A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Short-term Forecasting of Electricity Generation using Artificial Neural Networks (ANN)

As energias renováveis tornaram-se uma fonte substancial de energia em quase toda a Europa devido ao ambiente limpo e livre de poluição em comparação com os combustíveis fósseis que são usados principalmente para a geração de energia. Por estas razões também em Portugal a atenção para a utilização de energias renováveis tem vindo a crescer rapidamente. Na última década, muita investigação tem sido realizada sobre a previsão de curto prazo da produção de energias renováveis ao longo de um período de horas e dias na eletricidade ibérica. mercado (MIBEL). Esta dissertação centra-se nas previsões para o dia seguinte e começa com uma visão teórica e panorâmica do competitivo mercado de energia em Portugal. A principal análise para focar a previsão do dia à frente é garantir o equilíbrio entre a demanda e o fornecimento de eletricidade e porque a energia necessária deve ser vendida contra o preço do mercado à vista do dia seguinte. Com base no estudo detalhado da literatura no setor de previsão para cada tecnologia, certos fatores podem ser encontrados, como localização geográfica, fonte de dados meteorológicos e fonte de dados históricos que são alavancados na precisão e para construir muitos modelos com variáveis de entrada variadas. Nos dias atuais, as ferramentas de previsão precisas são requisitos essenciais para o produtor maximizar seus lucros, admitindo perdas de lucro devido ao erro de julgamento dos movimentos de produção futuros, e para o consumidor maximizar suas utilidades. A precisão dessas ferramentas de previsão depende principalmente do tipo e qualidade da informação que é posteriormente fornecida aos dados de entrada no modelo de previsão. Além disso, com base nas variáveis de entrada do estudo detalhado, como velocidade do vento, direção do vento, umidade relativa, temperatura, irradiação de pluviosidade e dados sazonais, foram considerados valiosos para desenvolver modelos de previsão. Muitas técnicas para prever a energia de produção para cada tecnologia são o método de regressão linear, a regressão multicamadas e as redes neurais artificiais (ANN) e a abordagem (Algoritmo de LevenbergMarquardt (LMA)) Os resultados obtidos após a correlação (correlação do coeficiente de Pearson) da entrada é feed-forward para a rede neural e muitos modelos foram construídos. Esses resultados da rede neural foram comparados com a produção real dos resultados de predição previstos. A saída obtida é fornecida para técnicas de gerenciamento de erros, como erros de porcentagem média absoluta (MAPE). A avaliação da conformidade foi realizada por meio do Erro Percentual Médio Absoluto (MAPE) e Erro Percentual Absoluto (APE), e foi encerrando os modelos de previsão desenvolvidos para apresentarem uma precisão bastante aceitável. entretanto, para minimizar a redução de erros, os resultados são exibidos. Além disso, muitos modelos de previsão foram executados e, posteriormente, comparados do menos com os bons modelos de previsão. Desta forma, ajuda a atingir modelos de previsão de produção de erro de baixo risco mais eficientes para cada tecnologiaRenewable energy has become a substantial source of energy nearly all through Europe since of a clean and pollution-free environment compared to fossil fuels which are primarily utilized for the era of energy. Due to these reasons moreover, within Portugal attention towards the utilization of renewable power has rapidly developing In the recent decade, an abundance of research has been performed on the short-term forecasting of renewable energy production over a period of an hour and day in the Iberian power market (MIBEL). This dissertation focuses on day-ahead forecasting and beginning with a theoretical and overview of the competitive energy market in Portugal. The main analysis to focus on dayahead forecasting is to ensure the balance between the demand and supply of the electricity and because of the energy required to be sold against at the day-ahead spot market price. Based on the detailed literature study in the sector of forecasting for each technology certain factors have been found such as geographical location, meteorological data source, and the historical data source which is leverage on the accuracy and to build many numbers of models with assorted input variables. Present days, Accurate forecasting tools are an essential requirement for the producer to maximize their profits, avowing profit losses over the misjudgement of future production movements, and for the consumer to maximize their utilities. The accuracy of these forecasting tools is mainly dependent on the kind and quality of information which is later given to the input data in the forecasting model. Furthermore, based on the detail study inputs variables such as wind speed, wind direction, relative humidity, temperature, pluviosity irradiation and seasonal data have been found valuable to develop forecasting models. From plentiful of techniques to predict production energy for each technology are linear regression method, multilayer regression, and Artificial neural networks (ANN) along with approach (Levenberg-Marquardt Algorithm (LMA)) Obtained results after correlation (Pearson coefficient correlation) of the input is feedforward to the neural network and many models have been constructed. These results from the neural network have been compared with actual production from predicted forecasting results. The obtained output is supplied to error management techniques such as Mean Absolute Percentage Errors (MAPE). The Accomplishment appraisal was performed through the Mean Absolute Percentage Error (MAPE) and Absolute Percentage Error (APE), and it was terminating the forecast models developed to show a very acceptable accuracy. however, to minimize the error reduction is accomplished which is exhibit the results. Furthermore, many forecasting models were performed and later compared from least to good forecasting models. By this way helps to attain the most efficient, low-risk error production forecasting models for each technology have been achieved in results

