Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

A framework for using real data with distributed low cost sensors

Currently, due to the widespread use of computers and the internet, students are trading libraries for the World Wide Web and laboratories with simulation programs. In most courses, simulators are made available to students and can be used to proof theoretical results or to test a developing hardware/product. Although this is an interesting solution: low cost, easy and fast way to perform some courses work, it has indeed major disadvantages. As everything is currently being done with/in a computer, the students are loosing the “feel” of the real values of the magnitudes. For instance in engineering studies, and mainly in the first years, students need to learn electronics, algorithmic, mathematics and physics. All of these areas can use numerical analysis software, simulation software or spreadsheets and in the majority of the cases data used is either simulated or random numbers, but real data could be used instead. For example, if a course uses numerical analysis software and needs a dataset, the students can learn to manipulate arrays. Also, when using the spreadsheets to build graphics, instead of using a random table, students could use a real dataset based, for instance, in the room temperature and its variation across the day. In this work we present a framework which uses a simple interface allowing it to be used by different courses where the computers are the teaching/learning process in order to give a more realistic feeling to students by using real data. A framework is proposed based on a set of low cost sensors for different physical magnitudes, e.g. temperature, light, wind speed, which are connected to a central server, that the students have access with an Ethernet protocol or are connected directly to the student computer/laptop. These sensors use the communication ports available such as: serial ports, parallel ports, Ethernet or Universal Serial Bus (USB). Since a central server is used, the students are encouraged to use sensor values results in their different courses and consequently in different types of software such as: numerical analysis tools, spreadsheets or simply inside any programming language when a dataset is needed. In order to do this, small pieces of hardware were developed containing at least one sensor using different types of computer communication. As long as the sensors are attached in a server connected to the internet, these tools can also be shared between different schools. This allows sensors that aren't available in a determined school to be used by getting the values from other places that are sharing them. Another remark is that students in the more advanced years and (theoretically) more know how, can use the courses that have some affinities with electronic development to build new sensor pieces and expand the framework further. The final solution provided is very interesting, low cost, simple to develop, allowing flexibility of resources by using the same materials in several courses bringing real world data into the students computer works.

A module for Data Centric Storage in ns-3

Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

On the analysis of data emerging in non-linear and complex systemscomparison of two X-Ray prony spectra

New arguments proving that successive (repeated) measurements have a memory and actually remember each other are presented. The recognition of this peculiarity can change essentially the existing paradigm associated with conventional observation in behavior of different complex systems and lead towards the application of an intermediate model (IM). This IM can provide a very accurate fit of the measured data in terms of the Prony's decomposition. This decomposition, in turn, contains a small set of the fitting parameters relatively to the number of initial data points and allows comparing the measured data in cases where the “best fit” model based on some specific physical principles is absent. As an example, we consider two X-ray diffractometers (defined in paper as A- (“cheap”) and B- (“expensive”) that are used after their proper calibration for the measuring of the same substance (corundum a-Al2O3). The amplitude-frequency response (AFR) obtained in the frame of the Prony's decomposition can be used for comparison of the spectra recorded from (A) and (B) - X-ray diffractometers (XRDs) for calibration and other practical purposes. We prove also that the Fourier decomposition can be adapted to “ideal” experiment without memory while the Prony's decomposition corresponds to real measurement and can be fitted in the frame of the IM in this case. New statistical parameters describing the properties of experimental equipment (irrespective to their internal “filling”) are found. The suggested approach is rather general and can be used for calibration and comparison of different complex dynamical systems in practical purposes.

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%.

