bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management and regulatory supervision of legacy sites and radioactively contaminated lands in Republic of Kazakhstan
Authors: Tazhibayeva Irina , Klepikov Alexander , Romanenko Oleg , Blynskiy Alexander , Sergazin Gumar , Ermatov Abdumalik , Zhunussova Tamara , Sneve Malgorzata 
Published: August 2021

Abstract
The safe management and disposal of radioactive waste (RW) arising from the nuclear legacy, as well as newly generated RW, are key problems. Their solution will have important implications for nuclear energy development, the introduction of other radiation technologies, and their public perception. In the framework of the cooperation between the Committee of Atomic and Energy Supervision and Control (CAESC) of the Ministry of Energy of the Republic of Kazakhstan and the Norwegian Radiation and Nuclear Safety Authority (DSA), work has been carried out to analyse the current state of nuclear and radiation safety in the Republic of Kazakhstan. The analysis was based on identifying gaps in national legislation and the assessment of corresponding threats in this area. Proposals for their elimination were developed, taking into account international experience and International Atomic Energy Agency recommendations. Analysis of the current situation in the Republic of Kazakhstan showed that at present the RWs are not properly regulated within an up-to-date regulatory framework. Currently, a list of key by-laws is being developed, which will support the provisions of a new law on RW management, and work is underway to adopt the already developed and drafted regulatory documents. Within the framework of the CAESC-DSA cooperation, the priority tasks established for 2021–2024 include the development of regulatory documents for the rehabilitation of uranium heritage sites, site selection for new nuclear facilities, and the management of nuclear materials for certain types of installations and manufactures. Practice has shown the need to use the advanced international experience and common approaches developed internationally, to develop and apply long-term and reliable solutions for the management of RW and nuclear legacy facilities and territories. The solution of these problems concerns not only scientists, technologists, and employers of the nuclear industry, but requires their cooperation with politicians, regulatory authorities, and the general population. The importance of sharing international experience to understand and solve these challenges is highlighted.
On the effects of strain gradients on spinodal decomposition
Authors: Petsos George 
Published: August 2021

Abstract
When the molar volume of a binary solid solution depends on composition, composition fluctuations are accompanied by strain fluctuations. In order to describe the process of spinodal decomposition in these systems, we develop a coupled one-dimensional elastodiffusion model that takes account of the developed coherency strains and their gradients. Based on this model we examine the effects of the developed strain gradients on the stability of the solution.
Enhanced preconditioner for JOREK MHD solver
Authors: Holod I , Hoelzl M , Verma P S , Huijsmans GTA , Nies R 
Published: August 2021

Abstract
The JOREK extended magneto-hydrodynamic (MHD) code is a widely used simulation tool for studying the non-linear dynamics of large-scale instabilities in divertor tokamak plasmas. The code is usually run with a fully implicit time integration allowing to use large time steps independent of a CFL criterion. This is particularly important due to the strong scale separation between transport processes and slowly growing resistive modes in contrast to fast time scales associated with MHD waves and fast parallel heat transport. For solving the resulting large sparse-matrix system iteratively in each time step, a preconditioner based on the assumption of weak coupling between the toroidal harmonics is applied. The solution for each harmonic matrix is determined independently in this preconditioner using a direct solver. In this article, a set of developments regarding the JOREK solver and preconditioner is described, which lead to overall significant benefits for large production simulations. The developments include the implementation of a complex solver interface for the preconditioner leading to the general reduction of memory consumption. The most significant development presented consists in a generalization of the physics based preconditioner to ‘mode groups’, which allows to account for the dominant interactions between toroidal Fourier modes in highly non-linear simulations. At the cost of a moderate increase of memory consumption, the technique can strongly enhance convergence in suitable cases allowing to use significantly larger time steps, and thus improving the overall time performance by more than a factor of 3.
Real Time Face Recognition using Effective Supervised Machine Learning Algorithms
Authors: Nagaraj P. , Banala Rajesh , Krishna Prasad A.V. 
Published: August 2021

Abstract
In security authentication systems, face recognition has become an emerging new trend. Modern FR processes can detect whether the individual is real (live) or not through face recognition, thus preventing the systems from being compromised by displaying an actual person’s image. These new systems of face recognition are the result of recent advances in the field of computer vision and efficient algorithms for machine learning. This thesis describes in depth how the identification of a real time face can be order to create a safety alert framework for the workplace, the machine learning algorithm Haarcascade classifier was used to build four distinct classes for identification of security equipment and eventually identify the faces in both images and video using python open CV. Initially, face detection technique is performed to scan the face identity marks through.
Hjorth Parameter based Seizure Diagnosis using Cluster Analysis
Authors: Arjaria Siddhartha Kumar , Chaubey Gyanendra , Shukla Nishtha 
Published: August 2021

