Packet backbone design differences between commercial network and Container Trial System of LTE/SAE

The mobile networks of earlier and current generations, or 2G and 3G networks, provide users voice and packet services with higher transmission rates and good quality over the same core network. When developing the next generation of mobile networks the current quality of services needs to be maintained. This thesis concentrates on the next generation mobile network, especially on the evolution of the packet network part. The new mobile network has requirements for the common packet backbone network, Mobile Packet Backbone Network, which is additionally discussed in this study. The next generation mobile network, called LTE/SAE, is currently under testing. The test system is called Container Trial System. It is a mini sized LTE/SAE site. The LTE/SAE is studied in this thesis concentrating on the evolved packet core, the SAE part of the composition. The empirical part of the study compares the LTE/SAE Container Trial System and commercial network designs and additionally produces documentation for internal personnel and customers. The research is performed by comparing the documentations and specifications of both the Container Trial System and commercial network. Since the LTE commercial network is not yet constructed, the comparison is done theoretically. The purpose is furthermore to find out if there are any design issues that could be done differently in the next version of the Container Trial System.

Success factors of customer and supplier master data system

Especially in global enterprises, key data is fragmented in multiple Enterprise Resource Planning (ERP) systems. Thus the data is inconsistent, fragmented and redundant across the various systems. Master Data Management (MDM) is a concept, which creates cross-references between customers, suppliers and business units, and enables corporate hierarchies and structures. The overall goal for MDM is the ability to create an enterprise-wide consistent data model, which enables analyzing and reporting customer and supplier data. The goal of the study was defining the properties and success factors of a master data system. The theoretical background was based on literature and the case consisted of enterprise specific needs and demands. The theoretical part presents the concept, background, and principles of MDM and then the phases of system planning and implementation project. Case consists of background, definition of as is situation, definition of project, evaluation criterions and concludes the key results of the thesis. In the end chapter Conclusions combines common principles with the results of the case. The case part ended up dividing important factors of the system in success factors, technical requirements and business benefits. To clarify the project and find funding for the project, business benefits have to be defined and the realization has to be monitored. The thesis found out six success factors for the MDM system: Well defined business case, data management and monitoring, data models and structures defined and maintained, customer and supplier data governance, delivery and quality, commitment, and continuous communication with business. Technical requirements emerged several times during the thesis and therefore those can’t be ignored in the project. Conclusions chapter goes through these factors on a general level. The success factors and technical requirements are related to the essentials of MDM: Governance, Action and Quality. This chapter could be used as guidance in a master data management project.

Electric-drive-based control and electric energy regeneration in a hydraulic system

Over the recent years, development in mobile working machines has concentrated on reducing emissions owing to the tightening rules and needs to improve energy utilization and reduce power losses. This study focuses on energy utilization and regeneration in an electro-hydraulic forklift, which is a lifting equipment application. The study starts from the modelling and simulation of a hydraulic forklift. The energy regeneration from the potential energy of the load was studied. Also a flow-based electric motor speed control was suggested in this thesis instead of the throttle control method or the variable displacement pump control. Topics related to further development in the future are discussed. Finally, a summary and conclusions are presented.

Design of Pulsed Electroacoustic Measurement System for Space Charge Characterisation

Pulsed electroacoustic (PEA) method is a commonly used non-destructive technique for investigating space charges. It has been developed since early 1980s. These days there is continuing interest for better understanding of the influence of space charge on the reliability of solid electrical insulation under high electric field. The PEA method is widely used for space charge profiling for its robust and relatively inexpensive features. The PEA technique relies on a voltage impulse used to temporarily disturb the space charge equilibrium in a dielectric. The acoustic wave is generated by charge movement in the sample and detected by means of a piezoelectric film. The spatial distribution of the space charge is contained within the detected signal. The principle of such a system is already well established, and several kinds of setups have been constructed for different measurement needs. This thesis presents the design of a PEA measurement system as a systems engineering project. The operating principle and some recent developments are summarised. The steps of electrical and mechanical design of the instrument are discussed. A common procedure for measuring space charges is explained and applied to verify the functionality of the system. The measurement system is provided as an additional basic research tool for the Corporate Research Centre of ABB (China) Ltd. It can be used to characterise flat samples with thickness of 0.2–0.5 mm under DC stress. The spatial resolution of the measurement is 20 μm.

