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EUREKA : Physics and Engineering
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ISSN (Online) 2461-4262
Published by Scientific Route OÜ Homepage  [8 journals]
  • GPS observations of ionospheric TEC variations over Nepal during 22 July
           2009 solar eclipse

    • Authors: Basu Dev Ghimire, Ashok Silwal, Narayan Prasad Chapagain, Sujan Prasad Gautam, Prakash Poudel, Balaram Khadka
      Pages: 3 - 14
      Abstract: As the study of ionospheric behavior during various solar activities is an important task, various studies of ionospheric changes during eclipse events have been widely performed in the different regions of the globe. This paper investigates the ionospheric responses to the solar eclipse on 22 July 2009 over Nepal using the total electron content (TEC) measured by dual-frequency Global Positioning System (GPS) receivers. The time-averaged Vertical TEC (vTEC) of ten GPS stations from Nepal is analyzed and it is found that the value of ionospheric TEC decreases due to the reduction of ionizing radiation. In addition, the deviation in the TEC value on eclipse day from the mean vTEC value of the top five quietest days is found to lie in the range ~1–5 TECu at those regions which were associated with the partial eclipse shadow. On the other hand, the region with the total eclipse (BRN2 and RMTE) faced ~6–7 TECu on average reduction in the TEC value. Considering that the eclipse of 22 July 2009 occurred just at sunrise in the Nepalese zone, a maximum reduction of about 5 TECu is very significant. Higher deviation in TEC is therefore linked with the path of totality and the obscuration rate. This study reveals that the ionospheric TEC over Nepal was altered by wave-like energy and momentum transport, as well as obscuration of the solar disc due to the partial and total solar eclipse. Furthermore, the cross-correlation results presented similar type signatures of the eclipse-induced ionospheric modification over Nepal. This research work serves a crucial future reference for the comparative study of change of ionospheric TEC variability over the Nepal region during Eclipse events
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002340
  • The effect of Clathrin protein addition on increasing the number of
           electrons in organic Dye-Sensitized Solar Cell (DSSC)

    • Authors: Prihanto Trihutomo, Marji Marji, Muchammad Harly, Bambang Adi Wahyudi, Muhammad Bustomi Radja
      Pages: 15 - 27
      Abstract: Dye-Sensitized Solar Cell (DSSC) is a solar cell that uses dyes to convert sunlight into electricity, which has a wide absorption spectrum, is inexpensive and environmentally friendly. Visible light sensitive dyes are used in Dye-Sensitized Solar Cell (DSSC) types to generate electricity. Natural sensitive dyes that are commonly used in DSSC are chlorophyll derived from plants. Chlorophyll is a source of electrons which will be excited when exposed to light, resulting in an electric current in the DSSC. The most basic problem in Dye-Sensitized Solar Cell (DSSC) is that the number of electrons produced is still lower than that of silicon solar cells. This is due to the high recombination process of free electrons due to limited diffusion of electrons trapped at the boundary between TiO2 particles caused by less than optimal contact between particles. Clathrin is a protein that plays an important role in the formation of the vesicle layer which is responsible for the transport of molecules in cells. As a protein that plays an important role in the cell transport system, Clathrin can bind to ions in order to transport cells. This study has proven that the addition of Clathrin protein to the DSSC layer can increase the number of electrons generated in the DSSC. The method used in this study was to vary the addition of Clathrin content to TiO2, namely the Clathrin concentration of 0 %, 25 %, 50 % and 75 %. The results showed that increasing the Clathrin content would increase the electric current and the number of electrons generated by the DSSC, namely the 75 % Clathrin content with an electric current of 5,247 mA and the number of electrons was 3.28x1016
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.001957
  • Development of empirical mode decomposition based neural network for power
           quality disturbances classification

