Integration of Electronic Commerce and Enterprise Systems

The necessity of EC (Electronic Commerce) and enterprise systems integration is perceived from the integrated nature of enterprise systems. The proven benefits of EC to provide competitive advantages to the organizations force enterprises to adopt and integrate EC with their enterprise systems. Integration is a complex task to facilitate seamless flow of information and data between different systems within and across enterprises. Different systems have different platforms, thus to integrate systems with different platforms and infrastructures, integration technologies, such as middleware, SOA (Service-Oriented Architecture), ESB (Enterprise Service Bus), JCA (J2EE Connector Architecture), and B2B (Business-to-Business) integration standards are required. Huge software vendors, such as Oracle, IBM, Microsoft, and SAP suggest various solutions to address EC and enterprise systems integration problems. There are limited numbers of literature about the integration of EC and enterprise systems in detail. Most of the studies in this area have focused on the factors which influence the adoption of EC by enterprise or other studies provide limited information about a specific platform or integration methodology in general. Therefore, this thesis is conducted to cover the technical details of EC and enterprise systems integration and covers both the adoption factors and integration solutions. In this study, many literature was reviewed and different solutions were investigated. Different enterprise integration approaches as well as most popular integration technologies were investigated. Moreover, various methodologies of integrating EC and enterprise systems were studied in detail and different solutions were examined. In this study, the influential factors to adopt EC in enterprises were studied based on previous literature and categorized to technical, social, managerial, financial, and human resource factors. Moreover, integration technologies were categorized based on three levels of integration, which are data, application, and process. In addition, different integration approaches were identified and categorized based on their communication and platform. Also, different EC integration solutions were investigated and categorized based on the identified integration approaches. By considering different aspects of integration, this study is a great asset to the architectures, developers, and system integrators in order to integrate and adopt EC with enterprise systems.

Analysis of open CNC architecture for machine tools

The evolution of digital circuit technology, leadind to higher speeds and more reliability allowed the development of machine controllers adapted to new production systems (e.g., Flexible Manufacturing Systems - FMS). Most of the controllers are developed in agreement with the CNC technology of the correspondent machine tool manufacturer. Any alterations or adaptation of their components are not easy to be implemented. The machine designers face up hardware and software restrictions such as lack of interaction among system's elements and impossibility of adding new function. This is due to hardware incompatibility and to software not allowing alterations in the source program. The introduction of open architecture philosophy propitiated the evolution of a new generation of numeric controllers. This brought the conventional CNC technology to the standard IBM - PC microcomputer. As a consequence, the characteristics of the CNC (positioning) and the microcomputer (easy of programming, system configuration, network communication etc) are combined. Some researchers have addressed a flexible structure of software and hardware allowing changes in the hardware basic configuration and all control software levels. In this work, the development of open architecture controllers in the OSACA, OMAC, HOAM-CNC and OSEC architectures is described.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

The effects of maternal hyperglycemia on human umbilical vascular gene expression and neonatal rat lung development

Background: Maternal diabetes affects many fetal organ systems, including the vasculature and the lungs. The offspring of diabetic mothers have respiratory adaptation problems after birth. The mechanisms are multifactorial and the effects are prolonged during the postnatal period. An increasing incidence of diabetic pregnancies accentuates the importance of identifying the pathological mechanisms, which cause the metabolic and genetic changes that occur in offspring, born to diabetic mothers. Aims and methods: The aim of this thesis was to determine changes both in human umbilical cord exposed to maternal type 1 diabetes and in neonatal rat lungs after streptozotocin-induced maternal hyperglycemia, during pregnancy. Rat lungs were used as a model for the potential disease mechanisms. Gene expression alterations were determined in human umbilical cords at birth and in rat pup lungs at two week of age. During the first two postnatal weeks, rat lung development was studied morphologically and histologically. Further, the effect of postnatal hyperoxia on hyperglycemia-primed rat lungs was investigated at one week of age to mimic the clinical situation of supplemental oxygen treatment. Results: In the umbilical cord, maternal diabetes had a major negative effect on the expression of genes involved in blood vessel development. The genes regulating vascular tone were also affected. In neonatal rat lungs, intrauterine hyperglycemia had a prolonged effect on gene expression during late alveolarization. The most affected pathway was the upregulation of extracellular matrix proteins. Newborn rat lungs exposed to intrauterine hyperglycemia had thinner saccular walls without changes in airspace size, a smaller relative lung weight and lung total tissue area, and increased cellular apoptosis and proliferation compared to control lungs, possibly reflecting an aberrant maturational adaptation. At one and two weeks of age, cell proliferation and secondary crest formation were accelerated in hyperglycemia-exposed lungs. Postnatal hyperoxic exposure, alone caused arrested alveolarization with thin-walled and enlarged alveoli. In contrast, the dual exposure of intrauterine hyperglycemia and postnatal hyperoxia resulted in the phenotype of thick septa together with arrested alveolarization and decreased number of small pulmonary arteries. Conclusions: Maternal diabetic environment seems to alter the umbilical cord gene expression profile of the regulation of vascular development and function. Fetal hyperglycemia may additionally affect the genetic regulation of the postnatal lung development and may actually induce prolonged structural alterations in neonatal lungs together with a modifying effect on the deleterious pulmonary exposure of postnatal hyperoxia. This, combined with the novel human umbilical cord gene data could serve as stepping stones for future therapies to curb developmental aberrations.

