bluuebunny/crossref_metadata_2025_split huggingface dataset:
The analysis of Si/Al ratio on CGA decomposition in Indonesian traditional Kreweng pottery coffee roaster to maximize coffee acidity
Authors: Qiram Ikhwanul , Hamidi Nurkholis , Yuliati Lilis , Nugroho Willy Satrio , Wardana I Nyoman Gede 
Published: September 2022

The use of pottery pans lowers the roasting temperature and gives the product a more favorable taste. This study uncovers the role of pottery particle on chlorogenic acid (CGA) decomposition during roasting process. This study aims to design pottery pans and the roasting process that optimize the CGA content and quality of the coffee using Indonesian traditional ceramics from Banyuwangi, East java named Kreweng. The pottery was ground to between 74–1000 µm before activation. The elemental, phase, and morphology characterization performs on the coffee bean. The morphology characteristic of the pottery observed further using digital imaging technique to unravel the pores and boundaries. The impact of the pottery usage for coffee roasting also tested through coffee product pH measurement. The pottery morphology determines coffee product acidity. The smaller the pottery catalyst particle size results in more acid coffee. The pore and grain boundary concentration increases as the particle size decreases. At the same time, the Si/Al ratio was higher at the smaller catalyst particle size with higher porosity, grain boundaries, and absorption. The porosity and defects reveal the negatively charged faces of the pottery crystal edges. The charged faces revealed due to the pottery crystal vibration in response to heat during roasting process. The effectiveness of surface contact is greater due to the distribution of negative charges around the pores that attract OH- side of CGA. This interaction traps hydrogen proton on catalyst conductive surface. As a result, the CGA decomposes into several groups of atoms and molecules including H2 and CO2. The interaction with the catalyst transforms the macronutrient into aliphatic acid. Therefore, roasting media with a higher Si/Al ratio at smaller particle sizes with high micropores will increase the rate of decomposition and the acidity of coffee products.
Developing application techniques of kinematics and simulation model for InMoov robot
Authors: Kenshimov Chingis , Sundetov Talgat , Kunelbayev Murat , Sarzhan Magzhan , Kutubayeva Madina , Amandykuly Arman 
Published: September 2022

In this work, the direct and inverse kinematic analysis of both robot arms are investigated based on the analytical and informational representation. The results of the study will be used to provide the functionality of gesturing by a robot in sign language, both Kazakh and other languages, used in educational systems, especially in children's institutions and societies for deaf people. A simulation model of the movement of the robot's arms in the workspace has been studied and built. The developed model will be further implemented and used as mathematical and information support for the created robot. The developed library contains implementations of forward kinematics and iterative algorithms for inverse kinematics.
The InMoov robot is a platform widely used in research tasks, supported by the MyRobotLab package. A direct kinematic model for the left and right hands of the robot has been studied. Based on the Python programming language, the working space for robot manipulators was calculated, using the matpilotlib library, an iteration method algorithm was developed to find the probable path of robot manipulators in space. A model of a structured artificial neural network (ANN) is proposed, which is used to find a solution to the inverse kinematics of the InMoov robot with six degrees of freedom (4-dof). The applied ANN model is a multilayer perceptron neural network (MLPNN) in which the learning rule of the Adam-a gradient diskend type is applied. To solve this problem, the problem of finding the best ANN configuration was studied. It has been established that a multilayer parseptron neural network gives the minimum mean square error. The regression coefficient analysis, which shows a 95.6 % fit of all communication variables, is acceptable for obtaining the inverse kinematics of the InMoov robot.
Revealing the influence of technological parameters on the process of extraction from walnut shell
Authors: Sultanova Madina , Abdrakhmanov Khamza , Nurysh Aida , Saduakas Aygerim , Akzhanov Nurtore 
Published: September 2022

