SRC’23 Conference Proceeding

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Title

Abstract

1

Sustainable Finance: Synthesis From Islamic and Western Theories

Due to the negative repercussions of financial development, which have led to climate change and environmental harm, “sustainability” is an essential initiative for survival in all spheres. Financial players can take a proactive role in juggling economic development and environmental conservation. The sustainable finance initiative ensures environmentally responsible behaviour in the financial industry and thus achieves the Sustainable Development Goals [ SDGs]. Several Western theorists have offered theoretical, moral, and ethical foundations for ensuring sustainable activities. These attempts have drawn heavy criticism for issues related to rationale, conceptual clarity, and potential inconsistency, as well as for failing to provide proper ethical directions to company executives who must choose the type of courses to undergo and the level of dedication to be exerted. As a start, this article analytically assesses the notion of sustainable finance, which has become widely accepted among academics and business groups from both Western and Islamic views. This goal was attained using an analytical method in the paper’s design to collect information from earlier publications about the Western and Islamic ideologies underpinning sustainable finance. Given that the concept of sustainable finance is deeply ingrained in numerous verses of the Holy Quran and is backed by numerous Islamic theories and principles, the finding suggests that Islam does not view it as a foreign concept. Rather, sustainable financial principles are remarkably similar to those advocated in Islam. Due to the fact that sustainable principles already guide Islamic financial actors, it is predicted that they will spontaneously practice sustainable finance in their operations.

http://dx.doi.org/10.12785/src/1570954026

2

Augmented Reality and the interior Design sector in Bahrain

This paper presents an innovative utilization of Augmented Reality technology in the field of interior design. Additionally, the article reviews the use of this technology within interior design offices in the Kingdom of Bahrain as a sample of GCC countries in the Middle East. Considering the substantial advancements in digital technology, virtual information techniques have become a necessary component of architectural projects. As such, the emerging technology of Augmented Reality provides numerous benefits for the digital architectural design and construction fields. Moreover, AR is being acknowledged as a novel approach to interior design. In an AR environment or project, virtual paint, furniture and spaces can be interactively displayed and modified in real-time on a screen, allowing users to experience the virtual design elements in a real-world context. Consequently, the AR environment is leveraged as a new working environment for interior designers and architects in the construction industry in Bahrain. The research adopts a qualitative approach to investigate the opportunities and obstacles facing the adoption of this technology in the construction sector in Bahrain market as well as education institutions. Finally, this study proposes a framework for the application of AR technology in interior design, where users can view virtual interior design elements and interact with 3D virtual furniture data through a dynamic and flexible user interface. The results suggest the importance of the technology in the field but require several steps to be adopted before fully utilizing its full potential in design, including program reviews, budget constraints, practical application boundaries, and Maintenance.

http://dx.doi.org/10.12785/src/1570954625

3

Design Optimization for Horizontal Axis Wind Turbine Blades

This project report is based on methods by which the blade design for a horizontal axis wind turbine can be enhanced. This was conducted by a series of research and CFD simulations of the various improvements devices with was observed by comparing the lift to drag ratios from the baseline model of a simple NACA 4415 blade design. The optimization was conducted by initially setting up a baseline value using a single NACA airfoil. Optimizations such as using multiple airfoils with indues twist in the blade followed by addition of wingtips and surface enhancements with the addition of flaps.

http://dx.doi.org/10.12785/src/1570959754

4

Sparse Identification for Fractional Order Systems

This study extends the Sparse Identification of Nonlinear Dynamics (SINDY) algorithm to the discovery of fractional order systems. The SINDY optimization problem was modified in order to incorporate fractional orders in the Caputo sense, with discretization executed using Grünwald-Letnikov finite differences. Noise was handled through weak formulation, while sparse regression was performed via sequential thresholding. The algorithm was tested on the fractional order Lorenz system.

http://dx.doi.org/10.12785/src/1570966802

5

Cooling of an Electronics Component like Graphics Processing Unit Using Euler’s Method as Application of Numerical Methods