Development of a measuring-control system for energy monitoring in low power

In this thesis a control system for an intelligent low voltage energy grid is presented, focusing on the control system created by using a multi-agent approach which makes it versatile and easy to expand according to the future needs. The control system is capable of forecasting the future energy consumption and decisions making on its own without human interaction when countering problems. The control system is a part of the St. Petersburg State Polytechnic University’s smart grid project that aims to create a smart grid for the university’s own use. The concept of the smart grid is interesting also for the consumers as it brings new possibilities to control own energy consumption and to save money. Smart grids makes it possible to monitor the energy consumption in real-time and to change own habits to save money. The intelligent grid also brings possibilities to integrate the renewable energy sources to the global or the local energy production much better than the current systems. Consumers can also sell their extra power to the global grid if they want.

Pumping system optimization tool

Pumping systems account for over 20 % of all electricity consumption in European industry. Optimization and correct design of such systems is important and there is a reasonable amount of unrealized energy saving potential in old pumping systems. The energy efficiency and therefore also the energy consumption of a pumping system heavily depends on the correct dimensioning and selection of devices. In this work, a graphical optimization tool for pumping systems is developed in Matlab programming language. The tool selects optimal pump, electrical motor and frequency converter for existing pumping process and calculates the life cycle costs of the whole system. The tool could be used as an aid when choosing the machinery and to analyze the energy consumption of existing systems. Results given by the tool are compared to the results of laboratory tests. The selection of pump and motor works reasonably well, but the frequency converter selection still needs development

Chaotic Behaviour of Active Magnetic Bearing System by Time Series Analysis

Chaotic behaviour is one of the hardest problems that can happen in nonlinear dynamical systems with severe nonlinearities. It makes the system's responses unpredictable. It makes the system's responses to behave similar to noise. In some applications it should be avoided. One of the approaches to detect the chaotic behaviour is nding the Lyapunov exponent through examining the dynamical equation of the system. It needs a model of the system. The goal of this study is the diagnosis of chaotic behaviour by just exploring the data (signal) without using any dynamical model of the system. In this work two methods are tested on the time series data collected from AMB (Active Magnetic Bearing) system sensors. The rst method is used to nd the largest Lyapunov exponent by Rosenstein method. The second method is a 0-1 test for identifying chaotic behaviour. These two methods are used to detect if the data is chaotic. By using Rosenstein method it is needed to nd the minimum embedding dimension. To nd the minimum embedding dimension Cao method is used. Cao method does not give just the minimum embedding dimension, it also gives the order of the nonlinear dynamical equation of the system and also it shows how the system's signals are corrupted with noise. At the end of this research a test called runs test is introduced to show that the data is not excessively noisy.

MLTDL - Recommendation system for Digital Libraries

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

Nurses’ Acceptance of an Internet-Based Support System in The Care of Adolescents with Depression

The overall goal of the study was to describe nurses’ acceptance of an Internet-based support system in the care of adolescents with depression. The data were collected in four phases during the period 2006 – 2010 from nurses working in adolescent psychiatric outpatient clinics and from professionals working with adolescents in basic public services. In the first phase, the nurses’ anticipated perceptions of the usefulness of the Internet-based support system before its implementation was explored. In the second phase, the nurses’ perceived ease of computer and Internet use and attitudes toward it were explored. In the third phase, the features of the support system and its implementation process were described. In the fourth phase, the nurses’ experiences of behavioural intention and actual system use of the Internet-based support were described in psychiatric out-patient care after one year use. The Technology Acceptance Model (TAM) was used to structure the various research phases. Several benefits were identified from the nurses’ perspective in using the Internet-based support system in the care of adolescents with depression. The nurses’ technology skills were good and their attitudes towards computer use were positive. The support system was developed in various phases to meet the adolescents’ needs. Before the implementation of the information technology (IT)-based support system, it is important to pay attention to the nurses’ IT-training, technology support, resources, and safety as well as ethical issues related to the support system. After one year of using the system, the nurses perceived the Internet-based support system to be useful in the care of adolescents with depression. The adolescents’ independent work with the support system at home and the program’s systematic character were experienced as conducive from the point of view of the treatment. However, the Internet-based support system was integrated only partly into the nurseadolescent interaction even though the nurses’ perceptions of it were positive. The use of the IT-based system as part of the adolescents’ depression care was seen positively and its benefits were recognized. This serves as a good basis for future IT-based techniques. Successful implementations of IT-based support systems need a systematic implementation plan and commitment from the part of the organization and its managers. Supporting and evaluating the implementation of an IT-based system should pay attention to changing the nurses’ work styles. Health care organizations should be offered more flexible opportunities to utilize IT-based systems in direct patient care in the future.

