Data mining with graphical models

Data Mining, Learning from data, graphical models, possibility theory

monitoring-based approach to object-oriented real-time computing

Monitoring, object-orientation, real-time, execution-time, scheduling

SQL based frequent pattern mining

Data mining, frequent pattern mining, database mining, mining algorithms in SQL

Spatial data mining in precision agriculture

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Online-Data-Mining auf Datenströmen : Methoden zur Clusteranalyse und Klassifikation

Online Data Mining, Data Streams, Classification, Clustering

Data mining in diagnostic charts and treatment outcome prediction for vision restoration therapy

Data Mining, Vision Restoration, Treatment outcome prediction, Self-Organising-Map

Mining perennial objects

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Application of data mining for assessment of material properties : creep behavior of high-temperature steels

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2009

On utilising change over time in data mining

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Generic object classification for autonomous robots

Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Estimating the Impact on Efficiency of the Adoption of a Voluntary Environmental Standard: An Empirical Study of the Global Copper Mining Industry

This paper uses data on the world's copper mining industry to measure the impact on efficiency of the adoption of the ISO 14001 environmental standard. Anecdotal and case study literature suggests that firms are motivated to adopt this standard so as to achieve greater efficiency through changes in operating procedures and processes. Using plant level panel data from 1992-2007 on most of the world's industrial copper mines, the study uses stochastic frontier methods to investigate the effects of ISO adoption. The variety of models used in this study find that adoption either tends to improve efficiency or has no impact on efficiency, but no evidence is found that ISO adoption decreases efficiency.

A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

Fear assessment in pigs exposed to a novel object test

The experiment aimed to study approach and locomotive behaviour as indicators of fear in a novel object test carried out in pigs. Thirty post-weaning (30 kg) and 30 finishing (90 kg) pigs were exposed to visual, auditory and olfactory novel stimuli during 2 different experiments. The facilities consisted of a test pen in which a trough was located. The trough contained chopped apples. Once the animals were trained to enter the test pen individually they were subjected to 3 different fear stimuli. These stimuli were applied in the test pen and next to the trough. The variables studied were feeding behaviour, approach behaviour (the distance and position of the animal with respect to the trough) and locomotive behaviour (general activity, reluctance to move, turning back and retreat attempts). Two groups were studied: saline and midazolam treated group. Twenty minutes before the start of the sessions, 15 post-weaning and finishing pigs received an intramuscular injection of 0.20 and 0.15 mg/kg, respectively, midazolam (Dormicum1). The saline pigs (15 animals per group) were injected with saline. The administration of midazolam increased the feeding behaviour and approaching behaviour, and reduced the locomotive behaviour. In front of the visual and olfactory stimuli post-weaning pigs showed a higher general activity than finishing pigs, but the contrary was found when the auditory stimulus was applied. The olfactory stimulus was more related to the turning back behaviour, whereas the visual stimulus was more related to retreat attempts. Although it could be concluded that reluctant to move was the most common response to the different fear stimuli applied in our study regardless of the age of animals, the combination of reluctant to move and turning back would be a good criterion to assess fear in domestic pigs. The use of midazolam as anxiolytic for studies of fear in commercial conditions in pigs is recommended.