Graphics cards need cooling to work, last, and be reliable. This case study simulates and analyzes graphics card cooling using Euler’s method. Euler’s numerical approach simulates graphics card fluctuations in temperature with cooling and heating. It begins with the graphics card discharge of heat. Uncontrolled heat can damage electronics and performance. Active fan, liquid, and heat sink cooling are common. Euler’s method measures graphics card temperature with each cooling strategy. The efficiency of each cooling method is simulated. Affordable and effective fan-based active cooling soothes graphics cards. Advanced liquid cooling is best for high-end electronics. Heat sink cooling is inefficient but good for low-cooling settings. This case study describes Euler’s graphics card cooling method. It lets users instantly compare cooling systems to make informed decisions based on their needs and limits. Effective cooling boosts electrical component performance and lifespan.

http://dx.doi.org/10.12785/src/1570966808

6

Four-element Microstrip Patch Antenna Array for Low-Power RF Energy Harvesting

This article presents the design and simulation of a four-element microstrip patch antenna array specifically tailored for low-power RF energy harvesting. The proposed antenna array aims to efficiently capture and convert RF energy into usable electrical power, making it suitable for various wireless energy harvesting applications. The design process involves optimizing the patch geometry and dimensions, as well as the array configuration, to achieve enhanced power harvesting performance. The simulations explore the antenna array’s characteristics, including its radiation pattern, return loss, and power conversion efficiency, which are evaluated and analyzed. The results demonstrate the effectiveness and potential of the proposed design, peak gain of 4.87 dBi and a VSWR of 1.04, for low-power RF energy harvesting systems.

http://dx.doi.org/10.12785/src/1570966810

7

Impact of Advanced Work Packaging on the Oil and Gas Sector: A Review

Advanced Work Packaging (AWP), a term coined by the Construction Industry Institute (CII), incorporates a structured approach to project planning and execution. Its origin lies in tackling issues like budget and timeline excesses within the realm of industrial construction. Evaluations of AWP through real-world instances reveal a spectrum of advantages spanning productivity, expenses, safety, and scheduling. Nevertheless, a notable hurdle in grabbing AWP is the absence of a clearly defined framework for measuring its costs and merits, which leaves a void in substantiating the indicated gains. This study focuses on the AWP phenomena, the barriers coming in the implementation of AWP, and the improvement of the Oil and Gas sector through AWP. The integration between construction and engineering, lower workforce turnover, and better accountability results in the improvement of the Oil and Gas sector. The cost overrun and time delay can be reduced using this integrated approach.

http://dx.doi.org/10.12785/src/1570967276

8

Enhancing Breast Cancer Detection through Machine Learning: A Comparative Analysis of Logistic Regression and Linear Discriminant Analysis

This paper intends to analyze classification models that can predict whether breast cancer is cancerous or noncancerous through the attributes of the selected dataset with the application of machine learning algorithms. The high-dimensional Breast Cancer Wisconsin (Diagnostic) Dataset is reduced through principal component analysis (PCA). Six major components were extracted with a cumulative variance of 91.063%. The selected classifier models that were evaluated were logistic regression and linear discriminant analysis (LDA). After training and testing, the model’s performance was evaluated using a confusion matrix where metrics such as accuracy, precision, recall, and F1-score were calculated. Experimental results obtained a commendable prediction with 99.7% accuracy for logistic regression and 95.4% accuracy for LDA. It was observed that the LDA model has greater misclassified diagnoses than logistic regression. Thus, it is inferred that in binary classification problems like breast cancer detection, logistic regression produces more promising predictions.

http://dx.doi.org/10.12785/src/1570967447

9

Artificial Neural Networks for Strength Prediction of Fly Ash-based 3D-Printed Cementitious Materials

This methodology employs Artificial Neural Networks (ANN) to predict the compressive strength of 3D-printed alkali-activated geopolymers, focusing on materials containing fly ash (FA). Data for training is gathered through an extensive literature review, encompassing parameters relevant to FA-containing geopolymers. After meticulous curation, a dataset of 53 experimental records, including mix ratios, chemical data, and 28-day compressive strength, is assembled. ANN architecture determination involves trial and error, considering different neurons and hidden layers, and various training algorithms. Results reveal that Levenberg Marquardt (LM) models consistently exhibit lower Mean Square Error (MSE), signifying superior accuracy. The best-performing LM model (7-11-1) outperforms Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) models. The ANN achieves optimal validation performance offering a reliable framework for predicting 3D-printed material strength and enhancing construction material performance through understanding input parameter interplay.

