bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Analysis of Arbitration Scheduling Algorithm Based on RR Optimization for Network-on-chips
Authors: Ma Ruofei , Bao Liyong , Ding Hongwei , Guan Zheng
Published: January 2021

The RR arbitration algorithm commonly used in the current Network-on-chips cannot meet the requirements for low power consumption and rapid response under high load conditions, with the continuous development of microelectronics technology. In order to solve this problem, based on the idea of non-competitive transmission and parallel optimization, this paper improves on the RR algorithm to obtain a MAC layer arbitration scheduling algorithm suitable for the Network-on-chips. By optimizing the service and query transfer process in parallel, the algorithm reduces the queue length of information grouping in the system and shortens the query period of the system. The algorithm model is established by using Markov process and probability generating function, mathematically analyze the first-order characteristics of the system, and obtain an accurate solution. The simulation model of the algorithm is established based on the simulation platform to verify the accuracy of the precise solution. After optimization, the system’s average queue length and average cycler have been greatly improved.
Optimization Research and Defect Object Detection of Aeroengine Blade Boss Based on YOLOv4
Authors: Chen Wei , Zhong Xintong , Zhang Jing
Published: January 2021

This paper proposes an object detection algorithm based on YOLOv4 (You Only Look Once) aiming at detecting the defects of the blade boss inside the aeroengine. The algorithm uses transfer learning to load the weights of the pre-trained model trained on the coco public data set. In order to adapt to the characteristics of small targets and complex structures better in the detection of bosses, the size of the bounding boxes is adjusted through the cluster analysis. In the meantime, the original data set is enhanced through the Mosaic method. The experimental results show that the improved YOLOv4 model increased the detection accuracy by 15.85%, the recall rate by 21%, with an average intersection ratio of 0.75, and the detection performance is significantly better than the data applying the SSD object detection algorithm in the same data set.
Optimization and Implementation Performance of Sequence Alignment on the Intel Xeon Phi-based Heterogeneous System
Authors: Chen Shaolong , Luo Zhenzhen , Yang Wei , Wang Wenle
Published: January 2021

The heterogeneous system based on different architectures becomes a convenient solution in the high performance computing research when facing the expanding sequence data in bioinformatics analysis. Intel Xeon Phi-based cluster is one of the most utilized heterogeneous systems in recent years. Without accurate results from sequence alignment, the remaining two steps in the variant analysis, variant calling and variant annotation, cannot achieve the correct consequence. However, most sequence aligners are developed facing the multicore system and cannot take advantage of Intel Xeon Phi-based cluster. This paper explored the implementation modes on the Intel Xeon Phi-based heterogeneous system, including native, offload and symmetric modes. We indicate that native mode cannot take advantage of Intel Xeon Phi-based cluster through the evaluation of scalability of various modes under sequence alignment. Although offload mode owns a promising future, it is not easy to enhance performance without comprehensive coding ability. Finally, the symmetric mode could provide a low complexity solution that supports significant improvements in performance.
The Optimization of the Running Technique using Video Analysis Method
Authors: Dobre A G , Gheorghe C
Published: January 2021

Systematic and continuous monitoring of athletic performance for the purpose of developing incrementally adaptive optimized training solutions is often presented as the future of more efficient training systems. This is a shared view in the specialty literature, with authors such as Lyle J (2005, p. 21) stating that “operational training implies the existence of a continuous monitoring process, not only within a competition but also within the training and preparation”. The periodic analysis of key performance parameters with a great effect on performance during a sports contest is a process based on a coherent, self-adaptive and continuously developing system, being the result of a a systemic analysis mechanism that focuses on the analytical evaluation, data collection and analytics, interpreting, and reporting the information obtained as a result of the research. Our approach is to apply and expand on the video analysis method by focusing on certain key questions: how much, how well, how precise but with what costs, with what effort, with what efficiency. Eliminating the “traditional” methods prompt the conclusions that using advanced mechatronic devices render us capable continuous monitoring, recording, and developing comparison solutions that enable concrete interventions on improving the technical execution of various athletic events and more.
Cardiovascular Diseases Prediction using various Machine Learning Techniques
Authors: Aradhana S , Jankisharan P , Virendra SK , Ashish M
Published: January 2021

Prediction of cardiovascular diseases is one of the crucial aspects which every healthcare organization has to do with. Prediction of cardiovascular disease well in time may save the life of patients. In this paper, we applied various machine learning techniques for cardiovascular disease or heart disease prediction. In the urge to provide an efficient technique for the prediction of cardiovascular diseases, we have used UCI heart disease data. This data set is dedicated to classification problems related to cardiovascular disease patients. To predict this disease various machine learning techniques like KNN, Logistic Regression, Random Forest, Decision Tree, and naive Bayes have been tested on Data Set. It has been found from the conducted experiments that the results obtained by the Gaussian Naïve Bayes have given superior results compared to other techniques.
Preeminent Development Boards to Design Sustainable Integrated Model of a Smart Healthcare System under IoT
Authors: Dalal Priya , Aggarwal Gaurav , Tejasvee Sanjay
Published: January 2021

