Fundamental Method Research Articles

THE THEME OF THE DEPORTATION OF THE CHECHEN PEOPLE IN THE GRAPHIC CYCLE CROSSROADS OF MEMORY (1944-2019) BY RUSTAM YAKHIKHANOV

This study is the first to present an analysis of previously unexplored works that serve as an artistic response to the tragic events in the history of the Chechen people in 1944. Using the works of the graphic cycle by artist R. Yakhihhanov as an example, the study reveals the peculiarities of interpreting ideas and plots to unfold the theme of deportation. Drawing on the life experiences of senior family members and relatives who suffered political repression, the artist conveys personal tragedies and losses to the viewer.
 The aim of the research is to identify as well as philosophically and culturally analyze the artistic representation of the theme of the deportation of the Chechen people in the graphic cycle Crossroads of Memory, dedicated to the 75th anniversary of the deportation of the Chechen and Ingush peoples. Objectives: to uncover the ideological and moral aspects of the author’s graphic works, as well as to show the way the artist transforms his experiences into dynamic and memorable visual images; examine and analyze the ways in which the theme of deportation is embodied in the author’s works.
 Materials and methods. The work is primarily based on graphic works created between 2013-2018, as well as information from the catalogue of exhibitions by the Chechen artist. The fundamental research method is a comprehensive approach, incorporating methods of concrete-historical and semiotic analysis, figurative-stylistic analysis, as well as methods of extraction and explication.
 Results. In the images of the cycle Crossroads of Memory by R. Yakhikhanov, one can see a combination of artistic and documentary elements, modern graphic techniques, and traditional symbolic systems within the context of archetypes of traditional Chechen culture. The graphic canvases vividly and convincingly recreate the sense of pain felt by an entire nation due to the loss of their homeland. The main idea of the cycle is the belief in the courage, resilience, and sense of justice of the people who managed to endure these terrible years and return to their homeland with honour.
 Practical implications. The research findings can be applied in lectures and seminars on museum studies and cultural studies, in conducting tours in art galleries, and in compiling a catalogue of R. Yakhikhanov’s works.

The Rise of Digital Business Models: Thriving in the Post-COVID Era

The COVID-19 pandemic has become an undeniable reality and has forced the world to seek out a “new normal” as we move forward into a post-pandemic era. In the face of this crisis, businesses are now confronted with the difficult task of adapting their business models to fit this new reality, which has been directly influenced by the pandemic. These challenges are the direct result of the pandemic, and this research aims to explore the key obstacles that businesses must overcome as they navigate the post-COVID-19 environment. Additionally, we will discuss several fundamental transformative methods that firms can adopt to not only survive, but thrive in this “new normal” and beyond. We will also examine the importance of technology and the digital transformation that companies must undergo in order to remain competitive in today's technology-driven world.

Enhancing Individual Worker Risk Awareness: A Location-Based Safety Check System for Real-Time Hazard Warnings in Work-Zones

This study focuses on improving pre-emptive risk recognition and safety checks to prevent workplace accidents. It underscores improvements by addressing existing research issues, suggesting potential enhancements through system development. Work approval procedures and workers’ prior risk awareness, through the confirmation of work safety standards in physically separated work areas, are fundamental methods of preventing serious accidents and creating a safe work environment. A key factor concerning worker safety is recognizing the potential accident risk factors (or hazards) in advance through practical job hazard analysis and consequently take risk-reduction measures in case the safety standards are not met. Despite the crucial significance of pre-awareness of work risks at the majority of construction sites, tools to enhance this awareness are currently limited. Furthermore, real-time detection of work risks and the implementation of risk reduction measures are contingent upon a monitoring environment and a robust safety culture. This study proposed construction worker location-tracking technology that recognizes personal identification (ID). A safety check system based on location tracking combining personal quick response code (QR code) recognition and computer vision technology to automatically identify workers’ personal identities and track their physical location was proposed. A real-time safety check system was implemented to classify automatically whether workers have confirmed hazards and to approve a work process in high-risk workplaces by supervisors. Location-tracking technology with ID recognition performed the following two safety management functions. First, if a construction worker does not pre-check the work risk information before entering the work zone, the geofencing technology automatically classifies workers as those who are not aware of job hazards. Secondly, the safety manager or supervisor entering the on-site work zone possesses the authority to halt work if the work environment fails to meet safety standards and can issue warnings regarding risky situations. Essential functions were validated through a case study involving preliminary testing within the development system. To assess the practical application of the system, virtual simulations were conducted using recorded videos from a construction site to replicate the two essential functions of the system. The system was constructed using an Apache server and Python code, and for testing purposes, the names of the workers were randomized.

