Search results for "computer.software_genre"
showing 10 items of 3858 documents
Evaluating Classifiers for Mobile-Masquerader Detection
2006
As a result of the impersonation of a user of a mobile terminal, sensitive information kept locally or accessible over the network can be abused. The means of masquerader detection are therefore needed to detect the cases of impersonation. In this paper, the problem of mobile-masquerader detection is considered as a problem of classifying the user behaviour as originating from the legitimate user or someone else. Different behavioural characteristics are analysed by designated one-class classifiers whose classifications are combined. The paper focuses on selecting the classifiers for mobile-masquerader detection. The selection process is conducted in two phases. First, the classification ac…
Personalized distance learning based on multiagent ontological system
2004
The paper presents architecture of a personalized distance learning system based on multiagent technology and ontological modelling of students' profiles. Delocalization of a student data in the system is achieved by software agents, which assumed to be distributed at different platforms. These platforms operate as separate Web services and use the ACL (agent communication language) for the data transfer. In this paper the algorithm is proposed, according to which the multiagent ontological system for personalized distance learning (MOSPDL) solves the tasks of distant learning process automation, which assume utilization of the ontological models of students' and learning resources' profile…
Introduction to the Minitrack on Software Development for Mobile Devices, the Internet-of-Things, and Cyber-Physical Systems
2021
On the Generalizability of Programs Synthesized by Grammar-Guided Genetic Programming
2021
Grammar-guided Genetic Programming is a common approach for program synthesis where the user’s intent is given by a set of input/output examples. For use in real-world software development, the generated programs must work on previously unseen test cases too. Therefore, we study in this work the generalizability of programs synthesized by grammar-guided GP with lexicase selection. As benchmark, we analyze proportionate and tournament selection too. We find that especially for program synthesis problems with a low output cardinality (e.g., a Boolean output) lexicase selection overfits the training cases and does not generalize well to unseen test cases. An analysis using common software metr…
Smart Technologies for Improved Software Maintenance
2015
Steadily increasing complexity of software systems makes them difficult to configure and use without special IT knowledge. One of the solutions is to improve software systems making them “smarter”, i.e. to supplement software systems with features of self-management, at least partially. This paper describes several software components known as smart technologies, which facilitate software use and maintenance. As to date smart technologies incorporate version updating, execution environment testing, self-testing, runtime verification and business process execution. The proposed approach has been successfully applied in several software projects.
A Framework for Component Reuse in a Metamodelling-Based Software Development
2001
A Case Study of Open Source Software Development in Proteomic Area: The LIMS ePims
2008
The objective of this paper is to provide an illustrative feedback on development of Open Source software among several partners. We describe the first stage of the design of a specific software package, namely a customized Laboratory Information Management System (LIMS) for biology applications. This software package is structured in several modules which are reusable and can be customized for other applications. In this paper, we address the problem of multi-licensing for the same software tools due to the participation of several partners, the reuse of code source, and the subsequent distribution of this produced software.
Methods for optimal shape design of electrical devices
1996
Often the primary problem facing designers of structural systems is determining the shape of the structure. In spite of graphical work stations and modern software for analyzing the structure, finding the best geometry for the structure by “trial and error” is still a very tedious and timeconsuming task. The goal in optimal shape design (structural optimization, or redesign) is to computerize the design process and therefore shorten the time it takes to design new products or improve the existing design. Structural optimization is already used in many applications in industry. In general, however, structural optimization is just beginning to penetrate the industrial community. Integrating F…
A Support Vector Machine Signal Estimation Framework
2018
Support vector machine (SVM) were originally conceived as efficient methods for pattern recognition and classification, and the SVR was subsequently proposed as the SVM implementation for regression and function approximation. Nowadays, the SVR and other kernel‐based regression methods have become a mature and recognized tool in digital signal processing (DSP). This chapter starts to pave the way to treat all the problems within the field of kernel machines, and presents the fundamentals for a simple, framework for tackling estimation problems in DSP using support vector machine SVM. It outlines the particular models and approximations defined within the framework. The chapter concludes wit…
Learning Bayesian Metanetworks from Data with Multilevel Uncertainty
2006
Managing knowledge by maintaining it according to dynamic context is among the basic abilities of a knowledge-based system. The two main challenges in managing context in Bayesian networks are the introduction of contextual (in)dependence and Bayesian multinets. We are presenting one possible implementation of a context sensitive Bayesian multinet-the Bayesian Metanetwork, which implies that interoperability between component Bayesian networks (valid in different contexts) can be also modelled by another Bayesian network. The general concepts and two kinds of such Metanetwork models are considered. The main focus of this paper is learning procedure for Bayesian Metanetworks.