The paper introduces a new randomized sampling-based method of motion planning suitable for the problem of narrow passages. The proposed method was inspired by the method of exit points for cavities in protein models and is based on the Rapidly Exploring Random Tree (RRT). Unl...

A natural method to evaluate the effectiveness of a testing technique is to measure the defect detection rate when applying the created test cases. Here, real or artificial software defects can be injected into the source code of software. For a more extensive evaluation, inje...

This paper summarizes findings related to the problematics of glottis detection in video sequences obtained by medical examination of vocal cords by high speed videolaryngoscopy (HSV). The glottis detection is based on cluster analysis method K-means which complements the existing set of...

Brief description of a method based on computing correlation between parameters for vocal cords recorded by high speed video camera. This method gives us possibility to analyze vocal cords kinematics and tries to evaluate specific vocal cords based on statistical data.

In this paper, two efficient communication protocols for distributed road traffic simulation, which we developed during our previous research, are compared. These protocols – the Long Step (LS) protocol and the Long Step Binary (LSB) protocol – reduce the inter-process communication using&#x...

In this paper, we describe our method for detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora,chosen from different time periods, for English, German, Latin, and Swedish. Our method was created&#...

This paper deals with multi-lingual dialogue act (DA) recognition. The proposed approaches are based on deep neural networks and use word2vec embeddings for word representation. Two multi-lingual models are proposed for this task. The first approach uses one general model trained on the...

Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns. However, the ubiquity of massive continuously generated data streams poses an enormous challenge...

With increasing amounts of experimental data, openness, fairness, and reproducibility of scientific experimental work have become important factors for researchers, journals and funding bodies. However, these kinds of challenges are not easily and directly achievable. The goal of this paper is&#x...

In this paper, we are presenting a method and a tool that allows detecting duplicity in the heap dump of a Java application, based on the shallow and deep object comparison. The tool allows to identify the problematic instances in the memory and thus helps programmers...

Diabetic patient desires to avoid hypo- and hyperglycemic episodes, which result from insufficient insulin production. As the diabetes disease progresses, it requires an advance control of external insulin administration with an insulin pump. Given the importance of blood-glucose level prediction ...

As the number of digitized archival documents increases very rapidly, named entity recognition (NER) in historical documents has become very important for information extraction and data mining. For this task an annotated corpus is needed, which has up to now been missing for Czech...

Continuous EEG activity in the measured subjects includes different patterns depending on what activity the subject performed. ERD and ERS are examples of such patterns related to movement, for example of a hand, finger or foot. This article deals with the detection of motion b...

In this paper, we describe our method for detection of lexical semantic change (i.e.,word sense changes over time) for the DIACR-Ita shared task, where we ranked 1st. We examine semantic differences between specific words in two Italian corpora, chosen from different time periods. ...

A machine learning-based method for blood glucose level prediction thirty and sixty minutes in advance based on highly multiclass classification (as opposed to the more traditional regression approach) is proposed. An advantage of this approach is the possibility of modelling and visualising...

Both approximation and interpolation are techniques commonly used in many scientific areas. Many approaches are depending on input data type, result purpose etc. Input data can be formed in a mesh or not (meshless/meshfree data). This contribution is oriented on meshless data appro...

This paper describes a real-time simulation of muscle movement that is based on inverse kinematics where bone placement is known apriori and muscle shape is calculated by a modified position-based dynamics (PBD) method. The method is comparable and competitive with the others, moreover,...

This contribution presents a new formulation of Plücker coordinates using geometric algebra and standard linear algebra with projective representation. The Plücker coordinates are usually used for a line representation in space, which is given by two points. However, the line can be als...

They are many risk factors decreasing overall human physical and cognitive performance and increasing incidence of chronic diseases. It is very beneficial for any society to map, discuss and cope with these factors. This can be supported and evaluated by designing, developing, testing&#...

Over the past few years, ontology merging, and ontology semantic alignment has gained significant interest as research topics in automotive application domain for finding solutions to semantic data heterogeneity. To accomplish the complex and novel vehicle service requirements such as autonomous&...