Conventional healthcare systems were just passive with the approach of smart healthcare services. Smart healthcare has been tended to consequently decrease the death and casualty rates the world over. The gratefulness lies in the court of the Internet and ICTs. IoT (Internet of Things) helps healthcare administrations by providing dynamic, inescapable, and intellectual services. Due to deal with medical issues and various unexpected diseases, a suitable, incorporated, smart, well-groomed, modern, and sustainable healthcare monitoring with wellness service deliverance arrangement is required under the IoT platform. A variety of development-boards have been created and are currently being utilized in the field of healthcare. These IoT based development boards reduce endeavors, cost, and time in a feasible way. Patients care better in IoT based integrated healthcare services system. Several companies have made-up these development-boards and these are being used by several organizations to fulfill the requirement of healthcare services for many purposes. This review paper provides an insight on aspects, dimensions, a prototype of sustainable integrated smart healthcare architecture with explicit clarification of significant development boards to design and implement a sustainable smart healthcare system that empowers strong connectivity among numerous devices and human beings in the recent digital era.
A comparative study of new and existing segmentation techniques
Authors: Sarma Rituparna , Gupta Yogesh Kumar
Published: January 2021

Image segmentation is the most crucial part in image processing techniques. Numerous segmentation techniques are used to segment digital images into smaller regions called segments, consisting of sets of pixels in order to analyze important information from the images. Segmentation simplifies the process of information retrieval from the region of interest (ROI).It helps in converting the digital image into more relevant information and easier to analyze. This paper presents a comparative analysis of existing segmentation techniques and its modification to form new segmentation techniques to overcome some of the drawbacks of the existing image segmentation approaches.
Machine Learning in liver disease diagnosis: Current progress and future opportunities
Authors: Tanwar Neha , Rahman Khandakar Faridar
Published: January 2021

There has been a rapid growth in the use of automatic decision-making systems and tools in the medical domain. By using the concepts of big data, deep learning, and machine learning, these systems extract useful information from large medical datasets and help physicians in making accurate and timely decisions regarding predictions and diagnosis of diseases. In this regard, this study provides an extensive review of the progress of applying Artificial Intelligence in forecasting and detecting liver diseases and then summarizes related limitations of the studies followed by future research.
Hurricane Damage Detection using Machine Learning and Deep Learning Techniques: A Review
Authors: Kaur Swapandeep , Gupta Sheifali , Singh Swati
Published: January 2021

Hurricane is one of the most disastrous natural disasters causing immense harm to the ecosystem and economic system worldwide. It is also known as a tropical cyclone. Heavy rainfall and high winds accompanying hurricane inflict damage to property as well as loss of human life. Hence, appropriate steps need to be taken to mitigate the damage caused by the disaster. Recently, social media platforms are used that help in providing immediate relief to the people affected by the disaster. Since, the difficulty arises in analysis of high volume data of social media, satellite imagery is also being used for damage detection due to its ability to cover large spatial and temporal areas. But manual damage detection is error prone. Therefore, machine learning and deep learning which automated methods are used for detection of damage. This paper includes the use of machine learning and deep learning for detection of damage caused by natural disasters with a special focus on hurricane damage.
Blockchain and IoT based Vehicle Tracking System for Industry 4.0 Applications
Authors: Chauhan Harsha , Kumar Devashish , Gupta Deepali , Gupta Sheifali , Verma Vishal
Published: January 2021

Vehicle automation is one of the main applications of industry 4.0 especially for tourism companies who provide their vehicles to migrants for traveling purposes. It is difficult to maintain trust among the travel agency and the customers. Although there are many existing solutions in the research that addresses the trust issues, but most of the solutions are based on centralized architecture such as cloud computing where the data is prone to various security threats. Motivated by the aforementioned discussion, the authors have proposed a vehicle tracking system based on the integration of blockchain and IoT in this paper. The proposed system will increase the trust among the entities by providing them transparency in tracking details of the vehicle. As the trip details are immutable and decentralized in nature, so, blockchain is used to store the details. Also, the system will generate the trip summary that contains the route detail, the number of kilometres travelled and the total cost of the trip. Tools such as Ethereum, Remix IDE, MetaMask, and RinkeyBy have been used to measure the performance of the system.
EMT: Ensemble Meta-Based Tree Model for Predicting Student Performance in Academics
Authors: Kumar Mukesh , Mehta Gaurav , Nayar Nandini , Sharma Abha
Published: January 2021

