bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic rat brain image segmentation using triple cascaded convolutional neural networks in a clinical PET/MR
Authors: Gao Ya , Li Zaisheng , Song Cheng , Li Lei , Li Mengmeng , Schmall Jeffrey , Liu Hui , Yuan Jianmin , Wang Zhe , Zeng Tianyi , Hu Lingzhi , Chen Qun , Zhang Yanjun
Published: February 2021

The purpose of this work was to develop and evaluate a deep learning approach for automatic rat brain image segmentation of magnetic resonance imaging (MRI) images in a clinical PET/MR, providing a useful tool for analyzing studies of the pathology and progression of neurological disease and to validate new radiotracers and therapeutic agents. Rat brain PET/MR images (N = 56) were collected from a clinical PET/MR system using a dedicated small-animal imaging phased array coil. A segmentation method based on a triple cascaded convolutional neural network (CNN) was developed, where, for a rectangular region of interest covering the whole brain, the entire brain volume was outlined using a CNN, then the outlined brain was fed into the cascaded network to segment both the cerebellum and cerebrum, and finally the sub-cortical structures within the cerebrum including hippocampus, thalamus, striatum, lateral ventricles and prefrontal cortex were segmented out using the last cascaded CNN. The dice score coefficient (DSC) between manually drawn labels and predicted labels were used to quantitatively evaluate the segmentation accuracy. The proposed method achieved a mean DSC of 0.965, 0.927, 0.858, 0.594, 0.847, 0.674 and 0.838 for whole brain, cerebellum, hippocampus, lateral ventricles, striatum, prefrontal cortex and thalamus, respectively. Compared with the segmentation results reported in previous publications using atlas-based methods, the proposed method demonstrated improved performance in the whole brain and cerebellum segmentation. In conclusion, the proposed method achieved high accuracy for rat brain segmentation in MRI images from a clinical PET/MR and enabled the possibility of automatic rat brain image processing for small animal neurological research.
Reshaping the output of fiber lasers by using a variable intra-cavity filter based on a reconfigurable Fabry–Perot interferometer
Authors: Torres-Torres M , Salceda-Delgado G , Rodríguez-Carreón V C , Martinez-Rios A , Sierra-Hernandez J M , Antonio-Lopez J E , Amezcua-Correa R , Estudillo-Ayala J
Published: February 2021

The shaping of the output laser by using a modifiable intra-cavity filter, which is based on a reconfigurable Fabry–Perot interferometer, is experimentally demonstrated. This output shaping method is carried out using a Fabry–Perot interferometer formed by the partially reflected faces of two single-mode fibers (SMFs). The two SMF ends are inside a capillary glass, where one is fixed, and the other one can be linearly displaced. As the free fiber is displaced, the separation distance between the planar faces is modified, which changes the interferometer properties to allow the adjustment of the laser intra-cavity losses to shape the output laser. The shaping of the output laser is focused on varying the wavelength peak number that may induce laser emissions and also shift these peaks. For the laser setup used in this work, a maximum of four simultaneous laser emissions was achieved. In addition, the experimental results for a constant interferometer separation distance provide emissions with negligible variations.
Non-contact optical measurement of material surfaces with a laser based sensor
Authors: Satapathy Priyanka , Nath Ganeswar , Mishra Punyatoya
Published: February 2021

The precise measurement of surface roughness is an important ability in surface engineering applications. Non-destructive techniques like laser speckle characterization is one of the key analysis for the surface of the material. The speckles coming from different atomic and subatomic regions are recorded for different surfaces like rough, smooth and non smooth surfaces, using a laboratory designed laser sensor. The sensitivity of speckle signals measured at different distances from the surfaces are recorded. The strength of the signal and its variation with distances of the source from the surfaces provides significant information about surface conditions embedded in the present work. Furthermore, the speckle contrast changes significantly with the change of the beam strength of incidence laser signal with distance which provides clear illuminance of the texture of the material.
Plasticity and melting characteristics of metal Al with Ti-cluster under shock loading*
Authors: Luan Dong-Lin , Wang Ya-Bin , Li Guo-Meng , Yuan Lei , Chen Jun
Published: February 2021

Impurity agglomeration has a significant influence on shock response of metal materials. In this paper, the mechanism of Ti-clusters in metal Al under shock loading is investigated by non-equilibrium molecular dynamics simulations. Our results show that the Ti-cluster has obvious effects on the dislocation initiation and melting of bulk Al. First, the Ti clusters induces the strain concentrate and leads the dislocations to be initiated from the interface of Ti cluster. Second, dislocation distribution from the Ti-cluster model results in a formation of a grid-like structure, while the dislocation density is reduced compared with that from the perfect Al model. Third, the critical shock velocity of dislocation from the Ti-cluster model is lower than from perfect Al model. Furthermore, it is also found that the temperature near the interface of Ti-cluster is 100 K-150 K higher than in the other areas, which means that Ti-cluster interface melts earlier than the bulk area.
Magnetic-resonance image segmentation based on improved variable weight multi-resolution Markov random field in undecimated complex wavelet domain*
Authors: Fan Hong , Sun Yiman , Zhang Xiaojuan , Zhang Chengcheng , Li Xiangjun , Wang Yi
Published: February 2021

