Front Cover
Publication Month: January 2022, Page(s): A1 – A1
Editorial Board
Publication Month: January 2022, Page(s): B1 – B1
Editorial
Publication Month: January 2022, Page(s): C1 – C1
Table of Contents
Publication Month: January 2022, Page(s): D1 – D1
Visual Slam-Based Mapping and Localization for Aerial Images
Onur Eker, Hakan Cevikalp, Hasan Saribas
J. Engg. Res. & Sci. 1(1), 1-9 (2022);
Fast and accurate observation of an area in disaster scenarios such as earthquake, flood and avalanche is crucial for first aid teams. Digital surface models, orthomosaics and object detection algorithms can play an important role for rapid decision making and response in such scenarios. In recent years, Unmanned Aerial Vehicles (UAVs) have become increasingly popular because of their ability to perform different tasks at lower costs. A real-time orthomosaic generated by using UAVs can be helpful for various tasks where both speed and efficiency are required. An orthomosaic provides an overview of the area to be observed, and helps the operator to find the regions of interest. Then, object detection algorithms help to identify the desired objects in those regions. In this study, a monocular SLAM based system, which combines the camera and GPS data of the UAV, has been developed for mapping the observed environment in real-time. A deep learning based state-of-the-art object detection method is adapted to the system in order to detect objects in real time and acquire their global positions. The performance of the developed method is evaluated in both single and multiple UAVs scenarios.
Neural Networks and Digital Arts: Some Reflections
Rômulo Augusto Vieira Costa, Flávio Luiz Schiavoni
J. Engg. Res. & Sci. 1(1), 10-18 (2022);
The Constant advancement in the area of machine learning has unified some areas that until then di a of computing with the arts in general. With the emergence of digital art, people have become increasingly interested in the development of expressive techniques and algorithms for creating works of art, whether in the form of music, image, aesthetic artifacts, or even combinations of these forms, usually being applied in an interactive technology installation. Due to their high diversity of creation and complexity during processing, neural networks have been used to create these digital works, which present results that are difficult to reproduce by human hand and are usually presented in museums, conferences, or even at auctions, being sold at high prices. The fact that these works are gaining more and more recognition in the art scene, ended up raising some questions about authenticity and art. In this way, this work aims to address the historical context regarding the advancement of the area of machine learning, addressing the evolution of neural networks in this field, about what art would be and who would be the artist responsible for digital work, given that despite After performing a good part of the creation process, the computer does not perform the entire process, becoming dependent on the programmer, who in turn is responsible for defining parameters, techniques and, above all, concepts that will attribute all the aesthetic value to the work. From this point of view and the growing interest in the generation of art via computers, the present work presents applied research around neural network techniques and how they can be applied in artistic practice, either generating visual elements or generating visual elements or generating sound elements. Finally, perspectives for the future are presented and how this area can evolve even further.
Harmonic and Sequence Component Estimation by a Novel Method
Abinash Rath, Rumpa Saha
J. Engg. Res. & Sci. 1(2), 1-9 (2022);
Power quality monitoring is one of the most important aspects of designing of compensators and other FACTS devices used in the power system. This paper aims at finding the power quality indices from the voltage and current samples of a harmonic polluted grid, by using a newly proposed sample manipulating technique. Here, all the harmonic components of voltage, current, active and reactive powers are estimated along with the total harmonic distortion (THD) of the grid voltage and current waveforms. All the estimations are done using the sample values of the grid voltage and current signals along with only one standard sinusoidal signal of the fundamental frequency where conventional methods require standard signals of all the harmonic frequencies. Hence, the requisite memory space for the proposed scheme is reduced. In addition to that, the rms values of the sequence components in an unbalanced grid is estimated using the sample shifting technique. The proposed techniques are been verified with MATLAB simulation results and a comparative analysis is presented. The proposed method is also verified upon the real-time data extracted from a digital storage oscilloscope (DSO).
Distributed Approach for the Indoor Deployment of Wireless Connected Objects by the Hybridization of the Voronoi Diagram and the Genetic Algorithm
Wajih Abdallah, Sami Mnasri, Thierry Val
J. Engg. Res. & Sci. 1(2), 10-23 (2022);
IoT data collection networks have recently become one of the important research areas due to their fundamental role and wide application in many domains. The establishment of networks of objects is based essentially on the deployment of connected objects to process the collected data and transmit them to the various locations. Subsequently, a large number of nodes must be adequately deployed to achieve complete coverage. This manuscript introduces a distributed approach, which combines the Voronoi Diagram and the Genetic algorithm (VD-GA), to maximize the coverage of a region of interest. The Voronoi diagram is used to divide region into cells and generate initial solutions that present the positions of the deployed IoT objects. Then, a genetic algorithm is executed in parallel in several nodes to improve these positions. The developed VD-GA approach was evaluated on an experimental environment by prototyping on a real testbed utilizing M5StickC nodes equipped with ESP32 processor. The experiments show that the distributed approach provided better degree of coverage, RSSI, lifetime and number of neighboring objects than those given by the original algorithms in terms of the suggested distributed Genetic-Voronoi algorithm outperforms the centralized one in terms of speed of computing.