The object of this study is the influence of technological parameters on the extraction process from walnut shells.
The main practical application of walnut is associated with the use of a kernel placed inside the shell. The kernel isolated after processing is used in confectionery, fat-and-oil, flour milling, pharmaceutical, and other industries. The walnut shell that remains after cleaning is waste and is usually disposed of. Analysis of studies reveals that walnut shells are rich in phenolic acids and related polyphenols, which are essentially a natural antibiotic with numerous healing effects. Along with this, crushed walnut shell is a universal organic, biodegradable, environmentally friendly, and valuable raw material with unique physical characteristics and chemical properties used in various sectors of the economy. Walnut shell is 52.3 % lignin, for comparison ‒ almond shell contains 28.9 %, pine nut – 40 % lignin. Studies show that lignin characterizes the level of strength of the shell, and in its chemical composition is a source of antioxidants. Various methods of extraction of biologically active substances from walnut shells are used. However, the results obtained by different methods have a wide range of data. Optimization of extraction processes has been carried out and its regularity was established. By the method of mathematical modeling, optimal extraction modes were revealed under which the most complete extraction of biologically active substances is observed. Optimal extraction modes have been developed.
Development of probiotic yogurt from small cattle milk
Authors: Ospanov Assan , Velyamov Shukhrat , Makeeva Raushan , Tlevlessova Dinara , Tastanova Raushan 
Published: September 2022

This paper considers the physicochemical parameters of sheep's and goat's milk as raw materials to produce live yogurt. Sheep's milk of 12 breeds (14 samples per breed) and goat's milk of 4 breeds (10 samples per breed) were examined. Milk was selected to produce yogurt from cow's, sheep's, goat's milk and combined mixtures of cow's and sheep's milk in different ratios. The milk was selected for the purpose of producing yogurt with long-term viability of dairy bacteria, thereby obtaining live yogurt without the addition of synthetic preservation agents. The viability of probiotics (Bifidobacterium and Lactobacterium) in the composition of yogurts from cow's, sheep's, goat's milk, and mixtures: cow's and sheep's milk in various ratios, cow's and goat's in similar ratios has been investigated. For consumer preference, organoleptic analyzes are very important, according to the results of which yogurt was selected in a ratio of 3:1 cow's milk and sheep's milk, respectively. An equally important indicator is the safety of the product, so microbiological and biochemical analyzes were carried out on day 1 and during storage (day 28 at 4 °C). Producing yogurt using sheep's milk is an interesting approach because of the improved nutritional value compared to cow's and goat's milk. Yogurt with the best indicators and a rational ratio of 2 types of milk was also identified. The physicochemical parameters of all types of yogurts were studied, the rational number of added starter cultures was selected. At the same time, yogurt from cow's milk received low marks on organoleptic analysis, the rest of the samples showed a good result. The best in terms of the organoleptic analysis are yogurts with the addition of sheep's milk. Yogurts have the ability to increase the body's resistance to harmful environmental factors, subject to the consumption of live yogurt.
Justifying the experimental method for determining the parameters of liquid infiltration in bulk material
Authors: Abramov Yuriy , Basmanov Oleksii , Oliinik Volodymyr , Khmyrov Ihor 
Published: September 2022