http://dx.doi.org/10.12785/src/1570967474

10

Heating and cooling energy consumption prediction model for a residential apartment considering design parameters

A substantial portion of the total energy is consumed by buildings, and the number of residential structures in Morocco has significantly risen. Consequently, it is crucial to focus more on energy consumption in residential buildings. Furthermore, accurately predicting energy consumption in these residential buildings is of great importance. The current study has developed a predictive model for residential building energy consumption by employing multivariate model construction and weather data. The study involved predicting the energy consumption for heating and cooling in apartment buildings in order to assess the influence of the building envelope structure on energy conservation and indoor thermal comfort. The study has established a confirmed relationship that demonstrates the dependencies of energy consumption on various design variables within the envelope systems of residential buildings. This relationship was then used to create a predictive model for heating and cooling energy consumption. As a result . The Increasing the thermal transmittance values led to a 25% – 27% increase in heating energy consumption. In contrast, cooling energy consumption decreased by 8% to 26% when thermal transmittance was increased. This demonstrates that the developed model can swiftly estimate energy usage for apartment buildings using basic information about design variables. Moreover, it can readily identify the most crucial design factor for creating more energy-efficient residential building designs.

http://dx.doi.org/10.12785/src/1570969205

11

Construction Productivity Monitoring Techniques: A Review and Bibliometric Analysis

Despite previous attempts to mitigate these limitations, there exists a gap in the automated monitoring of construction productivity. The aim of this research endeavor is to analyze and evaluate the different techniques utilized for monitoring productivity in the context of building construction projects. To achieve this objective, a comprehensive methodology incorporating bibliometric analysis and systematic review was employed. A thorough examination was conducted, revealing that computer vision-based approaches, and photogrammetry are the predominantly utilized means of data acquisition for productivity monitoring in building projects. Additionally, Building Information Modeling (BIM) was integrated with monitoring tools and technologies to enhance the performance of automated monitoring in construction productivity. Furthermore, it was observed that the existing studies did not encompass the full range of complex construction job sites and were based on a limited sample of construction workers and machines.

http://dx.doi.org/10.12785/src/1570969411

12

Present and Future Load Optimization of Electric Three Wheelers in Bangladesh

Electric Vehicles (EVs) have already been playing a key role in reducing carbon emissions; and in the future, their importance is expected to grow even more. The number of EVs in developing countries is also increasing with time. Bangladesh, a developing country located in South Asia has witnessed a remarkable bloom in the number of Electric 3-wheelers vehicles. However, like other developing countries, Bangladesh faces great difficulties in balancing the net energy supply and demand. To address this issue of maintaining grid stability and fostering the ever-growing trend of EV adoption, this study introduces an optimization approach that regulates the total load of electric vehicles. Utilizing a heuristic method, this paper focuses on peak shaving and valley filling techniques customized to the unique EV charging patterns of Bangladesh. This approach incorporates three objective functions designed to amplify the difference between power generation and EV load during peak hours while reducing it during valley hours, all while considering the inclusion of weightage factors. Simulation result shows that the proposed algorithm shows better performance compared to the non-optimized lading system. Furthermore, we also estimated the electricity generation and EV load for the year 2030, and the result shows that the algorithm also function well with the forecasted data of electricity generation and demand.

http://dx.doi.org/10.12785/src/1570969642

13

IR4.0 Technologies Deployment to Enhance Marine Aquaculture Production

Enhancing aquaculture production systems can contribute to meeting several Sustainable Development Goals of the National Union, such as SDG 1, Zero Hunger, and SDG 14, Life below Water. The traditional methodologies used in aquaculture face several challenges that negatively affect the quality and quantity of the harvested fish. This paper investigates the various challenges faced in the marine aquaculture industry and how IR4.0 technologies can mitigate these challenges to enhance production that will result in sustainable aquaculture. A framework based on triple-helix is proposed, consisting of a collaboration between industry, academia, and government. A Blue Water Fishery Company case study has been considered to analyze the real-time challenges they faced in the existing aquaculture farm in the Sultanate of Oman. Sustainable solutions based on technology are not just static products for a fixed requirements set. Technology is evolving significantly when solving a dynamic environment such as aquaculture. To achieve this, the proposed framework considers upskilling the national youth. This will build the capacity to solve various challenges through IR 4.0 technologies, such as IoT, AI, and Big data, resulting in Smart fisheries industries.

