Application of logistic regression for fault analysis in an industrial printing process

A statistical technique for fault analysis in industrial printing is reported. The method specifically deals with binary data, for which the results of the production process fall into two categories, rejected or accepted. The method is referred to as logistic regression, and is capable of predicting future fault occurrences by the analysis of current measurements from machine parts sensors. Individual analysis of each type of fault can determine which parts of the plant have a significant influence on the occurrence of such faults; it is also possible to infer which measurable process parameters have no significant influence on the generation of these faults. Information derived from the analysis can be helpful in the operator's interpretation of the current state of the plant. Appropriate actions may then be taken to prevent potential faults from occurring. The algorithm is being implemented as part of an applied self-learning expert system.

Species-specific responses of Late Quaternary megafauna to climate and humans

Despite decades of research, the roles of climate and humans in driving the dramatic extinctions of large-bodied mammals during the Late Quaternary period remain contentious. Here we use ancient DNA, species distribution models and the human fossil record to elucidate how climate and humans shaped the demographic history of woolly rhinoceros, woolly mammoth, wild horse, reindeer, bison and musk ox. We show that climate has been a major driver of population change over the past 50,000 years. However, each species responds differently to the effects of climatic shifts, habitat redistribution and human encroachment. Although climate change alone can explain the extinction of some species, such as Eurasian musk ox and woolly rhinoceros, a combination of climatic and anthropogenic effects appears to be responsible for the extinction of others, including Eurasian steppe bison and wild horse. We find no genetic signature or any distinctive range dynamics distinguishing extinct from surviving species, emphasizing the challenges associated with predicting future responses of extant mammals to climate and human-mediated habitat change.

Challenges in communicating and using ensembles in operational flood forecasting.

Following trends in operational weather forecasting, where ensemble prediction systems (EPS) are now increasingly the norm, flood forecasters are beginning to experiment with using similar ensemble methods. Most of the effort to date has focused on the substantial technical challenges of developing coupled rainfall-runoff systems to represent the full cascade of uncertainties involved in predicting future flooding. As a consequence much less attention has been given to the communication and eventual use of EPS flood forecasts. Drawing on interviews and other research with operational flood forecasters from across Europe, this paper highlights a number of challenges to communicating and using ensemble flood forecasts operationally. It is shown that operational flood forecasters understand the skill, operational limitations, and informational value of EPS products in a variety of different and sometimes contradictory ways. Despite the efforts of forecasting agencies to design effective ways to communicate EPS forecasts to non-experts, operational flood forecasters were often skeptical about the ability of forecast recipients to understand or use them appropriately. It is argued that better training and closer contacts between operational flood forecasters and EPS system designers can help ensure the uncertainty represented by EPS forecasts is represented in ways that are most appropriate and meaningful for their intended consumers, but some fundamental political and institutional challenges to using ensembles, such as differing attitudes to false alarms and to responsibility for management of blame in the event of poor or mistaken forecasts are also highlighted. Copyright © 2010 Royal Meteorological Society.

Challenges in quantifying changes in the global water cycle

Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes.

The labor demand was downward sloping: disentangling migrants’ inflows and outflows, 1929–1957

This paper studies in- and out-migration from the U.S. during the first half of the twentieth century and assesses how these flows affected state-level labor markets. It shows that out-migration positively impacted the earnings growth of remaining workers, while in-migration had a negative impact. Hence, immigrant arrivals were substitutes of the existing workforce, while out-migration reduced the competitive pressure on labor markets

On the predictive content of leading indicators: the case of U.S. real estate markets

This paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.

Schooling and the intergenerational transmission of values

We present a model of the evolution of identity via dynamic interaction between the choice of education and the transmission of values in a community from parents to children, when parents care about the preservation of their traditional community values, different from the values of the host society. We compare the educational and socioeconomic outcomes in different scenarios (melting pot versus multiculturalism). If schooling shifts children’s identity away from their parents’ values, parents may choose lower levels of education for their children, at the cost of reducing their future earnings. We show how this effect can be attenuated and reversed when the school or, indeed, the host society are willing to accommodate the values of the community and/or to adjust to these values; otherwise the community gradually becomes alienated. This approach may be applied to the analysis of temporal changes in values and attitudes in a community of immigrants, as well as ethnic, religious, or other minority groups.

