a relevant website and a system for a sustainable operation of the website. The established ANENT website features function as a database providing collected information, a link facilitating a systematic worldwide access to relevant websites, and an activity implementation for supporting the individual tasks of ANENT. The required information is being collected and loaded onto the database, and the website will be improved step by step. Consequently, networking is expected to play an important role, through cooperating with other networks, and thus contributing to a future global network for a sustainable development of nuclear technology. (author)

  4. Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

    International Nuclear Information System (INIS)

    Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

    2016-01-01

    Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics. In particular the model provides an explicit quantification of the economic value of DSR against alternative investment strategies. Through sensitivity analysis it is able to indicate the maximum price payable for DSR service such that DSR remains economically optimal against these alternatives. The proposed model thus provides Regulators with clear insights for overseeing DSR contractual arrangements. Further it highlights that differences exist in the economic perspective of the regulated DNO business and of customers. Our proposed model is therefore capable of highlighting instances where a particular investment strategy is favorable to the DNO but not to its customers, or vice-versa, and thus aspects of the regulatory framework which may

  5. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  6. Probabilistic logic networks a comprehensive framework for uncertain inference

    CERN Document Server

    Goertzel, Ben; Goertzel, Izabela Freire; Heljakka, Ari

    2008-01-01

    This comprehensive book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. A broad scope of reasoning types are considered.

  7. Network modelling methods for FMRI.

    Science.gov (United States)

    Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

    2011-01-15

    There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

  8. Drainage network extraction from a high-resolution DEM using parallel programming in the .NET Framework

    Science.gov (United States)

    Du, Chao; Ye, Aizhong; Gan, Yanjun; You, Jinjun; Duan, Qinyun; Ma, Feng; Hou, Jingwen

    2017-12-01

    High-resolution Digital Elevation Models (DEMs) can be used to extract high-accuracy prerequisite drainage networks. A higher resolution represents a larger number of grids. With an increase in the number of grids, the flow direction determination will require substantial computer resources and computing time. Parallel computing is a feasible method with which to resolve this problem. In this paper, we proposed a parallel programming method within the .NET Framework with a C# Compiler in a Windows environment. The basin is divided into sub-basins, and subsequently the different sub-basins operate on multiple threads concurrently to calculate flow directions. The method was applied to calculate the flow direction of the Yellow River basin from 3 arc-second resolution SRTM DEM. Drainage networks were extracted and compared with HydroSHEDS river network to assess their accuracy. The results demonstrate that this method can calculate the flow direction from high-resolution DEMs efficiently and extract high-precision continuous drainage networks.

  9. Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework.

    Science.gov (United States)

    Cai, Zuowei; Huang, Lihong; Guo, Zhenyuan; Zhang, Lingling; Wan, Xuting

    2015-08-01

    This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani's fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive-response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. A framework for multi-object tracking over distributed wireless camera networks

    Science.gov (United States)

    Gau, Victor; Hwang, Jenq-Neng

    2010-07-01

    In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

  11. A Smallholder Socio-hydrological Modelling Framework

    Science.gov (United States)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  12. Social Support System in Learning Network for lifelong learners: A Conceptual framework

    NARCIS (Netherlands)

    Nadeem, Danish; Stoyanov, Slavi; Koper, Rob

    2009-01-01

    Nadeem, D., Stoyanov, S., & Koper, R. (2009). Social support system in learning network for lifelong learners: A Conceptual framework [Special issue]. International Journal of Continuing Engineering Education and Life-Long Learning, 19(4/5/6), 337-351.

  13. A conceptual framework for analyzing sustainability strategies in industrial supply networks from an innovation perspective.

    NARCIS (Netherlands)

    van Bommel, H.W.M.; van Bommel, Harrie W.M.

    2011-01-01

    This article proposes a new conceptual framework concerning the implementation of sustainability in supply networks from an innovation perspective. Based upon a recent qualitative literature review in environmental, social/ethical and logistics/operations management journals, this article summarizes

  14. Spatial Modeling for Resources Framework (SMRF): A modular framework for developing spatial forcing data for snow modeling in mountain basins

    Science.gov (United States)

    Havens, Scott; Marks, Danny; Kormos, Patrick; Hedrick, Andrew

    2017-12-01

    In the Western US and many mountainous regions of the world, critical water resources and climate conditions are difficult to monitor because the observation network is generally very sparse. The critical resource from the mountain snowpack is water flowing into streams and reservoirs that will provide for irrigation, flood control, power generation, and ecosystem services. Water supply forecasting in a rapidly changing climate has become increasingly difficult because of non-stationary conditions. In response, operational water supply managers have begun to move from statistical techniques towards the use of physically based models. As we begin to transition physically based models from research to operational use, we must address the most difficult and time-consuming aspect of model initiation: the need for robust methods to develop and distribute the input forcing data. In this paper, we present a new open source framework, the Spatial Modeling for Resources Framework (SMRF), which automates and simplifies the common forcing data distribution methods. It is computationally efficient and can be implemented for both research and operational applications. We present an example of how SMRF is able to generate all of the forcing data required to a run physically based snow model at 50-100 m resolution over regions of 1000-7000 km2. The approach has been successfully applied in real time and historical applications for both the Boise River Basin in Idaho, USA and the Tuolumne River Basin in California, USA. These applications use meteorological station measurements and numerical weather prediction model outputs as input. SMRF has significantly streamlined the modeling workflow, decreased model set up time from weeks to days, and made near real-time application of a physically based snow model possible.

  15. Pedagogy framework design in social networked-based learning: Focus on children with learning difficulties

    Directory of Open Access Journals (Sweden)

    Samira Sadat Sajadi

    2014-09-01

    Full Text Available This paper presents an investigation on the theory of constructivism applicable for learners with learning difficulties, specifically learners with Attention Deficit Hyperactivity Disorder (ADHD. The primary objective of this paper is to determine whether a constructivist technology enhanced learning pedagogy could be used to help ADHD learners cope with their educational needs within a social-media learning environment. Preliminary work is stated here, in which we are seeking evidence to determine the viability of a constructivist approach for learners with ADHD. The novelty of this research lies in the proposals to support ADHD learners to overcome their weaknesses with appropriate pedagogically sound interventions. As a result, a framework has been designed to illuminate areas in which constructivist pedagogies require to address the limitations of ADHD learners. An analytical framework addressing the suitability of a constructivist learning for ADHD is developed from a combination of literature and expert advice from those involved in the education of learners with ADHD. This analytical framework is married to a new model of pedagogy, which the authors have derived from literature analysis. Future work will expand this model to develop a constructivist social network-based learning and eventually test it in specialist schools with ADHD learners.

  16. Multilayer network modeling creates opportunities for novel network statistics. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

    Science.gov (United States)

    Muldoon, Sarah Feldt

    2018-03-01

    As described in the review by Gosak et al., the field of network science has had enormous success in providing new insights into the structure and function of biological systems [1]. In the complex networks framework, system elements are network nodes, and connections between nodes represent some form of interaction between system elements [2]. The flexibility to define network nodes and edges to represent different aspects of biological systems has been employed to model numerous diverse systems at multiple scales.

  17. Sink-to-Sink Coordination Framework Using RPL: Routing Protocol for Low Power and Lossy Networks

    Directory of Open Access Journals (Sweden)

    Meer M. Khan

    2016-01-01

    Full Text Available RPL (Routing Protocol for low power and Lossy networks is recommended by Internet Engineering Task Force (IETF for IPv6-based LLNs (Low Power and Lossy Networks. RPL uses a proactive routing approach and each node always maintains an active path to the sink node. Sink-to-sink coordination defines syntax and semantics for the exchange of any network defined parameters among sink nodes like network size, traffic load, mobility of a sink, and so forth. The coordination allows sink to learn about the network condition of neighboring sinks. As a result, sinks can make coordinated decision to increase/decrease their network size for optimizing over all network performance in terms of load sharing, increasing network lifetime, and lowering end-to-end latency of communication. Currently, RPL does not provide any coordination framework that can define message exchange between different sink nodes for enhancing the network performance. In this paper, a sink-to-sink coordination framework is proposed which utilizes the periodic route maintenance messages issued by RPL to exchange network status observed at a sink with its neighboring sinks. The proposed framework distributes network load among sink nodes for achieving higher throughputs and longer network’s life time.

  18. Framework based on communicability and flow to analyze complex network dynamics

    Science.gov (United States)

    Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

    2018-05-01

    Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

  19. Systematic identification of crystallization kinetics within a generic modelling framework

    DEFF Research Database (Denmark)

    Abdul Samad, Noor Asma Fazli Bin; Meisler, Kresten Troelstrup; Gernaey, Krist

    2012-01-01

    A systematic development of constitutive models within a generic modelling framework has been developed for use in design, analysis and simulation of crystallization operations. The framework contains a tool for model identification connected with a generic crystallizer modelling tool-box, a tool...

  20. Enabling framework for service-oriented collaborative networks

    NARCIS (Netherlands)

    Sargolzaei, M.

    2018-01-01

    In today's economy, collaboration and co-development among organizations has evolved from the traditional format of static supply chains to the dynamic formation of federated organization networks. Networking among business partners has proven to yield lower costs, higher quality, larger

  1. DAPNA: an architectural framework for data processing networks

    NARCIS (Netherlands)

    Sözer, Hasan; Nouta, Sander; Wombacher, Andreas; Perona, Paolo

    2013-01-01

    A data processing network is as a set of (software) components connected through communication channels to apply a series of operations on data. Realization and maintenance of large-scale data processing networks necessitate an architectural approach that supports analysis, verification,

  2. Classification framework of knowledge transfer issues across value networks

    NARCIS (Netherlands)

    Bagheri, S.; Kusters, R.J.; Trienekens, J.J.M.; van der Zandt, Hugo; Cavalieri, S.; Ceretti, E.; Tolio, T.; Pezzotta, G.

    2016-01-01

    Co-creating integrated solutions with customers requires collaboration of different partners within a value network. In this emerging context, knowledge is considered as a foundation for value co-creation. Therefore, identifying different types of issues, with which value network actors in knowledge

  3. Knowledge and innovation in networks : a conceptual framework

    NARCIS (Netherlands)

    Man, de A.P.; Berends, J.J.; Lammers, I.S.; Raaij, van E.M.; Weele, van A.J.; Man, de A.P.

    2008-01-01

    Increasingly, innovation na longer takes place within individual firms, but within networks of organizations. An important requirement tor such network-based innovations to come to fruition is that knowledge flows across organizational boundaries. Yet, it is not self-evident or easy to create and

  4. A small-world network model of facial emotion recognition.

    Science.gov (United States)

    Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto

    2016-01-01

    Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.

  5. Research on the model of home networking

    Science.gov (United States)

    Yun, Xiang; Feng, Xiancheng

    2007-11-01

    It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

  6. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  7. A proposal framework for investigating website success in the context of e-banking:an analytic network process approach

    OpenAIRE

    Salehi, Mona; Keramati, Abbas

    2009-01-01

    This study proposes a framework to investigate website success factors, and their relative importance in selecting the most preferred e-banking website. For one thing, Updated Delone and Mclean IS success model is chosen to extract significant website success factors in the context of e-banking in Iran. Secondly, Updated Delone and McLean IS success model is extended through applying an analytic network process (ANP) approach in order to investigate the relative importance of each factor and ...

  8. Covering the Monitoring Network: A Unified Framework to Protect E-Commerce Security

    Directory of Open Access Journals (Sweden)

    Lirong Qiu

    2017-01-01

    Full Text Available Multimedia applications in smart electronic commerce (e-commerce, such as online trading and Internet marketing, always face security in storage and transmission of digital images and videos. This study addresses the problem of security in e-commerce and proposes a unified framework to analyze the security data. First, to allocate the definite security resources optimally, we build our e-commerce monitoring model as an undirected network, where a monitored node is a vertex of the graph and a connection between vertices is an undirected edge. Moreover, we aim to find a minimal cover for the monitoring network as the optimal solution of resource allocation, which is defined as the network monitoring minimization problem (NMM. This problem is proved to be NP-hard. Second, by analyzing the latent threats, we design a novel and trusted monitoring system that can integrate incident monitoring, data analysis, risk assessment, and security warnings. This system does not touch users’ privacy data. Third, we propose a sequential model-based risk assessment method, which can predict the risk according to the text semantics. Our experimental results on web scale data demonstrate that our system is flexible enough when monitoring, which also verify the effectiveness and efficiency of our system.

  9. A business case modelling framework for smart multi-energy districts

    OpenAIRE

    Good, Nicholas; Martinez Cesena, Eduardo Alejandro; Liu, Xuezhi; Mancarella, Pierluigi

    2017-01-01

    The potential energy, environmental, technical and economic benefits that might arise from multi-energy systems are increasing interest in smart districts. However, in a liberalised market, it is essential to develop a relevant attractive business case. This paper presents a holistic techno-economic framework that couples building/district, multi-network and business case assessment models for the development of robust business cases for smart multi-energy districts. The framework is demonstr...

  10. A multiobjective optimization framework for multicontaminant industrial water network design.

    Science.gov (United States)

    Boix, Marianne; Montastruc, Ludovic; Pibouleau, Luc; Azzaro-Pantel, Catherine; Domenech, Serge

    2011-07-01

    The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhijun Yu

    2009-01-01

    Full Text Available This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR is chosen there as reference node for time difference of arrive (TDOA calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.

  12. A framework for visualization of battlefield network behavior

    Science.gov (United States)

    Perzov, Yury; Yurcik, William

    2006-05-01

    An extensible network simulation application was developed to study wireless battlefield communications. The application monitors node mobility and depicts broadcast and unicast traffic as expanding rings and directed links. The network simulation was specially designed to support fault injection to show the impact of air strikes on disabling nodes. The application takes standard ns-2 trace files as an input and provides for performance data output in different graphical forms (histograms and x/y plots). Network visualization via animation of simulation output can be saved in AVI format that may serve as a basis for a real-time battlefield awareness system.

  13. Model parameter updating using Bayesian networks

    International Nuclear Information System (INIS)

    Treml, C.A.; Ross, Timothy J.

    2004-01-01

    This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

  14. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

    2015-01-01

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation

  15. A system-of-systems framework for the reliability analysis of distributed generation systems accounting for the impact of degraded communication networks

    International Nuclear Information System (INIS)

    Mo, Hua-Dong; Li, Yan-Fu; Zio, Enrico

    2016-01-01

    Highlights: • A system-of-systems framework is proposed for reliability analysis of DG system. • The impact of degraded communication networks is included and quantified. • Various uncertainties and contingencies in the DG system are considered. • A Monte Carlo simulation-optimal power flow computational framework is developed. • The results of the application study show the power of the proposed framework. - Abstract: Distributed generation (DG) systems install communication networks for managing real-time energy imbalance. Different from previous research, which typically assumes perfect communication networks, this work aims to quantitatively account for the impact of degraded communication networks on DG systems performance. The degraded behavior of communication networks is modeled by stochastic continuous time transmission delays and packet dropouts. On the DG systems side, we consider the inherent uncertainties of renewable energy sources, loads and energy prices. We develop a Monte Carlo simulation-optimal power flow (MCS-OPF) computational framework that is capable of generating consecutive time-dependent operating scenarios of the integrated system. Quantitative analysis is carried out to measure the impact of communication networks degradation onto the DG systems. For illustration, the framework is applied to a modified IEEE 13 nodes test feeder. The results demonstrate that the degraded communication networks can significantly deteriorate the performance of the integrated system. A grey differential model-based prediction method for reconstructing missing data is effective in mitigating the influence of the degraded communication networks.

