Analysis of the applicability of singlemode optical fibers for measurement of deformation with distributed systems BOTDR

Distributed optical fiber sensors allow monitoring physical effects across the whole cable. The paper presents results obtained from the performed tests and shows that single mode fibers can provide analyses of the deformation changes, when distributed optical systems BOTDR used. We used standard optical fiber G.652.D with primary and secondary protected layers and specialized cable SMC-V4 designed for this purpose. The aim was to compare the deformation sensitivity and determine which fiber types are the best to use. We deformed the fiber in the longitudinal and transverse directions and mechanically stressed in orthogonal directions to find how to localize optical fibers. They could be deployed in real use. For achieving optimal results of mechanical changes and acting forces, sensor fibers have to be located carefully

Encapsulation of FBG sensor into the PDMS and its effect on spectral and temperature characteristics

Fiber Bragg Grating (FBG) is the most distributed type of fiber-optic sensors. FBGs are primarily sensitive to the effects of temperature and deformation. By employing different transformation techniques, it is possible to use FBG to monitor any physical quantity. To use them as parts of sensor applications, it is essential to encapsulate FBGs to achieve their maximum protection against external effects and damage. Another reason to encapsulate is increasing of sensitivity to the measured quantity. Polydimethylsiloxane (PDMS) encapsulation appears to be an interesting alternative due to convenient temperature and flexibility of the elastomer. This article describes an experimental proposal of FBG PDMS encapsulation process, also providing an analysis of the FBG spectral characteristics and temperature sensitivity, both influenced by high temperature and the process of polydimethylsiloxane curing itself. As for the PDMS type, Sylgard 184 was employed. Encapsulation consisted of several steps: allocation of FBG to PDMS in its liquid state, curing PDMS at the temperature of 80°C ± 5 %, and a 50-minute relaxation necessary to stabilize a Bragg wavelength. A broadband light source and an optical spectrum analyzer were both used to monitor the parameters during the processes of curing and relaxation. Presented results imply that such a method of encapsulation does not have any influence on the structure or functionality of the FBG. At the same time, a fourfold increase of temperature sensitivity was monitored when compared to a bare FBG

A weather forecast model accuracy analysis and ECMWF enhancement proposal by neural network

This paper presents a neural network approach for weather forecast improvement. Predicted parameters, such as air temperature or precipitation, play a crucial role not only in the transportation sector but they also influence people's everyday activities. Numerical weather models require real measured data for the correct forecast run. This data is obtained from automatic weather stations by intelligent sensors. Sensor data collection and its processing is a necessity for finding the optimal weather conditions estimation. The European Centre for Medium-Range Weather Forecasts (ECMWF) model serves as the main base for medium-range predictions among the European countries. This model is capable of providing forecast up to 10 days with horizontal resolution of 9 km. Although ECMWF is currently the global weather system with the highest horizontal resolution, this resolution is still two times worse than the one offered by limited area (regional) numeric models (e.g., ALADIN that is used in many European and north African countries). They use global forecasting model and sensor-based weather monitoring network as the input parameters (global atmospheric situation at regional model geographic boundaries, description of atmospheric condition in numerical form), and because the analysed area is much smaller (typically one country), computing power allows them to use even higher resolution for key meteorological parameters prediction. However, the forecast data obtained from regional models are available only for a specific country, and end-users cannot find them all in one place. Furthermore, not all members provide open access to these data. Since the ECMWF model is commercial, several web services offer it free of charge. Additionally, because this model delivers forecast prediction for the whole of Europe (and for the whole world, too), this attitude is more user-friendly and attractive for potential customers. Therefore, the proposed novel hybrid method based on machine learning is capable of increasing ECMWF forecast outputs accuracy to the same level as limited area models provide, and it can deliver a more accurate forecast in real-time.Web of Science1923art. no. 514

Network degradation effects on different codec types and characteristics of video streaming

Nowadays, there is a quickly growing demand for the transmission of voice, video and data over an IP based network. Multimedia, whether we are talking about broadcast, audio and video transmission and others, from a global perspective is growing exponentially with time. With incoming requests from users, new technologies for data transfer are continually developing. Data must be delivered reliably and with the fewest losses at such high speed. Video quality as part of multimedia technology has a very important role nowadays. It is influenced by several factors, where each of them can have many forms and processing. Network performance is the major degradation effect that influences the quality of resulting image. Poor network performance (lack of link capacity, high network load…) causes data packet losses or different delivery time for each packet. This work focuses exactly on these network phenomena. It examines the impact of different delays and packet losses on the quality parameters of triple play services, to evaluate the results using objective methods. The aim of this work is to bring a detailed view on the performance of video streaming over IP-based networks

Impact of H.264/AVC and H.265/HEVC compression standards on the video quality for 4K resolution

This article deals with the impact of H.264/AVC and H.265/HEVC compression standards on the video quality for 4K resolution. In the first part a short characteristic of both compression standards is written. The second part focuses on the well-known objective metrics which were used for evaluating the video quality. In the third part the measurements and the experimental results are described

