Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis

Parkinson’s disease is found as a progressive neurodegenerative condition which affects motor circuit by the loss of up to 70% of dopaminergic neurons. Thus, diagnosing the early stages of incidence is of great importance. In this article, a novel chaos-based stochastic model is proposed by combining the characteristics of chaotic firefly algorithm with Kernel-based Naïve Bayes (KNB) algorithm for diagnosis of Parkinson’s disease at an early stage. The efficiency of the model is tested on a voice measurement dataset that is collected from “UC Irvine Machine Learning Repository.” The dynamics of chaos optimization algorithm will enhance the firefly algorithm by introducing six types of chao…

Translingual text mining for identification of language pair phenomena

Translingual Text Mining (TTM) is an innovative technology of natural language processing for building multilingual parallel corpora, processing machine translation, contextual knowledge acquisition, information extraction, query profiling, language modeling, contextual word sensing, creating feature test sets and for variety of other purposes. The Keynote Lecture will discuss opportunities and challenges of this computational technology. In particular, the focus will be made on identification of language pair phenomena and their applications to building holistic language model which is a novel tool for processing machine translation, supporting professional translations, evaluation of tran…

Weight Adaptation Stability of Linear and Higher-Order Neural Units for Prediction Applications

This paper is focused on weight adaptation stability analysis of static and dynamic neural units for prediction applications. The aim of this paper is to provide verifiable conditions in which the weight system is stable during sample-by-sample adaptation. The paper presents a novel approach toward stability of linear and higher-order neural units. A study of utilization of linear and higher-order neural units with the foundations on stability of the gradient descent algorithm for static and dynamic models is addressed.

Contextual neural-network based spectrum prediction for cognitive radio

Cognitive radio is the technique of effective electromagnetic spectrum usage important for future wireless communication including 5G networks. Neural networks are nature-inspired computational models used to solve cognitive radio prediction problems. This paper presents the use of contextual Sigma-if neural network in prediction of channel states for cognitive radio. Our results indicate that Sigma-if neural network confirms better predictions than Multilayer Perceptron (MLP) network and decreases sensing time for the benefit of the increase of the effectiveness of e-m spectrum usage.

Prediction of Highly Non-stationary Time Series Using Higher-Order Neural Units

Adaptive predictive models can use conventional and nonconventional neural networks for highly non-stationary time series prediction. However, conventional neural networks present a series of known drawbacks. This paper presents a brief discussion about this concern as well as how the basis of higher-order neural units can overcome some of them; it also describes a sliding window technique alongside the batch optimization technique for capturing the dynamics of non-stationary time series over a Quadratic Neural Unit, a special case of higher-order neural units. Finally, an experimental analysis is presented to demonstrate the effectiveness of the proposed approach.

Rough Set Theory for Optimization of Packet Management Mechanism in IP Routers

Bandwidth and consequently optimum overall efficiency of network system relies greatly on mechanism of packet management in IP routers. Our research objective is to implement rough set theory to minimizing number of the network system attributes responsible for decision making in selection of those packets, which improve its transmission. Such an approach is called priority queuing system model, as we assign priority to the packets selected, following rough set theory. Regardless of the file format, for all the routers, packets are transmitted in sequence one-by-one. Nonetheless, quality of streaming data largely depends on how much the packet loss is minimized, or eliminated at all, if pos…

Rough Set Theory for Supporting Decision Making on Relevance in Browsing Multilingual Digital Resources

Browsing digital library (DL) collections seems to pose a challenge for a user owning to the number of factors like for instance, operability of the system, interface readability or clarity, and retrieval efficiency directly related to it, or the number of digital items within the user’s domain. However, when it comes to searching for an item in a foreign language to the user, the number of the factors arises even more which translates proportionally to the growing number of clicks aimed to retrieve the target item. Such a procedure usually leads to disheartening the user from browsing the digital collections. Our study into the user’s behavior interacting with multilingual DL system is set…

Extraction of Medical Terms for Word Sense Disambiguation within Multilingual Framework

