bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Characteristics Analysis of Grinding Plate of Food Waste Grinding Mill Based on ANSYS Workbench
Authors: Li Jicheng , Pan Mingbo , Sun Kunpeng , Guo Lin
Published: January 2022

Food waste accounts for 30% - 50% of domestic waste, and its centralized treatment is difficult. For commercial places with large production of food waste, it is a better way to use grinding mill to crush food waste and then discharge it into sewer. The mechanical properties of grinding plate are the decisive factors affecting the performance of grinding mill. In this paper, the static analysis and modal analysis of the grinding plate of commercial grinding mill are carried out. The results show that: under the rated load, the maximum equivalent stress of grinding hammer is 83.4mpa, the maximum equivalent stress of cutter head is 77.6mpa, which meets the design requirements, but the stress is relatively concentrated. The lowest modal vibration frequency of the lapping plate is 456.2hz, and the lapping plate will not have resonance damage under normal conditions.
Research on Microstructure and Growth Mechanism of Different Primary Silicon in Hypereutectic Aluminum Alloy
Authors: Zhao Gaozhan , Xing Zhihui , Li Ming , Gao Shiqing , Tao Jianquan , Chai Shuxin
Published: January 2022

The as-cast microstructure of a typical hypereutectic Al-25Si alloy was studied, and the growth mechanism of different primary silicon phases was analyzed. The results show that the as-cast microstructure phase composition of the alloy is mainly primary silicon and eutectic silicon. Primary silicon is mainly petal-like, massive and other complex polyhedrons, and there are a lot of cavities, cracks and other defects in the interior and boundary; Eutectic silicon is coarse and long needle-like, and the distribution is relatively messy, which seriously deteriorates the mechanical properties and cutting performance, and hinders the further application of the alloy in the field of lightweight pistons. Petal-shaped primary silicon is grown by combining five tetrahedral crystal nuclei in the melt into a decahedron, while bulk primary silicon is mainly caused by the unbalanced aggregation of impurity elements. And these two types of silicon phase growth methods are related to the twin groove growth mechanism, which is the result of a combination of multiple mechanisms.
Analysis and Development Review of Metal and Metal/Ceramic Composite Coating Prepared on Magnesium Alloy Surface
Authors: Zhang Haichuan , Pu Xuemei , Yang Hua , Jiang Yifan , Wang Xiao
Published: January 2022

Magnesium, as one of the lightest metal structural materials, also has its advantages such as high specific strength, good electromagnetic shielding characteristics, good processability and easy recycling, so it has a wide application prospect. However, its poor insulation, corrosion resistance, wear resistance and other properties limited it to be an alloy that can be used in a large area. Therefore, how to improve the corrosion resistance and wear resistance of magnesium alloy is the key to promote the development of magnesium alloy field. This paper reviews the research progress of using magnetron sputtering technology to prepare ceramic composite film on the surface of magnesium alloy and briefly introduces the film corrosion resistance and wear resistance of the thin films. It analyzes the impact of metal transition layer, process parameters and other factors on structure and properties of metal / ceramic coatings and prospects for the development prospects of magnetron sputtering in the field of magnesium alloy surface protection.
Interaction Between Edge Dislocation and Single-Layered Graphene in Aluminum Matrix Investigated by Molecular Dynamics Simulation
Authors: Chen Liu , Li Zhencheng , Xu Sai , Sha Aixue
Published: January 2022

The influence of graphene on dislocation movement and subsequent mechanical response of aluminum is investigated by the computational method of molecular dynamics simulation. A Lennard–Jones potential describing Al-C interaction was obtained through ab
initio calculation. It was observed that the 2D graphene could reinforce Al matrix similar to the traditional Orowan mechanism. The Al/graphene interface first attract the gliding dislocation to reduce the system energy, which is unlike the grain boundary to repel gliding dislocations through pile-up mechanism. With the increase of stress, dislocation attracted and trapped at the front of graphene could glide along the interface and finally bypass it through climbing when graphene is orientated out of the shear plane. In addition, the strengthening ability of graphene is size dependent, showing a linear relationship between strength increment and graphene size.
Sound Absorption Performance of Aluminum Silicate Fiber for Noise and Vibration Reduction of Distribution Transformer
Authors: Chen Qunli , Wu Wengeng , Gao Xu , Huang Yibiao , Chen Xiangwen , Kang Jinping , Li Chaoxuan
Published: January 2022

In view of the low-frequency noise problem in urban substation, the sound absorption (SA) properties of aluminum silicate fibers (ASF) with different materials, unit weight, plate thickness and cavity thickness were tested in this paper. It was found that the high-purity ASF with larger unit weight, plate thickness and cavity thickness had larger low-frequency SA coefficient, which provided technical support for the development of new low-frequency noise reduction materials for substation.
Research and Innovation of Rapid Test Method for Water Quality Analysis
Authors: Lian Zheng , Ai Changpeng , Zhou Yonghua
Published: January 2022