Bridging the Urban-Rural Broadband Connectivity Gap using 5G Enabled HAPs Communication Exploiting TVWS Spectrum
Habib M. Hussien, Konstantinos Katzis, Luzango P. Mfupe, Ephrem T. Bekele
J. Engg. Res. & Sci. 1(2), 24-32 (2022);
As with previous generations of mobile cellular networks, rural regions are projected to face financial and technological challenges in deploying 5G services. At the time, researchers all around the world are investigating the feasibility of utilizing TV White Spaces (TVWS). TVWS is an underutilized/unused section of television spectrum that might be used as a low-cost alternative to typical licensed wired/wireless broadband networks, as well as to bridge the broadband service availability gap between rural and urban regions. A feasible alternative is to deliver TVWS services via High Altitude Platforms (HAPs) for many developed and developing nations to deliver broadband services to a large proportion of their rural and low-income populations. This article examines the advantages of utilizing TVWS spectrum from HAPs as well as the challenges connected with this type of communication architecture. This article examines the advantages of leveraging TVWS spectrum from HAPs as well as the challenges that come with this type of communication architecture. They distribute messages across a large region while monitoring and optimizing radio resource allocation, owing to their position in the sky and the centralized design of the communication system. The article assesses the performance of such a system using the IEEE 802.22 standard and the ITU-R P.452 free space path-loss model. Moreover, this article pointed out the main challenge of using TVWS spectrum from HAP system.
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).
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);
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.
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.
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.
Image Processing and Data Storage for Fire Alarm
Muhammad Zia ur Rahman, Saba Waseem, Sidra Riaz, Zainab Riaz, Aneeq Asif, Ayesha Saddiqa, Ali Asghar
J. Engg. Res. & Sci. 1(4), 87-92 (2022);
This paper explains the algorithm for fire alarm for the purpose of safety from any loss and property damage. Here, the designed algorithm is for the comparison of captured pictures. The purpose of comparison is to validate our results. In captured pictures, there may exist fire colour in pictures, which is the indication of fire in that specific area. Captured pictures are stored in folder and its path is stored in excel. We observed the indication of fired picture through fire alarm. When the fire is diminished, we used to reset button to stop the buzzer and to monitor the system again. The path of those pictures as well as the time and date of captured pictures will remain store in excel for later study of the failure of the system and also for the record purposes.
Human-Computer Interaction for Older Adults – a Literature Review on Technology Acceptance of eHealth Systems
Awais Ahmad, Peter Mozelius
J. Engg. Res. & Sci. 1(4), 119-126 (2022);
The population of older adults globally increased during the last couple of decades. Due to these demographic changes, the need for medical care has also significantly increased. Despite the age-related disabilities and chronic diseases, most older adults prefer independent living in their home environment. Technology-enhanced systems and eHealth applications seem to provide some promising solutions for older adults’ well-being and independent living. However, the adoption and acceptance of these applications for older adults are unclear and further research is needed in this area. This study was carried out as a literature review, to meet the aim of identifying and discussing important factors in the Human-computer interaction of eHealth for older adults. The overall research question for this study was: What are the critical factors to consider for an improved human-computer interaction in technology-enhanced health care systems for older adults? Findings indicate some important factors to address: personal integrity, trust, technology acceptance, accessibility of ICT and eHealth literacy. If the presented factors are considered and addressed, it would be easier to achieve the desired aim of independent living. The authors recommend a human-computer interaction that is older adults centred, with the involvement of older adults users in the design process. Proper education and training on the use of eHealth services are also of great importance. Finally, the technology-enhanced system should also provide good social and technological support to the users.
Determining the Parameters of the Sine-Wave Filter Factors Affecting Filtration Quality
Pustovetov Mikhail
J. Engg. Res. & Sci. 1(4), 127-136 (2022);
The paper deals with proposals for the procedure of selecting the parameters of the sine-wave filter in case of increased voltage frequency (400—600 Hz) on the output of frequency converter, which is an element of power supply system. Author describes in article the structure of the power supply system for an unmanned underwater vehicle, which contains a sine-wave filter connected to frequency converter output. The system’s simulator has a block structure. As blocks previously developed computer models of electrical devices (transformer, autonomous voltage inverter, L-shaped filter, rectifier) are used. The subject of sine-wave filter output voltage quality and contribution to this of input voltage’s modulation index is also described at 100—200 Hz.