A new nuclear magnetic resonance-based permeability model based on two pore structure characterization methods for complex pore structure rocks: Permeability assessment in Nanpu Sag, China

The nuclear magnetic resonance (NMR) estimate of permeability is a fundamental method that has numerous applications in reservoir engineering and petrophysics. To improve the accuracy of the NMR-based permeability model, many variables are introduced into NMR-based permeability prediction models due to geometric complexity and pore structure heterogeneity. In this paper, two pore structure characterization methods are investigated based on the Kozeny-Carman model and equivalent component model. Furthermore, an NMR-based permeability model accounting for the effect of pore structure is developed based on the analysis of the relationship between two pore structure parameters, and it is applied to practically predict permeability. Results indicate that the new model-calculated permeability has good agreement with experimental data; moreover, the adaptability of the new NMR-based permeability prediction model is highly improved through reducing undetermined variables, and key parameters can be measured directly using NMR. The new model provides a valuable scientific resource and assists in the evaluation of hydrocarbon-bearing reservoirs with complex pore structure, such as tight sandstone, shale, and carbonate rock.

Automatic item generation for non-verbal reasoning items

The purpose of this study is to generate non-verbal items for a visual reasoning test using templated-based automatic item generation (AIG). The fundamental research method involved following the three stages of template-based AIG. An item from the 2016 4th-grade entrance exam of the Science and Art Center (known as BİLSEM) was chosen as the parent item. A cognitive model and an item model were developed for non-verbal reasoning. Then, the items were generated using computer algorithms. For the first item model, 112 items were generated, and for the second item model, 1728 items were produced. The items were evaluated based on subject matter experts (SMEs). The SMEs indicated that the items met the criteria of one right answer, single content and behavior, not trivial content, and homogeneous choices. Additionally, SMEs' opinions determined that the items have varying item difficulty. The results obtained demonstrate the feasibility of AIG for creating an extensive item repository consisting of non-verbal visual reasoning items.

A fundamental sequences method with time-reduction for one-dimensional lateral Cauchy problems

A fundamental sequences method is derived for the numerical solution of an ill-posed one-dimensional lateral Cauchy problem for a hyperbolic damped wave equation, including as a special case the parabolic heat equation. Either the Laguerre transform or the Houbolt finite difference scheme is applied to reduce the time-dependent lateral Cauchy problem to a sequence of second-order ordinary differential equations (ODEs) with function values and derivatives specified at the right endpoint of a finite space interval. A set of fundamental solutions is constructed, termed a fundamental sequence, to the differential equations. The solution of the obtained ODEs is approximated by a linear combination of elements in the fundamental sequence. Source points are placed outside of the solution interval in space, and by collocating at the endpoints of this interval a sequence of linear equations is obtained for finding the unknown coeficients. Tikhonov regularization is used to render a stable solution to the obtained systems of linear equations. Numerical results both for the parabolic and hyperbolic case confirm the efficiency of the proposed method including noisy data. The presented results complement the higher-dimensional case initiated in our previous researches.

Elemental analysis of hourly collected air filters with X-ray fluorescence under grazing incidence.

The X-ray fluorescence under grazing incidence condition (XRF-UGI) was applied for the direct analysis of aerosol filters. Particulate matter less than 2.5 microns (PM2.5) was collected hourly on polytetrafluoroethylene filters using a continuous PM monitor with a virtual impactor method. Although the sampling mass is in trace amounts of 5-30μg, the metallic contents, such as V, Cr, Mn, Fe, Zn, and Pb, can be measured at sub-ng m-3 detection limits. The effects of the non-uniformity and poor flatness of the PM filters were discussed with regard to the measurement repeatability. The relationship between the XRF-UGI intensities and the mass concentrations obtained via conventional X-ray fluorescence (XRF) analysis was confirmed using the fundamental parameter method. Finally, quantification was successfully demonstrated using the XRF-UGI results with the relative sensitivity factors.