Data Mining is a field in which hidden information is extracted from a large database by using some algorithms implementation. These algorithms are further divided into some categories like classification, clustering, association rule mining etc according to information we want to extract. Data mining is a field which is widely spread over different areas like telecommunication, marketing, operation, hospitals, hotel industry, education etc. Predicting the academic’s performance and progress of the students has revealed the attention of the young researchers. To facilitate the task of building an academic prediction model, historical student academic dataset is used. In this paper, the contributions are exhibited in two different folds. In the first fold, the main aim is to build the prediction model by different families of the Machine Learning Techniques on the selected dataset for consideration. In the second fold, implementations of different ensemble meta-based model are presented by combining with different classification algorithms of Machine Learning Techniques. Different ensemble meta-based model taken into consideration for implementation are Bagging, AdaBoostM1, RandomSubSpace. The implementation results demonstrate that the ensemble meta-based technique (AdaBoostM1) gained a superior accuracy performance with MultilayerPerceptron Machine Learning technique reaching up to 80.33%.
A Review Paper on Breast Cancer Detection Using Deep Learning
Authors: Priyanka Kumar Sanjeev
Published: January 2021

Breast Cancer is most popular and growing disease in the world. Breast Cancer is mostly found in the women. Early detection is a way to control the breast cancer. There are many cases that are handled by the early detection and decrease the death rate. Many research works have been done on the breast cancer. The Most common technique that is used in research is machine learning. There are many previous researches that conducted through the machine learning. Machine learning algorithms like decision tree, KNN, SVM, naïve bays etc. gives the better performance in their own field. But now days, a new developed technique is used to classify the breast cancer. The new developed technique is deep learning. Deep learning is used to overcome the drawbacks of machine learning. A deep learning technique that is mostly used in data science is Convolution neural network, Recurrent neural network, deep belief network etc. deep learning algorithms gives the better results as compared to machine learning. It extracts the best features of the images. In our research, CNN is used to classify the images. Basically our research is based on the images and CNN is most popular technique to classify the images. In present paper, reviews of all authors are conducted.
The Impact of COVID-19 Epidemic on Indian Economy Unleashed By Machine Learning
Authors: Garg Kamal Deep , Gupta Manik , Kumar Munish
Published: January 2021

The outbreak of the Corona Virus (COVID-19) that has begun in December 2019 drastically affected the world. Endemic Coronavirus (COVID-19) is rapidly growing across the globe. SARS-CoV-2 is the virus name that causes a highly contagious and deadly disease COVID-19. It also entered India by the end of January 2020 and has significantly influenced India. More than two million people worldwide have been confirmed to have been contaminated with this virus as of the date (29 July 2020), and more than 7, 24,000 have died of this disease. The governments of most countries, including India, have already taken several measures to reduce the spread of COVID-19, such as lockdown, social distancing, closure of shopping malls, gyms, schools, universities, religious gatherings, etc. This lockdown has affected every Indian sector, such as the Economy, Retail Sector, Tourism Industry, etc. This paper aims to explore to what extent a 2020 epidemic like Covid-19 had impacted the Indian economy using a machine learning approach. The statistical data from esteemed and trustworthy information sources were gathered to realize the impact of the Corona Virus on the Indian economy. Based on this trusted data, analysis has been performed using the various regression models.
A Study on Tree Rings: Dendrochronology using Image Processing
Authors: Divya K , Kaur Sukhvir
Published: January 2021

This paper outlines an introduction to dendrochronology. The tree rings are being identified through image processing and statistical simulations. The study of the tree rings is known as dendrochronology but the techniques do need to be modified for better performance. Image analyses convert the tree ring into digital data using imaging tools. This method involves the scaling, piling, width calculation. Technology is required to evaluate the factors of different tree ring pattern. In this review paper, literature survey has been provided which deals with the contribution of different researchers, which methodologies they preferred and what were their limitations. And two attributes are being calculated named MSE and PSNR, as these obtainable values indicates to work further with the enhanced image. Also, researcher can get idea what all the attributes are important to implement this technique.
A novel approach for Hyper Spectral Images using Transfer Learning
Authors: Bharti Rohit , Saini Dipen , Malik Rahul
Published: January 2021

The spectral analysis and spatial analysis of high dimensional images are very important and in this paper we tried to cover some aspects that how this problem can be handled and proposed a way through which we can overcome the problem of the time constraint and using some deep learning novel approach like transfer learning for getting the best results while performing the actual computations and the results which we obtained. The dataset used is EuroSAT in which by using a VGG network, the accuracy is achieved 95 per cent and the validation accuracy achieved is 92 per cent. Also, the Kappa score which we got for this observation is 0.95. The tool used for the implementation purpose is TensorFlow with GPU which is also discussed in the paper.
Dynamic Combined Treatment of Curved Surfaces by Two-Component Processing Media
Authors: Kuzovkin A V , Boldyrev A I , Boldyrev A A , Padurets A A
Published: January 2021

