Theoretical analysis of the factors, influencing composition uniformity of the cadmium zinc telluride substrates grown by THM

The effect of the sample composition, variation of the temperature field and the feed material non-homogeneity on uniformity of the growing crystal is considered. It is shown that optimization of the solvent composition makes it possible to minimize the jump of the ZnTe concentration at the seed/crystal boundary. The composition fluctuations at variation of the thermal field during crystal growth are smooth enough and relatively non-significant. The feed composition distribution has, as a rule, a random character. Different harmonics of composition distribution non-uniformity in the feed material differently affect the homogeneity of the growing crystal. Longwave non-uniformities in the feed transform into the growing crystal almost completely. At the wavelength equals to a half of the solvent length or shorter, the perturbations of the growing crystal composition are relatively small. Evidently, the cause of the local composition variations, found in real crystals, is, basically, the feed composition non-uniformities

Flexible Electrode Formed by Patterned Layers of Single-Walled Carbon Nanotubes for Optoelectronic Applications

The technology of creating patterned flexible electrodes based on single-walled carbon nanotubes and polydimethylsiloxane was demonstrated in this paper. A series of experiments were carried out to study whether the percolation affects the conductivity of patterned SWCNT layers. It was found that in patterns with the linewidth above 1 μm and the cell size above 50 μm the random character of SWCNT networks may be neglected. The impact of bending on the grid conductivity was studied. We observed a very moderate increase of resistance below 5% under the strain up to 4 %, which is comparable with the previous results for continuous SWCNT layers and shows the improvement in comparison with the previous reports on patterned SWCNT layers.

The measurement of a weak alternating magnetic field in unshielded space

In connection with attempts to use various types of sensors for measuring weak magnetic fields in geophysics, magnetobiology, and medicine in an unshielded space, the problem of comparing the results of these measurements arose. The issues of measuring a weak alternating magnetic field by various magnetic induction sensors in an unshielded space in the absence of obvious geomagnetic variations are considered. It is shown that the amplitude of natural geomagnetic noise in a quiet geomagnetic field in the absence of geomagnetic variations has a random character; therefore, gradient methods for measuring a weak alternating magnetic field are limited from below by the level of natural geomagnetic noise. The influence of the size of sensors of a weak alternating magnetic field on the results of measurements of broadband random geomagnetic noise is noted.

Designing the Composition of Cement-Stabilized Rammed Earth with the Association Analysis Application

The main advantage of the structural composite material known as cement-stabilized rammed earth (CSRE) is that it can be formulated as a sustainable and cost-saving solution. The use of the aggregates collected very close to a construction site allows economizing on transportation costs. Another factor that makes sustainability higher and the costs lower is a small addition of cement to the CSRE in comparison to the regular concrete. However, the low cement content makes the compressive strength of this structural material sensitive to other factors. One of them is the composition of the aggregates. Considering the fact that they are obtained locally, without full laboratory control of their composition, achieving the required compressive strength of CSRE is a challenge. To assess the possibility of achieving a certain compressive strength of CSRE, based on its core properties, the innovative algorithm of designing CSRE is proposed. Based on 582 crash-test of CSRE samples of different composition and compaction levels, along with the use of association analysis, the spreadsheet application is created. Applying the algorithm and the spreadsheet, it is possible to design the composition of CSRE with high confidence of achieving the required compressive strength. The algorithm considers a random character of aggregates locally collected and proposes multiple possible ways of increasing the confidence. They are verified through innovatively applied association analyses in the enclosed spreadsheet.

An Efficient Security Model for Password Generation and Time Complexity Analysis for Cracking the Password

Passwords tend to be one of the most popular approaches to protect operating systems and user’s data also. Most businesses rely on password protection schemes, and secure passwords are incredibly necessary to them. The proposed model typically aims to impose protection by forcing users to obey protocols to build passwords. For user protection, password has become a prevailing method in terms of exposure to scarce tools. The main problem with password is its consistency or power, i.e. how simple (or how difficult) a third person can be "assumed" to enter the tool that you use while claiming to be you. In operating systems, text-based passwords remain the primary form of authentication, following major improvements in attackers' skills in breaking passwords. The proposed Random Character Utilization with Hashing (RCUH) is used for generation of new passwords by considering user parameters. The proposed model introduces a new framework to design a password by considering nearly 10 parameters from the user and also analyze the time for cracking the generated password to provide the system strength. The proposed model aims to generate an efficient security model for password generation by considering several secret parameters from the user. To break a set of consistency passwords, analysis is also performed on time for password cracking. The tests show a close positive correlation between guessing complexity and password consistency. The proposed model is compared with the traditional password generation and cracking models. The proposed model takes much time in cracking the password that improves the systems security.

