ROC Curves within the Framework of Neural Network Assembly Memory Model: Some Analytic Results

On the basis of convolutional (Hamming) version of recent Neural Network Assembly Memory Model (NNAMM) for intact two-layer autoassociative Hopfield network optimal receiver operating characteristics (ROCs) have been derived analytically. A method of taking into account explicitly a priori probabilities of alternative hypotheses on the structure of information initiating memory trace retrieval and modified ROCs (mROCs, a posteriori probabilities of correct recall vs. false alarm probability) are introduced. The comparison of empirical and calculated ROCs (or mROCs) demonstrates that they coincide quantitatively and in this way intensities of cues used in appropriate experiments may be estimated. It has been found that basic ROC properties which are one of experimental findings underpinning dual-process models of recognition memory can be explained within our one-factor NNAMM.

Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.

Classification of Data to Extract Knowledge from Neural Networks

A major drawback of artificial neural networks is their black-box character. Therefore, the rule extraction algorithm is becoming more and more important in explaining the extracted rules from the neural networks. In this paper, we use a method that can be used for symbolic knowledge extraction from neural networks, once they have been trained with desired function. The basis of this method is the weights of the neural network trained. This method allows knowledge extraction from neural networks with continuous inputs and output as well as rule extraction. An example of the application is showed. This example is based on the extraction of average load demand of a power plant.

Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network

In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

Long-term drivers of broadband traffic in next-generation networks

This paper is concerned with long-term (20+ years) forecasting of broadband traffic in next-generation networks. Such long-term approach requires going beyond extrapolations of past traffic data while facing high uncertainty in predicting the future developments and facing the fact that, in 20 years, the current network technologies and architectures will be obsolete. Thus, "order of magnitude" upper bounds of upstream and downstream traffic are deemed to be good enough to facilitate such long-term forecasting. These bounds can be obtained by evaluating the limits of human sighting and assuming that these limits will be achieved by future services or, alternatively, by considering the contents transferred by bandwidth-demanding applications such as those using embedded interactive 3D video streaming. The traffic upper bounds are a good indication of the peak values and, subsequently, also of the future network capacity demands. Furthermore, the main drivers of traffic growth including multimedia as well as non-multimedia applications are identified. New disruptive applications and services are explored that can make good use of the large bandwidth provided by next-generation networks. The results can be used to identify monetization opportunities of future services and to map potential revenues for network operators. © 2014 The Author(s).

Reconfiguration of distribution network into islanded microgrids considering development of distributed energy resources

This paper discusses the potentiality of reconfiguring distribution networks into islanded Microgrids to reduce the network infrastructure reinforcement requirement and incorporate various dispersed energy resources. The major challenge would be properly breaking down the network and its resultant protection and automation system changes. A reconfiguration method is proposed based on allocation of distributed generation resources to fulfil this purpose, with a heuristic algorithm. Cost/reliability data is required for the next stage tasks to realise a case study of a particular network.

Impact of electric vehicles on GB electricity demand and associated benefits for system control

This paper investigates the impact that electric vehicle uptake will have on the national electricity demand of Great Britain. Data from the National Travel Survey, and the Coventry and Birmingham Low Emissions Demonstration (CABLED) are used to model an electrical demand profile in a future scenario of significant electric vehicle market penetration. These two methods allow comparison of how conventional cars are currently used, and the resulting electrical demand with simple substitution of energy source, with data showing how electric vehicles are actually being used at present. The report finds that electric vehicles are unlikely to significantly impact electricity demand in GB. The paper also aims to determine whether electric vehicles have the potential to provide ancillary services to the grid operator, and if so, the capacity for such services that would be available. Demand side management, frequency response and Short term Operating Reserve (STOR) are the services considered. The report finds that electric cars are unlikely to provide enough moveable demand peak shedding to be worthwhile. However, it is found that controlling vehicle charging would provide sufficient power control to viably act as frequency response for dispatch by the transmission system operator. This paper concludes that electric vehicles have technical potential to aid management of the transmission network without adding a significant demand burden. © 2013 IEEE.

