Towards the Interactive ESS-Food Catalogue
Towards the Interactive ESS-Food catalogue is a multifaceted project with focus mainly on visualization and interaction. In the first part of the project concerns volumetric visualization of CT-scanned pig meat. CT-Scans only carry density information, so a number of steps must be taken to properly visualize the data in an appealing fashion.
The second part of the project is concerned with how the user should interact with the visualized volumetric data. The goal is to allow the user to cut the meat in a simple and straightforward manner. By using a haptic feedback device, we hope that the user will be able to intuitively interact with the meat.
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Date: 16/3-2010
Towards the Virtual Slaughterhouse - Modelling Bone Structures of Pigs
The Danish slaughterhouses process approximately 25 million pig carcasses every year. Today the optimisation of the use of pig carcasses is based on empirically determined relations between simple measurements taken on the carcass and the size/quality of the obtained cuts.
It is the purpose of this project to statistically model central bone structures in 3D as an initial part of a "virtual slaughterhouse" based on computed tomography (CT) scanning of pig carcasses.
The "virtual slaughterhouse" can be used to e.g. determine the optimum cutting of specific sections and help in the design process of new slaughterhouse tools. The project is a collaboration between Informatics and Mathematical Modelling, DTU and the Danish Meat Research Institute (DMRI).
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Estimation of Turbulent Airflow in Livestock Buildings
The goal for this project is to estimate flow fields for the turbulent airflow that occur in livestock buildings for subsequent use in a further modelling and quantitative determination of relevant parameters. The end goal being to enable us to predict risk of draft as a function of the ventilation system.
The project is a collaboration between the Informatics and Mathematical Modelling at The Technical University of Denmark, and the Statens Jordbrugstekniske Forsøg, Bygholm. This project is funded by Statens Jordbrugs- og Veterinærvidenskabelige Forskningsråd, and the two collaborators.
All experiments are carried out at Statens Jordbrugstekniske Forsøg in the Airphysics Laboratory. A full-scale model as well as a 1:10 model of a segment of a livestock buildings is used. The airflow is visualized by inducing smoke in the air-inlets og the model and illuminating a plane using a laser sheet. The smoke in the illuminated plane is recoded using a light sensitive video camera. Read more about this here...
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Intelligent Sensor for Autonomous Cleaning
Manual cleaning of livestock buildings, using high-pressure water technology, is one of the most tedious and health threatening tasks conducted by human labour. The cleaning process itself contributes to deterioration of the working environment due to stirring up dirt, micro organisms and water, which are inhaled by the operator. Consequently, improving the working conditions for personnel performing cleaning of today's livestock buildings is essential.
Societies concerns about food safety and livestock welfare are also important issues on the modern farmer's agenda. Ongoing research in Europe includes development of autonomous cleaning robots, of which few are commercialised. Further investigations have shown that robot performance is poor regarding effectiveness and utilization of detergent and water. The water consumption for robotic cleaning is up to 40% higher than what is used for manual cleaning. Robotic cleaning often entails subsequent manual cleaning because the robot did not detect the cleanliness of the surfaces.
The aim of the project is to improve the human working environment, secure the hygienic standard and optimised use of cleaning resources in livestock buildings. The specific objective is to develop an intelligent sensor system that can supply data to a system for autonomous cleaning of livestock compartments.
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Multivariate Statistics in Predictive Biotechnology
The aims of the studies are based on the main hypothesis that the combination of multivariate statistics and image analysis of features can be used as a tool in (visual and chemical) database identification processes within isolates from the fungal genera Penicillium and Aspergillus.
Databases of functional characteristics are expected to be complementary to the known DNA-sequence based databases. The identification is based on visual as well as secondary metabolite profiles. Secondary metabolites are end products of the bio-chemical processes that take place within cells of all living organisms, and they are therefore indirectly descriptive of the cells metabolic processes. If different cells use different processes, there will also be a difference in the variety of metabolites produced. Furthermore the chemical variation in the metabolites can be directly related to ecology and habitat. Read more about this here...
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Image Analysis of 2D Gel Electrophoresis Images
The main goal of this project is to investigate and develop methods to partly automate and ease the tedious and time consuming task of locating, quantifying, and matching protein spot patterns in series of 2D electrophoresis gel images.
The image shows an example with 1900+ proteins represented as dark spots on the bright background. The principles in 2D electrophoresis process are as follows. The protein contents of a biological sample, e.g., a blood sample or a tissue/bone biopsy can be separated using the 2D electrophoresis technique. The proteins are separated in two dimensions according to iso-electic focus point (horizontal direction) and molecular weight (vertical direction), respectively. The values of these two properties determine the spatial position of each protein spot.
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