A platform for assessing the current state of data repositories in Korea, Japan and China

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Novel virtual environment and real-time simulation based methods for improving life-cycle efficiency of non-road mobile machinery

Virtual environments and real-time simulators (VERS) are becoming more and more important tools in research and development (R&D) process of non-road mobile machinery (NRMM). The virtual prototyping techniques enable faster and more cost-efficient development of machines compared to use of real life prototypes. High energy efficiency has become an important topic in the world of NRMM because of environmental and economic demands. The objective of this thesis is to develop VERS based methods for research and development of NRMM. A process using VERS for assessing effects of human operators on the life-cycle efficiency of NRMM was developed. Human in the loop simulations are ran using an underground mining loader to study the developed process. The simulations were ran in the virtual environment of the Laboratory of Intelligent Machines of Lappeenranta University of Technology. A physically adequate real-time simulation model of NRMM was shown to be reliable and cost effective in testing of hardware components by the means of hardware-in-the-loop (HIL) simulations. A control interface connecting integrated electro-hydraulic energy converter (IEHEC) with virtual simulation model of log crane was developed. IEHEC consists of a hydraulic pump-motor and an integrated electrical permanent magnet synchronous motorgenerator. The results show that state of the art real-time NRMM simulators are capable to solve factors related to energy consumption and productivity of the NRMM. A significant variation between the test drivers is found. The results show that VERS can be used for assessing human effects on the life-cycle efficiency of NRMM. HIL simulation responses compared to that achieved with conventional simulation method demonstrate the advances and drawbacks of various possible interfaces between the simulator and hardware part of the system under study. Novel ideas for arranging the interface are successfully tested and compared with the more traditional one. The proposed process for assessing the effects of operators on the life-cycle efficiency will be applied for wider group of operators in the future. Driving styles of the operators can be analysed statistically from sufficient large result data. The statistical analysis can find the most life-cycle efficient driving style for the specific environment and machinery. The proposed control interface for HIL simulation need to be further studied. The robustness and the adaptation of the interface in different situations must be verified. The future work will also include studying the suitability of the IEHEC for different working machines using the proposed HIL simulation method.

Absence of hepatitis B virus DNA in patients with hepatitis C and non-A-E hepatitis in the State of São Paulo, Brazil

Occult hepatitis B virus (HBV) infection has been reported as cases in which HBV DNA was detected despite the absence of any HBV serological markers or in cases in which anti-HBc antibody was the sole marker. The aim of the present study was to determine, using the polymerase chain reaction (PCR), whether HBV infection occurs in hepatitis C and non-A-E hepatitis patients without serological evidence of hepatitis B infection in São Paulo State. Two different populations were analyzed: 1) non-A-E hepatitis patients, including 12 patients with acute and 50 patients with chronic hepatic disorders without serological evidence of infection with known hepatitis viruses; 2) 43 patients previously diagnosed as hepatitis C with positive results for anti-HCV and HCV RNA. Among hepatitis C patients, anti-HBc was detected in 18.6% of the subjects. Three different sets of primers were employed for HBV DNA detection by nested PCR, covering different HBV genes: C, S and X. HBV-DNA was not detected in any sample, whereas the positive controls did produce signals. The lack of HBV DNA detection with these pairs of primers could be due to a very low viral load or to the presence of mutations in their annealing sites. The latter is unlikely as these primers were screened against an extensive dataset of HBV sequences. The development of more sensitive methods, such as real time PCR, to detect circular covalent closed DNA is necessary in order to evaluate this question since previous studies have shown that cryptic hepatitis B might occur.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Fuzzy real option analysis in patent related decision making and patent valuation

The shift towards a knowledge-based economy has inevitably prompted the evolution of patent exploitation. Nowadays, patent is more than just a prevention tool for a company to block its competitors from developing rival technologies, but lies at the very heart of its strategy for value creation and is therefore strategically exploited for economic pro t and competitive advantage. Along with the evolution of patent exploitation, the demand for reliable and systematic patent valuation has also reached an unprecedented level. However, most of the quantitative approaches in use to assess patent could arguably fall into four categories and they are based solely on the conventional discounted cash flow analysis, whose usability and reliability in the context of patent valuation are greatly limited by five practical issues: the market illiquidity, the poor data availability, discriminatory cash-flow estimations, and its incapability to account for changing risk and managerial flexibility. This dissertation attempts to overcome these impeding barriers by rationalizing the use of two techniques, namely fuzzy set theory (aiming at the first three issues) and real option analysis (aiming at the last two). It commences with an investigation into the nature of the uncertainties inherent in patent cash flow estimation and claims that two levels of uncertainties must be properly accounted for. Further investigation reveals that both levels of uncertainties fall under the categorization of subjective uncertainty, which differs from objective uncertainty originating from inherent randomness in that uncertainties labelled as subjective are highly related to the behavioural aspects of decision making and are usually witnessed whenever human judgement, evaluation or reasoning is crucial to the system under consideration and there exists a lack of complete knowledge on its variables. Having clarified their nature, the application of fuzzy set theory in modelling patent-related uncertain quantities is effortlessly justified. The application of real option analysis to patent valuation is prompted by the fact that both patent application process and the subsequent patent exploitation (or commercialization) are subject to a wide range of decisions at multiple successive stages. In other words, both patent applicants and patentees are faced with a large variety of courses of action as to how their patent applications and granted patents can be managed. Since they have the right to run their projects actively, this flexibility has value and thus must be properly accounted for. Accordingly, an explicit identification of the types of managerial flexibility inherent in patent-related decision making problems and in patent valuation, and a discussion on how they could be interpreted in terms of real options are provided in this dissertation. Additionally, the use of the proposed techniques in practical applications is demonstrated by three fuzzy real option analysis based models. In particular, the pay-of method and the extended fuzzy Black-Scholes model are employed to investigate the profitability of a patent application project for a new process for the preparation of a gypsum-fibre composite and to justify the subsequent patent commercialization decision, respectively; a fuzzy binomial model is designed to reveal the economic potential of a patent licensing opportunity.

