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The paper presents application of a transfer learning-based, deep neural network classification model to the brain-computer interface EEG data. The model was initially trained on the publicly available dataset of motor imagery EEG data gathered ...

The field of biometrics is currently an area that is both very interesting as well as rapidly growing. Among various types of behavioral biometrics, human gait recognition is worthy of particular attention. Unfortunately, one issue which is ...

The advancement in biological and medical image acquisitions has allowed the development of numerous investigations in different fields supported by image analysis, from cell to physiological level. The complexity in the treatment of data, ...

Driver drowsiness is one of major causes of growing number of road accidents. To combat this problem car makers install their proprietary and expensive driver alert systems. In this paper an analogous system based on an opensource machine learning ...

The work presents a method that allows delimiting the borders of allophones in isolated English words. The described method is based on the DTW algorithm combining two signals, a reference signal and an analyzed one. As the reference signal, ...

A new method of the synthesis of finite state machines is proposed. In this method, the speed of FSM is taken into account already at the early stage of synthesis process. The method is based on sequential merging and splitting two internal states ...

The Internet of Things (IoT) is growing in popularity in recent years. With the increasing use, security threats are also becoming a bigger concern, especially considering new challenges, like limited computational power, low storage capacity and ...

A few years ago blockchain technology was used in cryptocurrency. Nowadays, a variety of diverse areas are seeing the benefits of applying this technological approach to their needs. One way transactions without reverse mode is making blockchain a ...

The synthesis method of high-speed finite state machines (FSMs) in field programmable gate arrays (FPGAs) based on LUT (Look Up Table) by internal state splitting is offered. Estimations of the number of LUT levels are presented for an ...

The business decisions at different levels require processing different kinds of information. In this regard, the usage of suitable tools will contribute to making effective business decisions. The described framework of the business intelligence ...

The recent advances in ICT and increased market competition make the problem of business decisions more significant and more complex. This is related to the performance evaluation of a variety of business decisions that have multi-level and multi-...

Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming model (MIP) based on the ...

The paper addresses the inventory control problem in logistic networks with complex, mesh-type interconnection structure. Contrary to the majority of previously analyzed models, the considered topology does not assume any simplifications nor ...

The success of any project lies in a great manner on keeping costs in the estimated values, as well as meeting customer required due date. Therefore, there is a current need of developing an information system that facilitates the creation and ...

Six sigma has been used in different industries to reach operational excellence. However, in the chemical industry, the application of this methodology is limited. This research presents an implementation of the six sigma method for ammonium ...

Within companies of the construction sector, the evaluation and selection of concrete suppliers, is considered a fundamental topic for the adequate construction of buildings, due to the impact it has, not only in the stability of the building but ...

Representation learning algorithms have recently led to a significant progress in knowledge extraction from network structures. In this paper, a representation learning framework for the medical diagnosis domain is proposed. It is based on a ...

There is a huge problem in public health around the world called severe maternal morbidity (SMM). It occurs during pregnancy, delivery, or puerperium. This condition establishes risk for babies and women lives since it’s earlier detection isn’t ...

With the constant development of neural networks, traditional algorithms relying on data structures lose their significance as more and more solutions are using AI rather than traditional algorithms. This in turn requires a lot of correctly ...

In the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We ...

Assessment of cognitive workload level is important to understand human mental fatigue, especially in the case of performing intellectual tasks. The paper presents a case study on binary classification of cognitive workload levels. The dataset was ...

Disorder Attention Deficit/Hyperactivity Disorder, or ADHD, is recognized as one of the pathologies of high prevalence in children and adolescents from the global environment population; this disorder generates visible symptoms usually diminish ...

In this study, we focus on the problem of a breast cancer diagnosis using mammography images by classifying them as belonging either to a negative or to a malignant mass class. We explore the potential of densely connected convolutional neural ...

This paper presents a method for augmenting the motion capture trajectories to improve generalization performance of recurrent long short-term memory (LSTM) neural networks. The presented algorithm is based on the interpolation of existing time ...