Water quality safety is closely related to people’s production and life, and it is necessary for human survival. In recent years, water pollution incidents occur frequently, which not only reminds us of environmental protection, but also exposes the lack of rapid detection ability of water quality analysis in China. At present, there are obvious shortcomings in the mainstream rapid detection methods of water quality analysis. Therefore, this paper puts forward the research and innovation of the rapid detection methods for water quality analysis. In this paper, the main methods of water quality analysis and detection in China are studied in depth, and the advantages and disadvantages of various methods are compared and analyzed. The results show that most of the current mainstream detection methods have the contradiction between detection cost and detection accuracy. In view of this situation, according to the actual needs of rapid detection of water quality analysis, combined with vacuum detection tube electronic colorimetry, this paper innovatively proposed a rapid detection method of water quality analysis based on vacuum detection tube electronic colorimetry. In this paper, the principle of this method is introduced in detail. Through the relevant comparative test experiments, it can be seen that in the detection experiment of pH value and nitrite concentration, the vacuum detection tube electron colorimetry method in this paper has obvious advantages over the traditional spectrophotometer. This paper analyzes that the innovation research of water quality analysis and detection is the innovation of the whole process and the whole system. Therefore, this paper puts forward the ideas and specific optimization and improvement measures for the management work, industry standards and work concept of water quality detection.
Corrosion Detection of Structural Reinforcement Based on Artificial Intelligence Technology
Authors: Fei Hong , Hu Zifu
Published: January 2022

Due to the environmental degradation caused by soil erosion, it is of great significance to establish the relationship model between geological environmental factors and piping erosion. The method to determine the prone area of pipeline corrosion is limited. This paper introduces the mechanism of reinforcement corrosion, points out the non-destructive detection methods of common steel corrosion, and puts forward the measures to prevent and maintain the corrosion of reinforcement from the aspects of design, construction and material selection, so as to prolong the service life of concrete structure. Abrasion, capitation and chemical attack in concrete hydraulic structures can lead to deterioration of spillways, stilling basins, chutes, slabs and transverse joints, concrete blocks under sluices and any irregular surfaces affected by high flow rates. There are numerous coatings on the market that can be used to repair damaged surfaces. However, the basic data provided by the manufacturer is very limited, and if so, it is usually limited to room temperature values. The results show that the data of concrete, corrosion solution and chloride ion are 0.534, 0.673 and 0.384 respectively.
Application of Environmental Protection and Energy Saving Technology in Building Decoration Engineering
Authors: Kou Lan
Published: January 2022

On the road to sustainable development, the concepts of energy saving and environmental protection are deeply rooted in people’s hearts, and their technology has penetrated into all aspects of life. Like the construction industry, with the advancement of environmental protection and energy-saving technologies, the prospects for development will also be huge. Many materials used in construction projects can cause pollution. Although environmental protection technology is supported, its technology cannot remain unchanged. Technical researchers must reduce the risks of materials and continue to innovate and develop environmentally friendly technologies. Only in this way can we continue to make progress, ensure that we have a high-quality construction project, and ensure that energy conservation is consistent with social development. Therefore, to use the qualified construction methods adopted for the renovation project, you can use what you have now and ensure its ecological and human safety. Reduce material costs and reduce environmental pollution caused by indoor raw materials. As a basic framework, it combines the definitions of modern environmental protection and energy-saving technologies, and effectively applies environmental protection and energy efficiency technologies. Decoration and decoration of energy-efficient buildings. Adopt environmental protection technology, rationally use various energy-saving and environmental-friendly materials, and raise awareness of energy conservation and environmental protection. In addition, in-depth discussion and analysis of energy-saving management of building materials and equipment are also conducted. The goal is to improve the awareness of energy conservation and environmental protection in building decoration projects and lay a solid foundation for creating an environmentally friendly and energy-saving living environment. Experimental research results show that people do not know enough about the application of environmental protection and energy-saving technologies in building decoration projects. Therefore, we must increase publicity to let people know better, and we must also increase efforts to innovate in order to better implement and apply. People and regions have better development.
The Manufacture and Performance of Low Temperature Superconductors
Authors: Han Xuheng
Published: January 2022

The application of Nb3Sn superconductor joints is an important part in the production of ITER, MRI and so on. This paper first introduced the application, like coil of MRI, and basic information including the micro crystal structure of Nb3Sn superconductor, which includes the theoretical critical temperature of 18.1K, even mostly, experiments take place under 4.2K, which is the boiling point of liquid helium. Second, it talked a little about the production of CICC joints in industry. Then, mainly introduced the testing device, material parameters and testing procedures of resistance testing of Nb3Sn joints. Concluded all the data from several tests and summarized it. At last, it displayed some of its mechanical property especially about its brittle property and discussed some details in manufacture. Finally conclude about them all.
Estimation Method of Biomass Energy Reserves in China: A Case Study of Corn Straw
Authors: Miao Haixi
Published: January 2022

