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Biosystems Instrumentation |
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Organiser |
AgroTechnology, Dep. of
Agricultural Sciences, RVAU. |
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| Lecturers | Prof. Simon Blackmore, Prof. Henrik Have, Assoc. Prof Hans Werner Griepentrog and Assoc. Prof. Dvoralai Wulfson, RVAU. | |
| Assessment |
Project presentation and oral examination Marking scale Approved / not approved |
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| Language | English | |
| ECTS |
10 |
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| Time | March 7-18, 2005 | |
| Place | RVAU, Denmark | |
| Deadline | ||
| Teaching methods | The course comprises lectures, practical as well as identification and description of individual course projects on a subject of their own choice within the course subject area. The practical are to a large extent organised as practical problem based measuring tasks carried out as group work involving 3-4 students. After the course period the students are expected to do their project works and send their reports to the course supervisors. Finally the students will present and defend their projects using video-link to save costs. | |
| Lecture material | Holman, J.P. (1994): Experimental methods for Engineers McGraw-Hill, or similar. Various supplementary material, copies of overhead transparencies. Most additional material will be available on the Internet. | |
| Purpose |
The students shall understand principles and
limitations in using measuring and sensing systems as well as data
processing methods as tools for scientific research within agriculture
and related areas. The students will achieve a deeper knowledge about
measuring principles, planning of measurements and selection of
measuring, sensing, and data processing systems. They will also achieve
qualifications to judge results with regard to credibility and accuracy.
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| Rationale | The usage of measuring and sensing systems is a basic discipline of research and is also becoming a still more important in production systems and processes, including systems for agriculture. The possibility of acquiring large amounts of data on many different quantities has been greatly improved during the last decade, especially through remote and computer assisted sensing methods. However, there are considerable challenges in organising, storing and processing these large amounts of data to achieve reliable and acceptable results | |
| Description |
Overview of perception methods; general
laboratory equipment; sensors and transducers; signal conditioning; data
capture and storage; information extraction and data reduction;
calibration; errors and accuracy; planning of measurements and set up of
measuring systems according to criteria’s. Practical application in a
selected field, e.g. volumetric space measurements using laser scanners,
crop property measurements using hyper spectral spectrometer, pattern
recognition or parameter estimation using machine vision, force
measurements using stain gauge dynamometers. |
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| Prerequisites | The students should have basic knowledge of computing and some understanding of programming; basic knowledge in physics (mechanics, optics and electronics), statistics (probability calculus, variance, correlation, estimates, confidence intervals and hypothesis testing) and basic understanding of measuring principles achieved by reading the text book before the start of the course. | |
| Audience | Ph.D. students and researchers specialising in the area | |
| Financial support | The NOVA-University and NorFA (Nordic Academy for Advanced Study) scholarships for Baltic students. | |
| Sponsor | DaNet | Topic specific course |
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Introduction |
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