Spatial load forecasting using a demand propagation approach

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

Family health team knowledge concerning the health needs of people with tuberculosis

The purposes of the study were to get to know conceptions on tuberculosis and health needs and to describe the care provided to people with tuberculosis, according to health professionals' perspective. Qualitative study developed at family health units in Capao Redondo, Sao Paulo. The data were collected through open interviews in January 2010 and submitted to discourse analysis, resulting in three categories: meanings attributed to tuberculosis and health needs and care characteristics. The conceptions regarding the disease are supported by the multi-causal theory of the health-disease process. The care is characterized by interventions that go beyond the biological dimension. The precarious living conditions define the needs of most people with tuberculosis, and can be more important to the ill than the very diagnosis of the disease, influencing treatment adherence, and should gain relevance in care.

Mobile Cloud Networking: Mobile Network, Compute, and Storage as One Service On-Demand

The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and academia commit to jointly establish the vision of Mobile Cloud Networking, to develop a fully cloud-based mobile communication and application platform.

Defence on demand: mechanisms behind optimal defence patterns

Background The optimal defence hypothesis (ODH) predicts that tissues that contribute most to a plant's fitness and have the highest probability of being attacked will be the parts best defended against biotic threats, including herbivores. In general, young sink tissues and reproductive structures show stronger induced defence responses after attack from pathogens and herbivores and contain higher basal levels of specialized defensive metabolites than other plant parts. However, the underlying physiological mechanisms responsible for these developmentally regulated defence patterns remain unknown. Scope This review summarizes current knowledge about optimal defence patterns in above- and below-ground plant tissues, including information on basal and induced defence metabolite accumulation, defensive structures and their regulation by jasmonic acid (JA). Physiological regulations underlying developmental differences of tissues with contrasting defence patterns are highlighted, with a special focus on the role of classical plant growth hormones, including auxins, cytokinins, gibberellins and brassinosteroids, and their interactions with the JA pathway. By synthesizing recent findings about the dual roles of these growth hormones in plant development and defence responses, this review aims to provide a framework for new discoveries on the molecular basis of patterns predicted by the ODH. Conclusions Almost four decades after its formulation, we are just beginning to understand the underlying molecular mechanisms responsible for the patterns of defence allocation predicted by the ODH. A requirement for future advances will be to understand how developmental and defence processes are integrated.

Quasi-experimental evidence on the drivers of index-based livestock insurance demand in Southern Ethiopia

Microinsurance is widely considered an important tool for sustainable poverty reduction, especially in the face of increasing climate risk. Although index-based microinsurance, which should be free from the classical incentive problems, has attracted considerable attention, uptake rates have generally been weak in low-income rural communities. We explore the purchase patterns of index-based livestock insurance in southern Ethiopia, focusing in particular on the role of accurate product comprehension and price, including the prospective impact of temporary discount coupons on subsequent period demand due to price anchoring effects. We find that randomly distributed learning kits contribute to improving subjects' knowledge of the products; however, we do not find strong evidence that the improved knowledge per se induces greater uptake. We also find that reduced price due to randomly distributed discount coupons has an immediate, positive impact on uptake, without dampening subsequent period demand due to reference-dependence associated with price anchoring effects.

Is FTA/EPA effective for a developing country to attract FDI? : simulation analysis based on an extended knowledge-capital model

To prepare an answer to the question of how a developing country can attract FDI, this paper explored the factors and policies that may help bring FDI into a developing country by utilizing an extended version of the knowledge-capital model. With a special focus on the effects of FTAs/EPAs between market countries and developing countries, simulations with the model revealed the following: (1) Although FTA/EPA generally ends to increase FDI to a developing country, the possibility of improving welfare through increased demand for skilled and unskilled labor becomes higher as the size of the country declines; (2) Because the additional implementation of cost-saving policies to reduce firm-type/trade-link specific fixed costs ends to depreciate the price of skilled labor by saving its input, a developing country, which is extremely scarce in skilled labor, is better off avoiding the additional option; (3) If a country hopes to enjoy larger welfare gains with EPA, efforts to increase skilled labor in the country, such as investing in education, may be beneficial.

Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain

Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.

Knowledge about a Species' Conservation Status and Funding for its Preservation: Analysis

Using a species' population to measure its conservation status, this paper explores how increased knowledge about a species' status changes the public's willingness to donate funds for its conservation. This is based on the behavioral relationship between the level of donations and a species' conservation status satisfying general mathematical properties. This level of donation increases, on average, with greater knowledge of a species' conservation status if it is endangered, but falls if it is secure. Modelling enables individuals' demand for extra information about the conservation status of species to be specified. While this model may suggest that conservation bodies could boost funds for conservation of species by exaggerating species' endangerment, such a strategy is shown to be potentially counterproductive. (c) 2006 Elsevier B.V. All rights reserved.

