Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039618
Sachin Sase, B. Ballal
Sign language is a way which deaf and dumb people use for communication. These people face lots of difficulty in communication with normal people since normal people does not know the sign language. This paper describes the several methods for data collection, pre- processing, features extraction and classification for the translation of sign language to audio, along with the suggested system. The purpose of this paper is to outline several techniques for translation of sign language into audio and vice versa, as well as to develop a communication system to achieve efficient communication between disable and normal people. This project converts sign language into Audio for Dumb people and Audio into sign language for deaf people. It consists of two stages: the first stage comprises of CNN which translates an ASL hand gesture into audio, and the second stage comprises of speech recognition which translates audio from any language into sign language.
{"title":"Review and Comparison of Different Methods Involved in Process of Efficient Communication Between Disabled and Normal People","authors":"Sachin Sase, B. Ballal","doi":"10.1109/ICAST55766.2022.10039618","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039618","url":null,"abstract":"Sign language is a way which deaf and dumb people use for communication. These people face lots of difficulty in communication with normal people since normal people does not know the sign language. This paper describes the several methods for data collection, pre- processing, features extraction and classification for the translation of sign language to audio, along with the suggested system. The purpose of this paper is to outline several techniques for translation of sign language into audio and vice versa, as well as to develop a communication system to achieve efficient communication between disable and normal people. This project converts sign language into Audio for Dumb people and Audio into sign language for deaf people. It consists of two stages: the first stage comprises of CNN which translates an ASL hand gesture into audio, and the second stage comprises of speech recognition which translates audio from any language into sign language.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"20 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123618546","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039547
S. Agarwal, Vikram Kandoria, Yash Kankriya, Anish Kuckian, Vaishali Wadhe
This article focuses on the application on momentary intelligence-supported computing technology. The article first analyzes computer science technology and its applicability within the financial field and so analyzes the thought of monetary intelligence application construction. this text takes a financial robot actually put into use by an organization as an example and introduces the particular applications and effects of economic intelligence applications within the four perspectives on the financial sector: fundamental operations, intelligent processing, data statistics, and risk management. this text provides empirical data from the appliance of AI in finance and provides references for other enterprises to use computer science technology.
{"title":"Innovations in Financial Intelligence Applications using Artificial Intelligence","authors":"S. Agarwal, Vikram Kandoria, Yash Kankriya, Anish Kuckian, Vaishali Wadhe","doi":"10.1109/ICAST55766.2022.10039547","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039547","url":null,"abstract":"This article focuses on the application on momentary intelligence-supported computing technology. The article first analyzes computer science technology and its applicability within the financial field and so analyzes the thought of monetary intelligence application construction. this text takes a financial robot actually put into use by an organization as an example and introduces the particular applications and effects of economic intelligence applications within the four perspectives on the financial sector: fundamental operations, intelligent processing, data statistics, and risk management. this text provides empirical data from the appliance of AI in finance and provides references for other enterprises to use computer science technology.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129112633","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039580
Vedant Kokate, Arghyadeep Karmakar, Mustansir Kapasi, H. Chavan
Voice and speech pattern analysis can help improve conversational and persuading abilities, especially in situations or applications where direct face-to-face human engagement is not possible or preferable. This paper proposes methods for accurately predicting emotions. in a voice sample. Additive white Gaussian noise is added to avoid overfitting and create real-environment sound. This paper uses the Mel spectrogram to extract features. Multilayer Perceptron, 1D-CNN, 2D-CNN, and transformer-based parallel CNN have been used to appropriately classify human emotions from speech samples. Previously unseen, transformer-based architectures have had a breakthrough in recent times and using them in audio processing and emotion mapping is rather novel which we intend to do.
{"title":"An Algorithmic Approach to Audio Processing and Emotion Mapping","authors":"Vedant Kokate, Arghyadeep Karmakar, Mustansir Kapasi, H. Chavan","doi":"10.1109/ICAST55766.2022.10039580","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039580","url":null,"abstract":"Voice and speech pattern analysis can help improve conversational and persuading abilities, especially in situations or applications where direct face-to-face human engagement is not possible or preferable. This paper proposes methods for accurately predicting emotions. in a voice sample. Additive white Gaussian noise is added to avoid overfitting and create real-environment sound. This paper uses the Mel spectrogram to extract features. Multilayer Perceptron, 1D-CNN, 2D-CNN, and transformer-based parallel CNN have been used to appropriately classify human emotions from speech samples. Previously unseen, transformer-based architectures have had a breakthrough in recent times and using them in audio processing and emotion mapping is rather novel which we intend to do.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117062567","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039589
S. Redekar, S. Varma, A. Bhattacharjee
Glioblastoma multiforme (GBM) is an aggressive type of brain tumour that progresses quickly and has a poor survival. Survival analysis is a statistical method used to examine how long an event is likely to take place before occurring, such as death in biological organisms or failure in mechanical systems. This analysis is called as time to event analysis as it is used to determine how long it will be before a specific event of interest, like death or recurrence, happens. There are numerous statistical techniques that make it possible to estimate the overall survival (OS) of GBM patients, which is highly useful for developing targeted medicines to slow the growth of a disease. It also helps to determine factors contributing to the survival of the patient. Based on the distribution of relevant events, these statistical techniques use a variety of non-parametric, semi-parametric, and parametric approaches. From TCGA, genomic datasets of GBM patients and information on their survival are gathered for this investigation. Three statistical techniques to evaluate the patterns of event timings and investigate how much some genetic characteristics influence the risk of an event of interest, Kaplan Meier, Cox Regression Model, and Accelerated Failure Time Model are used. Significant genes that are connected to the GBM patient's survival are identified in study.