The object of this study is the process of impregnation of liquid into the bulk material, in particular, into the soil. Determining the impregnation parameters is a relevant task when assessing the consequences of an emergency spill of a hazardous liquid. Infiltration of liquid into the soil leads to pollution of water resources. However, the greatest danger is the ignition of the spill of a combustible liquid.
Based on the Green-Ampt model, a mathematical description of the impregnation of liquid into bulk material was built. It is a system of two ordinary differential equations of the first order, one of which describes the reduction of the thickness of the liquid layer on the surface, and the other describes the dynamics of the impregnation of liquid into depth. The solution to the system was derived in the form of time dependence on the depth of impregnation.
An experimental study was conducted on the example of impregnation of crude oil in the sand. To this end, sand was poured into a vertical measuring glass cylinder. After that, the liquid was poured and a video recording of the impregnation process was carried out. By processing the video recording, the depth of impregnation and the corresponding time were determined. The results of the study show that the relationship between the thickness of the liquid layer on the surface of the sand and the depth of impregnation is linear in nature: the relative deviation of linear approximation from experimental data does not exceed 3.5.
By expanding the logarithmic function contained in the solution to the system of differential equations into the Taylor series, a polynomial dependence of time on the depth of impregnation was established. To determine the coefficients of the polynomial based on the experimental data, the least squares method was used. In this case, the approximation error after the first minute after spilling does not exceed 10 %.
The proposed method could be used to account for seepage in the model of liquid spreading on the ground and the burning model of a flammable liquid spill
Effectiveness of the use of algorithms and methods of artificial technologies for sign language recognition for people with disabilities
Authors: Bayegizova Aigulim , Murzabekova Gulden , Ismailova Aisulu , Aitimova Ulzada , Mukhanova Ayagoz , Beldeubayeva Zhanar , Ainagulova Aliya , Naizagarayeva Akgul 
Published: September 2022

According to WHO, the number of people with disabilities in the world has exceeded 1 billion. At the same time, 80 percent of all people with disabilities live in developing countries. In this regard, the demand for the use of applications for people with disabilities is growing every day. The paper deals with neural network methods like MediaPipe Holistic and the LSTM module for determining the sign language of people with disabilities. MediaPipe has demonstrated unprecedented low latency and high tracking accuracy in real-world scenarios thanks to built-in monitoring solutions. Therefore, MediaPipe Holistic was used in this work, which combines pose, hand, and face control with detailed levels.
The main purpose of this paper is to show the effectiveness of the HAR algorithm for recognizing human actions, based on the architecture of in-depth learning for classifying actions into seven different classes.
The main problem of this paper is the high level of recognition of the sign language of people with disabilities when implementing their work in cross-platform applications, web applications, social networks that facilitate the daily life of people with disabilities and interact with society. To solve this problem, an algorithm was used that combines the architecture of a convolutional neural network (CNN) and long short-term memory (LSTM) to study spatial and temporal capabilities from three-dimensional skeletal data taken only from a Microsoft Kinect camera. This combination allows you to take advantage of LSTM when modeling temporal data and CNN when modeling spatial data.
The results obtained based on calculations carried out by adding a new layer to the existing model showed higher accuracy than calculations carried out on the existing model.
Development of a comprehensive methodology for assessing information and analytical support in decision support systems
Authors: Mahdi Qasim Abbood , Mohammed Basem Abdullah , Salnikova Olha , Skliar Oleksandr , Skorodid Serhii , Panasiuk Vasil , Veretnov Andrii , Shknai Oleh , Prokopenko Yevgen , Pyvovarchuk Sergij 
Published: September 2022

The object of the study is decision support systems. A methodology for evaluating information and analytical support in decision support systems was developed. The method consists of the main stages: assessment of the type of uncertainty about the state of the analysis object, calculation of criteria and determination of development options, determination of system reaction time, formation of the initial scenario. The next steps are establishing the target state of the object, analyzing options for influencing the analysis object, obtaining intermediate target states of the analysis object, and determining options for the development of the analysis object.
The method was developed because of the need to process more information and has a moderate computational complexity.
It was found that the proposed method has a computational complexity of 10–15 % lower compared to the methods for evaluating the effectiveness of management decisions. This method will allow assessing the state of information and analytical support and determining effective measures to increase efficiency. The method will allow analyzing possible options for the development of the assessment object in each development phase and the moments in time when it is necessary to carry out structural changes that ensure the transition to the next phase. In this case, subjective factors of choice are taken into account while searching for solutions, which are formalized in the form of weights for the components of the integral efficiency criterion. The maximization of the criteria, calculated taking into account the preferences, makes it possible to determine the best option for the development of the assessment object. The method allows increasing the speed of assessment of the state of information and analytical support, reducing the use of computing resources of decision support systems, developing measures aimed at increasing the efficiency of information and analytical support
Methods of UAVs images segmentation based on k-means and a genetic algorithm
Authors: Ruban Igor , Khudov Hennadii , Makoveichuk Oleksandr , Khudov Vladyslav , Kalimulin Temir , Glukhov Sergey , Arkushenko Pavlo , Kravets Taras , Khizhnyak Irina , Shamrai Nazar 
Published: September 2022