Abstract
The health-related issues have been increased with a wide range in few years. Hence the need for effective and advanced health care systems or aids isexpanding. New methodologies and instruments must be developed to aid the doctors inintelligent health caring of patients. Biomedical signals are a rich source of information, and it is not easy to understand by the normal human beings. To provide ease, extraction and analysis of biomedical signals can help get the correct information to everyone. The signals generated by the brain control the status of the mind and control the action of the whole body. Epilepsy is a disease by which around 50 million people are affected worldwide. Abnormal synchronisation of the neural activity with symptoms like convulsion is the phenomenon of epileptic seizures. An advanced seizure diagnosis system will help in the detection and diagnosis of epileptic seizures. In this paper, clustering algorithms are applied to Electroencephalogram (EEG) data to classify it in normal and epileptic seizures using the Hjorth parameters. After extracting the Hjorth parameters from EEG signals and k-means, basic sequential algorithmic scheme (BSAS), partitioning around medoids (PAM), fuzzy c-means (FCM), and Vally-Seeking clustering algorithms are applied to group it into normal and seizure. With the used dataset, the Vally Seeking clustering algorithm gives the best performance with an accuracy of about 87%.
A security enhancement for the two way clustering algorithm for image mining
Authors: Jaya Ram M , Vyaya Bhaskara Reddy V 
Published: August 2021

Abstract
Image mining is one of the mining technique which is used for the mining of the image from the huge databases. The Image mining is used in the various sectors for the prospective use of the mining techniques. The increase in the data theft become one of the biggest challenge for the image repositories. This paper proposes the security architecture for the image repositories which is used for the image mining. The salient featured algorithm called as Imago-Sec Algorithm is proposed and used for the efficient providing of the security to the image repositories which is used for the image mining. The relative mining technique is used for the mining of the data from the image database. The Proposed algorithm is a homomorphic token algorithm which uses a single key contribution for both the encryption and decryption of the data in the image databases. The experimental results thus follow which provides that efficiency and throughput of the security that is being implemented.
Cloud data security and various security algorithms
Authors: Tyagi Kanika , Yadav S.K , Singh Mayank 
Published: August 2021

Abstract
The term Cloud computing is a most trending and promisingtechnology. It is the most basic need for many organizations. Cloud technology has many advantages as user can access the files from anywhere over the internet. It has also a very known feature of using the resources according to their demand and user does need to pay extra charges for the unused resources. In Cloud Computing user do not need to carry all their documents with them as cloud access is global. But as Cloud computing means sending data over internet so sometimes there may be security issues and threat of intruder attack at the time of data transmission. As traditional banking industry is totally changed and now the total control in the hand of customer rather than the bank. In banking industry cloud computing provides various features viz; cost saving, business continuity, business agility and time saving. but as data in bank is the most crucial data so cloud security is the first priority for every bank before adopting cloud. security at cloud is the biggest obstacle for the banking industry to adopt this trending technology and its services. So there is need to provide security to the cloud. This paper aims on cloud basic methodology and analyze some security algorithms and their applicability in cloud banking environment.
Parasitic sorority of speech processing algorithms with an assortment of statistical toolkits
Authors: Sudhakaran Prathibha , Yadav Ashwani Kumar , Karamchandani Sunil 
Published: August 2021

Abstract
Speech is a one-dimensional quasi non-stationary time varying signal produced by a sequence of sounds. Speech signals are random in nature. Speech signals are easily corrupted by noise so recognition is an important role in speech processing. Many researches have designed recognition system with challenging parameters. Speech corpus can vary from environment, region, dialects, age, rate at which words are spoken. Pre-processing is the first step which includes framing, de-noisingand filtering. This paper focuses on speech techniques and statistical open source tools such as HTK, Julius, CMUSphinx and Kaldi. The word error rate obtained using all the toolkits on WSJ1 corpus gives us a clear understanding that Kaldi stands out as the most advanced recipes and scripts for speech recognition systems. An Indian English corpus by IITM was implemented in Kaldi yeilds WER of 6.41 and has been compared to other indian and international languages and well known corpuses.
Black Start Operation using a MMC based HVDC system
Authors: Sudarsana Reddy K. , Vigneshwar R. , Tripathi Anushka , Soundharya S P , Kirthika Devi V. S. 
Published: August 2021

Abstract
Blackouts could occur due to various faults and in order to keep the power stations running constantly to avoid consumers losing power a backup plan is necessary. Black start is the process of restoring power to the electric power stations. The Modular Multilevel Converter (MMC) topology has been propitious technology in High Voltage DC (HVDC) system. The research in MMC technology has significantly increased. The MMC based HVDC system has many advantages when compared to the other technology based HVDC system. In this paper, Black Start Operation using a MMC Based HVDC system is proposed to provide continuous power to the load for a certain period of time within which alternative methods of power generation can be made ready. The paper also provides a mathematical model of a continuous equivalent circuit of the MMC Phase Leg. The efficiency of the proposed idea has been verified by MATLAB/Simulink Software and discussed.
Integration of Machine Learning Techniques in Virtual Wireless Sensor Network for insect monitoring
Authors: Hussain Mohammad Equebal , Hussain Rashid 
Published: August 2021

