Methodology Scheme Research Articles

UAV vision-based crack quantification and visualization of bridges: system design and engineering application

Accurately measuring visible cracks in bridges is crucial for their structural health diagnosis, damage detection, performance evaluation, and maintenance planning. The primary means of visual crack detection still relies heavily on manual visual inspection, an inefficient process that can pose significant safety risks. This article develops a unmanned aerial vehicle (UAV) vision-based surface crack measurement methodology and visualization scheme for the bridges that can detect and measure cracks automatically with improved efficiency. The surface crack measurement methodology is achieved by designing a three-stage crack sensing system including the You Only Look Once-based crack recognition, U-shaped network-based crack segmentation, and deep-vision-based crack width calculation. This workflow is integrated into a comprehensive UAV inspection system, which is intended for operation at the field. The surface crack visualization scheme is accomplished by taking advantage of time-series image fusion, GPS information migration, and three-dimensional (3D) point cloud technique to reconstruct the 3D geometrical model of the tested bridge, which is convenient for unveiling the crack information in the bridge. The proposed methodology was successfully validated by a case study on an arch bridge. The achievement of this article promotes the UAV vision-based bridge’s surface crack inspection technology to a new status that no preparation for pasting calibration marker is needed, and crack identification, segmentation, and width calculation are realized promptly during the UAV flying on-site, as well as damage evaluation for bridges is visually fulfilled based on the reconstructed digital-graphical 3D model. The working environments and influencing factors to the developed system are sufficiently discussed. Certain limitations in the current application are pointed out for future improvements.

Optimization Method of Multi-Mode Model Predictive Control for Wind Farm Reactive Power

This paper presents a novel approach for optimizing wind farm control through the utilization of a combined model predictive control method. In contrast to conventional methods of controlling active and reactive power in wind farms, the suggested approach integrates a wind power prediction model driven by a neural network and a state-space model for wind turbines. This combination facilitates a more precise forecast of active power, thereby enabling the dynamic prediction of the range of reactive power output from the wind turbines. When combined with the equation of state in wind farm space, it is possible to accurately optimize the reactive power of a wind farm. Furthermore, the impact of active power on voltage fluctuations in the wind farm collector system was examined. The utilization of model predictive control enhances voltage regulation, optimizes system redundancy, and increases the reactive capacity. Sensitivity coefficients were calculated using analytical methods to enhance computational efficiency and to resolve issues related to convergence. In order to validate the proposed methodology and control scheme, a wind farm simulation model comprising 20 turbines was developed to assess the feasibility of the scheme.

Features of Wear of Gears of Agricultural Machinery

Abstract The paper presents data on the resource and wear of the gears of agricultural tractor transmissions, on the basis of which the research problem and the novelty of the proposed methodology are formulated, based on the development and application of the stress state model of the gear, taking into account surface hardening. The methodology and calculation scheme for determining the power parameters of gearing are described in detail. In this case, the dependences and results of previous studies in the field of increasing the durability and reducing the wear of gears of transmission elements of vehicles of various functional purposes were used. To achieve this goal, the mathematical models of the stress state of gears are constructed without the presence of an external diffusion hardening coating and with a coating. Based on the simulation of the process of interaction of rubbing pairs of gears, the distribution of stresses in the contact zone over the surface layer of non-hardened and cemented to a depth of 1 mm gears, as well as the dependence of deflection on the thickness of the cemented layer and the deformation of the cemented layer during operation was established. Considering the research results given in literature, as well as those obtained on the basis of our own research, it should be noted that the analysis of gear stress state is an important direction in the study of the durability of gear units, the entire gearbox, and other gears of tractor transmissions and automotive technology at the present time. At the same time, the actual task is to establish the ratios of the allowable wear of gears and the limiting value of displacement of the centre distance, taking into account changes in the stress state scheme when using various types of coatings.