    • Authors: Faqih Rofii, Agus Naba, Hari Arief Dharmawan, Fachrudin Hunaini
      Pages: 28 - 44
      Abstract: The complexity of the electric power network causes a lot of distortion, such as a decrease in power quality (PQ) in the form of voltage variations, harmonics, and frequency fluctuations. Monitoring the distortion source is important to ensure the availability of clean and quality electric power. Therefore, this study aims to classify power quality using a neural network with empirical mode decomposition-based feature extraction. The proposed method consists of 2 main steps, namely feature extraction, and classification. Empirical Mode Decomposition (EMD) was also applied to categorize the PQ disturbances into several intrinsic mode functions (IMF) components, which were extracted using statistical parameters and the Hilbert transformation. The statistical parameters consist of mean, root mean squared, range, standard deviation, kurtosis, crest factor, energy, and skewness, while the Hilbert transformation consists of instantaneous frequency and amplitude. The feature extraction results from both parameters were combined into a set of PQ disturbances and classified using Multi-Layer Feedforward Neural Networks (MLFNN). Training and testing were carried out on 3 feature datasets, namely statistical parameters, Hilbert transforms, and a combination of both as inputs from 3 different MLFNN architectures. The best results were obtained from the combined feature input on the network architecture with 2 layers of ten neurons, by 98.4 %, 97.75, and 97.4 % for precision, recall, and overall accuracy, respectively. The implemented method is used to classify PQ signals reliably for pure sinusoids, harmonics with sag and swell, as well as flicker with 100 % precision
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002046
  • Developing an algorithm for monitoring gas generators of hydrogen storage
           and supply systems

    • Authors: Yuriy Abramov, Oleksii Basmanov, Valentina Krivtsova, Andrey Mikhayluk, Oleksandra Mikhayluk
      Pages: 45 - 54
      Abstract: In relation to the main element of the hydrogen storage and supply system based on the hydro-reacting composition – the gas generator – an algorithm for its control has been developed. The development of such an algorithm is carried out in three stages. At the first stage, the problem of formalizing the hydrogen generation process is solved. Formalization of this process is carried out using the transfer function of the gas generator. The use of the criterion for the minimum error of the mismatch of the given amplitude-frequency characteristics of the gas generator allows to represent its transfer function in the form of a transfer function of the inertial link. At the second stage, the problem of determining the conditions for the occurrence of self-oscillations in the pressure stabilization subsystem is solved. A prerequisite for the emergence of a self-oscillating mode of operation of the hydrogen storage and supply system is the presence of a relay static characteristic of the pressure sensor. For the characteristic parameters of such a system, the ranges of values of the parameters of self-oscillations, frequencies and amplitudes, are determined. For these parameters, analytical expressions are obtained, which include the main parameters of the pressure stabilization subsystem in the hydrogen storage and supply system. At the third stage, the problem of forming a gas generator control algorithm is solved. As a test action in the implementation of the control algorithm, self-oscillations in the pressure stabilization subsystem are used. The control algorithm for the gas generator of the hydrogen storage and supply system includes determining the parameters of self-oscillations and comparing their values with the values obtained a priori. A typical diagram of a hydrogen storage and supply system is presented, in which the developed gas generator control algorithm is implemented
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002262
  • Enhancement efficiency of Michell-Banki turbine using NACA 6512 modified
           blade profile via CFD

    • Authors: Steven Galvis-Holguin, Jorge Sierra-Del Rio, D. Hincapié-Zuluaga
      Pages: 55 - 67
      Abstract: The small hydroelectric power plants (SHPP) are implemented in non-interconnected zones (NIZ) of developing countries. In which, the provision of electrical energy from the national interconnected system is not economically feasible. Therefore, in the literature, hydroelectric generation technologies have been implemented taking advantage of the energy available in the rivers. One of these technologies is the Michell-Banki type cross-flow turbines (MBT), which, despite having lower efficiencies than turbines such as Pelton and Francis, maintain their efficiency although fluctuations in site conditions. For this reason, different studies have been made to increase the efficiency of the MBT by making geometric modifications to both the nozzle and the rotor. The purpose of this study is to determine numerically the effect of the geometry of the blades that form the runner on the efficiency of Michell-Banki Turbine (MBT). For this, two (2) geometries were studied corresponding to a circular sector of a standard tubular profile and an airfoil NACA 6512 modified in curvature profile and chord length, according to the profile of the standard tubular blade. For this study, transient simulations for multiphase water-air flow were implemented using a k-ε turbulence model in the Ansys 2020R1® CFX software. The two (2) turbine models were configured to the same hydraulic conditions of head and volumetric flow corresponding to 0.5 m and 16.27 L/s, respectively. Variations in rotational speed were configured between 100 and 200 RPM with 20 RPM steps. It was found that using the modified 6512 hydrodynamic profile, at 140 RPM increased efficiency by 6 %, compared to the conventional tubular type blade geometry
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002351
  • Implementation of the dynamic balancing approach of a rotating composite
           hollow shaft