{"title":"Extrication of Survival Associated Genes of Glioblastoma Multiforme Patient through Statistical Modeling","authors":"S. Redekar, S. Varma, A. Bhattacharjee","doi":"10.1109/ICAST55766.2022.10039589","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039589","url":null,"abstract":"Glioblastoma multiforme (GBM) is an aggressive type of brain tumour that progresses quickly and has a poor survival. Survival analysis is a statistical method used to examine how long an event is likely to take place before occurring, such as death in biological organisms or failure in mechanical systems. This analysis is called as time to event analysis as it is used to determine how long it will be before a specific event of interest, like death or recurrence, happens. There are numerous statistical techniques that make it possible to estimate the overall survival (OS) of GBM patients, which is highly useful for developing targeted medicines to slow the growth of a disease. It also helps to determine factors contributing to the survival of the patient. Based on the distribution of relevant events, these statistical techniques use a variety of non-parametric, semi-parametric, and parametric approaches. From TCGA, genomic datasets of GBM patients and information on their survival are gathered for this investigation. Three statistical techniques to evaluate the patterns of event timings and investigate how much some genetic characteristics influence the risk of an event of interest, Kaplan Meier, Cox Regression Model, and Accelerated Failure Time Model are used. Significant genes that are connected to the GBM patient's survival are identified in study.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124152252","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039650
A. Deshmukh, S. Govilkar
Traditional media is no more the only source of gaining news. Social media has taken over traditional media for various reasons, like being easy to use, free of cost, and always available. However, not all news published on social media is genuine, as it can come from unverified sources also. Most people believe what they read, and hence it is essential to check the authentication of news readers. The spread of fake news could cause severe impacts not just politically but also socially. We strongly believe that spread of intentionally created fake news is more harmful than an accidental one. This paper mainly focuses on the deliberate creation and sharing of false manipulated information intended to deceive and mislead audiences. Fake news detection is a classic classification problem though many attempts of solving it through clustering are being made. Our study mainly focuses on classification algorithms. We used various classification algorithms like SVM, DT, LR, and passive Aggressive Classifier on datasets to find if the news is real or fake on two different datasets. Evaluation parameters were executed to compare the efficiency of the various algorithm. Later we also try to find out which other social media the author accounts for to stop the spread of fake news.
{"title":"Fake News Detection on Datasets","authors":"A. Deshmukh, S. Govilkar","doi":"10.1109/ICAST55766.2022.10039650","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039650","url":null,"abstract":"Traditional media is no more the only source of gaining news. Social media has taken over traditional media for various reasons, like being easy to use, free of cost, and always available. However, not all news published on social media is genuine, as it can come from unverified sources also. Most people believe what they read, and hence it is essential to check the authentication of news readers. The spread of fake news could cause severe impacts not just politically but also socially. We strongly believe that spread of intentionally created fake news is more harmful than an accidental one. This paper mainly focuses on the deliberate creation and sharing of false manipulated information intended to deceive and mislead audiences. Fake news detection is a classic classification problem though many attempts of solving it through clustering are being made. Our study mainly focuses on classification algorithms. We used various classification algorithms like SVM, DT, LR, and passive Aggressive Classifier on datasets to find if the news is real or fake on two different datasets. Evaluation parameters were executed to compare the efficiency of the various algorithm. Later we also try to find out which other social media the author accounts for to stop the spread of fake news.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126577464","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039666
Dishant Padalia, K. Vora, Deepak Kumar Sharma
Dental disorders can lead to serious implications such as heart attack or strokes if not diagnosed and treated early. The diagnosis of these disorders differs from dentist to dentist due to differences in perception, poor x-ray quality because of noise, and different types of patients. As a result, there is an urgent need to create automated, AI-driven diagnostic solutions for dental disorders. Deep learning solutions have shown outstanding results in automated medical image analysis tasks. Our work proposes a U-Net with attention blocks to segment teeth from dental panoramic X-rays. The proposed Attention U-Net consists of four encoding and decoding blocks and achieved Dice Coefficient, IOU score, Specificity, and F1 Score of 0.9318, 0.8724, 0.9910, and 0.9379, respectively. The Attention U-Net achieves a 1.7% better Dice Coefficient score and 2.9% better IOU (Intersection Over Union) score than one of the best segmentation models, the U-Net. The segmented output can be used in computer-aided diagnostic (CAD) systems to detect various mouth disorders, helping the dentist diagnose the problem efficiently and accurately.