Machine Learning in Pattern Recognition

Supervised or unsupervised classification is the main objective of pattern recognition. The statistical approach is the most popular approach that is practised among the several frameworks where pattern recognition is initially formulated. In the recent past, the neural network technique and the methodology scheme from the statistical learning theory have garnered the attention of people. It requires proper attention to deal with the design of the recognition system. There are several issues associated with the design of the recognition system. They are the pattern class definition, sensing environment and representation extraction and selection of features, cluster analysis, classifier design, learning, and choosing the training and test samples. There is no solution to the general issue of recognizing complex patterns associated with arbitrary patterns. Data mining, web searching, and retrieval of multimedia are the various emerging applications that require proper and effective regulation techniques. The main purpose of this paper is to give a detailed overview of the various methods that can be used in the different stages of the pattern recognition system. The paper also aims to figure out the research topics in the application that can be highlighted in this challenging field.

Технология производства бионутриентов на основе активированных копролитов и оценка их эффективности

The production of bionutrients in the conditions of industrial production and agricultural enterprises requires the development of technology and a production line for the production of bionutrients of stable quality without the use of chemical reagents. To this end, the authors have developed a technology and a technological line for the production of bionutrients based on the processing of animal waste into coprolites and the use of cavitation to increase their biological efficiency. The article presents the methodology and technological scheme of the production of bionutrients. The technology and the obtained bionutrient ABT-Plant were tested in the Belgorod region on sugar beet LMS-94. In the control sample, the seeds were moistened with water. In four variants, ABT-Plant bionutrient was treated: in the fi rst - seeds; in the second - spraying of vegetative sugar beet plants in the phase of 6-8 real leaves (20 g·t-1); in the third - spraying of vegetative plants (15 g·ha-1) before closing the leaves in the row spacing of sugar beet; in the fourth - seed treatment (20 g·t-1) and spraying of vegetative plants (15 g·ha-1) before closing the leaves in the row spacing of sugar beet. The positive eff ect of the bionutrient ABT-Plant on the productivity of sugar beet has been established. The best results were achieved when the ABT-Plant preparation was used twice during seed treatment (20 g·t-1) and the vegetation period of plants in the phase of closing beet leaves in row spacing (15 g·ha-1) provided an increase in the yield of sugar beet of 3.5 t·ha-1. The sugar content of sugar beet increased by 5.5-6% compared to the control, the sugar harvest by 0.85 t/ha or by 11.2%.

METHODOLOGY OF CONSTRUCTION OF TRANSPORT AND TECHNOLOGICAL SCHEMES OF DELIVERY OF SUPPORT MEANS FOR MAINTENANCE OF COMBAT AIRCRAFT AT THE AIRPORTS OF UKRAINE

The article analyzed the existing methods of building technologies for the maintenance of civil and military aircraft and identified mathematical methods that can be used to study the prospects for the development of aircraft maintenance systems, which allowed to form the purpose of the study in this development. The chosen topic is quite relevant, because the formation of transport and technological schemes for the delivery of support for the maintenance of combat aircraft can increase the efficiency of resource use and reduce the time for training at Ukrainian airports in a conflict situation. One of the ways to reduce maintenance time is to determine the effective distribution of transport and technical means for the preparation of aircraft. It was established that in the scientific developments of foreign scientists, solutions were proposed related to the construction of transport and technological schemes for the delivery of support for the maintenance of various types of aircraft. Most of these solutions were aimed at using agent-based simulation models for application to the process of generating combat sorties of aircraft - this made it possible to process a large amount of data and generate management decisions in the transport service system. Also, most authors propose to take into account the conditions of uncertainty and time constraints when building a methodology to improve the efficiency of aircraft maintenance. An algorithm for the rational distribution of transport resources for aircraft preparation at Ukrainian airports has been developed, based on the results of simulation modeling of the aircraft maintenance process under different service conditions (time of day and climatic conditions that affect the time of aircraft maintenance and the time of movement of vehicles along transportation routes). On the basis of the developed algorithm of rational distribution of transport resources for aircraft preparation, the technology of aircraft maintenance at Ukrainian airports is proposed, which indicates the sequence of operations aimed at determining and comparing the normative values of the duration of maintenance of the corresponding aircraft with the calculated values and determining their rational number. Keywords: methodology, transport and technological scheme, means of support, combat aircraft, airports.

