Developing an introductory object-oriented programming course

The state of the object-oriented programming course in Lappeenranta University of Technology had reached the point, where it required changes to provide better learning opportunities and thus the learning outcomes. Based on the student feedback the course was partially dated and ineffective. The components of the course were analysed and the ineffective elements were removed and new methods were introduced to improve the course. The major changes included the change from traditional teaching methods to reverse classroom method and the use of Java as the programming language. The changes were measured by the student feedback, lecturer’s observations and comparison to previous years. The feedback suggested that the changes were successful; the course received higher overall grade than before.

Oliopohjaisen mallinnuksen käyttömahdollisuudet erään ohjelmistotuotteen eri kehitysvaiheissa

Oliopohjainen lähestymistapa on varsin uusi toimintaperiaate käytännön ohjelmistotuotantoprosesseissa. Oliopohjaisuus mahdollistaa nopean ja tehokkaan ohjelmistotuotannon sekä tuottaa uudelleenkäytettäviä luokkia. Tässä työssä tutkitaan oliopohjaisen mallinnuksen käyttömahdollisuuksia erään ohjelmistotuotteen kehityksessä ja keskitytään tuotteen määrittely- ja suunnitteluvaiheisiin. Tavoitteena on konkretisoida tarkastelun kohteena olevalle yritykselle oliopohjaisen mallinnuksen käyttötavat ja -mahdollisuudet osana yrityksen ohjelmistotuotantoprosessia. Työssä tarkastellaan yleisiä oliopohjaisen mallinnuksen toimintoja määrittely- ja suunnitteluvaiheissa. Erityisesti tarkastellaan yrityksen omaa ohjelmistotuotantoprosessia, TE Objectia, ja sen yhtymäkohtia yleisen oliopohjaisen mallinnuksen kanssa. Työssä kuvataan ohjelmistotuote, mallinnetaan ohjelmistotuotteen osa TE Objectia hyödyntäen ja pohditaan TE Objectin soveltuvuutta kyseisen tuotteen määrittelyyn ja suunnitteluun. Oliopohjaisen mallinnuksen todetaan sopivan hyvin tarkastellun tuotepohjaisen ohjelmiston kehitykseen. Tarkasteltavan tuotteen kehityksen pääpaino on uudelleenkäytettävyydellä, jota oliopohjainen mallintaminen erityisesti tukee. Kohdeyrityksen oman ohjelmistotuotantoprosessin, TE Objectin, todetaan vastaavan hyvin yleistä oliopohjaista mallinnusta määrittely- ja suunnitteluvaiheissa ja sitä suositellaan hyödynnettävän tarkastellun tuotteen määrittelyyn ja suunnitteluun soveltuvin osin. Työssä mallinnettiin kohdeyrityksen tuotteen osa esimerkinomaisesti, mikä konkretisoi TE Objectin käyttömahdollisuuksia osana yrityksen ohjelmistotuotantoprosessia.

Comparison of application frameworks designed to support application extensibility

Reusability has become more popular factor in modern software engineering. This is mainly because object-orientation has brought methods that allow reusing more easily. Today more and more application developer thinks how they can reuse already existing applications in their work. If the developer wants to use existing components outside the current project, he can use design patterns, class libraries or frameworks. These provide solution for specific or general problems that has been already encountered. Application frameworks are collection of classes that provides base for the developer. Application frameworks are mostly implementation phase tools, but can also be used in application design. The main purpose of the frameworks is separate domain specific functionalities from the application specific. Usually the frameworks are divided into two categories: black and white box. Difference between those categories is the way the reuse is done. The application frameworks provide properties that can be examined and compared between different frameworks. These properties are: extensibility, reusability, modularity and scalability. These examine how framework will handle different platforms, changes in framework, increasing demand for resources, etc. Generally application frameworks do have these properties in good level. When comparing general purpose framework and more specific purpose framework, the main difference can be located in reusability of frameworks. It is mainly because the framework designed to specific domain can have constraints from external systems and resources. With general purpose framework these are set by the application developed based on the framework.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

The Reflections of Strategic Orientation on profitability - A resource-based study in pulp and paper industry

Tutkielman tavoitteena oli analysoida erilaisia strategisia orientaatioita sellu- ja paperiteollisuudessa. Sellu- ja paperiteollisuus on kohtaamassa strategisia haasteita, jotka ulottuvat syvälle sen rakenteisiin. Yritykset ovat valinneet erilaisia lähestymistapoja organisoidessaan tuotantoa ja kansainvälistä arvoketjuaan tässä muuttuvassa ympäristössä. Tutkimukseen valittiin 30 suurinta sellu- ja paperiteollisuudessa toimivaa yritystä ja mahdollisia syitä kannattavuuseroihin yritysten välillä analysoitiin. Yritysten strategista orientaatiota tarkasteltiin vertailemalla muun muassa seuraavia tekijöitä: vertikaalinen integraatioaste, tuotevalikoiman laajuus, tuotantokapasiteetin levinneisyys ja tuotantokapasiteetin ikä. Kannattavuutta mitattiin erilaisilla talouden tunnusluvuilla (liikevoitto, oman pääoman tuotto-%, koko pääoman tuotto-%). Tulosten mukaan yrityksiä voidaan ryhmitellä strategisen orientaation perusteella ja ryhmien välillä on kannattavuuseroja.

Local and Global Feature Extraction for Invariant Object Recognition

Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.

Big Data Processing in the Cloud: a Hydra/Sufia Experience

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

Generative Part-Based Gabor Object Detector

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.

University students’ regulation of learning and text processing – examples from medical and teacher education

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.

Effects of feed processing on the apparent ileal digestibility of amino acids in pig diets containing wheat bran or wheat middlings

Selostus: Prosessoinnin vaikutus vehnän sivutuotteita sisältävien rehuseosten aminohappojen ohutsuolisulavuuteen sioilla