Volume 1, Issue 3
Download Complete Issue
Front Cover
Publication Month: March 2022, Page(s): i – i
Editorial Board
Publication Month: March 2022, Page(s): ii – ii
Editorial
Publication Month: March 2022, Page(s): iii – vii
Table of Contents
Publication Month: March 2022, Page(s): viii – ix
Ways to Increase the Efficiency of Sucker Rod Pump Units in Oil Production
Aliev Telman Abbas, Guluyev Gambar Agaverdi, Rzayev Asif Haji, Aliyev Yaver Gabil, Rezvan Mahammad Huseyn, Yashin Anton Nikolaevich, Khakimyanov Marat Ilgizovich
J. Engg. Res. & Sci. 1(3), 1-8 (2022);
The article shows that in the middle and late stages of oil field development, of all mechanized methods, the most common is oil extraction by sucker rod pump units (SRPU). However, due to inefficient management of them, their operating costs are increasing. The article presents the results of improving the efficiency of SRPU due to the use of NOISE technology for early diagnosis of the technical condition of equipment and frequency converters for controlling its induction motor. The results of the implementation of the “NOISE Control, Diagnostics and Management Complex for oil wells operated by SRPU” created at the Institute of Management Systems of the National Academy of Sciences of Azerbaijan are presented. A method for calculating the saving of electrical energy in the control of SRPU frequency converters has been developed. The results of calculation of electric energy savings for the oil and gas production facility Bibi-Heybat Oil of the Republic of Azerbaijan are also presented.
Soil Properties Prediction for Agriculture using Machine Learning Techniques
Vijay Kumar, Jai Singh Malhotra, Saurav Sharma, Parth Bhardwaj
J. Engg. Res. & Sci. 1(3), 9-18 (2022);
Information about soil properties help the farmers to do effective and efficient farming, and yield mo . An attempt has been made in this paper to predict the soil properties using machine learning approaches. The main properties of soil prediction are Calcium, Phosphorus, pH, Soil Organic Carbon, and Sand. These properties greatly affect the production of crops. Four well-known machine learning models, namely, multiple linear regression, random forest regression, support vector machine, and gradient boosting, are used for prediction of these soil properties. The performance of these models is evaluated on Africa Soil Property Prediction dataset. Experimental results reveal that the gradient boosting outperforms the other models in terms of coefficient of determination. Gradient boosting is able to predict all the soil properties accurately except phosphorus. It will be helpful for the farmers to know the properties of the soil in their particular terrain.
An Overview of Solutions Regarding the Problems in Vocational and Technical Education – Example of Elazığ Province
Ceyda Akıllı, İmam Bakır Arabacı, Engin Kırçıl
J. Engg. Res. & Sci. 1(3), 19-27 (2022);
Vocational and technical education institutions help to train individuals in a well-equipped manner, increase their employability level, and provide workforce in areas that countries need. Vocational and technical education is of great importance in terms of ensuring the development of countries at the national and international level, training qualified intermediate staff and increasing employment opportunities. Despite the innovations and projects carried out in the vocational and technical education process; educators and students face many problems in the process. The aim of this research is to examine the solution proposals for the problems experienced in vocational and technical education institutions in terms of management, program and application. In the research, the situation analysis design, which is among the qualitative research methods, was used. Focus group interview technique was used in order to examine the subject discussed in the research in detail. A semi-structured interview form was used as a data collection tool. As a result of the research, the main solution to the problems experienced in the management dimension in vocational and technical education institutions is to establish an effective control mechanism, to strengthen the education-employment-production relationship, and to take deterrent measures for the implementation of the Vocational Education Law No. 3308. As a result of the research, solution suggestions for the problems experienced in the dimension of the curriculum in vocational education are to adapt to the new generation teaching methods and techniques, to offer internship opportunities to students abroad, and to have the qualified manpower needed by the domestic and national defense industry. Finally, solution suggestions for the problems experienced in the implementation phase in vocational and technical education institutions are to make school and field preferences in certain time periods during the student placement processes, to limit these processes and to allocate sufficient quotas to the relevant institutions.