This article is devoted to the tool usage as conductive filler with application of electric field for dynamic dimensional finishing combined treatment of hard-to-reach surfaces with high degree of curvature. The area of its technological use is shown in relation to aircraft engineering, rocket and space technology component parts and oil and gas industry. The common criterion for method applicability is that such parts have sections with variable curvature and limited tool access to the treatment area. The authors show that in dynamic combined process control of the required technological and operational indicators is possible due to the combination of current-carrying granules kinetic energy and surface anodic dissolution in treatment area. Methods for remote control of dimensional processing with the creation of required reinforced surface layer due to the dynamic mechanical action of solid granules and surface roughness due to anodic dissolution of work surface are presented. The resulting effect is increase in service life and durability in critical assemblies of aerospace equipment and oil and gas apparatus.
Influence of the structure of coolant flows on the temperature profile by phases in a water heating dryer
Authors: Safarov J E , Sultanova Sh A , Dadayev G T , Zulpanov Sh U
Published: January 2021

This research of the profiles of the temperature field of the process of convective drying of plant raw materials. Mathematical modeling of the temperature field on the basis of the three-phase flow structure was carried out. In a wide range of variation of design and operating parameters (from 50 to 150%) their nominal values are identified. A qualitatively new picture of the temperature field was found, which is expressed in the fact that, depending on the contact conditions of the gas and solid phases and the relative air flow, the temperature profile on the pallets can have both positive and negative slopes. The sensitivity of this relationship, formalized in the form of axonometric graphs and the corresponding families of isolines on the plane of variable factors, is shown. Criteria for non-uniformity of temperature profiles across pallets (dispersion of material temperature and angle of inclination of the approximating straight line with fixed values of the average temperature of the substance) are proposed. The procedure for solving the optimization problem on the conditions of the minimum criterion for the unevenness of the material profile is justified when the average temperature of the material specified in accordance with the conditions of the process schedule is restricted as equality. For the conditions of solving an optimization problem by the criterion of minimizing the square of the slope, minimization of the material temperature by the dispersion gives minor deviations:gotimal=0.3833, kmgoptimal=0.0124. For r=0 gives optimal, gotimal=1.2857, kmgoptimal=0.032, and for r=0.725, we get gotimal=0.3832, kmg=0.0126, which is in good agreement with the nomogram.
Synergetic synthesis of aggregated discrete regulators for induction motors
Authors: Veselov G , Kondratiev I , Semenov V
Published: January 2021

The paper presents the method of synergetic synthesis of a nonlinear discrete control system for induction motors. The proposed approach is based on using the methods of the synergetic control theory and nonlinear mathematical models of induction motors. This approach allows to create nonlinear closed-loop piecewise-continuous control systems which guarantee the asymptotic stability of the controlled induction motors, accomplishment of the determined technological and electromagnetic invariants and selective invariance to the unknown external disturbances acting on the system. The invariance of the designed systems is ensured due to the usage of a dynamic discrete regulator which increases the astatism of the synthesized system.
Vibration dynamics and cutting process temperature at various stages of forming the wear of the cutting wedge
Authors: Lapshin V P , Turkin I A
Published: January 2021

On today, there is no single and consistent mathematical model describing the complex connectivity of the metal cutting process. Therefore, the article proposes new approach based on the formation of feedback connecting subsystems describing the power, thermal and vibration reactions from the cutting process. The purpose of the work: By forming a consistent model of connections between subsystems describing the power, thermal and vibration reactions from the cutting process to the shaping movements of the tool, you can obtain a description of the mechanism of self-organization of the cutting process in the process of evolutionary changes of the tool. The resulting mechanism is needed to search for some mode of operation of the cutting system, in which further wear of the cutting wedge, cutting force, temperature in the cutting zone and vibration of the tool can be stabilized. Research methods: For processing and analysis of the obtained data, a Matlab package of mathematical programs was used, in which a subprogram was developed that allows a series of numerical experiments. The main conclusion on the work is the provision put forward by us on the self-organization of the cutting system, through the process of evolution of the instrument.
Verification of thermal models in the design of personal protective equipment against cold
Authors: Cherunova I V , Stenkina M P , Kornev N V
Published: January 2021

