Syed Muhammad Hassan, Haque Nawaz, Imtiaz Hussain, Basit Hassan, Mashooque Ali Mahar
In response to the challenges posed by climate change and the need for sustainable food supply, this study addresses the problem of efficiently categorizing and predicting the weight of fish in aquaculture. Leveraging machine learning and deep learning algorithms, we propose a regression model to predict fish weight and classification models for species identification based on weight, width, and length parameters. The focus is on automating fish farming processes to ensure uninterrupted food supply amidst environmental uncertainties. Comparative analysis of various machine learning algorithms reveals promising accuracy levels, with deep learning sequential models achieving 99.77% accuracy under specific conditions. This research aims to contribute to the advancement of automated fish farming practices, mitigating the impact of climate change on food security and promoting sustainable resource management.
{"title":"Impact of Climate Change on Fish Species Classification Using Machine Learning and Deep Learning Algorithms","authors":"Syed Muhammad Hassan, Haque Nawaz, Imtiaz Hussain, Basit Hassan, Mashooque Ali Mahar","doi":"10.46338/ijetae0224_02","DOIUrl":"https://doi.org/10.46338/ijetae0224_02","url":null,"abstract":"In response to the challenges posed by climate change and the need for sustainable food supply, this study addresses the problem of efficiently categorizing and predicting the weight of fish in aquaculture. Leveraging machine learning and deep learning algorithms, we propose a regression model to predict fish weight and classification models for species identification based on weight, width, and length parameters. The focus is on automating fish farming processes to ensure uninterrupted food supply amidst environmental uncertainties. Comparative analysis of various machine learning algorithms reveals promising accuracy levels, with deep learning sequential models achieving 99.77% accuracy under specific conditions. This research aims to contribute to the advancement of automated fish farming practices, mitigating the impact of climate change on food security and promoting sustainable resource management.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"16 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141272846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Miao Ning, Cai Bo, Qingyue Wang, Xinran Wang, Qianqian Guo
This study explores the development trends of AI in education through a bibliometric analysis of literature from 2011 to 2021. Using the Biblioshiny toolkit for Bibliometrix in R language, we analyzed titles, authors, abstracts, keywords, citations, and affiliations. The findings reveal research changes and hot directions in AI education, forecasting future developments. While regions like the US and UK have achieved success in AI education, China is integrating AI into teaching disciplines. The rise of AIGC and companies like OpenAI is accelerating AI integration in education, creating opportunities for personalized learning, adaptive education, and intelligent educational management. Collaboration among stakeholders and comprehensive strategies are crucial for successful AI implementation in education.
本研究通过对 2011 年至 2021 年的文献进行文献计量分析，探讨人工智能在教育领域的发展趋势。我们使用 R 语言中的 Bibliometrix Biblioshiny 工具包，分析了标题、作者、摘要、关键词、引文和所属单位。研究结果揭示了人工智能教育领域的研究变化和热点方向，预测了未来的发展。美国和英国等地区在人工智能教育方面取得了成功，而中国正在将人工智能融入教学学科。AIGC和OpenAI等公司的崛起正在加速人工智能与教育的融合，为个性化学习、自适应教育和智能教育管理创造机会。利益相关者之间的合作和全面的战略对于在教育领域成功实施人工智能至关重要。
{"title":"Bibliometric Analysis of the Influence of Artificial Intelligence on the Development of Education","authors":"Miao Ning, Cai Bo, Qingyue Wang, Xinran Wang, Qianqian Guo","doi":"10.46338/ijetae0224_01","DOIUrl":"https://doi.org/10.46338/ijetae0224_01","url":null,"abstract":"This study explores the development trends of AI in education through a bibliometric analysis of literature from 2011 to 2021. Using the Biblioshiny toolkit for Bibliometrix in R language, we analyzed titles, authors, abstracts, keywords, citations, and affiliations. The findings reveal research changes and hot directions in AI education, forecasting future developments. While regions like the US and UK have achieved success in AI education, China is integrating AI into teaching disciplines. The rise of AIGC and companies like OpenAI is accelerating AI integration in education, creating opportunities for personalized learning, adaptive education, and intelligent educational management. Collaboration among stakeholders and comprehensive strategies are crucial for successful AI implementation in education.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"19 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141272978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— IoT networks suffered from different kinds of attacks. The main issue of IoT security is the limitation of its node’s energy ability to perform big tasks such as encryption. This paper provides a comprehensive overview of the dynamic landscape of lightweight cryptography research, particularly in the context of real-time traffic security and Internet of Things (IoT) networks. The aim of this research is to identify the gaps in IoT research efforts and draw up ways to address it. The objectives are highlighting the global collaboration and standardization initiatives that have shaped its development. Also, it emphasizes the importance of balancing cryptographic strength with practical considerations such as encryption latency, energy efficiency, and memory constraints, particularly crucial in the context of resource constrained IoT devices. Furthermore, it highlights innovative approaches proposed by researchers to enhance the security of cryptographic operations while minimizing overhead and ensuring compatibility with evolving wireless environments. It calls for sustained research efforts to address these challenges and foster the development of robust cryptographic solutions capable of meeting the stringent security requirements of modern digital ecosystems.
