Volume 1, Issue 5
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Editorial
Front Cover

Publication Month: May 2022, Page(s): A1 – A1 

Editorial Board

Publication Month: May 2022, Page(s): B1 – B1

Editorial

Publication Month: May 2022, Page(s): C1 – C1

Table of Contents

Publication Month: May 2022, Page(s): D1 – D1

Articles
Visual Slam-Based Mapping and Localization for Aerial Images

Onur Eker, Hakan Cevikalp, Hasan Saribas

J. Engg. Res. & Sci. 1(5), 1-16 (2022);

Fast and nd accurate observation of an area in disaster scenarios such as earthquake, flood and avalanch l 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.

Machine Learning Aided Depression Detection in Community Dwellers

Vijay Kumar, Muskan Khajuria, Anshu Singh

J. Engg. Res. & Sci. 1(5), 17-24 (2022);

Depression is a mental condition that can have serious negative effects on an individual’s thoughts and nd health problems that could lead to grave heart diseases. Depression detection has become necessary in community dwellers considering the lifestyle being followed. Here we use NHANES dataset to compare the performance of various machine learning algorithms in depression detection. The 2015 dataset was used to train the models and testing was done on data from 2017 to analyze the robustness of the model. Feature extraction was also performed on the dataset to observe relevant features. It was found that ADABoost used wit ic Minority Oversampling Technique (SMOTE) gave the best test results in terms of F1 score.

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.

Analyzing the Impact of Challenges in Prefabricated Building Construction Supply Chains

Rishabh Rastogi, Sushil Kumar Solanki, Virendra Kumar Paul

J. Engg. Res. & Sci. 1(5), 71-78 (2022);

Across various barriers pertaining to prefabricated building construction projects, a major barrier identified by the literature was integration of various components of prefabricated building project supply chain network, including the material and human resource supply chains. The literature suggests a need of exploring this barrier of supply chain integration into its various sub factors/challenges (termed as supply chain challenges) with the perspective of prefabricated building construction supply chains. This research tries to fill this gap by analyzing three cases of existing prefabricated building construction supply chains in Indian context with different configurations, geophysical profiles and project typologies. This study gives an understanding of the relationship among supply chain challenges, the variation in their relative impact on project time and cost (within the supply chain and across the different configurations of supply chains), and the underlying causes of these variations.

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.

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.

Humankind and Ubiquitous Autonomous AI: A Symbiotic or Dystopian Interaction? A Socio-Philosophical Inquiry

Michael A. Vidalis, Antonios S. Andreatos

J. Engg. Res. & Sci. 1(5), 109-118 (2022);

The technological revolution in Artificial Intelligence (AI) and Autonomous Robotics is expected to transform societies in ways we cannot even imagine. The way we live, interact, work, and fight wars, will not be like anything witnessed before in human history. This qualitative research paper endeavors to examine the effect of said technological advancements on multiple socio-philosophical planes, including societal structure and ethics. AI mismanagement which we are already beginning to witness, coupled with humankinds’ historical ethical infractions, serve as an awakening call for global action to safeguard humanity; AI ethics ought to be examined through the Social Principle and the Social Contract. A proactive, vigilant stance seems imperative, in order to safeguard misuse, as in the case of robot-soldiers or armed drones, which is a case of amensalism disguised. As technological progress is already interfering with humankind and conscience, and in light of expressed concerns from legal and civil liberties groups, it is imperative to immediately criminalize any research in AI weapons, shumans and the crossbreeding of humans with machines, considering these as crimes against umanity.

Proper use of the Blackboard Learning Management System (LMS) motivates students to engage with their studies but the students within Material Science and Engineering (MSE) often use these LMSs to copy mathematical derivations, scientific information and submit coursework tasks without spending much time interacting with the system. Quantitatively, there is a piece of missing information on how interaction with the Blackboard LMS influences students’ performances. Statistical evaluations were made by using the average times students spent on Blackboard and their final examination grades for their three-year Bachelor’s degree period. There was a linear positive correlation between the time students spent on the LMS and their grades. Observations also show that students engage more with LMS at certain periods within a week. It was recognised that the more students engage with the Blackboard, the more they construct information for themselves. This result provides a quantitative analysis that gives evidence of how time spent on LMS supports students’ learning.