Prediction model of triple play services for QoS assessment in IP based networks

This paper brings a QoS (Quality of Service) assessment model which can estimate voice and video quality. Based on the proposed model, speech or video quality is computed with regard to congestion management QoS configuration in the network and its level of total utilization. The contribution of this paper lies in designing a new mathematical model capable of predicting the quality of multimedia services respecting network behavior and performance. Index Terms—delay, E-Model, packet loss, QoS, SSIM, triple play.Web of Science10423923

Multi-modal rigid image registration and segmentation using multi-stage forward path regenerative genetic algorithm

Medical image diagnosis and delineation of lesions in the human brain require information to combine from different imaging sensors. Image registration is considered to be an essential pre-processing technique of aligning images of different modalities. The brain is a naturally bilateral symmetrical organ, where the left half lobe resembles the right half lobe around the symmetrical axis. The identified symmetry axis in one MRI image can identify symmetry axes in multi-modal registered MRI images instantly. MRI sensors may induce different levels of noise and Intensity Non-Uniformity (INU) in images. These image degradations may cause difficulty in finding true transformation parameters for an optimization technique. We will be investigating the new variant of evolution strategy of genetic algorithm as an optimization technique that performs well even for the high level of noise and INU, compared to Nesterov, Limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm (LBFGS), Simulated Annealing (SA), and Single-Stage Genetic Algorithm (SSGA). The proposed new multi-modal image registration technique based on a genetic algorithm with increasing precision levels and decreasing search spaces in successive stages is called the Multi-Stage Forward Path Regenerative Genetic Algorithm (MFRGA). Our proposed algorithm is better in terms of overall registration error as compared to the standard genetic algorithm. MFRGA results in a mean registration error of 0.492 in case of the same level of noise (1-9)% and INU (0-40)% in both reference and template image, and 0.317 in case of a noise-free template and reference with noise levels (1-9)% and INU (0-40)%. Accurate registration results in good segmentation, and we apply registration transformations to segment normal brain structures for evaluating registration accuracy. The brain segmentation via registration with our proposed algorithm is better even in cases of high levels of noise and INU as compared to GA and LBFGS. The mean dice similarity coefficient of brain structures CSF, GM, and WM is 0.701, 0.792, and 0.913, respectively.Web of Science148art. no. 150

Sparse signal representation, sampling, and recovery in compressive sensing frameworks

Compressive sensing allows the reconstruction of original signals from a much smaller number of samples as compared to the Nyquist sampling rate. The effectiveness of compressive sensing motivated the researchers for its deployment in a variety of application areas. The use of an efficient sampling matrix for high-performance recovery algorithms improves the performance of the compressive sensing framework significantly. This paper presents the underlying concepts of compressive sensing as well as previous work done in targeted domains in accordance with the various application areas. To develop prospects within the available functional blocks of compressive sensing frameworks, a diverse range of application areas are investigated. The three fundamental elements of a compressive sensing framework (signal sparsity, subsampling, and reconstruction) are thoroughly reviewed in this work by becoming acquainted with the key research gaps previously identified by the research community. Similarly, the basic mathematical formulation is used to outline some primary performance evaluation metrics for 1D and 2D compressive sensing.Web of Science10850188500

Design of Emotion Recognition System

The chapter deals with a speech emotion recognition system as a complex solution including a Czech speech database of emotion samples in a form of short sound records and the tool evaluating database samples by using subjective methods. The chapter also involves individual components of an emotion recognition system and shortly describes their functions. In order to create the database of emotion samples for learning and training of emotional classifier, it was necessary to extract short sound recordings from radio and TV broadcastings. In the second step, all records in emotion database were evaluated using our designed evaluation tool and results were automatically evaluated how they are credible and reliable and how they represent different states of emotions. As a result, three final databases were formed. The chapter also describes the idea of new potential model of a complex emotion recognition system as a whole unit

Alternative approaches to measurement of ground vibrations due to the vibratory roller: A pilot study

At present, one of the primary tasks of the construction industry is to build transport infrastructure. This concerns both the construction of new bypasses of towns and the repair of existing roads, which are damaged by congestion, especially by freight transport. Whether it is a new building or a reconstruction, it is always very important to choose a suitable method of subsoil treatment. One of the most commonly used methods for soil treatment is currently compaction using vibratory rollers. This method is very effective both in terms of results and due to its low financial demands compared to other methods. Vibration is transmitted to the surrounding rock environment when compacting the subsoil using vibratory rollers. Although the intensity of these vibrations is not as pronounced as in other methods of subsoil treatment, such vibrations can have a significant effect, for example during compaction in urban areas or in an area with the presence of historical objects. Therefore, it is very advisable to monitor the effect of these vibrations on the environment during construction. This paper brings an original experimental comparative study of standard seismic instrumentation with a developed interferometric sensor for the field of monitoring vibrations generated during compaction of subsoil using vibrating rollers. The paper presents time and frequency domain results, as well as attenuation curves, which represent real attenuation of vibrations in a given rock environment. The results presented here show that a system operating on a different physical principle from the one used at present has the potential to replace the existing, very expensive, seismic equipment.Web of Science1924art. no. 542