bluuebunny/crossref_metadata_2025 huggingface dataset:
Remote Combined Effects of Coal Dust and High-Dose -Irradiation on Immune System Changes
Authors: Chulenbayeva Laura E. , Ilderbayev Oralbek Z. , Suleymeneva Dametken M.
Published: June 2021

The objective of this research is to assess the effect of combined exposure of a high dose gamma radiation (6Gy) and coal dust on the immune system values in the long-term period. The study was carried out on 40 male Wistar rats divided into 4 groups: group I, intact animals; group II, exposure to coal dust; group III, exposure to 6Gy -irradiation; group IV, combined exposure to sublethal irradiation and coal dust. In groups II and IV, anthracosis was caused by exposure to coal dust at a concentration of 50 mg/m3, using an exposure chamber for 90 days after irradiation. The animals of groups III and IV were irradiated once in dose 6Gy prior to the study, with the TERAGAM CO60 gamma-therapeutic device (ISOTREND spol. s.r.o., Czech Republic). The study revealed a significant immunotoxicological shift induced by coal dust and high dose of radiation separately and in combination. The combined effect of factors exhibited an obvious immunodeficiency, as compared to the separate exposure. The combined exposure to the studied factors resulted in deterioration of T-cell immunity and disruption of cytokine production accompanied by reduced resistance to neoplasms, increased tendency to allergic diseases, and weakened immunological response of the organism.
Agrotechnological Fundamentals of Direct Sowing of Grain Crops in Russia’s ARID Conditions
Authors: Goryanin Oleg I. , Zudilin Sergey N. , Medvedev Ivan F. , Dzhangabaev Baurzhan Zh. , Shcherbinina Elena V. , Pronovich Lilia V.
Published: June 2021

The authors presented the multiyear results of the research on testing the technological complexes of growing the grain crops with direct sowing in the black earth steppe of Russia’s European part. In the zonal crop rotations, in comparison with a traditional technology, it did not lead to worsening of the agrophysical, agrochemical, water and biological soil features, increased the humus content by 0.55% (NSR05- 0.42 %). In spring, during the crops sprouting, the Р2О5 and K2O quantity corresponded to 192 and 189 mg/kg of soil, which is 29 mg (17.8%) and 35 mg (22,7%) more than control. The established least production costs – 2975.1 rub/hectare on an option with direct sowing of the spring grain crops, which are 499.9 rub/hectare -16.8 % lower than the traditional technology figures, favored the acquisition of the highest contingent net income of 1220.1 rub./hectare and the profitability level of 41.0%. During the direct sowing of the spring hard wheat, the highest contingent net income is gained on options with the use of integrated plant protection and the fertilizer application – 9507.9-9753.9 rub/hectare, which is 3667.6-3913.6 rub/hectare (62.8-67.0 %) more than the control, and 825.8-3626.9 rub/hectare (9.5-59.2 %) higher than figures on other options. On the basis of the research conducted, the authors offer a new generation of technologies of growing the winter and spring wheat and the spring barley, which are built on the system basis.
Reintroduction of Kok-saghyz (Taraxacum Kok-saghyz L. Rodin)
Authors: Uteulin Kairat R.
Published: June 2021

For the first time in the Republic of Kazakhstan, the reintroduction of the kok-saghyz dandelion (Taraxacum kok-saghyz L. Rodin) has been carried out, a rare species included in the Red Book of Kazakhstan. Kok-saghyz is a valuable resource plant of world importance. It is used as an industrial crop, a source of high-quality rubber. During the works held in 2017-2018 the method of returning kok-saghyz to the limits of its natural growth zone, located on the intermountain valleys of the North-Eastern Tien Shan of Kazakhstan, has been tested. The survival rate of kok-saghyz seedlings decreased from 94% to 84% and then to 77% with an increase in the height of the seedlings above sea level (1795, 1842, 1900 meters, respectively). The tested method will be used in the practice of restoration, expansion and preservation of natural populations of Taraxacum kok-saghyz Rodin.
Grouping of the Turkistan Area Regions based on a Complex Evaluation of Demographic Processes, Indices of Health, Medication Provision, and Social-economic Development of the Territory
Authors: Buleshov Myrzatay A. , Almasov Zhusip B. , Akimov Kayrat O. , Buleshova Ayzhan M.
Published: June 2021

The research objective was to elaborate methodological approaches to group the Turkistan regions through a complex evaluation of their demographic situation, public health, healthcare system, and social-economic development. The regions were grouped by normalizing a set of indices with various dimensions and vectors. The indices used were budget expenses per capita, unemployment rate, birth rate, death rate, income per capita, availability of pharmacies, provision with medical and pharmaceutical personnel, etc. During the studied period, the Turkistan area regions showed varied normalized values. The differences amounted to 1.2 times by normalized values and up to 2.4 times by complex values, which is due to the various developmentlevels, multi-faceted character and complex spatial hierarchy of the Turkistan area regions. The research showed the normalizing method to be very effective for the regional and municipal statistical service as they have consolidated medical-statistical tables for the whole area and individual regions.
Randomized Application of Low-Frequency Electrostatic Field and General Magnetic Therapy after Surgical Treatment of Breast Cancer
Authors: Gerasimenko Marina Yu. , Evstigneeva Inna S. , Zaytseva Tatiana N. , Aksenenko Irina P.
Published: June 2021