    • Authors: Ala’a M. Al-Falahat
      Pages: 68 - 73
      Abstract: Balancing is essential in rotating machinery, which is widely employed in many technical sectors, particularly in high-speed rotor-bearing systems. The mass balancing method of the hollow shaft manufactured of composite materials is investigated in this study over the whole speed range of the rotor. The main goal of the balancing technique is to generate a smooth-running machine by removing the commonality imbalance mass through the use of compensating mass unbalance. As a result, MATLAB code is created to produce a functioning mathematical model of the rotor-bearing system. The unbalanced rotor-bearing system finite element model is proposed to set the balancing mass of the composite hollow shaft at a selected speed rotor that allows minimizing the vibration response amplitude of the rotor as much as possible with minimal impact on the rest of the imbalance response within the speed range of the interest. As a consequence, this study validates the process for distributing imbalance in modelling balancing to balance the flexible hollow shaft with an unbalanced mass throughout the complete speed range of the shaft. The balance of the hollow shaft at the critical speed was observed in this approach, and the vibration amplitude was determined by adding extra mass at a specific angle
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002336
  • Development of statistical modeling of the pipelines' reliability
           projections of the main heat networks, according to the period of
           operation and diameter

    • Authors: Olga Maliavina, Anatolii Yakunin, Viktoriia Hrankina, Viktoria Milanko
      Pages: 74 - 81
      Abstract: Using the method of statistical modeling of pipeline reliability, the statistical model for forecasting the dependence of the failure parameter of pipelines of main heating networks on the service life and diameter was developed and analyzed. This method includes two techniques. The first allows to obtain predictive dependences of pipeline reliability indicators for systems that include sections of different diameters with different service life periods and actual data on damage over several years. The second increases the correctness of the obtained dependences by optimizing the service life step in the study of damage to heat pipes. As a result of the study, the dependence of the reliability of main pipelines on the service life and diameter was established. The condition and forecast values of the specified indicator of reliability of main heat pipelines, and also dynamics and range of its changes are defined. The average value of the failure rate parameter increases from 0.23 1/km year (diameter 300 mm) to 0.62 1/km year (diameter 800 mm), which is 2.7 times larger than the pipes with the diameter 300 mm. The multiplicity of changes in the value of the parameter of the flow of failures was also established in accordance with the change in the diameter of the pipelines. According to the developed statistical model the dependence for calculation of the forecast of quantity of damages of the main heat pipelines according to their service life, diameter and length is established. This will increase the reliability of heating systems and effectively plan the cost of material, technical and labor resources. The given method can be used to assess the forecast of the reliability of pipelines, respectively, of their diameters for other engineering systems and networks
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002302
  • Statistical analysis of the relative position of the rod hanger and the

    • Authors: Ibrahim Habibov, Sevinc Abasova, Vusala Huseynova
      Pages: 82 - 90
      Abstract: One of the leading methods of exploitation of oil fields is oil production with the help of downhole rod pumping units (DRPU). Over 80 % of the operating well stock of Azneft PA is equipped with deep well pumps and about 30 % of oil is produced in the country with their help. The widespread use of DRPU is associated with a fairly high maturity of installations, simplicity of its design and maintenance, repair in field conditions, ease of adjustment, the possibility of servicing the installation by unskilled workers, a small effect on the operation of DRPU of the physical and chemical properties of the pumped liquid, as well as high efficiency. However, along with the high efficiency of the applied DRPU, there are also complaints regarding the need to increase the reliability and resource of wellhead equipment, including in order to improve the environmental situation in the oil fields. One of the conditions for ensuring high reliability of the ground equipment of the DRPU is to ensure the tightness of the wellhead rod-wellhead stuffing box assembly, the violation of which is not only a failure of the installation, but also leads to environmental pollution. This is facilitated by inaccuracies in the assembly and installation of DRPU at the wellhead. When mounting the pumping unit, for many reasons, the tolerance of the wellhead rod with the suspension point of the rod string to the balancer head is not ensured. In this regard, in the requirements for the accuracy of mounting the pumping unit at the point of application, a certain mismatch of the axes within the circular coordinates is allowed. So, for widely used pumping units of the CK8 type, the permissible mismatch between the axis of the wellhead rod and the suspension point of the rods is determined by the conditions under which the projection of the suspension point of the rods onto the plane of the base of the pumping unit at any position of the balancer is allowed within a circle with a diameter of 25 mm.
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002267
  • A study on the effects of plasma spraying parameters on the adhesion
           strength of Cr3C2-NiCr coating on 16Mn steel

