Local Components Research Articles

ДІАГНОСТИКА СТАНУ ПІДПРИЄМСТВА З ВИКОРИСТАННЯМ НЕЧІТКОГО АНАЛІЗУ

The article develops a methodical approach for assessing the overall state of an enterprise, taking into account the conditions of uncertainty in which it operates. It is based on the application of the strategic diagnostics tools, fuzzy set theory and fuzzy multi-criteria analysis. The article identifies the “state of the enterprise” concept. Diagnostics of the state of the enterprise is divided into two stages namely preliminary analysis of the general state of the enterprise and the stage of the direct assessment. We apply classic methods of strategic analysis and competitive analysis at the stage of preliminary analysis of the general state of the enterprise. The stage of the direct assessment is examined in detail. The study introduces a general algorithm for assessing the overall state of the enterprise by means of the fuzzy set theory tools. The algorithm contains seven stages: Stage 1. Establishing an expert group for assessing the state of the enterprise. Stage 2. Decomposition of the state of the enterprise into local components. Stage 3. Applying the Fuzzy AHP method to determine the importance of local components of the state of the enterprise. Stage 4. Decomposition of each local component of the enterprise’s state into assessment indicators. Stage 5. Applying the Fuzzy AHP method to determine the importance of the assessment indicators. Stage 6. Fuzzy assessment of the state of the enterprise by local components using the Fuzzy SAW method. Stage 7. Calculation of the integral assessment of the state of the enterprise applying the Fuzzy SAW method. The article provides a brief description of each of the above mentioned diagnostic stages. It is emphasized that the state of the enterprise is a multi-vector characteristic of the activity of any enterprise. For assessment, the conditional structure of the state of the enterprise is presented in the form of the local components, on the basis of which it is possible to calculate the integral indicator of the state of the enterprise. Considering the fuzziness of the source data, it is advisable to use expert assessments with their translation into triangular fuzzy numbers for assessing the state of the enterprise based on local components. We suggest applying the Fuzzy AHP method to determine the importance of the local components of the state of the enterprise and their assessment indicators and the Fuzzy SAW method to calculate the integral assessment of the state of the enterprise. Special attention is paid to the issues accompanying the process of assessing the state of the enterprise by means of a fuzzy approach. The results of assessing the state of the enterprise (in dynamics) and their interpretation allows the management of the enterprise to develop recommendations and take measures aimed at improving the local components of the state of the enterprise, and as a result, increase the level of the overall condition of the enterprise.

Pain type and neuropathic pain components in acute herpes zoster.

The aim of this study was to investigate the pain type (nociceptive or neuropathic) and neuropathic pain components in patients with acute herpes zoster (HZ). Patients with acute HZ referred to the outpatient Dermatology and Venereology clinic between January 2021 and January 2022 were retrospectively detected. The demographic data including gender and age, rash localization, pain severity, and neuropathic pain components were recorded. Pain severity and neuropathic pain components were evaluated using a Visual Analog Scale (VAS) and Douleur Neuropathique 4 (DN4), respectively. The study included a total of 58 patients, comprising 33 females and 25 males. Of these patients, 35 (60.3%) were found to have neuropathic pain. Itching, burning, pins and needles, and tingling were the most frequently reported neuropathic pain signs and symptoms. The proportion of female patients with neuropathic pain was found to be significantly higher than that of male patients (p=0.021). No significant differences were observed in the distribution of pain across different body sites or in the age of patients with neuropathic pain (p>0.05). Itching was significantly more common in younger patients (p=0.02). In conclusion, the study found that over half of the patients with acute HZ experienced neuropathic pain, and this was more frequently observed in female patients. Analysis of different components of neuropathic pain showed significant differences in age, gender, and site distribution. The findings of this study may have important implications for the manage-ment and treatment of acute HZ.

Modeling of Multiple Spatial-Temporal Relations for Robust Visual Object Tracking.