COMPARISON OF ALGORITHMS FOR FUNDAMENTAL FREQUENCY DETECTION IN THE CONTEXT OF AUDIO PLUG-INS

This scientific article presents a comprehensive study of audio signals' fundamental frequency detection methods, focusing on both time-domain and frequency-based approaches and audio file processing since it is crucial for the post-processing part of the audio plug-ins for which this study is intended. Additionally, the article introduces self-repairing algorithms that adaptively identify and correct errors in the detected signals, ensuring robustness and accuracy in signal processing tasks and enhancing the overall detection performance. The findings from this study offer valuable insights into advancing signal processing techniques with broader implications across various domains.

Research on the Integration Teaching Mode of Traditional Music Elements and College Piano under the Background of Information Technology

Abstract With the deep integration of information technology and music education, how to integrate traditional music to innovate college piano teaching mode has become a problem that must be solved for the development of the times. Based on the scaffolding teaching method, this paper integrates traditional music elements with college piano in-depth and realizes the innovation of college piano integration teaching mode by adopting online pre-study before class, offline teaching during class and timely reflection and evaluation after class. In the teaching process, traditional music signals are represented by time-frequency domain features so as to realize the digital pre-processing of traditional music signals, and traditional music fundamental tone contours are transformed by using the fundamental tone feature extraction method. Then, based on the principles of physics, we explored the string vibration equation of the piano-generating principle and constructed a mathematical model for the piano music signal. To verify the effectiveness of this paper’s method in piano teaching in colleges and universities, relevant algorithms and teaching practices are used. The results show that the GNSDR of this paper’s method on vocals is improved by 6.58% compared with Unet, and its SDR is 4.25dB and 5.21dB when separating the two music source signals of Piano and Vocals, which is improved by 0.36dB and 0.14dB compared with SHN-4, respectively. The college piano scaffolding teaching model that integrates traditional music elements has enhanced sight-reading ability by 116.44%. Under the background of information technology, it is necessary to fully combine the relevant technology to extract the characteristics of traditional music elements so as to help teachers better carry out the design of piano music teaching programs and improve the quality of colleges and universities to cultivate piano talents who inherit traditional music.

On the Issue of the Typological Definition of the So-called “Central European Castell”

Typology is one of the fundamental archaeological methods that helps to organise large amounts of data and facilitates their handling. It is also used in castellology, where it categorises castles into various types, for example, on the basis of their layout, as observed in Czech castellology. Among these classifications, the socalled Central European castell has proved to be particularly problematic. Nevertheless, none of the representatives within this group completely aligns with the definition formulated by T. Durdík. The best-explored representatives of this group, which come closest to meeting the definition, are the castles in Písek and Kadaň. For this reason, they served as analogies for other supposed representatives, forming the basis for the conceptualisation of the original form. Recent research has cast doubts on their inclusion in this typological group. In contrast to the examples mentioned above, there are other sites that come close to the definition, yet their classification into the group of so-called Central European castell has been questioned, to say the least. The issues discussed in this article underscore the insufficient level of knowledge available regarding the representatives of the so-called Central European castell, effectively challenging the legitimacy of using this type in terms of an archaeological method. A potential solution to this situation lies in reclassifying them into another typological group, preferably within the category of castles with a perimeter layout, which would allow their further use. Moreover, such a merger would eliminate the artificial boundaries currently separating these related sites. Nevertheless, typology should primarily be regarded as a method that helps and simplifies the handling of accumulated data. Existing groups require revision to make them more applicable for further research. This should not be limited to the assessment of architectural and historical qualities; it should also incorporate other approaches that have been underutilised thus far. This will help to create a more nuanced understanding and improved comprehension of castle sites.

Exploring Parental Experiences With School-Aged Children Receiving Web-Based Learning: Cross-Sectional Study.