  16. Implementation of a Framework for Collaborative Social Networks in E-Learning

    Science.gov (United States)

    Maglajlic, Seid

    2016-01-01

    This paper describes the implementation of a framework for the construction and utilization of social networks in ELearning. These social networks aim to enhance collaboration between all E-Learning participants (i.e. both traineeto-trainee and trainee-to-tutor communication are targeted). E-Learning systems that include a so-called "social…

  17. A statistical framework for differential network analysis from microarray data

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  18. Towards a framework for a network warfare capability

    CSIR Research Space (South Africa)

    Veerasamy, N

    2008-07-01

    Full Text Available . These include the legal issues, ethical dilemmas, technical solutions, financial impact and skill/manpower investment. Logical constraints/implications have been grouped together in the discussion that follows. 5.1.1 Legal Ethical Issues As network warfare... but the underlying causes of crime also needs to be understood. Ethics and morals play a significant role in determining the personality traits of an individual. Users will need to balance ethical dilemmas before engaging in offensive network warfare. Computers...

  19. Development of a distributed air pollutant dry deposition modeling framework

    International Nuclear Information System (INIS)

    Hirabayashi, Satoshi; Kroll, Charles N.; Nowak, David J.

    2012-01-01

    A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. - Highlights: ► A distributed air pollutant dry deposition modeling system was developed. ► The developed system enhances the functionality of i-Tree Eco. ► The developed system employs nationally available input datasets. ► The developed system is transferable to any U.S. city. ► Future planting and protection spots were visually identified in a case study. - Employing nationally available datasets and a GIS, this study will provide urban forest managers in U.S. cities a framework to quantify and visualize urban forest structure and its air pollution removal effect.

  20. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  1. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  2. Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

    DEFF Research Database (Denmark)

    Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2016-01-01

    Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....

  3. Models and algorithms for biomolecules and molecular networks

    CERN Document Server

    DasGupta, Bhaskar

    2016-01-01

    By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. * Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms * Sampling techniques for estimating evolutionary rates and generating molecular structures * Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations * End-of-chapter exercises

  4. A novel Direct Small World network model

    Directory of Open Access Journals (Sweden)

    LIN Tao

    2016-10-01

    Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.

  5. RMBNToolbox: random models for biochemical networks

    Directory of Open Access Journals (Sweden)

    Niemi Jari

    2007-05-01

    Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

  6. Modelling and predicting biogeographical patterns in river networks

    Directory of Open Access Journals (Sweden)

    Sabela Lois

    2016-04-01

    Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

  7. Simulation-Optimization Framework for Synthesis and Design of Natural Gas Downstream Utilization Networks

    Directory of Open Access Journals (Sweden)

    Saad A. Al-Sobhi

    2018-02-01

    Full Text Available Many potential diversification and conversion options are available for utilization of natural gas resources, and several design configurations and technology choices exist for conversion of natural gas to value-added products. Therefore, a detailed mathematical model is desirable for selection of optimal configuration and operating mode among the various options available. In this study, we present a simulation-optimization framework for the optimal selection of economic and environmentally sustainable pathways for natural gas downstream utilization networks by optimizing process design and operational decisions. The main processes (e.g., LNG, GTL, and methanol production, along with different design alternatives in terms of flow-sheeting for each main processing unit (namely syngas preparation, liquefaction, N2 rejection, hydrogen, FT synthesis, methanol synthesis, FT upgrade, and methanol upgrade units, are used for superstructure development. These processes are simulated using ASPEN Plus V7.3 to determine the yields of different processing units under various operating modes. The model has been applied to maximize total profit of the natural gas utilization system with penalties for environmental impact, represented by CO2eq emission obtained using ASPEN Plus for each flowsheet configuration and operating mode options. The performance of the proposed modeling framework is demonstrated using a case study.

  8. Statistical inference to advance network models in epidemiology.

    Science.gov (United States)

    Welch, David; Bansal, Shweta; Hunter, David R

    2011-03-01

    Contact networks are playing an increasingly important role in the study of epidemiology. Most of the existing work in this area has focused on considering the effect of underlying network structure on epidemic dynamics by using tools from probability theory and computer simulation. This work has provided much insight on the role that heterogeneity in host contact patterns plays on infectious disease dynamics. Despite the important understanding afforded by the probability and simulation paradigm, this approach does not directly address important questions about the structure of contact networks such as what is the best network model for a particular mode of disease transmission, how parameter values of a given model should be estimated, or how precisely the data allow us to estimate these parameter values. We argue that these questions are best answered within a statistical framework and discuss the role of statistical inference in estimating contact networks from epidemiological data. Copyright © 2011 Elsevier B.V. All rights reserved.

  9. Security Frameworks for Machine-to-Machine Devices and Networks

    Science.gov (United States)

    Demblewski, Michael

    Attacks against mobile systems have escalated over the past decade. There have been increases of fraud, platform attacks, and malware. The Internet of Things (IoT) offers a new attack vector for Cybercriminals. M2M contributes to the growing number of devices that use wireless systems for Internet connection. As new applications and platforms are created, old vulnerabilities are transferred to next-generation systems. There is a research gap that exists between the current approaches for security framework development and the understanding of how these new technologies are different and how they are similar. This gap exists because system designers, security architects, and users are not fully aware of security risks and how next-generation devices can jeopardize safety and personal privacy. Current techniques, for developing security requirements, do not adequately consider the use of new technologies, and this weakens countermeasure implementations. These techniques rely on security frameworks for requirements development. These frameworks lack a method for identifying next generation security concerns and processes for comparing, contrasting and evaluating non-human device security protections. This research presents a solution for this problem by offering a novel security framework that is focused on the study of the "functions and capabilities" of M2M devices and improves the systems development life cycle for the overall IoT ecosystem.

  10. RTnet -- A Flexible Hard Real-Time Networking Framework

    NARCIS (Netherlands)

    Kiszka, Jan; Wagner, Bernardo; Zhang, Yuchen; Broenink, Johannes F.

    2005-01-01

    In this paper, the open source project RTnet is presented. RTnet provides a customisable and extensible framework for hard real-time communication over Ethernet and other transport media. The paper describes architecture, core components, and protocols of RTnet. FireWire is introduced as a powerful

  11. A Novel Message Scheduling Framework for Delay Tolerant Networks Routing

    KAUST Repository

    Elwhishi, Ahmed; Ho, Pin-Han; Naik, K.; Shihada, Basem

    2013-01-01

    new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive

  12. Business model framework applications in health care: A systematic review.

    Science.gov (United States)

    Fredriksson, Jens Jacob; Mazzocato, Pamela; Muhammed, Rafiq; Savage, Carl

    2017-11-01

    It has proven to be a challenge for health care organizations to achieve the Triple Aim. In the business literature, business model frameworks have been used to understand how organizations are aligned to achieve their goals. We conducted a systematic literature review with an explanatory synthesis approach to understand how business model frameworks have been applied in health care. We found a large increase in applications of business model frameworks during the last decade. E-health was the most common context of application. We identified six applications of business model frameworks: business model description, financial assessment, classification based on pre-defined typologies, business model analysis, development, and evaluation. Our synthesis suggests that the choice of business model framework and constituent elements should be informed by the intent and context of application. We see a need for harmonization in the choice of elements in order to increase generalizability, simplify application, and help organizations realize the Triple Aim.

  13. Neural Network Based Models for Fusion Applications

    Science.gov (United States)

    Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

    2017-10-01

    Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-­network (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.

  14. NET: a new framework for the vectorization and examination of network data.

    Science.gov (United States)

    Lasser, Jana; Katifori, Eleni

    2017-01-01

    The analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like Drosophila tracheoles or leaf venation patterns: the Network Extraction Tool ( NET ) to extract data and the Graph-edit-GUI ( GeGUI ) to visualize and modify networks. NET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space. NET also provides tools for statistical analysis of the network properties, such as the number of nodes or total network length. Other, more complex metrics can be calculated by importing the vectorized network to specialized network analysis packages. GeGUI is designed to facilitate manual correction of non-planar networks as these may contain artifacts or spurious junctions due to branches crossing each other. It is tailored for but not limited to the processing of networks from microscopy images of Drosophila tracheoles. The networks extracted by NET closely approximate the network depicted in the original image. NET is fast, yields reproducible results and is able to capture the full geometry of the network, including curved branches. Additionally GeGUI allows easy handling and visualization of the networks.

  15. Framework and implementation of a continuous network-wide health monitoring system for roadways

    Science.gov (United States)

    Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

    2014-03-01

    According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.

  16. Adaptation in Food Networks: Theoretical Framework and Empirical Evidences

    Directory of Open Access Journals (Sweden)

    Gaetano Martino

    2013-03-01

    Full Text Available The paper concerns the integration in food networks under a governance point of view. We conceptualize the integration processes in terms of the adaptation theory and focus the issues related under a transaction cost economics perspective. We conjecture that the allocation of decisions rights between the parties to a transaction is a key instrument in order to cope with the sources of basic uncertainty in food networks: technological innovation, sustainability strategies, quality and safety objectives. Six case studies are proposed which contribute to corroborate our conjecture. Managerial patters based on a joint decision approach also are documented

  17. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  18. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  19. A Learning Framework for Control-Oriented Modeling of Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.

    2018-01-18

    Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.

  20. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  1. Network bandwidth utilization forecast model on high bandwidth networks

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-03-30

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  2. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  3. Adaptive spectrum decision framework for heterogeneous dynamic spectrum access networks

    CSIR Research Space (South Africa)

    Masonta, M

    2015-09-01

    Full Text Available Spectrum decision is the ability of a cognitive radio (CR) system to select the best available spectrum band to satisfy dynamic spectrum access network (DSAN) users¿ quality of service (QoS) requirements without causing harmful interference...

  4. Social Networking Framework for Universities in Saudi Arabia

    Science.gov (United States)

    Alqahtani, Sulaiman

    2016-01-01

    The interactive capacities of social networking instruments have unleashed a number of possibilities for enhancing teaching and learning in the higher education sector and many universities are engaged in harnessing the capabilities of these tools. While much valuable research has been conducted on this theme, scholarship has tended to be oriented…

  5. Towards smart service networks : An interdisciplinary diagnostic framework

    NARCIS (Netherlands)

    Wang, Yan; Taher, Yehia; van den Heuvel, Willem-Jan

    2015-01-01

    Service Networks (SNs) are open systems accommodating the co-production of new knowledge and services through organic peer-to-peer interactions. Key to broad success of SNs in practice is their ability to foster and ensure a high performance. By performance we mean the joint effort of tremendous

  6. Value of digital information networks : A holonic framework

    NARCIS (Netherlands)

    Madureira, A.J.P.S.

    2011-01-01

    The extraordinary level of interest worldwide in Digital Information Networks (DINs)’ deployment is due to the strong perception that they bring economic, social and environmental value. However, scientific attempts to evidence this perception lead to speculative, elusive or limited conclusions. In

  7. A framework for modelling the complexities of food and water security under globalisation

    Science.gov (United States)

    Dermody, Brian J.; Sivapalan, Murugesu; Stehfest, Elke; van Vuuren, Detlef P.; Wassen, Martin J.; Bierkens, Marc F. P.; Dekker, Stefan C.

    2018-01-01

    We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

  8. framework for modelling the complexities of food and water security under globalisation

    Directory of Open Access Journals (Sweden)

    B. J. Dermody

    2018-01-01

    Full Text Available We present a new framework for modelling the complexities of food and water security under globalisation. The framework sets out a method to capture regional and sectoral interdependencies and cross-scale feedbacks within the global food system that contribute to emergent water use patterns. The framework integrates aspects of existing models and approaches in the fields of hydrology and integrated assessment modelling. The core of the framework is a multi-agent network of city agents connected by infrastructural trade networks. Agents receive socio-economic and environmental constraint information from integrated assessment models and hydrological models respectively and simulate complex, socio-environmental dynamics that operate within those constraints. The emergent changes in food and water resources are aggregated and fed back to the original models with minimal modification of the structure of those models. It is our conviction that the framework presented can form the basis for a new wave of decision tools that capture complex socio-environmental change within our globalised world. In doing so they will contribute to illuminating pathways towards a sustainable future for humans, ecosystems and the water they share.

  9. A port-Hamiltonian approach to power network modeling and analysis

    NARCIS (Netherlands)

    Fiaz, S.; Zonetti, D.; Ortega, R.; Scherpen, J.M.A.; van der Schaft, A.J.

    2013-01-01

    In this paper we present a systematic framework for modeling of power networks. The basic idea is to view the complete power network as a port-Hamiltonian system on a graph where edges correspond to components of the power network and nodes are buses. The interconnection constraints are given by the

  10. Surgical model-view-controller simulation software framework for local and collaborative applications.

    Science.gov (United States)

    Maciel, Anderson; Sankaranarayanan, Ganesh; Halic, Tansel; Arikatla, Venkata Sreekanth; Lu, Zhonghua; De, Suvranu

    2011-07-01

    Surgical simulations require haptic interactions and collaboration in a shared virtual environment. A software framework for decoupled surgical simulation based on a multi-controller and multi-viewer model-view-controller (MVC) pattern was developed and tested. A software framework for multimodal virtual environments was designed, supporting both visual interactions and haptic feedback while providing developers with an integration tool for heterogeneous architectures maintaining high performance, simplicity of implementation, and straightforward extension. The framework uses decoupled simulation with updates of over 1,000 Hz for haptics and accommodates networked simulation with delays of over 1,000 ms without performance penalty. The simulation software framework was implemented and was used to support the design of virtual reality-based surgery simulation systems. The framework supports the high level of complexity of such applications and the fast response required for interaction with haptics. The efficacy of the framework was tested by implementation of a minimally invasive surgery simulator. A decoupled simulation approach can be implemented as a framework to handle simultaneous processes of the system at the various frame rates each process requires. The framework was successfully used to develop collaborative virtual environments (VEs) involving geographically distributed users connected through a network, with the results comparable to VEs for local users.

