A distributed, cloud-ready, digital content processing and transformation platform and a specific use case

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

What’s in it for me? Incentivizing the use of institutional repositories

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

Interfirm Information System for Supply Chain Management from the Cloud: An Exploratory Case Study from the Telecom Industry

This study examines the practice of supply chain management problems and the perceived demand information distortion’s (the bullwhip effect) reduction with the interfirm information system, which is delivered as a cloud service to a company operating in the telecommunications industry. The purpose is to shed light in practice that do the interfirm information system have impact on the performance of the supply chain and in particularly the reduction of bullwhip effect. In addition, a holistic case study of the global telecommunications company's supply chain is presented and also the challenges it’s facing, and this study also proposes some measures to improve the situation. The theoretical part consists of the supply chain and its management, as well as increasing the efficiency and introducing the theories and related previous research. In addition, study presents performance metrics for the bullwhip effect detection and tracking. The theoretical part ends in presenting cloud -based business intelligence theoretical framework used in the background of this study. The research strategy is a qualitative case study, supported by quantitative data, which is collected from a telecommunication sector company's databases. Qualitative data were gathered mainly with two open interviews and the e-mail exchange during the development project. In addition, other materials from the company were collected during the project and the company's web site information was also used as the source. The data was collected to a specific case study database in order to increase reliability. The results show that the bullwhip effect can be reduced with the interfirm information system and with the use of CPFR and S&OP models and in particularly combining them to an integrated business planning. According to this study the interfirm information system does not, however, solve all of the supply chain and their effectiveness -related problems, because also the company’s processes and human activities have a major impact.

Simulation of wind powered hydraulic heating system

The objective of this master’s thesis was to design and simulate a wind powered hydraulic heating system that can operate independently in remote places where the use of electricity is not possible. Components for the system were to be selected in such a way that the conditions for manufacture, use and economic viability are the as good as possible. Savonius rotor was chosen for wind turbine, due to its low cut in speed and robust design. Savonius rotor produces kinetic energy in wide wind speed range and it can withstand high wind gusts. Radial piston pump was chosen for the flow source of the hydraulic heater. Pump type was selected due to its characteristics in low rotation speeds and high efficiency. Volume flow from the pump is passed through the throttle orifice. Pressure drop over the orifice causes the hydraulic oil to heat up and, thus, creating thermal energy. Thermal energy in the oil is led to radiator where it conducts heat to the environment. The hydraulic heating system was simulated. For this purpose a mathematical models of chosen components were created. In simulation wind data gathered by Finnish meteorological institute for 167 hours was used as input. The highest produced power was achieved by changing the orifice diameter so that the rotor tip speed ratio follows the power curve. This is not possible to achieve without using electricity. Thus, for the orifice diameter only one, the optimal value was defined. Results from the simulation were compared with investment calculations. Different parameters effecting the investment profitability were altered in sensitivity analyses in order to define the points of investment profitability. Investment was found to be profitable only with high average wind speeds.

JNK regulates dendrite and spine architecture in the central nervous system influencing spatial learning and motor tasks

