45 resultados para model-based reasoning processes


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In this Thesis the interaction of an electromagnetic field and matter is studied from various aspects in the general framework of cold atoms. Our subjects cover a wide spectrum of phenomena ranging from semiclassical few-level models to fully quantum mechanical interaction with structured reservoirs leading to non-Markovian open quantum system dynamics. Within closed quantum systems, we propose a selective method to manipulate the motional state of atoms in a time-dependent double-well potential and interpret the method in terms of adiabatic processes. Also, we derive a simple wave-packet model, based on distributions of generalized eigenstates, explaining the finite visibility of interference in overlapping continuous-wave atom lasers. In the context of open quantum systems, we develop an unraveling of non-Markovian dynamics in terms of piecewise deterministic quantum jump processes confined in the Hilbert space of the reduced system - the non-Markovian quantum jump method. As examples, we apply it for simple 2- and 3-level systems interacting with a structured reservoir. Also, in the context of ion-cavity QED we study the entanglement generation based on collective Dicke modes in experimentally realistic conditions including photonic losses and an atomic spontaneous decay.

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Traditionally limestone has been used for the flue gas desulfurization in fluidized bed combustion. Recently, several studies have been carried out to examine the use of limestone in applications which enable the removal of carbon dioxide from the combustion gases, such as calcium looping technology and oxy-fuel combustion. In these processes interlinked limestone reactions occur but the reaction mechanisms and kinetics are not yet fully understood. To examine these phenomena, analytical and numerical models have been created. In this work, the limestone reactions were studied with aid of one-dimensional numerical particle model. The model describes a single limestone particle in the process as a function of time, the progress of the reactions and the mass and energy transfer in the particle. The model-based results were compared with experimental laboratory scale BFB results. It was observed that by increasing the temperature from 850 °C to 950 °C the calcination was enhanced but the sulfate conversion was no more improved. A higher sulfur dioxide concentration accelerated the sulfation reaction and based on the modeling, the sulfation is first order with respect to SO2. The reaction order of O2 seems to become zero at high oxygen concentrations.

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Tässä tutkimuksessa käsitellään teollisuuden palveluliiketoimintaa. Yritykset ovat perinteisesti saavuttaneet kilpailuetua markkinoilla tuottamalla teknisesti innovatiivisia koneita ja laitteita, mutta viime vuosien aikana yritykset ovat havainneet tarpeen myös palveluliiketoiminnan kehitykselle. Kohdeyrityksenä on teollisuudelle korkealuokkaisia mittalaitteita kehittävä ja valmistava yritys. Tutkimuksen tarkoituksena oli kehittää uusi innovatiivinen vuokraukseen perustuva palveluliiketoimintamalli perinteisen hankinnan sijaan. Olennaisena osana uuteen palveluliiketoimintamalliin liittyi myös tuotteen elinkaarikustannusten selvittäminen ja laskeminen. Toisena tutkimuksen kohteena oli selvittää semi-kvalitatiivisen kyselytutkimuksen avulla, miten yrityksen asiakkaat ja henkilökunta näkevät palveluiden tuottamisen nykytilan ja mitä haasteita palveluliiketoimintaan siirtyminen aiheuttaa organisaatiolle. Työn teoriaosuudessa käsiteltiin palveluliiketoimintaa eri näkökulmista, palvelun laadun muodostumista sekä uuden liiketoimintamallin kehittämistä Osterwalderin Canvas mallin avulla. Lisäksi käsiteltiin elin-kaarilaskennan soveltamista palveluliiketoiminnassa sekä eri investointimalleja teollisiin palveluihin. Kyselytutkimuksen tulosten perusteella asiakkaiden ja yrityksen henkilökunnan näkemykset erosivat palvelun laadun ja prosessien nykytilasta. Asiakkaat arvostivat palvelut paremmalle tasolle kuin henkilökunta. Tulosten perusteella yrityksen olisi kohdennettava resursseja sisäisten prosessien parantamiseen ja kehitettävä organisaatiota enemmän palveluorientoituneeksi. Tuotteen elinkaarikustannukset onnistuttiin selvittämään hyvin ja niiden avulla pystyttiin luomaan sekä yritykselle kannattava että asiakkaille houkutteleva palveluliiketoimintamalli, jonka avulla yrityksen on mahdollista palvella asiakkaitaan entistä paremmin.