All the languages belonging to the same language family have a certain number of the common characteristics called language pair phenomena, which can be found quite useful for processing them for multilingual purposes like translation across the cognate languages, building dictionaries, thesauri, transcript collections, or for multilingual text retrieval of digital documents. In addition, it is estimated that more than 30% of English vocabulary has been inherited from Latin, which has dominated medical terminology in particular. We use this fact by exploring word sense disambiguation (WSD) in multilingual environment. Specifically in the medical domain, language pair phenomena can be limite…

PORE Algorithm for Object Recognition in Photo Layers based on Parametric Characteristics of the Object Edges

PORE stands for Photo-Object Recognition based on the Edges. Coincidentally, PORE means to examine something carefully and with due attention, so "we pore over the object layers in search for information about their characteristics with the aim at improving image recognition process". Therefore, this study presents a novel approach to object recognition based on the pattern by using photo layers and by defining the objects' specific characteristics. We select and introduce the parameters which determine a higher efficiency of image retrieval of the image objects. In this paper, we describe how the same photos are recognized in a process of classical retrieval compared to our model by analyz…

Computer networks stability independence of the queuing delays

Communication in intelligent computer networks is an indispensible attribute of the dataflow quality in Web traffic. We propose a model that investigates intelligent computer networks stability while specifying its limits. Packet queuing delay affects the performance of the network, and especially its stability. If the network is presented as a dynamic system in block diagram form, we compute a transfer function and determine the quasi-polynomial system. The characteristic polynomial distribution of zeros of complex variable quasi-plane determines the boundaries of the network stability. The approach relies on estimation of the network system's transfer functions and its quasi-polynomial. C…

Particle Swarm Optimization as a New Measure of Machine Translation Efficiency

The present work proposes a new approach to measuring efficiency of evolutionary algorithm-based Machine Translation. We implement some attributes of evolutionary algorithms performing cosine similarity objective function of a Particle Swarm Optimization (PSO) algorithm then, we evaluate an English text set for translation precision into the Spanish text as a simulated benchmark, and explore the backward process. Our results show that PSO algorithm can be used for translation of multiple language sentences with one identifier only, in other words the technology presented is language-pair independent. Specifically, we indicate that our cosine similarity objective function improves the veloci…

Security framework for dynamic service-oriented IT systems

The paper proposes a framework for dynamic service-oriented IT systems security. We review the context of service-oriented architecture (SOA), which constitutes a paradigm of dynamic system configuration including security constraints at the system module development stage, supporting with the domain-driven resources, carrying out routine SOA maintenance and implementing XML-compatible parsing technologies in order to improve the system performance. Likewise, we discuss the fundamental differences between security management systems with traditional centralized and monolithic architecture and service-oriented IT systems from the perspective of security-related issues. Web services security …

Current communication technologies in language processing

Even the most cutting-edge communication-mediated technology like satellite navigation for orbit positioning, pedestrian movement recognition systems based on inertial sensors, 5G systems, let alone medical devices for coordination of human organs functionality would not be invented without technologies for language processing as an information source between humans and communication systems. Regardless of the way we communicate that is via emails, website short tweets, video conferencing systems, social networking, blogs, instant messaging through websites or mobile applications, or texting only, we use a language that is processed by computer system. Thus, the keynote paper discusses lang…

Access to eHealth language-based services for multinational patients

In more and more countries the number of citizens with double nationality is growing substantially. In their developing stage, current eHealth technologies are oriented towards helping the native patients rather than those speaking a foreign language that limits an access to the medical care. Nowadays, most people search the web for the medical symptoms of their disorders before going to the General Practitioner (GP), however multinational patients have limited chance to access eHealth care services not only owning to the lack of medical knowledge, but specifically due to their language barriers. In this study we investigate eHealth services on multilingual information access and online com…

Source-Target Mapping Model of Streaming Data Flow for Machine Translation

Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building automatic translation system that facilitates processing any of various abstract entities which combine to specify underlying phonological, morphological, semantic and syntactic properties of linguistic forms and that act as the targets of linguistic rules and operations in a source language foll…