Nowadays, biomass resources are the best choice to replace fossil resources. Energy development in biomass is mainly through pyrolysis of biomass. At present, no one has estimated how much biomass energy there is for a country. In this article, taking corn as an example, China as the production country, the potential biomass resources in China are speculated, in which Lignocellulose is the main experimental biomass and pyrolyzed to obtain biomass energy. The most common method of biomass energy conversion is isothermal conversion. The first-order reaction model is used for kinetic analysis of the conversion. The sample is subjected to powder falling pyrolysis at 480 degrees. In order to overcome the regional differences in China, the data of 30 degrees north latitude are used. Finally, the reaction time and the total amount of biomass energy available for development and utilization in China in 2020 are obtained.
Reviewing the elements of marine ice cliff instability
Authors: Zhang Zhe
Published: January 2022

Antarctica’s ice sheets are the largest potential sea-level rise contributors, but projections of future sea-level rise yield wide ranges of estimates under different emission scenarios. An important factor in the variability of estimates is marine ice cliff instability (MICI). Inclusion of MICI yields the highest potential sea-level rise cases but also the largest uncertainty due to poor understanding of the factors that control it and the mechanisms of how it happens. Although evidence for MICI has been implied by paleo-ice sheet studies and observations of keel plough mark on sea-floor, recent statistical and modelling studies have suggested a lower magnitude of MICI effect on sea-level rise due to thinning of ice sheets and buttressing forces exerted on potentially failing cliffs. This paper reviews the factors that control MICI with the goal of identifying priorities for modern ice sheet studies to better bound the estimates.
Overview of the Recent Progress of Suppressing the Dendritic Growth on Lithium Metal Anode for Rechargeable Batteries
Authors: Liu Yang
Published: January 2022

The lithium metal has been considered as a competitive material for anode on the high-energy storage battery because of its various advantages, such as high capacity, low density, and the lowest electrochemical potential. However, the uncontrolled dendritic growth on the anode surface could cause the short circuit, even explosion of the battery. Therefore, strategies about how to effectively inhibit the formation of dendrites is of great importance. This paper will first give a brief introduction on the growth of dendrites. The attention is then focused on the recent advancements to suppress the dendrite growth of lithium metal, such as the optimization of electrolyte, application of artificial solid electrolyte interphase (SEI), and the modification of lithium anode. The future research directions will be presented at the end.
Numerical Simulation of the Influence of Taylor Vortex on the Apparent Viscosity Measurement of Semi-Solid Metallic Based On ANSYS Fluent
Authors: Dong Enjie , Li Gan , Hu Xiaogang , Li Zhong , Chen Juan , Zhu Qiang
Published: January 2022

The apparent viscosity of semi-solid metallic slurry with a low solid fraction, which is one of the most essential parameters for representing the rheological behavior, is mainly measured by the concentric cylinder rotational approach. The principle of this method is based on the assumptions that the fluid is in an ideal laminar flow state and obey the Newton’s internal friction law. However, as the angular velocity ω increases, the fluid undergoes a transition from a stable laminar flow state to a Taylor vortex and turbulent flow state. These unstable flow conditions such as Taylor vortex and turbulence have a severe impact on the accuracy of apparent viscosity measurement. However, these unstable flow conditions are difficult to monitored and analyzed in real time through experimental methods. Computer numerical simulation technology provides the possibility and convenience for the visualization of the flow state of the semi-solid metallic slurry in the measurement system. In this work, ANSYS Fluent was used to simulate the apparent viscosity measurement process of semi-solid slurry, and the flow state transition process of the semi-solid slurry in the measurement system was successfully visualized and analyzed. In order to avoid the influence of Taylor vortex, combined with the measurement principle of the concentric cylinder rotational rheometer and Taylor’s study on flow stability, the empirical equation of limiting speed to avoid Taylor vortex in the process of Searle rheometer viscosity measurement is given.
The Significance of Size Screening on the Pretreatment of Low Grade Bauxite: A Case Study of Block E70 / 3160 in Darling Range of Australia
Authors: Shao Zhurui , Liang Yunhan , Zhang Pan , Chen Zhiqiang , Jiang Zhenguo , Li Jinzhen , Yang Fan
Published: January 2022

In this paper, the size screening method and X-ray fluorescent spectroscopy were used to analyze low-grade bauxite samples from Darling Range, Australia. The results showed that the Av Al / Re Si(available alumina to reactive silica ratio) of samples JDB225 and JDB364 increased by 34.5% (8.7% to 11.7%) and 11.2% (8.9% to 9.9%); the available aluminum increased by 11.2% (27.8% to 30.9%) and 4.9% (30.9% to 32.4%) respectively. In screening, the optimum particle sizes of the two samples were 4 mm and 2.8 mm respectively. The results show that the best screening particle size can be determined by the size screening method, which can achieve the optimal combination of available aluminum grade, Av Al / Re Si and mass recovery rate, so as to significantly improve the grade and Av Al / Re Si of low-grade bauxite.
Evolution of the surface structure the proton-irradiated tungsten during isochronal annealing in the temperature range 600-1000 °C
Authors: Aldabergenova T , Baigonov M , Dikova L , Kislitsin S
Published: January 2022