An Overview on Various Techniques used for Correct Interpretation of Roadway Symbols
Abhinav Vinod Deshpande
J. Engg. Res. & Sci. 1(3), 28-38 (2022);
In this study paper, a comparative analysis of various image enhancements in local domain techniques was made based on three-dimensional image quality statistics namely Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) and Image Quality Model (SSIM) to determine image quality. especially among them so that the process of image enhancement in the local domain is carried out. The conditions for choosing the best method are to have a small number of Mean Squared Error (MSE) and a high number of Peak Signal to Noise Ratio (PSNR) and Structural Properties to measure Image Quality (SSIM).
The Effects of Total Health Expenditure on Economic Growth in Southern and Western sub-Saharan Africa
Faith Onechojo Yusufu, Bosede Olanike Awoyemi, Kehinde Akomolafe
J. Engg. Res. & Sci. 1(3), 39-51 (2022);
The purpose of this work was to investigate the effects of total health spending on the growth of the economy in Southern and Western Sub-Saharan Africa. The mean group, dynamic fixed effect, and pooled mean group/ARDL (Autoregressive Distributed Lags) panel data analyses were used to scrutinize the short and long-term effects of total per capita health spending on the growth of the economy. The short-run finding reveals that total health per capital expenditure and life expectancy at birth (LEB) has an upbeat effect on the growth of the economy (LGDP PC) in Southern Africa at all relevant levels. At all significant levels, total health per capital expenditure and life expectancy at birth (LEB) both have an upbeat outcome on the growth of the economy (LGDP PC). The short-run analysis shows that current health per capital spending and government spending has a positive effect on the growth of the economy (LGDP PC) at a 5% significant level in West Africa, while total and current health per capital expenditure has an upbeat effect on economic growth (LGDP PC) at 5% significant level in the long run. Because per-capita health spending has a beneficial impact on the growing economy, more monies should be dedicated to the health sector to increase the quality of healthcare operations.
Physical Interpretation of the Solution to the Problem of Diffraction on a Half-plane with Non-Ideal Boundary Conditions
Michael Vesnik
J. Engg. Res. & Sci. 1(3), 52-58 (2022);
The recently proposed method of fundamental components is employed to develop a technique for obtaining a heuristic solution to the problem of diffraction on a half-plane with non-ideal boundary conditions. The difference between the new method and traditional heuristic approaches, such as the geometric theory of diffraction and the method of edge waves, is the presence of an adjustment procedure which allows increasing the accuracy while maintaining the compactness of the formulas. For the case of the problem of diffraction on an impedance half-plane, heuristic formulas are constructed. Then they are refined using a verification solution. A quantification of accuracy is carried out, and a physical interpretation of the solution is presented. The prospects for applying this approach to constructing high-speed solvers and carrying out the physical interpretation of numerical solutions are discussed.
An Evaluation of 2D Human Pose Estimation based on ResNet Backbone
Hai-Yen -Tran, Trung-Minh Bui, Thi-Loan Pham, Van-Hung Le
J. Engg. Res. & Sci. 1(3), 59-67 (2022);
2D HumanPose Estimation (2D-HPE) has been widely applied in many practical applications in life su ction, human-robot interaction, using Convolutional Neural Networks (CNNs), which has achieved many good results. In particular, the 2D-HPE results are intermediate in the 3D Human Pose Estimation (3D-HPE) process. In this paper, we perform a study to compare the results of 2D-HPE using versions of Residual Network (ResNet/RN) (RN-10, RN- 18, RN-50, RN-101, RN-152) on HUman 3.6M Dataset (HU-3.6M-D). We transformed the original 3D annotation data of the Human 3.6M dataset to a 2D human pose. The estimated models are fine-tuning based on two protocols of the HU-3.6M-D with the same input parameters in the RN versions. The best estimate has an error of 34.96 pixels with Protocol #1 and 28.48 pixels with Protocol #3 when training with 10 epochs, increasing the number of training epochs reduces the estimation error (15.8 pixels of Protocol #3). The results of quantitative evaluation, comparison, analysis, and illustration in the paper.