如果不及早诊断和治疗，牙齿疾病会导致严重的后果，如心脏病发作或中风。不同的牙医对这些疾病的诊断也不同，因为他们的感知不同，x光片的质量因噪音而差，以及不同的患者类型。因此，迫切需要为牙齿疾病创建自动化、人工智能驱动的诊断解决方案。深度学习解决方案在自动医学图像分析任务中显示出出色的效果。我们的工作提出了一个带有注意块的U-Net，用于从牙齿全景x射线中分割牙齿。本文提出的注意力U-Net由4个编解码块组成，其Dice Coefficient、IOU score、Specificity和F1 score分别为0.9318、0.8724、0.9910和0.9379。注意力U-Net比最好的分割模型之一U-Net的Dice Coefficient得分高1.7%，IOU (Intersection Over Union)得分高2.9%。分割输出可用于计算机辅助诊断(CAD)系统中检测各种口腔疾病，帮助牙医高效准确地诊断问题。
{"title":"An Attention U-Net for Semantic Segmentation of Dental Panoramic X-ray images","authors":"Dishant Padalia, K. Vora, Deepak Kumar Sharma","doi":"10.1109/ICAST55766.2022.10039666","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039666","url":null,"abstract":"Dental disorders can lead to serious implications such as heart attack or strokes if not diagnosed and treated early. The diagnosis of these disorders differs from dentist to dentist due to differences in perception, poor x-ray quality because of noise, and different types of patients. As a result, there is an urgent need to create automated, AI-driven diagnostic solutions for dental disorders. Deep learning solutions have shown outstanding results in automated medical image analysis tasks. Our work proposes a U-Net with attention blocks to segment teeth from dental panoramic X-rays. The proposed Attention U-Net consists of four encoding and decoding blocks and achieved Dice Coefficient, IOU score, Specificity, and F1 Score of 0.9318, 0.8724, 0.9910, and 0.9379, respectively. The Attention U-Net achieves a 1.7% better Dice Coefficient score and 2.9% better IOU (Intersection Over Union) score than one of the best segmentation models, the U-Net. The segmented output can be used in computer-aided diagnostic (CAD) systems to detect various mouth disorders, helping the dentist diagnose the problem efficiently and accurately.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131841608","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}
With the rise in Internet and Network applications in the last decade, there is a need for making communication over the internet to be more secure and strong in order to avoid cyber-attacks. The use of digital signatures has been widely used and there is a need to strengthen the existing public key algorithms. RSA is among the most common public key algorithms but is prone to security risks and attacks due to the advancing computing technology. This paper suggests a new algorithm based on RSA which increases the randomness and diffusion of the RSA algorithm making it more secure from cyber-attacks than RSA. The suggested approach employs four prime integers to generate two sets of public and private keys and involves double encryption and decryption. This modified form of the RSA method adds to the complexity of the encryption process while simultaneously decreasing the decryption time by leveraging the Chinese Remainder theorem.
{"title":"Enhanced RSA Cryptosystem: A Secure and Nimble Approach","authors":"Tanay Gandhi, Meith Navlakha, Rahul Raheja, Varun Mehta, Yash Jhaveri, N. Shekokar","doi":"10.1109/ICAST55766.2022.10039627","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039627","url":null,"abstract":"With the rise in Internet and Network applications in the last decade, there is a need for making communication over the internet to be more secure and strong in order to avoid cyber-attacks. The use of digital signatures has been widely used and there is a need to strengthen the existing public key algorithms. RSA is among the most common public key algorithms but is prone to security risks and attacks due to the advancing computing technology. This paper suggests a new algorithm based on RSA which increases the randomness and diffusion of the RSA algorithm making it more secure from cyber-attacks than RSA. The suggested approach employs four prime integers to generate two sets of public and private keys and involves double encryption and decryption. This modified form of the RSA method adds to the complexity of the encryption process while simultaneously decreasing the decryption time by leveraging the Chinese Remainder theorem.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131548396","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039613
Ankit Thakker, Nikhil Namboodiri, Ritik Mody, Riya Tasgaonkar, Mansi Kambli
For many years, lossless image compression has been a promising topic of study. Various techniques have been created over time to obtain an approximation of the reduced data size. While discrete wavelet transform (DWT) and discrete cosine transform (DCT) have historically been employed for the purpose of compressing images, various machine learning methods and deep learning networks are now being offered. In this research, we conduct a comparative analysis of conventional and contemporary lossy image compression techniques on the Kodak Dataset, including Autoencoders, Principal Component Analysis (PCA), K-Means, and Discrete Wavelet Transform (DWT). The metrics used for the evaluation of the proposed study are Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR), and Structural Similarity Index (SSIM).