Surface Defect Detection using Convolutional Neural Network Model Architecture

Sohail Shaikh, Deepak Hujare, Shrikant Yadav

J. Engg. Res. & Sci. 1(5), 134-144 (2022);

With the dominance of a technical and volatile environment with enormous consumer demands, this study aims to investigate the advancements in quality assurance in the era of Industry 4.0. For better production efficiency, rapid and robust automated quality visual inspection is developing rapidly in product quality control. Deep neural network architecture is built for a real-world industrial case study to achieve automatic quality inspection built on image processing to replace the manual inspection, and its capacity to detect quality defects is analysed to minimise the errors. The primary goal is to understand the developments in quality inspection and their implications regarding finances, time expenditure, flexibility, and the model’s optimum accuracy-precision compared to manual inspection. As an innovative technology, machine vision inspection offers reliable and rapid inspections and assists producers in improving quality inspection efficiency. The research provides a deep learning-based method for extended target recognition that uses visual data acquired in real-time for neural network training, validation, and predictions. The data made available by machine vision setup is utilised to evaluate error patterns and enable prompt quality inspection to achieve defect-free products. The proposed model uses all data provided by integrated technologies to find trends in data and recommend corrective measures to assure final product quality. As a result, the work in this study focuses on developing a deep convolutional neural networks (CNN) model architecture for defect identification that is also highly accurate and precise and suggests the machine vision inspection setup.

Design and Analysis of Dual Acting Opposed Piston MR Damper

Muhammad Aamish Khan

J. Engg. Res. & Sci. 1(5), 145-153 (2022);

Magnetorheological dampers are dampers filled with magnetorheological fluid, which is controlled by a magnetic field, usually using an electromagnet. Viscosity of MR fluid changes with the application of magnetic field. In this way we can directly change the stiffness and performance of MR damper based on velocity of vehicle and topology of road, thus, providing the improved damping effect. This paper deals with improvement in MR damper design. The design proposed in this paper consists of two pistons with two linear generators in such a way that each piston couples with one linear generator. Both pistons work as opposed pistons, moving directly opposite to each other. This model utilizes six forces converging system to stability, leading to more compactness. Most of the forces including in this system vary with topology of road and velocity of car so leading to better robustness. In addition to this, model proposed is self-actuating and regenerative. Thus, resolves the issue of external power supply and harvests the vibrational force to develop electricity for its running. This model is self-dependent and doesn’t require on board electrical sensors and microprocessors, leading to more reliable MR damper design comprising of least components. There are multiple methods of actuation of MR damper which varies on the basis of structure and assembly, and type of generator used. Both linear and rotary generators can serve the purpose. In this paper linear actuation for this model is analyzed. This paper also deals with structural design and development of the model on the basis of certain parameters.  Simulation and analysis of this model is then performed to assure the effectiveness of design. Solid works is being used for designing the structure of model and MATLAB for vibrational analysis. Simulink interface of MATLAB is used for electronic component analysis.

Survey on Developing a Low Cost System for Taxi Payment

Suleiman Taha, Raed Saeed Mohammad Daraghma

J. Engg. Res. & Sci. 1(5), 154-159 (2022);

In this post, we built a small gadget that can be placed in the front of the cockpit, closer to the driver, and can be accessed by both the taxi driver and the passenger. It is simple to operate since it has a crystal display that displays a wealth of information about both the section cut and the distance’s eventual cost. The piece, which is also the delivery charge, as well as the passenger card’s identification card and other explanatory information, and the system, is equipped with a simple and secure payment method that is based on radio wave technology and is linked to the company database. The payment service and the taxi driver are both connected to the internet via a wireless transmission device, and the person who has the card is stored in a specific financial bank’s database. Because the payment manner is easy, the primary goal of this instrument’s design is to prevent passenger money from being stolen, as well as for the driver, and it is a more pleasant, softer, faster, and safe method to handle.