  11. Tissue microstructure estimation using a deep network inspired by a dictionary-based framework.

    Science.gov (United States)

    Ye, Chuyang

    2017-12-01

    Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies. It models the diffusion signal with three compartments that are characterized by distinct diffusion properties, and the parameters in the model describe tissue microstructure. In NODDI, these parameters are estimated in a maximum likelihood framework, where the nonlinear model fitting is computationally intensive. Therefore, efforts have been made to develop efficient and accurate algorithms for NODDI microstructure estimation, which is still an open problem. In this work, we propose a deep network based approach that performs end-to-end estimation of NODDI microstructure, which is named Microstructure Estimation using a Deep Network (MEDN). MEDN comprises two cascaded stages and is motivated by the AMICO algorithm, where the NODDI microstructure estimation is formulated in a dictionary-based framework. The first stage computes the coefficients of the dictionary. It resembles the solution to a sparse reconstruction problem, where the iterative process in conventional estimation approaches is unfolded and truncated, and the weights are learned instead of predetermined by the dictionary. In the second stage, microstructure properties are computed from the output of the first stage, which resembles the weighted sum of normalized dictionary coefficients in AMICO, and the weights are also learned. Because spatial consistency of diffusion signals can be used to reduce the effect of noise, we also propose MEDN+, which is an extended version of MEDN. MEDN

  12. Marketing communications model for innovation networks

    Directory of Open Access Journals (Sweden)

    Tiago João Freitas Correia

    2015-10-01

    Full Text Available Innovation is an increasingly relevant concept for the success of any organization, but it also represents a set of internal and external considerations, barriers and challenges to overcome. Along the concept of innovation, new paradigms emerge such as open innovation and co-creation that are simultaneously innovation modifiers and intensifiers in organizations, promoting organizational openness and stakeholder integration within the value creation process. Innovation networks composed by a multiplicity of agents in co-creative work perform as innovation mechanisms to face the increasingly complexity of products, services and markets. Technology, especially the Internet, is an enabler of all process among organizations supported by co-creative platforms for innovation. The definition of marketing communication strategies that promote motivation and involvement of all stakeholders in synergic creation and external promotion is the central aspect of this research. The implementation of the projects is performed by participative workshops with stakeholders from Madan Parque through IDEAS(REVOLUTION methodology and the operational model LinkUp parameterized for the project. The project is divided into the first part, the theoretical framework, and the second part where a model is developed for the marketing communication strategies that appeal to the Madan Parque case study. Keywords: Marketing Communication; Open Innovation, Technology; Innovation Networks; Incubator; Co-Creation.

  13. A graph model for opportunistic network coding

    KAUST Repository

    Sorour, Sameh

    2015-08-12

    © 2015 IEEE. Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.

  14. LAMMPS Framework for Dynamic Bonding and an Application Modeling DNA

    DEFF Research Database (Denmark)

    Svaneborg, Carsten

    2012-01-01

    and bond types. When breaking bonds, all angular and dihedral interactions involving broken bonds are removed. The framework allows chemical reactions to be modeled, and use it to simulate a simplistic, coarse-grained DNA model. The resulting DNA dynamics illustrates the power of the present framework....

  15. A qualitative evaluation approach for energy system modelling frameworks

    DEFF Research Database (Denmark)

    Wiese, Frauke; Hilpert, Simon; Kaldemeyer, Cord

    2018-01-01

    properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks...

  16. A Framework for Formal Modeling and Analysis of Organizations

    NARCIS (Netherlands)

    Jonker, C.M.; Sharpanskykh, O.; Treur, J.; P., Yolum

    2007-01-01

    A new, formal, role-based, framework for modeling and analyzing both real world and artificial organizations is introduced. It exploits static and dynamic properties of the organizational model and includes the (frequently ignored) environment. The transition is described from a generic framework of

  17. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

    2010-01-01

    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  18. Perception of similarity: a model for social network dynamics

    International Nuclear Information System (INIS)

    Javarone, Marco Alberto; Armano, Giuliano

    2013-01-01

    Some properties of social networks (e.g., the mixing patterns and the community structure) appear deeply influenced by the individual perception of people. In this work we map behaviors by considering similarity and popularity of people, also assuming that each person has his/her proper perception and interpretation of similarity. Although investigated in different ways (depending on the specific scientific framework), from a computational perspective similarity is typically calculated as a distance measure. In accordance with this view, to represent social network dynamics we developed an agent-based model on top of a hyperbolic space on which individual distance measures are calculated. Simulations, performed in accordance with the proposed model, generate small-world networks that exhibit a community structure. We deem this model to be valuable for analyzing the relevant properties of real social networks. (paper)

  19. Application priority framework for fixed mobile converged communication networks

    OpenAIRE

    Chaudhry, Saqib Rasool

    2011-01-01

    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University. The current prospects in wired and wireless access networks, it is becoming increasingly important to address potential convergence in order to offer integrated broadband services. These systems will need to offer higher data transmission capacities and long battery life, which is the catalyst for an everincreasing variety of air interface technologies targeting local area to wide area connec...

  20. Spinal Cord Injury Model System Information Network

    Science.gov (United States)

    ... the UAB-SCIMS More The UAB-SCIMS Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network as a resource to promote knowledge in the ...

  1. A Framework for Supporting Survivability, Network Planning and Cross-Layer Optimization in Future Multi-Domain Terabit Networks

    Energy Technology Data Exchange (ETDEWEB)

    Baldin, Ilya [Renaissance Computing Inst. (RENCI), Chapel Hill, NC (United States); Huang, Shu [Renaissance Computing Inst. (RENCI), Chapel Hill, NC (United States); Gopidi, Rajesh [Univ. of North Carolina, Chapel Hill, NC (United States)

    2015-01-28

    This final project report describes the accomplishments, products and publications from the award. It includes the overview of the project goals to devise a framework for managing resources in multi-domain, multi-layer networks, as well the details of the mathematical problem formulation and the description of the prototype built to prove the concept.

  2. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  3. Introducing Synchronisation in Deterministic Network Models

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

    2006-01-01

    The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

  4. Population Balance Models: A useful complementary modelling framework for future WWTP modelling

    DEFF Research Database (Denmark)

    Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

    2014-01-01

    Population Balance Models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by statistical distributions. This has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit...

  5. Population balance models: a useful complementary modelling framework for future WWTP modelling

    DEFF Research Database (Denmark)

    Nopens, Ingmar; Torfs, Elena; Ducoste, Joel

    2015-01-01

    Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling...

  6. Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

    Science.gov (United States)

    Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

    2015-05-01

    We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.

  7. Modeling Cancer Metastasis using Global, Quantitative and Integrative Network Biology

    DEFF Research Database (Denmark)

    Schoof, Erwin; Erler, Janine

    understanding of molecular processes which are fundamental to tumorigenesis. In Article 1, we propose a novel framework for how cancer mutations can be studied by taking into account their effect at the protein network level. In Article 2, we demonstrate how global, quantitative data on phosphorylation dynamics...... can be generated using MS, and how this can be modeled using a computational framework for deciphering kinase-substrate dynamics. This framework is described in depth in Article 3, and covers the design of KinomeXplorer, which allows the prediction of kinases responsible for modulating observed...... phosphorylation dynamics in a given biological sample. In Chapter III, we move into Integrative Network Biology, where, by combining two fundamental technologies (MS & NGS), we can obtain more in-depth insights into the links between cellular phenotype and genotype. Article 4 describes the proof...

  8. Framework for implementation of maintenance management in distribution network service providers

    International Nuclear Information System (INIS)

    Gomez Fernandez, Juan Francisco; Crespo Marquez, Adolfo

    2009-01-01

    Distribution network service providers (DNSP) are companies dealing with network infrastructure, such as distribution of gas, water, electricity or telecommunications, and they require the development of special maintenance management (MM) capabilities in order to satisfy the needs of their customers. In this sector, maintenance management information systems are essential to ensure control, gain knowledge and improve decision making. The aim of this paper is the study of specific characteristics of maintenance in these types of companies. We will investigate existing standards and best management practices with the scope of defining a suitable ad-hoc framework for implementation of maintenance management. The conclusion of the work supports the proposition of a framework consisting on a processes framework based on a structure of systems, integrated for continuous improvement of maintenance activities. The paper offers a very practical approach to the problem, as a result of more of 10 years of professional experience within this sector, and specially focused to network maintenance.

  9. Web-based networking within the framework of ANENT

    International Nuclear Information System (INIS)

    Han, K.W.; Lee, E.J.; Kim, Y.T.; Nam, Y.M.

    2004-01-01

    Recognizing the importance of nuclear knowledge management, KAERI has been actively involved in the establishment of the IAEA Asian Network for Higher Education in Nuclear Technology (ANENT). The institute, on behalf of the Korean government, initiated discussions with the IAEA on the concept of ANENT and hosted an IAEA Consultant Meeting in July 2003, which was intended to prepare a draft report for the establishment of ANENT. From the preparatory stage, the institute volunteered to establish a website to support the ANENT activities. This led the ANENT Coordination Committee, at its first meeting in April 2004, to designate KAERI as the coordinating organization for a work package on the 'Web-based Exchange of Information and Material for Nuclear Education and Training'. The committee also identified four more work packages and the respective coordinators at the same meeting. To implement the task of the web-based exchange, a website (www.anent-tepm.org) was designed with three functional objectives. The first function was to provide the ANENT member websites with a comprehensive connection with each other as well as to other sites relevant to nuclear education and training. The second one was to provide the collected information and materials. The last one was to provide a systematic and sustainable means to add, revise, and share the information and materials of high quality. As a result, the web site has been structured to deal with the overall information about ANENT, group activities (e.g. Coordination Committee meetings and work packages), inter-organization (or network) link, thematic information/materials database (or link), and the management of human resources. The ANENT website has been temporarily operated and is being revised to fulfil the objectives and reach a consensus among the ANENT members. In parallel, a set of information about education and training courses and teaching materials available from the network members is being collected, which

  10. eWOM credibility on social networking sites: A framework

    OpenAIRE

    Moran, Gillian; Muzellec, Laurent

    2017-01-01

    Social networking sites (SNS) offer brands the ability to spread positive electronic Word of Mouth (eWOM) for the purposes of building awareness and acquiring new customers. However, the credibility of eWOM is threatened of late as marketers increasingly try to manipulate eWOM practices on SNS. A greater understanding of eWOM credibility is necessary to better enable marketers to leverage true consumer engagement by generating credible peer-to-peer communications. Yet, to date, there is no on...

  11. Network Traffic Monitoring Using Poisson Dynamic Linear Models

    Energy Technology Data Exchange (ETDEWEB)

    Merl, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2011-05-09

    In this article, we discuss an approach for network forensics using a class of nonstationary Poisson processes with embedded dynamic linear models. As a modeling strategy, the Poisson DLM (PoDLM) provides a very flexible framework for specifying structured effects that may influence the evolution of the underlying Poisson rate parameter, including diurnal and weekly usage patterns. We develop a novel particle learning algorithm for online smoothing and prediction for the PoDLM, and demonstrate the suitability of the approach to real-time deployment settings via a new application to computer network traffic monitoring.

  12. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  13. Chemical structure, network topology, and porosity effects on the mechanical properties of Zeolitic Imidazolate Frameworks

    OpenAIRE

    Tan, J. C.; Bennett, T. D.; Cheetham, A. K.

    2010-01-01

    The mechanical properties of seven zeolitic imidazolate frameworks (ZIFs) based on five unique network topologies have been systematically characterized by single-crystal nanoindentation studies. We demonstrate that the elastic properties of ZIF crystal structures are strongly correlated to the framework density and the underlying porosity. For the systems considered here, the elastic modulus was found to range from 3 to 10 GPa, whereas the hardness property lies between 300 MPa and 1.1 GPa. ...

  14. A QoS Framework with Traffic Request in Wireless Mesh Network

    Science.gov (United States)

    Fu, Bo; Huang, Hejiao

    In this paper, we consider major issues in ensuring greater Quality-of-Service (QoS) in Wireless Mesh Networks (WMNs), specifically with regard to reliability and delay. To this end, we use traffic request to record QoS requirements of data flows. In order to achieve required QoS for all data flows efficiently and with high portability, we develop Network State Update Algorithm. All assumptions, definitions, and algorithms are made exclusively with WMNs in mind, guaranteeing the portability of our framework to various environments in WMNs. The simulation results in proof that our framework is correct.

  15. Packets with deadlines a framework for real-time wireless networks

    CERN Document Server

    Hou, I-Hong

    2013-01-01

    With the explosive increase in the number of mobile devices and applications, it is anticipated that wireless traffic will increase exponentially in the coming years. Moreover, future wireless networks all carry a wide variety of flows, such as video streaming, online gaming, and VoIP, which have various quality of service (QoS) requirements. Therefore, a new mechanism that can provide satisfactory performance to the complete variety of all kinds of flows, in a coherent and unified framework, is needed.In this book, we introduce a framework for real-time wireless networks. This consists of a m

  16. Collaborative Procurement within Enterprise Networks: A Literature Review, a Reference Framework and a Case Study

    Science.gov (United States)

    Cagnazzo, Luca; Taticchi, Paolo; Bidini, Gianni; Sameh, Mohamed

    Collaboration among companies is nowadays a success leverage from those involved, especially for SMEs. The networking advantages are several and among them, reducing costs is a critical one. Costs reduction due to the possibility of Collaborative Procurement (CP) among partners is one of the most important achievements in a network. While the literature available offers good bases for managing single contractor procurement issues, little research addresses the case of CP within Enterprise Networks (ENs). This paper explore the mentioned issue and proposes a general framework for managing CP in ENs, those with the Virtual Development Office (VDO) structure. The findings from the application of the framework proposed in an Italian network are highlighted so as to provide preliminary results and drive future research.

  17. Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

    Science.gov (United States)

    Bosse, Stefan

    2013-05-01

    Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour

  18. Conceptualising Business Models: Definitions, Frameworks and Classifications

    OpenAIRE

    Erwin Fielt

    2013-01-01

    The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in...

  19. A network model for characterizing brine channels in sea ice

    Science.gov (United States)

    Lieblappen, Ross M.; Kumar, Deip D.; Pauls, Scott D.; Obbard, Rachel W.

    2018-03-01

    The brine pore space in sea ice can form complex connected structures whose geometry is critical in the governance of important physical transport processes between the ocean, sea ice, and surface. Recent advances in three-dimensional imaging using X-ray micro-computed tomography have enabled the visualization and quantification of the brine network morphology and variability. Using imaging of first-year sea ice samples at in situ temperatures, we create a new mathematical network model to characterize the topology and connectivity of the brine channels. This model provides a statistical framework where we can characterize the pore networks via two parameters, depth and temperature, for use in dynamical sea ice models. Our approach advances the quantification of brine connectivity in sea ice, which can help investigations of bulk physical properties, such as fluid permeability, that are key in both global and regional sea ice models.

  20. A Network Model of Interpersonal Alignment in Dialog

    Directory of Open Access Journals (Sweden)

    Alexander Mehler

    2010-06-01

    Full Text Available In dyadic communication, both interlocutors adapt to each other linguistically, that is, they align interpersonally. In this article, we develop a framework for modeling interpersonal alignment in terms of the structural similarity of the interlocutors’ dialog lexica. This is done by means of so-called two-layer time-aligned network series, that is, a time-adjusted graph model. The graph model is partitioned into two layers, so that the interlocutors’ lexica are captured as subgraphs of an encompassing dialog graph. Each constituent network of the series is updated utterance-wise. Thus, both the inherent bipartition of dyadic conversations and their gradual development are modeled. The notion of alignment is then operationalized within a quantitative model of structure formation based on the mutual information of the subgraphs that represent the interlocutor’s dialog lexica. By adapting and further developing several models of complex network theory, we show that dialog lexica evolve as a novel class of graphs that have not been considered before in the area of complex (linguistic networks. Additionally, we show that our framework allows for classifying dialogs according to their alignment status. To the best of our knowledge, this is the first approach to measuring alignment in communication that explores the similarities of graph-like cognitive representations.