Households’ willingness to engage in demand response in the Finnish retail electricity market: an empirical study

If electricity users adjusted their consumption patterns according to time-variable electricity prices or other signals about the state of the power system, generation and network assets could be used more efficiently, and matching intermittent renewable power generation with electricity demand would be facilitated. This kind of adjustment of electricity consumption, or demand response, may be based on consumers’ decisions to shift or reduce electricity use in response to time-variable electricity prices or on the remote control of consumers’ electric appliances. However, while demand response is suggested as a solution to many issues in power systems, actual experiences from demand response programs with residential customers are mainly limited to short pilots with a small number of voluntary participants, and information about what kinds of changes consumers are willing and able to make and what motivates these changes is scarce. This doctoral dissertation contributes to the knowledge about what kinds of factors impact on residential consumers’ willingness and ability to take part in demand response. Saving opportunities calculated with actual price data from the Finnish retail electricity market are compared with the occurred supplier switching to generate a first estimate about how large savings could trigger action also in the case of demand response. Residential consumers’ motives to participate in demand response are also studied by a web-based survey with 2103 responses. Further, experiences of households with electricity consumption monitoring systems are discussed to increase knowledge about consumers’ interest in getting more information on their electricity use and adjusting their behavior based on it. Impacts of information on willingness to participate in demand response programs are also approached by a survey for experts of their willingness to engage in demand response activities. Residential customers seem ready to allow remote control of electric appliances that does not require changes in their everyday routines. Based on residents’ own activity, the electricity consuming activities that are considered shiftable are very limited. In both cases, the savings in electricity costs required to allow remote control or to engage in demand response activities are relatively high. Nonmonetary incentives appeal to fewer households.

Quality of propolis commercialized in the informal market

The purpose of this research was to evaluate the quality of propolis produced and commercialized informally in São Paulo State through physicochemical analyses of ethanolic extracts of propolis (EEP). Thus, 40 samples of in nature propolis, provided by beekeepers from 32 towns, were analyzed. The EEP were prepared in a proportion of 30% (w/v), and the physicochemical tests were performed according to the Technical Regulation of Propolis Identity and Quality. The pH of each EEP sample was also evaluated. Regarding the dry extract, it was observed that 80% of the samples meet the minimum requirements established by the Brazilian legislation. With regard to the oxidizing property, 67.5% of EEP were below the maximum time allowed for oxidation. With regard to the solubility in lead acetate, 97.5% of the samples showed positive results, whereas no sample produced a negative result in terms of solubility in sodium hydroxide. Regarding the concentration of flavonoids, 95% of the samples produced results consistent with the minimum value allowed, and regarding the phenolic compounds, all samples were in accordance with the legislation. The EEP pH was slightly acidic. Therefore, it can be concluded that most EEP is consistently in accordance with the Brazilian legislation, which suggests that good quality propolis is produced by those beekeepers.

Detection of genetically modified organisms in soy products sold in Turkish market

PCR-based technique for GMO detection is the most reliable choice because of its high sensitivity and specificity. As a candidate of the European Union, Turkey must comply with the rules for launching into the market, traceability, and labeling of GMOs as established by EU legislation. Therefore, the objective of this study is to assess soybean products in the Turkish market to verify compliance with legislation using qualitative Polymerase Chain Reaction (PCR) assay to detect the presence of GM soybean and to quantify its amount of GM soybean in the samples tested positive using real-time PCR. DNA extracted by the modified CTAB method was properly used for PCR amplification of food materials. The amplification of a 118 bp DNA fragment of the lectin gene from soybean by PCR was successfully achieved in all samples. The GMO screening was based on the detection of 35S promoter and NOS terminator sequences. The GM positive samples were subjected to detection of Roundup ReadyTM soybean (RR) using quantitative real-time PCR. It was found that 100% of the tested food samples contained less than 0.1 per cent of EPSPS gene.

