Effective Data Management Enables Intelligent Utility Management

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to manage data from smart water meters to the collaboration of data across third party corporations. This paper focuses on practical, utility successes in the water industry where utility managers are leveraging instantaneous access to data from proven, commercial off-the-shelf ODMS solutions to enable better real-time decision making. Successes include saving $650,000 / year in water loss control, safeguarding water quality, saving millions of dollars in energy management and asset management. Immediate opportunities exist to integrate the research being done in academia with these ODMS solutions in the field and to leverage these successes to utilities around the world.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Evaluation of the Genotoxicity of Chitosan Nanoparticles for Use in Food Packaging Films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of gamma-irradiation on caprolactam level from multilayer PA-6 films for food packaging: Development and validation of a gas chromatographic method

A gas chromatographic method to determine caprolactam in multilayer PA-6 films used for meat foodstuffs and cheese was developed and validated. A wide linear range (0.8-400 mu g/ml), RSD <= 4.1% and recovery higher than 90.0% were obtained for the chromatographic system, while precision and accuracy of the method showed RSD <= 3.8%, recovery from 95.5-100.0% and LOQ of 32 mu g/g. Irradiated (3, 7 and 12 kGy) and non-irradiated commercial films were analyzed. Most of them increased caprolactam levels with the increase of irradiation doses. (C) 2008 Elsevier Ltd. All rights reserved.

MIGRATION MEASUREMENTS FROM PLASTIC PACKAGING: A SIMULATION STUDY ON INFLUENCE OF INITIAL CONCENTRATION PROFILE

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

The transformation between exploration and exploitation applied to inventors of packaging innovations

While the inventor is often the driver of an invention in the early stages, he/she needs to move between different social networks for knowledge in order to create and capture value. The main objective of this research is to propose a literature-based framework based on innovation network theory and complemented with C-K theory, in order to analyze the invention/innovation process of inventors and the product concepts in a packaging industry context. Empirical input from three case studies of packaging inventions and their inventors is used to elaborate the suggested framework.The article identifies important gaps in the literature of innovation networks. This is addressed through a theoretical framework based on network theories, complemented with C-K theory for the product design level. The strength-of-ties dimension of the theoretical framework suggests, in agreement with the mainstream literature and the cases presented, that weak ties are required to access the knowledge related to exploration networks and strong ties are required to utilize the knowledge in the exploitation network. The transformation network is an intermediate step acting as a bridge where entrepreneurs can find required knowledge. The transformation network is also an intermediate step where entrepreneurs find financing and companies interested in commercializing inventions. (C) 2010 Elsevier Ltd. All rights reserved.

Application of intelligent systems for specification of automotive equipments using LEDs

The advantages offered by the electronic component light emitting diode ( LED) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data. (C) 2005 Elsevier B.V. All rights reserved.

A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Large nuclear vacuoles are indicative of abnormal chromatin packaging in human spermatozoa

The aim of this investigation was to determine the presence of abnormal sperm chromatin packaging in spermatozoa with large nuclear vacuoles (LNV) selected via high magnification by analysing the pattern of chromomycin A3 (CMA3) staining. A prospective observational study was designed to analyse semen samples obtained from 66 men undergoing infertility diagnosis and treatment. The numbers of cells with normal (dull yellow staining of the sperm head/CMA3-negative) and abnormal (bright yellow fluorescence of the sperm head/CMA3-positive) chromatin packaging were determined on slides with normal and LNV spermatozoa. The presence of bright yellow fluorescence (CMA3-positive) was significantly higher (p < 0.0001) in spermatozoa with LNV than in normal spermatozoa (719/1351; 53.2% vs. 337/835; 40.3%, respectively), reflecting a higher percentage of abnormal chromatin packaging in spermatozoa with large LNV. Our data support the hypothesis that the presence of LNV reflects the presence of abnormal chromatin packaging, which may facilitate sperm DNA damage. As sperm nuclear vacuoles are evaluated more precisely at high magnifications using motile sperm organelle morphology examination (MSOME), the present results support the use of high-magnification sperm selection for intracytoplasmic sperm injection (ICSI).