To solve the problem that the magnetic resonance (MR) image has weak boundaries, large amount of information, and low signal-to-noise ratio, we propose an image segmentation method based on the multi-resolution Markov random field (MRMRF) model. The algorithm uses undecimated dual-tree complex wavelet transformation to transform the image into multiple scales. The transformed low-frequency scale histogram is used to improve the initial clustering center of the K-means algorithm, and then other cluster centers are selected according to the maximum distance rule to obtain the coarse-scale segmentation. The results are then segmented by the improved MRMRF model. In order to solve the problem of fuzzy edge segmentation caused by the gray level inhomogeneity of MR image segmentation under the MRMRF model, it is proposed to introduce variable weight parameters in the segmentation process of each scale. Furthermore, the final segmentation results are optimized. We name this algorithm the variable-weight multi-resolution Markov random field (VWMRMRF). The simulation and clinical MR image segmentation verification show that the VWMRMRF algorithm has high segmentation accuracy and robustness, and can accurately and stably achieve low signal-to-noise ratio, weak boundary MR image segmentation.
Thermodynamic properties of massless Dirac–Weyl fermions under the generalized uncertainty principle*
Authors: Xiong Guang-Hua , Long Chao-Yun , Su He
Published: February 2021

The Dirac–Weyl equation characterized quasi-particles in the T3 lattice are studied under external magnetic field using the generalized uncertainty principle (GUP). The energy spectrum of the quasi-particles is found by the Nikiforov–Uvarov method. Based on the energy spectrum obtained, the thermodynamic properties are given, and the influence of the GUP on the statistical properties of systems is discussed. The results show that the energy and thermodynamic functions of massless Dirac–Weyl fermions in the T3 lattice depend on the variation of the GUP parameter.
Measurement of 59Co(n, x) reaction cross sections with the fast neutrons based on the 9Be(p, n) reaction *
Authors: Zaman Muhammad , Nadeem Muhammad , Sahid Muhammad , Kim Kwangsoo , Kim Guinyun , Thi Hien Nguyen
Published: February 2021

The cross sections of the 59Co(n, x) reaction in the average energy range of 15.2-37.2 MeV were measured using activation and an off-line γ-ray spectrometric technique. The neutrons were generated from the 9Be(p, n) reaction with proton beam energies of 25-45 MeV at the MC-50 Cyclotron facility of the Korean Institute of Radiological and Medical Sciences (KIRAMS). Theoretical calculations of neutron–induced reactions on 59Co were performed using the nuclear model code TALYS-1.9. The results for the 59Co(n, x) reactions were compared with the theoretical values obtained using TALYS-1.9 and the literature data provided in EXFOR and the TENDL 2019 nuclear data library. The theoretical values obtained using TALYS-1.9 with adjusted parameters are comparable to the experimental data. The measured reaction cross sections of a few radionuclides are new, and the others are comparable to the literature data, and thus, they can strengthen the database. The present study on cross sections leads to useful insight into the mechanisms of 59Co(n, x) reactions.
Relativistic Borromean states *
Authors: Wang Ziyue , Jiang Shao-Jian , Jiang Yin
Published: February 2021

In this work, the existence of Borromean states is discussed for bosonic and fermionic cases in both the relativistic and non-relativistic limits from the 3-momentum shell renormalization. With the linear bosonic model, we check the existence of Efimov-like states in the bosonic system. In both limits a geometric series of singularities is found in the 3-boson interaction vertex, while the energy ratio is reduced by around 70% in the relativistic limit because of the anti-particle contribution. Motivated by the quark-diquark model in heavy baryon studies, we have carefully examined the p-wave quark-diquark interaction and found an isolated Borromean pole at finite energy scale. This may indicate a special baryonic state of light quarks in high energy quark matter. In other cases, trivial results are obtained as expected. In the relativistic limit, for both bosonic and fermionic cases, potential Borromean states are independent of the mass, which means the results would also be valid even in the zero-mass limit.
Entropic force between two horizons of dilaton black holes with a power-Maxwell field *
Authors: Zhao Hui-Hua , Zhang Li-Chun , Gao Ying , Liu Fang
Published: February 2021

In this paper, we consider

-dimensional topological dilaton de Sitter black holes with a power-Maxwell field as thermodynamic systems. The thermodynamic quantities corresponding to the black hole horizon and the cosmological horizon are interrelated. Therefore, the total entropy of the space-time should be the sum of the entropies of the black hole horizon and the cosmological horizon plus a correction term which is produced by the association of the two horizons. We analyze the entropic force produced by the correction term at given temperatures, which is affected by the parameters and dimensions of the space-time. It is shown that the change of entropic force with the position ratio of the two horizons in some regions is similar to that of the variation of the Lennard-Jones force with the position of particles. If the effect of entropic force is similar to that of the Lennard-Jones force, and other forces are absent, the motion of the cosmological horizon relative to the black hole horizon should have an oscillating process. The entropic force between the two horizons is probably one of the participants in driving the evolution of the universe.
MSSM at future Higgs factories *
Authors: Li Honglei , Song Huayang , Su Shufang , Su Wei , Yang Jin Min
Published: February 2021