Анализ показателей противодефляционной эффективности полезащитных лесных насаждений в засушливой зоне Cтавропольского края

The problem of soil degradation is widespread in many agricultural regions of our country. The Stavropol Territory, as one of the leading agricultural regions, is no exception. It is characterized by the presence of a number of factors influencing the destructive processes in the soil, the main of which are the increase in the anthropogenic load on the soil and the regional features of climate change. In this regard, the relevance of issues related to the development of comprehensive measures to combat degradation processes is increasing every year. A key element of these activities in the Stavropol Territory is the formation of a framework of protective forest plantations, which requires regular monitoring of both their safety and effectiveness. The study was conducted on the territory of the arid zone of the Stavropol Territory. In this zone, the observed regional climatic changes can cause significant damage to the soil cover and significantly reduce the efficiency of agricultural production. Here, the increase in climate extremeness is most acute—an increase in the likelihood of droughts and heavy rainfall. Due to the fact that protective forest plantations are located on vast areas, it is most rational to use modern data processing and visualization systems for their monitoring—geographic information systems and Earth remote sensing data. The author’s technique was considered in the work, which allows analyzing various characteristics for assessing the anti-deflation efficiency of field-protective forest plantations, such as the protective forest cover of the territory and interstrip distances. As part of the study, a technological mapping scheme was proposed based on the formation of a continuous hexagonal surface with data. The presented methodology and technological scheme can be adapted for any agricultural region, taking into account their characteristics.

Digital Support for Renal Patients Before and During the COVID-19 Pandemic: Examining the Efforts of Singapore Social Service Agencies in Facebook.

During the coronavirus disease 2019 (COVID-19) pandemic, social service agencies (SSAs) play a crucial role in supporting renal patients, who are particularly vulnerable to infections. Social media platforms such as Facebook, serves as an effective medium for these SSAs to disseminate information. Content analysis of the SSAs’ Facebook posts can provide insights on whether Facebook has been adequately utilized during the COVID-19 pandemic and enable SSAs to improve their social media use in future pandemics. This study aimed to compare renal-related SSAs’ Facebook post content before and during the COVID-19 pandemic. Facebook posts of three SSAs National Kidney Foundation (NKF), Kidney Dialysis Foundation (KDF), and Muslim Kidney Action Association (MKAC), posted during the pre-COVID-19 period (January 23, 2019 to June 2, 2019) and the peri-COVID-19 period (January 23, 2020 to June 1, 2020) were extracted. A classification scheme was developed by two coders with themes derived inductively and deductively. Each Facebook post was assigned with a theme. Quantitative analyses indicate that the number of Facebook posts increased from 115 in the pre-COVID-19 period to 293 in the peri-COVID-19 period. During peri-COVID-19, posts regarding lifestyle changes, donations and infectious disease surfaced. While the proportion of posts about encouraging kindness increased from one to 77 posts, the proportion of posts about community-based events and psychosocial support decreased from 44 to 15 posts and 17 to 10 posts respectively during the two periods. Facebook was found to be well-utilized by two of the three renal SSAs in engaging their beneficiaries during the pandemic. During future pandemics, renal SSAs should place emphasis on posts related to psychosocial support and encouraging kindness. Further studies are required to ascertain the impact of COVID-19 from the perspective of renal patients and also to validate the classification scheme which was developed in this study. The study’s methodology and classification scheme can be used to guide future studies for evaluating the social media outreach performance of renal health support groups.

Multi-objective optimization of AAJM process parameters for cutting of B4C/Gr particles reinforced Al 7075 composites using RSM-TOPSIS approach

The present study deals with the machining of hybrid Al 7075/B4C/Gr composite using Abrasive Aqua Jet Machining. The effects of selected input factors, i.e., water jet pressure (WJP), stand-off distance (SOD), and traverse speed (TS) on the performance characteristics, namely taper angle (TA), surface roughness (Ra), and the material removal rate (MRR) are investigated. The experimental runs and test strategies are formulated using the Response Surface Methodology-Central Composite Design approach. Analysis of Variance (ANOVA) was used to examine the effect of input factors and their interactions with performance characteristics. MRR, Ra, and TA optimum condition and mathematical equations were also developed. Further, the multi-optimization method “Technique for Order of Preference by Similarity to Ideal Solution” is considered to find out the best combinations of input factors for optimized output factors on the hybrid composite. The ANOVA results confirm that among the input factors, WJP and SOD are the most significant factors, and the percentage distribution of input factors are found to be jet pressure (55.21%), stand-off distance (23.36%), and traverse speed (2.56%). The multi-objective optimum conditions of the input factors are WJP (A1) 210 bar, SOD (B1), and TS (C3) 30 mm/min, that produce optimal values of the considered responses, i.e., MRR up to 4.8703 mm3/min, Ra up to 3.57 μm and TA up to 0.189°. The TA has improved by 49.6% through the multi-objective optimum results when compared with single parameter optimized results.Article HighlightsHybrid Al7075/B4C/Gr composite fabricated through the rotary stir casting techniqueExperimental planning and designing layouts using Response Surface Methodology scheme and mathematical equations are produced with Design Expert 11.0.The best TA was obtained by RSM-TOPSIS approach, found at a lower WJP and SOD and a higher TS.

