Prediction of nutrient digestibility and energy concentrations in fresh grass using nutrient composition

Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

Exploring the impact of social axioms on firm reputation: a stakeholder perspective

This study proposes a model of how deeply held beliefs, known as ‘social axioms, moderate the interaction between reputation, its causes and consequences with stakeholders. It contributes to the stakeholder relational field of reputation theory by explaining why the same organizational stimuli lead to different individual stakeholder responses. The study provides a shift in reputation research from organizational-level stimuli as the root causes of stakeholder responses to exploring the interaction between individual beliefs and organizational stimuli in determining reputational consequences. Building on a conceptual model that incorporates product/service quality and social responsibility as key reputational dimensions, the authors test empirically for moderating influences, in the form of social axioms, between reputation-related antecedents and consequences, using component-based structural equation modelling (n = 204). In several model paths, significant differences are found between responses of individuals identified as either high or low on social cynicism, fate control and religiosity. The results suggest that stakeholder responses to reputation-related stimuli can be systematically predicted as a function of the interactions between the deeply held beliefs of individuals and these stimuli. The authors offer recommendations on how strategic reputation management can be approached within and across stakeholder groups at a time when firms grapple with effective management of diverse stakeholder expectations.

Wireless energy behaviour monitoring (Wi-be) for office buildings

This paper presents a study on reduction of energy consumption in buildings through behaviour change informed by wireless monitoring systems for energy, environmental conditions and people positions. A key part to the Wi-Be system is the ability to accurately attribute energy usage behaviour to individuals, so they can be targeted with specific feedback tailored to their preferences. The use of wireless technologies for indoor positioning was investigated to ascertain the difficulties in deployment and potential benefits. The research to date has demonstrated the effectiveness of highly disaggregated personal-level data for developing insights into people’s energy behaviour and identifying significant energy saving opportunities (up to 77% in specific areas). Behavioural research addressed social issues such as privacy, which could affect the deployment of the system. Radio-frequency research into less intrusive technologies indicates that received-signal-strength-indicator-based systems should be able to detect the presence of a human body, though further work would be needed in both social and engineering areas.

Improving data perturbation testing techniques for Web services

The widespread use of service-oriented architectures (SOAs) and Web services in commercial software requires the adoption of development techniques to ensure the quality of Web services. Testing techniques and tools concern quality and play a critical role in accomplishing quality of SOA based systems. Existing techniques and tools for traditional systems are not appropriate to these new systems, making the development of Web services testing techniques and tools required. This article presents new testing techniques to automatically generate a set of test cases and data for Web services. The techniques presented here explore data perturbation of Web services messages upon data types, integrity and consistency. To support these techniques, a tool (GenAutoWS) was developed and applied to real problems. (C) 2010 Elsevier Inc. All rights reserved.

Design issues for knowledge artifacts

The notion of knowledge artifact has rapidly gained popularity in the fields of general knowledge management and more recently knowledge-based systems. The main goal on this paper is to propose and discuss a methodology for the design and implementation of knowledge-based systems founded on knowledge artifacts. We advocate that the systems built according to this methodology can be effective to convey the flow of knowledge between different communities of practice. Our methodology has been developed from the ground up, i.e. we have built some concrete systems based on the abstract notion of knowledge artifact and synthesized our methodology based on reflections upon our experiences building these systems. In this paper, we also describe the most relevant systems we have built and how they have guided us to the synthesis of our proposed methodology. (C) 2008 Elsevier B.V. All rights reserved.

Chemiluminescence as a PDT light source for microbial control

The photodynamic therapy (PDT) is a combination of using a photosensitizer agent, light and oxygen that can cause oxidative cellular damage. This technique is applied in several cases, including for microbial control. The most extensively studied light sources for this purpose are lasers and LED-based systems. Few studies treat alternative light sources based PDT. Sources which present flexibility, portability and economic advantages are of great interest. In this study, we evaluated the in vitro feasibility for the use of chemiluminescence as a PDT light source to induce Staphylococcus aureus reduction. The Photogem (R) concentration varied from 0 to 75 mu g/ml and the illumination time varied from 60 min to 240 min. The long exposure time was necessary due to the low irradiance achieved with chemiluminescence reaction at mu W/cm(2) level. The results demonstrated an effective microbial reduction of around 98% for the highest photosensitizer concentration and light dose. These data suggest the potential use of chemiluminescence as a light source for PDT microbial control, with advantages in terms of flexibility, when compared with conventional sources. (C) 2011 Elsevier B.V. All rights reserved.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Describing Web Service Architectures through Design-by-Contract

Architectural description languages (ADLs) are used to specify a high-level, compositional view of a software application, specifying how a system is to be composed from coarse-grain components. ADLs usually come equipped with a formal dynamic semantics, facilitating specification and analysis of distributed and event-based systems. In this paper, we describe the TrustME, an ADL framework that provides both a process and a structural view of web service-based systems. We use Petri-net descriptions to give a dynamic view of business workflow for web service collaboration. We adapt the approach of Schmidt to define a form of Meyer's design-by-contract for configuring workflow architectures. This serves as a configuration-level means of constructing safer, more robust systems.