Abstract
Agriculture industries are comparatively slow in adopting emerging technologies than any other industries despite lot of exciting research. The use of Wireless sensor network (WSN) is very important role in agriculture for more productive and sustainable growth. The structure of WSN is tightly application dependent. Every WSN have sensors, processing unit, low frequency radio wave transmitter and power supply using battery. With increasing number of interconnected WSN devices, there is substantial increase in data generation. It contains both control messages as well as application dependent data, collected by the sensors. The collected data are frequently sent to the nearest centralized controller for further processing and decision making. For continuous functioning of WSN, uninterrupted power supply is needed. Many researches are carried out to overcome these challenges. In this manuscript we are proposing a simple and effective machine learning techniques combined with pause and play method to increase battery life of WSN. This could be achieved in three stages play-pause-play (PPP) model. First by gathering data for some time (play mode), Second by putting WSN to sleep (pause mode), in the backend, apply machine learning algorithm that helps to build model from training data to predict the future data. At the final stage, put WSN back to play mode. Compare the result with actual data and fine tune the model to reduce the error. Using this method WSN will get enough sleep time to increase overall life by simulating the normal behaviour of sensor node. The sleep time will be calculated dynamically.
Hybrid Approach for Identification of Manhole and Staircase Using Image Processing
Authors: Sravani Jadala , Vaishnavi Adigiri , Durga Peruri Sravani , Kumar Ashwani 
Published: August 2021

Abstract
The main aim of this research paper is to provide multi security for the pedestrians/older using smart stick using IOT and GPS. This stick having IOT, voice module and attached with multiple sensors to provide high security to the blind peoples while walking. Now a day’s safety is main important cause to the peoples while walking or driving and many more places. This smart stick provides the high security and show way to walk, by using this system we can monitor the blind person position using web application/mobile application and also we can get emergency alert message along with exact location. This system has obstacle sensor, water sensor and MEMS sensors, so that it can detect obstacles sizes automatically and gives voice alert. By using water sensors, it can detect the floor condition is dry or wet and shows the way to walk. In case of any emergency person suddenly fall at floor/any place then this system immediately detects using MEMS tilt sensor and automatically send the message to respective numbers with location and also gives buzzer alarm continuously to alert the neighbours. So that this smart stick can be very useful to peoples to show correct path while walking on the floor or steps and many more places. In this paper, the system can be interconnected with the microcontroller and alert the respective persons when any emergency occurs. This tracking system is composed of a GPS receiver, Microcontroller. The Microcontroller processes this information and this processed information is sent to the respective numbers using web page.
Characterization of Flexible Patch Antennas on Planar and Curved Surfaces
Authors: Khan Habeeba , Ali Sayyed Arif , Wajid Mohd , Alam Muhammad Shah 
Published: August 2021

Abstract
This paper analyses patch antennas operating at 16 GHz on flexible Kapton polyimide substrate in various shapes, namely rectangular, circular, pentagon, hexagon, heptagon, and octagon. Their applications in medical areas, more particularly in wearable devices for E-health, are targeted. The bending effects of these antennas are studied, more specifically on gain, return loss, radiation characteristics, bandwidth, and beamwidth. A detailed comparison results showed that the rectangular patch had better performance even under the bending when the diameter of the surface is varied from 40mm to 120mm and maintains a gain of 4.8 dB at the given frequency. Under such extreme bending, the antennas operate satisfactorily with an efficiency of 43.424% to 47.41%.
Creation of architectural forms by combining additive and information technologies
Authors: Bogodukhova E S , Britvina V V , Bobrova E O , Gavrilyuk A V , Sorokin A Y 
Published: August 2021

Abstract
This work is devoted to the integration of advanced technologies of the modern industry for the creation of construction objects and architectural forms, as well as the development trends of this direction in the construction industry. The aim of the work is to modernize building methods for the construction of building and architectural structures by combining additive and information technologies. An empirical analysis of the construction industry market identified the main intra-industry development priorities affecting the formation of the industry, and a comparative analysis of “traditional” and additive manufacturing showed the advantages of digital technologies. The study of foreign experience has confirmed the relevance of the introduction of additive technologies into production practice. This article presents a 3D project “Digital manufacturing 2030” aimed at obtaining a positive effect from the implementation of layer-by-layer growing of complex building forms using computerization. The data proving its economic feasibility and social significance for the development of urban infrastructure and improvement of the standard of living are presented. Moreover, the percentage of “classic” and additive construction shows the effectiveness of the proposed development. The article is supplied with graphic materials and tables, as well as a detailed description of each stage of the study.
Development of a simulation model to research environmental index of a GTP-110 gas turbine operating as part of a combined cycle gas turbine power unit under changing operational and external climatic factors
Authors: Muravev I K , Kosyakov S V , Muraveva T E 
Published: August 2021