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Teollisuuden palvelut tuottavat tulevaisuudessa yhä suuremman osan yritysten liikevaihdosta ja tämän vuoksi niiden systemaattinen kehittäminen yrityksessä on erityisen tärkeää. Tutkimuksen tavoitteena on luoda teorian pohjalta malli, jonka avulla mekatroniikkaklusterin yritykset voivat analysoida tarjottavia palveluitaan asiakkaan näkökulmasta. Tutkimuksessa pyritään myös selvittämään empiirisesti mallin soveltuvuus palvelutarjonnan kehittämiseen tutkimuksessa mukana oleville erikokoisille yrityksille. Tutkimuksen teoreettisessa osassa luodaan katsaus yrityksen kasvustrategioihin. Palveluiden innovaatio- sekä kehitysprosessit käydään lyhyesti läpi, sekä esitetään lähtökohtia, miten yritykset voivat siirtyä tuotetarjoajasta palveluntarjoajaksi. Teoriaosassa käydään läpi QFD -malli, jota voidaan käyttää hyödyksi kun analysoidaan asiakkaan palvelutarpeita ja priorisoidaan yrityksen resursseja. QFD -mallin lisäksi esitellään myös muita laatutyökaluja sekä asiakkaan tarpeiden selvitysmenetelmiä, joita yritys voi käyttää hyödykseen QFD -mallin kanssa. Synteesiosassa esitellään ensin MS Excel -pohjainen QFD -malli. Mallin käyttö-kokeilu toteutetaan työpaja tyylisessä kokouksessa, ja tutkimustulokset kerätään havainnoimalla, teemahaastattelulla sekä kyselyn avulla.

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This dissertation examines knowledge and industrial knowledge creation processes. It looks at the way knowledge is created in industrial processes based on data, which is transformed into information and finally into knowledge. In the context of this dissertation the main tool for industrial knowledge creation are different statistical methods. This dissertation strives to define industrial statistics. This is done using an expert opinion survey, which was sent to a number of industrial statisticians. The survey was conducted to create a definition for this field of applied statistics and to demonstrate the wide applicability of statistical methods to industrial problems. In this part of the dissertation, traditional methods of industrial statistics are introduced. As industrial statistics are the main tool for knowledge creation, the basics of statistical decision making and statistical modeling are also included. The widely known Data Information Knowledge Wisdom (DIKW) hierarchy serves as a theoretical background for this dissertation. The way that data is transformed into information, information into knowledge and knowledge finally into wisdom is used as a theoretical frame of reference. Some scholars have, however, criticized the DIKW model. Based on these different perceptions of the knowledge creation process, a new knowledge creation process, based on statistical methods is proposed. In the context of this dissertation, the data is a source of knowledge in industrial processes. Because of this, the mathematical categorization of data into continuous and discrete types is explained. Different methods for gathering data from processes are clarified as well. There are two methods for data gathering in this dissertation: survey methods and measurements. The enclosed publications provide an example of the wide applicability of statistical methods in industry. In these publications data is gathered using surveys and measurements. Enclosed publications have been chosen so that in each publication, different statistical methods are employed in analyzing of data. There are some similarities between the analysis methods used in the publications, but mainly different methods are used. Based on this dissertation the use of statistical methods for industrial knowledge creation is strongly recommended. With statistical methods it is possible to handle large datasets and different types of statistical analysis results can easily be transformed into knowledge.