Text-Based Traffic Panels Detection using the Tiny YOLOv3 Algorithm
Saba Kheirinejad, Noushin Riahi, Reza Azmi
J. Engg. Res. & Sci. 1(3), 68-80 (2022);
Lately, traffic panel detection has been engrossed by academia and industry. This study proposes a new categorization method for traffic panels. The traffic panels are classified into three classes: symbol-based, text-based, and supplementary/additional traffic panels. Although few types of research have investigated text-based traffic panels, this type is considered in detail in this study. However, there are many challenges in this type of traffic panel, such as having different languages in different countries, their similarity with other text panels, and the lack of suitable quality datasets. The panels need to be detected first to obtain a reasonable accuracy in recognizing the text. Since there are few public text-based traffic panels datasets, this study gathered a novel dataset for the Persian text-based traffic panels all over the streets of Tehran-Iran. This dataset includes two collections of images. The first collection has 9294 images, and the latter has 3305 images. The latter dataset is more monotonous than the first one. Thus, the latter is utilized as the main dataset, and the first is used as an additional dataset. To this end, the algorithm uses the additional dataset for pre-training and the main datasets for training the network. The tiny YOLOv3 algorithm that is fast and has low complexity compared to the YOLOv3 is used for pre-training, training, and testing the data to examine the utility and advantages of the data. The K-fold cross-validation procedure is used to estimate the model’s skill on the new data. It achieves 0.973 for Precision, 0.945 for Recall, and 0.955 for Fmeasure.
Bearing Fault Diagnosis Based on Ensemble Depth Explainable Encoder Classification Model with Arithmetic Optimized Tuning
Kaibi Zhang, Yanyan Wang, Hongchun Qu
J. Engg. Res. & Sci. 1(3), 81-97 (2022);
In a dynamic and complex bearing operating environment, current auto-encoder-based deep models for fault diagnosis are having difficulties in adaptation, which usually leads to a decline in accuracy. Besides, the opaqueness of the decision process by such deep models might reduce the reliability of the diagnostic results, which is not conducive to the subsequent optimization of the model. In this work, an ensemble deep auto-encoder method is developed and tested for intelligent fault diagnosis. To mitigate the influence of the changing operating environment on the diagnostic accuracy of the model, a tuning algorithm is used to adaptively adjust the parameters of the model, and a hypersphere classification algorithm is used to separately train different types of fault data. The encoder components in the ensemble model are automatically updated based on the diagnostic accuracy of the base encoder model under different operating conditions. To improve the reliability of the diagnosis results, the power spectrum analysis and Layer-wise Relevance Propagation algorithm are combined to explain the diagnosis results. The model was validated on three public datasets and compared with individual encoder methods as well as other common fault diagnosis algorithms. The results confirm that the model proposed is flexible enough to cope with changes in operating conditions and has better diagnostic and generalizing capabilities.