Web-based learning has transformed education. Its ability to overcome physical barriers and deliver knowledge at the click of a button has made web-based learning popular and ensured that it will continue to be used in the future. The involvement of parents in web-based learning is fundamental to the success of the educational process, but limited attention has been paid to the impact of web-based learning on parents. This study examined parental experiences with school-aged children receiving web-based learning in Jeddah, Saudi Arabia. We sent cross-sectional, anonymous web-based questionnaires to school-aged children's parents. A total of 184 parents completed the survey. Parents' negative experiences of web-based learning (mean 4.13, SD 0.62) exceeded their positive experiences (mean 3.52, SD 0.65). The most negative experience reported by parents was their child's boredom due to prolonged sitting in front of a device (mean 4.56, SD 0.69). The most positive experience was their child's technological skill enhancement (mean 3.98, SD 88). Their child's lack of social interaction and friendship building promoted stress among parents (r=-0.190; P=.01). At the same time, their child's technological skill enhancement reduced stress among parents (r=0.261; P=.001). The most reported (63/184, 34.2%) obstacle to web-based learning was having multiple learners in the same household. Web-based learning is a fundamental learning method and will continue to be used in the future because of its ability to overcome many barriers to education. Parental involvement in the continuity and success of the web-based learning process is crucial. However, the findings of this study illustrated that parents' experiences of web-based learning were more negative than positive. Parents who reported negative experiences reported an increase in stress and faced more obstacles due to web-based learning. Thus, more attention and intervention are needed to promote positive web-based learning experiences among parents.

Design automation system synchronization for cyber physical system with dynamic voltage and frequency scaling in industry 5.0

Recent innovations in determining power—including the Internet of Things, M2M, online services, computational AI, and ARM-based big little multicores for encased applications—have aided in developing industrial process automation. Advanced IP-enabled, the fifth edition of Industry guidelines, are being implemented via actuators, sensing devices, and processors in machinery automation. This allows for increased degrees of competence with less human participation. Because of these novel innovations, the SCPS (Smart et al.) will be pivotal in the next industrialization phase. Multiple integrated systems with varying software are interconnected in an SCPS to perform tasks such as calculation, interaction, supervision, and action. Based on our findings, we propose an inconsistent structure for SCPS that facilitates the execution of composite workflow dynamics via electrical, pneumatic, and hydrodynamic operations. By modeling system problems, instrument postponement, operator interruption, and translation interruption, the proposed design allows for the separation of all components of an operational change, including calculation, oversight, interactions, and activation. This allows us to disentangle these many components. Voltage frequency islands (VFI) with an elevated level of flexibility are used to allocate intellectually integrated components to the many different physical operations, with the amount of flexibility varying from procedure to procedure. All modeled process parameters are fine-tuned using the Variable Volt and Fundamental Shifting methods. In the coming era of manufacturing 5.0, where human involvement is also a part of the procedure in different industries like fuel, compost, paper goods, concrete, space travel, and motor vehicle manufacturing, the suggested layout would be best suited for implementation.

Exploring the Role of Desmoplastic Physical Stroma in Pancreatic Cancer Progression Using a Three-Dimensional Collagen Matrix Model.

Pancreatic ductal adenocarcinoma (PDAC) is a refractory tumor with a poor prognosis, and its complex microenvironment is characterized by a fibrous interstitial matrix surrounding PDAC cells. Type I collagen is a major component of this interstitial matrix. Abundant type I collagen promotes its deposition and cross-linking to form a rigid and dense physical barrier, which limits drug penetration and immune cell infiltration and provides drug resistance and metabolic adaptations. In this study, to identify the physical effect of the stroma, type I collagen was used as a 3D matrix to culture Capan-1 cells and generate a 3D PDAC model. Using transcriptome analysis, a link between type I collagen-induced physical effects and the promotion of Capan-1 cell proliferation and migration was determined. Moreover, metabolomic analysis revealed that the physical effect caused a shift in metabolism toward a glycolytic phenotype. In particular, the high expression of proline in the metabolites suggests the ability to maintain Capan-1 cell proliferation under hypoxic and nutrient-depleted conditions. In conclusion, we identified type I collagen-induced physical effects in promoting Capan-1 cells, which cause PDAC progression, providing support for the role of dense stroma in the PDAC microenvironment and identifying a fundamental method for modeling the complex PDAC microenvironment.