A firm's capability to calibrate supply chain knowledge-antecedents and consequences

This paper proposes a conceptual model for a firm's capability to calibrate supply chain knowledge (CCK). Knowledge calibration is achieved when there is a match between managers' ex ante confidence in the accuracy of held knowledge and the ex post accuracy of that knowledge. Knowledge calibration is closely related to knowledge utility or willingness to use the available ex ante knowledge: a manager uses the ex ante knowledge if he/she is confident in the accuracy of that knowledge, and does not use it or uses it with reservation, when the confidence is low. Thus, knowledge calibration attained through the firm's CCK enables managers to deal with incomplete and uncertain information and enhances quality of decisions. In the supply chain context, although demand- and supply-related knowledge is available, supply chain inefficiencies, such as the bullwhip effect, remain. These issues may be caused not by a lack of knowledge but by a firm's lack of capability to sense potential disagreement between knowledge accuracy and confidence. Therefore, this paper contributes to the understanding of supply chain knowledge utilization by defining CCK and identifying a set of antecedents and consequences of CCK in the supply chain context.

Fuzzy knowledge-based approach to treating uncertainty in inventory control

Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

"Customer" knowledge management in healthcare

This paper reports on a work-in-progress project on the management of patient knowledge in a UK general hospital. Greater involvement of patients is generally seen as crucial to the effective provision of healthcare in the future. However, this presents many challenges, especially in the light of the ageing population in most developed countries and the consequent increasing demand for healthcare. In the UK, there have been many attempts to increase patient involvement by the systematisation of patient feedback, but typically they have not been open to academic scrutiny or formal evaluation, nor have they used any knowledge management principles. The theoretical foundations for this project come first from service management and thence from customer knowledge management. Service management stresses the importance of the customer perspective. Healthcare clearly meets the definitions of a service even though it may also include some tangible elements such as surgery and provision of medication. Although regarding hospital patients purely as "customers" is a viewpoint that needs to be used with care, application of the theory offers potential benefits in healthcare. The two main elements we propose to use from the theory are the type of customer knowledge and its relationship to attributes of the quality of the service provided. The project is concerned with investigating various knowledge management systems (KMS) that are currently in use (or proposed) to systematise patient feedback in an NHS Trust hospital, to manage knowledge from and to a lesser extent about patients. The study is a mixed methods (quantitative and qualitative) action research investigation intended to answer the following three research questions: • How can a KMS be used as a mechanism to capture and evaluate patient experiences to provoke patient service change • How can the KMS assist in providing a mechanism for systematising patient engagement? • How can patient feedback be used to stimulate improvements in care, quality and safety?

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.

No Royal Road but at Least a Gateway to the Mathematical Knowledge: The EuDML Project

Радослав Павлов - Представен е проектът EuDML – Европейската цифрова библиотека по математика (http://www.eudml.eu), който цели: • да създаде обща инфраструктура за безпроблемна навигация, търсене и взаимодействие в рамките на плътна мрежа от разпределено валидирано многоезично математическо съдържание в цифрова форма, което да е достъпно в цяла Европа, и така да направи математиката лесно достъпна за всички потребители; • да задоволи изискването за надежден и дългосрочен достъп до математическите изследвания. Представен е и българският принос в проекта – BulDML – цифрово хранилище за математическа литература на Института по математика и информатика на БАН (http://sci-gems.math.bas.bg).

A diagnostic framework for demand amplification problems in supply chains

This dissertation delivers a framework to diagnose the Bull-Whip Effect (BWE) in supply chains and then identify methods to minimize it. Such a framework is needed because in spite of the significant amount of literature discussing the bull-whip effect, many companies continue to experience the wide variations in demand that are indicative of the bull-whip effect. While the theory and knowledge of the bull-whip effect is well established, there still is the lack of an engineering framework and method to systematically identify the problem, diagnose its causes, and identify remedies. ^ The present work seeks to fill this gap by providing a holistic, systems perspective to bull-whip identification and diagnosis. The framework employs the SCOR reference model to examine the supply chain processes with a baseline measure of demand amplification. Then, research of the supply chain structural and behavioral features is conducted by means of the system dynamics modeling method. ^ The contribution of the diagnostic framework, is called Demand Amplification Protocol (DAMP), relies not only on the improvement of existent methods but also contributes with original developments introduced to accomplish successful diagnosis. DAMP contributes a comprehensive methodology that captures the dynamic complexities of supply chain processes. The method also contributes a BWE measurement method that is suitable for actual supply chains because of its low data requirements, and introduces a BWE scorecard for relating established causes to a central BWE metric. In addition, the dissertation makes a methodological contribution to the analysis of system dynamic models with a technique for statistical screening called SS-Opt, which determines the inputs with the greatest impact on the bull-whip effect by means of perturbation analysis and subsequent multivariate optimization. The dissertation describes the implementation of the DAMP framework in an actual case study that exposes the approach, analysis, results and conclusions. The case study suggests a balanced solution between costs and demand amplification can better serve both firms and supply chain interests. Insights pinpoint to supplier network redesign, postponement in manufacturing operations and collaborative forecasting agreements with main distributors.^