  1. An integrated knowledge-based framework for synthesis and design of enterprise-wide processing networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    material, product portfolio and process technology selection for a given market scenario, their sustainability metrics and risk of investment under market uncertainties enabling risk-aware decision making. The framework is highlighted with successful applications for soybean oil processing (food technology......, the synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc) and engineering levels (considering synthesis, design and optimization...

  2. A Game-theoretic Framework for Network Coding Based Device-to-Device Communications

    KAUST Repository

    Douik, Ahmed S.; Sorour, Sameh; Tembine, Hamidou; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based deviceto- device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.

  3. An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

    Directory of Open Access Journals (Sweden)

    Xiangmin Guan

    2015-01-01

    Full Text Available Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology.

  4. A Game-theoretic Framework for Network Coding Based Device-to-Device Communications

    KAUST Repository

    Douik, Ahmed

    2016-06-29

    This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based deviceto- device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.

  5. The study and implementation of the wireless network data security model

    Science.gov (United States)

    Lin, Haifeng

    2013-03-01

    In recent years, the rapid development of Internet technology and the advent of information age, people are increasing the strong demand for the information products and the market for information technology. Particularly, the network security requirements have become more sophisticated. This paper analyzes the wireless network in the data security vulnerabilities. And a list of wireless networks in the framework is the serious defects with the related problems. It has proposed the virtual private network technology and wireless network security defense structure; and it also given the wireless networks and related network intrusion detection model for the detection strategies.

  6. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  7. A Modeling Framework for Conventional and Heat Integrated Distillation Columns

    DEFF Research Database (Denmark)

    Bisgaard, Thomas; Huusom, Jakob Kjøbsted; Abildskov, Jens

    2013-01-01

    In this paper, a generic, modular model framework for describing fluid separation by distillation is presented. At present, the framework is able to describe a conventional distillation column and a heat-integrated distillation column, but due to a modular structure the database can be further...

  8. How to model wireless mesh networks topology

    International Nuclear Information System (INIS)

    Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M

    2013-01-01

    The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches

  9. Model checking mobile ad hoc networks

    NARCIS (Netherlands)

    Ghassemi, Fatemeh; Fokkink, Wan

    2016-01-01

    Modeling arbitrary connectivity changes within mobile ad hoc networks (MANETs) makes application of automated formal verification challenging. We use constrained labeled transition systems as a semantic model to represent mobility. To model check MANET protocols with respect to the underlying

  10. A DSM-based framework for integrated function modelling

    DEFF Research Database (Denmark)

    Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.

    2017-01-01

    an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...... of the functionality of a system. The article further presents the application of the framework based on a product example. Finally, an empirical study in industry is presented. Therein, feedback on the potential of the proposed framework to support interdisciplinary design practice as well as on areas of further...

  11. Understanding Global Change: Frameworks and Models for Teaching Systems Thinking

    Science.gov (United States)

    Bean, J. R.; Mitchell, K.; Zoehfeld, K.; Oshry, A.; Menicucci, A. J.; White, L. D.; Marshall, C. R.

    2017-12-01

    The scientific and education communities must impart to teachers, students, and the public an understanding of how the various factors that drive climate and global change operate, and why the rates and magnitudes of these changes related to human perturbation of Earth system processes today are cause for deep concern. Even though effective educational modules explaining components of the Earth and climate system exist, interdisciplinary learning tools are necessary to conceptually link the causes and consequences of global changes. To address this issue, the Understanding Global Change Project at the University of California Museum of Paleontology (UCMP) at UC Berkeley developed an interdisciplinary framework that organizes global change topics into three categories: (1) causes of climate change, both human and non-human (e.g., burning of fossil fuels, deforestation, Earth's tilt and orbit), (2) Earth system processes that shape the way the Earth works (e.g., Earth's energy budget, water cycle), and (3) the measurable changes in the Earth system (e.g., temperature, precipitation, ocean acidification). To facilitate student learning about the Earth as a dynamic, interacting system, a website will provide visualizations of Earth system models and written descriptions of how each framework topic is conceptually linked to other components of the framework. These visualizations and textual summarizations of relationships and feedbacks in the Earth system are a unique and crucial contribution to science communication and education, informed by a team of interdisciplinary scientists and educators. The system models are also mechanisms by which scientists can communicate how their own work informs our understanding of the Earth system. Educators can provide context and relevancy for authentic datasets and concurrently can assess student understanding of the interconnectedness of global change phenomena. The UGC resources will be available through a web-based platform and

  12. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  13. Research of G3-PLC net self-organization processes in the NS-3 modeling framework

    Science.gov (United States)

    Pospelova, Irina; Chebotayev, Pavel; Klimenko, Aleksey; Myakochin, Yuri; Polyakov, Igor; Shelupanov, Alexander; Zykov, Dmitriy

    2017-11-01

    When modern infocommunication networks are designed, the combination of several data transfer channels is widely used. It is necessary for the purposes of improvement in quality and robustness of communication. Communication systems based on more than one data transfer channel are named heterogeneous communication systems. For the design of a heterogeneous network, the most optimal solution is the use of mesh technology. Mesh technology ensures message delivery to the destination under conditions of unpredictable interference environment situation in each of two channels. Therewith, one of the high-priority problems is the choice of a routing protocol when the mesh networks are designed. An important design stage for any computer network is modeling. Modeling allows us to design a few different variants of design solutions and also to compute all necessary functional specifications for each of these solutions. As a result, it allows us to reduce costs for the physical realization of a network. In this article the research of dynamic routing in the NS3 simulation modeling framework is presented. The article contains an evaluation of simulation modeling applicability in solving the problem of heterogeneous networks design. Results of modeling may be afterwards used for physical realization of this kind of networks.

  14. Social Support Theory: A New Framework for Exploring Gender Differences in Business Owner Networks

    DEFF Research Database (Denmark)

    Neergaard, Helle

    The paper argues that to advance knowledge about small firm networks and consider the impact of gender, research should also consider the network experiences of women business owners. To engage in such research, this paper proposes a conceptual model of business owner networking which is informed...... by social support theory....

  15. ALTENER. Strategic framework municipal solid waste. Waste for energy network

    International Nuclear Information System (INIS)

    Kwant, K.W.; Van Halen, C.; Pfeiffer, A.E.

    1997-01-01

    General objective of European, national and regional waste for energy (WfE) policies is to support sustainable development. In each of the Altener WfE countries (Austria, Denmark, Finland, Italy, Netherlands, Portugal, Spain, Sweden and UK) general waste management strategies have been implemented. Common aspects are waste management hierarchies and general objectives such as: (1) to reduce the amount of wastes; (2) to make the best use of the wastes that are produced; and (3) to choose waste management practices, which (4) minimise the risks of immediate and future environmental pollution and harm to human health. All WfE countries have defined an order of preference for waste handling, starting with prevention as most preferred option, through re-use and recycling, thermal treatment with energy-recovery to landfill as a least desired option. In all Altener WfE countries, waste management structures are in a phase of transformation. At least three general transition processes can be recognized to take place, which are of great importance for the waste for energy future of the Altener countries: (1) increased energy recovery from MSW; (2) increased separation of MSW for recycling and recovery; and (3) reorganization of landfills. Two groups of instruments to stimulate the use of waste to energy are distinguished: (1) instruments, aiming to create improved WfE solutions; and (2) instruments, aiming to create a WfE market. In this framework document an overview is given of today's WfE situation in 9 European countries, as well as up-to-date national waste and energy policies, including the available instruments and future goals

  16. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

  17. Theoretical Models, Assessment Frameworks and Test Construction.

    Science.gov (United States)

    Chalhoub-Deville, Micheline

    1997-01-01

    Reviews the usefulness of proficiency models influencing second language testing. Findings indicate that several factors contribute to the lack of congruence between models and test construction and make a case for distinguishing between theoretical models. Underscores the significance of an empirical, contextualized and structured approach to the…

  18. The new challenges of multiplex networks: Measures and models

    Science.gov (United States)

    Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

    2017-02-01

    What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.

  19. Bayesian exponential random graph modeling of whole-brain structural networks across lifespan

    OpenAIRE

    Sinke, Michel R T; Dijkhuizen, Rick M; Caimo, Alberto; Stam, Cornelis J; Otte, Wim

    2016-01-01

    Descriptive neural network analyses have provided important insights into the organization of structural and functional networks in the human brain. However, these analyses have limitations for inter-subject or between-group comparisons in which network sizes and edge densities may differ, such as in studies on neurodevelopment or brain diseases. Furthermore, descriptive neural network analyses lack an appropriate generic null model and a unifying framework. These issues may be solved with an...

  20. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina

    2012-12-29

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

  1. POSITIVE LEADERSHIP MODELS: THEORETICAL FRAMEWORK AND RESEARCH

    Directory of Open Access Journals (Sweden)

    Javier Blanch, Francisco Gil

    2016-09-01

    Full Text Available The objective of this article is twofold; firstly, we establish the theoretical boundaries of positive leadership and the reasons for its emergence. It is related to the new paradigm of positive psychology that has recently been shaping the scope of organizational knowledge. This conceptual framework has triggered the development of the various forms of positive leadership (i.e. transformational, servant, spiritual, authentic, and positive. Although the construct does not seem univocally defined, these different types of leadership overlap and share a significant affinity. Secondly, we review the empirical evidence that shows the impact of positive leadership in organizations and we highlight the positive relationship between these forms of leadership and key positive organizational variables. Lastly, we analyse future research areas in order to further develop this concept.

  2. Sensor network based solar forecasting using a local vector autoregressive ridge framework

    Energy Technology Data Exchange (ETDEWEB)

    Xu, J. [Stony Brook Univ., NY (United States); Yoo, S. [Brookhaven National Lab. (BNL), Upton, NY (United States); Heiser, J. [Brookhaven National Lab. (BNL), Upton, NY (United States); Kalb, P. [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-04-04

    The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

  3. Network structure exploration via Bayesian nonparametric models

    International Nuclear Information System (INIS)

    Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

    2015-01-01

    Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

  4. A Mutual Authentication Framework for Wireless Medical Sensor Networks.

    Science.gov (United States)

    Srinivas, Jangirala; Mishra, Dheerendra; Mukhopadhyay, Sourav

    2017-05-01

    Wireless medical sensor networks (WMSN) comprise of distributed sensors, which can sense human physiological signs and monitor the health condition of the patient. It is observed that providing privacy to the patient's data is an important issue and can be challenging. The information passing is done via the public channel in WMSN. Thus, the patient, sensitive information can be obtained by eavesdropping or by unauthorized use of handheld devices which the health professionals use in monitoring the patient. Therefore, there is an essential need of restricting the unauthorized access to the patient's medical information. Hence, the efficient authentication scheme for the healthcare applications is needed to preserve the privacy of the patients' vital signs. To ensure secure and authorized communication in WMSN, we design a symmetric key based authentication protocol for WMSN environment. The proposed protocol uses only computationally efficient operations to achieve lightweight attribute. We analyze the security of the proposed protocol. We use a formal security proof algorithm to show the scheme security against known attacks. We also use the Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator to show protocol secure against man-in-the-middle attack and replay attack. Additionally, we adopt an informal analysis to discuss the key attributes of the proposed scheme. From the formal proof of security, we can see that an attacker has a negligible probability of breaking the protocol security. AVISPA simulator also demonstrates the proposed scheme security against active attacks, namely, man-in-the-middle attack and replay attack. Additionally, through the comparison of computational efficiency and security attributes with several recent results, proposed scheme seems to be battered.

  5. FSO-Based Vertical Backhaul/Fronthaul Framework for 5G+ Wireless Networks

    KAUST Repository

    Alzenad, Mohamed

    2018-01-12

    The presence of a super high rate, but also cost-efficient, easy-to-deploy, and scalable, back-haul/fronthaul framework, is essential in the upcoming 5G wireless networks and beyond. Motivated by the mounting interest in unmanned flying platforms of various types, including UAVs, drones, balloons, and HAPs/MAPs/LAPs, which we refer to as networked flying platforms (NFPs), for providing communications services, and by the recent advances in free space optics (FSO), this article investigates the feasibility of a novel vertical backhaul/fronthaul framework where the NFPs transport the backhaul/fronthaul traffic between the access and core networks via point-to-point FSO links. The performance of the proposed innovative approach is investigated under different weather conditions and a broad range of system parameters. Simulation results demonstrate that the FSO-based vertical backhaul/fronthaul framework can offer data rates higher than the baseline alternatives, and thus can be considered a promising solution to the emerging backhaul/fronthaul requirements of the 5G+ wireless networks, particularly in the presence of ultra-dense heterogeneous small cells. This article also presents the challenges that accompany such a novel framework and provides some key ideas toward overcoming these challenges.

  6. A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks

    NARCIS (Netherlands)

    De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob

    2008-01-01

    De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.

  7. FSO-Based Vertical Backhaul/Fronthaul Framework for 5G+ Wireless Networks

    KAUST Repository

    Alzenad, Mohamed; Shakir, Muhammad Z.; Yanikomeroglu, Halim; Alouini, Mohamed-Slim

    2018-01-01

    The presence of a super high rate, but also cost-efficient, easy-to-deploy, and scalable, back-haul/fronthaul framework, is essential in the upcoming 5G wireless networks and beyond. Motivated by the mounting interest in unmanned flying platforms

  8. Mobile Applications and 4G Wireless Networks: A Framework for Analysis

    Science.gov (United States)

    Yang, Samuel C.

    2012-01-01

    Purpose: The use of mobile wireless data services continues to increase worldwide. New fourth-generation (4G) wireless networks can deliver data rates exceeding 2 Mbps. The purpose of this paper is to develop a framework of 4G mobile applications that utilize such high data rates and run on small form-factor devices. Design/methodology/approach:…

  9. Koopman Operator Framework for Time Series Modeling and Analysis

    Science.gov (United States)

    Surana, Amit

    2018-01-01

    We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

  10. A conceptual framework for measuring airline business model convergence

    OpenAIRE

    Daft, Jost; Albers, Sascha

    2012-01-01

    This paper develops a measurement framework that synthesizes the airline and strategy literature to identify relevant dimensions and elements of airline business models. The applicability of this framework for describing airline strategies and structures and, based on this conceptualization, for assessing the potential convergence of airline business models over time is then illustrated using a small sample of five German passenger airlines. For this sample, the perception of a rapprochement ...