In the article research results are presented, which aim to verification of thermal models in the design of personal protective equipment against cold. Under the effect of wind, movement, and pressure of the human being himself on the clothing, the design thermal resistance of the clothing decreases and does not provide the stable human comfort. To eliminate such risks, special heated garments are being developed, which are fitted with electric batteries. The basis for such a development is the mathematical model of the system “Human-Clothes-Environment”, which allows to establish the main parameters of the heating intensity of each individual section of the clothing, taking into account the overall functioning of the system. Such a model has been developed. The problems of verification of thermal models for designing if the clothing are associated with the assessment of experimental data on the parameters of the system under study. A structure for the formation of a method for experimental verification of the models of thermal protective clothing has been developed. Design of experimental protective clothing against cold with heating based on a mathematical model has been developed. The ratio of feelings of thermal comfort and temperature under heated clothing of small thickness under wind load, cold and lack of physical activity has been installed.
Kids security on social networks by face blur technique
Authors: Mladenovic V , Djukanovic S , Stefanovic N , Kar A , Jovanovic M , Makov S
Published: January 2021

This article deals with increasing security and children protection under the age of 16 (underage) on social networks with photo content such as Facebook, Instagram, Twitter, and similar. Particularly, the emphasis is placed on the official sites of public institutions on Facebook, such as kindergartens, primary and secondary schools, and all institutions dealing with children. One of the source key issues is the ability to track these public pages by malicious visitors. The main point is the developed algorithm that analyzes any photo, recognizes kid(s), and blurs it during the upload photo onto the page of the social network. The complete procedure for processing is shown and performed testing, verification, and validation.
Modeling of carrot thin layer convective drying process
Authors: Petković M , Filipović V , Filipović I , Lukyanov A , Studennikova S , Mardasova E A
Published: January 2021

The effects of different dehydration temperature (35, 50 and 70 °C) and carrot slice thickness (3, 6, and 9 mm), at the constant (hot) air speed and mass load, on moisture ratio (MR) and drying ratio (DR) in thin layer convective drying process were investigated. The mathematical models Modified Page, Logarithmic, and Two-term models (forMR), and Gauss Modified model (forDR) were the most appropriate. Based on the obtained results for theR2andRSME, the optimal parameters for thin layer drying carrot slices in laboratory dehydrator are dehydration temperature 70 °C, and carrot slice thickness of 3 mm, with the shortest dehydration time of 4.5 hours and the maximum DR of 106.7 g/h.
Compositions Based on Expansion Additive for the Repair of Reinforced Concrete Structures
Authors: Shlyakhova E A , Serebryanaya I A , Egorochkina I O , Matrosov A A , Soloviev A N
Published: January 2021

In this paper the issues of creation of effective composite materials for performance of repair and restoration works of operated reinforced concrete structures are considered. The necessity of introducing repair compositions is justified. Theoretical foundations of concrete mixtures preparation process are given. Original repair compositions developed by the authors with an expansion additive based on Portland cement, as well as substandard fine aggregates with increased physical and mechanical properties of concrete are proposed
The design parameters optimization of the oscillating ploughshare mechanism of the root harvester
Authors: Vislousova I N , Matrosov A A , Kotov V V , Lesnyak O N , Soloviev A N
Published: January 2021

The problem of optimizing the design parameters of the oscillating ploughshare drive is solved. The purpose of optimization is to ensure the technological process of digging up the soil and harvesting root crops while expanding the speed range of the harvesting machine. The optimization criterion is the torque amplitude on the drive shaft determined from the dynamic drive model. The value of the optimization criterion depends on the parameters of agricultural background and kinematics of the drive mechanism. The load levels and reliability indicators of the optimized and original design of the digging mechanism are investigated.
Multifractal parameterization of metal structure dynamic evolution under high-speed surface heat treatment
Authors: Brover A V , Brover G I , Topolskaya I A
Published: January 2021

The paper presents the results of experimental studies of the structural state peculiarities and the properties of steel surface layers after laser treatment. The study is devoted to the examination of relationship between the processes of self-organization and adaptability of structures emerging from laser radiation, and material properties using key synergistic basics and fractal theory.
Mechanical properties and failure mechanisms of 3D-printed PLA scaffolds: A preliminary study
Authors: Mitrin B I , Chapek S V , Sadyrin E V , Swain M V
Published: January 2021

Polylactic acid (PLA) porous composite scaffolds with three different infill patterns were subjected to compression testing. The composites were fabricated by 3D printing based on Fused Filament Fabrication (FFF) technology. Stress-strain curves were obtained which allowed to identify Young’s modulus, yield point and residual strain of samples. 3D tomography images were taken before and after deformation. Comparison between images corresponding to a particular sample were used to identify deformation and failure mechanisms.
Organization of unmanned aerial vehicles movement as a group
Authors: Heiss E A
Published: January 2021