This paper presents the research results the surface structure evolution of high-purity tungsten after irradiation with 350 keV protons and subsequent annealing in the temperature range 600 – 1000 °C. Irradiation to a fluence of 5×1017 cm‒2 leads to blisters formation on the irradiated surface. Successive two-hour annealing results in the evolution of the distribution of blisters - the total number of blisters decreases while the fraction of larger blisters increases. At an annealing temperature of 1000C, the blisters dissolve. Do not observed the blisters disclosure and surface flaking both after proton irradiation and subsequent annealing in temperature range 600 – 1000 °C.
Increasing the photoluminescence intensity of silicon nitride by forming K and N radioactive centres
Authors: Murzalinov D O , Shaikenova A A , Umirzakov A G , Fedosimova A I , Baitimbetova B A , Dmitriyeva Y A , Rakymetov B A
Published: January 2022

Creating a light emitter to transfer an electrical signal by optical way has a great importance in development of optoelectronics. The silicon nitride films studied by photoluminescence techniques, and determined luminescence is associated with presence of an extended zone of tail states. Defects play the main role in radiative recombination for structures annealed at 600 °C and 1100 °C. Photoluminescence (Pl) intensity of obtained films by plasma enhanced chemical vapor deposition is increased after annealing at 600 °C which are related to increased concentration of defects as a result of broken Si–H and N–H bonds. Due to the formation of N-centers through the breaking of N–H bonds, annealing at 1100 °C led to sharp decrease in the luminescence intensity 5 and 3 times for SiN1.1 and SiN1.5 samples respectively. Replacement of Si-Si bonds by Si-N enhance Eg with increasing stoichiometric parameter, which leads to blue shift edge of photoluminescence maximum. Carbon implantation of silicon nitride films with extra Si obtained by Plasma Enhanced Chemical Vapor deposition at 1x1014 cm‒2, 2x1015 cm‒2, and 1x1016 cm‒2 fluencies, in combination with prolonged annealing at 1100 °C temperature leads to the formation of additional K-centers.
Structure of tantalum coatings on NiTi substrate deposited by magnetron sputtering
Authors: Dikov A S , Larionov A S , Zhakanbayev E A , Dikova L A , Sanssyzbayeva A Zh , Akaev S O
Published: January 2022

The paper provides the results of studies of the structural-phase state of tantalum coatings prepared by magnetron deposition. The coatings were deposited on substrates made of titanium nickelide with a shape memory. The NiTi temperature during coating deposition did not exceed 100 °C. The structural-phase state of Ta was determined by X-ray diffraction at different stages of coating formation. It has been shown that at the initial stage of deposition, two-phase coatings (α- and β-Ta) are formed. The synthesis of the coating from Ta leads to the growth of interplanar distance of the B2 austenite phase in the crystallographic direction (100). The growth of interplanar spacing is caused by formation of microstresses during interaction with incident tantalum ions. The lattice parameters of the B19 ‘phase, responsible for appearance of the shape memory effect, do not change during deposition of the tantalum coating.
Determination of thermophysical properties of prototypes of tin-lithium alloy by differential scanning calorimetry
Authors: Bochkov V , Ponkratov Yu , Nikitenkov N , Baklanova Yu , Gordienko Yu , Tulubayev Ye , Samarkhanov K , Karambayeva I
Published: January 2022

This paper presents a description of research works to determine the thermophysical properties of a tin-lithium alloy with a different percentage of lithium and tin atoms in the alloy. The method of differential scanning calorimetry (DSC) was used for the studies, by which the thermophysical properties of the alloy (temperature of phase transition and enthalpy) were determined. The work was carried out at the TiGrA experimental complex. Studies to determine the enthalpy and temperature of phase transition of prototypes of tin-lithium alloy were carried out in the temperature range from 150°C to 500°C at a heating rate of 10°C/min. The experiments were carried out with a pristine sample of tin (reference) and prototypes of a tin-lithium alloy, the percentage of lithium in which was 20, 25 and 27 at. %. As a result of the work performed, the melting point of the prototypes was determined, which was 224°C and 218°C. The values of the specific heat of fusion (enthalpy) of the investigated alloys were determined, which amounted to 76.5 J/g, 80.7 J/g and 86.3 J/g, respectively.
Development Of Scenarios For Controlling The Fuel Campaign Of The Ivg.1M Reactor With Leu-Fuel
Authors: Zhanbolatov O. M. , Vurim A. D. , Surayev A. S. , Irkimbekov R. A.
Published: January 2022

The paper provides calculation of various campaign scenarios of the IVG.1M Research Reactor with LEU-fuel. The schemes of replacement and transfer of the fuel are suggested. Several options are considered that include a complete and partial replacement of spent nuclear fuel with fresh one, change in the reactor reactivity margin during campaign is calculated.
Non-radioactive scandium oxide receiving out of uranium ISR solutions
Authors: Kylyshkanov M K , Yaroshenko N N , Khlebnikova I A
Published: January 2022