JNK1 is a MAP-kinase that has proven a significant player in the central nervous system. It regulates brain development and the maintenance of dendrites and axons. Several novel phosphorylation targets of JNK1 were identified in a screen performed in the Coffey lab. These proteins were mainly involved in the regulation of neuronal cytoskeleton, influencing the dynamics and stability of microtubules and actin. These structural proteins form the dynamic backbone for the elaborate architecture of the dendritic tree of a neuron. The initiation and branching of the dendrites requires a dynamic interplay between the cytoskeletal building blocks. Both microtubules and actin are decorated by associated proteins which regulate their dynamics. The dendrite-specific, high molecular weight microtubule associated protein 2 (MAP2) is an abundant protein in the brain, the binding of which stabilizes microtubules and influences their bundling. Its expression in non-neuronal cells induces the formation of neurite-like processes from the cell body, and its function is highly regulated by phosphorylation. JNK1 was shown to phosphorylate the proline-rich domain of MAP2 in vivo in a previous study performed in the group. Here we verify three threonine residues (T1619, T1622 and T1625) as JNK1 targets, the phosphorylation of which increases the binding of MAP2 to microtubules. This binding stabilizes the microtubules and increases process formation in non-neuronal cells. Phosphorylation-site mutants were engineered in the lab. The non-phosphorylatable mutant of MAP2 (MAP2- T1619A, T1622A, T1625A) in these residues fails to bind microtubules, while the pseudo-phosphorylated form, MAP2- T1619D, T1622D, Thr1625D, efficiently binds and induces process formation even without the presence of active JNK1. Ectopic expression of the MAP2- T1619D, T1622D, Thr1625D in vivo in mouse brain led to a striking increase in the branching of cortical layer 2/3 (L2/3) pyramidal neurons, compared to MAP2-WT. The dendritic complexity defines the receptive field of a neuron and dictates the output to the postsynaptic cells. Previous studies in the group indicated altered dendrite architecture of the pyramidal neurons in the Jnk1-/- mouse motor cortex. Here, we used Lucifer Yellow loading and Sholl analysis of neurons in order to study the dendritic branching in more detail. We report a striking, opposing effect in the absence of Jnk1 in the cortical layers 2/3 and 5 of the primary motor cortex. The basal dendrites of pyramidal neurons close to the pial surface at L2/3 show a reduced complexity. In contrast, the L5 neurons, which receive massive input from the L2/3 neurons, show greatly increased branching. Another novel substrate identified for JNK1 was MARCKSL1, a protein that regulates actin dynamics. It is highly expressed in neurons, but also in various cancer tissues. Three phosphorylation target residues for JNK1 were identified, and it was demonstrated that their phosphorylation reduces actin turnover and retards migration of these cells. Actin is the main cytoskeletal component in dendritic spines, the site of most excitatory synapses in pyramidal neurons. The density and gross morphology of the Lucifer Yellow filled dendrites were characterized and we show reduced density and altered morphology of spines in the motor cortex and in the hippocampal area CA3. The dynamic dendritic spines are widely considered to function as the cellular correlate during learning. We used a Morris water maze to test spatial memory. Here, the wild-type mice outperformed the knock-out mice during the acquisition phase of the experiment indicating impaired special memory. The L5 pyramidal neurons of the motor cortex project to the spinal cord and regulate the movement of distinct muscle groups. Thus the altered dendrite morphology in the motor cortex was expected to have an effect on the input-output balance in the signaling from the cortex to the lower motor circuits. A battery of behavioral tests were conducted for the wild-type and Jnk1-/- mice, and the knock-outs performed poorly compared to wild-type mice in tests assessing balance and fine motor movements. This study expands our knowledge of JNK1 as an important regulator of the dendritic fields of neurons and their manifestations in behavior.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

Control of a line robot system with Embedded Linux

Many, if not all, aspects of our everyday lives are related to computers and control. Microprocessors and wireless communications are involved in our lives. Embedded systems are an attracting field because they combine three key factors, small size, low power consumption and high computing capabilities. The aim of this thesis is to study how Linux communicates with the hardware, to answer the question if it is possible to use an operating system like Debian for embedded systems and finally, to build a Mechatronic real time application. In the thesis a presentation of Linux and the Xenomai real time patch is given, the bootloader and communication with the hardware is analyzed. BeagleBone the evaluation board is presented along with the application project consisted of a robot cart with a driver circuit, a line sensor reading a black line and two Xbee antennas. It makes use of Xenomai threads, the real time kernel. According to the obtained results, Linux is able to operate as a real time operating system. The issue of future research is the area of embedded Linux is also discussed.

Metrics for Predicting User Behavior and Experience in an Interactive Storytelling System

In much of the previous research into the field of interactive storytelling, the focus has been on the creation of complete systems, then evaluating the performance of those systems based on user experience. Less focus has been placed on finding general solutions to problems that manifest in many different types of interactive storytelling systems. The goal of this thesis was to identify potential candidates for metrics that a system could use to predict player behavior or how players experience the story they are presented with, and to put these metrics to an empirical test. The three metrics that were used were morality, relationships and conflict. The game used for user testing of the metrics, Regicide is an interactive storytelling experience that was created in conjunction with Eero Itkonen. Data, in the forms of internal system data and survey answers, collected through user testing, was used to evaluate hypotheses for each metric. Out of the three chosen metrics, morality performed the best in this study. Though further research and refinement may be required, the results were promising, and point to the conclusion that user responses to questions of morality are a strong predictor for their choices in similar situations later on in the course of an interactive story. A similar examination for user relationships with other characters in the story did not produce promising results, but several problems were recognized in terms of methodology and further research with a better optimized system may yield different results. On the subject of conflict, several aspects, proposed by Ware et al. (2012), were evaluated separately. Results were inconclusive, with the aspect of directness showing the most promise.