Lelonkiewicz_Ktori_Crepaldi_2020_Morphemes_as_letter_chunks

During visual word processing readers identify chunks of co-occurring letters and code for their typical position within words. Using an artificial script, we examined whether these phenomena can be explained by the ability to extract visual regularities from the environment. Participants were first familiarized with a lexicon of pseudoletter strings, each comprising an affix-like chunk that either followed (Experiment 1) or preceded (Experiment 2) a random character sequence. In the absence of any linguistic information, chunks could be defined only by their statistical properties - similarly to affixes in the real language, chunks occurred frequently and assumed a specific position within strings. In a later testing phase, we found that participants were more likely to attribute a previously unseen string to the familiarization lexicon if it contained an affix, and if the affix appeared in its typical position. Importantly, these findings suggest that readers may chunk words using a general, language-agnostic cognitive mechanism that captures statistical regularities in the learning materials. [NOTE: Please cite this paper as: Lelonkiewicz, J. R., Ktori, M., & Crepaldi, D. (2020). Morphemes as letter chunks: Discovering affixes through visual regularities. Journal of Memory and language, 115, 104152. https://doi.org/10.1016/j.jml.2020.104152 ]

Optimization of fastener pattern in airframe assembly

Purpose The authors consider the problem of optimizing temporary fastener patterns in aircraft assembly. Minimizing the number of fasteners while maintaining final product quality is one of the key enablers for intensifying production in the aerospace industry. The purpose of this study is to formulate the fastener pattern optimization problem and compare different solving approaches on both test benchmarks and rear wing-to-fuselage assembly of an Airbus A350-900. Design/methodology/approach The first considered algorithm is based on a local exhaustive search. It is proved to be efficient and reliable but requires much computational effort. Secondly, the Mesh Adaptive Direct Search (MADS) implemented in NOMAD software (Nonlinear Optimization by Mesh Adaptive Direct Search) is used to apply the powerful mathematical machinery of surrogate modeling and associated optimization strategy. In addition, another popular optimization algorithm called simulated annealing (SA) was implemented. Since a single fastener pattern must be used for the entire aircraft series, cross-validation of obtained results was applied. The available measured initial gaps from 340 different aircraft of the A350-900 series were used. Findings The results indicated that SA cannot be applicable as its random character does not provide repeatable results and requires tens of runs for any optimization analysis. Both local variations (LV) method and MADS have proved to be appropriate as they improved the existing fastener pattern for all available gaps. The modification of the MADS' search step was performed to exploit all the information the authors have about the problem. Originality/value The paper presents deterministic and probabilistic optimization problem formulations and considers three different approaches for their solution. The existing fastener pattern was improved.

Review of the genus classification of Abiinae (Cimbicidae, Hymenoptera)

Abiinae is the second-largest subfamily in Cimbicidae, a small family of true sawflies (Tenthredinoidea). The subfamily is adequately defined, but the generic classification has been unstable. Currently, only two genera are regarded as valid: Abia Leach, 1817 and Allabia Semenov & Gussakovskij, 1937. We evaluate the generic classification of Abiinae in a phylogenetic context. A total of 32 species (out of 57 described for the subfamily), including the type species of Allabia, Allabia infernalis (Semenov, 1896), are scored for 150 adult morphological characters. Results show some resolution, but only few clades can be circumscribed by consistent character combinations. Most of the characters that have previously been used to define genera are not congruent; consequently, most suggested genus definitions appear to be random character state combinations and few natural groups can be identified. For these reasons, we treat Allabia syn. nov. as a junior synonym of Abia and make the following additional taxonomic changes: Abia infernalis Semenov, 1896 comb. rev. and Abia malaisei (Semenov & Gussakovskij, 1937) syn. nov. For the purpose of long-term stability of the classification of Abiinae, we recommend recognizing only one genus, Abia, within the subfamily.

Stochastic Wiener filter in the white noise space

In this paper we introduce a new approach to the study of filtering theory by allowing the system's parameters to have a random character. We use Hida's white noise space theory to give an alternative characterization and a proper generalization to the Wiener filter over a suitable space of stochastic distributions introduced by Kondratiev. The main idea throughout this paper is to use the nuclearity of this space in order to view the random variables as bounded multiplication operators (with respect to the Wick product) between Hilbert spaces of stochastic distributions. This allows us to use operator theory tools and properties of Wiener algebras over Banach spaces to proceed and characterize the Wiener filter equations under the underlying randomness assumptions.

PRICE–VOLUME DEPENDENCE OF BITCOIN AND ITS FRACTAL ANALYSIS

Nowadays Bitcoin as cryptocurrency takes a significant place on the global financial markets. This paper analyzes the Bitcoin closing prices and traded volume during the period from December 28, 2013 to January 22, 2019. This period is known as a period with rapid increasing of the Bitcoin closing prices, mainly in the second half of the year 2017. The aim of this paper is twofold. First, we compute the Hurst coefficient to discover the close price dynamics and traded volume using a fractal point of view. We have discovered an anti-persistent behavior in the traded volume and random character of bitcoin closing prices. Second, we propose an analysis of the relationship between the close prices and traded volume. Our findings show how changes in the high-price period differ from changes in the low-price period. We also found that high prices caused investors to be afraid to trade due to possible rapid decrease in bitcoin closing prices.