Search results for "Pattern"
showing 10 items of 4203 documents
Connection between temperature, larval production, virulence and geographical distribution of Rhipidocotyle parasites infecting the duck mussel, Anod…
2015
In this thesis, two bucephalid trematode parasites Rhipidocotyle campanula and R. fennica, which use the same first (Anodonta anatina) and second intermediate (Rutilus rutilus) host were studied. The aim was to investigate the effect of temperature on one of the key processes in the transmission of these parasites: 1) the emergence of cercarial larvae from A. anatina over short (1 h) and 2) long (throughout the annual cercarial shedding period, from May to October) time periods as well, as on 3) mussel survival and 4) the seasonal timing of cercarial release. In addition, the aim was to study how the cercarial shedding traits are linked to the 5) geographical occurrence and abundance of the…
Intruder Pattern Identification
2008
This paper considers the problem of intrusion detection in information systems as a classification problem. In particular the case of masquerader is treated. This kind of intrusion is one of the more difficult to discover because it may attack already open user sessions. Moreover, this problem is complex because of the large variability of user models and the lack of available data for the learning purpose. Here, flexible and robust similarity measures, suitable also for non-numeric data, are defined, they will be incorporated on a one-class training K N N and compared with several classification methods proposed in the literature using the Masquerading User Data set (www.schonlau.net) repr…
Bot recognition in a Web store: An approach based on unsupervised learning
2020
Abstract Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to the problem of bot and human session classification, with a specific application to e-commerce. The approach studied in this work explores the use of unsupervised learning (k-means and Graded Possibilistic c-Means), followed by supervised labelling of clusters, a generative learning stra…
CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study
2020
Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric magnetic resonance imaging (MRI), which provides both morphologic and functional information pertaining to the pathological regions. Along with whole prostate gland segmentation, distinguishing between the central gland (CG) and peripheral zone (PZ) can guide toward differential diagnosis, since the frequency and severity of tumors differ in these regions; however, their boundary is often weak and fuzzy. This work presents a preliminary study on deep learning to automatically delineate the CG and PZ, aiming at evaluating the generalization ability o…
Peptide classification using optimal and information theoretic syntactic modeling
2010
Accepted version of an article published in the journal: Pattern Recognition. Published version available on Sciverse: http://dx.doi.org/10.1016/j.patcog.2010.05.022 We consider the problem of classifying peptides using the information residing in their syntactic representations. This problem, which has been studied for more than a decade, has typically been investigated using distance-based metrics that involve the edit operations required in the peptide comparisons. In this paper, we shall demonstrate that the Optimal and Information Theoretic (OIT) model of Oommen and Kashyap [22] applicable for syntactic pattern recognition can be used to tackle peptide classification problem. We advoca…
On the pattern recognition and classification of stochastically episodic events
2012
Published version of a chapter published in the book: Transactions on Compuational Collective Intelligence VI. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-29356-6_1 Researchers in the field of Pattern Recognition (PR) have traditionally presumed the availability of a representative set of data drawn from the classes of interest, say ω 1 and ω 2 in a 2-class problem. These samples are typically utilized in the development of the system’s discriminant function. It is, however, widely recognized that there exists a particularly challenging class of PR problems for which a representative set is not available for the second class, which has motivated a great deal of…
Methodology for the estimation of the increase in time loss due to future increase in tropical cyclone intensity in Japan
2009
Published version of an article from the journal: Climatic Change. The original publication is available at Spingerlink. http://dx.doi.org/10.1007/s10584-009-9725-9 The present paper develops a methodology for estimating the risks and consequences of possible future increases in tropical cyclone intensities that would allow policy makers to relatively quickly evaluate the cost of different mitigation strategies. The methodology simulates future tropical cyclones by modifying the intensity of historical tropical cyclones between the years 1978 and 2007. It then uses a Monte Carlo Simulation to obtain the expected number of hours that a certain area can expect to be affected by winds of a giv…
Mathematical modeling of a vehicle crash test based on elasto-plastic unloading scenarios of spring-mass models
2011
Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher on SpringerLink: htp://dx.doi.org/10.1007/s00170-010-3056-x This paper investigates the usability of spring which exhibit nonlinear force-deflection characteristic in the area of mathematical modeling of vehicle crash. We present a method which allows us to obtain parameters of the spring-mass model basing on the full-scale experimental data analysis. Since vehicle collision is a dynamic event, it involves such phenomena as rebound and energy dissipation. Three different spring unloading scenarios (elastic, plastic, and elasto-plastic) are covered…
A novel active contour model for unsupervised low-key image segmentation
2013
Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0050-0 Unsupervised image segmentation is greatly useful in many vision-based applications. In this paper, we aim at the unsupervised low-key image segmentation. In low-key images, dark tone dominates the background, and gray level distribution of the foreground is heterogeneous. They widely exist in the areas of space exploration, machine vision, medical imaging, etc. In our algorithm, a novel active contour model with the probability density function of gamma distribution is proposed. The flexible gamma distribution gives a bet…
Investigation of vehicle crash modeling techniques: theory and application
2013
Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…