In this work, we study the implications of Higgs precision measurements at future Higgs factories for the MSSM parameter space, focusing on the dominant stop sector contributions. We perform a multi-variable fit to both the signal strength for various Higgs decay channels at Higgs factories and the Higgs mass. The χ
2 fit results show sensitivity to mA
, tan β, stop mass parameter m
SUSY , and the stop left-right mixing parameter Xt. We also study the impact of the Higgs mass prediction on the MSSM and compare the sensitivities of different Higgs factories.
Radiative hydrodynamic simulations of the spectral characteristics of solar white-light flares
Authors: Yang Yu-Tong , Hong Jie , Li Ying , Ding Ming-De , Li Hui
Published: February 2021

As one of the most violent activities in the solar atmosphere, white-light flares (WLFs) are generally known for their enhanced white-light (or continuum) emission, which primarily originates in the solar lower atmosphere. However, we know little about how white-light emission is produced. In this study, we aim to investigate the response of the continua at 3600 Å and 4250 Å and also the Hα and Lyα lines during WLFs modeled using radiative hydrodynamic simulations. We take non-thermal electron beams as the energy source for the WLFs in two different initial atmospheres and vary their parameters. Our results show that the model with non-thermal electron beam heating clearly shows enhancements in the continua at 3600 Å and 4250 Å as well as in the Hα and Lyα lines. A larger electron beam flux, a smaller spectral index, or an initial penumbral atmosphere leads to a stronger emission increase at 3600 Å, 4250 Å and in the Hα line. The Lyα line, however, is more obviously enhanced in a quiet-Sun initial atmosphere with a larger electron beam spectral index. It is also notable that the continua at 3600 Å and 4250 Å and the Hα line exhibit a dimming at the start of heating and reach their peak emissions after the peak time of the heating function, while the Lyα line does not show such behaviors. These results can serve as a reference for the analysis of future WLF observations.
Research on the principle of space high-precision temperature control system of liquid crystals based Stokes polarimeter
Authors: Zhang Xin-Wei , Zhang Yang , Lin Jia-Ben , Hou Jun-Feng , Deng Yuan-Yong
Published: February 2021

The magnetic field is one of the most important parameters in solar physics, and a polarimeter is the key device to measure the solar magnetic field. Liquid crystals based Stokes polarimeter is a novel technology, and will be applied for magnetic field measurement in the first space-based solar observatory satellite developed by China, Advanced Space-based Solar Observatory. However, the liquid crystals based Stokes polarimeter in space is not a mature technology. Therefore, it is of great scientific significance to study the control method and characteristics of the device. The retardation produced by a liquid crystal variable retarder is sensitive to the temperature, and the retardation changes 0.09° per 0.1° C. The error in polarization measurement caused by this change is 0.016, which affects the accuracy of magnetic field measurement. In order to ensure the stability of its performance, this paper proposes a high-precision temperature control system for liquid crystals based Stokes polarimeter in space. In order to optimize the structure design and temperature control system, the temperature field of liquid crystals based Stokes polarimeter is analyzed by the finite element method, and the influence of light on the temperature field of the liquid crystal variable retarder is analyzed theoretically. By analyzing the principle of high-precision temperature measurement in space, a high-precision temperature measurement circuit based on integrated operational amplifier, programmable amplifier and 12 bit A/D is designed, and a high-precision space temperature control system is developed by applying the integral separation PI temperature control algorithm and PWM driving heating films. The experimental results show that the effect of temperature control is accurate and stable, whenever the liquid crystals based Stokes polarimeter is either in the air or vacuum. The temperature stability is within ±0.015° C, which demonstrates greatly improved stability for the liquid crystals based Stokes polarimeter.
Computation of the atmosphere-less light intensity curve during a total solar eclipse by using Lunar Reconnaissance Orbiter topography data and the DE430 astronomical ephemeris
Authors: Wang Yun-Bo , Yan Jian-Guo , Ye Mao , Yang Yong-Zhang , Li Fei , Barriot Jean-Pierre
Published: February 2021

Observations of the sky irradiation intensity in the visible wavelengths during a solar eclipse permit to model the Sun diameter, a key number to constrain the internal structure of our star. In this paper, we present an algorithm that takes advantage of the precise Moon topography from Lunar Reconnaissance Orbiter to compute, with a high resolution in time, the geometrical part (i.e. top-of-atmosphere, and for a given wavelength) of the sky irradiation at any given location on the Earth during these events. The algorithm is also able to model the Baily’s beads. We give as an application the theoretical computation of the light curve corresponding to the solar eclipse observed at Lakeland (Queensland, North Australia) on 2012 November 13. The application to real data, with the introduction of atmospheric and instrumental passbands, will be considered in a forthcoming paper.
Solar cycle prediction using a long short-term memory deep learning model
Authors: Wang Qi-Jie , Li Jia-Chen , Guo Liang-Qi
Published: February 2021