Main methodology provisions of forecasting socio-economic results of agriculture’s innovative development

The monographic analysis of the subject area under consideration was performed and the peculiarities of innovative development forecasting organization of the economy in Russia and abroad were defined, including the list of approaches and methods that have become most practically common in different countries. The peculiarities of innovative development of agriculture in Russia, its main directions and groups of applied innovations were revealed. It was established that at present agricultural producers are poorly involved in innovations’ creation and mainly act only as their consumers at high prices set by high-tech companies. Conceptual methodology scheme for forecasting socio-economic results of agriculture’s innovative development was proposed including a system of principles, approaches, methods, and expected results and allowing it to justify individual forecasts for separate enterprises with different organizational and economic characteristics and level of technical and technological development.

An Integrated Boost-LC-Resonant-Flyback Multimode Converter for Battery Charger Applications

An integrated boost-LC-resonant-flyback multimode converter with a wide voltage gain is proposed in this article. With three different pulsewidth modulation strategies, the proposed converter can realize three modes including high-, medium- and low-voltage-gain (LG), by multiplexing inductors and power switches. In the high-voltage-gain mode, it has better load characteristics than the conventional LLC converter through an extra energy storage stage. In the medium-voltage-gain mode, the working condition is similar to that of the conventional LLC converter, but the issues of current reflow and circulation can be addressed than reducing the conduction loss. In the LG mode, the proposed converter works as a flyback converter, and it has a higher conversion efficiency and simpler operation state than the conventional LLC converter. Additionally, all power switches can realize zero-current switching over a wide load range. The operating principle, voltage gain, design methodology, and control scheme are fully presented in this article. Finally, a laboratory prototype with 110 V input voltage, 0-5 A output current, and 24-165 V output voltage was conducted and verified the proposed solution.

Self-Powered 6LoWPAN Sensor Node for Green IoT Edge Devices

In this paper, a simulation model and practical testbed for green Internet of Things (IoT) edge devices are proposed based on solar harvester with constant voltage-maximum power point tracking (CV-MPPT) technique. Billions of connected edge devices represent the essential part of the IoT through the IP-enabled sensor networks based on IPv6 over Low power Wireless Personal Area Network (6LoWPAN). In traditional IoT edge devices, the stored energy in the non-rechargeable battery determines the node lifetime while it is being depleted with time. Therefore, purchasing billions of such batteries is costly and must be disposed of efficiently. This paper is aimed at simulating and implementing a new class of green IoT edge devices that can report data wirelessly and powered perpetually using clean energy. The developed edge device utilizes solar energy harvesting mechanism through photovoltaic (PV) module, this approach will avoid periodical battery replacement and hence, the energy supplied to the sensor mode is not limited anymore. The implemented testbed is based on open-source hardware and software platforms while the simulation environment is based on MATLAB/SIMULINK 2019a. The effects of temperature and solar irradiance on the performance of the developed approach are examined in order to confirm the leverage of the proposed methodology scheme. The lifetime of the developed green IoT device is predicted based on the device’s activities, current consumption, and energy storage capacity. The obtained results showed that the battery lifetime is extended by 38-49% when the edge device runs on an independent power source.

