International Journal on Communications Antenna and Propagation最新文献_第9页

S-Band Transceiver Antenna for Telemetry and Telecommand Applications 遥测和遥控应用的s波段收发天线

International Journal on Communications Antenna and Propagation Pub Date : 2021-10-31 DOI: 10.15866/irecap.v11i5.20926

Sushma Shankarappa, V. S. Rao

引用次数: 0

Improving Network Entry Procedure in Broadband Wi-Fi Networks 改进宽带Wi-Fi网络入网程序

International Journal on Communications Antenna and Propagation Pub Date : 2021-10-31 DOI: 10.15866/irecap.v11i5.20996

M. Malkawi, Ahmed S. Shatnawi, Khaldoon Al-Zoubi, L. Alawneh

引用次数: 0

Electronically Controlled Reconfigurable Antenna for Polarization Diversity 用于极化分集的电控可重构天线

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20258

Sivakumar Ellusamy, Ramachandraan Balasubramanian

引用次数: 0

High Gain 30 GHz Multi-Band Multi-Faceted Miniature Antenna for 5G and Cancer Detection 用于5G和癌症检测的高增益30 GHz多频段多面微型天线

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.19747

Maria Moussa, M. Madi, K. Kabalan

引用次数: 0

Optimization the Accuracy of FFNN Based Speaker Recognition System Using PSO Algorithm 利用粒子群算法优化基于FFNN的说话人识别系统的精度

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.19883

A. M. Aaref, Zuhair Shakor Mahmood

{"title":"Optimization the Accuracy of FFNN Based Speaker Recognition System Using PSO Algorithm","authors":"A. M. Aaref, Zuhair Shakor Mahmood","doi":"10.15866/irecap.v11i4.19883","DOIUrl":"https://doi.org/10.15866/irecap.v11i4.19883","url":null,"abstract":"Speaker recognition systems use a model that learns a speaker's speech by inputting an audio recording and processing it. Time-varying signal, with frequencies that continuously change, is identified as a speech signal. There are many uncertain attributes to speech; thus traditional speech recognition techniques such as using zero crossings and the Fourier Transform are not up to the task. It aims to be accomplished with the aim of helping two causes. The first part is designed to address speaker identification technology that is resistant to noise. While most prior solutions have relied on changing mel frequency cepstrum coefficients, with a Fundamental frequency feature coefficient, this proposal integrates both of these modifications with a new cepstrum component. In order to construct the feature matrix, the system is fed with two-hundred and fifty speech imprints that are used to apply features extraction techniques. The matrix is used to teach the algorithm about features, and each one is then evaluated using incomplete data (thirty percent of total data in features matrix). Speaker recognition models with improved accuracy are developed by studying the algorithms invasively. These variables (metrics) are generated for each algorithm and applied to the algorithm for recognition accuracy and the time required to achieve that accuracy. When tested against previous research, the findings show that the Feed Forward Neural Network-based Particle Swarm Optimization method has been better. This model can accurately identify 96% of the input with less processing time. According to the findings, optimization utilizing advanced particle swarm optimization (a.k.a. Particle Swarm Optimization) is most likely responsible for the higher accuracy seen in speaker identification.","PeriodicalId":38104,"journal":{"name":"International Journal on Communications Antenna and Propagation","volume":"163 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86406451","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}

引用次数: 4

A Novel Approach to Brain Tumor Detection Using Texture Based Gabor Filter Followed by Genetic Algorithm 基于纹理Gabor滤波和遗传算法的脑肿瘤检测新方法