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.

Evolution in Software Product Lines: Defining and Modelling for Management

Amougou Ngoumou, Marcel Fouda Ndjodo

J. Engg. Res. & Sci. 1(5), 179-185 (2022);

Evolution in Software Product Line (SPL) is claimed when there are changes in the requirements, product structure or the technology being used. Currently, many different approaches have been proposed on how to manage SPL assets and some also address how evolution affects these assets. However, the usefulness, effectiveness and applicability of these approaches are unclear, as there is no clear consensus on what an asset is. In this work, we plan to reduce complexity in SPL evolution management. For this goal, the difficulty is defining and modeling SPL evolution and we expect to propose a flexible way to manage it. However, a large variety of artifacts is considered in SPL evolution studies, but feature models are by far the most researched ones. Feature models are widely used to represent SPLs and have been greatly developed in the Feature-Oriented Reuse Method (FORM). Consequently, in our previous works, after observed that this method has a loose structure since it does not provide guidance to reuse and rigorously analyze its assets, we have extended FORM to FORM/BCS (the Feature Oriented Reuse Method with Business Component Semantics) by enveloping its assets among which feature models with business component semantics. The contribution and the novelty of this work is that, by highlighting formally the concept of software asset and revisiting feature business components, to add new information when analyzing a domain, such as clashing actions. conflicts or undesired interactions between existing features in a product line and new features due to evolution of the product line can be manage in a flexible way.

The increased penetration of renewable energy sources in the distribution system affects the stability and efficiency of the system. To account for the intermittent nature of these sources, distribution network reconfiguration and the integration of custom power devices are important. This paper aims to identify the optimum location of photovoltaic systems and unified power quality conditioners in the distribution system considering economic and technical aspects. Three metaheuristic algorithms namely nondominated sorting genetic algorithm-II (NSGA-II), strength pareto evolutionary algorithm-2 (SPEA2) and multi-objective evolutionary algorithm based on decomposition (MOEA/D) were employed. Furthermore, three hybrid algorithms were developed by dividing the population into two parts. Multi-objective particle swarm optimisation (MOPSO) was applied in the upper part while NSGA-II, SPEA2 or MOEA/D was used in the lower part of the population resulting in three hybrid algorithms: MOPSO-NSGA II, MOPSO-SPEA2, MOPSO-MOEA/D. The simulation was performed on the IEEE-123 Node Test Feeder system using the OpenDSS and MATLAB environment. The performance of the proposed algorithms was compared according to their computation time and performance metrics such as pure diversity, generational distance and spacing. It was found that the hybrid algorithms enhance the convergence of the solutions to the true Pareto front. Combining SPEA2 or MOEA/D with MOPSO also reduced the complexity of the algorithms resulting in a lower simulation time.

Evaluating Project Complexity in Construction Sector in India

Amit Moza, Virendra Kumar Paul, Sushil Kumar Solanki

J. Engg. Res. & Sci. 1(5), 198-212 (2022);

Evaluating complexity, in order to manage it effectively, has been stressed by many researchers as one of the key areas of project management. This, as literature shows, has been done using different methodologies and assessing it from different perspectives resulting in measures that differ in their characteristics, their application, and their relevance with respect to location or typography. Since no such quantitative study with respect to Indian construction sector was found in literature, the aim of this research is, therefore, to develop a model for evaluating complexity in projects in Indian construction sector with aim of enabling informed interventions at the planning stage to manage the complexity better. A comprehensive literature study enabled identification of 23 such determinants initially which were grouped under 7 components of complexity, each component representing a different type of complexity. Using a two-stage Delphi process, the determinants were narrowed down to 21 and were weighed using mean rank weightages. The results of the survey were used to develop a framework for evaluating complexity which was further idealized into a model in the form of Project Complexity Index that could provide a single quantitative value of complexity at any stage of the project and highlight the areas of concern. Application of the developed model was demonstrated on two case studies of similar infrastructure projects. The framework made it possible to evaluate the complexity as well as highlight the areas needing attention on the basis of component complexity scores thereby indicating that the framework was robust.