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Lignocellulosic biomasses (e.g., wood and straws) are a potential renewable source for the production of a wide variety of chemicals that could be used to replace those currently produced by petrochemical industry. This would lead to lower greenhouse gas emissions and waste amounts, and to economical savings. There are many possible pathways available for the manufacturing of chemicals from lignocellulosic biomasses. One option is to hydrolyze the cellulose and hemicelluloses of these biomasses into monosaccharides using concentrated sulfuric acid as catalyst. This process is an efficient method for producing monosaccharides which are valuable platforn chemicals. Also other valuable products are formed in the hydrolysis. Unfortunately, the concentrated acid hydrolysis has been deemed unfeasible mainly due to high chemical consumption resulting from the need to remove sulfuric acid from the obtained hydrolysates prior to the downstream processing of the monosaccharides. Traditionally, this has been done by neutralization with lime. This, however, results in high chemical consumption. In addition, the by-products formed in the hydrolysis are not removed and may, thus, hinder the monosaccharide processing. In order to improve the feasibility of the concentrated acid hydrolysis, the chemical consumption should be decreased by recycling of sulfuric acid without neutralization. Furthermore, the monosaccharides and the other products formed in the hydrolysis should be recovered selectively for efficient downstream processing. The selective recovery of the hydrolysis by-products would have additional economical benefits on the process due to their high value. In this work, the use of chromatographic fractionation for the recycling of sulfuric acid and the selective recovery of the main components from the hydrolysates formed in the concentrated acid hydrolysis was investigated. Chromatographic fractionation based on the electrolyte exclusion with gel type strong acid cation exchange resins in acid (H+) form as a stationary phase was studied. A systematic experimental and model-based study regarding the separation task at hand was conducted. The phenomena affecting the separation were determined and their effects elucidated. Mathematical models that take accurately into account these phenomena were derived and used in the simulation of the fractionation process. The main components of the concentrated acid hydrolysates (sulfuric acid, monosaccharides, and acetic acid) were included into this model. Performance of the fractionation process was investigated experimentally and by simulations. Use of different process options was also studied. Sulfuric acid was found to have a significant co-operative effect on the sorption of the other components. This brings about interesting and beneficial effects in the column operations. It is especially beneficial for the separation of sulfuric acid and the monosaccharides. Two different approaches for the modelling of the sorption equilibria were investigated in this work: a simple empirical approach and a thermodynamically consistent approach (the Adsorbed Solution theory). Accurate modelling of the phenomena observed in this work was found to be possible using the simple empirical models. The use of the Adsorbed Solution theory is complicated by the nature of the theory and the complexity of the studied system. In addition to the sorption models, a dynamic column model that takes into account the volume changes of the gel type resins as changing resin bed porosity was also derived. Using the chromatography, all the main components of the hydrolysates can be recovered selectively, and the sulfuric acid consumption of the hydrolysis process can be lowered considerably. Investigation of the performance of the chromatographic fractionation showed that the highest separation efficiency in this separation task is obtained with a gel type resin with a high crosslinking degree (8 wt. %); especially when the hydrolysates contain high amounts of acetic acid. In addition, the concentrated acid hydrolysis should be done with as low sulfuric acid concentration as possible to obtain good separation performance. The column loading and flow rate also have large effects on the performance. In this work, it was demonstrated that when recycling of the fractions obtained in the chromatographic fractionation are recycled to preceding unit operations these unit operations should included in the performance evaluation of the fractionation. When this was done, the separation performance and the feasibility of the concentrated acid hydrolysis process were found to improve considerably. Use of multi-column chromatographic fractionation processes, the Japan Organo process and the Multi-Column Recycling Chromatography process, was also investigated. In the studied case, neither of these processes could compete with the single-column batch process in the productivity. However, due to internal recycling steps, the Multi-Column Recycling Chromatography was found to be superior to the batch process when the product yield and the eluent consumption were taken into account.

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This study combines several projects related to the flows in vessels with complex shapes representing different chemical apparata. Three major cases were studied. The first one is a two-phase plate reactor with a complex structure of intersecting micro channels engraved on one plate which is covered by another plain plate. The second case is a tubular microreactor, consisting of two subcases. The first subcase is a multi-channel two-component commercial micromixer (slit interdigital) used to mix two liquid reagents before they enter the reactor. The second subcase is a micro-tube, where the distribution of the heat generated by the reaction was studied. The third case is a conventionally packed column. However, flow, reactions or mass transfer were not modeled. Instead, the research focused on how to describe mathematically the realistic geometry of the column packing, which is rather random and can not be created using conventional computeraided design or engineering (CAD/CAE) methods. Several modeling approaches were used to describe the performance of the processes in the considered vessels. Computational fluid dynamics (CFD) was used to describe the details of the flow in the plate microreactor and micromixer. A space-averaged mass transfer model based on Fick’s law was used to describe the exchange of the species through the gas-liquid interface in the microreactor. This model utilized data, namely the values of the interfacial area, obtained by the corresponding CFD model. A common heat transfer model was used to find the heat distribution in the micro-tube. To generate the column packing, an additional multibody dynamic model was implemented. Auxiliary simulation was carried out to determine the position and orientation of every packing element in the column. This data was then exported into a CAD system to generate desirable geometry, which could further be used for CFD simulations. The results demonstrated that the CFD model of the microreactor could predict the flow pattern well enough and agreed with experiments. The mass transfer model allowed to estimate the mass transfer coefficient. Modeling for the second case showed that the flow in the micromixer and the heat transfer in the tube could be excluded from the larger model which describes the chemical kinetics in the reactor. Results of the third case demonstrated that the auxiliary simulation could successfully generate complex random packing not only for the column but also for other similar cases.