MC-SPWM and MC-THIPWM Methods for Symmetric and Asymmetric Design of CHB-MLI: A Study
Jigneshkumar Patel, Vijay Sood
J. Engg. Res. & Sci. 1(4), 148-160 (2022);
Cascaded H-bridge multilevel inverters (CHB-MLI) are employed in a variety of medium/high power applications. These inverters are known to inject unwanted harmonics into the grid, which negatively affects the grid and connected loads. CHB-MLI topology can reduce many of these harmonics by producing multiple output voltage levels and improves the fundamental component using a suitable modulation technique. However, the CHB-MLI topology configuration requires multiple isolated input sources which must be balanced either with the modulation technique or with an additional method. This paper analyzes multi-carrier pulse width modulation (MC-PWM) techniques for CHB-MLIs. In this study, two basic configurations of CHB-MLI symmetrical and asymmetrical are reviewed, followed by their mathematical analysis. Also, this paper analyses multi-carrier based sinusoidal pulse width modulation (MC-SPWM) and multi-carrier based third-harmonic injected pulse width modulation (MC-THIPWM) techniques with phase-shifted (PS) and level-shifted (LS) carrier arrangements for the CHB-MLI. Moreover, a simulation study has been conducted using MATLAB Simulink to analyze the performance of MC-PWM techniques for the symmetrical and asymmetrical type CHB-MLIs. The 7-level and 9-level CHB-MLIs were evaluated for the stated MC-PWM techniques in terms of harmonics and fundamental components. In addition, discharging current of all input sources was checked to verify the ability of all MC-PWM techniques to balance all input sources.
An Extreme Learning Machine for Blood Pressure Waveform Estimation using the Photoplethysmography Signal
Gonzalo Tapia, Rodrigo Salas, Matías Salinas, Carolina Saavedra, Alejandro Veloz, Alexis Arriola, Steren Chabert, Antonio Glaría
J. Engg. Res. & Sci. 1(4), 161-174 (2022);
Pressure (BP) waveform is a result of the response of the arteries to the blood ejectionproduced by tant indicator of the state of the cardiovascular system. Currently, its measurement is performed invasively in critically ill patients who need a continuous and real time monitoring of their treatment response, however, it is possible to measure the BP, continuously and non-invasively, in non-critical patients to detect, monitor and control possible hypertensive events. Nevertheless, current non-invasive techniques can cause discomfort in patients and they are not used in critically ill patients. Consequently, non-Invasive and minimally-Intrusive methodologies (nImI) are required to estimate BP and its waveform. In the current study, the performance of machine learning algorithms, specifically the Extreme Learning Machine (ELM) algorithm, is evaluated to estimate both Blood Pressure and its waveform from the Photoplethysmography (PPG) signal and its first derivative’s (VPG) waveforms. A total of 15 healthy volunteers participated in this study. They performed two handgrips, which is isometric maneuver to induce controlled BP rises. The first handgrip is used to train ELM and the second handgrip is used to test the ELM. Our results show that there are high correlation performances (0.98) between the estimated and measured BP waveforms, and a relative error of 3.3 1.4%. An arterial volume-clamp at the middle finger is used as the gold-standard measurement. Meanwhile, BP extreme values estimations, Systolic BP (SBP) and Diastolic BP (DBP), are also performed. ELMs have a performance with an average RMSE of 5.9 ± 2.7 mmHG f and 4.8 ± 2.0 mmHg for DBP and, an average relative error of 5.0 ± 2.7% for SBP and 7.0 ± 4.0% for DBP.
A Deep Reinforcement Learning Approach to Eco-driving of Autonomous Vehicles Crossing a Signalized Intersection
Joshua Ogbebor, Xiangyu Meng, Xihai Zhang
J. Engg. Res. & Sci. 1(5), 25-33 (2022);
This paper outlines a method for obtaining the optimal control policy for an autonomous vehicle appro med that traffic signal phase and timing information can be made available to the autonomous vehicle as the vehicle approaches the traffic signal. Constraints on the vehicle’s speed and acceleration are considered and a microscopic fuel consumption model is considered. The objective is to minimize a weighted sum of the travel time and the fuel consumption. The problem is solved using the Deep Deterministic Policy Gradient algorithm under the reinforcement learning framework. First, the vehicle model, system constraints, and fuel consumption model are translated to the reinforcement learning framework, and the reward function is designed to guide the agent away from the system constraints and towards the optimum as defined by the objective function. The agent is then trained for different relative weights on the travel time and the fuel consumption, ults are presented. Several considerations for deploying such reinforcement learning-based ents are also discussed.
PWM Controlled Bidirectional Converter having Load-Independent Voltage-Gain
Muhammad Tanveer Riaz, Umar Saeed, Saba Waseem, Sidra Riaz, Eman Manzoor Ahmed
J. Engg. Res. & Sci. 1(5), 34-40 (2022);
The power balancing is the issue that creates when voltage fluctuations occur in the DC microgrid. In order to compensate for the DC bus voltages in the DC microgrid, the energy storage system is used. This system absorbs or releases the power to make the DC bus voltages is stable. In this research, a bidirectional series resonant (BSR) converter is proposed which operates at the fixed frequency for the energy storage system. A simple PWM control technique is used for the power flow regulation in the system. The gain voltage of the BSR converter depends only on the duty cycle of the applied voltage and does not change the direction and amplitude of the power flow. Theoretically, after the calculations, the gain voltage of the BSR converter changed from minimum (zero) to maximum (unlimited) which means the designed converter is a buck-boost converter as well. This property of the BSR converter will help the researcher to use a wide range of voltage applications. The operations mode i.e. forward and backward modes, and the direction of the power flow can be changed smoothly by Pulse Width Modulation control. Zero voltage switching for all the voltage ranges of the active switches is also achieved in this research.