  11. A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Suleman Khan

    2014-01-01

    Full Text Available Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

  12. A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing.

    Science.gov (United States)

    Khan, Suleman; Shiraz, Muhammad; Wahab, Ainuddin Wahid Abdul; Gani, Abdullah; Han, Qi; Rahman, Zulkanain Bin Abdul

    2014-01-01

    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

  13. A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

    Science.gov (United States)

    Abdul Wahab, Ainuddin Wahid; Han, Qi; Bin Abdul Rahman, Zulkanain

    2014-01-01

    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC. PMID:25097880

  14. Development of Network Interface Cards for TRIDAQ systems with the NaNet framework

    International Nuclear Information System (INIS)

    Ammendola, R.; Biagioni, A.; Cretaro, P.; Frezza, O.; Cicero, F. Lo; Lonardo, A.; Martinelli, M.; Paolucci, P.S.; Pastorelli, E.; Simula, F.; Valente, P.; Vicini, P.; Lorenzo, S. Di; Piandani, R.; Pontisso, L.; Sozzi, M.; Fiorini, M.; Neri, I.; Lamanna, G.; Rossetti, D.

    2017-01-01

    NaNet is a framework for the development of FPGA-based PCI Express (PCIe) Network Interface Cards (NICs) with real-time data transport architecture that can be effectively employed in TRIDAQ systems. Key features of the architecture are the flexibility in the configuration of the number and kind of the I/O channels, the hardware offloading of the network protocol stack, the stream processing capability, and the zero-copy CPU and GPU Remote Direct Memory Access (RDMA). Three NIC designs have been developed with the NaNet framework: NaNet-1 and NaNet-10 for the CERN NA62 low level trigger and NaNet 3 for the KM3NeT-IT underwater neutrino telescope DAQ system. We will focus our description on the NaNet-10 design, as it is the most complete of the three in terms of capabilities and integrated IPs of the framework.

  15. A Framework for Collaborative Networked Learning in Higher Education: Design & Analysis

    Directory of Open Access Journals (Sweden)

    Ghassan F. Issa

    2014-06-01

    Full Text Available This paper presents a comprehensive framework for building collaborative learning networks within higher educational institutions. This framework focuses on systems design and implementation issues in addition to a complete set of evaluation, and analysis tools. The objective of this project is to improve the standards of higher education in Jordan through the implementation of transparent, collaborative, innovative, and modern quality educational programs. The framework highlights the major steps required to plan, design, and implement collaborative learning systems. Several issues are discussed such as unification of courses and program of studies, using appropriate learning management system, software design development using Agile methodology, infrastructure design, access issues, proprietary data storage, and social network analysis (SNA techniques.

  16. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  17. A Recommended Framework for the Network-Centric Acquisition Process

    Science.gov (United States)

    2009-09-01

    ISO /IEC 12207 , Systems and Software Engineering-Software Life-Cycle Processes  ANSI/EIA 632, Processes for Engineering a System. There are...engineering [46]. Some of the process models presented in the DAG are:  ISO /IEC 15288, Systems and Software Engineering-System Life-Cycle Processes...e.g., ISO , IA, Security, etc.). Vetting developers helps ensure that they are using industry best industry practices and maximize the IA compliance

  18. Operations management in distribution networks within a smart city framework.

    Science.gov (United States)

    Cerulli, Raffaele; Dameri, Renata Paola; Sciomachen, Anna

    2017-02-20

    This article studies a vehicle routing problem with environmental constraints that are motivated by the requirements for sustainable urban transport. The empirical research presents a fleet planning problem that takes into consideration both minimum cost vehicle routes and minimum pollution. The problem is formulated as a mixed integer linear programming model and experimentally validated using data collected from a real situation: a grocery company delivering goods ordered via e-channels to customers spread in the urban and metropolitan area of Genoa smart city. The proposed model is a variant of the vehicle routing problem tailored to include environmental issues and street limitations. Its novelty regards also the use of real data instances provided by the B2C grocery company. Managerial implications are the choice of both the routes and the number and type of vehicles. Results show that commercial distribution strategies achieve better results in term of both business and environmental performance, provided the smart mobility goals and constraints are included into the distribution model from the beginning. © The authors 2017. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  19. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  20. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    . The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

  1. A modeling framework for investment planning in interdependent infrastructures in multi-hazard environments.

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Nathanael J. K.; Gearhart, Jared Lee; Jones, Dean A.; Nozick, Linda Karen; Prince, Michael

    2013-09-01

    Currently, much of protection planning is conducted separately for each infrastructure and hazard. Limited funding requires a balance of expenditures between terrorism and natural hazards based on potential impacts. This report documents the results of a Laboratory Directed Research & Development (LDRD) project that created a modeling framework for investment planning in interdependent infrastructures focused on multiple hazards, including terrorism. To develop this framework, three modeling elements were integrated: natural hazards, terrorism, and interdependent infrastructures. For natural hazards, a methodology was created for specifying events consistent with regional hazards. For terrorism, we modeled the terrorists actions based on assumptions regarding their knowledge, goals, and target identification strategy. For infrastructures, we focused on predicting post-event performance due to specific terrorist attacks and natural hazard events, tempered by appropriate infrastructure investments. We demonstrate the utility of this framework with various examples, including protection of electric power, roadway, and hospital networks.

  2. A Framework for Relating Timed Transition Systems and Preserving TCTL Model Checking

    DEFF Research Database (Denmark)

    Jacobsen, Lasse; Jacobsen, Morten; Møller, Mikael Harkjær

    2010-01-01

    Many formal translations between time dependent models have been proposed over the years. While some of them produce timed bisimilar models, others preserve only reachability or (weak) trace equivalence. We suggest a general framework for arguing when a translation preserves Timed Computation Tree...... Logic (TCTL) or its safety fragment.The framework works at the level of timed transition systems, making it independent of the modeling formalisms and applicable to many of the translations published in the literature. Finally, we present a novel translation from extended Timed-Arc Petri Nets...... to Networks of Timed Automata and using the framework argue that itpreserves the full TCTL. The translation has been implemented in the verification tool TAPAAL....

  3. Integrated Business and Engineering Framework for Synthesis and Design of Enterprise-Wide Processing Networks

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2012-01-01

    The synthesis and design of processing networks is a complex and multidisciplinary problem, which involves many strategic and tactical decisions at business (considering financial criteria, market competition, supply chain network, etc) and engineering levels (considering synthesis, design...... and optimisation of production technology, R&D, etc), all of which have a deep impact on the profitability of processing industries. In this study, an integrated business and engineering framework for synthesis and design of processing networks is presented. The framework employs a systematic approach to manage...... the complexity while solving simultaneously both the business and the engineering aspects of problems, allowing at the same time, comparison of a large number of alternatives at their optimal points. The results identify the optimal raw material, the product portfolio and select the process technology...

  4. Multilevel Models: Conceptual Framework and Applicability

    Directory of Open Access Journals (Sweden)

    Roxana-Otilia-Sonia Hrițcu

    2015-10-01

    Full Text Available Individuals and the social or organizational groups they belong to can be viewed as a hierarchical system situated on different levels. Individuals are situated on the first level of the hierarchy and they are nested together on the higher levels. Individuals interact with the social groups they belong to and are influenced by these groups. Traditional methods that study the relationships between data, like simple regression, do not take into account the hierarchical structure of the data and the effects of a group membership and, hence, results may be invalidated. Unlike standard regression modelling, the multilevel approach takes into account the individuals as well as the groups to which they belong. To take advantage of the multilevel analysis it is important that we recognize the multilevel characteristics of the data. In this article we introduce the outlines of multilevel data and we describe the models that work with such data. We introduce the basic multilevel model, the two-level model: students can be nested into classes, individuals into countries and the general two-level model can be extended very easily to several levels. Multilevel analysis has begun to be extensively used in many research areas. We present the most frequent study areas where multilevel models are used, such as sociological studies, education, psychological research, health studies, demography, epidemiology, biology, environmental studies and entrepreneurship. We support the idea that since hierarchies exist everywhere, multilevel data should be recognized and analyzed properly by using multilevel modelling.

  5. An Ising model for metal-organic frameworks

    Science.gov (United States)

    Höft, Nicolas; Horbach, Jürgen; Martín-Mayor, Victor; Seoane, Beatriz

    2017-08-01

    We present a three-dimensional Ising model where lines of equal spins are frozen such that they form an ordered framework structure. The frame spins impose an external field on the rest of the spins (active spins). We demonstrate that this "porous Ising model" can be seen as a minimal model for condensation transitions of gas molecules in metal-organic frameworks. Using Monte Carlo simulation techniques, we compare the phase behavior of a porous Ising model with that of a particle-based model for the condensation of methane (CH4) in the isoreticular metal-organic framework IRMOF-16. For both models, we find a line of first-order phase transitions that end in a critical point. We show that the critical behavior in both cases belongs to the 3D Ising universality class, in contrast to other phase transitions in confinement such as capillary condensation.

  6. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...

  7. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  8. Network interconnections: an architectural reference model

    NARCIS (Netherlands)

    Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.

    1985-01-01

    One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for

  9. Mediation Analysis in a Latent Growth Curve Modeling Framework

    Science.gov (United States)

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  10. Theories and Frameworks for Online Education: Seeking an Integrated Model

    Science.gov (United States)

    Picciano, Anthony G.

    2017-01-01

    This article examines theoretical frameworks and models that focus on the pedagogical aspects of online education. After a review of learning theory as applied to online education, a proposal for an integrated "Multimodal Model for Online Education" is provided based on pedagogical purpose. The model attempts to integrate the work of…

  11. Performance modeling of network data services

    Energy Technology Data Exchange (ETDEWEB)

    Haynes, R.A.; Pierson, L.G.

    1997-01-01

    Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.

  12. Real time natural object modeling framework

    International Nuclear Information System (INIS)

    Rana, H.A.; Shamsuddin, S.M.; Sunar, M.H.

    2008-01-01

    CG (Computer Graphics) is a key technology for producing visual contents. Currently computer generated imagery techniques are being developed and applied, particularly in the field of virtual reality applications, film production, training and flight simulators, to provide total composition of realistic computer graphic images. Natural objects like clouds are an integral feature of the sky without them synthetic outdoor scenes seem unrealistic. Modeling and animating such objects is a difficult task. Most systems are difficult to use, as they require adjustment of numerous, complex parameters and are non-interactive. This paper presents an intuitive, interactive system to artistically model, animate, and render visually convincing clouds using modern graphics hardware. A high-level interface models clouds through the visual use of cubes. Clouds are rendered by making use of hardware accelerated API -OpenGL. The resulting interactive design and rendering system produces perceptually convincing cloud models that can be used in any interactive system. (author)

  13. Cytoview: Development of a cell modelling framework

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    is an important aspect of cell modelling. ... 1Supercomputer Education and Research Centreand 2Bioinformatics Centre, Indian Institute ... Important aspects in each panel are listed. ... subsumption relationship, in which the child term is a more.

  14. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

    2017-01-01

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes

  15. Network models in economics and finance

    CERN Document Server

    Pardalos, Panos; Rassias, Themistocles

    2014-01-01

    Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis  that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

  16. Causal mapping of emotion networks in the human brain: Framework and initial findings.

    Science.gov (United States)

    Dubois, Julien; Oya, Hiroyuki; Tyszka, J Michael; Howard, Matthew; Eberhardt, Frederick; Adolphs, Ralph

    2017-11-13

    Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Resource Optimization Techniques and Security Levels for Wireless Sensor Networks Based on the ARSy Framework

    Science.gov (United States)

    Kitagawa, Akio

    2018-01-01

    Wireless Sensor Networks (WSNs) with limited battery, central processing units (CPUs), and memory resources are a widely implemented technology for early warning detection systems. The main advantage of WSNs is their ability to be deployed in areas that are difficult to access by humans. In such areas, regular maintenance may be impossible; therefore, WSN devices must utilize their limited resources to operate for as long as possible, but longer operations require maintenance. One method of maintenance is to apply a resource adaptation policy when a system reaches a critical threshold. This study discusses the application of a security level adaptation model, such as an ARSy Framework, for using resources more efficiently. A single node comprising a Raspberry Pi 3 Model B and a DS18B20 temperature sensor were tested in a laboratory under normal and stressful conditions. The result shows that under normal conditions, the system operates approximately three times longer than under stressful conditions. Maintaining the stability of the resources also enables the security level of a network’s data output to stay at a high or medium level. PMID:29772773

  18. Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks.

    Science.gov (United States)

    Van Landeghem, Sofie; Van Parys, Thomas; Dubois, Marieke; Inzé, Dirk; Van de Peer, Yves

    2016-01-05

    Differential networks have recently been introduced as a powerful way to study the dynamic rewiring capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such differential networks are generated and visualised using ad hoc methods, and are often limited to the analysis of only one condition-specific response or one interaction type at a time. In this work, we present a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set of condition-specific responses against one reference network. To this end, we have implemented novel ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical interactions and regulatory associations, symmetric and directed edges, edge weights and negation. We propose this integrative framework as a standardised methodology that allows a unified view on differential networks and promotes comparability between differential network studies. As an illustrative application, we demonstrate its usefulness on a plant abiotic stress study and we experimentally confirmed a predicted regulator. Diffany is freely available as open-source java library and Cytoscape plugin from http://bioinformatics.psb.ugent.be/supplementary_data/solan/diffany/.

  19. Synergistic effects in threshold models on networks

    Science.gov (United States)

    Juul, Jonas S.; Porter, Mason A.

    2018-01-01

    Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

  20. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  1. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  2. Fisher information framework for time series modeling

    Science.gov (United States)

    Venkatesan, R. C.; Plastino, A.

    2017-08-01

    A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

  3. Using structural equation modeling for network meta-analysis.

    Science.gov (United States)

    Tu, Yu-Kang; Wu, Yun-Chun

    2017-07-14

    Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

  4. Frameworks for Understanding the Nature of Interactions, Networking, and Community in a Social Networking Site for Academic Practice

    Directory of Open Access Journals (Sweden)

    Grainne Conole

    2011-03-01

    Full Text Available This paper describes a new social networking site, Cloudworks, which has been developed to enable discussion and sharing of learning and teaching ideas/designs and to promote reflective academic practice. The site aims to foster new forms of social and participatory practices (peer critiquing, sharing, user-generated content, aggregation, and personalisation within an educational context. One of the key challenges in the development of the site has been to understand the user interactions and the changing patterns of user behaviour as it evolves. The paper explores the extent to which four frameworks that have been used in researching networked learning contexts can provide insights into the patterns of user behaviour that we see in Cloudworks. The paper considers this within the current debate about the new types of interactions, networking, and community being observed as users adapt to and appropriate new technologies.

  5. A Conceptual Framework of Business Model Emerging Resilience

    OpenAIRE

    Goumagias, Nik; Fernandes, Kiran; Cabras, Ignazio; Li, Feng; Shao, Jianhao; Devlin, Sam; Hodge, Victoria Jane; Cowling, Peter Ivan; Kudenko, Daniel

    2016-01-01

    In this paper we introduce an environmentally driven conceptual framework of Business Model change. Business models acquired substantial momentum in academic literature during the past decade. Several studies focused on what exactly constitutes a Business Model (role model, recipe, architecture etc.) triggering a theoretical debate about the Business Model’s components and their corresponding dynamics and relationships. In this paper, we argue that for Business Models as cognitive structures,...