Background: Various methods of physical therapy are widely used in the rehabilitation of patients with cancer (magnetotherapy, pneumocompression, electrotherapy, laser therapy). The goal of such rehabilitation is to minimize side effects and complications after radical treatment. However, a staged approach to the appointment of physiotherapeutic factors in the early period after surgical treatment of breast cancer has not been developed enough. Aim: To develop a staged approach to the appointment of physiotherapeutic factors at different times after surgical treatment of breast cancer. Design: a randomized-placebo-controlled study. Location: the clinic named after professor Yu. N. Kasatkin of the Russian Medical Academy of Continuing Professional Education of the Ministry of Health of the Russian Federation, Moscow. Population: Examination and treatment of 78 patients aged 30-70 after surgery for breast cancer were performed. The main group of 39 patients underwent a 2-stage course of medical rehabilitation: the first course on days 2-4 after surgery and the second course after 1-1.5 months against the background of adjuvated radiation therapy. The control group of 39 patients underwent physiotherapy placebo procedures. Methods: All the patients underwent medical rehabilitation: individual exercise therapy, balance-therapy, sessions with a medical psychologist, course exposure to an alternating low-frequency electrostatic field and general magnetic therapy. Results: two-stage physical rehabilitation improves the quality of life, decreases swelling, increases the range of motion, decreases pain, decreases the number of postoperative complications, and shortens the duration of lymphorrhea. Conclusions: It is advisable to include general magnetic therapy procedures and exposure to an alternating low-frequency electrostatic field in combination with physiotherapy exercises, balance-therapy and individual lessons from a medical psychologist in rehabilitation courses. Clinical Rehabilitation Impact: Prescribing two courses of medical rehabilitation after breast cancer surgeries in the early stages (on days 2-4) and 1-1.5 months after surgery contributed to a decrease in pain and postoperative edema, and an increase in the range of motion in the shoulder joint, preventing severe lymphostasis and improving the quality of life.
Building Better Risk Management Information System (RMIS) for Sustainable Bank Management in Vietnam
Authors: Thach Nguyen Ngoc , Huy Dinh Tran Ngoc , Trung Nguyen Dinh
Published: June 2021

Recently the roles of building a risk management information system in commercial banks in Vietnam has been becoming necessary during Covid 19 effects. This study mainly use combination of quantitative methods and qualitative methods including synthesis, inductive and explanatory methods. We analyze rism management and risk evaluation in case of one big listed bank in Vietnam, Navibank (NVB) who became National Citizen Bank later (NCB). We figure out that CPI, lending rate and VNIndex have negative correlation with both beta CAPM and stock price of NVB. And these risk results and models can be delivered to suitable users in a management information system (MIS).
http://www.revistageintec.net/index.php/revista/article/view/1668
Authors: Kasiselvanathan M. , Narayanan S. Lakshmi , Gurumoorthy K.B. , Subbulakshmi N.
Published: June 2021

The Arduino UNO microcontroller based smart portable soil testing system is developed to determine the values like pH content and moisture level. This can be done using the sensor respectively to check the values. The GSM Module which uses the mobile communication to communicate the value to the given mobile. The communication method used here to retrieve the values whenever it is necessary and after getting the values it would be displayed in LCD. Then when the button is pressed, the GSM starts to work, search for the signal and after responding to the signal the values are sent to the registered mobile. This method would be easier to check the value of soil so that it will be viewed whenever the values are needed. It describes that the values are available at our doorstep because it is smart portable monitoring system. This project helps us to create a new idea to do further additional functions that can be done.
Some Theoretical Issues about Assets and Income Auditing by State Auditors
Authors: Hanh Hoang Thanh
Published: June 2021

Asset-Income declaration and auditing has been becoming hot issues in the revolution of anti-corruption in our country in recent years. This study mainly use qualitative analysis methods, synthesis, inductive and explanatory methods, combined with law references. Our research results show that asset-income declaration audit follows a process with several steps: planning, conducting audits, audit reports and examining audit conclusions. We recognize that a transparent declaration audit will benefit the public in anti-corruption revolution.
ECC Data Hide – Using Steganoraphy and Deep Neural Network
Authors: Vennila Dr.V. , Poomani L.I. , Thaaranya S.
Published: June 2021

