2021-07-25
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Signal Processing For Vocal Recognition Of Sturnus Vulgaris
Budáč, Adam
This paper describes the issue of sturnus vulgaris detection in the vineyards in order toscare these animals more effectively. The analysis and classification of bird singing is difficultbecause many problems can appear. One of the problems is background noise e.g. sounds of cars,trees, and also the singing of various bird species at once. Another problem is different types of birdsongs. For example, an alarm melody, search for food, and also communication between the birdsduring a flight. This article presents a solution to one of these problems in case when only audiorecordings are available.
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2021-07-25
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2021-07-25
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Universal Security Solution For Iot Data Collection Systems
Trchalík, Mirek ; Paluřík, Michal
The article presents our data collection solution based on RIOT operating system andMessage Queuing Telemetry Transport (MQTT) technology. Our solution is secure, universal, andeasy to integrate to already existing and often insecure IoT networks. Furthermore, we integrated oursolution into the temperature and humidity monitoring system. This system detects the potentiallydangerous level of these physical quantities and warns users by smartphone notification about relevantthreats such as the impact on the infectivity of COVID-19.
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2021-07-25
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Detection Of Road Surface Defects From Data Acquired By A Laser Scanner
Benešová, Petra
Research in the field of automatic detection of road surface defects has been relativelywidespread in recent years. Most of the existing works solve this issue by processing the imageacquired by camera technology. The contribution of this study is the proposal of the LRS-CNN algorithmfor the detection of defects on road surfaces based on their laser scans. The advantage ofLRS-CNN is the ability to detect so-called microcracks, which can not be recognized from camerarecordings. We have also found that transfer learning methods are not suitable for the use of road defectdetection from their laser scans. Our LRS-CNN algorithm has been trained on unique nonpublicdata and is able to achieve up to 99.33% of success depending on the type of task.
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2021-07-25
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Web Server Security Analyzation Tool
Touš, Filip
Nowadays it is common practice to have a securely hosted web server. To have a secureweb server it is required to ensure that CIA (Confidentiality, Integrity, Availability) triad is in place.CIA triad is fulfilled by using different mechanisms like symmetric cryptography and public keyinfrastructure. These mechanisms on the other side use a set of algorithms and parameters. Thispaper focuses on the automation of analyzing the security of these algorithms, parameters and alsovulnerability testing.
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2021-07-25
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Identification Of Sleep/Wake Stages In Actigraphy Data Utilising Gradient Boosting Algorithm
Misiurev, Denis
Sleep disorders are early markers of various serious diseases that can be treated moreeffectively when diagnosed in their prodromal stage. Actigraphy is a noninvasive sleep monitoringmethod for the detection of sleep patterns and determination of sleep parameters that could support thediagnosis of these disorders. This study aims to compare a newly proposed actigraphy-based methodof sleep/wake detection with a conventional one in terms of consistency with a polysomnography(PSG) reference. 55 recordings (acquired in 28 subjects) of actigraphy and PSG were modelled by aheuristics-based method and by a new approach utilising a gradient boosting algorithm. In addition,another database (22 subjects, 150 recordings) was used to compare scores of the new method withdata reported in sleep diaries. The proposed method achieves 89% accuracy and Mathews correlationcoefficient equal to 0.75 when compared to the polysomnography reference. Such results outperformthe ones provided by the heuristic technique. The newly proposed method has good consistency withthe PSG reference, thus being a good alternative to the golden standard in sleep disorders assessment,especially in decentralised clinical trials.
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2021-07-25
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The Application Of Tempo Calculation For Musicological Purposes
Šmatlo, Filip
Beat tracking systems capture time positions of beats within digital recordings. Theyare used, for example, in streaming portals, but applications in the musicological analysis are oftenneglected. In this article, two different methods of beat tracking systems are tested—conventionaland the state-of-the-art—on the specific motif of a string quartet music, which is one of the mostcomplex tasks for beat detectors in general. The aim here is to determine which system is better formusicology purposes. This often involves determining not only the position of individual beats andestimating the tempo but also the accuracy of determining their number. Evaluation analysis maybe suitable for comparing the accuracy of detectors, but may not necessarily reflect the requirementsof musicological analysis. The results of selected detectors show that a system based on a recurrentneural network seems to be the most suitable.
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2021-07-25
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2021-07-25
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2021-07-25
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