In this paper, we propose a long short-term memory (LSTM) deep learning model to deal with the smoothed monthly sunspot number (SSN), aiming to address the problem whereby the prediction results of the existing sunspot prediction methods are not uniform and have large deviations. Our method optimizes the number of hidden nodes and batch sizes of the LSTM network structures to 19 and 20, respectively. The best length of time series and the value of the timesteps were then determined for the network training, and one-step and multi-step predictions for Cycle 22 to Cycle 24 were made using the well-established network. The results showed that the maximum root-mean-square error (RMSE) of the one-step prediction model was 6.12 and the minimum was only 2.45. The maximum amplitude prediction error of the multi-step prediction was 17.2% and the minimum was only 3.0%. Finally, the next solar cycle (Cycle 25) peak amplitude was predicted to occur around 2023, with a peak value of about 114.3. The accuracy of this prediction method is better than that of the other commonly used methods, and the method has high applicability.
A simulation experiment on the GM estimation for Comet 133P/Elst-Pizarro
Authors: Gao Wu-Tong , Yan Jian-Guo , Jin Wei-Tong , Yang Xuan , Yang Chen , Ye Mao , Li Fei , Barriot Jean-Pierre
Published: February 2021

In China’s asteroid mission to be launched around 2025, (7968) 133P/Elst-Pizarro (hereafter 133P) will be the second target, after a visit to asteroid (469219) Kamo’oalewa. This paper describes a simulation of precise orbit determination for the spacecraft around comet 133P, as well as estimation of its gravitational parameter (GM) value and the solar radiation pressure coefficient Cr
for the spacecraft. Different cometocentric distances of 200, 150 and 100 km orbits are considered, as well as two tracking modes: exclusive two-way range-rate mode (Earth station to spacecraft) and combinations of two-way range-rate and local spacecraft onboard ranging to the comet. Compared to exclusive two-way range-rate, the introduction of local ranging observables improves the final GM uncertainties by up to one order of magnitude. An ephemeris error in the orbit of 133P is also considered, and we show that, to obtain a reliable estimate of the GM for 133P, this error cannot exceed a one km range.
Satellite RFI mitigation on FAST
Authors: Wang Yu , Zhang Hai-Yan , Hu Hao , Huang Shi-Jie , Zhu Wei-Wei , Zhi Guo-Ping , Zhang Tao , Fan Zhan-Chun , Yang Li
Published: February 2021

As the most sensitive single-dish radio telescope, the Five-hundred Aperture Spherical radio Telescope (FAST) is very susceptive to radio frequency interference (RFI) from active radio services. Moreover, due to the rapid development of space applications and research, satellite interference has become one of the main RFI sources for FAST, particularly at the L band. Therefore, we have developed several measures to mitigate satellite RFI. On the one hand, an antenna with 4.5-meter diameter has been constructed and installed at the FAST site to detect the satellite interference in the frequency band between 1 to 5 GHz. Meanwhile, we have developed a satellite RFI database based on the FAST sky coverage, the observing frequency bands, and known satellite systems. By combining the satellite RFI monitoring antenna and the database, we have established a satellite RFI mitigation system. With this system, we can not only track satellites to collect their characteristics and update the database but also help the observer to program the observing plan by predicting satellite interference. During the practical observation of FAST at the L band, the feasibility of this system to mitigate satellite RFI has been proved. In particular, the system effectively avoids strong satellite interference from entering the main beam of the telescope and causing receiver saturation.
The composite X-ray spectra of radio-loud and radio-quiet SDSS quasars
Authors: Zhou Min-Hua , Gu Min-Feng
Published: February 2021

We present a study of the X-ray emission for a sample of radio-detected quasars constructed from the cross-matches between SDSS, FIRST catalogs and XMM-Newton archives. A sample of radio-quiet SDSS quasars without FIRST radio detection is also assembled for comparison. We construct the optical and X-ray composite spectra normalized at rest frame 4215 Å (or 2200 Å) for both radio-loud quasars (RLQs) and radio-quiet quasars (RQQs) at z ≤ 3.2, with matched X-ray completeness of 19%, redshift and optical luminosity. While the optical composite spectrum of RLQs is similar to that of RQQs, we find that RLQs have a higher X-ray composite spectrum than RQQs, consistent with previous studies in the literature. By dividing the radio-detected quasars into radio loudness bins, we find the X-ray composite spectra are generally higher with increasing radio loudness. Moreover, a significant correlation is found between the optical-to-X-ray spectral index and radio loudness, and there is a unified multi-correlation between the radio and X-ray luminosities and radio loudness in radio-detected quasars. These results could be possibly explained with the corona-jet model, in which the corona and jet are directly related.
The influence of the Insight-HXMT/LE time response on timing analysis
Authors: Zhou Deng-Ke , Zheng Shi-Jie , Song Li-Ming , Chen Yong , Li Cheng-Kui , Li Xiao-Bo , Chen Tian-Xiang , Cui Wei-Wei , Chen Wei , Han Da-Wei , Hu Wei , Huo Jia , Ma Rui-Can , Li Mao-Shun , Li Tian-Ming , Li Wei , Liu He-Xin , Lu Bo , Lu Fang-Jun , Qu Jin-Lu , Tuo You-Li , Wang Juan , Wang Yu-Sa , Wu Bai-Yang , Xiao Guang-Cheng , Xu Yu-Peng , Yang Yan-Ji , Zhang Shu , Zhang Zi-Liang , Zhao Xiao-Fan , Zhu Yu-Xuan
Published: February 2021