The task of the research was to study and determine an effective method for the preparation of non-radioactive scandium compounds from uranium In-Situ Recovery (ISR) solutions. The widespread use of scandium is restrained by the high price due to its small production volumes, low content in the raw materials (scandium is a scattered element and does not form its own deposits), as well as the complexity of technological schemes for its extraction. Scandium receiving out of uranium reverses ISR solutions technological scheme was experimental tested, including sorption on MTS 9580 (Purolite’s production) ion exchanger with recurrent ballast impurities desorption and receiving concentrate that contains scandium. New radiation cleaning technological sequencing based on different solubility of radioactive elements and scandium in carbonate solutions, that accompanied by insoluble macro components complex formation, that contains in deactivated scandium concentrate and allows to get scandium oxide with desired component maintenance more than 94 % and less than 0,3 kilobecquerels/kg specific activity level was developed. The developed technology is based on the ability to form soluble carbonate complexes of scandium and radioactive elements, while the main macro components of the concentrate - ferrum, aluminum, calcium, silicon and others under the conditions of carbonation of the concentrate are inert or form insoluble compounds. Optimal radioactive impurity removing from concentrate conditions and scandium leaching from deactivated residue of scandium and macro impurity were studied and identified in laboratory conditions and during pilot tests.
Research on obtaining gadolinium oxide from waste technologies for processing of uranium-gadolinium containing materials
Authors: Kylyshkanov M K , Yaroshenko N N , Gusakova G V , Dorn A A , Gofman A A , Varyvdin Y V
Published: January 2022

One of the activities of the Uranium production of JSC “UMP” is the processing of hard-to-open uranium-gadolinium-containing scraps. When processing materials of this type, after their dissolution, the gadolinium fluoride precipitation operation is carried out with the subsequent extraction purification of the obtained uranyl nitrate solutions.

At the deposition stage, almost all the gadolinium contained in the scraps is transferred to the GdF3 precipitate and sent to the tailings dump as part of the solid waste.

In order to determine the possibility of obtaining gadolinium oxide from waste processing of uran-gadolinium containing materials, exploratory studies were initiated.

In the course of the work, various methods of obtaining gadolinium oxide were tested. A number of experiments were carried out to refine the modes of obtaining gadolinium oxide by the method of two-stage precipitation of oxalate. A technological scheme was developed, according to which a finished product was obtained, suitable for further use in the technology of obtaining uranium-gadolinium tablets of UMP JSC.

The scheme consists of the following main operations: dissolution of gadolinium fluoride in a solution of aluminum nitrate, precipitation of gadolinium oxalate, washing of gadolinium oxalate in the first stage of precipitation with a solution of nitric acid, conversion of oxalate to gadolinium hydroxide, dissolution of hydroxide in a solution of nitric acid, re-precipitation of gadolinium oxalate, calcination to gadolinium oxide.
Route measurements of natural surface radiation background in the Almaty region
Authors: Bigeldiyeva M T , Dyachkov V V , Zherebchevsky V I , Zaripova Yu A , Yushkov A V
Published: January 2022

Measurements of the spatial distribution of radon isotopes were carried out from April 2021 to August 2021 in the foothills of the Trans-Ili Alatau of the Tien Shan in the Almaty region at various heights above sea level: from 500 to 2500 meters. They were carried out using electronic radiometric equipment: beta-dosimeter “RKS-01B-SOLO”; gamma dosimeter “RKS-01G-SOLO”; radiometer of radon and its daughter decay products “RAMON- 02” in the field. As a result, preliminary assessment schemes were built for route measurements of the 222Rn radon isotope, beta and gamma radiation fields from natural daughter products of decay of radon isotopes and radionuclides located in the surface atmospheric layer.
Application of the medical linear accelerator ELEKTA AXESSE in the study of sorption properties of impurities and absorption coefficients of medium and heavy chemical elements
Authors: Zaripova Yu A , Gladkikh T M , Bigeldiyeva M T , Dyachkov V V , Yushkov A V
Published: January 2022

In this article, the authors propose a new technique for measuring linear attenuation coefficients on the medical linear accelerator Elekta Axesse. Linear attenuation coefficients were obtained for four samples at different concentrations of substances at a gamma-ray energy of 6 MeV. A unified ionization chamber was used as a detector to register the transmitted gamma-ray beam through the samples under study. Linear absorption coefficients were obtained for elements B, C, O, S, Fe, Ba taking into account their concentration, as well as taking into account the different mass inclusion of paraffin in the samples under study, which is acyclic hydrocarbons CnH2n+2. The measurement results showed that taking into account certain components in impurities leads to relatively small, but quite noticeable differences in the determination of the total absorption coefficients. This is especially important to take into account for determining the concentration of light elements in samples. To determine the content of medium and heavy chemical elements, taking into account the content of light elements can be neglected. The use of a 6 MeV gamma-ray beam made it possible to reduce the errors in determining the absorption coefficients, since their dependence on energy in the region of applicable gamma-ray energies is not so great in comparison with the low-energy region, in which the shell effects for heavy elements will introduce significant contribution.
High-sensitive colour indicator of absorbed dose of epithermal neutrons radiation
Authors: Kulabdullaev G A , Kim A A , Djuraeva G T , Nebesniy A F , Abdullaeva G A , Yuldashev D O
Published: January 2022