Comparative Analysis of Scheduling Algorithms in 5G Uplink Transmission
Maryam Imran Sheik Mamode, Tulsi Pawan Fowdur
J. Engg. Res. & Sci. 1(5), 41-51 (2022);
5G is the successor to 4G technology and it has enabled a new level of user experience with much greater speeds and much lower latencies. Scheduling is the method of allocating resources for transmission of data. In this paper, three scheduling algorithms have been investigated, namely Proportional Fair, Round Robin and Best CQI. An uplink 5G system with one base station and four user equipment were used to evaluate the three algorithms by varying four sets of parameters. Simulation results showed that the Round Robin algorithm was the fairest of all three algorithms by displaying almost similar resource share percentage for the four user equipment. Proportional Fair algorithm was observed to yield a higher throughput than the Round Robin algorithm for a specific user in some cases. It offered a better trade-off between throughput and fairness. In the case where distance of user 1 from the base station was 100m, the system simulated with the proportional fair technique yielded a peak throughput 30% higher than the system simulated with Round Robin technique. On the other hand, the Best CQI algorithm displayed a peak throughput value about 35% higher than the proportional fair algorithm for the 100m distance case. The Best CQI algorithm was found to be the least fair of all three algorithms as it favored users with better channel conditions.
Impact Analysis of Duck Curve Phenomena with Renewable Energies and Storage Technologies
Giovani Manuel Pitra, Kameswara Subrahmanya Sastry Musti
J. Engg. Res. & Sci. 1(5), 52-60 (2022);
When higher quantities of solar energy is injected into power grid, then it is likely to result in what is known as “Duck curve phenomena”. The net load under this phenomenon is negative and thus energy generation needs to be curtailed during the peak hours and also a part of the load during off-peak hours cannot be met. Due to several economical and technical challenges, the environmentally friendly solar energy source will be switched-off during the peak hours. Analyzing the impact of duck curve on a system can be challenging. This paper presents a novel methodology to analyze the duck curve phenomena and to mitigate its effects. The proposed methodology requires two popular, open source software tools – IRENA FlexTool and System Advisory Model (SAM). SAM is used to obtain the data for solar energy production and FlexTool is used carryout the optimal energy dispatch. A 4-bus power system is considered with base load plants, renewable energy sources and energy storage facilities. Then the proposed methodology is applied on this system to analyze the impact of duck curve to demonstrate the effectiveness of both the methodology and the open-source tools.
Optimization of Proportional Solenoid for Flow Control Valve using Recursive Method in OCTAVE and FEMM
Tom Thampy, Emmanuel Gospel Raj Rivington, Rajath Chandrashekar
J. Engg. Res. & Sci. 1(5), 61-70 (2022);
Proportional solenoid valves are used in various applications that require smooth control of flow or pressure. Manufacturing such valves would involve design of valve component, solenoid core and the coil for specific input and output ratings. Materials for each component of the solenoid valve need to be selected for their magnetic properties, application specific requirements such as medical grade, temperature compatibility, etc. With proportional control as the primary objective, the proportional solenoid valve must exhibit linear characteristics between the control input and the output. Optimization of the magnetic core plays a vital role in achieving these requirements. Optimizing the core geometry of the proportional solenoid is crucial in achieving necessary linearity in the plunger movement without compromising the actuating force on the plunger for a given size of the solenoid. A proportional solenoid valve for mass flow control in low pressure application such as medical oxygen ventilators is developed based on the performance requirements such as flow rate, pressure and control requirements such as the solenoid voltage and current ratings. The materials used for manufacturing the valve components such as medical grade stainless steel with required magnetic properties are selected based on the application requirements. An optimization technique based on recursive method is used to determine the efficient core geometry for a proportional solenoid valve. The experimental results obtained from the proportional solenoid valve manufactured based on optimization results closely matched with the calculated values of plunger displacements from different offsets of 0 mm, 1 mm and 2 mm from the reference position in a total stroke length of 5 mm, which is presented in this paper.
Electrochemical Desalination Test of Bricks as a Building Material for Historical Buildings in Japan
Risako Fukami, Toshiya Matsui
J. Engg. Res. & Sci. 1(5), 79-87 (2022);
Brick buildings and structures are often exposed to outdoor condition, and deterioration of the bricks due to salt weathering caused by the surrounding environment has been reported in various parts of Japan. In Japan, not only the preservation of cultural properties but also their utilization is currently being promoted, and the beauty of brick surfaces is at a stage where it is becoming more important. For these reasons, a simple, low-cost, easily installed desalination model to desalinate only those areas where salt weathering was observed as first aid of deteriorated bricks was created. Powdered cellulose and copper plates were used as electrodes and these materials are readily available and easy to handle for professionals of conservation science as well as non-professionals. The aim of the research presented in this paper was twofold: to investigate the desalination effect of a simple electrochemical desalination model and to obtain knowledge for practical tests by conducting experiments under different energization conditions and observing the surface of the bricks after energization. Na2SO4 solution was used in the experiments and the brick samples containing Na2SO4 were used for desalination test by energizing for 8 days and sample exposure test after energization. When powdered cellulose and copper plates were used as electrodes, it was found that when sufficient water was supplied, approximately 64% of sulfate ions in the brick sample were removed when the energization conditions were 5 V and 0.5 A and 73% of sulfate ions were removed when the energization conditions were 5 V and 1 A. Visual observation confirmed that this removal rate suffices in preventing salt precipitation after energization is applied. This desalination method is expected to be suitable for Japanese historical bricks, which have varied characteristics, because it is possible to adjust the amount of water supplied during the energization by using an easily removable powdered cellulose for the electrode, and desalination can be performed without damaging the brick surface. However, it was found that the black areas consisting mainly of Cu2O were formed after the 8-day energization. Since the efficiency of desalination from this area to the anode may be low, this remains a challenge for the future.