This paper describes the organization of movement of unmanned aerial vehicles in a swarm based on modification of the potential field method. Collision prevention is carried out by the potential field method, and relatively uniform distribution of agents in the free space is provided by the control system component, which uses the change of the repulsion field radius depending on the number of neighbors and the distance to them. Averaging the value with neighbors is used to reach consensus on the value of the repulsion field radius. In addition, the results of modeling an algorithm demonstrating satisfactory work and low requirements to the speed of information exchange network are given.
The formalization of the characteristics of automatic workplace (AWP) with the use of linguistic variables (LV)
Authors: Kramarov S O , Khramov V V , Belyaev A V , Grebenyuk E V
Published: January 2021

The article suggests using a new approach to formalize requirements and describe them in the form of a fuzzy area in the settings space. To do this, an alphabet is made that contains the values of linguistic variables. Using this method, it is possible to quantify the extent to which the proposed system is part of a variety of effective ARM’s. In this article, the authors used a new solution to apply elements of artificial intelligence and elements of fuzzy logic in the creation of ARM. Using linguistic variables in the article it is possible to determine the degree of belonging of the research system to the effectiveness of this ARM. The method of fuzzy aggregation using linguistic variables (LV) is used in this paper when forming a vector of requirements for an automatic workplace (AWP), as well as its elements, including cognitive analysis methods, a technical description of existing AWPs, their algorithmic and software tools, as well as to determine the degree of compliance of AWP variants with the necessary technical requirements. In this article, we have applied a new approach to formalizing the requirements for determining the effectiveness of ARM use using artificial intelligence and fuzzy logic elements. To do this, we propose to make a special alphabet that contains the values of linguistic variables. Using this method, it is possible to quantify the extent of belonging to many effective ARM’s.
Wave hydrodynamics discrete models construction and research
Authors: Sukhinov A I , Chistyakov A E , Protsenko E A , Sidoryakina V V , Protsenko S V
Published: January 2021

Analysis of the existing methods and tools for predictive modeling of hydrodynamics suggests the need to develop discrete analogs of the constructed models that have the properties of conservatism, stability and convergence, as well as algorithms for their solution, providing an increase in the accuracy of predictive modeling. In this work, a continuous three-dimensional mathematical model of the hydrodynamics of shallow water bodies is considered, and its discretization is carried out. To solve the problem of hydrodynamics, the method of correction to pressure in the case of variable density was used. When constructing discrete mathematical models of hydrodynamics, the filling of the control cells was taken into account, which made it possible to increase the real accuracy of the solution in the case of a complex geometry of the investigated area by improving the approximation of the boundary. The preservation of the flow at the discrete level of the developed hydrodynamic model, as well as the absence of non-conservative dissipative terms obtained as a result of the discretization of the system of equations, is proved.
Dependent twin-engine hydraulic drive of the drilling rig with a mechano-hydraulic variable pump control circuit
Authors: Rakulenko S V , Grishchenko V I , Poleshkin M S , Sirotenko A N
Published: January 2021

The work is devoted to the study of an adaptive hydraulic drive for tool feed of a mobile drilling rig. The analysis of the ways of regulation of the considered hydraulic systems is carried out, the criteria and parameters of their functioning are determined. As a result of the analysis, an original circuit design of an adaptive hydraulic drive was applied, where the tool is fed using an adjustable volumetric hydraulic motor with a hydraulic control loop, taking into account the changing load on the tool during drilling. By a computational experiment in the Matlab Simulink program, the parameters of the control loop devices are determined: a hydromechanical sensor and a hydraulic valve, on the basis of which the experimental setup is implemented. The performed multifactorial experiment made it possible to identify the processes in the original hydraulic circuit for controlling the hydraulic motor under various modes of tool loading. The results made it possible to determine the rational ranges of functioning of the hydromechanical system for a typical working cycle. The use of the developed research methods and their results makes it possible to reduce the time and money spent in the design of adaptive hydraulic systems of mobile technological machines, in the creation of prototypes and in the commissioning.
Probability of thermal runaway in high-capacity nickel-cadmium batteries with pocket electrodes
Authors: Yazvinskaya N N , Galushkin D N , Isaev I R
Published: January 2021

An experimental investigation was given to the occurrence probability of the thermal runaway in the high-capacity nickel-cadmium batteries with the pocket electrodes. 800 charge-discharge cycles were performed using a hard charge mode at a voltage of 2.2 V and a temperature of 40 ° C. It was shown that in the batteries of this kind, the thermal runaway is either impossible or its probability is much lower than that in the batteries with the sintered electrodes. The explanation was given to this phenomenon based on the previously proposed thermal runaway mechanism based on the exothermic reaction of the thermal runaway.
Energy saving based on minimization of water consumption in housing and communal services machines
Authors: Larina L V , Ruslyakov D V , Tikhonova O B
Published: January 2021