In our study, the high-sensitivity colour indicator of the absorbed dose of radiation of epithermal neutrons with energy 0 to 10 keV for dosimetry of low-energy neutrons was developed. We had been developed an indicator on the basis of the dye solution of arsenazo III and gadopentetic acid, allowing precisely define of absorbed dose in the range 2 to 103 Gy. The properties of arsenazo III as metallic indicator, which changes colour after binding of free ions of metals, were used. Colour of the indicator solution before irradiation and after it is stable enough in time at storage in the dark, at artificial illumination or at scattered sunlight. The developed indicator, consisting of a solution of arsenazo III and gadopentetic acid, allows estimating the absorbed dose of epithermal neutron irradiation with good accuracy and reduces the error of measurement related to changing colour of dye under the influence of other factors (light, temperature etc.) Dosimeter is tissue-equivalent and possesses a high-sensitivity neutron radiation due to the content of gadolinium in solution, which has great neutron capture cross-section. The developed dosimeter persists spectrophotometric characteristics after irradiaion within few weeks that allows to use it for measurement of the absorbed dose, both in real time mode and with the delayed measurement within few weeks.
Synthesis of CH3NH3PbI3 hybrid perovskite crystals for optoelectronic devices
Authors: Dyussembekova S , Kinev V , Smirnova A , Gladyshev P
Published: January 2022

This article is deals with the synthesis of hybrid organic-inorganic perovskite crystals. We present a brief review of the literature devoted to the synthesis of perovskite crystals. We have analyzed methods for the synthesis of perovskite crystals to select optimal conditions. Bulk perovskite crystals of CH3NH3PbI3 were synthesized. The resulting crystals were analyzed by X-ray phase analysis, which confirms the formation of tetragonal perovskite crystals and can be used to obtain thin films.
Quality control challenges post covid-19 crisis: an integrated IoT and IoP approach
Authors: Sharma Harshit , Sumathi G
Published: January 2022

The Covid -19 is arguably the biggest pandemic in history and there are a lot of challenges that must be dealt with. One of the biggest challenges post Covid-19 is to tackle quality control challenges. This research paper discusses some of these challenges and solutions using an integrated internet of things (IoT) and internet of protocols (IoP) based approach and further showing its implementation in the industry world and hence, proving to be a solution for damage assessment. With the help of IoT- enabled quality control system, six-sigma rule is also analysed. Post Covid crisis, it is important for every institution to gain back customer trust so quality of materials should be maintained and IoT enables us to do the same. The unification of industrial IoT (IIoT) and industry 4.0 is also discussed as it leads us to understand that this unification is the next evolution of smart manufacturing and digital technologies. This methodology can lead us to accelerated innovation in applications for overcoming the eventual challenges post Covid in the near future. Also, small-scale/large-scale companies making use of the above research methodology can adhere to six-sigma criterion.
Performance analysis of cost effective multi-hop Time Sensitive Network for IEEE 802.1Qbv and IEEE 802.1Qbu standards
Authors: Hagargund Asha G , kulkarni Muralidhar , Satheesh Hariram S
Published: January 2022

Time-Sensitive Networking (TSN) is an emerging technology, which enables advancements in applications like industrial automation, automatic vehicle-to-vehicle communication, etc. which hosts various time-critical applications, ensuring bounded latency. The novel idea of this paper is to present OMNET++ simulation-based complex multi-hop TSN network using the native VLAN concept to bring out a cost-effective model for inter-TSN and Intra-TSN domains. This paper investigates the performance of hybrid IEEE standards, ie.IEEE 802.1Qbu and IEEE 802.1Qbv standards. The simulation results show that the combination of these standards, when effectively scheduled in switches will reduce the latency by 3.3 µseconds in time-critical applications. Further, it is observed that in Best effort traffic, frame loss is also very less in the range of 2-5 frames out of 1385 frames. These results certainly will be of great value in more complex TSN deployments.
Forecasting variance of NiftyIT index with RNN and DNN
Authors: Karthik C R , Raghunandan  , Ashwath Rao B , Subba Reddy N V
Published: January 2022

A time series is an order of observations engaged serially in time. The prime objective of time series analysis is to build mathematical models that provide reasonable descriptions from training data. The goal of time series analysis is to forecast the forthcoming values of a series based on the history of the same series. Forecasting of stock markets is a thought-provoking problem because of the number of possible variables as well as volatile noise that may contribute to the prices of the stock. However, the capability to analyze stock market leanings could be vital to investors, traders and researchers, hence has been of continued interest. Plentiful arithmetical and machine learning practices have been discovered for stock analysis and forecasting/prediction. In this paper, we perform a comparative study on two very capable artificial neural network models i) Deep Neural Network (DNN) and ii) Long Short-Term Memory (LSTM) a type of recurrent neural network (RNN) in predicting the daily variance of NIFTYIT in BSE (Bombay Stock Exchange) and NSE (National Stock Exchange) markets. DNN was chosen due to its capability to handle complex data with substantial performance and better generalization without being saturated. LSTM model was decided, as it contains intermediary memory which can hold the historic patterns and occurrence of the next prediction depends on the values that preceded it. With both networks, measures were taken to reduce overfitting. Daily predictions of the NIFTYIT index were made to test the generalizability of the models. Both networks performed well at making daily predictions, and both generalized admirably to make daily predictions of the NiftyIT data. The LSTM-RNN outpaced the DNN in terms of forecasting and thus, grips more potential for making longer-term estimates.
Classification of plant seedlings using deep convolutional neural network architectures
Authors: Makanapura Namratha , Sujatha C , Patil Prakash R , Desai Padmashree
Published: January 2022