The LE is the low energy telescope that is carried on Insight-HXMT. It uses swept charge devices (SCDs) to detect soft X-ray photons. LE’s time response is caused by the structure of the SCDs. With theoretical analysis and Monte Carlo simulations we discuss the influence of LE time response (LTR) on the timing analysis from three aspects: the power spectral density, the pulse profile and the time lag. After the LTR, the value of power spectral density monotonously decreases with the increasing frequency. The power spectral density of a sinusoidal signal reduces by a half at frequency 536 Hz. The corresponding frequency for quasi-periodic oscillation (QPO) signals is 458 Hz. The root mean square (RMS) of QPOs holds a similar behaviour. After the LTR, the centroid frequency and full width at half maxima (FWHM) of QPOs signals do not change. The LTR reduces the RMS of pulse profiles and shifts the pulse phase. In the time domain, the LTR only reduces the peak value of the cross-correlation function while it does not change the peak position; thus it will not affect the result of the time lag. When considering the time lag obtained from two instruments and one among them is LE, a 1.18 ms lag is expected caused by the LTR. The time lag calculated in the frequency domain is the same as that in the time domain.
Photometric and spectroscopic study of flares on Ross 15
Authors: Bai Jian-Ying , Esamdin Ali , Gao Xing , Yan Yan , Ren Juan-Juan
Published: February 2021

We conducted photometric and spectroscopic observations of Ross 15 in order to further study the flare properties of this less observed flare star. A total of 28B-band flares are detected in 128 hr of photometric observations, leading to a total flare rate of0.22−0.04+0.04hr−1, more accurate than that provided by previous work. We give the energy range of theB-band flare (1029.5– 1031.5erg) and the flare frequency distribution (FFD) for the star. Within the same energy range, the FFD is lower than that of GJ 1243 (M4) and YZ CMi (M4.5), roughly in the middle of those of three M5-type stars and higher than the average FFDs of spectral types ≥ M6. We performed, for the first time for Ross 15, simultaneous high-cadence spectroscopic and photometric observations, resulting in detection of the most energetic flare in our sample. The intensity enhancements of the continuum and Balmer lines with significant correlations between them are detected during the flare, which is the same as those of other deeply studied flare stars with similar spectral type.
Multi-stage scale of the incentive system for distributors of an electrical company
Authors: Nikitochkina Yu V
Published: February 2021

The model presented in the article expands the applied nature of the measurement theory and eliminates the gap in the application of measurements in the “agent theory” (the economic theory of incentives). Distribution channel management is one of the key issues for the vast majority of manufacturers. This channel is the widest, and therefore determines both the production plans and the marketing policy of the manufacturer. The current practice of setting discounts has become extremely sophisticated, and the variety of discounts is impressive: currently, about 20 different types of discounts are used in international trade practice. This article proposes a new model for stimulating distributors – a multi-stage scale that matches the distributor’s score with the percentage level of discount for regional coverage and specialization. The list of indicators for calculating the discount for specialization and regional coverage includes a group of indicators to increase the motivation of the distributor to improve the quality of their work and a group of indicators to increase the motivation of the distributor to expand the scope of action. Using the method of index grouping of expert estimates, the weight values of each indicator were found using the method of index grouping of expert estimates. The problem of calculating the score of distribution activity results was set as a multi-criteria problem, in which the method of additive optimization was used for the procedure of folding private criteria, which was preceded by checking all private criteria for additive independence. As a result of the calculations (using the processing of expert opinions by the method of index grouping of expert assessments), a five-step scale of discounts was obtained. The data of the international electrotechnical company Schneider Electric in Russia became the empirical basis for the implementation of the tasks set. The developed incentive model can be adapted for any commercial enterprise that is interested in promoting its product through regional coatings, as well as in supporting the image of the product, which, of course, helps to stimulate demand and increase sales.
Combining scenario approach and Choquet integral in decision making
Authors: Gisin V B
Published: February 2021

Scenario-based approach is applied to evaluate alternatives. Using the ideas of Dempster-Schaeffer a capacity distribution is defined over scenarios. This allows describing possible future developments in terms of individual and integrated expert judgments and transforming expert judgments into scenario assessments. To get a final numerical estimate of alternatives, we use integration over non-additive measures applying the Choquet integral.
Application of bioinspired algorithms for solving transcomputational tasks
Authors: Kureichik V V , Kursitys I O , Kuliev E V , Gerasimenko E M
Published: February 2021

