Utility Harmonic Impedance Measurement Based on Data Selection

Determination of the utility harmonic impedance based on measurements is a significant task for utility power-quality improvement and management. Compared to those well-established, accurate invasive methods, the noninvasive methods are more desirable since they work with natural variations of the loads connected to the point of common coupling (PCC), so that no intentional disturbance is needed. However, the accuracy of these methods has to be improved. In this context, this paper first points out that the critical problem of the noninvasive methods is how to select the measurements that can be used with confidence for utility harmonic impedance calculation. Then, this paper presents a new measurement technique which is based on the complex data-based least-square regression, combined with two techniques of data selection. Simulation and field test results show that the proposed noninvasive method is practical and robust so that it can be used with confidence to determine the utility harmonic impedances.

Inactive Disease and Remission in Childhood-Onset Systemic Lupus Erythematosus

Objective. To define inactive disease (ID) and clinical remission (CR) and to delineate variables that can be used to measure ID/CR in childhood-onset systemic lupus erythematosus (cSLE). Methods. Delphi questionnaires were sent to an international group of pediatric rheumatologists. Respondents provided information about variables to be used in future algorithms to measure ID/CR. The usefulness of these variables was assessed in 35 children with ID and 31 children with minimally active lupus (MAL). Results. While ID reflects cSLE status at a specific point in time, CR requires the presence of ID for >6 months and considers treatment. There was consensus that patients in ID/CR can have <2 mild nonlimiting symptoms (i.e., fatigue, arthralgia, headaches, or myalgia) but not Raynaud's phenomenon, chest pain, or objective physical signs of cSLE; antinuclear antibody positivity and erythrocyte sedimentation rate elevation can be present. Complete blood count, renal function testing, and complement C3 all must be within the normal range. Based on consensus, only damage-related laboratory or clinical findings of cSLE are permissible with ID. The above parameters were suitable to differentiate children with ID/CR from those with MAL (area under the receiver operating characteristic curve >0.85). Disease activity scores with or without the physician global assessment of disease activity and patient symptoms were well suited to differentiate children with ID from those with MAL. Conclusion. Consensus has been reached on common definitions of ID/CR with cSLE and relevant patient characteristics with ID/CR. Further studies must assess the usefulness of the data-driven candidate criteria for ID in cSLE.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.