The object of this study is the process of segmentation of images from unmanned aerial vehicles. It was established that segmentation methods based on k-means and a genetic algorithm work qualitatively on images from space observation systems. It is proposed to use segmentation methods based on k-means and a genetic algorithm for segmenting images from unmanned aerial vehicles. The main stages of image segmentation methods based on k-means and genetic algorithm have been determined.
An experimental study of segmentation of images from unmanned aerial vehicles was carried out. Unlike known ones, image segmentation by a k-means-based method that successfully works on images from space surveillance systems cannot be directly applied to image segmentation from unmanned aerial vehicles. Unlike known ones, image segmentation by a method based on a genetic algorithm that successfully works on images from space surveillance systems also cannot be directly applied to image segmentation from unmanned aerial vehicles.
The quality of segmentation of images from unmanned aerial vehicles by methods based on k-means and a genetic algorithm was assessed. It was established that:
– the average level of first-kind errors is 70 % and 51 % when segmenting an image from an unmanned aerial vehicle using methods based on k-means and a genetic algorithm, respectively;
– average level of second-kind errors is 61 % and 43 % when segmenting an image from an unmanned aerial vehicle using methods based on k-means and a genetic algorithm, respectively.
It was concluded that further research must be carried out to develop methods for segmenting images from unmanned aerial vehicles.
Development of a method for increasing the interruption protection of multi-antenna systems with spectrally effective special purpose signals under the influence of destabilizing factors
Authors: Sova Oleg , Shyshatskyi Andrii , Ostapchuk Viktor , Zhuravskyi Yurii , Rohovets Maksym , Borysov Ihor , Bovsunovskyi Viktor , Artabaev Yuriy , Trotsko Oleksandr , Pylypchuk Ihor 
Published: September 2022

The object of research is multi-antenna systems with spectrally efficient special purpose signals. The problematic issue, the solution of which is devoted to this research, is the improvement of immunity to interference of multi-antenna systems with spectrally efficient special purpose signals. A technique for improving the immunity of multi-antenna systems with spectrally efficient special-purpose signals under the influence of destabilizing factors has been developed. A distinctive feature of the proposed methodology is the use of an improved pre-coding procedure, evaluation of the channel state of multi-antenna radio communication systems with spectrally efficient signals by several indicators. The improved channel state estimation procedure consists in estimating channel bit error probability, channel state frequency response, and channel state impulse response. The formation of an estimate of the channel state for each of the assessment indicators takes place on a separate layer of the neural network using the apparatus of fuzzy sets, after which a generalized estimate is formed at the output of the neural network. The novelty of the proposed method also consists in the use of an improved procedure for forecasting the channel state of multi-antenna systems with spectrally efficient signals. The essence of the proposed procedure is the use of fuzzy cognitive models and an artificial neural network to predict the state of the channels of multi-antenna systems with spectrally efficient signals.
Based on the results of the research, it was established that the proposed method allows to increase the immunity of multi-antenna systems with spectrally efficient signals according to the 8×8 scheme and 64 subcarriers by 20–25 % compared to the known ones.
Investigation of fluid dynamics in microfracture channels
Authors: Mammadova Maleyka 
Published: September 2022