Proposal of a Combined AHP-PROMETHEE Decision Support Tool for Selecting Sustainable Machining Process Based on Toolpath Strategy and Manufacturing Parameters

Sustainable manufacturing technologies are the new challenge faced by enterprises, industries, and researchers. The development of a sustainability-based assessment method considering the environmental and economic impacts is crucial to realize viable manufacturing. However, few studies have addressed environmental economics and social flows using a common perspective. Mechanical machining is one of the most-used manufacturing techniques. The overall ecological, economic, and social footprint requires accurate and effective estimation and optimization. Several studies have addressed this issue by examining the entire process of machining, but sustainability flows for machining parameters and toolpaths have remained relatively unexplored. The lack of systematic assistance tools bridging the gap between decision-maker preferences and the three sustainability pillars—economic, social, and environmental—has impeded the widespread adoption of sustainable machining practices. To this end, this paper proposes an integrated approach to the decision-making problem that combines the Analytical Hierarchy Process (AHP) with the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) for selecting a sustainable machining strategy. The sustainability criteria are driven by manufacturing process parameters commonly employed and regulated during the manufacturing phase. This includes toolpath strategies as a qualitative input factor and manufacturing parameters such as cutting speed, feed rate, depth of cut, and stepover as quantitative input factors, affirming the practical applicability of the method in industrial contexts. New fundamental methods are also presented for selecting the most efficient machining parameters and toolpaths according to the weights assigned to each ecological, social, and economic footprint by the decision-maker (the manufacturer or production manager). In this way, sustainable machining strategies in the manufacturing industry will be strengthened in integrity. In a case study of part-end milling, both manufacturing parameters and toolpath strategies are considered to establish sustainable feature-based machining decisions.

A highly accurate indirect boundary integral equation solution for three dimensional elastic scattering problem

In this paper, we propose a numerical formula for three dimensional elastic wave scattering problem. Different from the classical boundary integral equation method, the three dimensional elastic scattering problem is transformed into a coupled boundary value problem including a scalar Helmholtz equation and a vector Helmholtz equation by the decomposition of the displacement. The coupled boundary value problem can be solved by the boundary integral equations based on the Helmholtz equation. A denseness result is given to support this algorithm. A comparative study with the classical method of fundamental solutions getting from the boundary integral equation method is given to check the accuracy with different types of boundary conditions. From the numerical results, the present method can give more accurate results than the classical method of fundamental solutions method.

A correspondence selection method based on same object and same position constraints

Establishing robust correspondences between two images is important for computer version tasks. However, in the real scene incorrect correspondences are inevitable no matter what kind of correspondence matching algorithms are adopted due to some complex factors, such as illumination, occlusion, and so on. To reduce the number of incorrect correspondences, an algorithm with the same object and same position constraints (SOSPC), is proposed to remove wrong correspondences from the given putative correspondences in this paper. The algorithm is based on the fact that in the given image pairs correct correspondences locate at the same position on the same objects. To select the correspondences on the same objects, an object matching method based on the correspondences selected by GMS is proposed. To select the correspondences on the correct positions, an iterative fundamental matrix estimation method based on clustering is presented. The experimental results have validated the effectiveness of the same object and the same position constraints, and the method achieves the state-of-art performance on five datasets.

Monochromatic wave equation reflection traveltime inversion

Wave equation reflection traveltime inversion (WRTI) is a fundamental method for interrogating the deep subsurface macrovelocity model. The time-domain WRTI calculates the gradient through the crosscorrelation of the source background and receiver scattered wavefields and the crosscorrelation of the source scattered and receiver background wavefields. During the backward propagation of the adjoint source, access to the source background and scattered snapshots of the entire propagation time is required. Because the source and receiver wavefields are extrapolated in opposite temporal directions, these source background and scattered wavefields are either stored in memory or reconstructed by additional wavefield extrapolation. This leads to a heavy memory burden and/or high computational cost. To address these challenges, we develop a new frequency-domain WRTI that is based on a monofrequency. By using the wavenumber coverage and gradient analyses, we prove that the monochromatic WRTI can produce comparable wavenumbers with time-domain and multifrequency-based WRTI. Our method directly stores monochromatic wavefields in memory because only one frequency is used for the gradient calculation. Therefore, our method significantly outperforms the conventional time-domain implementation in terms of memory requirement and computational cost. The accuracy of the monochromatic WRTI method is validated by gradient and result comparisons of several models with different complexities. Finally, we determine the effectiveness of our method by applying it to offshore streamer data.