  6. Towards reproducible descriptions of neuronal network models.

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2009-08-01

    Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.

  7. Improved Maximum Parsimony Models for Phylogenetic Networks.

    Science.gov (United States)

    Van Iersel, Leo; Jones, Mark; Scornavacca, Celine

    2018-05-01

    Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

  8. EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks.

    Science.gov (United States)

    Jenness, Samuel M; Goodreau, Steven M; Morris, Martina

    2018-04-01

    Package EpiModel provides tools for building, simulating, and analyzing mathematical models for the population dynamics of infectious disease transmission in R. Several classes of models are included, but the unique contribution of this software package is a general stochastic framework for modeling the spread of epidemics on networks. EpiModel integrates recent advances in statistical methods for network analysis (temporal exponential random graph models) that allow the epidemic modeling to be grounded in empirical data on contacts that can spread infection. This article provides an overview of both the modeling tools built into EpiModel , designed to facilitate learning for students new to modeling, and the application programming interface for extending package EpiModel , designed to facilitate the exploration of novel research questions for advanced modelers.

  9. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  10. Virtual shelves in a digital library: a framework for access to networked information sources.

    Science.gov (United States)

    Patrick, T B; Springer, G K; Mitchell, J A; Sievert, M E

    1995-01-01

    Develop a framework for collections-based access to networked information sources that addresses the problem of location-dependent access to information sources. This framework uses a metaphor of a virtual shelf. A virtual shelf is a general-purpose server that is dedicated to a particular information subject class. The identifier of one of these servers identifies its subject class. Location-independent call numbers are assigned to information sources. Call numbers are based on standard vocabulary codes. The call numbers are first mapped to the location-independent identifiers of virtual shelves. When access to an information resource is required, a location directory provides a second mapping of these location-independent server identifiers to actual network locations. The framework has been implemented in two different systems. One system is based on the Open System Foundation/Distributed Computing Environment and the other is based on the World Wide Web. This framework applies in new ways traditional methods of library classification and cataloging. It is compatible with two traditional styles of selecting information searching and browsing. Traditional methods may be combined with new paradigms of information searching that will be able to take advantage of the special properties of digital information. Cooperation between the library-informational science community and the informatics community can provide a means for a continuing application of the knowledge and techniques of library science to the new problems of networked information sources.

  11. An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

    Science.gov (United States)

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-02-11

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

  12. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    Directory of Open Access Journals (Sweden)

    Pardeep Kumar

    2014-02-01

    Full Text Available Robust security is highly coveted in real wireless sensor network (WSN applications since wireless sensors’ sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring. The proposed framework offers: (i key initialization; (ii secure network (cluster formation (i.e., mutual authentication and dynamic key establishment; (iii key revocation; and (iv new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

  13. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    Science.gov (United States)

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  14. A proposed best practice model validation framework for banks

    Directory of Open Access Journals (Sweden)

    Pieter J. (Riaan de Jongh

    2017-06-01

    Full Text Available Background: With the increasing use of complex quantitative models in applications throughout the financial world, model risk has become a major concern. The credit crisis of 2008–2009 provoked added concern about the use of models in finance. Measuring and managing model risk has subsequently come under scrutiny from regulators, supervisors, banks and other financial institutions. Regulatory guidance indicates that meticulous monitoring of all phases of model development and implementation is required to mitigate this risk. Considerable resources must be mobilised for this purpose. The exercise must embrace model development, assembly, implementation, validation and effective governance. Setting: Model validation practices are generally patchy, disparate and sometimes contradictory, and although the Basel Accord and some regulatory authorities have attempted to establish guiding principles, no definite set of global standards exists. Aim: Assessing the available literature for the best validation practices. Methods: This comprehensive literature study provided a background to the complexities of effective model management and focussed on model validation as a component of model risk management. Results: We propose a coherent ‘best practice’ framework for model validation. Scorecard tools are also presented to evaluate if the proposed best practice model validation framework has been adequately assembled and implemented. Conclusion: The proposed best practice model validation framework is designed to assist firms in the construction of an effective, robust and fully compliant model validation programme and comprises three principal elements: model validation governance, policy and process.

  15. A Global Modeling Framework for Plasma Kinetics: Development and Applications

    Science.gov (United States)

    Parsey, Guy Morland

    The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization

  16. A Framework for Organizing Current and Future Electric Utility Regulatory and Business Models

    Energy Technology Data Exchange (ETDEWEB)

    Satchwell, Andrew [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cappers, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schwartz, Lisa [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Fadrhonc, Emily Martin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-06-01

    In this report, we will present a descriptive and organizational framework for incremental and fundamental changes to regulatory and utility business models in the context of clean energy public policy goals. We will also discuss the regulated utility's role in providing value-added services that relate to distributed energy resources, identify the "openness" of customer information and utility networks necessary to facilitate change, and discuss the relative risks, and the shifting of risks, for utilities and customers.

  17. Tool wear modeling using abductive networks

    Science.gov (United States)

    Masory, Oren

    1992-09-01

    A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.

  18. Theoretical Tinnitus framework: A Neurofunctional Model

    Directory of Open Access Journals (Sweden)

    Iman Ghodratitoostani

    2016-08-01

    Full Text Available Subjective tinnitus is the conscious (attended awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional tinnitus model to indicate that the conscious perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional tinnitus model includes the peripheral auditory system, the thalamus, the limbic system, brain stem, basal ganglia, striatum and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the sourceless sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be associated with aversive stimuli similar to abnormal neural activity in generating the phantom sound. Cognitive and emotional reactions depend on general

  19. Theoretical Tinnitus Framework: A Neurofunctional Model.

    Science.gov (United States)

    Ghodratitoostani, Iman; Zana, Yossi; Delbem, Alexandre C B; Sani, Siamak S; Ekhtiari, Hamed; Sanchez, Tanit G

    2016-01-01

    Subjective tinnitus is the conscious (attended) awareness perception of sound in the absence of an external source and can be classified as an auditory phantom perception. Earlier literature establishes three distinct states of conscious perception as unattended, attended, and attended awareness conscious perception. The current tinnitus development models depend on the role of external events congruently paired with the causal physical events that precipitate the phantom perception. We propose a novel Neurofunctional Tinnitus Model to indicate that the conscious (attended) awareness perception of phantom sound is essential in activating the cognitive-emotional value. The cognitive-emotional value plays a crucial role in governing attention allocation as well as developing annoyance within tinnitus clinical distress. Structurally, the Neurofunctional Tinnitus Model includes the peripheral auditory system, the thalamus, the limbic system, brainstem, basal ganglia, striatum, and the auditory along with prefrontal cortices. Functionally, we assume the model includes presence of continuous or intermittent abnormal signals at the peripheral auditory system or midbrain auditory paths. Depending on the availability of attentional resources, the signals may or may not be perceived. The cognitive valuation process strengthens the lateral-inhibition and noise canceling mechanisms in the mid-brain, which leads to the cessation of sound perception and renders the signal evaluation irrelevant. However, the "sourceless" sound is eventually perceived and can be cognitively interpreted as suspicious or an indication of a disease in which the cortical top-down processes weaken the noise canceling effects. This results in an increase in cognitive and emotional negative reactions such as depression and anxiety. The negative or positive cognitive-emotional feedbacks within the top-down approach may have no relation to the previous experience of the patients. They can also be

  20. A framework of call admission control procedures for integrated services mobile wireless networks

    International Nuclear Information System (INIS)

    Mahmoud, Ashraf S. Hasan; Al-Qahtani, Salman A.

    2007-01-01

    This paper presents a general framework for a wide range of call admission control (CAC) algorithms. For several CAC schemes, which are a subset of this general framework, an analytical performance evaluation is presented for a multi-traffic mobile wireless network. These CAC algorithms consider a variety of mechanisms to prioritize traffic in an attempt to support different levels of quality of service (QoS) for different types of calls. These mechanisms include dividing the handoff traffic into more than one class and using guard channels or allowing channel splitting to admit more handoff calls. Other mechanisms aimed at adding priority for handoff calls consider employing queuing of handoff calls or dynamically reducing the number lower priority calls. Furthermore our analysis relaxes the typically used assumptions of equal channel holding time and equal resource usage for voice and data calls. The main contribution of this paper is the development of an analytical model for each of the three CAC algorithms specified in this study. In addition to the call blocking and termination probabilities which are usually cited as the performance metrics, in this work we derive and evaluate other metrics that not have be considered by the previous work such as the average queue length, the average queue residency, and the time-out probability for handoff calls. We also develop a simulation tool to test and verify our results. Finally, we present numerical examples to demonstrate the performance of the proposed CAG algorithms and we show that analytical and simulation results are in total agreement. (author)

  1. Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

    Science.gov (United States)

    Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

    2018-06-01

    The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  2. A Framework for PSS Business Models: Formalization and Application

    OpenAIRE

    Adrodegari, Federico; Saccani, Nicola; Kowalkowski, Christian

    2016-01-01

    In order to successfully move "from products to solutions", companies need to redesign their business model. Nevertheless, service oriented BMs in product-centric firms are under-investigated in the literature: very few works develop a scheme of analysis of such BMs. To provide a first step into closing this gap, we propose a new framework to describe service-oriented BMs, pointing out the main BM components and related PSS characteristics. Thus, the proposed framework aims to help companies ...

  3. Building oceanographic and atmospheric observation networks by composition: unmanned vehicles, communication networks, and planning and execution control frameworks

    Science.gov (United States)

    Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.

    2014-12-01

    The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.

  4. Modelling of virtual production networks

    Directory of Open Access Journals (Sweden)

    2011-03-01

    Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.

  5. A Network Disruption Modeling Tool

    National Research Council Canada - National Science Library

    Leinart, James

    1998-01-01

    Given that network disruption has been identified as a military objective and C2-attack has been identified as the mechanism to accomplish this objective, a target set must be acquired and priorities...

  6. A DUAL NETWORK MODEL OF INTERLOCKING DIRECTORATES

    Directory of Open Access Journals (Sweden)

    Humphry Hung

    2003-01-01

    Full Text Available The article proposes an integrative framework for the study of interlocking directorates by using an approach that encompasses the concepts of multiple networks and resource endowment. This serves to integrate the traditional views of interorganizational linkages and intra-class cohesion. Through appropriate strategic analysis of relevant resource endowment of internal environment and external networks of organizations and corporate elites, this article argues that the selection of directors, if used effectively, can be adopted as a strategic device to enhance the corporation's overall performance.

  7. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  8. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  9. Implementing network constraints in the EMPS model

    Energy Technology Data Exchange (ETDEWEB)

    Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

    2010-02-15

    This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

  10. A systematic framework for enterprise-wide optimization: Synthesis and design of processing network under uncertainty

    DEFF Research Database (Denmark)

    Quaglia, Alberto; Sarup, Bent; Sin, Gürkan

    2013-01-01

    technologies andproduct portfolio) which is feasible and have optimal performances over the entire uncertainty domain.Through the integration of different methods, tools, algorithms and databases, the framework guidesthe user in dealing with the mathematical complexity of the problems, allowing efficient...... formulationand solution of large and complex enterprise-wide optimization problem. Tools for the analysis of theuncertainty, of its consequences on the decision-making process and for the identification of strategiesto mitigate its impact on network performances are integrated in the framework. A decomposition...

  11. A community-based framework for aquatic ecosystem models

    DEFF Research Database (Denmark)

    Trolle, Didde; Hamilton, D. P.; Hipsey, M. R.

    2012-01-01

    Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through...... a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we...... aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv...

  12. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

    2017-10-01

    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  13. Frameworks for Assessing the Quality of Modeling and Simulation Capabilities

    Science.gov (United States)

    Rider, W. J.

    2012-12-01

    The importance of assuring quality in modeling and simulation has spawned several frameworks for structuring the examination of quality. The format and content of these frameworks provides an emphasis, completeness and flow to assessment activities. I will examine four frameworks that have been developed and describe how they can be improved and applied to a broader set of high consequence applications. Perhaps the first of these frameworks was known as CSAU [Boyack] (code scaling, applicability and uncertainty) used for nuclear reactor safety and endorsed the United States' Nuclear Regulatory Commission (USNRC). This framework was shaped by nuclear safety practice, and the practical structure needed after the Three Mile Island accident. It incorporated the dominant experimental program, the dominant analysis approach, and concerns about the quality of modeling. The USNRC gave it the force of law that made the nuclear industry take it seriously. After the cessation of nuclear weapons' testing the United States began a program of examining the reliability of these weapons without testing. This program utilizes science including theory, modeling, simulation and experimentation to replace the underground testing. The emphasis on modeling and simulation necessitated attention on the quality of these simulations. Sandia developed the PCMM (predictive capability maturity model) to structure this attention [Oberkampf]. PCMM divides simulation into six core activities to be examined and graded relative to the needs of the modeling activity. NASA [NASA] has built yet another framework in response to the tragedy of the space shuttle accidents. Finally, Ben-Haim and Hemez focus upon modeling robustness and predictive fidelity in another approach. These frameworks are similar, and applied in a similar fashion. The adoption of these frameworks at Sandia and NASA has been slow and arduous because the force of law has not assisted acceptance. All existing frameworks are

  14. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  15. Recursive Bayesian recurrent neural networks for time-series modeling.

    Science.gov (United States)

    Mirikitani, Derrick T; Nikolaev, Nikolay

    2010-02-01

    This paper develops a probabilistic approach to recursive second-order training of recurrent neural networks (RNNs) for improved time-series modeling. A general recursive Bayesian Levenberg-Marquardt algorithm is derived to sequentially update the weights and the covariance (Hessian) matrix. The main strengths of the approach are a principled handling of the regularization hyperparameters that leads to better generalization, and stable numerical performance. The framework involves the adaptation of a noise hyperparameter and local weight prior hyperparameters, which represent the noise in the data and the uncertainties in the model parameters. Experimental investigations using artificial and real-world data sets show that RNNs equipped with the proposed approach outperform standard real-time recurrent learning and extended Kalman training algorithms for recurrent networks, as well as other contemporary nonlinear neural models, on time-series modeling.

  16. Constructing rule-based models using the belief functions framework

    NARCIS (Netherlands)

    Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

    2012-01-01

    Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

  17. Designing the Distributed Model Integration Framework – DMIF

    NARCIS (Netherlands)

    Belete, Getachew F.; Voinov, Alexey; Morales, Javier

    2017-01-01

    We describe and discuss the design and prototype of the Distributed Model Integration Framework (DMIF) that links models deployed on different hardware and software platforms. We used distributed computing and service-oriented development approaches to address the different aspects of

  18. A framework for quantifying net benefits of alternative prognostic models

    NARCIS (Netherlands)

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Feskens, E.J.M.; Kromhout, D.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit)

  19. Industrial Sector Energy Efficiency Modeling (ISEEM) Framework Documentation

    Energy Technology Data Exchange (ETDEWEB)

    Karali, Nihan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Xu, Tengfang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sathaye, Jayant [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2012-12-12

    The goal of this study is to develop a new bottom-up industry sector energy-modeling framework with an agenda of addressing least cost regional and global carbon reduction strategies, improving the capabilities and limitations of the existing models that allows trading across regions and countries as an alternative.