The object of the work is an experimental study of the features of the movement of viscous and anomalous fluids in plane-parallel and plane-radial microcracks.
In the work, the unexplored problem of hydrodynamic features of fluid motion in the considered objects – channels is solved.
It was experimentally revealed that various fluids, when moving in microcracked channels with micron-sized openings, acquire new mechanical properties, which differ from their properties in the usual condition. The effect in the “microcrack-fluid” system is the reason for changes in the mechanical properties of fluids in microcracks and equivalent ultra-low-permeable porous media. It was revealed that when a one-parameter viscous fluid moves in a crack with an opening h<hcr, it becomes two-parameter, i.e. behaves like an anomalous fluid, and when moving with an opening h≥hcr, it restores one-parameter properties, and the anomalous fluid behaves like an anomalous fluid but increases the rheological constants of the model.
The results of the research require taking into consideration the crack effect in estimating the parameters of the technological processes system and technical devices “microcrack-fluid”. Machines and mechanisms must additionally have nodes that would prevent this effect. This is of scientific and practical importance for various fields of the industry, machine manufacturing, instrument manufacturing, chemical technology and medicine.
The effect of hybrid nanofluid CuO-TiO2 on radiator performance
Authors: Sudarmadji Sudarmadji , Irawan Bambang , Susilo Sugeng Hadi 
Published: September 2022

This study aims to improve the performance of the vehicle's cooling system called the radiator, which is part of increasing energy efficiency. Research has been done to investigate the convective heat transfer of hybrid nanofluid, using CuO and TiO2 nanoparticles and water-ethylene glycol (RC) as base fluids on a radiator. The mass concentration of the hybrid nanoparticles varied from 0.25 %, 0.30 %, and 0.35 %. For the preparation of the hybrid nanofluid through a two-step method, by mixing dry samples of CuO and TiO2 nanoparticles (50:50) and then the mixture of radiator coolant, RC (60 % water and 40 % ethylene glycol). The fluid flow varies from 20 liters per minute to 28 liters per minute. Temperature variations range from 70 °C to 90 °C by using controlled heating. Four thermocouples measure the inlet and outlet hot fluid flow and the airflow before and after the radiator. The experiment showed that the overall heat transfer coefficient increases remarkably with the increase of the hybrid nanoparticle concentration under various flow rate values. The maximum overall heat transfer coefficient increases by about 83 % compared to pure radiator coolant under 0.35 % mass concentration at a flow rate of 22 liters per minute and a temperature of 70 °C. It has also been found that the heat transfer rate is highly dependent on the radiator's mass fraction and flow rate. Increasing the mass concentration shows maximum enhancement in heat transfer rate. Inlet temperature also enhances the heat transfer rate, but its effect is small compared to nanofluid's mass concentration and flow rate. This study reveals that hybrid nanofluids can be suitable as a working fluid, especially in small-scale heat transfer devices.
Characterization of high impedance of multilayer coplanar waveguide transmission line design for integration with nanodevices
Authors: Nurzhaubayeva Gulsaya , Chezhimbayeva Katipa , Haris Norshakila 
Published: September 2022

Terahertz technology has recently attracted the attention of the researchers due to its wide range of applications such as security and military, biomedicine and health care, astronomy and biology. There are many scrutinized research papers among the terahertz applications with nanodevices such as self-switching devices. They need monolithic microwave integrated circuits for integration. It is evident that the system impedance of transmission lines is 50 Ω. However, the main limitation of self-switching diodes is high level of impedance in megaohms which is a huge value and is not so easy to implement. Paper focuses on the design and simulation of the coplanar waveguide transmission line structures with higher impedance by applying multilayer technology for the integration with self-switching diodes. Using multilayer technology in design allows wide range of impedances. Two approaches have been targeted such that meets all the requirements of integration with nanodevice. First approach is a widening the gap of the polyimide dielectric layers used in the fabrication of these components. Several design structures have been considered such as positioning the location of signal and grounds contacts with respect to the position of the dielectric layers. As the result the highest characteristic impedance of about 90 Ω was achieved at operating frequency of 110 GHz. Secondly, novel coplanar waveguide transmission line structure was investigated where the V – shape structure was joined with the signal elevated structure. The terahertz application research may effect on high data transmission rate of no less than 10 GBit/s and thereby in increase of traffic volume.