Volume-13 Issue-2, July 2024 – International Journal of Recent Technology and Engineering (IJRTE)

B812113020724

IJRTE Journal — Wed, 24 Jul 2024 12:26:09 +0000

Seismic Risk, Urbanization And Prevention, Case of Gjilan City
Shemsi Mustafa¹, Visar Krelani²

¹Shemsi Mustafa, Department of Seismology, Geological Survey of Kosovo, UBT-University of Business and Technology, Prishtina, Kosovo.
²Dr. Visar Krelani, UBT – Higher Education Institution, Kosovo Geological Survey of Kosovo.

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Seismic risk is one of the greatest threats facing our country, Kosovo. The Gjilan region is considered one of the most at-risk areas in the country. In the past, the Gjilan region has been struck hundreds of times by earthquakes with magnitudes ranging from 2.0 to 6.1. These seismic events attest to the seismic risks for the region, which is also based on the Gjilan fault, which extends southwest-northeast. Urban areas in the territory of Kosovo, including the city of Gjilan, are undergoing extreme urban transformation, and the urbanisation process since independence in 1999 has not been adequately addressed, particularly in consideration of the seismic risk factor. The current study does not encompass comprehensive research on the seismic risk of the Gjilan region. Still, for some urban areas of the city of Gjilan, the analysis resulting from geophysical studies in several locations with seismic acceleration parameters is being evaluated to assess risk prevention. This analysis is conducted for urban areas, encompassing all necessary parameters for design, thereby ensuring the security of citizens’ lives.

Keywords: Seismicity, Tectonics, Urbanism, Seismic Risk
Scope of the Article: Mechanical Engineering and Applications

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B812013020724

IJRTE Journal — Wed, 24 Jul 2024 12:08:27 +0000

Hybrid Phishing Detecting with Recommendation Decision Trees
Duncan Eric O. Ogonji¹, Cheruiyot Wilson², Waweru Mwangi³

¹Duncan Eric O. Ogonji, School of Computing and Information Technology, Jomo Kenyatta University of Agriculture and TechnologyNairobi, Kenya.

²Cheruiyot Wilson, School of Computing and Information Technology, Jomo Kenyatta University of Agriculture and Technology Nairobi, Kenya.

³Prof. Waweru Mwangi, School of Computing and Information Technology, Jomo Kenyatta University of Agriculture and Technology Nairobi, Kenya.

Abstract: Phishing is performed by trying to trick the victim into accessing any computing information that looks original and then instructing them to send necessary data to unauthorised/private resources. For prevention, it is essential to develop a phishing detection system. Recent phishing detection systems are based on data mining and machine learning techniques. Most of the related work literature requires the collection of previous phishing attack logs, analysing them to create a list of such activities, and blocking traffic from these sources. However, this is a cumbersome task because the data size is enormous, continues changing, and is dynamic. [1]. Instead of using a single algorithm approach, it would be better to use a hybrid approach. A hybrid approach would be more effective at mitigating phishing attacks because it handles the classification of different data formats, whether the intruder uses images or textual input to gain access to another user’s system for phishing purposes. Hybrid recommendation decision trees enhance the performance of machine learning and deep learning algorithms. The decision path of the model followed a series of if/else/then statements that connected the predicted class from the root of the tree through the branches to detect true positives and false negatives of phishing attempts. Ten decision trees were considered, and the features were used to train the recommendation decision regression model. The developed hybrid recommendation decision tree approach yielded an overall actual positive rate of 92.28% and a false negative rate of 7.72%.

Keywords: Phishing, Decision Tree, Detection, Hybrid, Attack
Scope of the Article: Computer Science and Applications

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B811813020724

IJRTE Journal — Wed, 24 Jul 2024 12:02:17 +0000

BIM and GIS Integration for Urban Revitalization Development in the Kumartuli Region, a Socio-Heritage Site
Gayatri Mahajan¹, Teesha Majumder², Kaustubh Kinge³, Parag Narkhede⁴

¹Gayatri Mahajan, Department of Architecture, Symbiosis Skills & Professional University, Pune (Maharashtra), India.

²Teesha Majumder, Department of Architecture, Symbiosis Skills & Professional University, Pune (Maharashtra), India.

³Kaustubh Kinge, Department of Architecture, Symbiosis Skills & Professional University, Pune (Maharashtra), India.

⁴Dr. Parag Narkhede, Department of Architecture, Symbiosis Skills & Professional University, Pune (Maharashtra), India.

Abstract: This study explores the use of Building Information Modeling (BIM) and Geographic Information Systems (GIS) in improving residents’ livelihood and living conditions in Kumartuli, a socio-heritage site in North Kolkata, India. The present investigation aims to explore current problems and provide future direction for redeveloping existing workplaces and living units, including improvements in infrastructure such as roads, water supply, drainage, and sewerage systems. It also explores the integration of bio-climate and biophilic design principles for sustainable neighbourhood development in Kumartuli. GIS can enhance BIM function by providing a systematic platform for problem-solving, while BIM represents detailed community working space data. The output may provide a new venue for investigating urban planning, infrastructure management, and construction management to improve the quality of livelihood for the communities of idol makers.