Weed management has a vital role in applications of agriculture domain. One of the key tasks is to identify the weeds after few days of plant germination which helps the farmers to perform early-stage weed management to reduce the contrary impacts on crop growth. Thus, we aim to classify the seedlings of crop and weed species. In this work, we propose a plant seedlings classification using the benchmark plant seedlings dataset. The dataset contains the images of 12 different species where three belongs to plant species and the other nine belongs to weed species. We implement the classification framework using three different deep convolutional neural network architectures, namely ResNet50V2, MobileNetV2 and EfficientNetB0. We train the models using transfer learning and compare the performance of each model on a test dataset of 833 images. We compare the three models and demonstrate that the EfficientNetB0 performs better with an average F1-Score of 96.26% and an accuracy of 96.52%.
Temporal face feature progression with cycle GAN
Authors: Ashish Roy , Prasad B G
Published: January 2022

The aging process creates significant changes in the appearances of people’s faces. When compared to other causes of variation in face imaging, aging-related variation has specific distinct properties. Facial Aging variations, for example, is unique for each person; it occurs gradually and is significantly influenced by other characteristics including health, gender, and life-style. As a result, the proposed effort will use Generative Adversarial Networks to address these critical concerns (GANs). Generative Adversarial Networks (GAN’s) is made up of a generator and a discriminator network. The generator model generates images that a discriminator model analyses to determine if they are real or fake. This paper provides a Temporal Face Feature Progressive framework with Cycle GAN, which maintains the initial appearance and identity in the elderly aspect of their facial structure. To address aging concerns, our goal is to transform an initial age category image into a targeted age with age progression. We show that our temporal face features progressive cycle GAN learns and transfers facial traits from the source group to the targeted group by training various images. The IMDB-WIKI Face dataset has been used to obtain the results for the same.
Medical diagnosis of COVID-19 using blood tests and machine learning
Authors: Chadaga Krishnaraj , Prabhu Srikanth , Vivekananda Bhat K , Umakanth Shashikiran , Sampathila Niranjana
Published: January 2022

Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2), colloquially known as Coronavirus surfaced in late 2019 and is an extremely dangerous disease. RT-PCR (Reverse transcription Polymerase Chain Reaction) tests are extensively used in COVID-19 diagnosis. However, they are prone to a lot of false negatives and erroneous results. Hence, alternate methods are being researched and discovered for the detection of this infectious disease. We diagnose and forecast COVID-19 with the help of routine blood tests and Artificial Intelligence in this paper. The COVID-19 patient dataset was obtained from Israelita Albert Einstein Hospital, Brazil. Logistic regression, random forest, k nearest neighbours and Xgboost were the classifiers used for prediction. Since the dataset was extremely unbalanced, a technique called SMOTE was used to perform oversampling. Random forest obtained optimal results with an accuracy of 92%. The most important parameters according to the study were leukocytes, eosinophils, platelets and monocytes. This preliminary COVID-19 detection can be utilised in conjunction with RT-PCR testing to improve sensitivity, as well as in further pandemic outbreaks.
Drone to Obstacle Distance Estimation Using YOLO V3 Network and Mathematical Principles
Authors: Aswini N , Uma S V , Akhilesh V
Published: January 2022

Now a days, drones are very commonly used in various real time applications. Moving towards autonomy, these drones rely on obstacle detection sensors and various collision avoidance algorithms programmed into it. Development of fully autonomous drones provide the fundamental benefits of being able to operate in hazardous environments without a human pilot. Among the various sensors, monocular cameras provide a rich source of information and are one of the main sensing mechanisms in low flying drones. These drones can be used for rescue and search operations, traffic monitoring, infrastructure, and pipeline inspection, and in construction sites. In this paper, we propose an onboard obstacle detection model using deep learning techniques, combined with a mathematical approach to calculate the distance between the detected obstacle and the drone. This when implemented does not need any additional sensor or Global Positioning Systems (GPS) other than the vision sensor.
Area and Energy Efficient QCA Based Compact Serial Concatenated Convolutional Code Encoder
Authors: Premananda B.S. , Dhanush T.N. , Parashar Vaishnavi S.
Published: January 2022