Manufacturing real wages in Mexico

In this paper we analyse the recent evolution and determinants of real wages in Mexico’s manufacturing sector, using theories based on the assumption of imperfect competition both in the product and in the labour markets, especially wage-bargain theory, insider-outsider and mark-up models. We show evidence that the Mexican labour market does not behave as a traditional competitive market. The proposed explanation for this fact is that some workers benefit from advantages when compared with others, so that they can get a greater share of the proceedings of the productive process. Also, we find that changes in the degree of competition in the market for output influence the behaviour of real wages.

Computational Market Dynamics of Virtual Economies

The last two decades have provided a vast opportunity to live and explore the compulsive imaginary world or virtual world through massively multiplayer online role-playing games (MMORPGs). MMORPG gives a wide range of opportunities to its users to participate with multi-players on the same platform, to communicate and to do real time actions. There is a virtual economy in these games which is largely player-driven. In-game currency provides its users to build up their Avatars, to buy or sell the necessary goods to play, survive in the games and so on. As a part of virtual economies generated through EVE Online, this thesis mainly focuses on how the prices of the minerals in EVE Online behave by applying the Jabłonska- Capasso-Morale (JCM) mathematical simulation model. It is to verify up to what degree the model can reproduce the virtual economy behavior. The model is applied to buy and sell prices of two minerals namely, isogen and morphite. The simulation results demonstrate that JCM model ts reasonably well to the mineral prices, which lets us conclude that virtual economies behave similarly to the real ones.

The Dutch disease and its neutralization: a Ricardian approach

The Dutch disease is a major market failure originated in the existence of cheap and abundant natural or human resources that keep overvalued the currency of a country for an undetermined period of time, thus turning non profitable the production of tradable goods using technology in the state-of-the-art. It is an obstacle to growth on the demand side, because it limits investment opportunities. The severity of the Dutch disease varies according to the extent of the Ricardian rents involved, i.e., according to the difference between two exchange rate equilibriums: the ‘current’ or market rate and the ‘industrial’ rate - the one that make viable efficient tradable industries. Its main symptoms, besides overvalued currency, are low rates of growth of the manufacturing industry, artificially high real wages, and unemployment. Its neutralization requires managing the exchange rate. The principal instrument for that is a sales or export tax on the commodities that give origin to the Dutch disease. In order to neutralize it policymakers face major political obstacles since it involves taxing exports and reducing wages. Finally, this papers argues that there is an extended concept of Dutch disease: besides having its origin in natural resources, it may arise from cheap labor provided that the ‘wage spread’ in the developing country is considerably larger than in the developed one - a condition that is usually present.

What is the current state of cloud service research and its promise for the future? A systematic literature review

The information technology (IT) industry has recently witnessed the proliferation of cloud services, which have allowed IT service providers to deliver on-demand resources to customers over the Internet. This frees both service providers and consumers from traditional IT-related burdens such as capital and operating expenses and allows them to respond rapidly to new opportunities in the market. Due to the popularity and growth of cloud services, numerous researchers have conducted studies on various aspects of cloud services, both positive and negative. However, none of those studies have connected all relevant information to provide a holistic picture of the current state of cloud service research. This study aims to investigate that current situation and propose the most promising future directions. In order to determine achieve these goals, a systematic literature review was conducted on studies with a primary focus on cloud services. Based on carefully crafted inclusion criteria, 52 articles from highly credible online sources were selected for the review. To define the main focus of the review and facilitate the analysis of literature, a conceptual framework with five main factors was proposed. The selected articles were organized under the factors of the proposed framework and then synthesized using a narrative technique. The results of this systematic review indicate that the impacts of cloud services on enterprises were the factor best covered by contemporary research. Researchers were able to present valuable findings about how cloud services impact various aspects of enterprises such as governance, performance, and security. By contrast, the role of service provider sub-contractors in the cloud service market remains largely uninvestigated, as do cloud-based enterprise software and cloud-based office systems for consumers. Moreover, the results also show that researchers should pay more attention to the integration of cloud services into legacy IT systems to facilitate the adoption of cloud services by enterprise users. After the literature synthesis, the present study proposed several promising directions for cloud service research by outlining research questions for the underexplored areas of cloud services, in order to facilitate the development of cloud service markets in the future.

The new international financial crisis: causes, consequences and perspectives

The paper investigates the recent financial crisis within a historical and comparative perspective having in mind that it is ultimately a confidence crisis, initially associated to a chain of high risk loans and financial innovations that spread thorough the international system culminating with impressive wealth losses. The financial market will eventually recover from the crisis but the outcome should be followed by a different and more disciplined set of international institutions. There will be a change on how we perceive the widespread liberal argument that the market is always efficient, or at least, more efficient than any State intervention, overcoming the false perception that the State is in opposition to the market. A deep financial crisis brings out a period of wealth losses and an adjustment process characterized by price corrections (commodities and equity price deflation) and real effects (recession and lower employment), and a period of turbulences and end of illusions is in place.