Keywords: BIM, GIS, Construction Project, Construction Management, Kumartuli, Culture Heritage.
Scope of the Article: Environmental Engineering

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B811313020724

IJRTE Journal — Wed, 24 Jul 2024 11:54:40 +0000

Digital Twin: Applications, Implementation and ROI In Printing Industry
Sameer Deshpande¹, Manisha Deshpande²

¹Mr. Sameer Deshpande, Lecturer, Government Institute of Printing Technology Mumbai (M.H), India.

²Mrs. Manisha Deshpande, Principal, Government Institute of Printing Technology Mumbai (M.H), India.

Abstract: It is expected that the global value across all print and printed packaging will reach $843 billion in 2026. This increase is a result of the pandemic-induced negative disruption in 2020. The packaging market has a growing share in it [1]. In Industry 4.0, the manpower, machinery, and printing processes are in the network digitally [2]. Accurate and precise data control is crucial for production, and digital twins are essential tools for enhancing overall efficiency and sustainability. Digital twins are connected from sensors to cloud-based software, which can be accessed by all stakeholders, including manufacturers, intermediate supply chain managers, wholesale clients, and end-use customers. Therefore, digital twins play a crucial role in Industry 4.0. In the print and packaging industry, due to increased automation, investments in plant and machinery are growing, but customers expect cost reductions with an emphasis on quality and sustainability measures. The order quantities are decreasing, and demand for short-run, customised products is increasing. Customers expect printing companies to follow international standards diligently. There are several benefits of digital twins in the printing and packaging industry, which result in saving time, manpower, and cost, thereby reducing the adverse impact on the environment in terms of effluents and power usage, and increasing overall equipment efficiency and sustainability.

Keywords: Industry 4.0, Digital Twin, Types, Applications
Scope of the Article: Computer Science and Applications

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B811113020724

IJRTE Journal — Wed, 24 Jul 2024 11:48:54 +0000

Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions
Praveen Borra

Praveen Borra, Department of Computer Science, Florida Atlantic University, Boca Raton, USA.

Abstract: Azure IoT, developed by Microsoft, is a leading platform in the realm of Internet of Things (IoT), revolutionizing industries through enhanced connectivity, robust data management, and advanced analytics. This paper provides an in-depth exploration of Azure IoT’s foundational technologies, including Azure IoT Hub and Azure Sphere, which are crucial for ensuring secure device communication and comprehensive IoT security. Azure IoT Hub enables secure, bidirectional communication between IoT devices and the cloud, supporting scalability for millions of devices across diverse sectors. In manufacturing, it enables predictive maintenance by analysing real-time sensor data to proactively identify equipment failures, thereby optimising operational efficiency and reducing costs. Similarly, in healthcare, Azure IoT enhances patient care through remote monitoring, enabling timely interventions based on continuous collection of health data. Azure Sphere complements Azure IoT Hub by offering a secure hardware, operating system, and cloud service ecosystem, essential for protecting IoT deployments against cyber threats. This integrated security approach ensures data integrity and privacy in interconnected IoT environments. The integration of Azure IoT with Azure’s AI and machine learning services enriches IoT solutions with advanced analytics and automation capabilities. Organizations leverage AI to derive actionable insights from IoT data, automate decision-making processes, and enhance operational efficiency across various applications. Looking ahead, Azure IoT is advancing edge computing capabilities to reduce latency and improve real-time analytics and decision-making. Additionally, Azure continues to prioritize cybersecurity enhancements to safeguard IoT ecosystems from emerging threats, ensuring secure and reliable IoT deployments. In conclusion, Azure IoT serves as a cornerstone of Microsoft’s IoT strategy, enabling organisations to innovate and streamline processes through scalable, secure, and AI-enhanced IoT solutions.

Keywords: Azure IoT Hub, Azure IoT Edge, IoT Security, Edge Computing, Predictive Maintenance, Industrial IoT, Smart Cities, Healthcare IoT, Data Analytics, AI Integration.
Scope of the Article: Computer Science and Applications

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B808513020724

IJRTE Journal — Wed, 24 Jul 2024 11:44:30 +0000

Impact of Irradiance and Temperature on Electrical Parameters of Polycrystalline Photovoltaic Module: A Five Parameter Analysis
Chandrashekhar Pardhi¹, Kanchan Khare², Ashish Choubey³

¹Chandrashekhar Pardhi, Department of Electrical Engineering, Jabalpur Engineering College, Jabalpur, (M.P.), India.

²Kanchan Khare, Department of Applied Chemistry, Jabalpur Engineering College, Jabalpur, (M.P.), India.

³Ashish Choubey, Department of Electrical Engineering, Jabalpur Engineering College, Jabalpur, (M.P.), India.