Analysis of dynamic service oriented systems for security related problems detection

The paper presents an approach to solve some problems arising in the management process of IT security. Our motivation of this research is to study in every detail the context of service oriented systems, which can be defined as considerable heterogeneous, dynamic and flexible configuration of the hardware and software system resources. The fundamental difference between security management systems with traditional centralized and monolithic architecture and service oriented systems is discussed. We propose a multilayered-reference model for service-oriented systems aimed predominantly at principal objectives related to IT based systems security working in dynamic environments. Likewise, co…

Stability of Positive Systems in WSN Gateway for IoT&IIoT

Modern sensor networks work on the basis of intelligent sensors and actuators, their connection is carried out using conventional or specifically dedicated networks. The efficiency and smooth transmission of such a network is of great importance for the accuracy of measurements, sensor energy savings, or transmission speed. Ethernet in many networks is typically based on the TCP/IP protocol suite. Regardless of whether or not the network transmission is wired or wireless, it should always be reliable. TCP ensures transmission reliability through retransmissions, congestion control and flow control. But TPC is different in networks based on the UDP protocol. The most important here is the tr…

Predicting the Short-Term Exchange Rate Between United State Dollar and Czech Koruna Using Hilbert-Huang Transform and Fuzzy Logic

In this paper, the combination of the Hilbert-Huang Transform, fuzzy logic and an embedding theorem is described to predict the short-term exchange rate from United States dollar to Czech Koruna. By Using the Hilbert-Huang Transform as an adaptive filter, the proposed method decreases the embedding dimension space from five (original samples) to four (de-noising samples). This dimension space provides the number of inputs to the fuzzy rule base system, which causes the number of rules, the time for training and the inference process to decrease. Experimental results indicated that this method achieves higher accuracy prediction than the direct use of original data.

Non Linear Fitting Methods for Machine Learning

This manuscript presents an analysis of numerical fitting methods used for solving classification problems as discriminant functions in machine learning. Non linear polynomial, exponential, and trigonometric models are mathematically deduced and discussed. Analysis about their pros and cons, and their mathematical modelling are made on what method to chose for what type of highly non linear multi-dimension problems are more suitable to be solved. In this study only deterministic models with analytic solutions are involved, or parameters calculation by numeric methods, which the complete model can subsequently be treated as a theoretical model. Models deduction are summarised and presented a…

Context-sensitive text mining with fitness leveling Genetic Algorithm

Contextual processing is a great challenge for information retrieval study - the most approved techniques include scanning content of HTML web pages, user supported metadata analysis, automatic inference grounded on knowledge base, or content-oriented digital documents analysis. We propose a meta-heuristic by making use of Genetic Algorithms for Contextual Search (GACS) built on genetic programming (GP) and custom fitness leveling function to optimize contextual queries in exact search that represents unstructured phrases generated by the user. Our findings show that the queries built with GACS can significantly optimize the retrieval process.

Post-search query modeling in federated web scenario

As opposed to query reformulation oriented towards changes made by a user to specify the information need more precisely, a post-search query modeling is a technique of exploiting syntax variation of gradually extended query which depending on some other factors like e.g. the resource, database or the key word alignment, facilitates the searching process. The study into modeling query submitted to some search engines that utilize different translation semantic paradigms is motivated by a real-world's challenges to retrieve heterogeneous textual documents from the web. For a couple of language pairs, we develop a user-centered framework for imposing the Hidden Web traffic optimization. In li…

Information Streaming Systems: A Review

Ubiquitous nature of information determines continuous decision making always based on its stream coming from the environment, not only in the human, but also in the animal world. Communication between the users of information system is a fundamental concept for acquiring, showing, spreading, sharing and constantly increasing the knowledge about the circumstances under which they are in need to make a move all alone as well as while working in groups. In this paper, we review information stream-based systems on amount of information acceptable to facilitate the process of decision making, also in multilingual settings. We analyze the information system objects and the resource management cy…