In the field of computer networks, cryptography and steganography are the well-known features for best security purpose. The main idea is to transmit the data securely. So, providing acceptable level of security is essential for data transmission. Also it should reduce the time complexity of the security algorithm. Here we have employed the “Elliptic Curve Cryptography” scheme to encrypt the data and image. A “Least Significant Bit” steganography algorithm is used to insert the encrypted data to be hidden inside the image in order to send the data securely. The encrypted data from the image is then decrypted by the decryption algorithm. Finally the hidden data is taken from the decrypted data. Then the image is compressed before sending through the internet. MATLAB is utilized to mimic outcomes which show that it has great inserting limit and security.
An Efficient Subjective Sentiment Classification of Hate Speech Using Tri-Model Approach
Authors: Sangavi K.
Published: June 2021

Arrangement highlights were gotten from the substance of each tweet, including syntactic conditions between words to perceive "othering" phrases, actuation to react with adversarial activity, and cases of very much established or legitimized oppression social gatherings. The consequences of the classifier were ideal utilizing a blend of probabilistic, rule-based, and spatial-based classifiers with a casted a ballot group meta-classifier. We show how the consequences of the classifier can be powerfully used in a factual model used to figure the probably spread of digital scorn in an example of Twitter information. The applications to strategy and dynamic are examined. We propose a cooperative multi-space assessment arrangement way to deal with train supposition classifiers for numerous areas at the same time. In our methodology, the supposition data in various spaces is shared to prepare more precise and vigorous notion classifiers for every area when named information is scant. In particular, we decay the slant classifier of every space into two segments, a worldwide one and an area explicit one. The area explicit model can catch the particular feeling articulations in every space. Moreover, we extricate Tri_Model (Naive Bayes IBK, SVM) sentiment information from both marked and unlabelled examples in every area and use it to upgrade the learning of Tri_Model (Naive Bayes IBK, SVM) sentiment classifiers.
Management Marketing Strategy for Formation of Local Brand of Milk and Dairy Products in the Digital Economy
Authors: Ikramov Murat , Eshmatov Sanjar , Samadov Asqarjon , Imomova Gavhar , Boboerova Maftuna
Published: June 2021

In the paper has been investigated issues of management marketing strategy for formation of local brand of milk and dairy products in the digital economy. By author was discussed the essence and main tasks of advertising, the features and importance of compliance with the rules of ethiсs, its role in ensuring conditions for fair competition and integration into the process of world economic management.
Better Risk Management of Banks and Sustainability - A Case Study in Vietnam
Authors: Hang Nguyen Thi , Huy Dinh Tran Ngoc , Ha Le Thu , Nhung Do Hong
Published: June 2021

Modern advanced bank risk management is a current and hot issue for all Vietnam banks, during the context of industry 4.0. Because of rapid economic growth under impacts of China-US commerce war and effects from Covid 19, as welll as industry 4.0, enhancing roles of banks in Vietnam economic development is becoming necessary. This paper also refers to new perspectives on corporate governance issues that can be applied into bank management. This study mainly use combination of quantitative methods and qualitative methods including synthesis, inductive and explanatory methods for a special case of big listed bank in Vietnam, Eximbank. The results show us that better management of bank need to forecast effects from GDP growth, Industrial manufacturing (IM) and Risk free rate (Rf) on both beta and stock price of Eximbank (EIB), in this case we found out there is positive relationship. Then, we can suggest suitable plans for risk management to enhance the bank roles and sustainable management strategies.
Preliminary Study on Educational Game-based Learning Approach in Financial Accounting Course: Bicycle Accounting Classification Game
Authors: Rahim Maisarah Abd
Published: June 2021

The study has designed an educational game-based learning through the introduction of an interactive game called “bicycle accounting classification game”. The game was created to stimulate interest in learning basic financial accounting courses that are normally portrayed as a serious subject. The bicycle accounting classification game tool kit has been developed as a learning and teaching aid to enable students to collaborate and engage in the financial accounting course. The main purpose of the study is to identify the effectiveness of the tool as a mechanism to enhance students’ learning motivation investigated through individual psychological needs of autonomy, competence and relatedness in a financial accounting course. The sampling was implemented to 4 accounting lecturers and one computer science lecturer in a small group tryout and 30 non accounting students in field tryout. Questionnaires were used for data collection and analyzed using quantitative methods. From the experimental results, it is discovered that the bicycle accounting classification game has contributed to the positive learning motivation, in terms of promoting their learning participation and improving their learning excitement and understanding in the financial accounting course given that knowledge organizing, and sharing is embedded in the collaborative gaming environment.
Suggested Risk Policies from Comparison of 2 Groups of Vietnam Banks - Previous SOE Banks and Private Banks During Post-Low Inflation Period 2015-2020
Authors: Nam Vu Quynh , Huy Dinh Tran Ngoc , Dung Nguyen Tien
Published: June 2021