Cell Model Systems in Characterizing Alpha2-Adrenoceptors as Drug Targets.

The three alpha2-adrenoceptor (alpha2-AR) subtypes belong to the G protein-coupled receptor superfamily and represent potential drug targets. These receptors have many vital physiological functions, but their actions are complex and often oppose each other. Current research is therefore driven towards discovering drugs that selectively interact with a specific subtype. Cell model systems can be used to evaluate a chemical compound's activity in complex biological systems. The aim of this thesis was to optimize and validate cell-based model systems and assays to investigate alpha2-ARs as drug targets. The use of immortalized cell lines as model systems is firmly established but poses several problems, since the protein of interest is expressed in a foreign environment, and thus essential components of receptor regulation or signaling cascades might be missing. Careful cell model validation is thus required; this was exemplified by three different approaches. In cells heterologously expressing alpha2A-ARs, it was noted that the transfection technique affected the test outcome; false negative adenylyl cyclase test results were produced unless a cell population expressing receptors in a homogenous fashion was used. Recombinant alpha2C-ARs in non-neuronal cells were retained inside the cells, and not expressed in the cell membrane, complicating investigation of this receptor subtype. Receptor expression enhancing proteins (REEPs) were found to be neuronalspecific adapter proteins that regulate the processing of the alpha2C-AR, resulting in an increased level of total receptor expression. Current trends call for the use of primary cells endogenously expressing the receptor of interest; therefore, primary human vascular smooth muscle cells (SMC) expressing alpha2-ARs were tested in a functional assay monitoring contractility with a myosin light chain phosphorylation assay. However, these cells were not compatible with this assay due to the loss of differentiation. A rat aortic SMC cell line transfected to express the human alpha2B-AR was adapted for the assay, and it was found that the alpha2-AR agonist, dexmedetomidine, evoked myosin light chain phosphorylation in this model.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Parasitic Order Machine. A Sociology and Ontology of Information Securing

This study examines information security as a process (information securing) in terms of what it does, especially beyond its obvious role of protector. It investigates concepts related to ‘ontology of becoming’, and examines what it is that information securing produces. The research is theory driven and draws upon three fields: sociology (especially actor-network theory), philosophy (especially Gilles Deleuze and Félix Guattari’s concept of ‘machine’, ‘territory’ and ‘becoming’, and Michel Serres’s concept of ‘parasite’), and information systems science (the subject of information security). Social engineering (used here in the sense of breaking into systems through non-technical means) and software cracker groups (groups which remove copy protection systems from software) are analysed as examples of breaches of information security. Firstly, the study finds that information securing is always interruptive: every entity (regardless of whether or not it is malicious) that becomes connected to information security is interrupted. Furthermore, every entity changes, becomes different, as it makes a connection with information security (ontology of becoming). Moreover, information security organizes entities into different territories. However, the territories – the insides and outsides of information systems – are ontologically similar; the only difference is in the order of the territories, not in the ontological status of entities that inhabit the territories. In other words, malicious software is ontologically similar to benign software; they both are users in terms of a system. The difference is based on the order of the system and users: who uses the system and what the system is used for. Secondly, the research shows that information security is always external (in the terms of this study it is a ‘parasite’) to the information system that it protects. Information securing creates and maintains order while simultaneously disrupting the existing order of the system that it protects. For example, in terms of software itself, the implementation of a copy protection system is an entirely external addition. In fact, this parasitic addition makes software different. Thus, information security disrupts that which it is supposed to defend from disruption. Finally, it is asserted that, in its interruption, information security is a connector that creates passages; it connects users to systems while also creating its own threats. For example, copy protection systems invite crackers and information security policies entice social engineers to use and exploit information security techniques in a novel manner.

Antigenic stimulation is more efficient than LPS in inducing nitric oxide production by human mononuclear cells on the in vitro granuloma reaction in schistosomiasis

Nitric oxide (NO) is an extremely important and versatile messenger in biological systems. It has been identified as a cytotoxic factor in the immune system, presenting anti- or pro-inflammatory properties under different circumstances. In murine monocytes and macrophages, stimuli by cytokines or lipopolysaccharide (LPS) are necessary for inducing the immunologic isoform of the enzyme responsible for the high-output production of NO, nitric oxide synthase (iNOS). With respect to human cells, however, LPS seems not to stimulate NO production in the same way. Addressing this issue, we demonstrate here that peripheral blood mononuclear cells (PBMC) obtained from schistosomiasis-infected patients and cultivated with parasite antigens in the in vitro granuloma (IVG) reaction produced more nitrite in the absence of LPS. Thus, LPS-induced nitrite levels are easily detectable, although lower than those detected only with antigenic stimulation. Concomitant addition of LPS and L-N-arginine methyl ester (L-NAME) restored the ability to produce detectable levels of nitrite, which had been lost with L-NAME treatment. In addition, LPS caused a mild decrease of the IVG reaction and its association with L-NAME was responsible for reversal of the L-NAME-exacerbating effect on the IVG reaction. These results show that LPS alone is not as good an NO inducer in human cells as it is in rodent cells or cell lines. Moreover, they provide evidence for interactions between LPS and NO inhibitors that require further investigation.

Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Novel control, haptic and calibration methods for teleoperated electrohydraulic servo systems

The aim of this thesis is to propose a novel control method for teleoperated electrohydraulic servo systems that implements a reliable haptic sense between the human and manipulator interaction, and an ideal position control between the manipulator and the task environment interaction. The proposed method has the characteristics of a universal technique independent of the actual control algorithm and it can be applied with other suitable control methods as a real-time control strategy. The motivation to develop this control method is the necessity for a reliable real-time controller for teleoperated electrohydraulic servo systems that provides highly accurate position control based on joystick inputs with haptic capabilities. The contribution of the research is that the proposed control method combines a directed random search method and a real-time simulation to develop an intelligent controller in which each generation of parameters is tested on-line by the real-time simulator before being applied to the real process. The controller was evaluated on a hydraulic position servo system. The simulator of the hydraulic system was built based on Markov chain Monte Carlo (MCMC) method. A Particle Swarm Optimization algorithm combined with the foraging behavior of E. coli bacteria was utilized as the directed random search engine. The control strategy allows the operator to be plugged into the work environment dynamically and kinetically. This helps to ensure the system has haptic sense with high stability, without abstracting away the dynamics of the hydraulic system. The new control algorithm provides asymptotically exact tracking of both, the position and the contact force. In addition, this research proposes a novel method for re-calibration of multi-axis force/torque sensors. The method makes several improvements to traditional methods. It can be used without dismantling the sensor from its application and it requires smaller number of standard loads for calibration. It is also more cost efficient and faster in comparison to traditional calibration methods. The proposed method was developed in response to re-calibration issues with the force sensors utilized in teleoperated systems. The new approach aimed to avoid dismantling of the sensors from their applications for applying calibration. A major complication with many manipulators is the difficulty accessing them when they operate inside a non-accessible environment; especially if those environments are harsh; such as in radioactive areas. The proposed technique is based on design of experiment methodology. It has been successfully applied to different force/torque sensors and this research presents experimental validation of use of the calibration method with one of the force sensors which method has been applied to.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.

Investigation of cytotoxic and mutagenic effects of Malpighia glabra L. (barbados cherry) fruit pulp and vitamin C on plant and animal test systems

Fruits are important sources of nutrients in human diet, and Barbados Cherry (Malpighia glabra L.) is of particular interest due to its high content of antioxidants. Diets rich in fruits and vegetables protect individuals against diseases and cancer, but excessive intake of vitamins may act as pro-oxidant and generate changes in DNA. To evaluate the effect of different in natura (BAN) and frozen (BAF) Barbados Cherry pulp concentrations and synthetic vitamin C in liquid form (VC) on the chromosome level and the cell cycle division, root meristeme cells of Allium cepa L. and bone marrow cells of Wistar rats Rattus norvegicus, were used as test system. In Allium cepa L., BAN, at the highest concentration (0.4 mg.mL-1) and BAF, at the lowest concentration (0.2 mg.mL-1), inhibited cell division, and there was recovery of cell division after the recovery period in water only for BAN. In the Wistar rats, all treatments with Barbados Cherry, either acute or subchronic, were not cytotoxic or mutagenic; only the highest concentration of VC increased significantly the rate of chromosomal abnormalities. The data obtained are important to reinforce the use of Barbados Cherry fruit in the diet.

Finnish perceptions on management accounting systems: towards an upgraded sophistication model

This study is based on a large survey study of over 1500 Finnish companies’ usage, needs and implementation difficulties of management accounting systems. The study uses quantitative, qualitative and mixed methods to answer the research questions. The empirical data used in the study was gathered through structured interviews with randomly selected companies of varying sizes and industries. The study answers the three research questions by analyzing the characteristics and behaviors of companies working in Finland. The study found five distinctive groups of companies according to the characteristics of their cost information and management accounting system use. The study also showed that the state of cost information and management accounting systems depends on the industry and size of the companies. It was found that over 50% of the companies either did not know how their systems could be updated or saw systems as inadequate. The qualitative side also highlighted the needs for tailored and integrated management accounting systems for creating more value to the managers of companies. The major inhibitors of new system implementation were the lack of both monetary and human resources. Through the use of mixed methods and design science a new and improved sophistication model is created based on previous research results combined with the information gathered from previous literature. The sophistication model shows the different stages of management accounting systems in use and what companies can achieve with the implementation and upgrading of their systems.