Call Admission Control for Real-Time Applications of TVWS Wireless Access from HAP
Habib M. Hussien, Sultan F. Meko, Konstantinos Katzis, Luzango P. Mfupe, Ephrem T. Bekele
J. Engg. Res. & Sci. 1(3), 98-105 (2022);
The rapid change in link capacity and user count induced by platform mobility in communication systems based on high altitude platform stations (HAPS) exploiting TV White Space (TVWS) spectrum may result in a high rate of handover failure and reduced resource utilization. In addition, in High Altitude Platform (HAP) wireless networks exploiting TV White Space (TVWS) spectrums, radio resources are frequently shared across numerous customers. When the number of users accepted into a network exceeds the network’s capacity, network congestion occurs, resulting in a decrease in Quality of Service (QoS) or user displeasure. To address these issues, Call admission control (CAC) may be used. This article proposed a novel call admission control scheme using deadline, channel, and tolerance aware scheduling (DCTS) algorithm to solve the challenge of scheduling real-time flows in wireless networks while maintaining tight latency guarantees. The DCTS system ensures that the average packet drop due to deadline violation converges to the preset packet loss tolerance for a given deadline requirement, packet loss tolerance, and arrival rate. Our approach covers how to handle multiple real-time packet flows at the same time with a high risk of packet losses due to latency violations without surpassing a set threshold. It also discusses how real-time application scheduling in a wireless context must account for the complicated relationship between packet deadlines, channel circumstances, and flow tolerance, as well as how to propose such scheduling policies. We also test our proposed algorithm’s performance for various arrival, channel state, deadline, and threshold scenarios. The convergence of packet drops near the threshold was demonstrated analytically. In wireless networks, CAC is a critical component in ensuring guaranteed quality of service. For real-time wireless applications that employ the DCTS scheduler, we present a threshold-based CAC method. We use the assumption that all flows belong to the same traffic class for determining the admission criteria. Our goal is to create a CAC algorithm that ensures that packet loss due to deadline violations is kept to a minimum for all allowed users. As a result, our CAC is based on a set of criteria that includes the maximum packet deadline, loss tolerance, and pace of newly received calls, as well as the accepted flows’ minimum flow priority. The admission controller threshold is compared to the properties of freshly arrived flow in our CAC method. We compare our scheme’s performance to that of the CAC of Violation Fair Exponential Rule (VFEXP) algorithm and the Modified Largest Weighted Delay First (MLWDF) methods.
Buckling Analysis of a Three-Dimensional Rectangular Plates Material Based on Exact Trigonometric Plate Theory
Onyeka Festus Chukwudi, Okeke Thompson Edozie, Nwa-David Chidobere
J. Engg. Res. & Sci. 1(3), 106-115 (2022);
In this study, exact trigonometric displacement function was used to solve the buckling problem of a three-dimensional (3-D) rectangular plate that is clamped at the first-three edges and the other remaining edge simply supported (CCCS) under uniaxial compressive load. Employing 3-D constitutive relations which consist of entire components, the functional for total potential energy was obtained. After that, the rotation and deflection at x-axis and y-axis were formulated from the established compatibility equations to get an exact trigonometric deflection function. The characteristics equation was obtained by differentiating energy equation with respect to deflect to obtain the relations between deflection and rotation. The equation of the total potential energy is minimized with respect to the deflection coefficient after incorporating the deflection and rotation function, the critical buckling load formula was established. The solution for the buckling problem gotten shown that the structure of the plate is safe when the plate thickness is increased as the outcome of the study showed that the critical buckling load increased as the span- thickness ratio increased. The overall difference in form of percent between the present work and previous studies recorded is 5.4%. This shows that at about 95% certainty, the present work is perfect. The comparison of this study with the results of previous similar studies revealed the uniformity 3-D plate theory and the variations of CPT and RPT theories in the exact buckling analysis of a rectangular plate. However, this approach which includes all the six stress elements of the plate material in the analysis produced an exact deflection function unlike the previous studies which used assumed functions. Furthermore, the theoretical analysis of this study demonstrates a novel approach to solve the buckling problem rectangular plate which is capable of analyzing rectangular plates of any thickness configuration.
A Review- Modelling Approach and Numerical Analysis of Additive Manufacturing
Vaishnavi Kohale* , Samidha Jawade, Ganesh Kakandikar
J. Engg. Res. & Sci. 1(3), 116-125 (2022);
Additive manufacturing creates 3-dimensional objects by depositing materials layer by layer. Different applications of additive manufacturing were examined to determine future growth possibilities. The current research seeks to discover existing additive manufacturing techniques based on the process mechanisms, evaluate modelling approaches based on modelling methodologies, and identify required studies. A significant number of numerical simulations are conducted to evaluate the thermal FE structure in terms of solid and powder material thermo – physical properties and permissible boundary conditions. The transient heat conduction is investigated using thermal analysis with a moving heat source.
