Dog face detection using yolo network

This work presents the real-world application of the object detection which belongs to one of the current research lines in computer vision. Researchers are commonly focused on human face detection. Compared to that, the current paper presents a challenging task of detecting a dog face instead that is an object with extensive variability in appearance. The system utilises YOLO network, a deep convolution neural network, to predict bounding boxes and class confidences simultaneously. This paper documents the extensive dataset of dog faces gathered from two different sources and the training procedure of the detector. The proposed system was designed for realization on mobile hardware. This Doggie Smile application helps to snapshot dogs at the moment when they face the camera. The proposed mobile application can simultaneously evaluate the gaze directions of three dogs in scene more than 13 times per second, measured on iPhone XR. The average precision of the dogface detection system is 0.92. © 2020, Brno University of Technology. All rights reserved

Improving CT image tumor segmentation through deep supervision and attentional gates

Computer Tomography (CT) is an imaging procedure that combines many X-ray measurements taken from different angles. The segmentation of areas in the CT images provides a valuable aid to physicians and radiologists in order to better provide a patient diagnose. The CT scans of a body torso usually include different neighboring internal body organs. Deep learning has become the state-of-the-art in medical image segmentation. For such techniques, in order to perform a successful segmentation, it is of great importance that the network learns to focus on the organ of interest and surrounding structures and also that the network can detect target regions of different sizes. In this paper, we propose the extension of a popular deep learning methodology, Convolutional Neural Networks (CNN), by including deep supervision and attention gates. Our experimental evaluation shows that the inclusion of attention and deep supervision results in consistent improvement of the tumor prediction accuracy across the different datasets and training sizes while adding minimal computational overhead. © Copyright © 2020 Turečková, Tureček, Komínková Oplatková and Rodríguez-Sánchez.Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2020/001]; COST (European Cooperation in Science Technology) [CA15140]; program Projects of Large Research, Development, and Innovations Infrastructures [e-INFRA LM2018140

Maximizing vector distances using differential evolution - Relation to data redundancy

This paper studies how redundant data affect maximizing of weighted distances of vectors in a set of vectors. To maximize distances differential evolution is used, because the problem does not have analytical solution and is complex. This paper at first describes suppressing of redundant data mathematically and then it checks this theoretical result in two experiments practically. As a result it was found that both experiments are in correspondence with theory

Deductions from a Sub-Saharan African bank’s tweets: A sentiment analysis approach

The upsurge in social media websites has in no doubt triggered a huge source of data for mining interesting expressions on a variety of subjects. These expressions on social media websites empower firms and individuals to discover varied interpretations regarding the opinions expressed. In Sub-Saharan Africa, financial institutions are making the needed technological investments required to remain competitive in today’s challenging global business environment. Twitter as one of the digital communication tools has in recent times been integrated into the marketing communication tools of banks to augment the free flow of information. In this light, the purpose of the present study is to perform a sentiment analysis on a large dataset of tweets associated with the Ecobank Group, a prominent pan-African bank in sub-Saharan Africa using four different sentiment lexicons to determine the best lexicon based on its performance. Our results show that Valence Aware Dictionary and sEntiment Reasoner (VADER) outperforms all the other three lexicons based on accuracy and computational efficiency. Additionally, we generated a word cloud to visually examine the terms in the positive and negative sentiment categories based on VADER. Our approach demonstrates that in today’s world of empowered customers, firms need to focus on customer engagement to enhance customer experience via social media channels (e.g., Twitter) since the meaning of competitive advantage has shifted from purely competing over price and product to building loyalty and trust. In theory, the study contributes to broadening the scope of online banking given the interplay of consumer sentiments via the social media channel. Limitations and future research directions are discussed at the end of the paper. © 2020, © 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.Tomas Bata University in Zlin [IGA/CebiaTech/2020/001

Mathematical model of an integrated circuit cooling through cylindrical rods

One of the main challenges in integrated circuits development is to propose alternatives to handle the extreme heat generated by high frequency of electrons moving in a reduced space that cause overheating and reduce the lifespan of the device. The use of cooling fins offers an alternative to enhance the heat transfer using combined a conduction-convection systems. Mathematical model of such process is important for parametric design and also to gain information about temperature distribution along the surface of the transistor. In this paper, we aim to obtain the equations for heat transfer along the chip and the fin by performing energy balance and heat transfer by conduction from the chip to the rod, followed by dissipation to the surrounding by convection. Newton's law of cooling and Fourier law were used to obtain the equations that describe the profile temperature in the rod and the surface of the chip. Ordinary differential equations were obtained and the respective analytical solutions were derived after consideration of boundary conditions. The temperature along the rod decreased considerably from the initial temperature (in contatct with the chip surface). This indicates the benefit of using a cilindrical rod to distribute the heat generated in the chip.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the project CEBIA [CZ.1.05/2.1.00/03.0089]; Grant Agency of the Czech Republic [GACR 588 P103/15/06700S]; Internal Grant Agency of Tomas Bata University in Zlin [IGA/CebiaTech/2016/007]; National Council for Science and Technology (CONACYT) in Mexico; Council for Science and Technology of the State of Guanajuato (CONCYTEG) in Mexic