{"title":"Wireless IoT Networks Security and Lightweight Encryption Schemes- Survey","authors":"Akram Qashou, Firas Hazzaa, Sufian Yousef","doi":"10.46338/ijetae0124_05","DOIUrl":"https://doi.org/10.46338/ijetae0124_05","url":null,"abstract":"— IoT networks suffered from different kinds of attacks. The main issue of IoT security is the limitation of its node’s energy ability to perform big tasks such as encryption. This paper provides a comprehensive overview of the dynamic landscape of lightweight cryptography research, particularly in the context of real-time traffic security and Internet of Things (IoT) networks. The aim of this research is to identify the gaps in IoT research efforts and draw up ways to address it. The objectives are highlighting the global collaboration and standardization initiatives that have shaped its development. Also, it emphasizes the importance of balancing cryptographic strength with practical considerations such as encryption latency, energy efficiency, and memory constraints, particularly crucial in the context of resource constrained IoT devices. Furthermore, it highlights innovative approaches proposed by researchers to enhance the security of cryptographic operations while minimizing overhead and ensuring compatibility with evolving wireless environments. It calls for sustained research efforts to address these challenges and foster the development of robust cryptographic solutions capable of meeting the stringent security requirements of modern digital ecosystems.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"154 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Oscar Benito Pacheco, Hugo Vega Huerta, Percy De-La-Cruz VdV, Ernesto Cancho Rodriguez, Ronald Melgarejo Solis, Jorge Pantoja Collantes, Javier Cabrera Díaz
The practice of Requirements Engineering (RE) within Agile development contexts markedly differs from that within traditional development process. As the RE discipline in Agile Software Development continues to evolve, this research highlights and assesses various challenges to refine its impact on software product development. This study describes inductive and empirical research on Agile RE challenges and practices based on an analysis of data collected in the binding academic and scientific literature. This research is also based on the guidelines of a Systematic Review of the Literature (SRL) proposed by Kitchenham. Our results indicate eight type of challenges that we grouped into four themes: suitability delimitations, on software product development projects, the formation of the development team, and the efficient participation of the client during the process. Finally, this paper contributes detailed insights into RE challenges specific to Agile project development, evaluates their resolution extent, and outlines existing research gaps in RE practices
{"title":"Challenges of Requirements Engineering in Agile Projects: A Systematic Review","authors":"Oscar Benito Pacheco, Hugo Vega Huerta, Percy De-La-Cruz VdV, Ernesto Cancho Rodriguez, Ronald Melgarejo Solis, Jorge Pantoja Collantes, Javier Cabrera Díaz","doi":"10.46338/ijetae0124_03","DOIUrl":"https://doi.org/10.46338/ijetae0124_03","url":null,"abstract":"The practice of Requirements Engineering (RE) within Agile development contexts markedly differs from that within traditional development process. As the RE discipline in Agile Software Development continues to evolve, this research highlights and assesses various challenges to refine its impact on software product development. This study describes inductive and empirical research on Agile RE challenges and practices based on an analysis of data collected in the binding academic and scientific literature. This research is also based on the guidelines of a Systematic Review of the Literature (SRL) proposed by Kitchenham. Our results indicate eight type of challenges that we grouped into four themes: suitability delimitations, on software product development projects, the formation of the development team, and the efficient participation of the client during the process. Finally, this paper contributes detailed insights into RE challenges specific to Agile project development, evaluates their resolution extent, and outlines existing research gaps in RE practices","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"1 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
— Distracted driving and speeding are significant contributors to traffic accidents, often resulting in injuries and fatalities. This research paper presents a comprehensive investigation into the factors contributing to driver negligence-related traffic accidents, offering quantifiable findings and proposing a novel solution to mitigate them. The study's primary objective is to design a technology-driven solution that enhances driver awareness, preventing activities like texting, multimedia consumption, browsing, and calls while driving. The system aims to ensure driver attentiveness without disrupting other passengers' data connectivity. Furthermore, the design addresses the issue of excessive speeding by introducing an intelligent strategy. Field testing and validation of the implemented system demonstrated a 97% accuracy in speed measurement and a gesture recognition algorithm with a detection rate of approximately 98.3%. The findings of this research provide valuable insights into combating distracted driving and speeding incidents, offering a data-driven approach to design an innovative solution that can contribute to safer roads.