Layer Based Firewall Application for Detection and Mitigation of Flooding Attack on SDN Network
Yubaraj Gautam, Kazuhiko Sato, Bishnu Prasad Gautam
J. Engg. Res. & Sci. 1(5), 88-101 (2022);
Software-Defined Networking (SDN) is an emerging Network technology that can augment the data plane with control plane by using programming technique. However, there are a numbers of security challenges which are required to address to achieve secured communication. Flooding attack is one of the most common threats on the internet for the last decades which is becoming the challenging issues in SDN networks too. To address these issues, we proposed a novel firewall application developed based on the multiple stages of packets filtering technique to provide flooding attack prevention system and layer-based packets detection system. In this research, we are using two main stages to detect the flooding attack and mitigate the flooding packets. The first stage is to identify the attacks and, the second stage is to identify the attacker’s information and act them based on layer-based packet header entity. The system contains two security entities to identify the flooding attacks, one is by measuring the packet size, and the other is by counting the packets flow. We used the details of packets flow to control over the flow and to identify the attacks being occurred or not. Along with, to identify the attacker’s information, we used layers (layer 2 to layer 4) based packet header entities by using multi-table architecture. The proposed solution was tested for different attack scenarios and successfully reduced the flow of volume-based bulk-size flooding attack and infinite packets flooding attack in SDN network.
Loaded by RL-Branch EMC Filter on the Output of the Inverter Transfer Function Taking into Account Resistances and Electric Transformer’s Transfer Function Derivation
Pustovetov Mikhail
J. Engg. Res. & Sci. 1(5), 102-108 (2022);
The derivation of the transfer function of the output filter of the electromagnetic compatibility of the inverter, loaded by RL-branch, proposed, which differs by taking into account the presence of resistances in the longitudinal and transverse branches of the L-shaped filter. The form of recording the voltage transfer function of an electrical transformer loaded by RL branch presented. A method for deriving the transfer function from the equations of the mathematical model of a single-phase two-winding transformer proposed. The transfer function derivation has made on T-shaped equivalent circuit of transformer basis, and takes into account the presence of resistance in the transformer windings, the winding connection group. To author’s opinion, results can be useful in the design of control systems and their mathematical models for electrical complexes, which include a sine-wave filter or a dv/dt filter and transformer.
Offline Signature Verification based on Edge Histogram using Support Vector Machine
Sunil Kumar Dyavaranahalli Sannappa, Kiran, Sudheesh Kannur Vasudeva Rao, Yashwanth Jagadeesh
J. Engg. Res. & Sci. 1(5), 160-166 (2022);
Investigation on verification of offline signature has explored a huge sort of techniques on more than one signature datasets, which can be amassed beneath managed conditions. However, these records will not necessarily reflect the characteristics of the signatures in some useful use cases. In this work, introduced a novel feature representation technique called edge histogram and 4 directional histograms for offline signature verification system. For classification of signature support vector machine (SVM) technique employed. Edge is a curve or point where the intensity of an image changes rapidly. Edges represent the boundary of object of an image. Edge detection is a process of detecting edges of an image. Several algorithms are available to detect edges effectively from an image. Canny, Roberts, Prewitt and Sobel are several popular available edge detectors.
Competency Manifestation Clues within Interactions in Computer Mediated Communication
Hocine Merzouki, Nada Matta, Hassan Atifi, Francois Rauscher
J. Engg. Res. & Sci. 1(5), 167-178 (2022);
The notion of competence is multidimensional and polysemic. Several definitions of this notion are present in the literature according to disciplines such as industry, sociology, management, psychology, etc. It often refers to the experience, knowledge, abilities, skills, behaviors, and attitudes that allow valuable action in a workplace. Beyond its intrinsic value for the individual, competence is considered in organizations as an intangible asset whose mere possession often provides very considerable competitive advantages. The manifestation of competence takes several forms and the methods of its evaluation differ, ranging from quantitative approaches to social recognition. The approach that we have developed is based on the hypothesis that interacting individuals emphasize the components of their functional competencies according to the activity they carry out and the context that surrounds it. We chose pragma-linguistic, which permits us a more in-depth analysis in comparison to statistical analysis based on text-mining or data-mining techniques that are insufficient for an accurate detection of competence. For that purpose, we have proposed an interaction analysis methodology based on natural language processing techniques to find language elements that highlight the clues of the manifestation of the competence in computer mediated communications. We have developed and implemented two algorithms for the detection and analysis of competence that we have applied to interactions from the “Ubuntu” corpus of the community of interest of the same name which deal with Ubuntu operating system issues. The results of the application of our approach are presented and discussed in this paper.