Model for Assessing Mobile Business Intelligence Readiness within South African Telecommunications Industry

Philip Marothi Lemekwane, Nkqubela Ruxwana

J. Engg. Res. & Sci. 1(5), 213-222 (2022);

To determine what needs to be done, organisations throughout the world need the capability to find out quickly, what is happening and why it happened. Therefore, having the intelligence to make informed decisions at the right time and place is the key to success in today’s dynamic environment. As mobile systems become increasingly available, more accessible, and better performing, data gathering and analysis can be performed off-site and on-site with greater flexibility, in turn extending Business Intelligence (BI) to mobile devices, commonly known as Mobile Business Intelligence (MBI). However, the MBI implementations remain unexplored and unsupported even with the sturdy increase in mobile technology adoption, especially in developing world like South Africa where it is the most viable option. The study aims to establish the MBI readiness factors and developed a model for these organisations to assess their MBI readiness, using South African telecommunications industry as a case. The study employed quantitative research approach, where a closed-ended questionnaires were used as the primary data collection method. Finding suggest a number of key factors significant to MBI readiness in context including Culture, Enterprise Mobility, Organisational Capability, Infrastructure, Security, Skills, Support, etc. The MBI readiness model and its validated elements provide a new way of identifying and verifying critical factors for MBI.

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.

An Algebraic Specification/Schema for JSON

Konstantinos Barlas, Petros Stefaneas

J. Engg. Res. & Sci. 1(5), 243-250 (2022);

Script Object Notation (JSON) is an open standard data format that is used widely across the int ured data due to its low overhead. While originally created in the early 2000s, it has only gained standard status in 2013 and then again in 2017 with a new version that focused more on security and interoperability. In this paper the authors present a different specification of the JSON standard that relies on algebraic formal methods and provides certain benefits over a regular natural language specification. This specification can also function as a schema that can attest a JSON data document’s compliance to its blueprint. The absorption of Formal Specification methods by the industry happens at a very slow pace, mostly because there is little incentive to tread into a fairly unknown territory. Notwithstanding this reluctance, the authors encourage the usage of Formal Specification techniques to the specifications of open standards; Formal specifications are more succinct, less ambivalent, consistent to the standard, reusable as they support module inheritance and can be executable. The process of designing new Standards can benefit from Formal Specifications as the resulting tangible; ii) allows a thorough and clear understanding of the standard and also allows property checking and property verification.

VSC-HVDC Robust LMI Optimization Approaches to Improve Small-Signal and Transient Stability of Highly Interconnected AC grids

Yankai Xing, Elkhatib Kamal, Bogdan Marinescu, Florent Xavier

J. Engg. Res. & Sci. 1(5), 251-263 (2022);

In this paper, for the situation of HVDC inserted in meshed AC power grid, a model-matching robust H∞ static output error feedback controller (RSOFC) and model-matching dynamic decoupled output feedback controller (DDOFC) are proposed to improve the damping of inter-area oscillation modes and maintain robustness to face the effects of different operating points and unstable zeros. Sufficient conditions for robust stability are derived in the sense of Lyapunov asymptotic stability and presented in the form of linear matrix inequalities to obtain H∞ RSOFC and DDOFC gains based on the reference model. The efficiency and robustness of the proposed controllers are tested and compared to Linear-Quadratic-Gaussian (LQG) control, mixed sensitivity H∞, standard (IEEE) Power Oscillation Damping (POD) controllers on a realistic benchmark of 19 generators connected by a meshed AC grid. The main contributions of this paper are: (i) Compensate the negative effect of unstable zeros (non-minimum phase behavior) on the performances of the closed-loop; (ii) the robustness is improved in order to provide good responses in case of network variations (load evolution, line, and generator trips, etc.) and HVDC line parameters changes; (iii) improve the damping compared with standard controller structures (LQG, mixed sensitivity H∞ and standard POD controller).

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