{"title":"From Data to Design: An IoT-Based Novel Solution for Combating Distracted Driving and Speeding Events","authors":"Abida Siddique, Mohammad Gousuddin, R. V J","doi":"10.46338/ijetae0124_02","DOIUrl":"https://doi.org/10.46338/ijetae0124_02","url":null,"abstract":"— Distracted driving and speeding are significant contributors to traffic accidents, often resulting in injuries and fatalities. This research paper presents a comprehensive investigation into the factors contributing to driver negligence-related traffic accidents, offering quantifiable findings and proposing a novel solution to mitigate them. The study's primary objective is to design a technology-driven solution that enhances driver awareness, preventing activities like texting, multimedia consumption, browsing, and calls while driving. The system aims to ensure driver attentiveness without disrupting other passengers' data connectivity. Furthermore, the design addresses the issue of excessive speeding by introducing an intelligent strategy. Field testing and validation of the implemented system demonstrated a 97% accuracy in speed measurement and a gesture recognition algorithm with a detection rate of approximately 98.3%. The findings of this research provide valuable insights into combating distracted driving and speeding incidents, offering a data-driven approach to design an innovative solution that can contribute to safer roads.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"62 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper a state feedback linearization controller is developed for enzyme-substrate reactions with ferroelectric behaviour in brain waves. The proposed control law generates a feedback signal that regulate the performance of the sate variables to their desired states. Then, the nonlinear closed loop control system is simulated to demonstrate the effectiveness of the developed control approach in obtaining the required steady state value. Keywords— Nonlinear systems, enzyme, Brain waves, feedback linearization, steady state.
{"title":"A State Feedback Linearization Controller for Enzyme- Substrate Reactions","authors":"E. Aljuwaiser, M. Alfadli, A. Almansour","doi":"10.46338/ijetae0124_01","DOIUrl":"https://doi.org/10.46338/ijetae0124_01","url":null,"abstract":"In this paper a state feedback linearization controller is developed for enzyme-substrate reactions with ferroelectric behaviour in brain waves. The proposed control law generates a feedback signal that regulate the performance of the sate variables to their desired states. Then, the nonlinear closed loop control system is simulated to demonstrate the effectiveness of the developed control approach in obtaining the required steady state value. Keywords— Nonlinear systems, enzyme, Brain waves, feedback linearization, steady state.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"68 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Duy Nguyen Minh Le, Huy Gia Le, Hai Thanh Hoang, Vu Anh Hoang
— In the digital age, social media's pervasive influence has inadvertently escalated the prevalence of hate speech and offensive comments, with alarming implications for mental health. There is increasing evidence indicating a clear correlation between two factors. exposure to such toxic online content and the onset of depression among users, particularly affecting vulnerable groups like content creators and channel owners. Addressing this critical issue, our research introduces XBert, a model for detecting hostile and provocative language in Vietnamese. We propose an approach related to data preprocessing, improved tokenization, and model fine-tuning. We have modified the architecture of the Roberta model, used the EDA technique, and added a dropout parameter to the tokenizer. Our model achieved an accuracy of 99.75% and an F1-Macro score of 98.05%. This is a promising result for a model detecting provocative and hostile language in Vietnamese.
