The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Traffic congestion in metropolitan areas has become more and more serious. Over the past decades, many academic and industrial efforts have been made to alleviate this problem, among which providing accurate, timely and predictive traffic conditions is a promising approach. Nowadays, online open data have rich traffic related information. Typical such resources include official websites of traffic...
In this paper, a framework using deep learning approach is proposed to identify two subtypes of human colorectal carcinoma cancer. The identification process uses information from gene expression and clinical data which is obtained from data integration process. One of deep learning architecture, multimodal Deep Boltzmann Machines (DBM) is used for data integration process. The joint representation...
The number of publications, along with the organization of new conferences are a couple of the relevant elements that usually indicate the progress of an area of study over the years. This is definitely true in the case of the Enterprise Architecture (EA) discipline, which went from having its first journal article published in 1989 to over two hundred published articles by 2015. But in spite of this...
Policy-based concept and service-oriented design are two promising techniques in network management. In this paper we show that integrating policy-based management with service-oriented design can significantly improve the autonomic and flexible capabilities for management. In particular, we propose an architecture that covers policy modeling, specification and enforcement in a service-oriented manner...
The transportation sector, and in particularly intelligent transportation systems, generate large volumes of real-time data that needs to be managed, communicated, interpreted, aggregated, and analyzed. To this end, innovative big data processing and mining as well as optimization techniques, need to be developed and applied in order to support real-time decision-making capabilities. Towards this...
Modern smartphones integrate multiple functionalities into a single device: they can establish peer-to-peer wireless links, they can sense the environment through several embedded sensors, they are provided with a multi-core CPU. Hence, they can play a crucial role on emergency scenarios, where there is need of acquiring data from the environment, processing, and quickly conveying them to the people...
Venn & Euler diagrams are well-defined mathematical diagram types, which are the major representation methods of Set Theory. Although understanding of different diagram types such as charts and coordinate graphs has been addressed, no research has been done for Venn and Euler diagram interpretation from an image. Venn and Euler Diagrams exist in various media types such as printed format in books,...
The goal of this paper is to create a hybrid system based on a Multi-Agent Architecture that will investigate the evolution of some prediction strategies (Elliott Wave, Lucas, GANN) along with technical, fundamental and macro-economical analysis methods on stock market indexes and how this information influences the stock market behavior in order to improve the profitability on a short or medium time...
In this paper, we describe Semantic Bookworm — a tool that supports scholarly text analysis. In contrast to the text-based Bookworm tool, the Semantic Bookworm identifies semantic concepts.
Big data processing and analytics technologies have drawn much attention in recent years. However, the recent explosive growth of online data streams brings new challenges to the existing technologies. These online data streams tend to be massive, continuously arriving, heterogeneous, time-varying and unbounded. Therefore, it is necessary to have an integrated approach to process both big static data...
In the paper, the deep evolving neural network and its learning algorithms (in batch and on-line mode) are proposed. The deep evolving neural network's architecture is developed based on Group Method of Data Handling approach and Least Squares Support Vector Machines with fixed number of the synaptic weights. The proposed system is simple in computational implementation, characterized by high learning...
Since several years, there is an increasing interest for new services based on the analysis of data coming from online social networks. Such services can, for example, provide the e-reputation of a product or a company, detect new trends in a commercial, social or political context, etc. The huge quantity of data is an opportunity in term of representativeness but is also difficult to manage. Within...
Modern transport systems rely on an increasing number of sensors to control their operation including orientation, speed, arrival and departure times, fuel consumption, passenger count etc. These have become important parts of the echo system with their availability and performance playing a key role in daily commuting. However, they produce data in high volume and frequency that need to be processed...
Data-Driven Software Reliability Modeling (DDSRM) is an approach in software reliability prediction problem which only relies on software failure data. There are two kinds of model architecture in this modeling, which are Single-Input Single-Output (SISO) and Multiple-Delayed-Input Single-Output (MDISO). In MDISO architecture, the prediction process involves having multiple inputs from the failure...
Research papers are often referred by researchers. But finding the desired or relevant research paper quickly and accurately is very difficult. As there are lot of research papers in given dataset and keeps enormously increasing. There is a need to avail automated processing approach for tackling such a huge volume of dataset to retrieve relevant papers accurately. This paper proposes a framework...
The term Big Data, refers to sizably voluminous data whose volume, variability, and velocity make it very arduous to manage, process or analyzed. To analyze this sizably voluminous kind of data Hadoop will be utilized. However, Processing is very time-consuming. To resolve this quandary & to decrement replication time one solution is to executing the job partially, where an approximate, early...
The use of digital games in education is already a reality, but their use in this area has been hampered by the lack of consolidated resources for evaluation of game-based learning. This paper reports a computational architecture for learning analytics in game-based learning that is based on relational analysis and data mining of data containing evidences of learning collected during the game play...
Due to its ability to solve nonlinear problems, Artificial Neural Network (ANN) could be applied in several areas of life. However, defining its architecture for solving a given problem is not formalized and remains an open research problem. On the other hand the complexity of such a technique due to its “black box” aspect, makes its interpretation more tedious. Since optimal factors completely cover...
Episode pattern mining is a very powerful technique to get high-valued information for people to solve real-life cross-disciplinary problems, such as for the analysis of manufacturing, stock markets, weather records and so on. As data grows, the mining process must be re-triggered again and again to obtain the most updated information. However, periodically re-mining the full dataset is not cost-effective,...
Big Data technologies enable new possibilities to analyze historical data generated by process plants. One possible application is the development of new types of operator support systems (OSS), which could help plant operators during operations in identifying and dealing with critical situations. The project FEE has the objective to develop such support functions based on Big Data analytics of historical...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.