    • Authors: Dang Xuan Thao, Cuong Pham Duc
      Pages: 91 - 100
      Abstract: This paper experimentally studied the adhesion strength of Cr3C2-30 %NiCr coating created on 16Mn steel substrate by plasma thermal coating technique in relation to spraying parameters. Experiments were carried out according to the central composite design (CCD) experimental matrix with three parameters: current intensity, powder feeding rate, and spray distance. Samples consisting of an annular disc and a latch made of 16Mn were fabricated according to the JIS H8664-1977 standard. Cr3C2-30 %NiCr coating was then created on the top surface of the disc including end of the latch. Adhesion strength of the coating to the substrate was measured through the tensile test. ANOVA analysis of variance was performed to evaluate the influence of the spraying parameters on adhesion strength and to build an empirical regression function representing the relationship between those parameters and the adhesion. Optimization problem was solved by ANOVA method and genetic algorithm (GA) to determine the value of the spraying parameters at which the coating has the greatest adhesion strength to the substrate. The results showed that the spraying parameters greatly affected the adhesion of the Cr3C2-30 %NiCr coating to the 16Mn substrate. Among them the spray distance has the greatest influence while the powder feeding rate has the least. Secondly, the regression function was well reflected the relationship between the three parameters and adhesion strength of the coating on the substrate. Using the values of spray parameter obtained from the GA optimization to create Cr3C2-30 %NiCr coating on 16Mn steel, the adhesion strength of the coating to the substrate reached a value of 98.4 % compared to the prediction
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.001827
  • A research on application of the measurement of alternatives and ranking
           according to compromise solution method for multi-criteria decision making
           in the grinding process

    • Authors: Hoang Xuan Thinh, Do Duc Trung
      Pages: 101 - 110
      Abstract: The efficiency of cutting methods in general and the grinding method in particular is evaluated through many parameters such as surface roughness, machining productivity, system vibrations, etc. The machining process is considered highly efficient when it meets the set requirements for these parameters such as ensuring the small surface roughness, small vibrations, and high productivity, etc. However, for each specific machining condition, sometimes the set criteria for the output criteria are opposite. In these cases, it is required to solve the Multi-Criteria Decision Making (MCDM) which means making the decision to ensure the harmonization of all criteria. In this study, a study on multi-criteria decision making in the grinding process of 9CrSi steel using CBN grinding wheels is presented. The experimental process was carried out with sixteen experiments according to an orthogonal matrix that designed by the Taguchi method. The workpiece velocity, feed rate, and depth of cut were changed in each experiment. At each experiment, the responses were determined including surface roughness (Ra), the vibration of the grinding wheel shaft in the three directions, corresponding to Ax, Ay, and Az, and material removal yield (Q). Four determination methods of weights for criteria were used. The Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was applied for multi-criteria decision making. The objective of this study is to identify an experiment that simultaneously ensures the small values of Ra, Ax, Ay, and Az and large value Q
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002120
  • Analysis of the crystal structure of the Ba3TeO6 compound