Abstract
Combined-cycle technologies to produce electrical and thermal energy are the most popular and promising all over the world. Their efficient application, however, has encountered a number of interdisciplinary problems. The present study was carried out on a mathematical model of a CCGT power unit. The results of the study are presented, allowing us to assess the impact of operational and environmental parameters on the stability of the combustion process in the combustion chamber of a GTP-110 gas turbine unit, and to determine the compatibility of environmental indicators with the standards for gas turbine operation with a wide range of loads, taking into account the technological and design constraints of thermal mechanical equipment. The main implementation features of a simulation model of a gas turbine unit (GTU) in the SimInTech dynamic modeling environment are considered.
Technologies of embedded project-based learning for undergraduate engineering students
Authors: Bazhenov R , Sabirova V , Samorukov A , Berseneva S , Beknazarova S 
Published: August 2021

Abstract
The purpose of the research is to develop a technology for incorporating project work in undergraduate engineering student training. A pedagogical experiment was conducted in the regional universities of Russia, the Kyrgyz Republic, and Uzbekistan in 2017-2021 among second-, third- and fourth-year engineering students. 126 students and 14 educators took part in it. To achieve the research goal, the authors used project-based learning, the authors’ technique for changing the content of the subject, and the questionnaire method. The authors designed the surveys in the Google forms service and processed the results with MS Excel. According to the experiment results, it can be argued that the successful implementation of project work in training is available through six techniques determined from the ratio of the time spent on face-to-face and independent study on the subject or learning and extracurricular activities. All the participants of the pedagogical experiment evaluated the techniques positively.
Methods of intelligent results ranking for the intermediate assessment of knowledge in mathematical disciplines
Authors: Masina O N , Petrov A A , Druzhinina O V , Shcherbatykh S V 
Published: August 2021

Abstract
We are developing methods of intelligent ranking of results for the intermediate assessment of knowledge on mathematical disciplines within the framework of a hybrid intelligent learning environment functioning. An extended structural diagram of a hybrid intelligent learning environment is presented and the methodology of forming a knowledge base is characterized. The study of new models of the pedagogical process is carried out using intelligent technologies. Clustering problems are solved and algorithms for analyzing test results based on the use of machine learning methods are proposed. The results of the proposed algorithms implementation are presented. The results of this study are of practical importance both for the development of methods for assessing knowledge in mathematical disciplines, and for identifying the abilities of students to research activities.
3D-printed Net-Structured Porous Capacitive Sensors Based Upon Silver-Coated-Glass Fiber-Filled Polymer Composites
Authors: Huang Pei , Cao Yingze , Xia Zhidong , Chen Shaosong , Wang Pengfei 
Published: August 2021

Abstract
Flexible sensors modified with microstructures possess excellent high sensitivity and ultralow detection limit. In this study, silver-coated-glass fiber-filled silicon rubbers with their net structures were 3D printed and designed. Porous structures were introduced through the multi-layer printing of the net structure. The high conductivity of the printed composites originated from the conductive fillers, which assure the composites applied in circuit connection. Flexible capacitive sensors were further fabricated with the porous composites as electrode layers and the flat polyethylene terephthalate film as the middle dielectric layer. The prepared capacitive sensors owned an excellent sensing property to detect ultralow load with a sensitivity of 0.0666 kPa−1. The evolution of the porous structure was schematically described, when the capacitive sensors were compressed. The net-structured porous capacitive sensors fabricated with 3D process would inspire us a new branch in the printing electronics.
Applications of Molten Pool Visual Sensing and Machine Learning in Welding Quality Monitoring
Authors: Sun Meiling , Yang Mingxuan , Wang Binrui , Qian Lijuan , Hong Yuxiang 
Published: August 2021

Abstract
On-line monitoring of welding quality is very important to the realization of intelligent welding technology and has become a research hotspot in the field of welding technology. This article reviews the research results and latest research progress of welding quality on-line monitoring based on molten pool visual sensing in recent years. First, it introduces the characterization of welding quality by the two-dimensional geometric features and three-dimensional topographic features of the molten pool in detail, and then analyzes the application of machine learning and feature engineering in the online prediction of welding status; we discuss the deep neural network and welding quality at the end Convergence of online detection technology. The work done in this paper reviews the progress of online monitoring technology for welding quality and provides a basis for the follow-up work.