{"title":"XBert - A Model for Hate Speech Detection in Vietnamese Text","authors":"Duy Nguyen Minh Le, Huy Gia Le, Hai Thanh Hoang, Vu Anh Hoang","doi":"10.46338/ijetae1223_01","DOIUrl":"https://doi.org/10.46338/ijetae1223_01","url":null,"abstract":"— In the digital age, social media's pervasive influence has inadvertently escalated the prevalence of hate speech and offensive comments, with alarming implications for mental health. There is increasing evidence indicating a clear correlation between two factors. exposure to such toxic online content and the onset of depression among users, particularly affecting vulnerable groups like content creators and channel owners. Addressing this critical issue, our research introduces XBert, a model for detecting hostile and provocative language in Vietnamese. We propose an approach related to data preprocessing, improved tokenization, and model fine-tuning. We have modified the architecture of the Roberta model, used the EDA technique, and added a dropout parameter to the tokenizer. Our model achieved an accuracy of 99.75% and an F1-Macro score of 98.05%. This is a promising result for a model detecting provocative and hostile language in Vietnamese.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"113 49","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138607608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unlike traditional currencies that rely on centralized such as banks or governments, cryptocurrencies have become popular due to its decentralized transactions. Decentralization takes advantage of no requirement for intermediaries, thus reducing transaction fees and processing times. However, investing in cryptocurrencies incurs risks and uncertainties due to price volatility and rapid changes. The fact that prediction of asset prices is complex due to the influence of multiple factors on price movements. This paper studied the technical factor to analyse the short-term returns of Ethereum (ETH) in the periods of 1-10 days. The historical data containing ETH closing price are collected from CoinGecko. The twenty-two indicators are chosen from Momentum, Volatility, and Sentiment factors as candidates to provide valuable insights in market trends. By calculating various indicators based on past closing prices, this study utilizes XGBoost, a powerful boosted decision trees ensemble, to discover patterns in previous trading. The model performance is evaluated using the multi-class AUC-ROC metric, which measures the accuracy of predicting three types of ETH returns: Downtrend, Sideway, and Uptrend. The results show that the models achieve accuracy scores ranging from 0.65 to 0.67. Moreover, the study emphasizes the importance of considering momentum indicators when making investment decisions in Ethereum. Keywords—cryptocurrency investment, technical factor, Ethereum, XGBoost, machine learning
{"title":"Prediction of Ethereum Short-term Returns Using XGBoost Model","authors":"Wipawee Nayam, Y. Limpiyakorn","doi":"10.46338/ijetae0823_01","DOIUrl":"https://doi.org/10.46338/ijetae0823_01","url":null,"abstract":"Unlike traditional currencies that rely on centralized such as banks or governments, cryptocurrencies have become popular due to its decentralized transactions. Decentralization takes advantage of no requirement for intermediaries, thus reducing transaction fees and processing times. However, investing in cryptocurrencies incurs risks and uncertainties due to price volatility and rapid changes. The fact that prediction of asset prices is complex due to the influence of multiple factors on price movements. This paper studied the technical factor to analyse the short-term returns of Ethereum (ETH) in the periods of 1-10 days. The historical data containing ETH closing price are collected from CoinGecko. The twenty-two indicators are chosen from Momentum, Volatility, and Sentiment factors as candidates to provide valuable insights in market trends. By calculating various indicators based on past closing prices, this study utilizes XGBoost, a powerful boosted decision trees ensemble, to discover patterns in previous trading. The model performance is evaluated using the multi-class AUC-ROC metric, which measures the accuracy of predicting three types of ETH returns: Downtrend, Sideway, and Uptrend. The results show that the models achieve accuracy scores ranging from 0.65 to 0.67. Moreover, the study emphasizes the importance of considering momentum indicators when making investment decisions in Ethereum. Keywords—cryptocurrency investment, technical factor, Ethereum, XGBoost, machine learning","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117042669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Digital forensics investigations play an essential role in modern law enforcement, national security, and civil litigation. To conduct a successful investigation, it is crucial to choose an appropriate digital forensics investigation model that fits the investigation's context, scope, purpose, and methods. This paper presents an overview of the main factors that should be considered when selecting a digital forensics investigation model, including the type of incident, legal and ethical requirements, technical and operational capabilities, and complexity of the scenario. Additionally, this paper describes 11 digital forensics investigation models, ranging from simple to complex, each with its own strengths and weaknesses. By understanding the advantages and limitations of each model, digital forensics professionals can choose the most suitable model for their specific investigation. Keywords—Digital forensics investigations, Forensic analysis, Investigation models, Forensics Model