  20. A community-based framework for aquatic ecosystem models

    NARCIS (Netherlands)

    Trolle, D.; Hamilton, D.P.; Hipsey, M.R.; Bolding, K.; Bruggeman, J.; Mooij, W.M.; Janse, J.H.; Nielsen, A.; Jeppesen, E.; Elliott, J.A.; Makler-Pick, V.; Petzoldt, T.; Rinke, K.; Flindt, M.R.; Arhonditsis, G.B.; Gal, G.; Bjerring, R.; Tominaga, K.; Hoen, 't J.; Downing, A.S.; Marques, D.M.; Fragoso, C.R.; Sondergaard, M.; Hanson, P.C.

    2012-01-01

    Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a

  1. Homophyly/Kinship Model: Naturally Evolving Networks

    Science.gov (United States)

    Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

    2015-10-01

    It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

  2. A Fluid Model for Performance Analysis in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Coupechoux Marceau

    2010-01-01

    Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

  3. LPI Optimization Framework for Target Tracking in Radar Network Architectures Using Information-Theoretic Criteria

    Directory of Open Access Journals (Sweden)

    Chenguang Shi

    2014-01-01

    Full Text Available Widely distributed radar network architectures can provide significant performance improvement for target detection and localization. For a fixed radar network, the achievable target detection performance may go beyond a predetermined threshold with full transmitted power allocation, which is extremely vulnerable in modern electronic warfare. In this paper, we study the problem of low probability of intercept (LPI design for radar network and propose two novel LPI optimization schemes based on information-theoretic criteria. For a predefined threshold of target detection, Schleher intercept factor is minimized by optimizing transmission power allocation among netted radars in the network. Due to the lack of analytical closed-form expression for receiver operation characteristics (ROC, we employ two information-theoretic criteria, namely, Bhattacharyya distance and J-divergence as the metrics for target detection performance. The resulting nonconvex and nonlinear LPI optimization problems associated with different information-theoretic criteria are cast under a unified framework, and the nonlinear programming based genetic algorithm (NPGA is used to tackle the optimization problems in the framework. Numerical simulations demonstrate that our proposed LPI strategies are effective in enhancing the LPI performance for radar network.

  4. Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

    Science.gov (United States)

    Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

    2017-08-24

    Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

  5. Determinants of successful clinical networks: the conceptual framework and study protocol.

    Science.gov (United States)

    Haines, Mary; Brown, Bernadette; Craig, Jonathan; D'Este, Catherine; Elliott, Elizabeth; Klineberg, Emily; McInnes, Elizabeth; Middleton, Sandy; Paul, Christine; Redman, Sally; Yano, Elizabeth M

    2012-03-13

    Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.

  6. Towards a Framework for Self-Adaptive Reliable Network Services in Highly-Uncertain Environments

    DEFF Research Database (Denmark)

    Grønbæk, Lars Jesper; Schwefel, Hans-Peter; Ceccarelli, Andrea

    2010-01-01

    In future inhomogeneous, pervasive and highly dynamic networks, end-nodes may often only rely on unreliable and uncertain observations to diagnose hidden network states and decide upon possible remediation actions. Inherent challenges exists to identify good and timely decision strategies to impr...... execution (and monitoring) of remediation actions. We detail the motivations to the ODDR design, then we present its architecture, and finally we describe our current activities towards the realization and assessment of the framework services and the main results currently achieved....

  7. Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

    Science.gov (United States)

    Dobchev, Dimitar; Karelson, Mati

    2016-07-01

    Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably, in the past two decades, ANNs have been used widely in the process of drug discovery. In this review, the authors discuss advantages and disadvantages of ANNs in drug discovery as incorporated into the quantitative structure-activity relationships (QSAR) framework. Furthermore, the authors examine the recent studies, which span over a broad area with various diseases in drug discovery. In addition, the authors attempt to answer the question about the expectations of the ANNs in drug discovery and discuss the trends in this field. The old pitfalls of overtraining and interpretability are still present with ANNs. However, despite these pitfalls, the authors believe that ANNs have likely met many of the expectations of researchers and are still considered as excellent tools for nonlinear data modeling in QSAR. It is likely that ANNs will continue to be used in drug development in the future.

  8. A Bayesian Belief Network framework to predict SOC stock change: the Veneto region (Italy) case study

    Science.gov (United States)

    Dal Ferro, Nicola; Quinn, Claire Helen; Morari, Francesco

    2017-04-01

    A key challenge for soil scientists is predicting agricultural management scenarios that combine crop productions with high standards of environmental quality. In this context, reversing the soil organic carbon (SOC) decline in croplands is required for maintaining soil fertility and contributing to mitigate GHGs emissions. Bayesian belief networks (BBN) are probabilistic models able to accommodate uncertainty and variability in the predictions of the impacts of management and environmental changes. By linking multiple qualitative and quantitative variables in a cause-and-effect relationships, BBNs can be used as a decision support system at different spatial scales to find best management strategies in the agroecosystems. In this work we built a BBN to model SOC dynamics (0-30 cm layer) in the low-lying plain of Veneto region, north-eastern Italy, and define best practices leading to SOC accumulation and GHGs (CO2-equivalent) emissions reduction. Regional pedo-climatic, land use and management information were combined with experimental and modelled data on soil C dynamics as natural and anthropic key drivers affecting SOC stock change. Moreover, utility nodes were introduced to determine optimal decisions for mitigating GHGs emissions from croplands considering also three different IPCC climate scenarios. The network was finally validated with real field data in terms of SOC stock change. Results showed that the BBN was able to model real SOC stock changes, since validation slightly overestimated SOC reduction (+5%) at the expenses of its accumulation. At regional level, probability distributions showed 50% of SOC loss, while only 17% of accumulation. However, the greatest losses (34%) were associated with low reduction rates (100-500 kg C ha-1 y-1), followed by 33% of stabilized conditions (-100 < SOC < 100 kg ha-1 y-1). Land use management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions

  9. Neural network tagging in a toy model

    International Nuclear Information System (INIS)

    Milek, Marko; Patel, Popat

    1999-01-01

    The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed

  10. An endogenous model of the credit network

    Science.gov (United States)

    He, Jianmin; Sui, Xin; Li, Shouwei

    2016-01-01

    In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.

  11. Modelling and designing electric energy networks

    International Nuclear Information System (INIS)

    Retiere, N.

    2003-11-01

    The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets

  12. Summary of innovation models on a company level – creating a framework for an innovation model that will increase a company’s innovation activity

    OpenAIRE

    Stefanovska Ceravolo, Ljubica; Polenakovik, Radmil; Dzidrov, Misko

    2016-01-01

    There are six known and generally accepted generations of innovation models. Innovation models transform from simple, linear models, to integrated and networking models that are dynamic and interactive. Each generation of innovation models is presented in this paper with their characteristics as well as drawbacks. The main goal of this paper is to show the transformation path of innovation models and create a framework for a new innovation model on a company level, that could be used by compa...

  13. Queueing Models for Mobile Ad Hoc Networks

    NARCIS (Netherlands)

    de Haan, Roland

    2009-01-01

    This thesis presents models for the performance analysis of a recent communication paradigm: \\emph{mobile ad hoc networking}. The objective of mobile ad hoc networking is to provide wireless connectivity between stations in a highly dynamic environment. These dynamics are driven by the mobility of

  14. Modeling GMPLS and Optical MPLS Networks

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann; Wessing, Henrik

    2003-01-01

    . The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...

  15. Cyber threat model for tactical radio networks

    Science.gov (United States)

    Kurdziel, Michael T.

    2014-05-01

    The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.

  16. Modeling documents with Generative Adversarial Networks

    OpenAIRE

    Glover, John

    2016-01-01

    This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

  17. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  18. FRAMEWORK FOR AD HOC NETWORK COMMUNICATION IN MULTI-ROBOT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Khilda Slyusar

    2016-11-01

    Full Text Available Assume a team of mobile robots operating in environments where no communication infrastructure like routers or access points is available. The robots have to create a mobile ad hoc network, in that case, it provides communication on peer-to-peer basis. The paper gives an overview of existing solutions how to route messages in such ad hoc networks between robots that are not directly connected and introduces a design of a software framework for realization of such communication. Feasibility of the proposed framework is shown on the example of distributed multi-robot exploration of an a priori unknown environment. Testing of developed functionality in an exploration scenario is based on results of several experiments with various input conditions of the exploration process and various sizes of a team and is described herein.

  19. Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

    Science.gov (United States)

    González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

    2017-06-02

    Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

  20. Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

    CERN Document Server

    Baianu, I C

    2004-01-01

    A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

  1. An Integrated Framework to Specify Domain-Specific Modeling Languages

    DEFF Research Database (Denmark)

    Zarrin, Bahram; Baumeister, Hubert

    2018-01-01

    , a logic-based specification language. The drawback of MS DSL Tools is it does not provide a formal and rigorous approach for semantics specifications. In this framework, we use Microsoft DSL Tools to define the metamodel and graphical notations of DSLs, and an extended version of ForSpec as a formal......In this paper, we propose an integrated framework that can be used by DSL designers to implement their desired graphical domain-specific languages. This framework relies on Microsoft DSL Tools, a meta-modeling framework to build graphical domain-specific languages, and an extension of ForSpec...... language to define their semantics. Integrating these technologies under the umbrella of Microsoft Visual Studio IDE allows DSL designers to utilize a single development environment for developing their desired domain-specific languages....

  2. A software engineering perspective on environmental modeling framework design: The object modeling system

    Science.gov (United States)

    The environmental modeling community has historically been concerned with the proliferation of models and the effort associated with collective model development tasks (e.g., code generation, data provisioning and transformation, etc.). Environmental modeling frameworks (EMFs) have been developed to...

  3. Modeling trust context in networks

    CERN Document Server

    Adali, Sibel

    2013-01-01

    We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others.? In this brief, 'trust context' is defined as the system level description of how the trust evaluation process unfolds.Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout

  4. Computer Network Attack and the Use of Force in International Law: Thoughts on a Normative Framework

    Science.gov (United States)

    1999-06-01

    interpretive consideration. See Vienna Convention, supra note 51, art. 31(3). 69 On economic sanctions, see Paul Szasz , The Law of Economic Sanctions...COMPUTER NETWORK ATTACK AND THE USE OF FORCE IN INTERNATIONAL LAW : THOUGHTS ON A NORMATIVE FRAMEWORK MICHAEL N...Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law , no person shall be subject to a

  5. SMALL AND MEDIUM ENTERPRISES, REGIONAL DEVELOPMENT AND NETWORKING: THE EMERGING FRAMEWORK IN ROMANIA

    OpenAIRE

    Daniela Luminita Constantin

    2002-01-01

    Networking is a key word in the recent debates on SMEs and regional policies, pointing out the need and advantages of integrating these businesses in a coherent framework, which creates links, relations, exchanges between them and other actors within the region (banks, universities, research institutes, training centres, consulting firms, chambers of commerce, associations of producers, local public administration). This paper aims to explore the main features and significance of the SME sect...

  6. Mathematical model of highways network optimization

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2017-12-01

    The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

  7. IFC to CityGML Transformation Framework for Geo-Analysis : A Water Utility Network Case

    NARCIS (Netherlands)

    Hijazi, I.; Ehlers, M.; Zlatanova, S.; Isikdag, U.

    2009-01-01

    The development of semantic 3D city models has allowed for new approaches to town planning and urban management (Benner et al. 2005) such as emergency and catastrophe planning, checking building developments, and utility networks. Utility networks inside buildings are composed of pipes and cables

  8. Hypothesis Management Framework: a exible design pattern for belief networks in decision support systems

    NARCIS (Netherlands)

    Gosliga, S.P. van; Voorde, I. van de

    2008-01-01

    This article discusses a design pattern for building belief networks for application domains in which causal models are hard to construct. In this approach we pursue a modular belief network structure that is easily extended by the users themselves, while remaining reliable for decision support. The

  9. Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation

    DEFF Research Database (Denmark)

    Mangado Lopez, Nerea; Ceresa, Mario; Duchateau, Nicolas

    2016-01-01

    . To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient......'s CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns......Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging...

  10. A Bayesian framework for parameter estimation in dynamical models.

    Directory of Open Access Journals (Sweden)

    Flávio Codeço Coelho

    Full Text Available Mathematical models in biology are powerful tools for the study and exploration of complex dynamics. Nevertheless, bringing theoretical results to an agreement with experimental observations involves acknowledging a great deal of uncertainty intrinsic to our theoretical representation of a real system. Proper handling of such uncertainties is key to the successful usage of models to predict experimental or field observations. This problem has been addressed over the years by many tools for model calibration and parameter estimation. In this article we present a general framework for uncertainty analysis and parameter estimation that is designed to handle uncertainties associated with the modeling of dynamic biological systems while remaining agnostic as to the type of model used. We apply the framework to fit an SIR-like influenza transmission model to 7 years of incidence data in three European countries: Belgium, the Netherlands and Portugal.

  11. INTEGRATING INTERNET PROTOCOL TELEVISION (IPTV IN DISTANCE EDUCATION: A Constructivist Framework for Social Networking

    Directory of Open Access Journals (Sweden)

    T. Volkan YUZER

    2011-07-01

    Full Text Available New communication technologies and constructivist pedagogy have the great potential to build very powerful paradigm shifts that enhance Internet Protocol Television (IPTV in distance education. Therefore, the main purpose of this chapter is to explore the new concerns, issues and potentials for the IPTV delivery of distance education to multicultural populations. In this study, the design strategies and principles of how to build social networking based on constructivist learning theory are discussed in order to generate a theoretical framework that provides everyday examples and experiences for IPTV in distance education. This framework also shows the needs, expectations and beliefs, and strengths-weaknesses of IPTV in distance. In short, this framework concentrates on discussing the main characteristics of IPTV in distance education and describes how those characteristics can help build constructivist online communities.

  12. Large-Scale Demand Driven Design of a Customized Bus Network: A Methodological Framework and Beijing Case Study

    Directory of Open Access Journals (Sweden)

    Jihui Ma

    2017-01-01

    Full Text Available In recent years, an innovative public transportation (PT mode known as the customized bus (CB has been proposed and implemented in many cities in China to efficiently and effectively shift private car users to PT to alleviate traffic congestion and traffic-related environmental pollution. The route network design activity plays an important role in the CB operation planning process because it serves as the basis for other operation planning activities, for example, timetable development, vehicle scheduling, and crew scheduling. In this paper, according to the demand characteristics and operational purpose, a methodological framework that includes the elements of large-scale travel demand data processing and analysis, hierarchical clustering-based route origin-destination (OD region division, route OD region pairing, and a route selection model is proposed for CB network design. Considering the operating cost and social benefits, a route selection model is proposed and a branch-and-bound-based solution method is developed. In addition, a computer-aided program is developed to analyze a real-world Beijing CB route network design problem. The results of the case study demonstrate that the current CB network of Beijing can be significantly improved, thus demonstrating the effectiveness of the proposed methodology.