Internet of things and industrial applications for precision machining

The Internet of Things (IoT) can be regarded as an attempt to bring together the physical and the digital world by using devices for seamlessly exchanging and processing information that can be used anywhere, anytime. For industrial automation and manufacturing, the Industrial Internet of Things (IIoT) is regarded as the next step of industrial revolution that promises a step-change in productivity and operational efficiency. Precision machining is a field that has received a lot of research interest as it deals with phenomena and underlying mechanisms that are very complex and highly interacting. As the requirements and demand for products of high quality and tolerances that must be produced with shorter lead times are increasing, innovative approaches and methodologies need to be developed to compensate and IIoT offers an appropriate platform. This paper aims to present an overview of IIoT, investigate potential industrial applications for precision machining and predict future trends

Cloud manufacturing architecture for part quality assessment

In this work, a cloud manufacturing architecture aimed at offering on-demand services for part quality assessment is presented and demonstrated with reference to an aeronautical industry application. The developed architecture is based on a three-level structure and considers two non-contact metrological procedures to be integrated via cloud service: laser-based 3D metrology and ultrasonic non-destructive inspection. The combination of these two techniques allows to measure part features and detect possible defects associated with the outer part geometry as well as the inner material structure. The data coming from the two metrological procedures and pre-processed at fog level are sent to the cloud that performs their integration with the aim to allow for the 3D visualization and manipulation of the heterogeneous metrological data into a single-user interface for the holistic part quality evaluation. The validation of the cloud manufacturing architecture for part quality assessment is performed on a composite material component employed in the aeronautical industry. Through the cloud platform, the heterogeneous data from the two non-contact metrological techniques are integrated, and the newly developed user interface allows for the simultaneous visualization and analysis of the 3D metrology and ultrasonic information for detecting geometrical defects and internal flaws of the inspected component

The Strategic Use of Information Technology in the Insurance Industry: A Case Study of State Insurance Company- Kumasi, Ghana

The study aimed at finding out the strategic use of information technology in the State Insurance Company limited- Ghana, using Kumasi area office as the case study.Generally, the study focused attention on how managers and workers need to know about technology, the kind of information systems that support business needs, the benefits of adopting emerging technologies in insurance among others.Sixty (60) respondents were purposively selected which was guided by sampling procedure.  Quota sampling was also adopted.  Two (2) questionnaires were administered to the Area Manager and the deputy, ten (10) to all Heads of departments, thirty (30) to Senior Staff and eighteen (18) to Junior Staff.The findings revealed that most of the respondents rated the strategic use of IT in the company as playing a good role due to the fact that it has improved the workflow, respond quickly and timely on information requests and reduce cost of filling, storing and retrieving paper document, and unlike the traditional method, documents stored electronically are seldom lost or misfiled whilst at the same time it has reduced risk to a manageable extent.  There was also insufficient transaction through the internet between clients and the company. It was recommended that State Insurance Company Limited should add knowledge in IT as a prerequisite for recruiting staffs with the intention of reducing the operating cost of IT. Keywords: Information Technology (IT), Insurance, Risk, Kumasi, Internet, Recovery, Recruitin

Features of enterprise risk management associated with operational risks

Purpose of the work: within the framework of the concept of corporate risk management Enterprise Risk Management (ERM) to study the basic types of risks, assess their role in the modern economy, analyze external and internal operational risks and propose approaches to their quantitative assessment. As a research methodology, it is proposed to use the developed tools of mathematical and numerical modeling, which allows one to obtain, in the key of interest to the decision maker, qualitative and quantitative characteristics of the dynamics of business processes. The operational and economic risks (as very often occurring in the activities of subjects of economic relations) and directly affecting their economic and information security are considered in sufficient detail. It is noted that the risks associated with disruption of business continuity (which enterprises face in their activities) can be included in various classification systems of risks, grouped according to various criteria. The need to identify the mismatch between the design and actual metrics of the organizational structure (establishment of its structure and operating schemes based on the needs of the enterprise/organization) is indicated for solving the optimization problem

Political Economy of International Climate Finance: Navigating Decisions in PPCR and SREP

This working paper explores how countries can build their own 'climate finance readiness' by understanding their internal political economy and use that understanding to steer consensus-based decisions on climate finance investments. For climate finance to be effective, national leaders must build shared commitments. This involves considering the arguments, incentives and power dynamics at play to ensure priorities are more equitable and representative of a broader group of stakeholders. Doing so will also help to reduce the risk of implementation delays. This paper uses case studies from Bangladesh, Ethiopia and Nepal to explore how narratives and incentives within the political economy drive climate investment outcomes under the Pilot Programme for Climate Resilience (PPCR) and the Scaling up Renewable Energy Programme (SREP). It draws from broader analysis of the discourses around these investments, including 80 interviews with government; multilateral development banks (MDBs) and other stakeholders

METROLOGICAL SUPPORT OF MONITORING SYSTEMS BASED ON UNMANNED AERIAL VEHICLES

The article discusses the fields and methods of application of unmanned aerial vehicles (UAV). Current legislation in Russia and in the world, significantly limit the use of UAV in monitoring. For the first time, we present a solution to the problem of a monitoring measurement system included in the state register of measuring instruments using the example of the basic UAV model. We conducted an analysis of promising approaches to the creation of UAV metrological and methodological support, as well as ways to adapt their target load to meet the challenges of operational monitoring of air pollution