Abstract: In the current era, adopting renewable energy is not just a choice but a necessity. The role of photovoltaic modules has a significant influence on this shift from conventional energy sources. The performance and parameters of these PV cells are greatly affected by both irradiance and temperature. While the standard test condition assumes 1000 watts per square meter and a 25°C temperature, the reality of solar geometry often alters these values, resulting in changes to the electrical parameters of the PV cell. This study, which employs a five-parameter single-diode model, is of paramount importance in understanding the impact of irradiance and temperature on the system. The parameters are extracted from the P-V and I-V curves of the simulated solar cell and matched with data from the TP300 series polycrystalline TATA Power solar module. The analysis across various temperature and irradiance levels provides crucial insights into changes in shunt and series resistance, diode ideality factor, reverse saturation current, and photo-generated current. This investigation is vital in understanding how parameter alterations correlate with changes in solar cell performance. The study uses the MATLAB Simulink platform, utilizing data from the TATA solar module TP-300 series datasheet.

Keywords: Photovoltaic Module, Irradiance, Temperature, Shunt Resistance, Series Resistance, Diode Ideality Factor, Reverse Saturation Current, Photogenerated Current.
Scope of the Article: Electrical and Electronics

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B807713020624

IJRTE Journal — Wed, 24 Jul 2024 11:35:34 +0000

Design and Implementation of Improved Battery Charger for Two-Wheeler Electric Vehicle
Sheetal Parmar¹, Pritesh R Mankad²

¹Sheetal Parmar, PhD Research Scholar, Gujarat Technological University, Ahmedabad (Gujarat), India.

²Dr. Pritesh R Mankad, Associate Professor, Mahatma Gandhi Institute of Technical Education and Research Center, Vadodara (Gujarat), India.

Abstract: Lithium-ion batteries are essential for the development of electric vehicles (EVs). Two-wheeler electric vehicles (EVs) can be charged using a wide variety of electric vehicle (EV) charging systems. In this research, existing and prospective EV charging technologies’ topologies, power levels, and charging control mechanisms are analyzed. In this study, a novel fast-charging approach is investigated to reduce battery temperature variance, shorten charging time, and enhance charging efficiency. In contrast to constant current (CC) charging, CC-CV Charging (CC-CV) separates the charging process into multiple stages based on its C-rate, enabling rapid charging of lithium-ion batteries. A 24Ah Li-ion battery, with a charging voltage of 54 volts, is considered for the two-wheeler EV experimental data in MATLAB, which are utilised to validate the suggested approach. The proposed technique is distinctive in that it may fully charge the battery.

Keywords: Electric Vehicle, Lithium-Ion Battery, Battery Charger for Two-Wheeler, Dc-Dc Converter, Half Bridge Inverter.
Scope of the Article: Electrical and Electronics

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B807313020624

IJRTE Journal — Wed, 24 Jul 2024 11:25:49 +0000

Estimating Tidal Sea levels along the Central Coast of the Western Arabian Gulf using Machine Learning Algorithms (MLAs)
Abdulrazak H. Almaliki

Abdulrazak H. Almaliki, Department of Civil Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.

Abstract: Precise tidal forecasting is an academic exercise and a crucial tool for designing and constructing coastal and marine infrastructure. Machine learning algorithms (MLAs), such as Random Forest Regression (RF), K-Nearest Neighbours Regression (KNN), Gradient Boosting Machines (GBM), and artificial neural networks (ANNs), are powerful data-driven techniques that can be harnessed for this practical purpose. This study utilizes four machine learning algorithms (MLAs), namely (RF), (KN), (GBM), and the Artificial Neural Network – Multilayer Perceptron (ANN-MLP) model, to accurately estimate the tidal levels along the central coast of the western Arabian Gulf, with direct implications for real-world infrastructure planning and construction. Several metrics, such as mean absolute error (MAE), mean squared error (MSE), normalized mean square error (NMSE), mean absolute percentage error (MAPE), correlation coefficient (R), and root mean square error (RMSE), are used to compare how well the MLAs forecast daily tidal levels. The results confirmed the superiority of the ANN-MLP model over the other approaches. The ANN-MLP model, a specific type of artificial neural network, yields enhancements in (RMSE) of 8.945% and 19.05%, 14.18% compared to (RF), (KN), and (GBM), respectively, throughout the testing process. The ANN-MLP, being a powerful and versatile machine learning algorithm, demonstrated the best level of accuracy, together with the lowest values for RMSE. This experiment unequivocally proves that the ANN-MLP method can be utilised as a supervised machine-learning method for accurately forecasting seawater levels of tides.

Keywords: The Arabian Gulf, Machine Learning Algorithms, Tidal Level, Forecasting.
Scope of the Article: Civil Engineering and Applications

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Volume-13 Issue-2, July 2024 – International Journal of Recent Technology and Engineering (IJRTE)

B812113020724

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