Quantum-dot Cellular Automata (QCA) is a transistor-less technology known for its low power consumption and higher clock rate. Serial Concatenated Convolutional Coding (SCCC) encoder is a class of forward error correction. This paper picturizes the implementation of the outer encoder as a (7, 4, 1) Bose Chaudhary Hocquenghem encoder that serves the purpose of burst error correction, a pseudo-random inter-leaver used for permuting of systematic code words and finally the inner encoder which is used for the correction of random errors in QCA. Two different architectures of the SCCC encoder have been proposed and discussed in this study. In the proposed two architectures, the first based on external clock signals whereas the second based on internal clock generation. The sub-blocks outer encoder, pseudo-random inter-leaver and inner encoder of the SCCC encoder are optimized, implemented and simulated using QCADesigner and then integrated to design a compact SCCC encoder. The energy dissipation is computed using QCADesigner-E. The proposed SCCC encoder reduced the total area by 46% and energy dissipation by 50% when compared to the reference SCCC encoder. The proposed encoders are more efficient in terms of cell count, energy dissipation and area occupancy respectively.
Simulation study of droplet formation in inkjet printing using ANSYS FLUENT
Authors: Thakur Neha , Murthy Hari
Published: January 2022

Flow simulations of jetting of inkjet drops are presented for water and ethylene glycol. In the inkjet printing process, droplet jetting behaviour is the deciding parameter for print quality. The multiphase volume of fluid (VOF) method is used because the interaction between two phases (air and liquid) is involved in the drop formation process. The commercial inkjet printer has a nozzle diameter of ∼73.2μm. In this work, a simulation model of inkjet printer nozzles with different diameters 40μm, 60μm, and 80μm are developed using ANSYS FLUENT software. It is observed that when water is taken as solvent then the stable droplets are generated at 60μm nozzle diameter till 9μs because of its low viscosity. For higher diameter, the stamen formation is observed. Ethylene glycol stable droplets are achieved at 80μm nozzle diameter till 9μs because of their high viscosity (∼10 times that of water). Along with the droplet formation, the sustainability of the droplet in the air before reaching the substrate is also important. The simulation model is an inexpensive, fast, and flexible alternative to study the ink characteristics of the real-world system without wasting resources.
Crop prediction using machine learning
Authors: Shripathi Rao Madhuri , Singh Arushi , Subba Reddy N.V. , Acharya Dinesh U
Published: January 2022

For most developing countries, agriculture is their primary source of revenue. Modern agriculture is a constantly growing approach for agricultural advances and farming techniques. It becomes challenging for the farmers to satisfy our planet’s evolving requirements and the expectations of merchants, customers, etc. Some of the challenges the farmers face are-(i) Dealing with climatic changes because of soil erosion and industry emissions (ii) Nutrient deficiency in the soil, caused by a shortage of crucial minerals such as potassium, nitrogen, and phosphorus can result in reduced crop growth. (iii) Farmers make a mistake by cultivating the same crops year after year without experimenting with different varieties. They add fertilizers randomly without understanding the inferior quality or quantity. The paper aims to discover the best model for crop prediction, which can help farmers decide the type of crop to grow based on the climatic conditions and nutrients present in the soil. This paper compares popular algorithms such as K-Nearest Neighbor (KNN), Decision Tree, and Random Forest Classifier using two different criterions Gini and Entropy. Results reveal that Random Forest gives the highest accuracy among the three.
Word Sense Disambiguation Models Emerging Trends: A Comparative Analysis
Authors: Tyagi Nemika , Chakraborty Sudeshna , Jyotsna  , Kumar Aditya , Katasohire Romeo Nzanzu
Published: January 2022

Word Sense Disambiguation (WSD) arises due to the presence of ambiguity in the text during the semantic analysis of natural languages. It is a major unsolved problem in the area of Natural Language Processing (NLP) and its applications. This paper explores and reviews WSD algorithms that have contributed to, or created state-of-art solutions in recent years. Moreover, this paper also aims to analyze the recent technological trends in the domain of WSD which can give us leverage to identify the possible future trajectory of the search for better WSD solutions.
Compressive Sensing Magnetic Resonance Image Reconstruction and Denoising using Convolutional Neural Network
Authors: Singh Ram , Kaur Lakhwinder
Published: January 2022

Restoration of high-quality brain Magnetic Resonance Image (MRI) from the sparse under-sampled complex k-space signal is a widely studied ill-posed inverse transform problem. A deep learning-based data-adaptive and data-driven convolutional technique has been proposed for high-quality MRI recovery from its under-sampled complex domain k-space signal. The uniform subsampling process is very slow in phase-encoding to generate high-resolution images. The longer scan times degrade the perceptual image quality. Various factors contribute to image degradation during data acquisition such as the inception of body motion artifacts, the thermal energy effects of the body, and random noise artifacts due to voltage fluctuations. Keeping in view the patient’s critical condition and comfort, longer scan times are not preferred in practice. To reduce the image acquisition time, noise levels, and motion artifacts in the MR images, Compressive Sensing (CS) provides an accelerated way to reconstructs the high-quality MR image from very limited signal measurements acquired much below the Nyquist rate. However, such data acquisition strategies require advanced computer algorithms for the reconstruction of high-quality MRI from the undersampled MRI data. An improved CNN-based MRI reconstructed algorithm has been presented in this paper which shows better performance to reconstruct high-quality MRI than similar other MR image reconstruction algorithms. The performance of the proposed algorithm is measured by image quality checking tools such as normalized-MSE, PSNR, and SSIM.