http://dx.doi.org/10.12785/src/1570969755

14

Design and Implementation of an Energy Monitoring System for Residential Premises with Interactive Emoji-Based Language

Amidst technological progress and an exponentially increasing global population, it became evident that it is essential to monitor energy consumption at the customer level to sustain the technological infrastructure that supports various facets of human existence and improve its overall efficiency. It is believed that consumers become more aware of their consumption habits when the technical language-describing their energy consumption- is simplified. Interactive energy monitoring systems aim to urge individuals to change their energy consumption behaviors by further exploiting the final distribution boards (FDB) that are available in every residential premise. The proposed system includes a touchscreen installed on the FDB that will alert the consumer to their real-time consumption rate. The scaled-down FDB is designed to imitate the FDB in residential premises, with loads that primarily exist in them. The loads used are LED lights, an exhaust fan, and outlet sockets. The measuring system consists of an ADE9000 shield that will measure the consumed energy from the FDB by connecting the voltage and current terminals using a suitable configuration. The alerting system is represented with an emoji animation portraying how excessive the consumption is, using raspberry pi and Ionic App. The purpose of using emojis is that the system is designed to alter the consumption rate using a behavioral change approach. The emoji language was chosen due to its simplicity, globality, and the fact that its continued prevalence as modern means of communication. The figure below depicts the initial prototype of the proposed system.

http://dx.doi.org/10.12785/src/1570970063

15

Sustainability in the Gigafactory: A Data-Driven Forecast of Non-renewable vs. Renewable Energy

The establishment of the Gigafactory is a pivotal development in the pursuit of a sustainable energy future on a global scale. The Gigafactory employs sustainable energy sources in order to manufacture a battery pack. The implementation of an environmentally conscious and sustainable energy system within the gigafactory has been found to yield favorable outcomes. Non-renewable energy sources pose a significant threat to the environment due to their carbon dioxide emissions. Predictive models are required to ascertain the projected energy consumption levels for the upcoming decades, wherever there is an observed increase in energy consumption. The study employed the Automatic ARIMA model, a predictive model commonly utilized for forecasting purposes, to anticipate the levels of non-renewable energy consumption and renewable energy consumption. This prediction carried out using the R package ‘forecast’.The research demonstrates that the implementation of Auto ARIMA on historical energy consumption data enables the projection of future non-renewable energy and renewable energy consumption for a period of ten years. Based on the forecast, the consumption level of non-renewable energy surpasses that of renewable energy.

http://dx.doi.org/10.12785/src/1570959754

16

Synthesis and characterization of NixCu1-xFe2O4 as fillers for Conductive polymer composite in EMI Shielding Application

High-performance electromagnetic (EM) interference shielding materials have become indispensable to prevent the adverse effect of EM pollution on human beings and safeguard electronic equipment from EM interference. This research proposes a new route to regulate the percolation threshold of conductive fillers in conductive polymer composite. Nano-size nickel copper ferrite nanoparticles (NixCu1-xFe2O4) were prepared by a facile Co-precipitation method at different stoichiometric ratios can be used to change the chemical vicinity of other conductive materials in conductive polymer composites. The resulting nanoparticles were characterized by X-ray diffraction (XRD) to depict their crystallinity and a Scanning electron microscope (SEM) to study their surface morphology. The result showed nanosized NixCu1-xFe2O4 has a crystalline size of 38.4nm with nanorod bundle like structures surrounded with small uniform nanocrystals. This unique morphology will be favorable EMI shielding

http://dx.doi.org/10.12785/src/1570970330

17

Leveraging Big Data and Machine Learning for Smart Park Management

The evaluation of ecosystem services is becoming increasingly important in urban research, yet its performance assessment remains to be explored. The Importance-Performance Analysis (IPA) provides a new perspective for the evaluation of ecosystem services. Recently, big data has provided higher data volume and dimensions for urban research, but the evaluation of ecosystem services based on big data still needs to be explored. This study takes the parks in Shanghai, China as an example, and explores the perceived evaluation of ecosystem services based on big data and machine learning. The study also uses Importance-Performance Analysis (IPA) to evaluate the optimization priorities of ecosystem services, and proposes corresponding resource allocation optimization strategies. Our study found that the overall satisfaction rating of various ecosystem services in the park is high, while their importance rating is low. Using both as park renewal indicators would lead to different optimization priorities. The IPA method can guide the optimization priorities of park ecosystem services. The ecosystem service that requires the highest priority optimization is Social interaction and recreational activities. This study provides methodological insights for ecosystem service assessment and other related urban research, which is of practical significance for achieving human well-being.

