Vol. 26, No. 2

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Now showing 1 - 5 of 7
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    The Classification of Documents in Malay and Indonesian Using the Naive Bayesian Method Uses Words and Phrases as a Training Set
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-12-21) Wijaya, Marvin Chandra
    Malay Language and Indonesian Language are two closely related languages, sharing a lot in common in the meanings of words and grammar. Classifying the two languages automatically using a tool is a challenge because the two languages are very similar. The classification method that is widely used today is the Naive Bayesian method. This method needs to be implemented in a particular way to increase the level of classification accuracy. In this study, a new method was used, by using a training set in the form of words and phrases instead of just using a training set in the form of words only. With this method, the level of classification accuracy of the two languages is increased.
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    Phase Transition as an Emergent Phenomenon Analysed by Violation of Structural Invariant (M, BM)
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-12-21) Bila, Jiri; Reshak, Ali H; Chysky, Jan
    When modeling complex systems, we usually encounter the following difficulties: partiality, large amounts of data and uncertainty of conclusions. The most common approach used for modeling is the physical approach, sometimes reinforced by statistical procedures. If we assume emergences in the complex system, a physical approach is not appropriate at all. Instead, we build here the approach of structural invariants. In this paper, we show that another plane can be built above the plane of physical description, which is responsible for violation of structural invariants. Main attention is concentrated (in this article) on the invariant matroid and bases of matroid (M, BM) in combination with Ramsey graph theory. In addition, the article introduces a calculus that describes the emergent phenomena using two quantities - the power of the emergent phenomenon and the complexity of the structure of the considered complex system. We show the application of the method for modeling phase transition in chemistry.
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    Assessing Factors Affecting Intention to Adopt AI and ML: The Case of the Jordanian Retail Industry
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-12-21) Alghamdi, Mohammed I.
    Aim: The aim of this research is to evaluate the factors that affect the adoption intention of AI and ML in the context of Jordan’s retail industry. Method: For this research paper, primary data was collected with the help of surveying different retail companies that are operational in Jordan with a sample of 400 participants. The survey questionnaire was based on a Likert scale where five points ranging from strongly agree to strongly disagree were provided to the participants. Structural Equation Modelling (SEM) used to analyse the impact and significance of the different factors on the adoption of AI and ML in Jordanian retail sector. Results: It has been concluded from this research paper that communication, government regulations, market structure, and technological infrastructure are important factors that influence the adoption of AI and ML in the retail industry of Jordan. However, the results of this research have pointed out that managerial support and vendor relationship do not have a significant influence on the adoption of AI and ML. Limitations: The scope of the research is restricted to the context of the retail industry only. This research has been carried out in the context of Jordan thus it cannot be applied on to other geographical backgrounds. Due to the time and scope limitations, there are restricted factors considered in the framework.
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    Cardiac Arrhythmia Prediction by Adaptive Analysis via Bluetooth
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-12-21) Rodrguez-Jorge, Ricardo; Bila, Jiri
    In this work, the development of a data acquisition system for adaptive monitoring based on a dynamic quadratic neural unit is presented. Acquisition of the continuous signal is achieved with the BITalino biomedical data acquisition card. The system is trained sample-by-sample with a real time recurrent learning method. Then, possible cardiac arrhythmia is predicted by implementing the adaptive monitoring in real time to recognize patterns that predict cardiac arrhythmia up to 1 second in advance. For the evaluation of the interface, tests are performed using the obtained signal in real time
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    Why Tuning the Control Parameters of Metaheuristic Algorithms Is So Important for Fair Comparison?
    (Institute of Automation and Computer Science, Brno University of Technology, 2020-12-21) Kazikova, Anezka; Pluhacek, Michal; Senkerik, Roman
    Although metaheuristic optimization has become a common practice, new bio-inspired algorithms often suffer from a priori ill reputation. One of the reasons is a common bad practice in metaheuristic proposals. It is essential to pay attention to the quality of conducted experiments, especially when comparing several algorithms among themselves. The comparisons should be fair and unbiased. This paper points to the importance of proper initial parameter configurations of the compared algorithms. We highlight the performance differences with several popular and recommended parameter configurations. Even though the parameter selection was mostly based on comprehensive tuning experiments, the algorithms' performance was surprisingly inconsistent, given various parameter settings. Based on the presented evidence, we conclude that paying attention to the metaheuristic algorithm's parameter tuning should be an integral part of the development and testing processes.