Recently, one-stream trackers have achieved parallel feature extraction and relation modeling through the exploitation of Transformer-based architectures. This design greatly improves the performance of trackers. However, as one-stream trackers often overlook crucial tracking cues beyond the template, they prone to give unsatisfactory results against complex tracking scenarios. To tackle these challenges, we propose a multi-cue single-stream tracker, dubbed MCTrack here, which seamlessly integrates template information, historical trajectory, historical frame, and the search region for synchronized feature extraction and relation modeling. To achieve this, we employ two types of encoders to convert the template, historical frames, search region, and historical trajectory into tokens, which are then collectively fed into a Transformer architecture. To distill temporal and spatial cues, we introduce a novel adaptive update mechanism, which incorporates a thresholding component and a local multi-peak component to filter out less accurate and overly disturbed tracking cues. Empirically, MCTrack achieves leading performance on mainstream benchmark datasets, surpassing the most advanced SeqTrack by 2.0% in terms of the AO metric on GOT-10k. The code is available at https://github.com/wsumel/MCTrack.

Alternative clean energy for sustainable growth and development of the Nigerian telecommunications sector

Telecommunications plays a crucial role in facilitating the transmission of voice, data, and multimedia over extended distances. This paper explores the significance of telecommunications, particularly in Nigeria, the largest ICT market in Africa, where telecom and internet usage hold substantial importance. However, the sector's heavy reliance on fossil fuels has resulted in environmental challenges. This research underscores the imperative to transition to clean energy sources, aligning with the commitment of the Nigerian Communications Commission. The paper presents a case study of a solar hybrid system designed to enhance Base Transceiver Station (BTS) coverage, emphasizing notable challenges such as elevated costs and the industry's familiarity with fossil fuels. The optimal power configuration for a BTS, as identified in the study, features a 16kW PV (photovoltaic) array, 14kW Diesel Generator (DG), 32kWh Battery Energy Storage System (BESS), and Utility, achieving the lowest Levelised Cost of Energy (LCOE) at $0.255/kWh. The production summary for the Solar PV array is 24,767 kWh/year (76%), the Diesel Generator is 1,250 kWh/year (4%), and the Utility is 6,503 kWh/year (20%). Consequently, the total estimated production is 32,520 kWh/year, constituting 100% of the energy requirement for the BTS. The study proposes solutions to challenges, including local clean energy component production, capacity building, and regulatory alignment. In conclusion, the adoption of clean energy is deemed essential for sustainability, with recommendations for policy adoption and efficient equipment utilisation.

Local Predictability Analysis-Based Significant Multipath Component Identification for OFDM Systems

Local Predictability Analysis-Based Significant Multipath Component Identification for OFDM Systems

Generalizable Polyp Segmentation via Randomized Global Illumination Augmentation.

Accurately segmenting polyps from colonoscopy images is essential for diagnosing colorectal cancer. Despite the tremendous success of the deep convolutional neural networks in automatic polyp segmentation, it suffers from domain shift issues, where the trained model yields performance deterioration on unseen test datasets. This paper proposes an illumination enhancement-based domain generalization approach to improve the generalization capability of the model on unseen test datasets and alleviate this issue. In particular, an image decomposition module (IDM) was developed to separate colonoscopy images into reflectance, local, and global illumination components. An illumination transform module (ITM) was proposed to augment images with different global illuminations by synthesizing target-like global illumination maps. A novel illumination variance insensitiveness (IViSen) is also introduced to evaluate the robustness of the model against illumination disturbance. IViSen is easy to compute and correlates well with model generalizability. The segmentation performance of the proposed model on four colonoscopy datasets was examined: CVC-ClinicDB, CVC-ColonDB, ETIS-Larib, and Kvasir-SEG. The method outperformed the competitive methods when tested on unseen domains. In particular, the proposed approach yielded 60.82% and 53.19% in terms of mean Dice and IoU, respectively, with 2.06% and 2.31% improvements.

Socially Responsible Operational Performance Industry 4.0 Framework Related to the Role of the Government in Health Device Producers

Because of the continued high volume of health product imports, followed by high government expenditure on imported health products, and strong government efforts to drive increased capacity of production of local health devices, it promotes increased production and technology support to domestic health device producers. The importance of producer performance, combined with the support of the latest technology Industry 4.0 towards domestic products that benefit the people and reducing state spending on imported products, would provide direction to producer in terms of social responsibility operational performance as part of the process of expanding the scope of use of health facilities for Indonesians. The objective of this study is to create a framework for Socially Responsible Operations Performance (SROP) as a new framework in the new normal era by emphasizing the need to adopt advanced Industry 4.0 technology in order to improve the operational performance of producers in the production of domestic health devices, as well as to boost government efforts to improve the use of local material components in the Indonesian health device industry. This is a qualitative study of two domestic health equipment manufacturers. The data were gathered through interviews with each company's director, who were asked questions about the topic of the study. Based on the interview with the directors, it can be concluded that the SROP framework can be applied to Indonesia’s condition, and the two factories under investigation are prioritizing three essential technologies—AI and IoT—in addition to 3D printers in order to boost manufacturing output.

Two-pore channel-2 and inositol trisphosphate receptors coordinate Ca2+ signals between lysosomes and the endoplasmic reticulum

Lysosomes and the endoplasmic reticulum (ER) are Ca2+ stores mobilized by the second messengers NAADP and IP3, respectively. Here, we establish Ca2+ signals between the two sources as fundamental building blocks that couple local release to global changes in Ca2+. Cell-wide Ca2+ signals evoked by activation of endogenous NAADP-sensitive channels on lysosomes comprise both local and global components and exhibit a major dependence on ER Ca2+ despite their lysosomal origin. Knockout of ER IP3 receptor channels delays these signals, whereas expression of lysosomal TPC2 channels accelerates them. High-resolution Ca2+ imaging reveals elementary events upon TPC2 opening and signals coupled to IP3 receptors. Biasing TPC2 activation to a Ca2+-permeable state sensitizes local Ca2+ signals to IP3. This increases the potency of a physiological agonist to evoke global Ca2+ signals and activate a downstream target. Our data provide a conceptual framework to understand how Ca2+ release from physically separated stores is coordinated.

Некоторые особенности исламской культуры Хорезма в эпоху Золотой Орды

Research objective: To analyze the features of the Islamic culture of Khwarezm and the role of the Turkic languages in the dissemination of Islamic knowledge. Research materials: The article is based on information from various written sources and publications of Russian, Kazakh, Turkish source scholars and historians that shed light on the role of the Turkic languages in the religious culture of Khwarezm in the Golden Horde period. Results and scientific novelty: As a result of the study, the author comes to the conclusion that in Khwarezm, Islam was represented by various practices manifested in the organization of rituals, Mutazilism, Sufi teachings, and the cult of saints. In the pre-Golden Horde period, the Muslim written culture of the region was dominated by the Arabic, Persian, and Khwarezmian languages. From the middle of the 13th century, Turkic writings appeared in dictionaries, and from the 14th century, religious literature appeared in the Turkic language. The main settled centers of the Turkic languages of the Ulus Jochi were Volga Bulgaria, Khwarezm, and the Syrdarya territories. The close interaction of the Turkic-speaking peoples of these territories, coupled with the policy of a certain part of the political elite to support the use of Turkic languages, manifested itself in the growth in the number of works in Turkic languages and the beginning of the formation of a single Turkic literary language. In this complex process, Khwarezm played the role of repeating the Arab-Persian cultural traditions with the participation of a certain local Turkic component. The scientific novelty of the article lies in the fact that, based on the analysis of sources and existing research, one can assume the development of the religious culture of Khwarezm based on the Arabic, Persian, and Turkic languages, which is confirmed by the increase in the number of works of a religious nature, the translation of the Holy Quran into the Turkic language, and the deve­lopment of Turkic religious terminology.

A family of Nonoverlapping Spectral Additive Schwarz methods (NOSAS) and their economic versions

NOSAS (Nonoverlapping Spectral Additive Schwarz) methods are nonoverlapping iterative domain decomposition methods for efficiently solving large sparse linear systems arising from elliptic problems with heterogeneous coefficients. NOSAS methods are of additive Schwarz types with local Dirichlet solver on each nonoverlapping subdomain Ωi, plus a coarse problem on the interface of the subdomains. The coarse problem has global and local interaction components which are associated respectively to low-frequency and high-frequency modes obtained locally from a generalized eigenvalue problem defined on each subdomain’s interface. In this paper, we propose several variants of the NOSAS methods by selecting different generalized eigenvalue problems and different coarse space extensions. Additionally, we propose an economic variant to reduce the complexity of these generalized eigenvalue problems. The analysis of all the variants is established, and numerical tests are provided.

SEPARATISM IN SCOTLAND AS A CHALLENGE OF GREAT BRITAIN’S POST-BREXIT UNITY

The article deals with the ontological aspects finding out of the separatist movement in Scotland as a phenomenon of political separatism, which contains the existing differences of ethnic units and state-political entities. The problem of separatism in the historical part of the Great Britain (country), Scotland, which since 2014 has chosen to leave the country, is considered. Attention is drawn to the fact that in the political life of modern British society, separatist sentiments in this country are the product of a long historical and political process, the conflicting pages of which are actively used by the “adult” elite of this region in the struggle for power. A distinctive feature of the modern Scottish separatism is its economic basis, which feeds the political strategy of the Scottish National Party. Considerable weight in the process of secession also belongs to the spiritual and cultural sphere, which over a long historical period formed a stable Scottish identity. It is stated that the Scottish version of separatism embodies the paradigm of political separatism in a distinct region, within which regional and local authorities, spiritual-cultural and socio-economic components function, which gives an additional leverage to the regional elite in the pursuit of independence from London. The factor that has accelerated the process of secession was Brexit, which has been opposed by the Scottish government. Keywords: separatism, Brexit, Scotland, Great Britain, Scottexit, independence, Scottish National Party.

Golden eagle based improved Att-BiLSTM model for big data classification with hybrid feature extraction and feature selection techniques

ABSTRACT The remarkable development in technology has led to the increase of massive big data. Machine learning processes provide a way for investigators to examine and particularly classify big data. Besides, several machine learning models rely on powerful feature extraction and feature selection techniques for their success. In this paper, a big data classification approach is developed using an optimized deep learning classifier integrated with hybrid feature extraction and feature selection approaches. The proposed technique uses local linear embedding-based kernel principal component analysis and perturbation theory, respectively, to extract more representative data and select the appropriate features from the big data environment. In addition, the feature selection task is fine-tuned by using perturbation theory through heuristic search based on their output accuracy. This feature selection heuristic search method is analysed with five recent heuristic optimization algorithms for deciding the final feature subset. Finally, the data are categorized through an attention-based bidirectional long short-term memory classifier that is optimized with a golden eagle-inspired algorithm. The performance of the proposed model is experimentally verified on publicly accessible datasets. From the experimental outcomes, it is demonstrated that the proposed framework is capable of classifying large datasets with more than 90% accuracy.

Idiomatic Toponymic Phrasemes in Bajan: Evidence from Amateur Paremiography

This study begins with the quantification of the paremiological inventory of Bajan, the English-based creole spoken in Barbados, by examining all the printed collections of proverbs, both amateur and professional, available to date. Consequently, by relying specifically on the amateur paremiographic work on Bajan compiled in 1987 by G. Addinton Forde, namely De Mortar-pestle: A Collection of Barbadian Proverbs, this article examines not just the proverbs but also the phrasemes which employ territorial place names found therein. In greater detail, this investigation is intended to show how the idiomatic use of such toponymic phrasemes yields cultural representations characterizing the unique worldview of Barbadians both within and outside the Anglophone Caribbean. Despite the fact that the colonial history of the island and the recollection of the slavery era are still undeniably evident in the toponymic Bajanisms considered, whose authentically local components are almost entirely drawn from the names of former plantations, the intrinsic Barbadianness that stands at their core is foregrounded.

Agricultural sector development and elasticity of its links with the food security level

Purpose. The purpose of the article is the assessment of the countries’ food security level and its connection with the agricultural sector results.
 Methodology / approach. The methodology for calculating the food security level is proposed by international organizations, national authorities, and individual researchers. Due to the fact that food security is a complex flexible concept and cannot be limited to the determination of one separate indicator, we propose to calculate a complex general indicator of food security level using the integral taxonomic estimation method and compare its results with those which provided by international organizations, in particular the Global Food Security Index developed by Economist Impact and supported by Corteva Agriscience and Food Security Index developed by Deep Knowledge Analytics. 
 Results. The article proposes the calculation of countries’ food security level using the integrated rating evaluation method and comparing its results with the results provided by different international organizations, identification of problematic local components of food security, and improving food security mechanism. Correlation coefficients and multivariate regression of dependence of global food security index on affordability, availability, quality and safety, sustainability and adaptation are presented. Functions of subjects of different levels of the hierarchy during interaction to ensure food security are considered. Components of food security ensuring mechanism, which will lead to innovations in food security, are proposed. The obtained results show that the availability of large fertile land and labor resources in the country, and the presence of favorable natural and climatic conditions for farming are insufficient for the high food security level, so it is also necessary to ensure food infrastructure in the country, the concern of the authorities for the citizens standard of living, ensuring political stability, etc. 
 Originality / scientific novelty. The level of food security is calculated and compared with the results of international organizations, using the maximum set of publicly available indicators, which include systems supporting food production, food distribution and supply chains, and food consumption indicators. The indicators that have the greatest impact on the food security level were identified, which will make it possible to influence these indicators timely to ensure a sufficient and acceptable food security level. 
 Practical value / implications. Timely research of ensuring food security, which depends mainly on agricultural products and is implemented through the possibility of purchasing food, taking into account its price, purchasing power, and availability in the appropriate quantity and quality will lead to social stability, meeting the food necessity, the country's independence from imports, the development of its food production, the creation of reserves to stabilize food security in an emergency, unforeseen circumstances in the future. The results of the research can be useful both for agricultural enterprises and for the authorities, which must pursue a balanced state agricultural policy, take care of farmers’ financing, timely resource provision, and ensure a stable, accessible, sufficient, safe, and balanced nutrition level of the population.

Texture characterization and classification of polarized images based on multi-angle orthogonal difference.

The Local Binary Pattern (LBP) and its variants are capable of extracting image texture and have been successfully applied to classification. However, LBP has not been used to extract and describe the texture of polarized images, and simple LBP cannot characterize the polarized texture information from different polarizations of angles. In order to solve these problems, we propose a new multi-angle orthogonal difference polarization image texture descriptor (MODP_ITD) by analyzing the relationship between the difference of orthogonal difference polarization images from different angles and the pixel intensity distribution in the local neighborhood of images from different angles. The MODP_ITD consists of three patterns: multi-angle polarization orthogonal difference local binary pattern (MODP_LBP), multi-angle polarization orthogonal difference local sampling point principal component sequence pattern (MODP_LPCSP) and multi-angle orthogonal difference polarization local difference binary pattern (MODP_LDBP). The MODP_LBP extracts local corresponding texture characteristics of polarized orthogonal difference images from multiple angles. The MODP_LPCSP sorts the principal component order of each angle orthogonal difference local sampling point. The MODP LDBP extracts the local difference characteristics between different angles by constructing a new polarized image. Then, the frequency histograms of MODP_LBP, MOD_LPCSP ,and MODP_LDBP are cascaded to generate MODP_ITD, so as to distinguish local neighborhoods. By using vertical and parallel polarization and unpolarized light active illumination, combined with the measurements at three different detection zenith angles, we constructed a polarization texture image database. A substantial number of experimental results on the self-built database show that our proposed MODP_ITD can represent the detailed information of polarization images texture. In addition, compared with the existing LBP methods, The MODP_ITD has a competitive advantage in classification accuracy.

The effect of voluntary hypoventilation in yoga breathing exercises on gas exchange and EEG activity in healthy trained subjects

Objective: to assess the effect of voluntary hypoventilation during yoga breathing exercises on gas exchange and EEG activity in a group of healthy, trained practitioners.Materials and methods: 25 volunteers (21 men and 4 women, average age 42.96 ± 9.19 years) performed hypoventilation yoga exercises with a decrease in respiratory rate to 1–1.5 times/minute. Registration of respiratory rate, tidal volume and minute volume of breathing, gas analysis of exhaled air (PetCO2, FeO2) and spectral analysis of electroencephalogram (EEG) in gICA model were carried out during breathing with a frequency of 1–1.5 times/minute and during relatively free breathing with mental calculation.Results: Breathing with a frequency of 1–1.5 times/minute causes a decrease in minute volume of breathing, the development of alveolar hypoxia and hypercapnia, which leads to an increase in the power of some local components in the slow delta, theta and alpha EEG bands. In addition, breathing with a frequency of 1–1.5 times/minute is accompanied by a decrease in the alpha- and beta-power of some components, the sources of which are located in the motor areas of the cortex, but is also accompanied by an increase in the power of components with widespread scalp topography in beta and gamma bands.Conclusion: Voluntary hypoventilation during yoga breathing exercises leads to the development of alveolar hypoxia and hypercapnia, accompanied by an increase in the power of local components in the slow EEG bands. At the same time, the alpha and beta powers of components localized in the motor areas of the cortex decrease, which may be a consequence of muscle tension during slow breathing.

Bayesian Structural Time Series Model for Forecasting the Composite Stock Price Index in Indonesia

One of the models that can be used to predict time series data is the Bayesian Structural Time Series (BSTS) model. The BSTS model is a more modern model and can handle data movement better. In the BSTS model, the Markov Chain Monte Carlo (MCMC) sampling algorithm is used to simulate the posterior distribution, which smoothes the forecasting results over a large number of potential models using Bayesian averaging models. The purpose of this study was to obtain the best BSTS model for Composite Stock Price Index (CSPI) data in Indonesia based on the state component and the number of MCMC iterations, and obtain forecasting results for CSPI value in Indonesia for the next 24 months, namely the period July 2023 to June 2024. The results obtained are based on a comparison of the R-square values in the model, the BSTS model with local linear trend and seasonal state components, and the number of MCMC iterations n = 5 00 is the best BSTS model that can be used for forecasting the CSPI value in Indonesia with an R-square value of 99.96%. The results of forecasting the CSPI value in Indonesia for the period July 2023 to June 2024 range from 6589 to 6760, with the lowest forecasting value in October 2023 and the highest in March 2023.

Simulating Stirred Tank Reactor Characteristics with a Lattice Boltzmann CFD Code

AbstractAlthough mixing in stirred tanks is common in the chemical and process industry, it is complex and not fully understood. In recent years, computational fluid dynamics (CFD) simulations with large eddy simulation turbulence models have become an important modeling tool. In this study, its current state for applicability to stirred tanks was evaluated. First, the power characteristics of different impellers were simulated and compared with experimental data. Second, Rushton and pitched blade turbines were validated in terms of the local velocity components, dissipation rates, and the trailing vortex. Finally, mixing times for different viscosity ratios were obtained from the CFD results and compared with a literature study. Hydrodynamics can be well predicted. However, mixing times for viscosity ratios larger than 1:100 are error‐prone.

Identification of recharge processes and mixing patterns by using CFC's and isotopic multi-tracing (δ18O, δ2H) of groundwater in a stratified volcanoclastic aquifer of the semiarid Amazcala Basin in Central Mexico

Understanding groundwater flow is essential for quantifying recharge and identifying relevant processes in an aquifer. Hydrogeochemical models have proven to be successful in identifying origin and processes during water recharge. We integrated the hydrogeochemistry, environmental isotopes and CFC technique to develop a conceptual and a groundwater mixing model of the Amazcala aquifer in Central Mexico. Results demonstrate that groundwater recharge consists of local meteoric recharge and a regional geothermal input. The local resident groundwater component represents the primary source of groundwater contributing with an average of 56% (σ = 0.07). The second crucial component of groundwater is the contribution of the local meteoric component contribution with averages to 23% (σ = 0.05). The third component is the regional geothermal component, which on average contributes to 21% (σ = 0.03). Regional geothermal influence has been reported in several aquifers in volcanic regions. This geothermal input influences volcanic aquifers located in the Trans-Mexican Volcanic Belt and should be considered in the water balance budget. Excessive groundwater extraction raises the vulnerability of the aquifer to natural and/or anthropogenic pollution, affecting the quality of water. Understanding the hydrogeological system offers a useful framework for developing and executing Managed Aquifer Recharge strategies (MAR).

Local positive sequence component based protection of series compensated parallel lines connecting solar photovoltaic plants

Local positive sequence component based protection of series compensated parallel lines connecting solar photovoltaic plants