0000000000084734
AUTHOR
R. Magdalena
Qualitative Analysis of Feed Management Practice on Goat Herds by Self Organizing Maps in Murcia Region of Spain
Abstract Fernandez, C., Soria, E., Magdalena, R., Martin, J.D. and Mata, C. 2007. Qualitative analysis of feed management practice on goat herds by self organizing maps in Murcia region of Spain. J. Appl. Anim. Res., 32: 41–47. Self organizing maps (SOM) were used to analyze data from ninety four herds. Data were obtained from surveys and management practices were evaluated. The 18% of farms were dairy goat farms with milking machines, with a herd size of 100 to 200 goats and most of these bought compound feed. 12% has the same characteristics but farmers prepared their own diet. 16% were similar to previous prototypes, but farmers in addition to dairy goat production kept sheep as well. 23…
Neural Models for Rainfall Forecasting
This chapter is focused on obtaining an optimal forecast of one month lagged rainfall in Spain. It is assessed by analyzing 22 years of both satellite observations of vegetation activity (e.g. NDVI) and climatic data (precipitation, temperature). The specific influence of non-spatial climatic indices such as NAO and SOI is also addressed. The approaches considered for rainfall forecasting include classical Auto-Regressive Moving-Average with Exogenous Inputs (ARMAX) models and Artificial Neural Networks (ANN), the so-called Multilayer Perceptron (MLP), in particular. The use of neural models is proven to be an adequate mathematical prediction tool in this problem due the non-linearity of th…
A Teaching Laboratory in Analog Electronics: Changes to Address the Bologna Requirements
Training new electronics engineers presents several major challenges. This paper proposes a new approach for practical lessons in second-level analog electronics, where students get a closer view of real-world practices in electronic engineering. The authors describe and evaluate a more dynamic way of teaching practical lessons in analog electronics in the first year of an electronic engineering degree. The method consists of creating a virtual company that contracts students to develop prototypes. The design process involves theoretical concepts from the students' lessons, and poses challenges with respect to costs and teamwork. The method brings the students closer to the working environm…
P and R Wave Detection in Complete Congenital Atrioventricular Block
Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads. The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pa…
Design of a Neural Network Model as a Decision Making Aid in Renal Transplant
This paper presents the application of this new tool of data processing in the study of the problem that arises when a renal transplant is indicated for a paediatric patient. Its aim is the development and validation of a neural network based model which can predict the success of the transplant over the short, medium and long term, using pre-operative characteristics of the patient (recipient) and implant organ (donor). When compared to results of logistic regression, the results of the proposed model showed better performance. Once the model is obtained, it will be converted into a tool for predicting the efficiency of the transplant protocol in order to optimise the donor-recipient pair …
Feature selection using ROC curves on classification problems
Feature Selection (FS) is one of the key stages in classification problems. This paper proposes the use of the area under Receiver Operator Characteristic curves to measure the individual importance of every input as well as a method to discover the variables that yield a statistically significant improvement in the discrimination power of the classification model.
BioLab: An Educational Tool for Signal Processing Training in Biomedical Engineering
This paper introduces and evaluates BioLab, a tool for teaching biosignal processing. BioLab has been used in the biomedical engineering module that is given in the second semester of the fifth year of the electronic engineering degree at the University of Valencia, Spain. This module and its correspondent curricular pathway are also reviewed. BioLab allows the results obtained with digital processing techniques to be shown interactively in the theory classes, and it also provides support in laboratory sessions. The graphic interface of BioLab simplifies its learning and use and provides access to processing and visualization functions by means of menus. The tool is based on Matlab since th…
Qualitative analysis of goat and sheep production data using self-organizing maps
The aim of this study was to analyse the relationship between different small ruminant livestock production systems with different levels of specialization. The analysis is carried out by using the self-organizing map. This tool allows high-dimensional input spaces to be mapped into much lower-dimensional spaces, thus making it much more straightforward to understand any set of data. These representations enable the visual extraction of qualitative relationships among variables (visual data mining), converting the data to maps. The data used in this study were obtained from surveys completed by farmers who are principally dedicated to goat and sheep production. With the self-organizing map …
Adaptive algorithms robust to impulsive noise with low computational cost using order statistic
Abstract In this paper a family of adaptive algorithms robust to impulsive noise and with low computational cost are presented. Unlike other approaches, no cost functions or filtering of the gradient are considered in order to update the filter coefficients. Its initial basis is the basic LMS algorithm and its sign-error variant. The proposed algorithms can be considered as some sign-error variants of the LMS algorithm. The algorithms are successfully tested in terms of accuracy and convergence in a standard system identification simulation in which an impulsive noise is present. Simulations show that they improve the performance of LMS variants that are robust to impulsive noise.
Survival prediction in patients undergoing ischemic cardiopathy
The ischemic cardiopathy is the main cause of death in developed countries. New improved drugs and therapies have appeared last years. However, the interventionist strategy and the most powerful drugs may have complications, and hence, it is very important to know the risk of death associated with patients during their stay in the hospital, or in the next six months. Thus, it is possible to tune the best treatment for each individual patient. In this framework, the use of artificial neural networks is proposed with a double objective: survival prediction and the extraction of the parameters with best predictive capabilities. A cohort of 691 patients treated in the Hospital Clinic, in Barcel…