Uso Sustentável de Vapor

Em 2006, a IEA (Agência Internacional de Energia), publicou alguns estudos de consumos mundiais de energia. Naquela altura, apontava na fabricação de produtos, um consumo mundial de energia elétrica, de origem fóssil de cerca 86,16 EJ/ano (86,16×018 J) e um consumo de energia nos sistemas de vapor de 32,75 EJ/ano. Evidenciou também nesses estudos que o potencial de poupança de energia nos sistemas de vapor era de 3,27 EJ/ano. Ou seja, quase tanto como a energia consumida nos sistemas de vapor da U.E. Não se encontraram números relativamente a Portugal, mas comparativamente com outros Países publicitados com alguma similaridade, o consumo de energia em vapor rondará 0,2 EJ/ano e por conseguinte um potencial de poupança de cerca 0,02 EJ/ano, ou 5,6 × 106 MWh/ano ou uma potência de 646 MW, mais do que a potência de cinco barragens Crestuma/Lever! Trata-se efetivamente de muita energia; interessa por isso perceber o onde e o porquê deste desperdício. De um modo muito modesto, pretende-se com este trabalho dar algum contributo neste sentido. Procurou-se evidenciar as possibilidades reais de os utilizadores de vapor de água na indústria reduzirem os consumos de energia associados à sua produção. Não estão em causa as diferentes formas de energia para a geração de vapor, sejam de origem fóssil ou renovável; interessou neste trabalho estudar o modo de como é manuseado o vapor na sua função de transporte de energia térmica, e de como este poderá ser melhorado na sua eficiência de cedência de calor, idealmente com menor consumo de energia. Com efeito, de que servirá se se optou por substituir o tipo de queima para uma mais sustentável se a jusante se continuarem a verificarem desperdícios, descarga exagerada nas purgas das caldeiras com perda de calor associada, emissões permanentes de vapor para a atmosfera em tanques de condensado, perdas por válvulas nos vedantes, purgadores avariados abertos, pressão de vapor exageradamente alta atendendo às temperaturas necessárias, “layouts” do sistema de distribuição mal desenhados, inexistência de registos de produção e consumos de vapor, etc. A base de organização deste estudo foi o ciclo de vapor: produção, distribuição, consumo e recuperação de condensado. Pareceu importante incluir também o tratamento de água, atendendo às implicações na transferência de calor das superfícies com incrustações. Na produção de vapor, verifica-se que os maiores problemas de perda de energia têm a ver com a falta de controlo, no excesso de ar e purgas das caldeiras em exagero. Na distribuição de vapor aborda-se o dimensionamento das tubagens, necessidade de purgas a v montante das válvulas de controlo, a redução de pressão com válvulas redutoras tradicionais; será de destacar a experiência americana no uso de micro turbinas para a redução de pressão com produção simultânea de eletricidade. Em Portugal não se conhecem instalações com esta opção. Fabricantes da República Checa e Áustria, têm tido sucesso em algumas dezenas de instalações de redução de pressão em diversos países europeus (UK, Alemanha, R. Checa, França, etc.). Para determinação de consumos de vapor, para projeto ou mesmo para estimativa em máquinas existentes, disponibiliza-se uma série de equações para os casos mais comuns. Dá-se especial relevo ao problema que se verifica numa grande percentagem de permutadores de calor, que é a estagnação de condensado - “stalled conditions”. Tenta-se também evidenciar as vantagens da recuperação de vapor de flash (infelizmente de pouca tradição em Portugal), e a aplicação de termocompressores. Finalmente aborda-se o benchmarking e monitorização, quer dos custos de vapor quer dos consumos específicos dos produtos. Esta abordagem é algo ligeira, por manifesta falta de estudos publicados. Como trabalhos práticos, foram efetuados levantamentos a instalações de vapor em diversos sectores de atividades; 1. ISEP - Laboratório de Química. Porto, 2. Prio Energy - Fábrica de Biocombustíveis. Porto de Aveiro. 3. Inapal Plásticos. Componentes de Automóvel. Leça do Balio, 4. Malhas Sonix. Tinturaria Têxtil. Barcelos, 5. Uma instalação de cartão canelado e uma instalação de alimentos derivados de soja. Também se inclui um estudo comparativo de custos de vapor usado nos hospitais: quando produzido por geradores de vapor com queima de combustível e quando é produzido por pequenos geradores elétricos. Os resultados estão resumidos em tabelas e conclui-se que se o potencial de poupança se aproxima do referido no início deste trabalho.