As fast growth of Vietnam banks going with risk policies, We categorize listed banks on Vietnam stock exchange into 2 groups: Previous SOEs banks (including Vietcombank and Vietinbank) and Previous Private banks (including SHB, EIB and ACB). Authors then use combination of quantitative methods (statistics, calculation formulas) and qualitative methods including synthesis, inductive and explanatory methods. The research findings tell us that In groups of banks (SOEs previously) VCB and CTG we find out: G and Risk free rate (Rf) have higher impacts on beta CAPM, for internal factors. While In groups of joint stock banks (private banks) SHB, ACB and EIB we figure out: exchange rate and SP500 have higher impacts on beta CAPM, for external factors. Besides, this study also give out recommendations for enhancing socio-economic roles of Vietnam banks in future and give out directions or implications for socio-economic policies.
An IoT based Machine Learning Technique for Efficient Online Load Forecasting
Authors: Madhuravani B. , Atluri Srujan , Valpadasu Hema
Published: June 2021

Internet of Things (IoT) networks are computer networks that have an extreme issue with IT security and an issue with the monitoring of computer threats in specific. The paper proposes a combination of machine learning methods and parallel data analysis to address this challenge. The architecture and a new approach to the combination of the key classifiers intended for IoT network attacks are being developed. The issue classification statement is created in which the consistency ratio to training time is the integral measure of effectiveness. To improve the preparation and assessment pace, it is suggested to use the data processing and multi-threaded mode offered by Spark. In comparison, a preprocessing data set approach is proposed, resulting in a significant reduction in the length of the sample. An experimental review of the proposed approach reveals that the precision of IoT network attack detection is 100%, and the processing speed of the data collection increases with the number of parallel threads.
Comparison of Lab based Device and Cuff-less based Device for Efficient Heart Rate Monitoring in Normal Individuals and Heart Diseased Individuals for Extended Duration
Authors: Sibhiraja S. , Dey Dr. Nibedita
Published: June 2021

Aim: This study was performed to validate and compare our designed cuff less device with standard heart rate monitors used in Hospitals. Materials and Methods: The Heart patient data were collected in Government PHC (Primary Healthcare Center), Navalpakkam hospital and the normal individual data were collected in Saveetha School of Engineering (SSE), Saveetha University (CLAB 404/425). Results: The means of the BPM also was found to be very similar with a minor deviation in heart rate of heart patients monitored by our cuff less device. The high insignificance assures that our device has given reading at par with commercial monitors used in the market Conclusion: Within the limits of our study our cuff-less device is as efficient as a vital sign monitor (lab based device) used in hospitals or Laboratories (one way ANOVA, P >0.05, insignificant).
Design of Angle based 27-level Trinary Ladder Inverter Using Cross Compiler
Authors: Prathap Dr. Joseph Anthony , Bandaru Priyanka , Darshanam Vaishnavi , Narendar B.
Published: June 2021

This paper presents the design of the Multi-Level Inverter circuit based on the switched ladder topology using the angle events for the level changes. The change of events for the inverter is formulated using the Half Height Algorithm. The VHDL code is utilized for the generation of the angles as digital equivalence with the resolution of 27 bits. In ladder topology, there are several types of inverter namely Binary Ladder Inverter, Ye Progression, Luo Progression. Among all these topologies, the Trinary Ladder topology is advantageous for the number of levels attainment with the less number of switches. Also, the carrier-based modulation is erroneous with the High THD% and low Voltage Parameter values. The use of the non-carrier half-height method manipulates the accurate angle to measure acceptable THD %. The proposed Trinary Switched Ladder Inverter is cross-compiled with Xilinx Vivado and Matlab Simulink Took to evaluate the parameters such as THD%, VRMS, VPEAK, for the 27-level. The parametric analysis exhibits improvement in the proposed Ladder topology with cost, size, and performance when synthesized using the Xilinx Vivado tool.
Non Homogeneous Rough Finite State Automaton
Authors: Praba B. , Saranya R.
Published: June 2021

Objective: The study of finite state automaton is an essential tool in machine learning and artificial intelligence. The class of rough finite state automaton captures the uncertainty using the rough transition map. The need to generalize this concept arises to adhere the dynamical behaviour of the system. Hence this paper focuses on defining non-homogeneous rough finite state automaton. Methodology: With the aid of Rough finite state automata we define the concept of non-homogeneous rough finite state automata. Findings: Non homogeneous Rough Finite State Automata (NRFSA) Mt is defined by a tuple (Q,Σ,δt,q0 (t),F(t)) The dynamical behaviour of any system can be expressed in terms of an information system at time t. This leads us to define non-homogeneous rough finite state automaton. For each time ‘t’ we generate lower approximation rough finite state automaton Mt_ and the upper approximation rough finite state automaton Mt- and the defined concepts are elaborated with suitable examples. The ordered pair , Mt=(M(t)-,M(t)-) is called as the non-homogeneous rough finite state automaton. Conclusion: Over all our study reveals the characterization of the system which changes its behaviour dynamically over a time ‘t’. Novelty: The novelty of the proposed article is that it clearly immense the system behaviour over a time ‘t’. Using this concept the possible and the definite transitions in the system can be calculated in any given time ‘t’.
Augmented Reality based Car Parking Application for Android
Authors: Dhivya K.
Published: June 2021