Barriers of the Green Supply Chain Management Implementation: A Benchmark of Studies of Analytic Hierarchy Process and Interpretive Structural Modeling
Hamza Fahmy, Mohamed Mazouzi, Ayoub Alami Masmoudi, Tamasna El Mehdi
J. Engg. Res. & Sci. 1(5), 223-230 (2022);
Because firms are considering the influence of their operations on the environment, the green supply chain has become a crucial indication of corporate performance. The issues here necessitate both competent management and a fresh, innovative strategy for cost reduction, productivity enhancement, and natural resource protection. We shall try to understand the Barriers of Green Supply Chain Management concept in this report. A total of 47 obstacles were discovered after a thorough review of the literature. Priority ranking stability is investigated via a sensitivity analysis. Using existing models have mostly focused on identifying these constraints.
An Analysis of SiC Power Electronics Implementation in Green Energy Based Extremely Fast Charging
Naireeta Deb, Rajendra Singh
J. Engg. Res. & Sci. 1(5), 231-242 (2022);
Existing extremely fast charging (XFC) of electrical vehicles (EVs) is based on silicon power electronics and internal conversion of AC power into DC power. In this paper it has been shown that silicon carbide power electronics and the use of DC power source in the design of XFC of EVs has many distinct advantages over current XFC of EVs. Silicon carbide power electronics provide reduction of charging time, higher power conversion efficiency, size reduction of heat sink and improved battery’s state of health. The use of larger size silicon carbide wafers will further reduce the cost of power electronics based on silicon carbide. Use of green energy sources (solar and wind) and lithium-ion batteries for electrical power storage can provide end to end DC power network. Such networks combined with silicon carbide based XFC of EVs can play a revolutionary role in saving green electrical and provide reduced of charging of EVs. This paper reports almost 50% reduction in power losses by using Silicon Carbide DC technology. End to end DC power networks combined with SiC based XFC of EVs can play a revolutionary role in solving climate emergency.
Machine-Learning based Decoding of Surface Code Syndromes in Quantum Error Correction
Debasmita Bhoumik, Pinaki Sen, Ritajit Majumdar, Susmita Sur-Kolay, Latesh Kumar KJ, Sundaraja Sitharama Iyengar
J. Engg. Res. & Sci. 1(6), 21-35 (2022);
Errors in surface code have typically been decoded by Minimum Weight Perfect Matching (MWPM) bas -based Machine Learning (ML) techniques have been employed for this purpose, although how an ML decoder will behave in a more realistic asymmetric noise model has not been studied. In this article we (i) establish a methodology to formulate the surface code decoding problem as an ML classification problem, and (ii) propose a two-level (low and high) ML-based decoding scheme, where the first (low) level corrects errors on physical qubits and the second (high) level corrects any existing logical errors, for various noise models. Our results show that our proposed decoding method achieves ~10x and ~2x higher values of pseudo-threshold and threshold respectively, than for those with MWPM. We also empirically establish that usage of more sophisticated ML models with higher training/testing time, do not provide significant improvement in the decoder performance.
Identification of Basic Respiratory Patterns for Disease-related Symptoms Through a Microphone Device
Amol M Khatkhate, Varad Raut, Madhura Jadhav, Shreya Alva, Kalpesh Vichare, Ameya Nadkarni
J. Engg. Res. & Sci. 1(6), 36-44 (2022);
The research in this paper focuses on the capture of respiratory patterns in real-time through a minor modification of an anti-snoring device that is readily available off the shelf or can be bought online and attaching a microphone to it. The audio pattern is recorded for the various lung conditions at different stages. The data recorded is generated in graphical form to understand the pattern. The setup for recording and generating data patterns is explained in the paper. The procedure for using the device and gathering data is mentioned in detail in this paper and sample raw data is presented for researchers. The purpose of this device is easy data collection and interpretation for self-diagnosis of the anomalies in the breathing pattern through audio data and display of the patterns in smartphone applications that can further be investigated by a physician.
Acceleration of Image Processing with SHA-3 (Keccak) Algorithm using FPGA
Argyrios Sideris, Theodora Sanida, Dimitris Tsiktsiris, Minas Dasygenis
J. Engg. Res. & Sci. 1(7), 20-28 (2022);
In our digital world, the transmission of images between people has played an essential part in every cedures to ensure the integrity and accuracy of the communicated data are required. Today, hashing is the most popular and secure way. This article focuses on the SHA-3 for hashing images dimensions 256 256 pixels with our custom implementations on the FPGA based on the Very High Speed Integrated Circuit Hardware Description Language (VHDL). We perform our experiments on the Intel Arria 10 GX FPGA and the Nios II processor. Also, our experiments with calculating metrics such as entropy, NPCR and UACI show that the SHA-3 is secure, reliable and has high application potential for hashing images. We propose designs to improve throughput, security, and efficiency criteria. We strengthened our design using the IP Block Floating Point Hardware 2 (FPH-2). Our experiments with the proposed implementation have shown increased throughput by 14.38% and efficiency by 13.95% of the SHA-3 algorithm. Finally, we compared our findings to other researchers’ existing optimization methodologies, giving data that demonstrate our research’s strengths.