Lecture Notes in Real-Time Intelligent Systems

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…

Metadata-Oriented Language Model in Translingual Retrieval of Digital Data

Translingual retrieval relies on processing a source language to retrieve digital document content in a target language. From the perspective of successful browsing digital catalogues, probability of retrieving the full text document in a language other than the query language is close to zero owning to the fact that it is not only the library collection, but especially a problem of matching the index terms with the query keywords which are assumed to be their translation equivalents. In addition, hardly any digital library system is incorporated with a translation component. As a result, such a matching is rather coincidental. Our approach to the translingual document retrieval problem is …

Adaptive Threshold, Wavelet and Hilbert Transform for QRS Detection in Electrocardiogram Signals

This paper combines Hilbert and Wavelet transforms and an adaptive threshold technique to detect the QRS complex of electrocardiogram signals. The method is performed in a window framework. First, the Wavelet transform is applied to the ECG signal to remove noise. Next, the Hilbert transform is applied to detect dominant peak points in the signal. Finally, the adaptive threshold technique is applied to detect R-peaks, Q, and S points. The performance of the algorithm is evaluated against the MIT-BIH arrhythmia database, and the numerical results indicated significant detection accuracy.

Interactive Gradually Generating Relevance Query Refinement Under the Human-Mediated Scenario in Multilingual Settings

As opposed to query modelling, relevance generating interactive query refinement (QR) is a technique aimed at exploiting syntax variations of gradually extended, being removed or replaced with some other keywords query, which depending on the factors like e.g. the information resource, the database structure, or the keyword alignment, facilitates significantly the searching process. Therefore our motivation is to explore the dynamism of the precision trend depended upon the factors analyzed. For a couple of language pairs which constitute multilingual settings, we develop a user-centred framework that imposes distributed search optimization. Our data set contains variety of query types subm…

Modelling swarm-intelligent systems for medical applications

Modeling swarm intelligent systems has attracted attention of researchers over the last decade, as the attributes such as self-organization, self-regulation or collective behavior exhibited by the system entities while following a certain set of rules, can be implemented with the aim at investigating complexity of the problems that an individual would be unable to tackle in real world. In this keynote paper, meta-heuristics and paradigms of modeling swarm-intelligent systems will be discussed with respect to their application areas for medical purposes.

Computer-assisted clinical diagnosis in the official European union languages

eHealth services integrate Web Information Retrieval and Intelligent Medical Decision Support for health care professionals based on the range of possible symptoms which a patient reports. However, many symptoms like high temperature, fever, or headache, are ambiguous in terms of suggesting wide variety of possible patient's conditions to the GP, while other symptoms are mutually dependant, which again can be misleading to make an accurate diagnosis. On the other hand, doctor's up-to-date knowledge on the medicaments, drugs, active medical substances included, anticipated range of diseases relating to the symptoms reported, and the most reliable pharmaceutical manufacturers, are of the grea…

Design and implementation of a data acquisition system for r peak detection in electrocardiograms

Message from the chairs

Sensitivity of Estimators for Measuring Information Amount in Web-Based Medical Documents

Nowadays, communication between patient and doctor during an appointment has changed significantly owning to the opportunity that medical portals provide. Whether or not necessarily appreciated by the doctors, the patients became more aware of the first symptoms’ suggesting a particular disease and the medical procedures that apply as a standard. Estimating amount of reliable factual medical information in a document is carried out by parametrizing space of digital documents and dividing it into subsequent layers that represent distribution of the system responses computed as random variables to a query about medical information. Analyzed are the following attributes: dynamism of decrease o…

Context-related data processing in artificial neural networks for higher reliability of telerehabilitation systems

Classification is a data processing technique of a great significance both for native eHealth systems and web telemedicine solutions. In this sense, artificial neural networks have been widely applied in telerehabilitation as powerful tools to process information and acquire a new medical knowledge. But effective analysis of multidimensional heterogeneous medical data, still poses considerable difficulties. It was shown that processing too many data features simultaneously is costly and has some adverse effects on the resulting models classification properties. Therefore, there is a strong need to develop new techniques for selecting features from the very large data sets that include many …