Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

Emprego de regras de associação para extração de padrões mercadológicos de touros Nelore com avaliação genética

Objetivou-se com este trabalho utilizar regras de associação para identificar forças de mercado que regem a comercialização de touros com avaliação genética pelo programa Nelore Brasil. Essas regras permitem evidenciar padrões implícitos nas transações de grandes bases de dados, indicando causas e efeitos determinantes da oferta e comercialização de touros. Na análise foram considerados 19.736 registros de touros comercializados, 17 fazendas e 15 atributos referentes às diferenças esperadas nas progênies dos reprodutores, local e época da venda. Utilizou-se um sistema com interface gráfica usuário-dirigido que permite geração e seleção interativa de regras de associação. Análise de Pareto foi aplicada para as três medidas objetivas (suporte, confiança e lift) que acompanham cada uma das regras de associação, para validação das mesmas. Foram geradas 2.667 regras de associação, 164 consideradas úteis pelo usuário e 107 válidas para lift ≥ 1,0505. As fazendas participantes do programa Nelore Brasil apresentam especializações na oferta de touros, segundo características para habilidade materna, ganho de peso, fertilidade, precocidade sexual, longevidade, rendimento e terminação de carcaça. Os perfis genéticos dos touros são diferentes para as variedades padrão e mocho. Algumas regiões brasileiras são nichos de mercado para touros sem registro genealógico. A análise de evolução de mercado sugere que o mérito genético total, índice oficial do programa Nelore Brasil, tornou-se um importante índice para comercialização dos touros. Com o uso das regras de associação, foi possível descobrir forças do mercado e identificar combinações de atributos genéticos, geográficos e temporais que determinam a comercialização de touros no programa Nelore Brasil.

Efficiency and feasibility of product disassembly: A case-based study

The productivity associated with commonly available disassembly methods today seldomly makes disassembly the preferred end-of-life solution for massive take back product streams. Systematic reuse of parts or components, or recycling of pure material fractions are often not achievable in an economically sustainable way. In this paper a case-based review of current disassembly practices is used to analyse the factors influencing disassembly feasibility. Data mining techniques were used to identify major factors influencing the profitability of disassembly operations. Case characteristics such as involvement of the product manufacturer in the end-of-life treatment and continuous ownership are some of the important dimensions. Economic models demonstrate that the efficiency of disassembly operations should be increased an order of magnitude to assure the competitiveness of ecologically preferred, disassembly oriented end-of-life scenarios for large waste of electric and electronic equipment (WEEE) streams. Technological means available to increase the productivity of the disassembly operations are summarized. Automated disassembly techniques can contribute to the robustness of the process, but do not allow to overcome the efficiency gap if not combined with appropriate product design measures. Innovative, reversible joints, collectively activated by external trigger signals, form a promising approach to low cost, mass disassembly in this context. A short overview of the state-of-the-art in the development of such self-disassembling joints is included. (c) 2008 CIRP.

Impact of Commercial Search Engines and International Databases on Engineering Teaching and Research

For the last three decades, the engineering higher education and professional environments have been completely transformed by the "electronic/digital information revolution" that has included the introduction of personal computer, the development of email and world wide web, and broadband Internet connections at home. Herein the writer compares the performances of several digital tools with traditional library resources. While new specialised search engines and open access digital repositories may fill a gap between conventional search engines and traditional references, these should be not be confused with real libraries and international scientific databases that encompass textbooks and peer-reviewed scholarly works. An absence of listing in some Internet search listings, databases and repositories is not an indication of standing. Researchers, engineers and academics should remember these key differences in assessing the quality of bibliographic "research" based solely upon Internet searches.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Allergen databases

Allergies represent a significant medical and industrial problem. Molecular and clinical data on allergens are growing exponentially and in this article we have reviewed nine specialized allergen databases and identified data sources related to protein allergens contained in general purpose molecular databases. An analysis of allergens contained in public databases indicates a high level of redundancy of entries and a relatively low coverage of allergens by individual databases. From this analysis we identify current database needs for allergy research and, in particular, highlight the need for a centralized reference allergen database.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Towards the wide implementation of standards IEC 61968/70 (CIM) and IEC 61850 in the distribution system (CIGRÉ C6-105_2010)

Currently, power systems (PS) already accommodate a substantial penetration of distributed generation (DG) and operate in competitive environments. In the future, as the result of the liberalisation and political regulations, PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage and provide market agents to ensure a flexible and secure operation. This cannot be done with the traditional PS operational tools used today like the quite restricted information systems Supervisory Control and Data Acquisition (SCADA) [1]. The trend to use the local generation in the active operation of the power system requires new solutions for data management system. The relevant standards have been developed separately in the last few years so there is a need to unify them in order to receive a common and interoperable solution. For the distribution operation the CIM models described in the IEC 61968/70 are especially relevant. In Europe dispersed and renewable energy resources (D&RER) are mostly operated without remote control mechanisms and feed the maximal amount of available power into the grid. To improve the network operation performance the idea of virtual power plants (VPP) will become a reality. In the future power generation of D&RER will be scheduled with a high accuracy. In order to realize VPP decentralized energy management, communication facilities are needed that have standardized interfaces and protocols. IEC 61850 is suitable to serve as a general standard for all communication tasks in power systems [2]. The paper deals with international activities and experiences in the implementation of a new data management and communication concept in the distribution system. The difficulties in the coordination of the inconsistent developed in parallel communication and data management standards - are first addressed in the paper. The upcoming unification work taking into account the growing role of D&RER in the PS is shown. It is possible to overcome the lag in current practical experiences using new tools for creating and maintenance the CIM data and simulation of the IEC 61850 protocol – the prototype of which is presented in the paper –. The origin and the accuracy of the data requirements depend on the data use (e.g. operation or planning) so some remarks concerning the definition of the digital interface incorporated in the merging unit idea from the power utility point of view are presented in the paper too. To summarize some required future work has been identified.

Análise de eficiência energética de transportes rodoviários

Projecto para obtenção do grau de Mestre em Engenharia Informática e de computadores

Digital disease detection and participatory surveillance: overview and perspectives for Brazil

ABSTRACT This study aimed to describe the digital disease detection and participatory surveillance in different countries. The systems or platforms consolidated in the scientific field were analyzed by describing the strategy, type of data source, main objectives, and manner of interaction with users. Eleven systems or platforms, developed from 1996 to 2016, were analyzed. There was a higher frequency of data mining on the web and active crowdsourcing as well as a trend in the use of mobile applications. It is important to provoke debate in the academia and health services for the evolution of methods and insights into participatory surveillance in the digital age.

Design and implementation of an autonomous, proactive, and reactive software infrastructure to help improving the management level of projects

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores