bluuebunny/crossref_metadata_2025 huggingface dataset:
Socio-Cultural Impact of Church Building in Russia (the Case of the Cathedral of Saint Martyr Catherine in Ekaterinburg)
Authors: Daineko L V , Goncharova N V , Larionova V A , Karavaeva N M , Sheveleva A E
Published: March 2021

In recent years, Russia has been going through a boom of church building. In 2009, the Russian Orthodox Church (ROC) had 29,263 parishes and by 2019 this figure had risen to 38,649. In the last decade, the growth in the number of Orthodox religious organizations and places of worship has by far exceeded that of other assets of social infrastructure. While the number of churches is growing, however, the number of schools, kindergartens and hospitals is steadily falling. Unlike other elements of social infrastructure, church building is funded not from the state budget but is financed by donors, sponsors and by the ROC itself, with some of the funds coming from payments for religious rites (baptism, weddings etc).

This article analyzes the historical significance and socio-economic impact of church building by focusing on the case of the Cathedral of Saint Martyr Catherine in Ekaterinburg. The right choice of the construction site for the cathedral - the choice that would be agreeable to the metropolitan bishop, municipal government, businesses and sponsors, local community and opinion leaders - will ensure not only that the project will be duly completed but also underline the fact that local communities are able to establish consensus and recognize each other’s interests in local decision-making. One of the possible locations considered for building St.Catherine’s Cathedral in Ekaterinburg was a former industrial site in the centre of the city. Eventually, it was chosen as the most suitable place for this large-scale project. Redevelopment of an underused or abandoned industrial site, resulting in the improvement in the quality of urban environment, can be seen as an effective instrument of project realization, contributing to the building’s social and economic significance.
The Principles of the Virtual Machine-Building Factory of the Future
Authors: Zagumennov F A , Radaykin A G , Dzvinko R V
Published: March 2021

Currently remote and digital services are significantly expanding, replacing entire departments of industrial enterprises. In the near future, it is possible that fabless-companies will conduct large-scale development, but carry out only intellectual research and development tasks, carrying out organizational and entrepreneurial activities.

This paper discusses the methods and foundations of a prospective organization, which can achieve an increase in profits using automated manufacturing of the entire production, marketing and logistic functions by cross-industry third-party interconnected companies. Resulting methods and algorithms are applicable primarily to such industries as the production of electronic devices, modules and devices, electrical engineering, instrumentation and mechanical engineering in general.

The algorithm of such digital factory is described.
Tools of Analysis in Performance Management in a Large Transport Company
Authors: Efimova O V , Baboshin E B , Avilova N D
Published: March 2021

With the help of the rating tool, transport companies will be able to improve their performance, solve strategic tasks, and conduct a comparative analysis of all divisions. The article describes the goals of conducting a comparative assessment of the structural divisions of a large transport company, calculating their place in the rating, and the main methodological provisions of the calculation. Rating evaluation of the performance of the transport holding company "Russian Railways" is carried out for the Railways and structural divisions of the company. The rating of Railways is proposed to be determined based on the performance coefficient of the target metric, taking into account the significance of each indicator, without assigning points, using the best practices approach. Three methods of selecting performance indicators for conducting a comparative assessment of the performance of structural divisions are proposed. The selected indicators are normalized and form an additive model for evaluating performance based on the significance of the criteria. The rating assessment of Railways based on an additive model showed transparency of calculation, direct influence of weight coefficients, high "sensitivity" to changes in performance parameters and the ability to model rating values by changing the performance indicators of structural divisions of the transport holding.
Structuring Organizational and Technical Measures of the Production Program
Authors: Abrosimov Yu , Babushkin V , Galyamov R
Published: March 2021

The main problem of the functioning of the organizational, technical and technological structures of the enterprise is the insufficient formalization of business processes, which, in turn, is based on the uncertainty of business process tasks influence level to the whole process, which complicates its further effective development. In this article, the structuring of such elements is based on the approach of forming the system of design and technological preparation of production (DTPP) at the enterprise, and the business processes are the subject of the study. The objective of the study is to improve the DTPP control system within the framework of research and development (R&D) with further deeper formalization for the implementation of an automated DTPP control system. To achieve this objective, tasks for assessing the business processes of DTPP control have been identified, as well as for analyzing the effectiveness of the business processes tasks for DTPP control.

To achieve the target goals and solve the tasks, the research plan includes such stages as the formation of a schedule of research, identifying the necessary resources and their sources, identifying the direct executors and bringing the plans to them, fixing the results of planning in the form of a project. The study is based on the use of expert assessment method. To obtain the correct result from two groups of expert assessments, individual assessments have been used, which are based on the use of the individual experts’ opinions who are specialists of the enterprise, and functionally independent from each other. The implementation of the individual assessments formation is based on an individual expert survey in the form of an interview with an analysis of expert assessments.
Analysis of the Influence of Factors on the Gross Regional Product of Russian Regions
Authors: Solomonov M P , Pakhomov A A , Okhlopkov G N
Published: March 2021

The main indicator of socio-economic development of the region is still the gross regional product. It is most susceptible to changes in the methodological indicator. The relevance research of influence of factors on the dynamics of GRP is caused by the need for their systematic analysis. The purpose of this work is to determine the degree of influence of factors on the growth of GRP and identify the strengths and weaknesses of the economic development regions. To achieve this goal, four main factors were previously identified: agglomeration, labor, capital and infrastructure, and for eight synthetic indicators that characterize them, their integral values were calculated, which, along with the GRP per capita indicator, were used in the classification of regions by the level of economic development based on cluster analysis. In accordance with the developed classification, coefficients of regression equations are calculated for each group of regions, in which the effective indicator is GRP per capita, and integral indicators of factors are used as explanatory indicators. In conclusion, based on the obtained regression equations, the factors that have the greatest impact on the GRP per capita are determined, and the features of economic development of the regions of the Russian Federation are revealed.
Impact of Agri-Food Potential on the Level and Quality of Life of the Population
Authors: Teryutina M M
Published: March 2021

In this article, the author examines various aspects of the impact of the agricultural and food potential of one of the largest regions of Russia, the Republic of Sakha (Yakutia), on higher living standards of the local population and the qualitative improvement of their life in this harsh Northern climate. The situation in providing for this Russian region has changed dramatically in recent years: if previously only quantitative and a few qualitative parameters were considered to assess the level of demand for food products, today the criteria have changed significantly. Suppliers are required not only to provide a certain range of food products, but also to increase the requirements for the quality component. The author clearly proves that support for agricultural producers and farms, infrastructure development of rural areas is a global trend of the last decade. These factors, in turn, contribute to stabilizing the socio-economic situation in the country as a whole. In addition, the food preferences and needs of citizens living in the Republic have recently changed: local agri-food products are more in demand. Balancing supplies from other regions and saturating the market with their own food is the main task in the field of state regulation of this area. In addition, local products are characterized by good biochemical parameters, and in terms of caloric content and mineralization, they correspond to a healthy diet for active life in the Far North. To study all these problems, the author needed to apply not only special economic methods, but also some cross-cutting methods that include a set of social, economic, and environmental methods.
“Cognitive Training of Attention and Microbiome Control as Prerequisites for Human Capital Development”
Authors: Dzyuba A V , Dzyuba V A
Published: March 2021

The paper discusses the role of gut microbiota control in human capital development. Using the analysis of existing literature authors suggest mutual entanglement of attention training practice and presence of certain microbiota population. Based on this conclusion recommendations for shaping future cognitive trainings is given. Authors also present a method for microbiome accounting in datasets where only dietary data is collected. Based on this approach possible association between microbiome and well-being domain of human capital is evaluated.
Success Factors of the Implementation of State Measures of Investments Stimulation in Russian Timber Industry
Authors: Ivantsova E D
Published: March 2021

Investment activity is critically important for the development of natural resource management industries in Russia. We believe that these significant volumes of natural resources that Russia possesses can be effectively exploited provided that an effective government policy that stimulates investment is formulated and implemented. When forming an effective industry investment policy, it is advisable to consider domestic and foreign experience, which necessitates a comprehensive analysis of existing investment attraction measures. Firstly, this paper provides an overview of the state investments stimulation mechanisms in natural resource sector, in particular, in timber industry. The most common and effective measures are identified, as well as the institutional features of their application environment. Secondly, the mechanism of priority investment projects implemented in Russia in the field of forest development is being examined in detail, a number of problems associated with its implementation are described. An econometric model is developed to grasp the factors determining the successful implementation of priority investment projects in Russia. The research results provide valuable information for decision making at the state level on the selection of investment projects to be supported.
Assessment of the Impact of Human Capital on the Gross Regional Product (for Example, the Udmurt Republic)
Authors: Pushina N N , Sokolova N G , Likhachev V
Published: March 2021

The authors focus on the measurement of the impact of human capital on economic growth because of negative trends in population, decreasing cash incomes, "brain - drain", decline in the quality of education and growing stratification in access by income level. It is pointed out that the existing tools of human capital valuation should be analyzed and tools for assessing the impact of human capital on economic growth have essential significant. Authors put forward a hypothesis that the growth of human capital drives to GDP growth or GRP growth is it is about a region. The article provides raw data and calculations of indicators of efficiency of use of capital goods and human capital for the Russian Federation for 2014-2016 and for the Udmurt Republic for 2013-2017. Conclusions drawn from calculations formulating indicate that the hypothesis concerning direct correlation between cost of human capital and efficiency of use tangible and intangible assets is failure. Particularly it is showed that the increase in the cost of human capital went hand in hand with decreasing of the efficiency of use of tangible and intangible assets in 2014 and 2016.
Condition Assessment Industrially Contaminated Soils of Kuzbass by Bioindication
Authors: Malchik A G , Rodionov P V , Tishchuk A A
Published: March 2021

This work evaluates the state of the soil that has undergone negative changes as a result of technogenic impacts, the presence of pollutants - heavy metals, considers the assessment of the state of the soil by the bioindication method. Shell amoebae, which are unicellular organisms, as well as earthworms and plants, were used as bioindicators. We also studied the ratio of the concentration of heavy metals in the soil to the distance of these soils from the source of heavy metals, and the seasonal dynamics of changes in the content of heavy metals in the soil. Using the method of stripping voltammetry, results were obtained on the presence of heavy metals in soil, earthworms and plants.
Environmental Problems of Biofuel Production in Modern Energy
Authors: Makhonko N I , Plotnikova Yu A , Tarasova E A , Varshamova N L , Yashina E V
Published: March 2021

One of the major challenges facing every developed state in recent decades has been ensuring that the national economy is energy-based and moving towards a sustainable energy future. The geopolitical interests of the leading world countries are formed and corrected by the well-known consequences of the shortage of hydrocarbons, efforts to ensure their own energy security and environmental issues. Therefore, the development and implementation of the state-of-the-art biofuel production technologies has become a matter of preoccupation for many states. The level of environmental and legal support for innovative energy options rely inextricably on the natural energy endowment, the development of a research base, the political and economic interests of states in achieving energy independence, as well as a public demand for environmental preservation over their national territory and neighboring states. This article attempts to study the legal framework for the eco-efficient biotechnology development in the energy-fuel sector of Europe, the United States and Latin America to harmonize national legislation and regulate relations within the framework of international cooperation. Under the economy-wide assessments the authors reviewed biofuel output figures in these countries, the biofuel production and use supply ratio in national energy systems, energy companies’ activities in the area of research and applying of various types of biofuel to production. The article proved possible to identify new interesting developments in this area and reach the understanding on the necessity for further active efforts in identifying a common approach to the biofuel targets in contemporary energy system within the context of wide-ranging environmental challenges.
Catode and Anode Processes in Sulfur Corrosion Destruction of Metal Constructions of Prolonged Exploitation in an Aggressive Environment
Authors: Makarenko V , Maksimov S , Makarenko Yu
Published: March 2021

The analysis of the literature and the practical data show that the existing scientific and technical and technological developments concerning the provision of reliable cross-mechanical stability and durability of the pipelines of the oil and gas industry are largely contradictory and uncertain; there was a need for a systematic study of the causes, conditions and mechanisms of corrosion damage of long-term equipment, features of cathodic and anodic processes in hydrogen sulfide destruction, in particular sulfur-hydrogen metal degradation. From the analysis of corrosion processes, we can draw the following conclusions: a) corrosion always destroys the anode, i.e. the electrode with a more negative potential; b) the cathode is not destroyed by corrosion and there is a process of depolarization, that is the removal of electrons; c) during hydrogen depolarization, electrons are neutralized by hydrogen ions and hydrogen gas is released from the cathode surface; d) during oxygen depolarization, the electrons are removed by oxygen dissolved in the electrolyte, which enters from the air or together with the environment; e) depolarization leads to a significant convergence of the values of the potentials of the electrodes and reduce the corrosion rate. Despite the large number of literature sources describing the experimental works, there is no single view of the mechanism of cathode and anode processes in the hydrogen sulfide degradation of oil and gas pipelines. This is explained by the multiplicity of factors affecting this mechanism, the complexity and insufficient study of individual elementary physicochemical processes, and therefore requires additional theoretical and experimental studies
Uncertainty Analysis Applied to Predicting Water Inflow in Confined Water
Authors: Xu Chengcheng , Lu Chuiyu , Wang Jianhua
Published: March 2021

In order to predict the amount of water inflow accurately, define the corresponding water influx response quantitatively in the parameter variation interval, this paper used the interval uncertainty analysis method, combined with the non-probability set theory and derived the predictive formula of confined water inflow under two conditions, the formula comes from the initial deterministic simple large-well method calculation formula to the consideration of parameter variation uncertainty fusion large-well method calculation formula transformation. Using the mining data, comparing the upper and lower limits of the actual calculated boundary obtained by the Monte Carlo method and of the derived formula, the relative error of the calculation result of the confined water inflow expression under the two conditions is calculated 5% and 10% or less, corresponding to the rate of change of the parameter variables, the results show that: according to the first formula calculated by the empirical formula, the relative error of the water inflow are 5% and 10%, the corresponding rate of change of the parameter variable are 0.109 and 0.14; according to the second formula calculated by the actual survey calculation, when the relative error of the water inflow are 5% and 10%, the change rates of the corresponding parameter variables are 0.274 and 0.131 respectively. Under the identical error condition, the maximum value change rates of the parameter are greater than the change rates of the parameter when the minimum value is calculated, which is beneficial to the upper limit of the calculation of mine water inflow.
Water Composition Changes in the Bureiskoe Reservoir after a Landslide and Blasting
Authors: Kondratyeva L M , Golubeva E M , Litvinenko Z N
Published: March 2021

Data on changes in the qualitative composition of volatile organic compounds and content of elements in waters of the Bureiskoe Reservoir after a great landslide, which blocked access to the hydroelectric power station, were presented. Blasting with use of trinitrotoluene and hexogen carried out to restore the hydrological regime by creating an artificial channel. Maximum content of methanol and acetone were recorded in water samples taken at the right bank near the landslide, where a lot of disintegrated wood entered the water after river tsunami. After filtering water through a landslide body, the content of Al, Fe, and Pb increased, and content of Mg, Ca, Zn, and Cd decreased. After restoration of the reservoir flow in water samples from the artificial channel, the content of Fe, Mn, Al, Cu, and Zn was at a low level and did not reach the initial values established before the blasting began. However, an increase the content of Pb by 7 times and Hg by 80 times was recorded. Presence of methanol and methylated benzene derivatives in water could stimulate the formation of more toxic bioavailable methylmercury, posing risks to aquatic organisms.
Intercropping with Oyster Mushroom (Pleurotus columbinus) Enhances Main Crop Yield and Quality
Authors: Hamed Hend A , Mohamed M F , Hosseny M H , El-Shaikh Kh A.A
Published: March 2021

This research trial was conducted in the open field to assess the integrated cultivation of oyster mushroom Pleurotus columbinus and field-grown vegetable crops. Oyster mushroom intercropped within cabbage (Brassica oleracea var capitata) and cauliflower (Brassica oleracea var botrytis) rows at the beginning of even head or curd formation. Data revealed superior intercropped cabbage and cauliflower growth parameters and higher yields compared with the respective sole cultivation. Pleurotus columbinus fruiting bodies weight, cab diameter, and total yield were significantly higher for mushroom intercropped with cauliflower than with cabbage. However, no differences or inconsistent differences were observed in fruiting bodies number, cab thickness, stem length, and stem diameter. Analysis of some mushroom fruiting bodies chemical composition showed that mushroom/cabbages intercropping surpassed mushroom/cauliflower intercropping in total phenols. However, no significant difference was observed between cabbages and cauliflowers concerning crude protein, total antioxidant activity, and total flavonoids. It is concluded that oyster mushroom/cabbage or cauliflower intercropping can provide additional marketable protein-rich food as well as enhance cabbage and cauliflower crop productivity based on sustainable practice.
Comparison of Hematological and Biochemical Parameters of Clinically Healthy Buck Kid of Saanen, Sapera, and Ettawa Crossbred in Indonesia
Authors: Sarmin  , Widiyono I , Anggraeni D
Published: March 2021

The Saanen goat has adaptation abilities and is used for genetic improvement through crossbreeding programs with Ettawa breeding to produce Sapera goats in Indonesia. The development requires support for data to determine health and metabolic status. Sixteen juvenile buck goats aged 4-6 months, comprising five Saanen, seven Sapera, and four Ettawa crossbred goats, were used in this study. Blood was collected aseptically through the jugular vein for hematology and biochemical analyses. There were no statistically significant variations in most hematological and biochemical variables, except MCH, MCHC, and P-LCR. MCH in juvenile bucks of both Saanen (40.26 ± 6.94 ρg) and Sapera goats (37.96 ± 6.24 ρg) were lower than that in juvenile bucks of the Ettawa crossbred goats (61.63 ± 19.74 ρg). MCHC in juvenile bucks of both Saanen (40.96 ± 6.82 g/dL) and Sapera goats (37.01 ± 6.72 was lower than that in juvenile bucks of Ettawa crossbred goats (61.18 ± 23.15 g/dL). P-LCR in juvenile bucks of Ettawa crossbred goats (41.30% ± 10.95%) was significantly lower than that in juvenile bucks of both Saanen (63.48 ± 8.98%) and Sapera goats (69.00 ± 12.00%). Besides, no statistically significant variations were observed in enzyme, iron, lipid, and electrolyte activity in all three breeds.
Water Resources Management: Green Watershed Index (GWI)
Authors: Caro C A , Bladé E
Published: March 2021

A large number of indices and indicators of water performance at the basin level exist throughout the world, however, the need to generate tools that allow the monitoring of basins from their administration and water and environmental management, takes greater force in a global context where sustainability takes great importance. The GWI (green watershed index) methodology is presented, as an extension of urban control methodologies, but this time for rural watersheds. The method is implemented in some rural areas of Colombia, and in some cases the difficulty of implementing the methodology is evidenced, and in other cases the opportunity to improve the management and administration of water resources at the level of rural basins.
Surveying the Effects of the Deep-Sea Tailings Disposal of Mine Wastes in Toledo City, Cebu, Philippines Three Decades After Mine Closure
Authors: Cabahug A N , Clemente E D , Lariba R S , Seblos G M
Published: March 2021

From 1971 to 1991, a major mining company performed submarine tailings disposal (STD) with the outfall at the coast of Ibo, Toledo, reaching up to 100,000 tons per day. In this study, five sampling points were selected near the outfall to determine if the STD is still a major factor in the physicochemical conditions and concentration of heavy metals in the areas near the outfall in Tañon Strait 28 years after the last disposal of mine tailings. The study found that Fe, Mn, and Cu contents on beach sediments significantly decreased around the outfall, as well metal contents on seawater which are within the DAO-2016-08 standards. Physicochemical parameters showed values within the normal range and standards. Comparing the species count from 1983 to 2019, the drastic decline can be attributed to ocean acidification, acid mine drainage, and siltation from Sapangdaku River.
The Water Pathway and Microfluidics: A Potential Solution to the Global Water Crisis
Authors: Santana Harrson S. , Markos B , Silva Jr João L. , Taranto Osvaldir P.
Published: March 2021

How can we ensure the access to water, a basic resource, for the global population? Among the several challenges related to water, we can highlight the reduction of water availability inherent from the climate changes, fountain contamination due to the low sanitation levels and the losses related to leaking in the distribution systems. In the present paper was presented a script for the cycle of use/reuse of water in human activities, “The Water Pathway”, and the use of Microfluidics as a technology capable to be used along this cycle. Our main goal was to identify fundamental stages along the different steps of the use/reuse water cycle in distinct human activities. Also, a generic flowchart was proposed to aid the identification of required knowledge and skills in the stages of the cycle. Then, some applications of Microfluidics in the Water Pathway were highlighted.
Passive Cooling Strategies for the Enhancement of Historical Buildings: A Comparison between Ventilation Chimneys and Courthouses
Authors: Laurini Eleonora , Vita Mariangela De , Berardinis Pierluigi De
Published: March 2021

The balancing of protection needs and performance improvement are essential to keep in use valuable buildings. For this reason, it is fundamental to evaluate the effects on the energetic behaviour and conservation issues caused by retrofit measures in historical structures. The research aims at the performance improvement of Architectural Heritage promoting passive cooling strategies through a comparison between ventilation chimneys and historical courthouses. The architect J. R. Gordon (1863-1937) designed seventeen courthouses in Texas, twelve of which are still existing and functioning at this time. Reinterpreting the period’s attention in mechanical systems’ innovations for ventilation, cooling and heating, Gordon’s courthouse buildings exploits natural ventilation as a strategy for achieving buildings’ passive cooling, in the hot and humid climate areas of the Texas state, in a design process that evolved over time to become more technologically sophisticated and climatically efficient. This research investigates the design and construction features and climatic response strategies of Gordon’s different types of court houses, specifically examines and assesses their natural ventilation effects. This study discusses the climate-responsive approach, moving from already established models to the creation of new climate responsive typologies of ventilation chimneys through a process of typological metamorphosis.
Basic Biological Aspects of Dormitator maculatus “Naca” (Bloch, 1792) from the Alvarado Lagoon in Veracruz, Mexico
Authors: Camacho Claudia Araceli Dávila , Galaviz-Villa Itzel
Published: March 2021

D. maculatus is an artisanal fishing resource of great economic and gastronomic importance in the area, although its annual availability is erratic due to the deterioration and contamination of its habitat, in addition to poor management of its fishery; the latter because it is easily captured during its breeding season. Basic biological aspects of D. maculatus were estimated, such as size composition, sex ratio, and type of growth. A total of 700 organisms, 364 males and 336 females, were collected and analyzed during 12 continuous months. As a result, sizes between 4.4 to 17.0 cm were obtained, averaging 10.2 cm. The most common length range in females was 8.1 - 9.0 cm and 9.1-10.0 cm in males. The annual sex ratio was 1M: 0.87F; with significant differences from July to October (2M:1F) and January (1M:2F). It was observed that the species tends to form aggregations, however, it maintains a 1M:1F ratio in the remaining period. The length-weight relationship parameters show that D. maculatus presents positive allometric growth (r2 = 0.93452) for both sexes. Males were slightly larger and heavier than females. The minimum size of sexual maturity obtained was Lm50 = 8.21 and 8.41 cm for females and males, respectively.
Research on the Economic Growth for Under-Developed Counties -- Based on Two-way Fixed-effects Model
Authors: Li Zhengze , Huang Zibo , Zhang Yongcheng , Huang Zili
Published: March 2021

The county economy, especially the problem of poor counties, is currently a hot issue in China. At present, the research on the key factors for county economy is scarce, partly because it is difficult to obtain accurate and sufficient data. Because power consumption and industrial level are often highly correlated, and the power consumption is real-time data and hard to falsify, this paper used spatial, electricity consumption and economic data of 66 Chinese counties, which contains 29 poor counties, from 2009 to 2016 to find out the key factors for under-developed counties’ economic growth by applying fixed effect regression model and machine learning models. The result shows that for poor counties, though the 1st industry is still the fundamental industry for county-level economy, the development of 3rd industry has significant positive impact on local economy. However, the development of 2nd industry, including recruiting large companies, and the input of electricity resources cannot well drive the local economies, which may suffer great loss due to the elimination policy of overcapacity in recent years. And the machine learning results support the above conclusions and suggest an obvious geographical cluster of poor counties, and the location, development of 1st and 3rd industry and net income of rural residents can explain most difference between the poor and non-poverty counties. These conclusions can be helpful for the government to lead the poor counties to get rid of poverty, and the cluster of poor counties should be focused.
Optimized Stress-Strain Ranges for Hyperelastic Constitutive Models Supporting the Simulation of Vertical Stiffness on Airless Tire
Authors: Phromjan J , Suvanjumrat C
Published: March 2021

The airless tires are developed to overcome a disadvantage of pneumatic tire which lost maneuverability caused of flattening and blasting. The finite element analysis (FEA) is an effective method for development of airless tires which have a complex construction. The material properties which describe mechanical behavior of each tire component are very important to yield accurate result. The high order constitutive model usually obtains the accuracy of FEA results. Unfortunately, it consumes the simulating time. The suitable stress-strain range of Mooney-Rivlin and Ogden model was selected in this research. The vertical stiffness of airless tire model was compared to the experiment. This study found that the accurate result and consuming less time of TWEEL airless tire model depended on an appropriate pair of material properties. There were 100% of tread and 30% of spoke stress-strain characteristic based on the Mooney-Rivlin model. Consequently, the study and design of airless tire by finite element method will be carried out efficiently in the further works.
Model of weld beads geometry produced on surface temperatures by Wire and Arc Additive Manufacturing (WAAM)
Authors: Manokruang S. , Vignat F. , Museau M. , Linousin M.
Published: March 2021

Wire and Arc Additive Manufacturing (WAAM) is an Additive Manufacturing (AM) technology that knows a strong interest in recent years. With this technology, the combination of an electrical arc welding and a metallic wire feedstock is used to manufacture parts layer by layer. As part geometry depends strongly on deposition conditions, this study is focused on the characterization of single bead walls and their geometrical evolutions according to welding parameters and surface temperatures. Our experiment has consisted of the production of walls manufactured with a 5083Al wire and built from 1 layer up to 10 layers with several surface temperatures (Tsur fixed at 100, 200, 300 and 400°C). Before the deposition of each new layer, we ensure that the substrate is at the correct temperature using a thermometer in order to guarantee constant welding conditions. Those welding parameters have been kept constant with a Wire Feed Speed (WFS) at 5 m/min and a Travel Speed (TS) at 0.6 m/min. Wall bead geometry and dimensions, width (w) and height (h), have been then measured using a 3D scanner. Results are used to feed a predictive model developed with a circular model curve fitting each top layer cross-section of walls. Data form this study, coupled with thermal simulation, will allow us to predict faithfully parts shapes and to control their dimensions.
Ensemble Flower-Pollination Algorithm for Automatic Breast Cancer Classification using Haar Features
Authors: Sannasi Chakravarthy S R , Rajaguru Harikumar
Published: March 2021

Breast cancer is a deadly disease which reports a higher mortality rate, every year. This type of cancer is more common in women of developed countries while compared with the incident rate in developing countries. The objective of this work is to propose a methodology to increase earlier breast cancer detection. The methodology makes use of ensemble-based classifiers namely histogram-based Gradient Boosting Machine (hbGBM), Gradient Boosting with Light GBM (lGBM), and Gradient Boosting with CatBoost (GBCB) algorithms. The paper adopts the Mammogram Image Analysis Society (MIAS) database for testing the effectiveness of the algorithms. Haar wavelet transform is used for feature extraction and Flower-Pollination Algorithm (FPA) is employed for selecting the best features. Thus, a flower-pollination based haar wavelet feature with three different ensemble-based classifiers is proposed for the automatic mammogram classification. The performance results are then compared briefly by using some benchmark metrics such as specificity, sensitivity, precision, accuracy, and precision, F1 score, and Matthews Correlation Coefficient (MCC) analysis. The result reveals that the highest classification accuracy is obtained for ensemble GBCB based FPA algorithm i.e., 91% when comparing with other existing models.
Analysis of EEG Signal for the Estimation of Concentration Level of Humans
Authors: Velnath R. , Prabhu V. , Krishnakumar S.
Published: March 2021

Especially when studying or thinking, focus is an important part of our lives. To understand humans’ concentration mechanism, the brain activity is monitored using EEG signals. Electroencephalogram (EEG) is test used to track and record the brain wave patterns based on the electrical activity of the brain. It is a very versatile tool for the detection of brain activity. Based on concentration and thinking the brain waves will get change due to their change in brain activity. The variations in brain waves are analysed and the features are extracted using various methods. EEG data are collected for different persons under two different age groups of 20 to 23 age and 29 to 31 aged people because the concentration varies with respect to age. The characteristics are extracted from the collected EEG signal using FFT, Mean, Standard Deviation (SD), Median and Mean Root Square. The concentration level is determined by comparing the extracted features for different aged individuals.
Design of Density Clustering In Diabetic Retinopathy Based Eye Fundus Segmentation
Authors: Udaya Kumar Naluguru , Nikitha Thelapolu , Bachu Srinivas
Published: March 2021

In order to prevent further complications, we learned in this paper that earlier diagnosis is critical in Diabetic Retinopathy (DR). The disease can be classified into one of two stages (the early stage of non-proliferative and later stage of proliferative diabetic retinopathy) of Eye Fundus Images (EFI), diagnosed on the basis of the presence and quantities of a complex series of lesions such as microaneurysms, haemorrhages or exudates. Therefore it is important to properly segment regions of potential lesions to demonstrate and classify the lesions and the degree of DR. Density clustering approaches are promising candidates for the isolation of individual lesions, and can be used along with effective methods for vascular tree elimination, extraction and classification. In this article, our approach, findings, tradeoffs and assumptions for segmenting and detecting individual lesions are reported.
Comparison of Paul Viola – Michael Jones algorithm and HOG algorithm for Face Detection
Authors: PNithish Sriman K , Raj Kumar P , Naveen A , Saravana Kumar R
Published: March 2021

The computer technology which helps to find the face of a person in video and image is face detection. It is like a biometric application that finds a person by analyzing and comparing the person’s face patterns. The face detection technique helps for security purposes, and also it has an rising interest in many fields. This technology has received good attention. It has some good applications based on law enforcement. For detecting face in an digital image, we have lot of algorithms. In this, Viola Jones algorithm and histogram of oriented gradients is used to detect the face of a person. The paper is proposed for a comparison between viola jones and Hog. By analyzing this we can find the gender, age and also emotions of the person. Here different type of images were used for detection. The Matlab tool and Jupyter is used for implementing this face detection process.
Wavelet Based CNN for Diagnosis of COVID 19 using Chest X Ray
Authors: Gunasekaran Suresh , Rajan Santhiya , Moses Leeban , Vikram S , Subalakshmi M , Shudhersini B
Published: March 2021

Human race has overcome numerous pandemic and epidemics like Spanish flu, SARS, cholera, plague, etc since ages and COVID 19 pandemic is one among them. COVID 19 being the recent one, is much different than the others due to the contribution of AI in diagnosis and prediction of COVID 19 patients. Among the various use cases, one widely used area is medical diagnosis. AI and deep learning based algorithms are exploited enormously by data scientist to support radiologist in early prediction and detection of corona patients. Subsequently, in this work, we utilize wavelet based Convolutional Neural Networks for detecting and recognizing of COVID 19 cases from chest X ray images. Currently, previous works utilize existing CNN architectures for classification of healthy and affected chest X rays, however these networks process the image in a single resolution and loss the potential features present in other resolutions of the input image. Wavelets are known to decompose the image into different spatial resolutions based on the high pass and low pass frequency components and extract valuable features from the affected portion of lung X ray efficiently. Henceforth, in this article, we utilize a hybrid CNN model of wavelet and CNN to diagnose the lung X rays. The proposed CNN model is trained and validated on open source COVID 19 chest X ray images and performs better than existing state of the art CNN models with an accuracy of 99.25%, ROC-AUC value of 1.00 and very less false negative values. Further, the performance of our model is validated by Gradient Class Activation Map visualization technique. The visualization of feature maps clearly indicates that our proposed network has perfectly extracted features from the corona virus affected portion of the lung.
Deep Learning Based Multilevel Classification of Alzheimer’s Disease using MRI Scans
Authors: Raju Manu , Thirupalani M , Vidhyabharathi S , Thilagavathi S
Published: March 2021