The paper investigates the pattern recognition task as one of the most important transcomputational problems. Pattern recognition is applied for statistical data analysis, signal processing, image analysis, bioinformatics, machine learning, and many other fields. The area of application is related to automated pattern detection in the data using computer algorithms and data classification in terms of different categories. The development of new ideas in the processing of large volumes of information creates a new trend in the pattern recognition area. A specific field is formed by the bioinspired algorithms as mathematical reorganization, that transform the initial information into the results based on simulating the evolution methods, natural analogies, and statistic approach. In terms of computer modelling based on the bioinspired algorithms, we can create and develop difficult concepts, for which we have no analytical description. The authors present the optimal bioinspired algorithms based on the ant, monkey, and bat behavior in nature and develop software based on the principle of pattern recognition using the uploaded photo and downloading the results into the file. The experiments demonstrate the effectiveness of the proposed approach.
Specific features of feed-forward neural networks application in classification and regression problems in algology
Authors: Grigoryeva N Yu , Zhangirov T R , Liss A A
Published: February 2021

Abundance and biological diversity of phytoplankton communities, investigated in this work, are often used as a marker for the determination of environmental health and fresh water quality. Presently their routine analysis is very time consuming and expensive. A lot of articles are devoted to the development of a system for an in situ automated analysis of phytoplankton properties. However, the applied problems of biology, ecology and, in particular, algology usually are associated with some difficulties due to shortage and/or fuzziness of the experimental data. Hence, while using neural network modelling a set of specific problems can occur. In this article on the base of experimental data several such problems are presented and possible solutions are suggested. In particular, the illogical behavior of classifying neural network is revealed, while studying the biological diversity of cyanobacteria, and the original technique for results validation is presented. This problem is investigated on a set of spectroscopic data, recorded by means of confocal laser scanning microscopy. The generalization quality of the trained model is studied as the main learning parameter. Another problem of shortage dataset is examined in the frames of regression model for bioplankton abundance. This problem is solved by means of feed-forward back-propagation neural networks with two hidden layers. The modelling was carried out on a small experimental selection (only 39 observations were available), despite this, the relatively high determination coefficient was obtained for the training and test samples, while using dropout layout.
The minimum cost flow finding under fuzzy intuitionistic conditions
Authors: Gerasimenko E , Kureichik V
Published: February 2021

Present paper deals with the minimum cost flow finding task with fuzzy trapezoidal intuitionistic values of arc capacities and costs. Nowadays, flow tasks in networks are leading tasks in flow modelling and urban logistics. Peculiarity of the problem is in optimal paths finding, which allows decreasing the total cost of transportation and choosing the best paths for transportation. Fuzzy logic as a powerful tool for dealing with uncertainty, vagueness and inaccurate data influenced the way of presenting characteristics of networks. Arc capacities and costs can be presented as fuzzy numbers of the different form enabling researchers to get more reliable solutions. However, during the simulation a researcher is often faced with difficulties in exact specifying of arc capacities and costs. It is a commonplace that experts hesitate or have doubts choosing a specific value for parameters of the network. In such circumstances arc capacities and costs can be presented in a fuzzy intuitionistic form, in particular, as fuzzy intuitionistic triangular or trapezoidal numbers. A fuzzy intuitionistic number allows taking into account a level of hesitation by including degree of membership, non-membership and indeterminacy margin. Incorporating fuzzy intuitionistic sets into conventional flow patterns enables researchers to solve tasks in fuzzy, vague conditions even when there is a lack of necessary data for problem statement. The main contribution to the paper is the proposal for the fuzzy intuitionistic minimum cost flow algorithm using fuzzy intuitionistic flow patterns based on the ranking technique and arithmetic operations with fuzzy intuitionistic trapezoidal numbers. A case study numerical is presented to illustrate the proposed algorithm.
Qualitative measure of the environment risk level for the fuzzy control systems of environmental safety
Authors: Novikova S V , Tunakova Y A , Shagidullin A R , Novikova K N
Published: February 2021

When creating an environmental management system that should generate a control actions set for regulating the quality of natural objects, it is necessary to be able to “calculate” the qualitative value of the environment state. A qualitative assessment of the environment state is a generalized measure of natural risk. For these purposes, it is very convenient to use the so-called “soft” models that take into account the fuzzy nature of information - a fuzzy inference system and neuro-fuzzy systems. The main advantage of the neuro-fuzzy model over the regression one is the consideration of the ambiguity and fuzziness of the concepts “Acceptable”, “Medium”, “High”, “Unacceptable” and “Catastrophic” risks, as well as the possibility of adaptive correction due to the training of a fuzzy neural network on experimental data.