Using overlay test to evaluate fracture properties of field-aged asphalt concrete

Field material testing provides firsthand information on pavement conditions which are most helpful in evaluating performance and identifying preventive maintenance or overlay strategies. High variability of field asphalt concrete due to construction raises the demand for accuracy of the test. Accordingly, the objective of this study is to propose a reliable and repeatable methodology to evaluate the fracture properties of field-aged asphalt concrete using the overlay test (OT). The OT is selected because of its efficiency and feasibility for asphalt field cores with diverse dimensions. The fracture properties refer to the Paris’ law parameters based on the pseudo J-integral (A and n) because of the sound physical significance of the pseudo J-integral with respect to characterizing the cracking process. In order to determine A and n, a two-step OT protocol is designed to characterize the undamaged and damaged behaviors of asphalt field cores. To ensure the accuracy of determined undamaged and fracture properties, a new analysis method is then developed for data processing, which combines the finite element simulations and mechanical analysis of viscoelastic force equilibrium and evolution of pseudo displacement work in the OT specimen. Finally, theoretical equations are derived to calculate A and n directly from the OT test data. The accuracy of the determined fracture properties is verified. The proposed methodology is applied to a total of 27 asphalt field cores obtained from a field project in Texas, including the control Hot Mix Asphalt (HMA) and two types of warm mix asphalt (WMA). The results demonstrate a high linear correlation between n and −log A for all the tested field cores. Investigations of the effect of field aging on the fracture properties confirm that n is a good indicator to quantify the cracking resistance of asphalt concrete. It is also indicated that summer climatic condition clearly accelerates the rate of aging. The impact of the WMA technologies on fracture properties of asphalt concrete is visualized by comparing the n-values. It shows that the Evotherm WMA technology slightly improves the cracking resistance, while the foaming WMA technology provides the comparable fracture properties with the HMA. After 15 months aging in the field, the cracking resistance does not exhibit significant difference between HMA and WMAs, which is confirmed by the observations of field distresses.

Tracing the evolution of physics on the backbone of citation networks

Many innovations are inspired by past ideas in a nontrivial way. Tracing these origins and identifying scientific branches is crucial for research inspirations. In this paper, we use citation relations to identify the descendant chart, i.e., the family tree of research papers. Unlike other spanning trees that focus on cost or distance minimization, we make use of the nature of citations and identify the most important parent for each publication, leading to a treelike backbone of the citation network. Measures are introduced to validate the backbone as the descendant chart. We show that citation backbones can well characterize the hierarchical and fractal structure of scientific development, and lead to an accurate classification of fields and subfields. © 2011 American Physical Society.

Application of automatic load transfer on feeder utilisation balance

This paper looks at how automatic load transfer may be used as a possible planning tool to help deliver faster connections for customers. A trial on an area of overhead line Network is presented to show how improvements in % feeder utilisation may be realised by changing the location of the open point. The reported Network data is compared to calculated data under two different configurations over a two week trial period. The results show that ALT open point determination in the presence of generation is different from a load only circuit and that the open points may not be fixed with time. Looking at improvements in Network headroom may not be conducive to other improvements in the network such as loss reduction or improving voltage profiles.

Resting state morphology predicts the effect of theta burst stimulation in false belief reasoning:ventrolateral prefrontal cortex in false belief reasoning

When required to represent a perspective that conflicts with one's own, functional magnetic resonance imaging (fMRI) suggests that the right ventrolateral prefrontal cortex (rvlPFC) supports the inhibition of that conflicting self-perspective. The present task dissociated inhibition of self-perspective from other executive control processes by contrasting belief reasoning-a cognitive state where the presence of conflicting perspectives was manipulated-with a conative desire state wherein no systematic conflict existed. Linear modeling was used to examine the effect of continuous theta burst stimulation (cTBS) to rvlPFC on participants' reaction times in belief and desire reasoning. It was anticipated that cTBS applied to rvlPFC would affect belief but not desire reasoning, by modulating activity in the Ventral Attention System (VAS). We further anticipated that this effect would be mediated by functional connectivity within this network, which was identified using resting state fMRI and an unbiased model-free approach. Simple reaction-time analysis failed to detect an effect of cTBS. However, by additionally modeling individual measures from within the stimulated network, the hypothesized effect of cTBS to belief (but, importantly, not desire) reasoning was demonstrated. Structural morphology within the stimulated region, rvlPFC, and right temporoparietal junction were demonstrated to underlie this effect. These data provide evidence that inconsistencies found with cTBS can be mediated by the composition of the functional network that is being stimulated. We suggest that the common claim that this network constitutes the VAS explains the effect of cTBS to this network on false belief reasoning. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

Impact of severity and type of depression on quality of life in cases identified in the community

