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Intrusion detection systems have been around for quite some time, to protect systems from inside ad outside threats. Researchers and scientists are concerned on how to enhance the intrusion detection performance, to be able to deal with real-time attacks and detect them fast from quick response. One way to improve performance is to use minimal number of features to define a model in a way that it...
Truly, heart is successor to the brain in being the most significant vital organ in the body of a human. Heart, being a magnificent pump, has his performance orchestrated via a group of valves and highly sophisticated neural control. While the kinetics of the heart is accompanied by sound production, sound waves produced, by the heart, are reliable diagnostic tools to check heart activity. Chronologically,...
Texture is considered as one of the most crucial image features used commonly in computer vision. It is important source of information about image content, especially for single-band images. In this paper we present the results of research carried out to assess the usefulness of selected textural features of different groups in panchromatic very high resolution (VHR) satellite image classification...
In the recent years, the Global Positioning System (GPS) has become a standard for the location and navigation for a huge number of people all over the world. This system is unquestionably one of the most significant developments of the twentieth century. GPS employs a great variety of applications from car navigation and cellular phone emergency positioning even to aeronautic positioning. Despite...
This paper discusses factors influencing accuracy of estimating localization of radio networks terminals in indoor environment. It introduces parameters that can be useful to describe the quality of localization of radio landmarks. The paper presents a software for computer aided reference radio stations placement inside the buildings and shows the results of exemplary simulations carried out with...
In this paper an extension for multi-stroke character recognition of FUzzy BAsed handwritten character Recognition (FUBAR) algorithm will be presented. First the basic concept of a single-stroke version will be overviewed; in the second part of the paper the new version of the algorithm with multi-stroke symbol support will be introduced, which deploy the same algorithm overviewed in the first part...
Cattle identification receives a great research attention as an important way to maintain the livestock. The identification accuracy and the processing time are two key challenges of any cattle identification methodology. This paper presents a robust and fast cattle identification scheme from muzzle print images using local invariant features. The presented scheme compensates some weakness of ear...
We report on experiments that demonstrate the relevance of our AntiSocial Behavior (ASB) corpus as a machine learning resource to detect antisocial behavior from text. We first describe the corpus and then, by using the corpus for training machine learning algorithms, we build a set of binary classifiers. Experimental evaluations revealed that classifiers built based on the ASB corpus produce reliable...
The advance of high-throughput techniques, such as gene microarrays and protein chips have a major impact on contemporary biology and medicine. Due to the high-dimensionality and complexity of the data, it is impossible to analyze it manually. Therefore machine learning techniques play an important role in dealing with such data. In this paper we propose to use a one-class approach to classifying...
In this paper, we suggest an inspired architecture by brain emotional processing for classification applications. The architecture is a type of ensemble classifier and is referred to as ‘emotional learning-inspired ensemble classifier’ (ELiEC). In this paper, we suggest the weighted k-nearest neighbor classifier as the basic classifier of ELiEC. We evaluate the ELiEC's performance by classifying some...
Binary classifiers are grouped into an ensemble to solve multi-class problems. One of proposed ensemble structure is a directed acyclic graph. In this structure, a classifier is created for each pair of classes. The number of classifiers can be reduced if groups of classes will be separated instead of individual classes. The proposed method is based on the similarity of classes defined as a distance...
The aim of this paper is to present a prototype LocNet API programming interface for indoor positioning systems and a prototype LocFusion API interface enabling joint use of terminal positioning data from mobile operator's GMLC and the LocNet API. The use of data from complementary information sources can improve the accuracy of user terminal positioning in large buildings, where coverage of satellite...
Location based services (LBS) are considered very relevant for the users of mobile networks. All local events and facts related to area nearby seem to be more important that others which happen in remote places. Localization data is used in all types of services: weather, traffic, tourist info, etc. One of its most important (and regulated by law) applications is providing persons location in case...
The combination of game theory and data mining opens new directions and opportunities for developing novel methods for extraction of knowledge among multiple collaborative agents. This paper extends on this combination, and motivated by the work of Nix and Kantarcioglu employs the Vickrey-Clarke-Groves (VCG) mechanism to achieve privacy-preserving collaborative classification. Specifically, in addition...
Spam detection based on flow-level statistics is a new approach in anti-spam techniques. The approach reduces number of collected data but still can obtain relative good results in a spam detection task. The main problems in the approach are selection of flow-level features that describe spam and detection of discrimination rules. In this work, flow-level model of spam is presented. The model describes...
Liver cancer is one of the major death factors in the world. Transplantation and tumor resection are two main therapies in common clinical practice. Both tasks need image assisted planning and quantitative evaluations. An efficient and effective automatic liver segmentation is required for corresponding quantitative evaluations. Computed Tomography (CT) is highly accurate for liver cancer diagnosis...
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