Micro Forming and its Application: A Critical Review
Neha Tiwari, Ganesh Kakandikar, Omkar Kulkarni
J. Engg. Res. & Sci. 1(3), 126-132 (2022);
In terms of manufacturing methods/processes, micro-manufacturing has received a lot of attention around the world. Micro-forming is one of the most widely used micro-manufacturing techniques. The micro forming is based on the properties of materials based on the process of shaping parts and object by mechanical deformation. Many efforts had been focused on micro-forming, in particular the deep drawing process, because of the method’s ability to produce an extensive variety of products, particularly in its conventional macro-process. This method is used to create the majority of everyday items. Although efforts were made to develop micro-forming for industrial use, the technique was deemed to be insufficiently advanced. Much development effort was required, in particular, to design a completely computerized high-extent production micro-forming machine that is dependable and ready to perform always in terms of procedures, material handling, and tooling to assure effective micro-product production. Micro forming, which is discussed in this work, is also one of the often-used micro-forming methods in deforming procedures. Finally, in addition to continuing to improve micro forming, this study aims to investigate the essential methods of the Limit dome height test, Nakajima test, M K Model test, and deep drawing processes and their major concerns in a systematic manner.
Detailed Overview on POLYMATH Software for Chemical Engineering Analysis
Abdulhalim Musa Abubakar, Bello Iliyasu, Zakiyyu Muhammad Sarkinbaka
J. Engg. Res. & Sci. 1(3), 133-147 (2022);
It is pertinent to highlight areas POLYMATH software is useful for chemical engineering analysis. Its applications had been demonstrated in this paper using 10 Problem Set, in areas that includes transport phenomena, heat transfer, reaction, and bioreaction kinetics to solve differential equations, nonlinear equations, simultaneous linear equations, graphical representation and regression problems arising in these fields using Licensed POLYMATH Software Version 6.10.261. POLYMATH is mostly used by students, teachers and researchers for educational purposes, but however limited in application by engineers in process industries, as more sophisticated softwares are preferred. Incorporating many solution approaches there in the literature for solving mathematical method problems, especially the newly proposed novel Extended Runge-Kutta Method of Order 6 into POLYMATH and the enabling of log-log plots is hereby recommended.
Experimental Methodology to Find the Center of Gravity of a Solid
Joohoon Je, Eunsung Jekal
J. Engg. Res. & Sci. 1(3), 148-152 (2022);
The center of gravity of a three-dimensional object found through an experimental method can be made easier and faster than calculating the movement manually to make it look more natural in graphic computer images. In addition, in various sports such as skating, the score can be increased by appropriately moving the position of the center of gravity. Lastly, it is expected that it can be used even when the performance is high in the manufacturing process to increase the stability and speed of various means of transportation (eg, automobiles, airplanes, etc.).
Disinfecting Omnidirectional Mobile Robot with Vision Capabilities
Waqas Qaisar, Muhammad Tanveer Riaz , Abdul Basit, Yasir Naseem, Zohaib Nazir
J. Engg. Res. & Sci. 1(3), 153-163 (2022);
The disinfecting mobile robot with omnidirectional movement is a vision-capable robot that uses image processing to follow a dedicated path regardless of the change in direction required and uses Ultraviolet rays from the UV light tubes to disinfect everything in its path and disinfect the entire room. The basic premise of the project in this paper is the principle of designing a mobile robot that has high mobility and can move in every direction to follow a dedicated path that can be used to disinfect certain places that are not feasible for human beings. This proposed project is an omnidirectional mobile robot that will be designed such that it will use controllers, a camera for image processing to avoid any obstacle in its path, and actuators all communicating with one another to rotate the wheels of the robot individually to achieve the desired linear and rotatory motion to avoid any obstacles in the path of the robot and clean all the bacteria and germs in the room that might be harmful to humans. All of these components work through feedback which is being given through an encoder to achieve the desired output motion of the robot. The main benefit of this disinfecting mobile robot will be its increased mobility due to the combined effect of its rotatory and linear motion. This increased mobility combined with a set of ultraviolet light rays and a camera in the front which uses image processing to detect any object in its path and avoid it to disinfect an entire targeted area and allow it to access areas where conventional robots and humans can’t go.
Cascaded Keypoint Detection and Description for Object Recognition
Abdulmalik Danlami Mohammed, Ojerinde Oluwaseun Adeniyi, Saliu Adam Muhammed, Mohammed Abubakar Saddiq, Ekundayo Ayobami
J. Engg. Res. & Sci. 1(3), 164-169 (2022);
Keypoints detection and the computation of their descriptions are two critical steps required in performing local keypoints matching between pair of images for object recognition. The description of keypoints is crucial in many vision based applications including 3D reconstruction and camera calibration, structure from motion, image stitching, image retrieval and stereo images. This paper therefore, presents (1) a robust keypoints descriptor using a cascade of Upright FAST -Harris Filter and Binary Robust Independent Elementary Feature descriptor referred to as UFAHB and (2) a comprehensive performance evaluation of UFAHB descriptor and other state of the art descriptors using dataset extracted from images captured under different photometric and geometric transformations (scale change, image rotation and illumination variation). The experimental results obtained show that the integration of UFAH and BRIEF descriptor is robust and invariant to varying illumination and exhibited one of the fastest execution time under different imaging conditions.
Biodigester and Feedstock Type: Characteristic, Selection, and Global Biogas Production
Abdulhalim Musa Abubakar
J. Engg. Res. & Sci. 1(3), 170-187 (2022);
This work aims at providing factual details necessary for the utilization of diverse feedstock for anaerobic digestion (AD) to produce biogas using either conventional or non-conventional types of digesters. This is necessary as different substrates had peculiar merits or potentials of biogas production due to their unique characteristics. Selection of right feedstock is usually based on sustainability, quantity, output requirement, availability and metallic nutrient content apart from digester type which is affected by the weather condition of the location among other factors. Global biogas production is increasing annually, especially in areas of biogas utilization for electricity generation, heating and fuel for transportation.
Length-Weight Relationships (LWRs) and Condition Factor of Seven Fish Species in River Nyangweta Tributary, Kenya
Fredrick Mang’era Ondemo, Albert Getabu, Zipporah Gichana, Job Ombiro Omweno
J. Engg. Res. & Sci. 1(3), 193-199 (2022);
Length-weight relationships (LWRs) and condition factors are important for effective management of riverine fisheries. This study investigated the LWRs and condition factors of the dominant fish species from Nyangweta tributary of River Kuja, in Lake Victoria Catchment, Kenya. A total of 615 fish of seven dominant species were analyzed: Enteromius altianalis, Enteromius neumeyeri, Clarias theodorae, Labeo victorianus, Labeobarbus altianialis, Chiloglanis species and Amphilias jacksonii. The fish were sampled from five locations from October 2020 to March 2021. The length and weight measurements were taken using a measuring board and an electronic balance respectively and used to determine Fulton’s (KF) and allometric (Ka) condition factors. The largest species was E. altianalis (70.74 ± 8.72g), followed by L. altianialis and L. victorianus with mean body weights of 62.14 ± 3.48g and 56.43 ± 11.26g respectively. With exception of E. altianalis and C. theodorae, the Fulton’s condition factors (KF) of all the species were greater than (1) and not significantly different (p = 0.43) among the species. Majority (four) of the species exhibited positive allometry (Ka > 3), while only one species exhibited isometric (Ka = 3) growth, due to different body profiles which may not allow uniform growth of all individuals of the same species, a large percentage of females in adult fish populations and high nutrient influxes. The LWRs were significant and showed strong linear relationships between total and standard lengths and body weight (p < 0.05, R2 > 0.5). These findings suggest that conservation measures need to be taken to improve the fish health and physiological condition in upstream areas of the Nyangweta tributary.