The calculation of the qualitative values for degree of danger to the environment is important not only in itself, but also as a criterion for making management decisions to normalize or prevent dangerous situations. To develop environmental recommendations on management impacts, the concept of “Risk Measure” is considered in the work, which corresponds to the management decisions made. The criterion “Risk Measure” takes values in the range from 1 to the number of tuples of the experimental sample, and the higher the Measure value, the more global the measures are recommended. Each value can be associated with either a single action or a set of actions. Thus, greater flexibility in the use of the system is achieved, and the range of recommended measures that can compensate for the emerging risks is significantly expanded.

The article describes an algorithm for calculating a quality risk measure. The theory is confirmed by computational experiments using in fuzzy control systems.
A problem of long distances in the educational environment
Authors: Nikiforov I S , Paderno P I
Published: February 2021

A process of the specialist’s professional development involve two aspects of the decision-making support: choosing a field of study (by an applicant) and choosing an applicant for a job position and training (by a company). The correctness of solving this task depends greatly on developing methods allowing to identify potential of an applicant. The goal of this research is developing a formalized approach to create the metrics in the educational environment, which would allow comparing applicants to each other in terms of compliance with the requirements of a certain job. The methods: the research uses system analysis approaches; models of characteristics changing during the training; scaling of heterogeneous values; integrating particular estimations (getting integral estimation) based on expert opinions. The results: the analysis allowed identify a set of dependencies related both to a study subject and job requirements, distinctive features and resource characteristics of learning technologies. Several models and an approach to assessing a prospective applicant were suggested taking into account a multi-dimensional resource, which is required to train a certain applicant up to the required level. The practical relevance: the suggested approach allows to make formalized setting and further addressing a set of evaluation and optimization tasks related both to the best choice of future job (for an applicant), and a choice of most promising applicants and learning techniques (for a company).
Pseudo-bulk SAW transducers fabricated in GaN epitaxial layers grown on sapphire substrate
Authors: Paszkiewicz B , Gierz Ł
Published: February 2021

Gallium nitride is a material commonly applied to the fabrication of various semiconductor devices, naming High Electron Mobility Transistors (HEMT) and Light Emitting Diodes (LED). Its unique feature is that it also possesses good piezoelectric properties. This enables to produce devices that integrate both active transistor operation and signal processing and filtration in one monolithic chip. This aim requires a comprehensive analysis of the acoustic wave propagation in the gan/sapphire system. Particularly attractive in the construction of modern acoustic instruments, due to higher propagation speeds, is the utilisation of pseudo-bulk mods. This paper presents the results of research on Surface Acoustic Wave (SAW) transducers using pseudo-bulk waves propagating in thin (2-6 μm) layers of GaN on sapphire. The layers were made by the MOVPE process using a low-temperature buffer layer. Transducers with a two-finger pitch of 9 and 18 μm with 48 and 24 periods respectively were made using electron lithography. Low finger resistivity was achieved by using Ru/Au/Ti/Au metal alloy. The results of microwave measurements identifying particular pseudo-bulk mods and their dispersion characteristics are presented. Two pseudo-bulk mods were observed, the first one with a propagation velocity range of 8500-7800 ms−1 and the second one of 7200-7300 ms−1. Additionally, pseudo-bulk modes were also compared with classical Rayleigh modes generated in the same transducers at lower frequencies. The results are important from the point of view of possible monolithic integration of the tested transducers with High Electron Mobility Transistors.
Research on the measurement of spraying time with seed treatment agent using an innovative valve
Authors: Semkło Ł , Gierz Ł
Published: February 2021

The demand for agricultural products increases with limited access to agricultural land. As a result, there is an increase in yield owing to new techniques applied to agriculture, i.e. precise seed potatoes treatment. For this purpose, the dressing of seed potatoes was tested using the author’s method of checking the quality of spraying with dressing agent and improving seed coverage. In the hereby work, the method of image analysis was used to detect the movement of particles of working liquid. The article presents a test stand for measuring spraying time after exiting an innovative pressure-pneumatic valve using image analysis. The analysis was made using a fast Cronos 1.4 camera. The subject of the research was the construction of the station and evaluation of the work of the innovative pressure-pneumatic valve in two configurations: without the addition of compressed air and using additional compressed air.
Numerical analysis issues in the evaluation of the helicopter’s main rotor stability
Authors: Raczyński R , Siadkowska K
Published: February 2021

The paper presents selected aspects of numerical analyses on the assessment of the helicopter’s main rotor operational stability, presents key issues for stability assessment, and discusses the application of the co-simulation methodology for helicopter’s main rotor exampled by a prototype unmanned aerial vehicle rotor. The presented approach enables the analysis and mapping of the rotor’s operation taking into account the effects of the aeroelasticity of the blade itself. The impact of wind on the tested structure is presented for two cases and thrust force for the cases of starting the rotor for front and crosswind was evaluated. The transition of the rotor between the idle and working revolutions at a small collective angle does not generate unstable states independently in the wind direction.
Assessment of influence of addition of potassium drilling fluid on potassium content in activated sludge in wastewater treatment process in SBR reactors
Authors: Cel W
Published: February 2021