An Architectural Description Language for Enterprise Computing

Architectural description languages (ADLs) are used to specify high-level, compositional view of a software application. ADLs usually come equipped with a rigourous state-transition style semantics, facilitating specification and analysis of distributed and event-based systems. However, enterprise system architectures built upon newer middleware (implementations of Java’s EJB specification, or Microsoft’s COM+/ .NET) require additional expressive power from an ADL. The TrustME ADL is designed to meet this need. In this paper, we describe several aspects of TrustME that facilitate specification and anlysis of middleware-based architectures for the enterprise.

Trust-By-Contract: Modelling, Analysing and Predicting Behaviour in Software Architectures

Architecture description languages (ADLs) are used to specify high-level, compositional views of a software application. ADL research focuses on software composed of prefabricated parts, so-called software components. ADLs usually come equipped with rigorous state-transition style semantics, facilitating verification and analysis of specifications. Consequently, ADLs are well suited to configuring distributed and event-based systems. However, additional expressive power is required for the description of enterprise software architectures – in particular, those built upon newer middleware, such as implementations of Java’s EJB specification, or Microsoft’s COM+/.NET. The enterprise requires distributed software solutions that are scalable, business-oriented and mission-critical. We can make progress toward attaining these qualities at various stages of the software development process. In particular, progress at the architectural level can be leveraged through use of an ADL that incorporates trust and dependability analysis. Also, current industry approaches to enterprise development do not address several important architectural design issues. The TrustME ADL is designed to meet these requirements, through combining approaches to software architecture specification with rigorous design-by-contract ideas. In this paper, we focus on several aspects of TrustME that facilitate specification and analysis of middleware-based architectures for trusted enterprise computing systems.

Aplicando métodos de solução de problemas em tarefas de interpretação de rochas

A Engenharia de Conhecimento (Knowledge Engineering - KE) atual considera o desenvolvimento de Sistemas Baseados em Conhecimento (Knowledge- Based Systems - KBSs) como um processo de modelagem baseado em modelos de conhecimento reusáveis. A noção de Métodos de Solução de Problemas (Problem- Solving Methods - PSMs) desempenha um importante papel neste cenário de pesquisa, pois representa o conhecimento inferencial de KBSs em um formalismo explícito. Não menos importante, PSMs também facilitam a compreensão do processo de raciocínio desenvolvido por humanos. PSMs são descritos em um formalismo abstrato e independente de implementação, facilitando a análise do conhecimento inferencial que muitas vezes é obscurecido em grandes bases de conhecimento. Desta forma, este trabalho discute a noção de PSMs, avaliando os problemas de pesquisa envolvidos no processo de desenvolvimento e especificação de um método, como também analisando as possibilidades de aplicação de PSMs. O trabalho apresenta a descrição e análise de um estudo de caso sobre o processo de desenvolvimento, especificação e aplicação de um PSM Interpretação de Rochas. As tarefas de interpretação de rochas são desenvolvidas por petrógrafos especialistas e correspondem a um importante passo na caracterização de rochasreservatório de petróleo e definição de técnicas de exploração, permitindo que companhias de petróleo reduzam custos de exploração normalmente muito elevados. Para suportar o desenvolvimento de KBSs neste domínio de aplicação, foram desenvolvidos dois PSMs novos: o PSM Interpretação de Rochas e o PSM Interpretação de Ambientes Diagenéticos. Tais métodos foram especificados a partir de uma análise da perícia em Petrografia Sedimentar, como também a partir de modelos de conhecimento e dados desenvolvidos durante o projeto PetroGrapher. O PSM Interpretação de Rochas e o PSM Interpretação de Ambientes Diagenéticos são especificados conceitualmente em termos de competência, especificação operacional e requisitos/suposições. Tais definições detalham os componentes centrais de um esquema de raciocínio para interpretação de rochas. Este esquema é empregado como um modelo de compreensão e análise do processo de raciocínio requerido para orientar o desenvolvimento de uma arquitetura de raciocínio para interpretação de rochas. Esta arquitetura é descrita em termos de requisitos de armazenamento e manipulação de dados e conhecimento, permitindo projetar e construir um algoritmo de inferência simbólico para uma aplicação de bancos de dados inteligentes denominada PetroGrapher.