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This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

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The objective of this thesis is to understand how to create and develop a successful place brand and how to manage it systematically. The thesis thoroughly explains the phenomenon of place brands and place branding and presents different sub-categories of place branding. The theoretical part of the thesis provides a wide overview on the prevailing literature of place branding, place brand development and place brand management, which form the basis of the thesis’ theoretical framework. The theoretical evidence is gathered from a case living area. The living area is developed by one construction company, which has a significant role in the construction industry in Finland. The empirical evidence is gathered through semi-structured in-depth interviews by interviewing the new living area’s carefully selected stakeholder groups. Afterwards the empirical data is analyzed and reflected to the theoretical findings. After examining the case living area, the thesis will present a new living area branding process model based on prevailing theories and empirical findings.

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Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

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Active magnetic bearing is a type of bearing which uses magnetic field to levitate the rotor. These bearings require continuous control of the currents in electromagnets and data from position of the rotor and the measured current from electromagnets. Because of this different identification methods can be implemented with no additional hardware. In this thesis the focus was to implement and test identification methods for active magnetic bearing system and to update the rotor model. Magnetic center calibration is a method used to locate the magnetic center of the rotor. Rotor model identification is an identification method used to identify the rotor model. Rotor model update is a method used to update the rotor model based on identification data. These methods were implemented and tested with a real machine where rotor was levitated with active magnetic bearings and the functionality of the methods was ensured. Methods were developed with further extension in mind and also with the possibility to apply them for different machines with ease.

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The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods

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The general aim of the thesis was to study university students’ learning from the perspective of regulation of learning and text processing. The data were collected from the two academic disciplines of medical and teacher education, which share the features of highly scheduled study, a multidisciplinary character, a complex relationship between theory and practice and a professional nature. Contemporary information society poses new challenges for learning, as it is not possible to learn all the information needed in a profession during a study programme. Therefore, it is increasingly important to learn how to think and learn independently, how to recognise gaps in and update one’s knowledge and how to deal with the huge amount of constantly changing information. In other words, it is critical to regulate one’s learning and to process text effectively. The thesis comprises five sub-studies that employed cross-sectional, longitudinal and experimental designs and multiple methods, from surveys to eye tracking. Study I examined the connections between students’ study orientations and the ways they regulate their learning. In total, 410 second-, fourth- and sixth-year medical students from two Finnish medical schools participated in the study by completing a questionnaire measuring both general study orientations and regulation strategies. The students were generally deeply oriented towards their studies. However, they regulated their studying externally. Several interesting and theoretically reasonable connections between the variables were found. For instance, self-regulation was positively correlated with deep orientation and achievement orientation and was negatively correlated with non-commitment. However, external regulation was likewise positively correlated with deep orientation and achievement orientation but also with surface orientation and systematic orientation. It is argued that external regulation might function as an effective coping strategy in the cognitively loaded medical curriculum. Study II focused on medical students’ regulation of learning and their conceptions of the learning environment in an innovative medical course where traditional lectures were combined wth problem-based learning (PBL) group work. First-year medical and dental students (N = 153) completed a questionnaire assessing their regulation strategies of learning and views about the PBL group work. The results indicated that external regulation and self-regulation of the learning content were the most typical regulation strategies among the participants. In line with previous studies, self-regulation wasconnected with study success. Strictly organised PBL sessions were not considered as useful as lectures, although the students’ views of the teacher/tutor and the group were mainly positive. Therefore, developers of teaching methods are challenged to think of new solutions that facilitate reflection of one’s learning and that improve the development of self-regulation. In Study III, a person-centred approach to studying regulation strategies was employed, in contrast to the traditional variable-centred approach used in Study I and Study II. The aim of Study III was to identify different regulation strategy profiles among medical students (N = 162) across time and to examine to what extent these profiles predict study success in preclinical studies. Four regulation strategy profiles were identified, and connections with study success were found. Students with the lowest self-regulation and with an increasing lack of regulation performed worse than the other groups. As the person-centred approach enables us to individualise students with diverse regulation patterns, it could be used in supporting student learning and in facilitating the early diagnosis of learning difficulties. In Study IV, 91 student teachers participated in a pre-test/post-test design where they answered open-ended questions about a complex science concept both before and after reading either a traditional, expository science text or a refutational text that prompted the reader to change his/her beliefs according to scientific beliefs about the phenomenon. The student teachers completed a questionnaire concerning their regulation and processing strategies. The results showed that the students’ understanding improved after text reading intervention and that refutational text promoted understanding better than the traditional text. Additionally, regulation and processing strategies were found to be connected with understanding the science phenomenon. A weak trend showed that weaker learners would benefit more from the refutational text. It seems that learners with effective learning strategies are able to pick out the relevant content regardless of the text type, whereas weaker learners might benefit from refutational parts that contrast the most typical misconceptions with scientific views. The purpose of Study V was to use eye tracking to determine how third-year medical studets (n = 39) and internal medicine residents (n = 13) read and solve patient case texts. The results revealed differences between medical students and residents in processing patient case texts; compared to the students, the residents were more accurate in their diagnoses and processed the texts significantly faster and with a lower number of fixations. Different reading patterns were also found. The observed differences between medical students and residents in processing patient case texts could be used in medical education to model expert reasoning and to teach how a good medical text should be constructed. The main findings of the thesis indicate that even among very selected student populations, such as high-achieving medical students or student teachers, there seems to be a lot of variation in regulation strategies of learning and text processing. As these learning strategies are related to successful studying, students enter educational programmes with rather different chances of managing and achieving success. Further, the ways of engaging in learning seldom centre on a single strategy or approach; rather, students seem to combine several strategies to a certain degree. Sometimes, it can be a matter of perspective of which way of learning can be considered best; therefore, the reality of studying in higher education is often more complicated than the simplistic view of self-regulation as a good quality and external regulation as a harmful quality. The beginning of university studies may be stressful for many, as the gap between high school and university studies is huge and those strategies that were adequate during high school might not work as well in higher education. Therefore, it is important to map students’ learning strategies and to encourage them to engage in using high-quality learning strategies from the beginning. Instead of separate courses on learning skills, the integration of these skills into course contents should be considered. Furthermore, learning complex scientific phenomena could be facilitated by paying attention to high-quality learning materials and texts and other support from the learning environment also in the university. Eye tracking seems to have great potential in evaluating performance and growing diagnostic expertise in text processing, although more research using texts as stimulus is needed. Both medical and teacher education programmes and the professions themselves are challenging in terms of their multidisciplinary nature and increasing amounts of information and therefore require good lifelong learning skills during the study period and later in work life.

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The purpose of this study is to find out how laser based Directed Energy Deposition processes can benefit from different types of monitoring. DED is a type of additive manufacturing process, where parts are manufactured in layers by using metallic powder or metallic wire. DED processes can be used to manufacture parts that are not possible to manufacture with conventional manufacturing processes, when adding new geometries to existing parts or when wanting to minimize the scrap material that would result from machining the part. The aim of this study is to find out why laser based DED-processes are monitored, how they are monitored and what devices are used for monitoring. This study has been done in the form of a literature review. During the manufacturing process, the DED-process is highly sensitive to different disturbances such as fluctuations in laser absorption, powder feed rate, temperature, humidity or the reflectivity of the melt pool. These fluctuations can cause fluctuations in the size of the melt pool or its temperature. The variations in the size of the melt pool have an effect on the thickness of individual layers, which have a direct impact on the final surface quality and dimensional accuracy of the parts. By collecting data from these fluctuations and adjusting the laser power in real-time, the size of the melt pool and its temperature can be kept within a specified range that leads to significant improvements in the manufacturing quality. The main areas of monitoring can be divided into the monitoring of the powder feed rate, the temperature of the melt pool, the height of the melt pool and the geometry of the melt pool. Monitoring the powder feed rate is important when depositing different material compositions. Monitoring the temperature of the melt pool can give information about the microstructure and mechanical properties of the part. Monitoring the height and the geometry of the melt pool is an important factor in achieving the desired dimensional accuracy of the part. By combining multiple different monitoring devices, the amount of fluctuations that can be controlled will be increased. In addition, by combining additive manufacturing with machining, the benefits of both processes could be utilized.

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In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.