The paper considers the feasibility of using a jet aeration system for water and energy saving in the operation of sweepers, irrigation and washing machines, channel washing machines. On the basis of physical models of air-water jets are made to the calculation of process parameters of aeration of the working fluid, to establish the possibility of reducing the consumption of water supplied to the washing chamber sewer machine 15%, when the pressure of the water inlet to the water system is 0.17 ATM. To establish the limits for regulating the parameters of the aeration process of liquid jets, a complete factor experiment was conducted for 6 significant factors. The resulting mathematical model of the water jet aeration process is adequate to the process under study. The limits of regulation of the process in question are determined: compressed air pressure, Q=0.3 - 0.35 MPa; nozzle size z=5-8 mm; angle of attack of the abrasive jet α=55-60°; distance to the treated surface L=120-180 mm; appropriate reduction of the diameter of the water jet during aeration -15÷ 50%. It is shown that the water saving in the washing chamber on the example of the KO-502B2 channel washing machine based on the ZIL-433362 chassis when using the aeration system will be, and the pump power will decrease by 1709 watts.

Analysis of the main trends in the development of municipal equipment has shown that the provision of resource-saving technologies for cleaning, maintenance of urban areas and pipelines is one of the priorities in the development of housing and utilities.
RETRACTED: The composition of the hydraulic drive on the example of the power head of high-speed equipment
Authors: Kobzev K , Rybak A , Zolotuhina I , Zanina I , Il’ev A , Kobzeva N
Published: January 2021

The article discusses the control system of a hydraulic power source of constant pressure, which is a pump-storage power source, equipped with the original design of the automatic unloading of the hydraulic pump, which provides relay switching of its operation mode. A mathematical model is proposed, obtained using a modeling technique based on the application of the theory of volumetric rigidity of hydraulic systems and their elements.

The main property of a power source with an automatic unloading device of the proposed design, confirmed as a result of a numerical experiment, is that the automatic unloading device provides a clear relay switching of the pump operation mode from unloading to operating mode and vice versa. The revealed properties make it very promising to use a pump-accumulator power source in the hydraulic systems of mobile machines and technological equipment.
RETRACTED: Dynamic change in the assessment of labor protection conditions at technological enterprises
Authors: Zolotuhina I , Kokun’ko I , Pashkova O , Kobzeva N , Kobzev K
Published: January 2021

Labor protection is a system of ensuring the safety of life and health of workers in the process of work, including legal, socio-economic, sanitary and hygienic, psychophysical, treatment and prophylactic, rehabilitation and other measures. The functions of labor protection are the study of sanitation and occupational hygiene, the implementation of measures to reduce the influence of harmful factors on the body of workers in the process of work. The main method of labor protection is the use of safety measures. At the same time, two main tasks are solved: the creation of machines and tools, when working with which the danger to humans is excluded, and the development of special protective equipment that ensures human safety in the labor process, as well as training workers in safe working practices and the use of protective equipment, conditions are created for safe work.

The main goal of improving working conditions is to achieve a social effect, i.e. ensuring labor safety, preserving the life and health of workers, reducing the number of accidents and diseases at work.

Improving working conditions also yields economic results: an increase in profits (due to an increase in labor productivity); reduction of costs associated with compensation for work with harmful and difficult working conditions; reduction of losses associated with injuries, occupational morbidity; decrease in staff turnover, etc. The main document in the normative and technical documentation is the normative act “Occupational safety standards system”.
RETRACTED: A dynamic increase in the impact of noise on the human body, in particular, on cardiovascular diseases
Authors: Lekhman M , Shubitidze M , Litvinov A , Zanina I , Pashkova O , Kobzeva N
Published: January 2021

Some manufacturing processes are accompanied by significant noise and vibration. Sources of intense noise and vibration are machines and mechanisms with unbalanced rotating masses, as well as technological installations and apparatuses in which the movement of gases and liquids occurs at high speeds and has a pulsating character. The modern development of technology, equipping enterprises with powerful and fast-moving machines and mechanisms leads to the fact that people are constantly exposed to noise of increasing intensity. Increasing noise and vibration in the workplace has a harmful effect on the human body. As a result of prolonged exposure to noise, the normal activity of the cardiovascular and nervous systems, digestive and hematopoietic organs is disturbed, and professional hearing loss develops, the progression of which can lead to complete hearing loss. Among industrial hazards, noise and vibration occupy one of the leading places among production hazards. The harmful effects of increased noise levels on the human body are well khown, therefore, the relevance of this problem is obvious.
Augmented reality in ophthalmology: development of a software interface for interaction with a virtual reality headset
Authors: Mikhalchuk V D , Epikhin A N
Published: January 2021