The activated sludge is described as a complex biological system composed of microorganisms. Within this system, processes of both physical and biochemical nature undergo, resulting in the purification of wastewater as well as industrial sewage. Recent researches indicate also on a possibility of co-treatment via activated sludge of used drilling fluids. As a result of wastewater treatment, sewage sludge is being formed, which according to its composition may become a waste to dispose or a product for natural reuse. The hereby paper presents the influence on potassium content in the activated sludge of addition of used drilling fluids (volume ranging from 0.25% to 4% of the volume of treated wastewater), which may have an impact on the final natural use of sludge.
Strength analysis of the rotor hub of an unmanned helicopter
Authors: Cygnarowska K , Czyż Z , Karpiński P , Skiba K
Published: February 2021

This article presents a method of strength analysis of the rotorcraft component which is the rotor hub of an unmanned helicopter with a MTOW up to 150 kg. The simulation takes into account two materials of which individual elements are made, i.e. steel and aluminum alloy. The load scheme and element support were defined, and numerical calculations were performed in the Ansys Workbench software. The simulation results were presented in the form of stress maps and were subjected to detailed analysis for individual elements. In the last stage, critical places in the assessment of the strength of the elements were indicated. On the basis of the performed strength analysis, the obtained results were individually interpreted for each of the tested elements depending on the adopted safety factors.
Evaluation of the diagnostic accuracy of MRI in detection of knee cartilage lesions using Receiver Operating Characteristic curves
Authors: Krakowski P , Karpiński R , Maciejewski R , Jonak J
Published: February 2021

Medical treatment, and especially surgical procedures, is carefully planned and executed based on various diagnostic methods. Physical examination provides preliminary information about the patient’s health; however, when orthopaedic surgery is concerned, more accurate radiological evaluation is necessary. MRI is perceived as a state-of-the-art radiological modality. In this study, we have evaluated MRI efficiency in detecting chondral lesions in the knee joint requiring surgical treatment. The evaluation of selected diagnostic methods used in the assessment of joint cartilage damage was carried out based on statistical indicators and ROC (Receiver Operating Characteristic) curves. The indicators were determined using Statistica and Matlab software. 95. patients underwent knee arthroscopy subsequently after performing MRI for various intraarticular lesions. Chondral lesions estimated with the use of the ICRS scale were divided into two groups, one requiring surgical treatment ICRS grade 3-4, and selected for conservative treatment ICRS grade 0-2. Results were evaluated with the use of ROC curves. MFC was the most common lesion site, where chondral lesions requiring surgical intervention were found in nearly 50% of patients. LTC was affected only in 9 patients, which was the rarest location for chondral lesions. The diagnostic efficiency for each anatomical location was evaluated. The highest diagnostic accuracy was found on MFC followed by LTC. The lowest diagnostic accuracy was found for PFJ. The AUC ranged from 0.8438 for MFC to 0.55 for PFJ. LFC and MTC showed similar accuracy with AUC respectively 0.6419 and 0. 6623. To sum up, MRI is a gold standard for cartilage evaluation, however, its accuracy differs among various anatomical locations, therefore requires a thorough assessment prior to surgical planning.
An enhanced fuzzy logic based strategy for non-disruptive load shedding and the predictive energy management system
Authors: Waheed W , Qingshan X , Abdullah M P
Published: February 2021

Electrical energy capacity mismatch and immense power shortages due to energy deficit in the power system keep on increasing because of inadequate power capacity, insufficient investment, demand growth, and the rise in living standards. To maintain a balanced relationship between production and consumption, several load shedding schemes have been implemented for load management in the last few years, but their inconsistency poses a challenge. This research work will apply the fuzzy logic algorithm (FLA) and optimise the existing conventional power systems with and without dispersed generators (DGs). In critical circumstances, the algorithm will find node sets or desired locations where limits are violated and system operators may request the utility or industrial customer to shed a required amount of load by operating distributed generators to maintain its system integrity. The performance and suitability of the proposed scheme are demonstrated and proved by testing on a standard 33-bus radial distribution system in MATLAB Simulink having an objective function of minimising its total load curtailed and reducing power system losses by improving its system stability.
Application of the Darcy and Richards equations for modelling of water capillary rise in building materials
Authors: Widomski M K , Łagód G , Suchorab Z , Pavlikova M , Pavlik Z , Zaleska M
Published: February 2021

This paper presents the application of the Darcy and Richards equations, describing water flow and dynamic changes of the water content in porous medium, for numerical modeling of water capillary rise in the selected building materials. The numerical simulations of unsaturated and variably saturated water flow in the studied materials were performed in FEFLOW commercial computational software, by DHI-Wasy, Germany. The developed model represented a wall section constructed of aerated concrete blocks, covered by mortar prepared using blended cement with biomass ash addition. The physical and water retention characteristics of the modeled materials were based on the previously performed laboratory measurements and literature research. The assumed initial conditions reflected air dry wall with limited moisture, while the boundary conditions allowed modeling of capillary rise due to direct contact of the studied materials with water with variable pressure head. The results of numerical calculations allowed observation of the time-dependent changes in the moisture content of building materials in relation to their physical properties and variable boundary conditions.