Master s thesis Professor Heikki Kälviäinen Supported by European Union Machine Vision and Pattern Recognition Laboratory (MVPR) Department of Mathematics and Physics LUT School of Technology Lappeenranta University of Technology (LUT) FINLAND Heikki.Kalviainen@lut.fi http://personal.lut.fi/users/heikki.kalviainen/ http://www2.it.lut.fi/mvpr/ 1
Content Degree programs and major subjects. Master s thesis as a thesis. An example. Topics. Workplaces. Thesis process. Instructions. Doing, supervision, and evaluation. 2
Degree programs and major subjects A degree program consists of major subjects. Education of Information Technology (in Finnish tietotekniikka ) at LUT has been divided into two degree programs (responsible persons in parentheses): Computer Science (Prof. Kari Smolander). Software Engineering (Prof. Jari Porras). Computational Science and Physics (Assoc. Prof. Matti Heiliö), Laskennallinen tiede ja fysiikka (in Finnish). (Assoc. Prof. Arto Kaarna). Älykäs laskenta (in Finnish). 3
Computational Science and Physics Computational Science combines the methods of Mathematics, Computer Science, and Natural Sciences, in the innovative way. 3 major subjects. More jobs based on information processing and more technology based on science. Technological development, innovations, and sustainability is based skills of mathematics and natural sciences. New kind of innovators and developers for the industry and the society. Natural Sciences Computer Science Mathematics Physics Technomathematics 4
Master s thesis project The thesis is a project of N months with carefully planned schedules and contents, considering the following evaluation criteria: Definition of research problem, objectives, and delimitations. Research approach, methods, and materials. Utilization of existing research knowledge. Systematic and responsible execution of the project. Logic and credibility of the interpretation of the results and the conclusions. Usability of the results. Readability, presentation, and language of the report. 5
Master s thesis: Many skills needed Measurements? Devices? Camera PAL => Optic Expert knowledge? Human s perception and reasoning? Fiber User interface? Software? Imaging and classification Vacuum chamber Connections? Data warehouse? Optic => PAL Define the quality of steel based on bubbling of liquid steel: Can a machine vision system replace a human being? 6
Tool for the hydrogen prediction 7
Many kinds of theses Environmental Monitoring Using Image Analysis. Retinal Image Analysis Using Machine Vision. Hand Tracking in High-speed Camera Videos. Traffic Sign Condition Analysis Using Machine Vision. Characterization of Fiber and Vessel Elements in Pulp Suspension Images. Unsupervised Visual Object Categorization. Predicting Diffusion of Innovations with Self-Organisation and Machine Learning. Customer Profiling in Supermarkets. Probabilistic pose estimation of rigid objects using an RGB-D sensor. Social media content as a high potential indicator for measuring innovation performance: case study of six major companies in computer industry. WebRTC Application for Cross-platform VoIP Communication. Using Moodle to provide added value in the teaching of a software development course. Framework for IT Service Management Integration. Etc. 8
Many kinds of work places for theses Microsoft, Nokia, Siemens, Ericsson, Motorola, jne. TeliaSonera, Elisa, DNA, etc. TietoEnator, OpenTTCN, Logica, Accenture, Appelsiini Finland, QAim, Proventia, Pintaworks, Syncron Tech, Viope Solutions, Severa, Mipro, Kaakontieto, Zokem, Stonesoft, Miradore, Eke Electronics, Propentus, Eatech, Itella, Software Innovation Finland, etc. Universities and research institutes: LUT, TUT, Aalto University, University of Jyväskylä, UEF, VTT, University of Oulu, Finnish Meteorological Institute, Statistics Finland, etc. City of Lappeenranta, City of Imatra, Tuusniemi Senior High School, Etelä-Saimaa Hospital, Evangelical Free Church of Finland, etc. Stora Enso, UPM-Kymmene, M-Real, Ovako Steel, Kone, Konecranes, Andritz, Metso Automation, Metso Paper, Kemira, Honeywell, Kesko, Etelä-Karjalan Osuuskauppa, etc. Not in Finland only but also abroad. 9
Thesis process Think first: What is your topic (research questions) and where to do it? A master s thesis: 30 ECTS = 30 x 26 h = 780 h. Pair project also possible. Browse the LUT Uni portal: https://uni.lut.fi/en/web/lut.fi-eng/ Read the LUT thesis instructions, called Final thesis instructions. https://uni.lut.fi/en/web/lut.fi-eng/master-s-thesis-project4 Read carefully the official Word template of the degree program. https://uni.lut.fi/en/web/lut.fi-eng/master-s-thesis-project4 Browse the web pages of the degree program: https://uni.lut.fi/en/web/lut.fi-eng/information-technology Starting the work: Contact the responsible person of your major subject and ask to allocate the first examiner (primary supervisor) who can be either a professor or a docent (an officially evaluated qualified doctor). Contact the first examiner. Write the abstract, the list of contents, and plan the schedule (what and when). 10
Thesis process (cont.) Applying for the topic: Title, workplace, 1 st and 2 nd examiners, supervisor (= practical one). Contact the study office of your faculty and introduce your study structure. Summit the application for the approval of the topic to the study office. Real actions: Do it! : Theory: literature review (remember the quality of references!). Practice: planning, actions, and results. Write: Comments from the examiners and the practical supervisor. Final version to be printed approved by the examiners. Print the thesis. Give the thesis presentation, and write the maturity test (if not done earlier). Book as advised. Assessment of the thesis can be done only after the presentation. 11
Thesis process (cont.) Apply for the assessment of the thesis. Joint written statement by the both examiners. https://uni.lut.fi/en/web/lut.fi-eng/application-forms5 Overall grading 0-5 and the following subgrades also 0-5: Definition of research problem, objectives, and delimitations. Research approach, methods and materials. Utilization of existing research knowledge. Systematic and responsible execution of the project. Logic and credibility of the interpretation of the results and the conclusions. Usability of the results. Readability, presentation and language of the report. Public/confidential, patents, reporting of (scientific) results, media. The dean approves the statement and the confidentiality notification. 12