Alzheimer’s disease is one of the most frequently studied diseases of the nervous system although it has no cure or slowing its progression. There are various options for treating the symptoms of Alzheimer’s disease in different stages and as the disease progresses over time, patients in their various stages need different treatment. Diagnosis of Alzheimer’s in the elderly is quietly difficult and requires representation of a discriminatory factor in isolation due to similar brain patterns and pixel strength. Deep learning strategies are able to learn such representations from the data. In this proposed work we perform multilevel classification of Alzheimer’s disease ie; Mild Demented, Moderate Demented, Non Demented and Very Mild Demented using transfer learning with VGG16 using Fastai. This approach results in 99% predictive accuracy which means a significant increase in accuracy compared to previous studies and clearly demonstrates the effectiveness of the proposed methods.
Brain Tumor Detection Using Spatial Filtering Algorithm
Authors: Sritha P , Valarmathi R S , Brundha K , Dhanusri V
Published: March 2021

In recent decades, many people suffered from brain tumor disease because of the living habits and the stress factors, The tumors in brain is detected by the magnetic resonance imaging (MRI) image by means of filtering and segmentation process.In particular of the image processing techniques Medical Image processing technique is applied to identify the tumors in any parts of the body easily and it saves time. A model was proposed in this paper to detect the brain tumor by means of Spatial filtering algorithm. In this algorithm, a new techniques which combines the segmentation and filtering mechanism to detect the growth of cells or tissues in the tumor. The simulation and experimental result has attained about 90.6 % accuracy, 88.6% specificity and 92.56% sensitivity in detection process of tumors.
RETRACTED: Detection and Classification of Breast Cancer Using improved Grey Wolf Algorithm
Authors: Senthil T , Deepika J , Nithya R.
Published: March 2021

Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there’s motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.
RETRACTED: Adaptive Beam forming algorithms for wireless Communication using LABVIEW
Authors: Ramya M. , Thamizharasan V. , Parthipan V.
Published: March 2021

Adaptive antenna arrays are being developed to cope with the high capacity requirement of the 5G wireless communications systems. As adaptive antenna arrays focus narrow high gain beams towards the desired users and nulls towards the unwanted interferers, both coverage and capacity of the network can be improved. The capacity of a Wireless network depends on the size of the antenna array, the beam pattern used and the speed with which the beam-former and Direction of Arrival estimator. To achieve the capacity demand required by a growing number of subscribers, smart antenna systems are used in the present cellular systems. In these systems cell-splitting and sectoring techniques are adopted to improve the capacity. The main disadvantage of these techniques is that decrease in trunking efficiency. It has been established that the smart antenna systems will provide a better solution for the capacity problem. Development of smart antenna includes design of antenna array and adjusting the incoming signal by changing the weights of the amplitude as well as phase using efficient Digital Signal processing algorithms using LabVIEW.
VLSI Implementation Of High Speed Low Power Design Using Hybrid Power Gating Technique
Authors: Pousia S , Murugan K
Published: March 2021

Nowadays, low powerhigh speed CMOS design is one among the challenging issues. As the technology is scaling down, the static power consumption has turned into a remarkableconcern. The proposed methodology incorporates the following technique such as sleep technique, stack technique, sleepy stack technique, sleepy keeper technique, leakage control transistor technique (LECTOR) and sleepy keeper leakage control transistor technique (SK-LCT) for leakage power reduction. The proposed power gating techniquelead to low power,high speed CMOS design. The xor gate, xnor gate, half adder & 6T sram cell is outlined using newly proposed power gating technique for a low power high speed design.When compared to the conventional methodology xor gate saves 19.95 % of power & 33.75% of delay, xnor gate saves 12 % of power & 23.29 % of delay, half adder saves 35.29% of power &25.69% of delay and sram cell saves 14.29% of power & 34.37 % of delay. Simulation is done using Tanner EDA tool and the outcomes demonstrate a noteworthy change in leakage power utilization and speed.