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20766

Kapil Kumar Gupta, Namrata Dhanda, U. Kumar

{"title":"A Novel Approach to Brain Tumor Detection Using Texture Based Gabor Filter Followed by Genetic Algorithm","authors":"Kapil Kumar Gupta, Namrata Dhanda, U. Kumar","doi":"10.15866/irecap.v11i4.20766","DOIUrl":"https://doi.org/10.15866/irecap.v11i4.20766","url":null,"abstract":"It is very important to consider the factors like blurred boundaries and external noise while analyzing the brain tumor structures. It is difficult to segment accurately the brain MRI. Many studies in both developing and developed countries indicate that an inactive diagnosis has led to the death of the majority of people who suffer from brain tumor. The proposed novel method is a filter mechanism based on texture Gabor filter, which is followed by a genetic algorithm proposed to improve segmentation accuracy. A texture-based Gabor filter has been used to detect irregularities and to extract statistical properties further used in segmentation and classification. In order to improve segmentation effectiveness, a better separation of different clusters of the features from Gabor filter is studied. An objective function has been also formalized to adjust filter parameters with gradient descent and genetic algorithm. This document has demonstrated the effects of the segmentation of both qualitative and quantitative productivity. The findings show that the novel proposed approach works better with respect to the segmentation accuracy.","PeriodicalId":38104,"journal":{"name":"International Journal on Communications Antenna and Propagation","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80924964","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}

引用次数: 1

Mitigating Deep learning Attacks Against Text Image CAPTCHA Using Arabic Scheme 使用阿拉伯语方案减轻对文本图像CAPTCHA的深度学习攻击

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20375

Mohammad Fawa’reh, Malik Qasaimeh, Ibrahim AbuArja, Mustafa A. Al-Fayoumi

{"title":"Mitigating Deep learning Attacks Against Text Image CAPTCHA Using Arabic Scheme","authors":"Mohammad Fawa’reh, Malik Qasaimeh, Ibrahim AbuArja, Mustafa A. Al-Fayoumi","doi":"10.15866/irecap.v11i4.20375","DOIUrl":"https://doi.org/10.15866/irecap.v11i4.20375","url":null,"abstract":"Confidentiality and availability are the main concerns of website stakeholders, entailing service-security trade-offs. Many solutions seek to improve security. The most popular one is the completely automated public Turing test (CAPTCHA) security framework, which distinguishes between human and bot activity by asking the user to perform a certain task, such as solving a mathematical equation or retyping text written in an image. Many people believe that websites using CAPTCHAs are secure, but today’s attackers using innovative technology, such as deep learning, that can break them in milliseconds. Many solutions have been proposed to overcome this issue, mainly relying on increased CAPTCHA complexity or technical CAPTCHAs too difficult for normal users. In this case, many customers may go to websites that use simple CAPTCHAs, at the expense of websites with more complex ones. This paper proposes a robust and simple image-based CAPTCHA using an Arabic scheme and noise to make breaking this captcha very difficult, even for deep learning approaches. The proposed model is evaluated using two-factor, which focuses on the usability and the ability to beak the proposed CAPTCHA. The first test has been done via an empirical experiment involving 16 people from different sectors, and the second test has involved breaking the model using Convolutional Neural Network (CNN). The experimental results demonstrate the superiority of the proposed model in security and usability.","PeriodicalId":38104,"journal":{"name":"International Journal on Communications Antenna and Propagation","volume":"244 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80558811","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}

引用次数: 1

Adjusted and Robust Routing Update Algorithms for Internet of Things 面向物联网的调整鲁棒路由更新算法

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20366

M. B. Yassein, Ahmad Alrawashdeh, Omar Alzoubi, M. Shatnawi

引用次数: 0

Fractal Inspired Metamaterial Superstrate for Gain Enhancement 用于增益增强的分形启发超材料衬底

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20861

B. K. A. Shaji, A. Pradeep, P. Mohanan

引用次数: 3

Sixth-Generation (6G) Microstrip Antenna with High-Gain 第六代(6G)高增益微带天线

International Journal on Communications Antenna and Propagation Pub Date : 2021-08-31 DOI: 10.15866/irecap.v11i4.20665

U. Nissanov, G. Singh, Akinola Segun

引用次数: 5