A Current-Fed LCL Resonant Converter for Wide Output-Voltage Applications

This article proposed a novel current-fed LCL resonant converter with a simple structure by multiplexing inductors and switches for wide output voltage applications. With three different pulsewidth modulation methods, the proposed converter can work at three voltage gain modes, namely high gain (HG), medium gain (MG), and low gain (LG). In HG mode, it has a higher voltage gain than the conventional LCL converter by an extra boost energy storage stage. In MG mode, it operates similarly as a conventional LCL converter. In LG mode, it is equivalent to a flyback converter in discontinuous conduction mode (DCM), which achieves higher efficiency and is easier to be controlled than an LCL converter. In these three modes, all power switches and rectifier diodes can obtain soft-switching performance, increasing the power conversion efficiency. The operating principle, design methodology, and control scheme are explained and verified by a laboratory prototype with 520 W output power, 30–150 V output voltage.

New Fusion Algorithm for Improving Secondary Forest Cover Mapping

Secondary forests play a central role in recovering earlier lost carbon and biodiversity viadeforestation and degradation, yet little data is applicable to the magnitude of numerous successionphases. Such information is considered a priority in tropical regions with elevated past and currentdisturbance rates; however, regrowth in the area is rapid. Focusing on Kuala Krai district, Kelantanstate, Malaysia, this paper offer a new fusion algorithm by using the clustering method (fuzzy k-means(FKM)) and Vector Supporting Machines (SVM) procedures. The methodology scheme applied wassplit into two phases, a clustering map firstly was acquired using FKM from the Sentinel-2A MSI (10 m)image; at the same time, the initial image used to extract Green Normalized Vegetation Index (GNDVI)layer. Using SVM classifier, the classification map was created. Second, SVM and FKM fusion as ahybrid classifier were tested, verified and compared to MLC-parametric and SVM-nonparametricclassification algorithms. The study results reveal the effectiveness of the GNDVI layer and FKMsegmentation map to enhance SVM classification through applying the Sentinel-2A MS image byapproximately 8 % and 14 %, respectively, as opposed to SVM and MLC. Thus this study is inspiringas it is extremely difficult to generate a reliably map land cover in heterogeneous areas, especially intropical areas, and yet this job is crucial for conservation projects, climate change mitigation strategies,and expansion plans and regional development policies. doi: https://doi.org/10.23953/cloud.ijarsg.456

Formalizing atom-typing and the dissemination of force fields with foyer

A key component to enhancing reproducibility in the molecular simulation community is reducing ambiguity in the parameterization of molecular models used to perform a study. Ambiguity in molecular models often stems from inadequate usage documentation of molecular force fields and the fact that force fields are not typically disseminated in a format that is directly usable by software. Specifically, the lack of a generally applicable scheme for the annotation of the rules of a particular force field and a general purpose tool for performing automated parameterization (i.e., atom-typing) based on these rules, may lead to errors in model parameterization that are not easily identified. Here, we present Foyer, an open-source Python tool that enables users to define and apply force field atom-typing rules in a format that is both human- and machine-readable and provides a framework for force field dissemination, thus eliminating ambiguity in atom-typing and improving reproducibility. Foyer defines force fields in an XML format, where SMARTS strings are used to define the chemical context of a particular atom type and “overrides” are used to set rule precedence, rather than a rigid hierarchical scheme. Herein we describe the underlying methodology and force field annotation scheme of the Foyer software, demonstrate its application in several use-cases, and discuss specific aspects of the Foyer approach that are designed to improve reproducibility.

Scientific and methodological basis of tourist services quality assessment

The article considers the quality assessment methods of tourist enterprise services. The authors conducted a research of scientific approaches and offered their own of assessing methodology scheme quality of tourist services quality. The main directions of tourist services quality assessment are determined and indicators which influence on the overall assessment of the tourists service quality are defined. It was determined that the indirect assessment of quality indicators is typical for goods and services of tourist destination. It was noted that the tourist product quality and service quality at tourism enterprises are latent indicators, i.e. they are immeasurable directly and described by a set of so-called characteristics-symptoms. Hence, the correct evaluation results can be obtained via a purely of comparative multivariate analysis methods. As a part for the quality assessing toolkit of the tourist product and the service quality at the tourist enterprises, it was proposed to use the taxonomic analysis method, which has a number of significant advantages compared with other methods of multivariate analysis. This methodology can serve as a basis for further management improvement of tourism enterprises services quality and also management decision making. It was determined that the management of tourism enterprises should be direct a quality management to the constant adaptation and perfecting of modern evaluating methods and improving the services quality, and also developing their own quality management systems, introducing international and national quality management standards with the purpose of profitability insuring of economic activity of own enterprises.