Research on Feature Extraction Method of Fiber Bragg Grating Vibration Monitoring Based on FFT
Mengxing Zhang, Youming Hua, Chunbin Chen, Chenkun Chu, Xiuli Zhang
J. Engg. Res. & Sci. 1(7), 44-47 (2022);
Optical fiber is used in various fields because of its advantages of large-capacity communication, long-distance transmission, low signal crosstalk, good confidentiality, anti-electromagnetic interference, good transmission quality, small size, light weight, and long life. In this paper, the latest research progress of optical fiber sensing technology and its application and development in the field of rotating parts are summarized, and the characteristics and working principles of optical fiber intelligent composite materials are introduced. Fast Fourier Transform (FFT) and Hilbert fringe spectra are then applied to frequency component analysis. Quantitative research is carried out on the variation of the frequency components in each frequency band of the vibration signal of the damaged and non-damaged rotating parts. The method can analyze the fault signal to achieve the purpose of accurately extracting the fault characteristics of the rolling bearing, which plays an important guiding role in the accurate diagnosis of the bearing fault.
Use of Uncertain External Information in Statistical Estimation
Sergey Tarima, Zhanna Zenkova
J. Engg. Res. & Sci. 1(8), 12-18 (2022);
A product’s life cycle hinges on its sales. Product sales are determined by a combination of market demand, industrial production, logistics, supply chains, labor hours, and countless other factors. Business-specific questions about sales are often formalized into questions relating to specific quantities in sales data. Statistical estimation of these quantities of interest is crucial but restricted availability of empirical data reduces the accuracy of such estimation. For example, under certain regularity conditions the variance of maximum likelihood estimators cannot be asymptotically lower than the Cramer-Rao lower bound. The presence of additional information from external sources therefore allows the improvement of statistical estimation. Two types of additional information are considered in this work: unbiased and possibly biased. In order to incorporate these two types of additional information in statistical estimation, this manuscript minimizes mean squared error and variance. Publicly available Walmart sales data from 45 stores across 2010-2012 is used to illustrate how these statistical methods can be applied to use additional information for estimating weekly sales. The holiday effect (sales spikes during holiday weeks) adjusted for overtime trends is estimated with the use of relevant external information.
CRESustain: Approach to Include Sustainability and Creativity in Requirements Engineering
Clara Silveira, Vitor Santos, Leonilde Reis, Henrique Mamede
J. Engg. Res. & Sci. 1(8), 27-34 (2022);
Requirements Engineering is an evolving field facing new challenges. One of the central conundrums is sustainability in software. The possibility of using known creativity techniques while introducing the dimensions of sustainability to help provide unexpected, original, practical, and sustainable answers in software development is challenging and motivating. This paper proposes an approach, CRESustain, incorporating sustainability dimensions when introducing creativity techniques in the Requirements Engineering process. CRESustain uses various creativity techniques considered appropriate for the different stages of the RE process. It is inspired by the Sustainable Development Goals, creative problem-solving methods, and the Karlskrona Manifesto. The methodology applied to give materiality to the outcome of this work was Design Science Research, a research paradigm that uses knowledge to solve problems, generate new knowledge and insights, and results in an artefact. The main results indicate that the approach stimulates discussion about sustainability in technical, economic, social, human, and environmental dimensions focusing on the Sustainable Development Goals and people’s needs.
CANClassify: Automated Decoding and Labeling of CAN Bus Signals
Paul Ngo, Jonathan Sprinkle, Rahul Bhadani
J. Engg. Res. & Sci. 1(10), 5-12 (2022);
Controller Area Network (CAN) bus data is used on most vehicles today to report and communicate sensor data. However, this data is generally encoded and is not directly interpretable by simply viewing the raw data on the bus. However, it is possible to decode CAN bus data and reverse engineer the encodings by leveraging knowledge about how signals are encoded and using independently recorded ground-truth signal values for correlation. While methods exist to support the decoding of possible signals, these methods often require additional manual work to label the function of each signal. In this paper, we present CANClassify — a method that takes in raw CAN bus data, and automatically decodes and labels CAN bus signals, using a novel convolutional interpretation method to preprocess CAN messages. We evaluate CANClassify’s performance on a previously undecoded vehicle and confirm the encodings manually. We demonstrate performance comparable to the state of the art while also providing automated labeling. Examples and code are available at https://github.com/ngopaul/CANClassify.
