Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
Culture supernatant containing laccase produced by Cerrena unicolor strain was used to examine laccase partitioning between phases in an aqueous two-phase system. The investigated system consisted of polyethylene glycol 3000 and sodium phosphate buffer adjusted to pH = 7. Influence of several parameters on partitioning was measured, including phase forming components’ concentrations, tie line lengths, phase volume ratio, supernatant dilution, process temperature and halogen salt supplementation. Partitioning coefficients up to 78 in the bottom phase were achieved with yields of over 90%. Tie line length and phase volume ratio had significant effect on enzyme partitioning.
Reliable, remote pulse rate measurement is potentially very important for medical diagnostics and screening. In this paper the Videoplethysmography was analyzed especially to verify the possible use of signals obtained for the YUV color model in order to estimate the pulse rate, to examine what is the best pulse estimation method for short video sequences and finally, to analyze how potential PPG-signals can be distinguished from other (e.g. background) signals. The presented methods were verified using data collected from 60 volunteers.
This paper aims to characterize and interpret the trends in reserves, resources, and mine production of diatomite in the Czech Republic in last two decades. With more than 2.4 million tonnes of total reserves, 1.6 million tonnes of exploitable (recoverable) reserves, and average annual production of 35 kt, diatomite is not one of the key industrial minerals of the Czech Republic, which ranks among the top 10 European producers. Historical diatomite deposits were situated within the Cheb Basin, where the Holocene Hájek diatomite deposit was abandoned in 1955 because of the establishment of the Soos National Natural Monument. The group of Tertiary diatomite deposits situated in the Central Bohemian Upland ceased extraction when the last deposit (Kučlín) was abandoned in 1966 after depletion of reserves. The last group of diatomite deposits is located within the Southern Bohemian basins, where the last productive deposit, Borovany-Ledenice, is situated. Miocene diatomites are extracted by open pit mining there. Production of crude diatomite varied from 0 to 83 kt, with an average of 35 kt, between 1999 and 2018 according to stockpiles. Raw diatomite is classified into two groups according to the chemical-technological properties. Better-quality diatomite (SiO2 ≥ 72%, Al2O3 ≤ 15%, Fe2O3 < 2.4%, bulk density 450 kg/m3, loss on ignition < 8%) is processed for filtration in the food industry (brewery, wine, and raw fruit juices). Material with lower quality is used in combination with bentonite to prepare cat litter products.
A technology that utilizes penetrating rays is one of the oldest nondestructive testing methods. Nowadays, the process of radiogram analysis is performed by qualified human operators and automatic systems are still under development. In this work we present advanced algorithms for automatic segmentation of radiographic images of welded joints. The goal of segmentation of a radiogram is to change and simplify representation of the image into a form that is more meaningful and easier to analyse automatically. The radiogram is divided into parts containing the weld line, image quality indicators, lead characters, and possible defects. Then, each part is analysed separately by specialized algorithms within the framework of the Intelligent System for Radiogram Analysis.
In the paper the idea of rational polynomial windows optimised towards low level of Fourier spectrum's sidelobes is presented. A relevant advantage of the polynomial windows family and their modifications is their ability to easily change their properties changing only the values of the polynomial coefficients. The obtained frequency characteristics demonstrate better properties of proposed rational Windows than their standard polynomial equivalents requiring only the additional division operation. Such approach does not increase the computational complexity in significant way and the great advantage of polynomial windows which is their low computational complexity is preserved.
The article presents an application of Prony’s method with some known components in the analysis of electric power quality. Modifications of the Prony algorithm broaden the scope of method application. Modification of the filter of known components enables more accurate analysis of the parameters of unknown components and components with known or assumed frequencies. This article presents a comparison of the results of analyses conducted with the proposed algorithm for simulated and real signals and the results obtained by means of a commercial electric power quality testing device, operating in class A and using the Fourier transform. The proposed method enables to estimate the levels of the harmonic components, the frequency of the fundamental signal and real parameters of the interharmonic components, which are grouped and averaged in the contemporary monitoring equipment. Knowledge of the individual parameters of the interharmonics has considerable diagnostic importance while removing causes of incorrect operation affecting sensitive equipment in some electric power systems. Additionally, the algorithm is capable of analyzing exponentially damped components and finds its application in analysis of disturbances, for example, transient oscillations.