The role of nuclear and other conventional power plants in the flexible energy system

This thesis reviews the role of nuclear and conventional power plants in the future energy system. The review is done by utilizing freely accesible publications in addition to generating load duration and ramping curves for Nordic energy system. As the aim of the future energy system is to reduce GHG-emissions and avoid further global warming, the need for flexible power generation increases with the increased share of intermittent renewables. The goal of this thesis is to offer extensive understanding of possibilities and restrictions that nuclear power and conventional power plants have regarding flexible and sustainable generation. As a conclusion, nuclear power is the only technology that is able to provide large scale GHG-free power output variations with good ramping values. Most of the currently operating plants are able to take part in load following as the requirement to do so is already required to be included in the plant design. Load duration and ramping curves produced prove that nuclear power is able to cover most of the annual generation variation and ramping needs in the Nordic energy system. From the conventional power generation methods, only biomass combustion can be considered GHG-free because biomass is considered carbon neutral. CFB combusted biomass has good load follow capabilities in good ramping and turndown ratios. All the other conventional power generation technologies generate GHG-emissions and therefore the use of these technologies should be reduced.

Optimization of Transportation System by Tailored Logistics Network: A Case Study in Automotive Industry

This thesis aims to redesign the supply chain system in an automotive industry in order to obtain space reduction in the inventory by using tailored logistics network. The redesigning process by tailored supply chain will combine all possible shipment methods including direct shipment, milk-run, milk-run via distribution center and Kanban delivery. The current supply chain system in Nissan goes rather well when the production volume is in moderate level. However, when the production volume is high, there is a capacity problem in the warehouse to accommodate all delivered parts from suppliers. Hence, the optimization of supply chain system is needed in order to obtain efficient logistics process and effective inventory consumption. The study will use primary data for both qualitative and quantitative approach as the research methods. Qualitative data will be collected by conducting interviews with people related to procurement and inventory control. Quantitative data consists of list of suppliers with their condition in several parameters which will be evaluated and analyzed by using scoring method to assign the most suitable transportation network to each suppliers for improvement of inventory reduction in a cost efficient manner.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

The Role of HR Management in the Corporate Matrix System

The successful performance of company in the market relates to the quality management of human capital aiming to improve the company's internal performance and external implementation of the core business strategy. Companies with matrix structure focusing on realization and development of innovation and technologies for the uncertain market need to select thoroughly the approach to HR management system. Human resource management has a significant impact on the organization and use a variety of instruments such as corporate information systems to fulfill their functions and objectives. There are three approaches to strategic control management depending on major impact on the major interference in employee decision-making, development of skills and his integration into the business strategy. The mainstream research has focus only on the framework of strategic planning of HR and general productivity of firm, but not on features of organizational structure and corporate software capabilities for human capital. This study tackles the before mentioned challenges, typical for matrix organization, by using the HR control management tools and corporate information system. The detailed analysis of industry producing and selling electromotor and heating equipment in this master thesis provides the opportunity to improve system for HR control and displays its application in the ERP software. The results emphasize the sustainable role of matrix HR input control for creating of independent project teams for matrix structure who are able to respond to various uncertainties of the market and use their skills for improving performance. Corporate information systems can be integrated into input control system by means of output monitoring to regulate and evaluate the processes of teams, using key performance indicators and reporting systems.

Development of a New Welding Product Quality Control and Management System Model for China

The Chinese welding industry is growing every year due to rapid development of the Chinese economy. Increasingly, companies around the world are looking to use Chinese enterprises as their cooperation partners. However, the Chinese welding industry also has its weaknesses, such as relatively low quality and weak management. A modern, advanced welding management system appropriate for local socio-economic conditions is required to enable Chinese enterprises to enhance further their business development. The thesis researches the design and implementation of a new welding quality management system for China. This new system is called ‗welding production quality control management model in China‘ (WQMC). Constructed on the basis of analysis of a survey and in-company interviews, the welding management system comprises the following different elements and perspectives: a ‗Localized congenital existing problem resolution strategies‘ (LCEPRS) database, a ‗human factor designed training system‘ (HFDT) training strategy, the theory of modular design, ISO 3834 requirements, total welding management (TWM), and lean manufacturing (LEAN) theory. The methods used in the research are literature review, questionnaires, interviews, and the author‘s model design experiences and observations, i.e. the approach is primarily qualitative and phenomenological. The thesis describes the design and implementation of a HFDT strategy in Chinese welding companies. Such training is an effective way to increase employees‘ awareness of quality and issues associated with quality assurance. The study identified widely existing problems in the Chinese welding industry and constructed a LCEPRS database that can be used in efforts to mitigate and avoid common problems. The work uses the theory of modular design, TWM and LEAN as tools for the implementation of the WQMC system.