In situ анализ кристаллической решетки нитридных однокомпонентных и многослойных покрытий ZrN/CrN в процессе термоциклирования

Introduction. Thermal expansion is an important thermal and physical characteristic of materials, showing its expansion when heated. Knowing this property is important both from a scientific point of view and for practical applications. Materials with low thermal expansion are widely used in electronics, thermal barrier coatings and other applications. Mismatch in thermal expansion between different materials can lead to thermal stress on contact surfaces. The in-situ synchrotron X-ray diffraction method can detect this mismatch. Thermal stress requires an analysis of the coefficient of thermal expansion. Bulk expansion behavior is observed in thermally sprayed coatings. The CTE is important for designing and predicting coating performance under thermal stresses. Changes in the KTE can cause cracking and degradation of the coating. In-situ X-ray diffraction analysis helps to understand thermal expansion, crystallite size and stress and strain variation with temperature change. The aim of this work is to interpret and use in-situ high temperature X-ray diffraction as an effective tool to study the thermal mismatch behavior of a W-Co alloy substrate (8 % w/w Co, WC — matrix) with CrN, ZrN and CrZrN multilayer coatings and the characteristic differences between single component coatings and its combination in a multilayer coating. Research Methodology. In this work, specimens of chromium and zirconium nitride coatings deposited on W-Co hard alloy substrates were investigated. The fundamental method in this work is in-situ analysis using synchrotron radiation. The lattice parameter as a function of cycling temperature, the coefficient of thermal expansion during heating and cooling, and the thermal expansion mismatch between the substrate-coating pair and the coating layers in the multilayer coating were evaluated. Results and discussion. The lattice parameters and thermal expansion of the coatings are investigated. The lattice parameter of all coatings decreased during thermal cycling, indicating nitrogen evaporation. The multilayer coating has the least change in the parameter, possibly due to diffusion barriers. Lattice distortions do not differ between single and multilayer coatings. All coatings exhibit thermal expansion similar to the substrate. The multilayer coating creates conditions for compressive stresses in one phase and tensile stresses in the other phase, so the lifetime of multilayer coatings is expected to be high.

3D real-time dynamic path planning for UAV based on improved interfered fluid dynamical system and artificial neural network

In complex and volatile unknown flight environments, the limited environmental information obtained by sensors in the face of sudden dynamic and static obstacles makes it extremely challenging for unmanned aerial vehicles (UAVs) to obtain a safe and efficient path to avoid obstacles and reach a designated target point. Therefore, a real-time dynamic path planning method based on an improved interfered fluid dynamical system (IFDS) and artificial neural network (ANN) is proposed to enhance path quality and computational efficiency. Firstly, to address the issue of insufficient sample quality and quantity, IFDS is employed as the fundamental method for path planning to simulate and generate an adequate amount of sample data for the ANN training. Then, an enhanced sand cat swarm optimization algorithm (ESCSO) with an adaptive social neighborhood search mechanism and Lévy flight strategy is proposed to improve the sample quality. Secondly, the information between the UAV and the target points and obstacles is extracted from the sample data as the input for the network, the parameters of the IFDS are used as the feature extraction at the output of the network, and the ESCSO is applied to optimize the weights and biases of the ANN, enabling offline training of the neural network. Finally, the trained neural network is utilized to dynamically output IFDS parameters based on the real-time environmental information obtained from the sensors, enabling the generation of real-time obstacle avoidance paths. Experimental results in a series of complex simulated environments demonstrate that the proposed method outperforms other algorithms in terms of path quality and meets real-time requirements. It provides excellent obstacle avoidance characteristics for the UAV.

Novel method of building train and test sets for evaluation of machine learning models related to software bugs assignment

Nowadays many tools are in use in processes related to handling bug reports, feature requests, supporting questions or similar related issues which should be handled during software development or maintenance. Part of them use machine learning techniques. In introduction is presented a review of fundamental methods used for evaluation of machine learning models. This paper points out weak points of currently used metrics for evaluation in specific context of the cases related to software development especially bug reports. The disadvantages of state of the art are related to disregarding time dependencies which are important to be applied for creating train and test sets as they may have impact on results. Extensive research of the art has been conducted and has not been found any article with the use of time dependencies for evaluation of machine learning models in the context of works related to software development applications like machine learning solutions to supporting bug tracking systems. This paper introduces a novel solution which is devoid of these drawbacks. Experimental research showed the effectiveness of the introduced method and significantly different results obtained compared to the state-of-the-art methods.