In this paper, we propose a new method of measuring the target velocity by estimating the scaling parameter of a chaos-generating system. First, we derive the relation between the target velocity and the scaling parameter of the chaos-generating system. Then a new method for scaling parameter estimation of the chaotic system is proposed by exploiting the chaotic synchronization property. Finally, numerical simulations show the effectiveness of the proposed method in target velocity measurement.
This article presents a way of analyzing the transfer function of electronic signal amplifiers. It also describes the possibility of using signal precorrection which improves the parasitic harmonics in the THD (Total Harmonic Distortion) of the amplified signal by correcting linearity of the tested amplifier’s transfer function. The proposed method of analyzing and presenting the transfer function allows to diagnose the causes of generating parasitic harmonics, what makes it a useful tool when designing low distortion amplifier systems, such as e.g. amplifiers in measurement systems. The presented THD correction can be used in e.g. amplifier systems that cooperate with arbitrary generators.
The paper presents a method of adaptation of the original second order Prony’s method for applications in lowcost digital measurement systems with low computing performance. The presented method can be used in measuring systems where it is important to obtain in real time the values of amplitude, frequency, initial phase and damping coefficient of a single sinusoidal component of an analysed signal. The paper presents optimized, in terms of the number of mathematical operations, implementation of the method in selected embedded devices as well as the calculation times of the method for each platform.
Enhanced Traffic Management System (ETMS) stores all the information gathered by the Federal Aviation Administration (FAA) from aircraft flying in the US airspace. The data stored from each flight includes the 4D trajectory (latitude, longitude, altitude and timestamp), radar data and flight plan information. Unfortunately, there is a data quality problem in the vertical channel and the altitude component of the trajectories contains some isolated samples in which a wrong value was stored. Overall, the data is generally accurate and it was found that only 0.3% of the altitude values were incorrect, however the impact of these erroneous data in some analyses could be important, motivating the development of a filtering procedure. The approach developed for filtering ETMS altitude data includes some specific algorithms for problems found in this particular dataset, and a novel filter to correct isolated bad samples (named Despeckle filter). As a result, all altitude errors were eliminated in 99.7% of the flights affected by noise, while preserving the original values of the samples without bad data. The algorithm presented in this paper attains better results than standard filters such as the median filter, and it could be applied to any signal affected by noise in the form of spikes
Raman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g. drugs, explosives) without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge due to noise and interferences present outside the laboratories. The design of a portable Raman spectrometer developed at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology is presented. The paper outlines sources of interferences present in Raman spectra measurements and signal processing techniques required to reduce their influence (e.g. background removal, spectra smoothing). Finally, the selected algorithms for automated chemicals classification are presented. The algorithms compare the measured Raman spectra with a reference spectra library to identify the sample. Detection efficiency of these algorithms is discussed and directions of further research are outlined.
A modification of the descriptor in a human detector using Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM) is presented. The proposed modification requires inserting the values of average cell brightness resulting in the increase of the descriptor length from 3780 to 3908 values, but it is easy to compute and instantly gives ≈ 25% improvement of the miss rate at 10‒4 False Positives Per Window (FPPW). The modification has been tested on two versions of HOG-based descriptors: the classic Dalal-Triggs and the modified one, where, instead of spatial Gaussian masks for blocks, an additional central cell has been used. The proposed modification is suitable for hardware implementations of HOG-based detectors, enabling an increase of the detection accuracy or resignation from the use of some hardware-unfriendly operations, such as a spatial Gaussian mask. The results of testing its influence on the brightness changes of test images are also presented. The descriptor may be used in sensor networks equipped with hardware acceleration of image processing to detect humans in the images.
Currently is the biggest problem of metallurgical companies the increase of fossil fuel prices and strict environmental regulations. As a result of this, companies must look for alternatives that would reduce the amount of fossil fuels and reduce emissions. Wood sawdust has huge energy potential, which can be used in the process of agglomerate production. This type of energy is locally available, has some similar properties as fossil fuels and is economically advantageous. For these reasons, experimental study using laboratory agglomeration pan was realized to study the possibility of agglomerate production with a mixed fuel. Experimental results show the viability of mixed fuel use in the agglomeration process, but also show significant possibility for improvement. The maximum acceptable substitution ratio, which corresponds to qualitatively suitable agglomerate is 20% of pine sawdust. Based on the realized experiments and the obtained results we have acceded to the intensification of the agglomeration process with an objective to increase the amount of added substitution fuel while maintaining the required quality of agglomerate.