    • Authors: Viktor Zavodyannyi
      Pages: 111 - 115
      Abstract: The object of research is the crystal structure of the Ba3TeO6 compound. It is known from the literature that this material has photoluminescent properties and crystallizes in the tetragonal system with the space symmetry group I41/a (88) and lattice periods a=19.3878 А; b=19.3878 Аº, c=34.909 Аº. At the same time, there are data on two other polymorphic modifications of this compound, which are in the PDF-2 database for 2009. Therefore, information about the crystal structure of this compound is incomplete. The existence of different spectra for a given compound mentioned in the literature may be due to different methods of synthesis of this compound. A study of the crystal structure of the compound Ba3TeO6 under the number 00-035-0995 in the PDF-2 database for 2009 is proposed. The study used the 2009 PDF-2 database. As well as the HighScorePlus 3.0 program (Netherlands), which makes it possible to refine the microstructural parameters of a structural model using the Rietveld method. The diffraction spectrum for the study was generated using the HighScorePlus 3.0 program and the 2009 pdf-2 database connected to it in UDF format. As a result, it was found that this diffraction spectrum of the studied compound can correspond to the following structural model: orthorhombic system with lattice periods a=4.2910 A; b=4.4062 A; c=4.3459 A. The space symmetry group Pnnn(48) is possible. Analyzing the results obtained, it should be recognized that the studied structure of the compound crystallizes in its own structural type. At the same time, the crystal structures of the polymorphic modifications of this compound are similar. The study of the crystal structure of the compound contributes to a better understanding of its physical properties, in particular, photoluminescence
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002337
  • Development of spreadsheet simulation models of gas cylinders inventory

    • Authors: Ekaterina Gribanova, Artur Mitsel, Alexandr Shilnikov
      Pages: 116 - 127
      Abstract: The solution of the problem of managing the inventory of an enterprise whose activities are related to the purchase and sale of gas cylinders is considered. To solve the problem, it was necessary to investigate and choose the best inventory management strategy that provides the minimum value of the average inventory balance in the warehouse with the established upper limit of the average deficit. The problem of determining the best strategy is presented as a discrete programming problem, the required variables of which depend on the replenishment method. With a periodic replenishment strategy, the controlled variables are the volume of the delivery line and the delivery interval, with a threshold one, the minimum inventory level and the volume of the delivery line. Let’s also consider replenishment with a predicted inventory level, where the delivery level and the minimum inventory level are used as control variables. Three tabular simulation models with a given delivery time and random demand are proposed. Using the Chi-square test, it was found that the quantity demanded has a normal distribution law. By carrying out computational experiments, the optimal values of controlled variables were determined. The best objective function values were obtained using a model with a predicted inventory level and a threshold replenishment strategy. Experiments conducted on the basis of historical data have shown the advantage of the two model strategies compared to the strategy currently used in the enterprise. The use of a model with a predictable inventory level would reduce the average inventory balance by 46 %, and, consequently, save working capital. The results of the study can be useful for managers of enterprises whose activities are related to inventory management
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002266
  • Analysis of semi-Markov systems with fuzzy initial data

    • Authors: Lev Raskin, Oksana Sira, Larysa Sukhomlyn, Roman Korsun
      Pages: 128 - 142
      Abstract: In real operating conditions of complex systems, random changes in their possible states occur in the course of their operation. The traditional approach to describing such systems uses Markov models. However, the real non-deterministic mechanism that controls the duration of the system's stay in each of its possible states predetermines the insufficient adequacy of the models obtained in this case. This circumstance makes it expedient to consider models that are more general than Markov ones. In addition, when choosing such models, one should take into account the fundamental often manifested feature of the statistical material actually used in the processing of an array of observations, their small sample. All this, taken together, makes it relevant to study the possibility of developing less demanding, tolerant models of the behavior of complex systems. A method for the analysis of systems described under conditions of initial data uncertainty by semi-Markov models is proposed. The main approaches to the description of this uncertainty are considered: probabilistic, fuzzy, and bi-fuzzy. A procedure has been developed for determining the membership functions of fuzzy numbers based on the results of real data processing. Next, the following tasks are solved sequentially. First, the vector of stationary state probabilities of the Markov chain embedded in the semi-Markov process is found. Then, a set of expected values for the duration of the system's stay in each state before leaving it is determined, after which the required probability distribution of the system states is calculated. The proposed method has been developed to solve the problem in the case when the parameters of the membership functions of fuzzy initial data cannot be clearly estimated under conditions of a small sample
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002346
  • A real-time defect detection in printed circuit boards applying deep