Mathematics for biological sciences undergraduates: a needs assessment

ABSTRACTThe purpose of this study was to investigate the mathematical needs of biological sciences undergraduate students. Student needs were measured through a needs assessment methodology scheme that included a content analysis of peer-reviewed journals, a nationwide cross-sectional survey, and semi-structured interviews. The research question that guided the study was: what are the mathematical needs of biological sciences undergraduate students as perceived by certain stakeholder groups? The stakeholder groups represented the areas of ecology, evolution, and behaviour, and developmental biology to portray two extremes in the use of mathematics. Major findings included: (1) The use of mathematics to support experimental design is the most consistent need across disciplines. (2) An overall understanding of mathematical models is needed as a minimum for scientific literacy. (3) Evolution and animal behaviour students need descriptive and inferential statistics, stochastic processes, differential equations, and mathematical models in general. Developmental biology students, on the other hand, need only descriptive and inferential statistics, and mathematical models. These needs, however, strongly vary depending on students’ career tracks within their subdisciplines, suggesting the necessity of a flexible undergraduate curriculum.

An Efficient Fault Tolerance Technique for Through-Silicon-Vias in 3-D ICs

Three-dimensional integrated circuits (3D-ICs) based on Through-Silicon-Vias (TSVs) interconnection technology appeared as a viable solution to overcome problems of cost, reliability, yield and stacking area. In order to be commercially feasible, the 3D-IC yield must be as high as possible, which requires a tested and reparable TSVs. To overpass this challenge, an integration of interconnect built-in self-test (IBIST) methodology for 3D-IC is given in the aims to test the defectives TSVs. Once the interconnection has been tested, the result extracted from IBIST initiate the repairing defectives TSVs based on the built-in self-repair (BISR) structure. This paper superposed two fault tolerance techniques in particularly the redundant TSV and the time division multiplexing access (TDMA) in case of multi defectives TSV. This novel repair architecture increase the yield of 3D-ICs in a high failure rate. It leads to 100% reparability for 30% failure rate. A parallel processing approach of the proposed structure is presented to accelerate the test and repair operations. Achieved experimental results with the proposed methodology scheme show a good performance in terms of repair rate and yield.

Exact evaluation of hydrodynamic loads on ships using NURBS surfaces and acceleration potential

The development of an accurate surface intersecting methodology and adaptive acceleration potential scheme, in order to precisely compute pressure on the wet surface of ships hulls, is presented. Non-Uniform Rational B-Spline (NURBS) surfaces are used to describe the ships hulls and the free surface evolutions. The intersection of free surface with ship hull is found by solving the resultant system of equations yielded from surface intersecting scheme. The pressure distribution over the exact wet surface of ship hull surface is obtained based on acceleration potential in a time domain simulation. Hence, implicit body boundary condition is applied to evaluate the time derivative of velocity potential on the hull surface in a fully nonlinear numerical wave tank. On the other hand, tangential derivatives of the velocity potential on the wet surface are approximated by B-Spline surface. Wave propagation is considered to examine the accuracy and convergence of the present solution. Motions of a Wigley hulls in linear wave are compared with experimental measurements and prior numerical solutions to verify the present numerical procedure. Also, fully nonlinear motions of a Wigley hull in nonlinear wave is simulated.

Concurrent Topology Optimization of Lightweight Cellular Materials and Structures

In this paper, a two-stage optimization algorithm is proposed to simultaneously achieve the optimum structure and microstructure of lightweight cellular materials. Microstructure is assumed being uniform in macro-scale to meet manufacturing requirements. Furthermore, to reduce the computation cost, the design process is divided into two stages, which are concurrent design and material design. In the first stage, macro density and modulus matrix of cellular material are used both as design variables. Then, the optimum topology of macro-structure and modulus matrix of cellular materials will be obtained under this configuration. In the second stage, topology optimization technology is used to achieve a micro-structure of cellular material which is corresponded with the optimum modulus matrix in the earlier concurrent design stage. Moreover, the effectiveness of the present design methodology and optimization scheme is then demonstrated through numerical example.