{"title":"A Comprehensive Review of the Evolution and Future Directions of Digital Forensic Investigation Model","authors":"S. Safie, Syah Reezal Md Bashah","doi":"10.46338/ijetae0723_01","DOIUrl":"https://doi.org/10.46338/ijetae0723_01","url":null,"abstract":"Digital forensics investigations play an essential role in modern law enforcement, national security, and civil litigation. To conduct a successful investigation, it is crucial to choose an appropriate digital forensics investigation model that fits the investigation's context, scope, purpose, and methods. This paper presents an overview of the main factors that should be considered when selecting a digital forensics investigation model, including the type of incident, legal and ethical requirements, technical and operational capabilities, and complexity of the scenario. Additionally, this paper describes 11 digital forensics investigation models, ranging from simple to complex, each with its own strengths and weaknesses. By understanding the advantages and limitations of each model, digital forensics professionals can choose the most suitable model for their specific investigation. Keywords—Digital forensics investigations, Forensic analysis, Investigation models, Forensics Model","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122345933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. A. M. Said, M. H. Misran, M. Othman, R. A. Manap, A. Jaafar, S. Suhaimi, N. I. Hassan
The fifth-generation (5G) wireless communication system requires high gain antennas to support the growing demand for high-speed data transmission and low-latency connectivity. High gain antennas are crucial for enhancing the signal strength and extending the coverage area of 5G networks. By using multiple antenna elements, an array can achieve higher gain and directivity compared to a single element antenna. This improvement in gain enables better signal reception and transmission, leading to increased communication range, higher data rates, and improved reliability. In this paper, we discuss the design and implementation of antenna arrays for improving antenna gain in 5G communication systems at 3.5 GHz.The design of the array antenna incorporates single, dual, quad, and octal element structures to enhance the antenna's gain. The proposed antenna has been examined, and the results indicate that it has a return loss of -37.4 dB at the resonant frequency of 3.5 GHz, an antenna gain of 7.22 dB, and a bandwidth of 286.5 MHz. The use of a single, dual, quad, and octal element array configuration is anticipated to improve the gain performance of the antenna, making it a promising option for 5G communication systems.
{"title":"Innovation Design of High Gain Array Antenna for 5G Communication","authors":"M. A. M. Said, M. H. Misran, M. Othman, R. A. Manap, A. Jaafar, S. Suhaimi, N. I. Hassan","doi":"10.46338/ijetae0723_02","DOIUrl":"https://doi.org/10.46338/ijetae0723_02","url":null,"abstract":"The fifth-generation (5G) wireless communication system requires high gain antennas to support the growing demand for high-speed data transmission and low-latency connectivity. High gain antennas are crucial for enhancing the signal strength and extending the coverage area of 5G networks. By using multiple antenna elements, an array can achieve higher gain and directivity compared to a single element antenna. This improvement in gain enables better signal reception and transmission, leading to increased communication range, higher data rates, and improved reliability. In this paper, we discuss the design and implementation of antenna arrays for improving antenna gain in 5G communication systems at 3.5 GHz.The design of the array antenna incorporates single, dual, quad, and octal element structures to enhance the antenna's gain. The proposed antenna has been examined, and the results indicate that it has a return loss of -37.4 dB at the resonant frequency of 3.5 GHz, an antenna gain of 7.22 dB, and a bandwidth of 286.5 MHz. The use of a single, dual, quad, and octal element array configuration is anticipated to improve the gain performance of the antenna, making it a promising option for 5G communication systems.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116103280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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