    • Authors: Van-Truong Nguyen, Huy-Anh Bui
      Pages: 143 - 153
      Abstract: Inspection of defects in the printed circuit boards (PCBs) has both safety and economic significance in the 4.0 industrial manufacturing. Nevertheless, it is still a challenging problem to be studied in-depth due to the complexity of the PCB layouts and the shrinking down tendency of the electronic component size. In this paper, a real-time automated supervision algorithm is proposed to test the PCBs quality among different scenarios. The density of the PCBs layout and the complexity on the surface are analyzed based on deep learning and image feature extraction algorithms. To be more detailed, the ORB feature and the Brute-force matching method are utilized to match perfectly the input images with the PCB templates. After transferring images by aiding the RANSAC algorithm, a hybrid method using modern computer vision algorithms is developed to segment defective areas on the PCBs surface. Then, by applying the enhanced Residual Network –50, the proposed algorithm can classify the groove defects on the surface mount technology electronic components which minimum size up to 1x3 mm. After the training process, the proposed system is capable to categorize various types of overproduced, recycled, and cloned PCBs. The speed of the quality testing operation maintains at a high level with an average precision rate up to 96.29 % in case of good brightness conditions. Finally, the computational experiments demonstrate that the proposed system based on deep learning can obtain superior results and it outperforms several existing works in terms of speed, precision, and robustness
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002127
  • Development of object detection and classification with YOLOv4 for similar
           and structural deformed fish

    • Authors: Ari Kuswantori, Taweepol Suesut, Worapong Tangsrirat, Navaphattra Nunak
      Pages: 154 - 165
      Abstract: Food scarcity is an issue of concern due to the continued growth of the human population and the threat of global warming and climate change. Increasing food production is expected to meet the challenges of food needs that will continue to increase in the future. Automation is one of the solutions to increase food productivity, including in the aquaculture industry, where fish recognition is essential to support it. This paper presents fish recognition using YOLO version 4 (YOLOv4) on the "Fish-Pak" dataset, which contains six species of identical and structurally damaged fish, both of which are characteristics of fish processed in the aquaculture industry. Data augmentation was generated to meet the validation criteria and improve the data balance between classes. For fish images on a conveyor, flip, rotation, and translation augmentation techniques are appropriate. YOLOv4 was applied to the whole fish body and then combined with several techniques to determine the impact on the accuracy of the results. These techniques include landmarking, subclassing, adding scale data, adding head data, and class elimination. Performance for each model was evaluated with a confusion matrix, and analysis of the impact of the combination of these techniques was also reviewed. From the experimental test results, the accuracy of YOLOv4 for the whole fish body is only 43.01 %. The result rose to 72.65 % with the landmarking technique, then rose to 76.64 % with the subclassing technique, and finally rose to 77.42 % by adding scale data. The accuracy did not improve to 76.47 % by adding head data, and the accuracy rose to 98.75 % with the class elimination technique. The final result was excellent and acceptable
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002345
  • Iris recognition method based on segmentation

    • Authors: Ans Ibrahim Mahameed, Mohammed Kassim Ahmed, Noor Basim Abdullah
      Pages: 166 - 176
      Abstract: The development of science and studies has led to the creation of many modern means and technologies that focused and directed their interests on enhancing security due to the increased need for high degrees of security and protection for individuals and societies. Hence identification using a person's vital characteristics is an important privacy topic for governments, businesses and individuals. A lot of biometric features such as fingerprint, facial measurements, acid, palm, gait, fingernails and iris have been studied and used among all the biometrics, in particular, the iris gets the attention because it has unique advantages as the iris pattern is unique and does not change over time, providing the required accuracy and stability in verification systems. This feature is impossible to modify without risk. When identifying with the iris of the eye, the discrimination system only needs to compare the data of the characteristics of the iris of the person to be tested to determine the individual's identity, so the iris is extracted only from the images taken. Determining correct iris segmentation methods is the most important stage in the verification system, including determining the limbic boundaries of the iris and pupil, whether there is an effect of eyelids and shadows, and not exaggerating centralization that reduces the effectiveness of the iris recognition system. There are many techniques for subtracting the iris from the captured image. This paper presents the architecture of biometric systems that use iris to distinguish people and a recent survey of iris segmentation methods used in recent research, discusses methods and algorithms used for this purpose, presents datasets and the accuracy of each method, and compares the performance of each method used in previous studies
      PubDate: 2022-03-31
      DOI: 10.21303/2461-4262.2022.002341
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