Today, Augmented Reality plays a vital role in the tech industry. This paper is based on Augmented Reality car application and is an important topic in R&D. This application, enables to place and drive virtual cars in the real world. This paper briefly, discuss about introducing Augmented Reality application for “Android”, because not everybody can afford for an iPhone which has tons of AR applications. This is the reason why this optimised AR car application is made only for Android. It enables to place cars in real world with exact dimensions. The tools used to build this application are “UNITY” and “VUFORIA”. So, it gets easier to see whether a car can fit into a particular place or not, we can see how many cars can fit in a particular place and also, we can drive a car virtually to see whether it is possible to park a car in a congested place. It clearly shows that it saves time to park a car when compared to manual work. The result examined that real world interaction of car using Augmented Reality was successfully executed by placing multiple cars and in the mere future, there will be an update to move the car in all possible directions. It will play a major role in AR based research and also will be very useful for car buyers and also for the car companies.
Reasonable Time in Criminal Proceedings of Ukraine in the Context of the European Court of Human Rights Case Law
Authors: Derdiuk Bohdan , Kovalchuk Serhii , Koropetska Snizhana , Savchenko Vasyl , Smushak Oleksandra
Published: June 2021

The purpose of the paper is an analysis of the notion of reasonable time, period which is taken into account in their calculation and criteria for determining a reasonable time for criminal proceedings in Ukrainian criminal procedural legislation in the context of the European Court of Human Rights case law. The subject of the study is an analysis of Ukrainian criminal procedural legislation from the point of view of its conformity to the ECHR’s case law in the designation of a reasonable time, period which is taken into account in calculation of a reasonable time and criteria for its determining for criminal proceedings. The research methodology includes comparative legal, systematic, functional, formal legal and others methods. The results of the study. The period which is taken into account in calculation of a reasonable time and the criteria for its determining is studied comprehensively as a basis for definition of the notion of reasonable time. Practical implication. The range of suggestions for improvements of Ukrainian criminal procedural legislation relating content of reasonable time and mechanism used to their calculate is defined. Value / originality. Based on the results of an analysis the authors’ concept of reasonable time is proposed.
Pedagogical and Psychological Features of the Development of Ecological Competences of Future Teachers
Authors: Mukhsieva Aziza
Published: June 2021

This article analyzes the current state of environmental education and education in Uzbekistan, classifies the main types of environmental competence of future teachers.
Methodology of Training Students in Design and Modeling of Clothes Using Information Communication Technologies
Authors: Abdurahimovna Umarova Fotima
Published: June 2021

The purpose of this article is to develop a methodology for the development of competence in the design and modeling of clothing for university students through the use of information and communication technologies, its introduction into the educational process and increase the effectiveness of education. This article discusses the issues of improving students' knowledge and skills, interest in the learning process and the ability to apply their knowledge in practice in the future, using modern information and communication technology tools in the training of design professionals. Emphasis will be placed on developing and implementing a new teaching method aimed at enhancing the competence of design students in designing and modeling clothing. The role and perspectives of teachers are very important and they are highlighted as key participants in the process. The data show that, the using authoring technology of SCADEduWeb and information communication technologies in the educational process on the basis of interactive teaching methods, that allow students of professional education to effectively teach the design and modeling of clothing through the design of innovative digital tools, modeling creative and reflexive approaches helps to increase the effectiveness of education and facilitates the organization of the learning process. In particular, it shows that the contribution of information communication technologies to the improvement of the educational process in educational institutions, where information communication technologies are an innovative factor. Authoring technology of SCADEduWeb allows each student to achieve good results through independent, creative thinking at each stage of mastering the subject "Design and modeling of sewing objects". Achieving this high level will lead the educational institution not only to modernize the technological tools, but also to change the teaching models. In order to achieve development, we need to master digital knowledge and modern information technologies, use new teaching methods. This allows us to take the shortest path. Indeed, the deep penetration of information technology into all parts of the world today is creating new opportunities.
Machine Vision and Machine Learning based Fruit Quality Monitoring
Authors: Anita C.S. , Nagarajan P. , Lakshminarayanan E. , Sankar M. Naveen , Rishikanth V.R.
Published: June 2021

The efficiency of the logistics of agricultural food needs to assure that its products are safe and of quality. This would earn the trust of consumers. To provide smart farming and packing solutions, the proposed work is an intelligent system using machine learning and image processing on Apple quality detection. The Apple image dataset was used with two stages of fruit, one is healthy and another one is damaged. The machine learning model is trained with this dataset to identify the fruit quality. The proposed technique uses feature extraction using image processing technique and SVM algorithm is applied to train and detect the quality of fruit.
Detecting Spam Bots on Social Network
Authors: Gnanasekar A.
Published: June 2021