{"title":"Lossy Image Compression-A Comparison Between Wavelet Transform, Principal Component Analysis, K-Means and Autoencoders","authors":"Ankit Thakker, Nikhil Namboodiri, Ritik Mody, Riya Tasgaonkar, Mansi Kambli","doi":"10.1109/ICAST55766.2022.10039613","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039613","url":null,"abstract":"For many years, lossless image compression has been a promising topic of study. Various techniques have been created over time to obtain an approximation of the reduced data size. While discrete wavelet transform (DWT) and discrete cosine transform (DCT) have historically been employed for the purpose of compressing images, various machine learning methods and deep learning networks are now being offered. In this research, we conduct a comparative analysis of conventional and contemporary lossy image compression techniques on the Kodak Dataset, including Autoencoders, Principal Component Analysis (PCA), K-Means, and Discrete Wavelet Transform (DWT). The metrics used for the evaluation of the proposed study are Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR), and Structural Similarity Index (SSIM).","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"99 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879143","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039607
S. Virnodkar, Kashyap Kotak, R. Jinturkar, Prince Karania
The digital world is lately experiencing tremendous increase in the number of users, leading to almost an exponential growth in data, which in turn has increased the number of users accessing the data, thus making the antecedent data handling and digital traffic handling techniques counterproductive. As a result, a demand for new technologies and standards for handling this huge amount of data and traffic accessing the data has come into sight. This review paper focuses on analyzing the presently existing big data handling technologies. This paper also discusses the network traffic handling methods used till date.
{"title":"Efficient Handling of Big Data and Network Traffic Control: A Review","authors":"S. Virnodkar, Kashyap Kotak, R. Jinturkar, Prince Karania","doi":"10.1109/ICAST55766.2022.10039607","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039607","url":null,"abstract":"The digital world is lately experiencing tremendous increase in the number of users, leading to almost an exponential growth in data, which in turn has increased the number of users accessing the data, thus making the antecedent data handling and digital traffic handling techniques counterproductive. As a result, a demand for new technologies and standards for handling this huge amount of data and traffic accessing the data has come into sight. This review paper focuses on analyzing the presently existing big data handling technologies. This paper also discusses the network traffic handling methods used till date.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133093037","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}
Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039615
Sonal R. Jatkar, N. Kasat
In this article, conductive electro-textile and cotton substrate is used to fabricate a T-shaped ultra-wideband (UWB) antenna. Using ANSYS high frequency structural simulator (HFSS), $mathrm{S}11leq-10 text{dB}$ and Voltage Standing Wave Ratio $(text{VSWR})leq 2$ is obtained for the coplanar waveguide (CPW)–fed antenna over the range of frequency from 3.5 to 12 GHz. The antenna's 50 mm x 38 mm x 0.6 mm dimensions allowed it to radiate in a directed manner with a 5 dBi average peak gain over the whole impedance bandwidth. This paper's main contribution is the use of a wearable antenna with a 159.24% wide impedance bandwidth.
本文采用导电电织物和棉质衬底制备了t型超宽带天线。利用ANSYS高频结构模拟器(HFSS)计算了共面波导馈电天线在3.5 ～ 12 GHz频率范围内的驻波比$mathrm{S}11leq-10 text{dB}$和电压驻波比$(text{VSWR})leq 2$。天线的尺寸为50mm x 38mm x 0.6 mm，使其能够在整个阻抗带宽上以5dbi的平均峰值增益定向辐射。本文的主要贡献是使用了159.24的可穿戴天线% wide impedance bandwidth.
{"title":"Design of a T-shaped UWB Textile Antenna for WiMax/WLAN Application","authors":"Sonal R. Jatkar, N. Kasat","doi":"10.1109/ICAST55766.2022.10039615","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039615","url":null,"abstract":"In this article, conductive electro-textile and cotton substrate is used to fabricate a T-shaped ultra-wideband (UWB) antenna. Using ANSYS high frequency structural simulator (HFSS), $mathrm{S}11leq-10 text{dB}$ and Voltage Standing Wave Ratio $(text{VSWR})leq 2$ is obtained for the coplanar waveguide (CPW)–fed antenna over the range of frequency from 3.5 to 12 GHz. The antenna's 50 mm x 38 mm x 0.6 mm dimensions allowed it to radiate in a directed manner with a 5 dBi average peak gain over the whole impedance bandwidth. This paper's main contribution is the use of a wearable antenna with a 159.24% wide impedance bandwidth.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115040860","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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