Janusz Gajda

Bio: Janusz Gajda is an academic researcher from AGH University of Science and Technology. The author has contributed to research in topics: Weigh in motion & Axle load. The author has an hindex of 14, co-authored 53 publications receiving 572 citations.

A vehicle classification based on inductive loop detectors

Abstract: The class of vehicle is one of more important parameters in the process of road traffic measurement. Up to now, strip piezoelectric sensors and video systems have been used. The use of very cheap inductive loop detectors for vehicle classification is also possible. Such vehicle classification systems are based on magnetic profiles recorded from inductive loops. The magnetic profile is sensitive to the loop dimensions. This paper presents a discussion concerning the influence of loop length (in direction of vehicle movement) on differences between characteristics describing the magnetic profiles of the vehicles belonging to the different classes. As characteristics describing the magnetic profile of the vehicle have been used: magnetic profiles in time domain (normalized in amplitude), probability density function and magnetic profiles in vehicle length domain. For real time applications, the conversion of the measured signal into a vector of numerical parameters (a few only) is also proposed. The influence of loop dimensions on a chosen signal parameter was investigated. The case of extremely short loop (10 cm), which allows detection of the number of axles, was also analyzed.

Acoustic Analysis Assessment in Speech Pathology Detection

Abstract: Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis PCA, kernel principal component analysis kPCA and an auto-associative neural network NLPCA in four kinds of pathology detection hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis using the a, i and u vowels, spoken at a high, low and normal pitch. The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient

Voice data mining for laryngeal pathology assessment

Abstract: The aim of this study was to evaluate the usefulness of different methods of speech signal analysis in the detection of voice pathologies. Firstly, an initial vector was created consisting of 28 parameters extracted from time, frequency and cepstral domain describing the human voice signal based on the analysis of sustained vowels /a/, /i/ and /u/ all at high, low and normal pitch. Afterwards we used a linear feature extraction technique (principal component analysis), which enabled a reduction in the number of parameters and choose the most effective acoustic features describing the speech signal. We have also performed non-linear data transformation which was calculated using kernel principal components. The results of the presented methods for normal and pathological cases will be revealed and discussed in this paper. The initial and extracted feature vectors were classified using the k-means clustering and the random forest classifier. We found that reasonably good classification accuracies could be achieved by selecting appropriate features. We obtained accuracies of up to 100% for classification of healthy versus pathology voice using random forest classification for female and male recordings. These results may assist in the feature development of automated detection systems for diagnosis of patients with symptoms of pathological voice. HighlightsWe examined pathological changes in the speech signal of vowels /a/, /i/ and /u/.Various methods of voice signal analysis were examined to detect voice pathologies.Selected features have the influence on detection accuracies of pathological voice.100% voice pathology detection is achievable using Random Forest algorithm.

Application of inductive loops as wheel detectors

Abstract: This article presents the findings of model and field research into narrow inductive loop used as vehicle wheels detector in normal traffic conditions. The efficiency of the solution was compared with that of strip, polymeric piezoelectric detectors. The findings confirmed that narrow inductive loops can be successfully applied as wheel detectors.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Regularization Of Inverse Problems

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Random Data Analysis And Measurement Procedures

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Brenner and Rector's The Kidney

Abstract: Brenner and Rector's The Kidney , edited by Barry Brenner, remains a classic reference in the field of renal diseases. For 20 years, each new edition of this comprehensive text has described all aspects of nephrology from basic science to clinical diagnosis and therapy. The fifth edition has surpassed the others in size and content. Overall, the new two-volume set has more than 2700 pages, 35 000 references (many recent), and more than 12 000 illustrations and tables. Now, there are more than 120 internationally distingushed contributors. The editor has added new chapters, many involving basic research, and has updated and expanded others. All the while, the authors have maintained the clear and well-organized style and format of previous editions. The first volume consists of two sections. Section one covers normal renal anatomy and physiology. There are new chapters on embryology, cellular biology, and biochemistry. Other chapters review current knowledge on