Bots have made an appearance on social media in a variety of ways. Twitter, for instance, has been particularly hard hit, with bots accounting for a shockingly large number of its users. These bots are used for nefarious purposes such as disseminating false information about politicians and inflating celebrity expectations. Furthermore, these bots have the potential to skew the results of conventional social media research. With the multiple increases in the size, speed, and style of user knowledge in online social networks, new methods of grouping and evaluating such massive knowledge are being explored. Getting rid of malicious social bots from a social media site is crucial. The most widely used methods for identifying fraudulent social bots focus on the quantitative measures of their actions. Social bots simply mimic these choices, leading to a low level of study accuracy. Transformation clickstream sequences and semi-supervised clustering were used to develop a new technique for detecting malicious social bots. This method considers not only the probability of user activity clickstreams being moved, but also the behavior's time characteristic. The detection accuracy for various kinds of malware social bots by the detection technique assisted transfer probability of user activity clickstreams will increase by a mean of 12.8 percent, as per results from our research on real online social network sites, compared to the detection method funded estimate of user behaviour.
The Effect of Emotional Intelligence on Transformational Leadership Style Towards Teacher’s Organizational Commitment: A Pilot Test
Authors: Ghazali Puspa Liza
Published: June 2021

This research focuses on the effect of emotional intelligence as a predictor between the relationship of transformational leadership style towards teachers’ organisational commitment. The purpose of the research is to examine is there any finding found between direct and indirect significant effect of transformational leadership style on teachers’ organisational commitment with emotional intelligence define as a mediator. Hundred respondents of daily secondary school teachers in Terengganu were chosen to answer the questionnaire for a pilot study. Exploratory Factor Analysis (EFA) need to be done to find the value of the factor loading for each item must be that greater than 0.6 which fits for the research. The data is suitable to proceed for an analysis of Exploratory Factor Analysis (EFA) if the value for Kaiser Meyer Olkins (KMO) and Bartlett Test of Sphericity achieve the significant level (p < 0.05) which indices the accuracy of EFA result and the value of K should be higher than 0.60 as proposed. The reliability test needs to be done to find the value of Cronbach’s Alpha which was greater than 0.6 and must be accepted. To conclude, the suitability test of the instruments which was adapted from previous study to the population and situation of the research are admissible.
Design of Wearable Microstrip Patch Antenna Using T-Shaped Slot Antenna Compared with U-Shaped Slot Antenna for Health Monitoring Systems
Authors: Meghana Mannem
Published: June 2021

Aim: To Enhance radiation characteristics such as bandwidth, gain and Voltage Standing Wave Ratio (VSWR) by designing innovative wearable T-shaped and U-shaped slot microstrip patch antennas using the FEKO tool for health monitoring systems by using FR4 substrate for an operating frequency ranging from 2.2 to 2.6 GHz. Materials and methods: The microstrip patch antenna ground plane is made with FR4 material by using FEKO software varying frequency between 2.2-2.6 GHz. The T-Shaped and U- shaped slot microstrip patch antennas was chosen as a group having 20 samples each. The bandwidth, gain and VSWR was obtained for T-shape and U-shape slot antennas. Results: T-shaped slot antennas (P=0.001) have significantly higher bandwidth, gain and lower VSWR than the U-shaped slot antenna (P=0.031).The obtained significance value is <0.005 and mean values also increased. Conclusion: T-shaped microstrip patch antenna is designed and simulated using FEKO tool. The T-shape slot antenna has higher bandwidth, gain (Mean of T-shape 2.7238 and U-shape 1.4626) and VSWR (Mean of T-shape 8.3951 and U-shape 6.7675) when compared to U-shaped slot antenna. So, this antenna is very suitable for health monitoring systems.
Simulation and Comparison of Current Voltage Characteristics of Si and Ge based Bio Field Effect Transistor by Varying Oxide Thickness to Get Better Sensitivity
Authors: Layasree S.
Published: June 2021

Aim: The current voltage characteristics of Silicon based BIOFET and Germanium based BIOFET are simulated by varying their oxide thickness ranging from 1nm to 100nm. Materials and Methods: The electrical conductance of Silicon based BIOFET (n=320) was compared with Germanium based BIOFET (n=320) by varying oxide thickness ranging from 1nm to 100nm in the NanoHub© tool simulation environment. Results: Germanium based BIOFET has significantly higher conductance than Silicon based BIOFET. The optimal gate oxide thickness for maximum conductivity was 1nm for Silicon based BIOFET and 35nm for Germanium based BIOFET. Conclusion: Within the limits of the study, Germanium based BIOFET with oxide thickness of 35nm offers the best conductivity.
Classification of Analyzed Text in Speech Recognition Using RNN-LSTM in Comparison with Convolutional Neural Network to Improve Precision for Identification of Keywords
Authors: Prasad Bathaloori Reddy
Published: June 2021

