Search results for "computer.software_genre"
showing 10 items of 3858 documents
Rough Pragmatic Description Logic
2013
In this chapter, a rough description logic is built on the basis of a pragmatic standpoint of representation of knowledge. The pragmatic standpoint has influenced the acceptance of a broader definition of the semantic network than that appearing in the literature. The definition of the semantic network is a motivation of the introduced semantics of the language of the descriptive logic. First, the theoretical framework of representation of knowledge that was proposed in the papers [24,25] is adjusted to the description of data processing. The pragmatic system of knowledge representation is determined, as well as situations of semantic adequacy and semantic inadequacy for represented knowled…
Modellierung überbetrieblicher behandlungsprozesse durch objekt-petrinetze
2005
Clinical processes are often performed by the cooperation of different healthcare organization. But even that for modeling of such processes the object Petri nets can be used, they often lack of intuitive comprehensibility. This contribution presents an interpretation of object Petri nets which assigns abstract net elements to real objects of the healthcare domain. By doing this it helps domain user to apply this Petri net type to the modeling of clinical processes. The application of this approach is demonstrated.
Linear Regression Analysis
2010
SUMMARY Background: Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. Methods: This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. Results: After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the resul…
An Intra-Subject Approach Based on the Application of HMM to Predict Concentration in Educational Contexts from Nonintrusive Physiological Signals in…
2021
Previous research has proven the strong influence of emotions on student engagement and motivation. Therefore, emotion recognition is becoming very relevant in educational scenarios, but there is no standard method for predicting students’ affects. However, physiological signals have been widely used in educational contexts. Some physiological signals have shown a high accuracy in detecting emotions because they reflect spontaneous affect-related information, which is fresh and does not require additional control or interpretation. Most proposed works use measuring equipment for which applicability in real-world scenarios is limited because of its high cost and intrusiveness. To tackle this…
Predicting lorawan behavior. How machine learning can help
2020
Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…
A data aggregation strategy based on wavelet for the internet of things
2017
The advent of emerging information and communication technologies, such as RFID, small size sensors and sensor networks, has made accessible a huge amount of information that requires sophisticated and efficient search algorithms to support queries on that data. In this paper we focus on the problem of aggregating data collected from these devices to efficiently support queries, inferences or statistics on them. In general, data aggregation techniques are necessary to efficiently collect information in a compact and cost-effective way. Some current solutions try to meet the above criteria, by exploiting different data aggregation techniques, for instance BitVector or Q_Digest. In this manus…
Lecture Notes in Real-Time Intelligent Systems
2018
Intelligent computing refers greatly to artificial intelligence with the aim at making computer to act as a human. This newly developed area of real-time intelligent computing integrates the aspect of dynamic environments with the human intelligence. This book presents a comprehensive practical and easy to read account which describes current state-of-the art in designing and implementing real-time intelligent computing to robotics, alert systems, IoT, remote access control, multi-agent systems, networking, mobile smart systems, crowd sourcing, broadband systems, cloud computing, streaming data and many other applications areas. The solutions discussed in this book will encourage the resear…
Capturing citizens — Emerging needs: Using social networks in smart cities
2017
In order to reach its objectives, smart cities (or whatever kind of smart urban environment) should be underpinned by complex cyber physical systems (CPS) able to discover needs and services and "smartly" combine them. Services may be thought as services offered by software components, of whatever nature, for instance software, bot, robot, app and so on. Searching for the best service depends on the need of the citizen(s) and also on the type of (smart) environment the citizens are in. Analysis and design of CPSs are more challenging than the only physical or the only cyber system. We propose a design paradigm shift towards runtime for identifying requirements of cyber physical systems for …
A relevance feedback CBIR algorithm based on fuzzy sets
2008
CBIR (content-based image retrieval) systems attempt to allow users to perform searches in large picture repositories. In most existing CBIR systems, images are represented by vectors of low level features. Searches in these systems are usually based on distance measurements defined in terms of weighted combinations of the low level features. This paper presents a novel approach to combining features when using multi-image queries consisting of positive and negative selections. A fuzzy set is defined so that the degree of membership of each image in the repository to this fuzzy set is related to the user's interest in that image. Positive and negative selections are then used to determine t…
P2PRealm - Peer-to-Peer Network Simulator
2006
Peer-to-peer realm (P2PRealm) is an efficient peer-to-peer network simulator for studying algorithms based on neural networks. In contrast to many simulators, which emphasize on detailed network simulation, the speed of simulation in P2PRealm is essential, because neural networks require a time consuming training phase. Efficiency has been obtained by optimizing training loops inside the simulator, using Java native interface (JNI) as well as distributing the simulator to hundreds of workstations using the P2PDisCo platform. In this paper we describe the architecture of P2PRealm and its input/output interfaces. Also, we present the mechanisms used for internally optimizing the implementatio…