http://dx.doi.org/10.12785/src/1570970356

18

Practical Predictive Control Strategy for Efficient Harnessing of Marine Energy

The control challenge in marine energy remains an ongoing research query due to the complexities involved in developing effective and economically viable control strategies. To address these challenges, this study proposes a predictive control strategy based on finite control set model approach for point absorber wave energy harvesters (WEHs). The developed control strategy deploys a comprehensive nonlinear system model specifically designed for vertically oscillating WEHs. By formulating the predictive control in the finite set control framework, the control objective is achieved without the need for a predefined control command trajectory. Instead, the strategy searches for optimal control laws, in the form of power converter switching functions, to maximize the converted electrical energy of the WEH. Simulation is conducted to evaluate the efficacy of the suggested controller. The results clearly demonstrate that the suggested approach outperforms its benchmark reference-based counterpart in both the conversion efficiency and also in the required PTO control effort.

http://dx.doi.org/10.12785/src/1570970568

19

Conditional Tracking for Maximizing Power Consumption out of Solar Photovoltaic Array: Temperature and Solar Irradiation

The efficiency of photovoltaic (PV) systems is intricately tied to temperature and solar radiation, impacting the I-V (current-voltage) and P-V (power-voltage) characteristics of PV arrays. To optimize efficiency, Maximum Power Point Tracking (MPPT) algorithms must ensure PV arrays operate at their Maximum Power Point (MPP). However, variations in solar array attributes can lead to shifts in the MPP. This research employs the Perturb and Observe (P&O) MPPT technique on a solar array to statistically tackle this issue. A novel Simulink-based methodology is employed, accurately estimating peak power outputs of 8.600×104 and 10.002×104 watts under consistent irradiance and temperature conditions with partial shading. By treating temperature and solar irradiation as distinct factors, along with partial shading-this approach significantly bolsters the model’s performance.

http://dx.doi.org/10.12785/src/1570970574

20

Energy Conservation Awareness Among University Students in Bangladesh: A Case Study of Comilla University

Energy conservation is a vital and effective way to reduce energy consumption and emissions. University students are a special social group with high and advanced energy needs. Their awareness of energy conservation can indicate the future trends of energy saving. In this study, we surveyed 90 students from Comilla University, Bangladesh, to measure their awareness of energy conservation and its influencing factors. We found that university students have a high level of awareness of energy conservation. However, they also face some challenges in implementing energy saving practices. Based on the feedback from the respondents, we suggest some effective methods to increase their awareness and motivation. This study provides some insights into the local context of energy conservation among university students, which is important for developing an energy saving culture among the young generation who will be our future scholars and leaders.

http://dx.doi.org/10.12785/src/1570970591

21

Sustainable Design of a Composite Bridge: A Comparison Between Normal and Green Concrete Composite Slab

Design is the first step that is considered the basis for the results expected to be obtained. Therefore, achieving the desired results from any project begins with achieving efficiency in the initial stages. To achieve sustainability in bridge construction, an efficient design must be taken into account, as it is considered the decision-making stage in terms of the expected results that will be obtained. By prioritizing sustainability in the design phase, a composite bridge can minimize environmental impacts, enhance resilience, improve resource efficiency, and provide long-term economic benefits. The design process should consider a holistic approach, integrating environmental, social, and economic considerations to create a sustainable bridge that positively contributes to the surrounding ecosystem and society as a whole [1]. This paper evaluates the sustainable design upon a single-span composite bridge with eight steel I-girders spaced 2.4 m apart, a span of 30 meters, and a width of 19.2 meters, Using the American Association of State Highway and Transportation Officials (AASHTO) and Load and Resistance Factor Bridge Design Specifications (LRFD), and examining two types of concrete, which are normal concrete and green concrete. As well as two steel sections W33 x 221 (W840 x 329) and W33 x 201 (W840 x 299) for the girder.

http://dx.doi.org/10.12785/src/1570972584