BACKGROUND: The impact of different levels of depression severity on quality of life (QoL) is not well studied, particularly regarding ICD-10 criteria. The ICD classification of depressive episodes in three levels of severity is also controversial and the less severe category, mild, has been considered as unnecessary and not clearly distinguishable from non-clinical states. The present work aimed to test the relationship between depression severity according to ICD-10 criteria and several dimensions of functioning as assessed by Medical Outcome Study (MOS) 36-item Short Form general health survey (SF-36) at the population level. METHOD: A sample of 551 participants from the second phase of the Outcome of Depression International Network (ODIN) study (228 controls without depression and 313 persons fulfilling ICD criteria for depressive episode) was selected for a further assessment of several variables, including QoL related to physical and mental health as measured with the SF-36. RESULTS: Statistically significant differences between controls and the depression group were found in both physical and mental markers of health, regardless of the level of depression severity; however, there were very few differences in QoL between levels of depression as defined by ICD-10. Regardless of the presence of depression, disability, widowed status, being a woman and older age were associated with worse QoL in a structural equation analysis with covariates. Likewise, there were no differences according to the type of depression (single-episode versus recurrent). CONCLUSIONS: These results cast doubt on the adequacy of the current ICD classification of depression in three levels of severity.

Hálózat – A globális gazdaság kvázi szervezete (The business network – the quasi organization of the global economy)

A tanulmány célja, hogy értelmezze a globális gazdaság alapvető fontosságú építőelemét, az üzleti hálózatot, majd megvizsgálja annak felépítését és működésének főbb vezérlőelveit. Először az alapfogalmak – üzleti hálózat, ellátási lánc és ellátási háló – meghatározására és azok felépítésének bemutatására kerül sor. Ezt követően a cikk röviden ismerteti, hogy melyek voltak azok a vállalati gazdálkodás környezetében végbement változások, melyek a gazdaság hálózatosodását elősegítették és ennek kapcsán elvezettek az üzleti hálózatok versenyképességben játszott szerepének erősödéséhez. A szerző ugyanakkor bemutatja a kialakuló új gazdasági modell, az ún. hálózati gazdaság működési modelljének lényeges új tulajdonságait. A tanulmány ezután ismerteti az üzleti hálózat – s ezen belül az ellátási lánc – működtetésében meghatározó koordinációs mechanizmusokban megfigyelhető markáns változásokat. Végül részletesen ismerteti az üzleti hálózat két fő építőelemét: a hálózatot alkotó üzleti egységeknek, illetve a közöttük kialakuló kapcsolatoknak az alapvető típusait. ________ The aim of the paper is to present and interpret the basic building element of global business: the business network, its structure and operation. First basic terms – network, supply chain, supply network – are defined and described, than those changes are introduced that played significant role in increasing their importance. Characteristics of the new network economy are presented; especially changes in the coordination mechanism between cooperating parties in the network are demonstrated. Finally the two building blocks of global business networks: (i) nodes (business units) and (ii) threads (partnerships) are described in details.

Horizontal diversity of higher education institutions. The case of Hungary – in European context

In the European Higher Education Area the diversification of higher education is considered to be an emphasized value, a guarantee of creativity. The various institutional rankings are the displays of vertical diversity, but in parallel with these, there is an increasing attention directed at horizontal diversity, the entirety of the institutions' activities. The European Mapping Project (U-map) undertook this challenge. The paper presents the research program, which is an attempt to adapt the U-map model to Hungary. According to the results, the U-map method which was intended for application on an international level, is very useful in the identification of the main groups of institutions in a specific national higher education system as well, and may provide a basis for the creation of institutional strategies and the development of the institutions’ network.

Lessons learned from the effect of tight monetary conditions and crises on corporate capital structure

The study reviews the theoretical and empirical literature on the effect of tight monetary conditions, crisis on corporate capital structure, further creates a framework for analyzing their relation, as well as sheds light on the lessons learned and open research areas. The results highlight that the supply side of capital has an effect on corporate capital structure, though the analysis of this relation is scarce. However, the impact of tight monetary conditions on capital structure is analyzed by several studies, there is limited evidence on the financial policy and the development of financing mix during a crisis period. The impact of the 2007/08 crisis on the corporate capital structure and especially in case of firms with impaired access to external financing is scarce. The study also highlights our lack in understanding of the relation of crisis and capital structure in case of the CEE region.