EUREKA: Physics and Engineering

Journal Information
ISSN / EISSN : 2461-4254 / 2461-4262
Published by: OU Scientific Route (10.21303)
Total articles ≅ 370
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Latest articles in this journal

Ans Ibrahim Mahameed, Mohammed Kassim Ahmed, Noor Basim Abdullah
EUREKA: Physics and Engineering pp 166-176;

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
Prihanto Trihutomo, Marji Marji, Muchammad Harly, Bambang Adi Wahyudi, Muhammad Bustomi Radja
EUREKA: Physics and Engineering pp 15-27;

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
Olga Maliavina, Anatolii Yakunin, Viktoriia Hrankina, Viktoria Milanko
EUREKA: Physics and Engineering pp 74-81;

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
Steven Galvis-Holguin, Jorge Sierra-Del Rio, D. Hincapié-Zuluaga
EUREKA: Physics and Engineering pp 55-67;

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
EUREKA: Physics and Engineering pp 3-14;

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
, Agus Naba, Hari Arief Dharmawan, Fachrudin Hunaini
EUREKA: Physics and Engineering pp 28-44;

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
, , Vusala Huseynova
EUREKA: Physics and Engineering pp 82-90;

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.
Ari Kuswantori, Taweepol Suesut, , Navaphattra Nunak
EUREKA: Physics and Engineering pp 154-165;

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
Ekaterina Gribanova, , Alexandr Shilnikov
EUREKA: Physics and Engineering pp 116-127;

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
Hoang Xuan Thinh,
EUREKA: Physics and Engineering pp 101-110;

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
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