Managing ServerHotel

This graduate study was assigned by Unisys Oy Ab. The purpose of this study was to find tools to monitor and manage servers and objects in a hosting environment and to remotely connect to the managed objects. Better solutions for promised services were also researched. Unisys provides a ServerHotel service to other businesses which do not have time or resources to manage their own network, servers or applications. Contracts are based on a Service Level Agreement where service level is agreed upon according to the customer's needs. These needs have created a demand for management tools. Unisys wanted to find the most appropriate tools for its hosting environment to fulfill the agreed service level with reasonable costs. The theory consists of literary research focusing on general agreements used in the Finnish IT business, different types of monitoring and management tools and the common protocols used inthem. The theory focuses mainly on the central elements of the above mentioned topics and on their positive and negative features. The second part of the study focuses on general hosting agreements and what management tools Unisys has selected for hosting and why. It also gives a more detailed account of the hosting environment and its features in more detail. Because of the results of the study Unisys decided to use Servers Alive to monitor network and MS applications’ services. Cacti was chosen to monitor disk spaces, which gives us an idea of future disk growth. For remote connections the Microsoft’s Remote Desktop tool was the mostappropriate when the connection was tunneled through Secure Shell (SSH). Finding proper tools for the intended purposes with cost-conscious financial resources proved challenging. This study showed that if required, it is possible to build a professional hosting environment.

Sustainability & Consumer behavior towards Sustainability in Norway and Sweden

AimSustainability has become an important factor to consider while buying goods and services. People are being more conscious toward environmental impacts of products and services. This attitude has motivated many businesses to develop their production in contact with sustainability. The aim of this paper is to investigate different consumer behaviors toward sustainability in general and in relation to vehicles in Norway and Sweden.ApproachThe project has been embarked by dividing it into two tasks.1. Analyzing past, present and future development, growth and importance of sustainability concept. Describe the role of Government authorities in Norway and Sweden to promote sustainable consumption.2. Investigating important factors of consumer behaviors which influence their buying decision toward sustainable products in general and in relation to sustainable vehicles. Highlight the role of vehicle manufacturing companies to promote sustainable consumption.MethodA research has been conducted in order to explore consumer behavior toward sustainability in Norway and Sweden. Research is based on Document study and primary research which include questionnaire survey with consumers and interviews with vehicle dealers. In addition an expert inquiry is conducted to light up consumer intensions in Norway and Sweden toward sustainability.ResultsThe result of investigation has been revealed in shape of analyses and conclusion at the end. A comparison has been made between primary research and secondary research and findings are overlapping. Sustainable vehicles are being more popular among consumers in Norway and Sweden. Consumption trends are changing over time and environmental friendly attitudes are more developing among Swedish consumers as compared to Norwegian.

Crescimento do consumo e a estrutura a termo de taxa de juros: um estudo voltado para o caso brasileiro

Tendo por base o trabalho realizado por Hyde e Sherif (2010) com dados do mercado inglês, foi desenvolvido estudo com o objetivo de avaliar a capacidade do spread de curto e longo prazo da taxa de juros de funcionar como indicador do crescimento futuro do consumo no Brasil. Tanto Hyde e Sherif (2010) como outros estudos realizados em países desenvolvidos indicaram relação positiva entre o spread de juros de curto e longo prazo e o crescimento do consumo. Entretanto, as análises empíricas realizadas neste estudo para o caso brasileiro, apresentaram resultados divergentes do esperado pela teoria, indicando relação negativa entre o spread de juros e o crescimento do consumo. Em algumas análises, os estudos não indicaram relação entre as variáveis. Foram discutidas possíveis razões para estes resultados contraintuitivos, tais como tamanho reduzido da amostra, nível da taxa de juros no Brasil e liquidez do mercado futuro de juros. Adicionalmente foram analisados os modelos teóricos C-CAPM (Consumption-based asset pricing model) e o modelo de consumo habitual desenvolvido por Campbell e Cochrane (1999) com a adaptação proposta por Wachter (2006). Os resultados encontrados no modelo C-CAPM divergiram do esperado, já que a estimativa do coeficiente relativo de aversão ao risco apresentou sinal negativo. Por outro lado, os resultados obtidos no modelo de Wachter (2006) ficaram em linha com o esperado na teoria, tanto em relação à significância dos parâmetros como aos respectivos sinais e magnitudes.