  13. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  14. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma

    2004-12-01

    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  15. Hand Posture Prediction Using Neural Networks within a Biomechanical Model

    Directory of Open Access Journals (Sweden)

    Marta C. Mora

    2012-10-01

    Full Text Available This paper proposes the use of artificial neural networks (ANNs in the framework of a biomechanical hand model for grasping. ANNs enhance the model capabilities as they substitute estimated data for the experimental inputs required by the grasping algorithm used. These inputs are the tentative grasping posture and the most open posture during grasping. As a consequence, more realistic grasping postures are predicted by the grasping algorithm, along with the contact information required by the dynamic biomechanical model (contact points and normals. Several neural network architectures are tested and compared in terms of prediction errors, leading to encouraging results. The performance of the overall proposal is also shown through simulation, where a grasping experiment is replicated and compared to the real grasping data collected by a data glove device.

  16. An intermodal transportation geospatial network modeling for containerized soybean shipping

    Directory of Open Access Journals (Sweden)

    Xiang Liu

    2017-06-01

    Full Text Available Containerized shipping is a growing market for agricultural exports, particularly soybeans. In order to understand the optimal strategies for improving the United States’ economic competitiveness in this emerging market, this research develops an intermodal transportation network modeling framework, focusing on U.S. soybean container shipments. Built upon detailed modal cost analyses, a Geospatial Intermodal Freight Transportation (GIFT model has been developed to understand the optimal network design for U.S. soybean exports. Based on market demand and domestic supply figures, the model is able to determine which domestically produced soybeans should go to which foreign markets, and by which transport modes. This research and its continual studies, will provide insights into future policies and practices that can improve the transportation efficiency of soybean logistics.

  17. Sparsity in Model Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Zagorski, M.

    2011-01-01

    We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

  18. Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation.

    Science.gov (United States)

    Mangado, Nerea; Ceresa, Mario; Duchateau, Nicolas; Kjer, Hans Martin; Vera, Sergio; Dejea Velardo, Hector; Mistrik, Pavel; Paulsen, Rasmus R; Fagertun, Jens; Noailly, Jérôme; Piella, Gemma; González Ballester, Miguel Ángel

    2016-08-01

    Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical μCT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.

  19. Modeling of ultrasonic processes utilizing a generic software framework

    Science.gov (United States)

    Bruns, P.; Twiefel, J.; Wallaschek, J.

    2017-06-01

    Modeling of ultrasonic processes is typically characterized by a high degree of complexity. Different domains and size scales must be regarded, so that it is rather difficult to build up a single detailed overall model. Developing partial models is a common approach to overcome this difficulty. In this paper a generic but simple software framework is presented which allows to coupe arbitrary partial models by slave modules with well-defined interfaces and a master module for coordination. Two examples are given to present the developed framework. The first one is the parameterization of a load model for ultrasonically-induced cavitation. The piezoelectric oscillator, its mounting, and the process load are described individually by partial models. These partial models then are coupled using the framework. The load model is composed of spring-damper-elements which are parameterized by experimental results. In the second example, the ideal mounting position for an oscillator utilized in ultrasonic assisted machining of stone is determined. Partial models for the ultrasonic oscillator, its mounting, the simplified contact process, and the workpiece’s material characteristics are presented. For both applications input and output variables are defined to meet the requirements of the framework’s interface.

  20. Three-Dimensional Networked Metal-Organic Frameworks with Conductive Polypyrrole Tubes for Flexible Supercapacitors.

    Science.gov (United States)

    Xu, Xingtao; Tang, Jing; Qian, Huayu; Hou, Shujin; Bando, Yoshio; Hossain, Md Shahriar A; Pan, Likun; Yamauchi, Yusuke

    2017-11-08

    Metal-organic frameworks (MOFs) with high porosity and a regular porous structure have emerged as a promising electrode material for supercapacitors, but their poor electrical conductivity limits their utilization efficiency and capacitive performance. To increase the overall electrical conductivity as well as the efficiency of MOF particles, three-dimensional networked MOFs are developed via using preprepared conductive polypyrrole (PPy) tubes as the support for in situ growth of MOF particles. As a result, the highly conductive PPy tubes that run through the MOF particles not only increase the electron transfer between MOF particles and maintain the high effective porosity of the MOFs but also endow the MOFs with flexibility. Promoted by such elaborately designed MOF-PPy networks, the specific capacitance of MOF particles has been increased from 99.2 F g -1 for pristine zeolitic imidazolate framework (ZIF)-67 to 597.6 F g -1 for ZIF-PPy networks, indicating the importance of the design of the ZIF-PPy continuous microstructure. Furthermore, a flexible supercapacitor device based on ZIF-PPy networks shows an outstanding areal capacitance of 225.8 mF cm -2 , which is far above other MOFs-based supercapacitors reported up to date, confirming the significance of in situ synthetic chemistry as well as the importance of hybrid materials on the nanoscale.

  1. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Stella Kafetzoglou

    2015-08-01

    Full Text Available Among the key aspects of the Internet of Things (IoT is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting—both in terms of data and energy—data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

  2. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    Science.gov (United States)

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-08-11

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios.

  3. A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies

    Science.gov (United States)

    Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A.

    2016-01-01

    Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving “live partial-area taxonomies” is demonstrated. PMID:27345947

  4. Prediction of hourly solar radiation with multi-model framework

    International Nuclear Information System (INIS)

    Wu, Ji; Chan, Chee Keong

    2013-01-01

    Highlights: • A novel approach to predict solar radiation through the use of clustering paradigms. • Development of prediction models based on the intrinsic pattern observed in each cluster. • Prediction based on proper clustering and selection of model on current time provides better results than other methods. • Experiments were conducted on actual solar radiation data obtained from a weather station in Singapore. - Abstract: In this paper, a novel multi-model prediction framework for prediction of solar radiation is proposed. The framework started with the assumption that there are several patterns embedded in the solar radiation series. To extract the underlying pattern, the solar radiation series is first segmented into smaller subsequences, and the subsequences are further grouped into different clusters. For each cluster, an appropriate prediction model is trained. Hence a procedure for pattern identification is developed to identify the proper pattern that fits the current period. Based on this pattern, the corresponding prediction model is applied to obtain the prediction value. The prediction result of the proposed framework is then compared to other techniques. It is shown that the proposed framework provides superior performance as compared to others

  5. Generic modelling framework for economic analysis of battery systems

    DEFF Research Database (Denmark)

    You, Shi; Rasmussen, Claus Nygaard

    2011-01-01

    opportunities, a generic modelling framework is proposed to handle this task. This framework outlines a set of building blocks which are necessary for carrying out the economic analysis of various BS applications. Further, special focus is given on describing how to use the rainflow cycle counting algorithm...... for battery cycle life estimation, since the cycle life plays a central role in the economic analysis of BS. To illustrate the modelling framework, a case study using a Sodium Sulfur Battery (NAS) system with 5-minute regulating service is performed. The economic performances of two dispatch scenarios, a so......Deregulated electricity markets provide opportunities for Battery Systems (BS) to participate in energy arbitrage and ancillary services (regulation, operating reserves, contingency reserves, voltage regulation, power quality etc.). To evaluate the economic viability of BS with different business...

  6. A Computational Framework for Quantifying and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation

    Science.gov (United States)

    Cioaca, Alexandru

    A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data assimila- tion is a rigorous procedure to fuse information from a priori knowledge of the system state, the physical laws governing the evolution of the system, and real measurements, all with associated error statistics. Data assimilation produces best (a posteriori) estimates of model states and parameter values, and results in considerably improved computer simulations. The acquisition and use of observations in data assimilation raises several important scientific questions related to optimal sensor network design, quantification of data impact, pruning redundant data, and identifying the most beneficial additional observations. These questions originate in operational data assimilation practice, and have started to attract considerable interest in the recent past. This dissertation advances the state of knowledge in four dimensional variational (4D-Var) data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of second-order adjoint modeling and the 4D-Var sensitivity equations. Efficient computational approaches for quantifying the observation impact include matrix free linear algebra algorithms and low-rank approximations of the sensitivities to observations. The sensor network configuration problem is formulated as a meta-optimization problem. Best values for parameters such as sensor location are obtained by optimizing a performance criterion, subject to the constraint posed by the 4D-Var optimization. Tractable computational solutions to this "optimization-constrained" optimization problem are provided. The results of this work can be directly applied to the deployment of intelligent sensors and adaptive observations, as well as

  7. Interaction between GIS and hydrologic model: A preliminary approach using ArcHydro Framework Data Model

    Directory of Open Access Journals (Sweden)

    Silvio Jorge C. Simões

    2013-08-01

    Full Text Available In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM models, the Geographical Information System (GIS is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion, situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin’s dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial temporal model.

  8. Modeling framework for crew decisions during accident sequences

    International Nuclear Information System (INIS)

    Lukic, Y.D.; Worledge, D.H.; Hannaman, G.W.; Spurgin, A.J.

    1986-01-01

    The ability to model the average behavior of operating crews in the course of accident sequences is vital in learning on how to prevent damage to power plants and to maintain safety. This paper summarizes the work carried out in support of a Human Reliability Model framework. This work develops the mathematical framework of the model and identifies the parameters which could be measured in some way, e.g., through simulator experience and/or small scale tests. Selected illustrative examples are presented, of the numerical experiments carried out in order to understand the model sensitivity to parameter variation. These examples ar discussed with the objective of deriving insights of general nature regarding operating of the model which may lead to enhanced understanding of man/machine interactions

  9. New framework for standardized notation in wastewater treatment modelling

    DEFF Research Database (Denmark)

    Corominas, L.; Rieger, L.; Takacs, I.

    2010-01-01

    Many unit process models are available in the field of wastewater treatment. All of these models use their own notation, causing problems for documentation, implementation and connection of different models (using different sets of state variables). The main goal of this paper is to propose a new...... is a framework that can be used in whole plant modelling, which consists of different fields such as activated sludge, anaerobic digestion, sidestream treatment, membrane bioreactors, metabolic approaches, fate of micropollutants and biofilm processes. The main objective of this consensus building paper...... notational framework which allows unique and systematic naming of state variables and parameters of biokinetic models in the wastewater treatment field. The symbols are based on one main letter that gives a general description of the state variable or parameter and several subscript levels that provide...

  10. A Liver-Centric Multiscale Modeling Framework for Xenobiotics.

    Directory of Open Access Journals (Sweden)

    James P Sluka

    Full Text Available We describe a multi-scale, liver-centric in silico modeling framework for acetaminophen pharmacology and metabolism. We focus on a computational model to characterize whole body uptake and clearance, liver transport and phase I and phase II metabolism. We do this by incorporating sub-models that span three scales; Physiologically Based Pharmacokinetic (PBPK modeling of acetaminophen uptake and distribution at the whole body level, cell and blood flow modeling at the tissue/organ level and metabolism at the sub-cellular level. We have used standard modeling modalities at each of the three scales. In particular, we have used the Systems Biology Markup Language (SBML to create both the whole-body and sub-cellular scales. Our modeling approach allows us to run the individual sub-models separately and allows us to easily exchange models at a particular scale without the need to extensively rework the sub-models at other scales. In addition, the use of SBML greatly facilitates the inclusion of biological annotations directly in the model code. The model was calibrated using human in vivo data for acetaminophen and its sulfate and glucuronate metabolites. We then carried out extensive parameter sensitivity studies including the pairwise interaction of parameters. We also simulated population variation of exposure and sensitivity to acetaminophen. Our modeling framework can be extended to the prediction of liver toxicity following acetaminophen overdose, or used as a general purpose pharmacokinetic model for xenobiotics.

  11. Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

    Science.gov (United States)

    Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

    2018-02-05

    Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Integrating knowledge seeking into knowledge management models and frameworks

    Directory of Open Access Journals (Sweden)

    Francois Lottering

    2012-09-01

    Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking. Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies. Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing. Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies.

  13. Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases.

    Science.gov (United States)

    Mezlini, Aziz M; Goldenberg, Anna

    2017-10-01

    Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations. We introduce a Bayesian framework, Conflux, to find disease associated genes from exome sequencing data using networks as a prior. There are two main advantages to using networks within a probabilistic graphical model. First, networks are noisy and incomplete, a substantial impediment to gene discovery. Incorporating networks into the structure of a probabilistic models for gene inference has less impact on the solution than relying on the noisy network structure directly. Second, using a Bayesian framework we can keep track of the uncertainty of each gene being associated with the phenotype rather than returning a fixed list of genes. We first show that using networks clearly improves gene detection compared to individual gene testing. We then show consistently improved performance of Conflux compared to the state-of-the-art diffusion network-based method Hotnet2 and a variety of other network and variant aggregation methods, using randomly generated and literature-reported gene sets. We test Hotnet2 and Conflux on several network configurations to reveal biases and patterns of false positives and false negatives in each case. Our experiments show that our novel Bayesian framework Conflux incorporates many of the advantages of the current state-of-the-art methods, while offering more flexibility and improved power in many gene-disease association scenarios.

  14. The QKD network: model and routing scheme

    Science.gov (United States)

    Yang, Chao; Zhang, Hongqi; Su, Jinhai

    2017-11-01

    Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.

  15. A Model of Network Porosity

    Science.gov (United States)

    2016-11-09

    Figure 1. We generally express such networks in terms of the services running in each enclave as well as the routing and firewall rules between the...compromise a server, they can compromise other devices in the same subnet or protected enclave. They probe attached firewalls and routers for open ports and...spam and malware filter would prevent this content from reaching its destination. Content filtering provides another layer of defense to other controls

  16. Thermal conductivity model for nanofiber networks

    Science.gov (United States)

    Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui

    2018-02-01

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  17. Thermal conductivity model for nanofiber networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA

    2018-02-28

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  18. A quantum-implementable neural network model

    Science.gov (United States)

    Chen, Jialin; Wang, Lingli; Charbon, Edoardo

    2017-10-01

    A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

  19. Combinatorial explosion in model gene networks

    Science.gov (United States)

    Edwards, R.; Glass, L.

    2000-09-01

    The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such

  20. Composable Framework Support for Software-FMEA Through Model Execution

    Science.gov (United States)

    Kocsis, Imre; Patricia, Andras; Brancati, Francesco; Rossi, Francesco

    2016-08-01

    Performing Failure Modes and Effect Analysis (FMEA) during software architecture design is becoming a basic requirement in an increasing number of domains; however, due to the lack of standardized early design phase model execution, classic SW-FMEA approaches carry significant risks and are human effort-intensive even in processes that use Model-Driven Engineering.Recently, modelling languages with standardized executable semantics have emerged. Building on earlier results, this paper describes framework support for generating executable error propagation models from such models during software architecture design. The approach carries the promise of increased precision, decreased risk and more automated execution for SW-FMEA during dependability- critical system development.