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

Design, implementation, and evaluation of an online water quality monitoring system in Lake Saimaa, Finland

Environmental threats are growing nowadays, they became global issues. People around the world try to face these issues by two means: solving the current affected environs and preventing non-affected environs. This thesis describes the design, implementation, and evaluation of online water quality monitoring system in Lake Saimaa, Finland. The water quality in Lake Saimaa needs to be monitored in order to provide responsible bodies with valuable information which allows them to act fast in order to prevent any negative impact on the lake's environment. The objectives were to design a suitable system, implement the system in Lake Saimaa, and then to evaluate the applicability and reliability of such systems for this environment. The needs for the system were first isolated, and then the design, needed modifications, and the construction of the system took place. After that was the testing of the system in Lake Saimaa in two locations nearby Mikkeli city. The last step was to evaluate the whole system. The main results were that the application of online water quality monitoring systems in Lake Saimaa can benefit of many advantages such as reducing the required manpower, time and running costs. However, the point of unreliability of the exact measured values of some parameters is still the drawback of such systems which can be developed by using more advanced equipments with more sophisticated features specifically for the purpose of monitoring in the predefined location.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

Forest inventory information needs in Northwest Russia

This thesis applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The thesis recommends strategic options for LiDAR technology’s value enhancement in Russian forestry.

Successful scale-up of human embryonic stem cell production in a stirred microcarrier culture system

Future clinical applications of human embryonic stem (hES) cells will require high-yield culture protocols. Currently, hES cells are mainly cultured in static tissue plates, which offer a limited surface and require repeated sub-culturing. Here we describe a stirred system with commercial dextran-based microcarriers coated with denatured collagen to scale-up hES cell production. Maintenance of pluripotency in the microcarrier-based stirred system was shown by immunocytochemical and flow cytometry analyses for pluripotency-associated markers. The formation of cavitated embryoid bodies expressing markers of endoderm, ectoderm and mesoderm was further evidence of maintenance of differentiation capability. Cell yield per volume of medium spent was more than 2-fold higher than in static plates, resulting in a significant decrease in cultivation costs. A total of 10(8) karyotypically stable hES cells were obtained from a unitary small vessel that needed virtually no manipulation during cell proliferation, decreasing risks of contamination. Spinner flasks are available up to working volumes in the range of several liters. If desired, samples from the homogenous suspension can be withdrawn to allow process validation needed in the last expansion steps prior to transplantation. Especially when thinking about clinical trials involving from dozens to hundreds of patients, the use of a small number of larger spinners instead of hundreds of plates or flasks will be beneficial. To our knowledge, this is the first description of successful scale-up of feeder- and Matrigel™-free production of undifferentiated hES cells under continuous agitation, which makes this system a promising alternative for both therapy and research needs.

Sensor communication in Smart cities and regions: An efficient IoT-based remote health monitoring system

Recent advances in Information and Communication Technology (ICT), especially those related to the Internet of Things (IoT), are facilitating smart regions. Among many services that a smart region can offer, remote health monitoring is a typical application of IoT paradigm. It offers the ability to continuously monitor and collect health-related data from a person, and transmit the data to a remote entity (for example, a healthcare service provider) for further processing and knowledge extraction. An IoT-based remote health monitoring system can be beneficial in rural areas belonging to the smart region where people have limited access to regular healthcare services. The same system can be beneficial in urban areas where hospitals can be overcrowded and where it may take substantial time to avail healthcare. However, this system may generate a large amount of data. In order to realize an efficient IoT-based remote health monitoring system, it is imperative to study the network communication needs of such a system; in particular the bandwidth requirements and the volume of generated data. The thesis studies a commercial product for remote health monitoring in Skellefteå, Sweden. Based on the results obtained via the commercial product, the thesis identified the key network-related requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, the thesis has proposed an architecture called IReHMo - an IoT-based remote health monitoring architecture. This architecture allows users to incorporate several types of IoT devices to extend the sensing capabilities of the system. Using IReHMo, several IoT communication protocols such as HTTP, MQTT and CoAP has been evaluated and compared against each other. Results showed that CoAP is the most efficient protocol to transmit small size healthcare data to the remote servers. The combination of IReHMo and CoAP significantly reduced the required bandwidth as well as the volume of generated data (up to 56 percent) compared to the commercial product. Finally, the thesis conducted a scalability analysis, to determine the feasibility of deploying the combination of IReHMo and CoAP in large numbers in regions in north Sweden.