Aim: Text classification is a method to classify the features from language translation in speech recognition from English to Telugu using a recurrent neural network- long short term memory (RNN-LSTM) comparison with convolutional neural network (CNN). Materials and Methods: Accuracy and precision are performed with dataset alexa and english-telugu of size 8166 sentences. Classification of language translation is performed by the recurrent neural network where a number of the samples (N=62) and convolutional neural network were a number of samples (N=62) techniques, the algorithm RNN implies speech recognition that can be compared with convolutional is the second technique. Results and Discussion: RNN-LSTM from the dataset speech recognition, feature Telugu_id produce accuracy 93% and precision 68.04% which can be comparatively higher than CNN accuracy 66.11%, precision 61.90%. It shows a statistical significance as 0.007 from Independent Sample T-test. Conclusion: The RNN-LSTM performs better in finding accuracy and precision when compared to CNN.
Principles of Criminal Justice as Guiding Principles in the Protection of Human and Civil Rights and Freedoms
Authors: Tokareva Ekaterina Viktorovna
Published: June 2021

The article deals with the problematic aspects related to the criminal procedure regulation of the implementation of the principles of criminal justice. The problematic aspects connected to the implementation of the principles of criminal justice by the participants on the part of the defense, the prosecution, and the court are touched upon. The article considers the features of the implementation of the principle of competition, equality of the parties, a reasonable period of criminal proceedings in the pre-trial stages of the criminal process. The conclusion summarizes all the procedural features which are encountered in the implementation of all the principles as fundamental principles during all stages of the criminal process.
Influence of Dietary Supplement Assortment on the Population's Quality of Life
Authors: Dymova Yuliya Igorevna
Published: June 2021

Since the appearance of the skin is an important attribute of the modern person, various methods can be used to achieve the desired. The most effective is often the simultaneous use of drugs “inside and outside”. The object of this research is dietary supplements, one of the methods for improving the appearance of the skin. The market situation for functional dietary supplements has been studied. The assortment of dietary supplements according to their purpose has been systematized (“cleansing”, “nutrition”, “protection”, “improvement of skin functions”). The results will help to make timely decisions about the need to develop products of this type.
Blockchain Technology Development as Tool for Enhancing Security in Management and Protection of Intellectual Property Rights in Additive Manufacturing
Authors: Sekerin Vladimir Dmitrievich
Published: June 2021

The purpose of the study is to analyze the capabilities of blockchain technology as a tool for enhancing the security in management and protection of intellectual property rights in additive manufacturing. The study is research-oriented and is an introduction to the use of blockchain technology for intellectual property protection. The following methods are used in the study: the analysis of documents on the use of blockchain technology in industrial asset management and the protection of content creators' rights, as well as the expert survey to assess the reliability of the selected sources. The authors introduce the term blockchain and discuss the capabilities of this technology for intellectual property protection in the field of design and production. A digital platform is proposed to enable the file exchange. Moreover, the authors describe the three main steps for developing a digital platform based on blockchain technology: the development of specialized tokens to reward users, the definition of conditions that should be included in smart contracts and the size of awards and incentives for each interested party that gains access to the platform.
Modeling the Management of International Reserves from the Perspective of Financial Stability
Authors: Voronkova Elena Konstantinovna
Published: June 2021

The paper explores the issues and international practices of the management of international reserves. The link is described between financial stability and international reserves. Emphasis is put on the specific significance of this subject for emerging economies. The main directions are charted for developing a systemic management approach in the domain and a case is made for applying modeling principles.
Causes and Consequences of Fire Emergencies on Oil and Gas Platforms
Authors: Jafarov Elkhan
Published: June 2021

This study presents an analysis of the causes and consequences of the largest offshore platform accidents associated with oil and gas production. The research on this problem allows improving the reliability of risk assessment associated with offshore oil and gas production, as well as developing methods for improving the fire safety of oil and gas platforms under various operating conditions.
Classification of Risks of High-Technology Production
Authors: Vyacheslavova Olga F.
Published: June 2021

In the modern economic system, the concept of developing high-technology production shapes the competitiveness and outlook of national economic development. The specifics of high-technology production imply considerable risks emerging across the lifecycle, which requires risk management. The paper explores the aspects of businesses engaged in high-technology production and the risks involved. A classification of risks is proposed for high-technology production in accordance with the requirements set in standard GOST R ISO 9001-2015.
Performance Improvement in Cloud Computing Environment by Load Balancing-A Comprehensive Review
Authors: K. Ramya
Published: June 2021