This work is devoted to the application of augmented reality in the field of ophthalmology. The paper presents information on image formation and discusses modern technologies used in diagnostics. For a visual demonstration of the possibilities of augmented reality, an application was implemented that allows a person to interact with a virtual reality headset and study the anatomy of the human eye using 3D models. The goal of the project is to develop a training software tool for human interaction with a virtual reality headset for use in the field of ophthalmology. The object of the research is the processes occurring in information systems during the functioning of augmented reality applications. The subject of the research is the functioning of augmented reality applications in the field of ophthalmology.
General model of hydropneumatic suspension for the grain combine harvester adapter
Authors: Kokhanenko V N , Sirotin P V , Evtushenko S I , Kondratenko A I , Maksimov V P
Published: January 2021

The paper presents the hydropneumatic suspension mathematical and simulation model development results for the grain combine harvester adapter. The urgency of the work in connection with the hydropneumatic suspensions spread and the need to increase the system efficiency for field relief copying has been substantiated. A computational model of a hydropneumatic suspension including hydraulic cylinders and hydropneumatic shock absorbers connected in parallel to them, including chokes and gas springs has been presented. A system of equations for the hydraulic cylinder piston motion, depending on the hydropneumatic suspension parameters and the number of the connected hydropneumatic shock absorbers has been presented. On the assumption basis, a simplified diagram of the adapter hydropneumatic suspension with back pressure and the corresponding equation system for determining the hydraulic cylinder piston movement have been drawn up. The model includes changing the parameters of external influence on the system, as well as the hydropneumatic accumulator presetting parameters. To assess the developed model’s performance, its simulation model, which was integrated into the well-known simulation model of the grain combine harvester movement, has been compiled. The modeling results of the combine movement on the field with real geometric evenness parameters have been presented. Based on the simulation results, an oscillogram of the hydraulic cylinder piston movement has been shown, depending on the hydropneumatic accumulators’ settings. Conclusions and directions for further research in this area have been presented.
Selection the measuring system for registering the metal parts temperature at microarc heating and its thermophysical analysis
Authors: Stepanov M S , Koshliakova I G , Sorochkina O Yu , Atoyan T V
Published: January 2021

Measuring the temperature of metal parts during thermal and thermochemical treatment is necessary for the control of the correctness of the technological process. Currently, new methods of thermochemical processing of parts under high-energy conditions, such as microarc surface alloying, are proposed. Heating is carried out by the action of microarc discharges on the surface of parts immersed in coal powder when an electric current flows. It reduces the processing time from a few hours to a few minutes, but makes it difficult to measure the temperature, because heating occurs in dynamic mode. The aim of the work was to select a measuring system for recording the metal parts’ temperature during microarc heating, and the thermophysical analysis of the heating process. The S-type sensor was selected. The measuring system also includes a digital multimeter and a personal computer. The density of the electric current on the surface of the samples was 0.53 A/cm2 The registered heating curve consists of several stages. At the first stage the heating speed was about 8 °C/s. At the second stage it increases to 16 °C/s, but then decreases to 3.5 °C/s. Then the temperature increases monotonously with an average speed of 9 °C/s. At the fourth stage the sample temperature is stabilized at 1250 °C. The thermophysical process’ model of the heating metal parts under the influence of microarc discharges was proposed. The analysis showed that the calculated data coincide with the experimental data.
Cost Assessment of Deloaded Photovoltaic Systems
Authors: Verma Pankaj , Kaur Tarlochan , Kaur Raminder
Published: January 2021

The maximum power point operation of the photovoltaics (PV) restricts them to participate in the frequency regulation of the connected system. Therefore, it is a common practice to deload the PV systems for generating an active power reserve. However, the deloading causes underrating of these systems, hence additional PV panels are installed to overcome the reserved power. Since the frequency regulations can be achieved by using batteries, hence in this paper, the generation cost of a six bus system is minimized by operating PV generator and batteries in coordination with the synchronous generators. The cost curves obtained by operating PV generator with synchronous generators, and batteries with synchronous generators are compared to justify the deloaded operation of PVs. The cost function minimizations are conducted by using the CVX toolbox in the MATLAB software.
Numerical investigation of dynamic behaviour of single and two hinged articulated towers in random sea
Authors: Sreelakshmi G , Somasundaran T P
Published: January 2021

The present paper deals with comparative studies on hydrodynamic behaviour of Single and two hinged articulated towers in Random sea. The dynamic behaviour of towers is investigated under long crested Uni directional random sea and the wave force calculations are performed using Modified Morison equation. A visual based C + + program is developed to evaluate the response of the towers by taking into account non linearities like time variation of submergence, instantaneous tower orientation and hydrodynamic loading. Finally, the equations of dynamic motion are solved using New Mark integration scheme followed by Fast Fourier transform to obtain Power spectral densities. From results, it is observed that presence of intermediate hinges reduced the spectral energy coming on Two hinged articulated tower indicating its significance over Single hinged towers.