Assessment of Village-wise Soil Nutrients and their Effect on Sugarcane Productivity in Western Maharashtra, India
Chhaya Narvekar, Madhuri Rao
J. Engg. Res. & Sci. 1(10), 19-25 (2022);
Soil fertility needs to be assessed to develop strategies for long-term agricultural productivity. A study has been undertaken at Shirol tehsil, Kolhapur district, Maharashtra state, India to evaluate the fertility status of soil using nutrient index approach. For the present study PH, organic carbon, and EC were chosen as potential markers of soil quality along with primary nutrient potash and phosphrous. Objectives of this research are i)To provide nutrient availability index, ii) To assess soil fertility status and sugarcane productivity in the study area. Based on the soil parameters analysis, it is found that the soil is fertile. Sugarcane is the most cultivated crop in this area and the productivity of sugarcane is observed to be higher in study area as compared to national productivity. The nutrient index values for PH, Organic carbon and Phosphorous were normal, EC was low, and Potash was high. It is also observed that all ten years of study potash is high. Productivity change as well as nutrient values change over a period of time tested with standard t- test approach.
Trajectory Correction Method of Motion Description Language of Vertebral Milling Robot based on Force Feedback
Wei Ding, Zhaoming Liu, Hongwei Wang, Long Cui
J. Engg. Res. & Sci. 1(10), 26-35 (2022);
In the real-time control procession of the vertebral milling robot, there are problems such as heavy workload of the operator, long working time, operational tremble and complicated procession. In order to solve the clinical practical basic problems such as avoiding excessive milling and force perception control of vertebral milling robot, this paper proposes a method of trajectory correction of motion description language of milling robot based on force feedback. The task of trajectory correction of the milling robot oriented to force feedback, on the basis of ensuring the atom relationship of motion description language, defines seven motion atoms for the function of avoiding excessive milling during the actual operation of the milling robot. A milling robot experimental system is built with a force feedback control handle and a milling robot. Experiments are carried out on the trajectory correction method of the milling robot based on the motion description language. The experimental results verify the feasibility and effectiveness of this method. The innovation of this paper is reflected in the following two aspects. The use of force feedback to define and model motion description language atoms is an innovation, and the application of motion description language trajectory correction method to the field of vertebral milling robots is an application innovation.
The Current Trends of Deep Learning in Autonomous Vehicles: A Review
Jing Ren, Raymond Ning Huang, Jing Ren, Hossam A. Gabbar
J. Engg. Res. & Sci. 1(10), 56-68 (2022);
Autonomous vehicles are the future of road traffic. In addition to improving safety and efficiency from reduced errors compared to conventional vehicles, autonomous vehicles can also be implemented in applications that may be inconvenient or dangerous to a human driver. To realize this vision, seven essential technologies need to be evolved and refined including path planning, computer vision, sensor fusion, data security, fault diagnosis, control, and lastly, communication and networking. The contributions and the novelty of this paper are: 1) provide a comprehensive review of the recent advances in using deep learning for autonomous vehicle research, 2) offer insights into several important aspects of this emerging area, and 3) identify five directions for future research. To the best of our knowledge, there is no previous work that provides similar reviews for autonomous vehicle design.
Fast Labeled Spanning Tree in Binary Irregular Graph Pyramids
Majid Banaeyan, Walter G. Kropatsch
J. Engg. Res. & Sci. 1(10), 69-78 (2022);
Irregular Pyramids are powerful hierarchical structures in pattern recognition and image processing. They have high potential of parallel processing that makes them useful in processing of a huge amount of digital data generated every day. This paper presents a fast method for constructing an irregular pyramid over a binary image where the size of the images is more than 2000 in each of 2/3 dimensions. Selecting the contraction kernels (CKs) as the main task in constructing the pyramid is investigated. It is shown that the proposed fast labeled spanning tree (FLST) computes the equivalent contraction kernels (ECKs) in only two steps. To this purpose, first, edges of the corresponding neighborhood graph of the binary input image are classified. Second, by using a total order an efficient function is defined to select the CKs. By defining the redundant edges, further edge classification is performed to partition all the edges in each level of the pyramid. Finally, two important applications are presented : connected component labeling (CCL) and distance transform (DT) with lower parallel complexity 𝒪(𝑙𝑜𝑔(𝛿)) where the 𝛿 is the diameter of the largest connected component in the image.
Linking Consumer Innovativeness to the Cryptocurrency Intention: Moderating Effect of the LOHAS (Lifestyle of Health and Sustainability) Lifestyle
Sooyeon Choi, Richard A. Feinberg
J. Engg. Res. & Sci. 1(12), 1-8 (2022);
Cryptocurrency is gaining worldwide recognition. This research examines the role of personality and psychological factors in consumers’ cryptocurrency adoption behavior. 452 samples are collected from U.S consumers and the data are analyzed by PLS-SEM. The findings reveal that consumer innovativeness has a positive influence on the intention to use cryptocurrency and its impact is partially mediated by attitude. The LOHAS lifestyle moderated the influence of consumer innovativeness on the cryptocurrency intention as well as the relation of attitude with the intention. This research provides theoretical and practical implications for the cryptocurrency market.