Chaos enhanced differential evolution in the task of evolutionary control of selected set of discrete chaotic systems

Evolutionary technique differential evolution (DE) is used for the evolutionary tuning of controller parameters for the stabilization of set of different chaotic systems. The novelty of the approach is that the selected controlled discrete dissipative chaotic system is used also as the chaotic pseudorandom number generator to drive the mutation and crossover process in the DE. The idea was to utilize the hidden chaotic dynamics in pseudorandom sequences given by chaotic map to help differential evolution algorithm search for the best controller settings for the very same chaotic system. The optimizations were performed for three different chaotic systems, two types of case studies and developed cost functions.Web of Science2014art. no. 83648

Selecting start-up businesses in a public Venture capital financing using Fuzzy PROMETHEE

Public Venture Capital financing often fail rigorous scrutiny in their selection of high-potential start-ups as compared to Private Venture capital. In some developing countries, decision making on final selection for financial support of early stage but high potential Small and Medium sized Enterprises (SMEs) are often 'clouded' by several factors including consideration of political party affiliations. This results in low capital recovery rate and a mischance in choosing deserving start-ups. This paper applies Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (Fuzzy PROMETHEE) method to evaluate and select early-stage but high potential start-up businesses in a government high priority area such as in Information and Communications Technology. A numerical example with pre-defined linguistic terms parameterized by triangular fuzzy numbers is provided. The framework could serve as a useful tool for decision makers in scrutinizing selection of start-ups in other government priority areas. © 2015 The Authors. Published by Elsevier B.V.MSMT-7778/2014, NPU, Northwestern Polytechnical Universit

A time performance comparison of particle swarm optimization in mobile devices

This paper deals with the comparison of three implementations of Particle Swarm Optimization (PSO), which is a powerful algorithm utilized for optimization purposes. Xamarin, a cross-platform development software, was used to build a single C# application capable of being executed on three different mobile operating systems (OS) devices, namely Android, iOS, and Windows Mobile 10, with native level performance. Seven thousand tests comprising PSO evaluations of seven benchmark functions were carried out per mobile OS. A statistical evaluation of time performance of the test set running on three similar devices each running a different mobile OS is presented and discussed. Our findings show that PSO running on Windows Mobile 10 and iOS devices have a better performance in computation time than in Android.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Grant Agency of the Czech Republic-GACR [588 P103/15/06700S]; Internal Grant Agency of Tomas Bata University in Zlin [IGA/CebiaTech/2016/007

Robotic automation of software testing from a machine learning viewpoint

The need to scale software test automation while managing the test automation process within a reasonable time frame remains a crucial challenge for software development teams (DevOps). Unlike hardware, the software cannot wear out but can fail to satisfy the functional requirements it is supposed to meet due to the defects observed during system operation. In this era of big data, DevOps teams can deliver better and efficient code by utilizing machine learning (ML) to scan their new codes and identify test coverage gaps. While still in its infancy, the inclusion of ML in software testing is a reality and requirement for coming industry demands. This study introduces the prospects of robot testing and machine learning to manage the test automation process to guarantee software reliability and quality within a reasonable timeframe. Although this paper does not provide any particular demonstration of ML-based technique and numerical results from MLbased algorithms, it describes the motivation, possibilities, tools, components, and examples required for understanding and implementing the robot test automation process approach. © 2021, Brno University of Technology. All rights reserved.IGA/CebiaTech/2021/00

Controlling complexity

Complex systems and dynamics are present in many parts of daily life and branches of science. This participation is continuation of our previous research, that introduced a novelty method of visualization and possible control of complex networks, that are used to visualize dynamics of evolutionary algorithms. Selected evolutionary algorithms are used as an example in order to show how its behavior can be understood as complex network and controlled via conversion into CML system - a model based on mutually joined nonlinear n equations. The main aim of this investigation was to show that dynamics of evolutionary algorithms can be converted to CML system and then controlled. Selected results of evolutionary controlled CML system are discussed here. © 2012 American Institute of Physics