With the advent of cloud computing, the affinity between business and technology had increased manifold, allowing users to access IT resources at their convenience through the pay-per-use scheme. With such huge demand surging day to day, the cloud environment must cater to the user requirements flawlessly and also should be rewarding to the providers of cloud service. To maintain its high level of efficiency, there are several challenges that the cloud environment should tackle. One amongst those challenges is the balancing of load. It is one of the primary features of cloud computing that focuses on avoiding the overloading of nodes where there may be idle nodes or nodes with lesser load present at the same juncture. By keeping an effective check on the load several the Quality of Service (QoS) parameters including response time, throughput, resource utilization, energy consumption, cost etc., can be improved, adding to better performance of the entire cloud environment. Even distribution of load among datacenters will contribute to optimal energy consumption and keeps a check on carbon emissions. In this paper we have presented a methodical review on literature pertaining to load balancing strategies that had been proposed in the cloud environment. We had made in-depth analyses of available load balancing techniques and had come up with their advantages, limitations along with the challenges to be addressed by researchers for developing efficient load balancing strategies in the near future. We had also suggested prospective insights about the aspects in load balancing that could be applied in the cloud environment.
Design of High-Speed Low Power Computational Blocks for DSP Processors
Authors: N. Alivelu Manga
Published: June 2021

In today’s deep submicron VLSI (Very Large-Scale Integration) Integrated Circuits, power optimization and speed play a very important role. This importance for low power has initiated the designs where power dissipation is equally important as performance and area. Power reduction and power management are the key challenges in the design of circuits down to 100nm. For power optimization, there are several techniques and extension designs are applied in the literature. In real time Digital Signal Processing applications, multiplication and accumulation are significant operations. The primary performance criteria for these signal processing operations are speed and power consumption. To lower the power consumption, there are techniques like Multi threshold (Multi-Vth), Dula-Vth etc. Among those, a technique known as GDI (Gate diffusion Input) is used which allows reduction in power, delay and area of digital circuits, while maintaining low complexity of logic design. In this paper, various signal processing blocks like parallel-prefix adder, Braun multiplier and a Barrel shifter are designed using GDI (Gate diffusion Input) technique and compared with conventional CMOS (Complementary Metal Oxide Semiconductor) based designs in terms of delay and speed. The designs are simulated using Cadence Virtuoso 45nm technology. The Simulation results shows that GDI based designs consume less power and delay also reduced compared to CMOS based designs.
A Preclinical Study on Radiomics-Driven Brain Tumor Prediction Using Deep Convolution Neural Network
Authors: S. Divya
Published: June 2021

Radiomics is an exponentially increasing discipline that focuses on mapping the textural details found in various tissues for medical diagnosis. Nevertheless, high-end GPUs, the method of producing Radiomics artifacts is practically infeasible but can take a long time with radiological representation for some higher order functionality like Gray-level Co-occurrence Matrix (GLCM). Researchers created RadSynth, a deep Convolutional Neural Network (CNN) framework that constructs Radiomics images efficiently. For simulation of GLCM uncertainty artifacts through post-contrast DCE-MRI, RadSynth has been investigated on a prostate cancer therapeutics market of seventy patients. When compared to conventional GLCM entropy images, RadSynth offered great computational uncertainty images. We conclude from this evaluation that both spatial distribution and optimization influence psychic distance estimation, and experimental results are less resilient to varying image resolution rather than varied optimization frequency.
Image Reconstruction in Surgical Field Using Deep Learning
Authors: S Divya
Published: June 2021

The field of medical image reconstruction helps to improve image quality by manipulating image features and artefact with Filtered-Back Propagation for X-ray Computer Tomography (CT), Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). This project focuses on detection of tumour cells using Radiomics application that aims to extract extensive quantitative features from magnetic resonance images. In this paper image discretization models and image interpolation techniques are used to segment the MR images and train them for Image Reconstruction. The image based gray level segmentation is carried out for required feature extraction to improve the clustering analysis for segmentation. Convolution Neural Network is used for image classification and recognition because of its high accuracy. The CNN follows a hierarchical model which works on building a network and finally gives out a fully-connected layer where all the neurons are connected to each other and the output is processed. The JPEG approach is a commonly used type of compression of lossy images that centres on the Discrete Cosine Transform. By splitting images into components of varying frequencies, the DCT functions. Finally the output from the Radiomics application is compared with the existing methodology for determining the Mean Squared Error - Loss Function to ensure the image compression quality.
New Features for Webcam Proctoring Using Python and Opencv
Authors: S. Harish
Published: June 2021

Online examinations have turned out to be the new normal. However, it is not that easy to proctor the students as rigorously as in in-center examinations. It is essential to find an approach to proctor the online examinations too as rigorously as possible. There are already several webcam proctoring systems that are used in the real world, but these systems are not very accurate and miss out on detecting all possible malpractices and in certain cases due to defect in the system it detects a malpractice for someone who never even attempted any. This project focuses mainly on building features that can make the existing webcam proctoring system more advanced and rigorous. The project is aimed at building the following features namely head pose estimation, mouth opening detection, eye ball monitoring, number of persons detection, mobile phone detection and face spoofing detection. For each of these features, machine learning models are built using Python. All these features make use of the live webcam feed which is obtained using OpenCV and an output is obtained which gives information about the direction of the head and eyes, presence of more than one person and presence of mobile phone, opening of mouth, occurrence of face spoofing. All these outputs are recorded as a log file which can be used to identify any possible malpractices based on these features.