Os impactos da conjuntura macroeconômica sobre o comércio no Brasil: uma análise empírica das grandes varejistas

Os resultados econômico-financeiros das empresas sofrem influência do ambiente macroeconômico no qual elas estão inseridas. Prever com sucesso o desempenho futuro das organizações é um objetivo que motiva gestores, analistas, pesquisadores, credores e investidores. O entendimento das relações entre as variáveis contábeis e macroeconômicas é um poderoso instrumento na formação de expectativas de resultados para as empresas. No presente estudo, selecionamos cinco grandes empresas pertencentes ao setor varejista e cuja atuação é restrita ao mercado interno brasileiro, com o objetivo de desenvolver e testar empiricamente um modelo econométrico que seja robusto o suficiente para prever as vendas futuras das empresas em questão. Considerando que são cinco varejistas bastante diferentes do ponto de vista dos produtos vendidos, que vão de alimentos a bens duráveis, os resultados encontrados mostraram-se proveitosos à medida que comprovaram que as variáveis macroeconômicas não exercem o mesmo grau de influência sobre elas.

O ágio e a Lei 12.793: a independência entre as partes e o valor justo dos ativos

Esta monografia analisa três das principais alterações ao instituto do ágio trazidas pela Lei nº 12.973, de 2014. Estudou-se neste trabalho, especialmente: (i) a alteração na contabilização do ágio; (ii) a obrigatoriedade de elaboração de laudo de avaliação para validade do ágio por perspectiva de rentabilidade futura; e (iii) a necessidade de “não dependência” entre as partes envolvidas na operação. Para elaboração deste estudo foi realizada uma resumida análise histórica do instituto do ágio no Brasil, atentando para os conceitos, critérios e requisitos para o surgimento deste instituto no plano do direito tributário e das ciências contábeis. Concluiu-se que as modificações na contabilização do ágio implementadas pela Lei nº 12.973, de 2014, tendem a diminuir o valor do ágio gerado nas operações de fusões e aquisições e de reorganização societária, reduzindo os incentivos tributários para realização destas operações. Além disso, no tocante à elaboração de laudo de avaliação concluiu-se que a medida garante aos contribuintes maior segurança jurídica, apesar de tornar a operação mais custosa. Por fim, em relação à obrigatoriedade de “não dependência” entre as partes envolvidas na operação, entendeu-se que esta regra extingue a ágio decorrente de operações entre sociedades pertencentes ao mesmo grupo econômico ou entre partes relacionadas. Diante da importância das alterações trazidas com a Lei nº 12.973, de 2014, recomenda-se que a doutrina e a jurisprudência aprofundem os estudos sobre o tema.

Aplicação do modelo de Bakshi-Chen no mercado acionário brasileiro : um modelo dinâmico de precificação de ações

É vasta a literatura em finanças quantitativas sobre o apreçamento de derivativos, porém é bem reduzida em se tratando de ações. Nessa dissertação, procuramos aplicar o modelo de Bakshi-Chen na avaliação de ações listadas na Bovespa. Os inputs do modelo são o lucro por ação, LPA, dos últimos doze meses, a expectativa de crescimento de lucro para os doze meses seguintes (g), e a taxa de juros. Vamos mostrar o ganho de precisão em relação ao modelo de Gordon e avaliar o modelo na prática realizando um backtest para descobrir se o modelo consegue estimar o valor das ações melhor do que os investidores.

Portfolio choice with a correlated background risk : theory and evidence

We extend the static portfolio choice problem with a small background risk to the case of small partially correlated background risks. We show that respecting the theories under which risk substitution appears, except for the independence of background risk, it is perfectly rational for the individual to increase his optimal exposure to portfolio risk when risks are partially negatively correlated. Then, we test empirically the hypothesis of risk substitutability using INSEE data on French households. We find that households respond by increasing their stockholdings in response to the increase in future earnings uncertainty. This conclusion is in contradiction with results obtained in other countries. So, in light of these results, our model provides an explanation to account for the lack of empirical consensus on cross-country tests of risk substitution theory that encompasses and criticises all of them.

Consumption-wealth ratio and expected stock returns: evidence from panel data

This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.