Search results for "Software engineering"
showing 10 items of 1151 documents
Digitization and Preservation of Cultural Heritage Products
2017
Cultural heritage encompasses various aspects of a nation's history. Cultural heritage artifacts are considered as priceless items that need special care. Since the wide adoption of new digital technologies, documenting and storing cultural heritage assets became more affordable and reliable. These records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. They are considering cultural heritage artifacts as products, and the history behind them as a product lifecycle. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advan…
A Generic Architectural Model Approach for Efficient Utilization of Patterns
2015
A software pattern describes the core of the solution to a problem that tends to (re-)occur in a particular environment. Such patterns are commonly used as a means to facilitate the creation of an architectural design satisfying the desired quality goals. In this chapter, the practical challenges of efficient usage of patterns in domain-specific software development are presented. The specific domain considered here is the mobile domain, for which is given a sample collection of potentially useful patterns. After that, a novel generic architectural model approach for organizing patterns is presented. In this approach, the identification of relevant patterns is considered as the process of r…
Agent-Oriented Captology for Anthropocentric Systems
2001
Abstract Considering that anthropo centric systems are an adequate domain for captological approaches, and that interface agents are most natural interactants for the humans involved, the paper presents a broad-spectrum generic architectural framework to support developing flexible interfaces for industrial applications, based on synergetic correlation between persuasive technologies and polymorphic agents. The design space for agent-oriented captology is defined and several of its main dimensions are elaborated upon. The main mechanisms used are dynamic priorities, "flexible cloning" and fuzzy temporal windows. Some agent-oriented test-bench applications instantiating the generic architect…
RTS2 - the Remote Telescope System
2010
RTS2 is an open source observatory manager. It was written from scratch in the C++ language, with portability and modularity in mind. Its driving requirements originated from quick follow-ups of Gamma Ray Bursts. After some years of development it is now used to carry tasks it was originally not intended to carry. This article presents the current development status of the RTS2 code. It focuses on describing strategies which worked as well as things which failed to deliver expected results. Copyright © 2010 Petr Kubánek.
Artificial Intelligence for Cybersecurity: A Systematic Mapping of Literature
2020
Due to the ever-increasing complexities in cybercrimes, there is the need for cybersecurity methods to be more robust and intelligent. This will make defense mechanisms to be capable of making real-time decisions that can effectively respond to sophisticated attacks. To support this, both researchers and practitioners need to be familiar with current methods of ensuring cybersecurity (CyberSec). In particular, the use of artificial intelligence for combating cybercrimes. However, there is lack of summaries on artificial intelligent methods for combating cybercrimes. To address this knowledge gap, this study sampled 131 articles from two main scholarly databases (ACM digital library and IEEE…
Neural Networks as Soft Sensors: a Comparison in a Real World Application.
2006
Physical atmosphere parameters, as temperature or humidity, can be indirectly estimated on the surface of a monument by means of soft sensors based on neural networks, if an ambient air monitoring station works in the neighborhood of the monument itself. Since the soft sensors work as virtual instruments, the accuracy of such measurements has to be analyzed and validated from statistical and metrological points of view. The paper compares different typologies of neural networks, which can be used as soft sensors in a complex real world application: a non invasive monitoring of the conservation state of old monuments. In this context, several designed connessionistic systems, based on radial…
Educational Software Based on Matlab GUIs for Neural Networks Courses
2016
Neural Networks (NN) are one of the most used machine learning techniques in different areas of knowledge. This has led to the emergence of a large number of courses of Neural Networks around the world and in areas where the users of this technique do not have a lot of programming skills. Current software that implements these elements, such as Matlab®, has a number of important limitations in teaching field. In some cases, the implementation of a MLP requires a thorough knowledge of the software and of the instructions that train and validate these systems. In other cases, the architecture of the model is fixed and they do not allow an automatic sweep of the parameters that determine the a…
Efficient MLP Digital Implementation on FPGA
2005
The efficiency and the accuracy of a digital feed-forward neural networks must be optimized to obtain both high classification rate and minimum area on chip. In this paper an efficient MLP digital implementation. The key features of the hardware implementation are the virtual neuron based architecture and the use of the sinusoidal activation function for the hidden layer. The effectiveness of the proposed solutions has been evaluated developing different FPGA based neural prototypes for the High Energy Physics domain and the automatic Road Sign Recognition domain. The use of the sinusoidal activation function decreases hardware resource employment of about 32% when compared with the standar…
Improving the Competency of Classifiers through Data Generation
2001
This paper describes a hybrid approach in which sub-symbolic neural networks and symbolic machine learning algorithms are grouped into an ensemble of classifiers. Initially each classifier determines which portion of the data it is most competent in. The competency information is used to generated new data that are used for further training and prediction. The application of this approach in a difficult to learn domain shows an increase in the predictive power, in terms of the accuracy and level of competency of both the ensemble and the component classifiers.
3D Matrix-Based Visualization System of Association Rules
2017
With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …