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Utilizing deep learning in chipless RFID tag detection: an investigation on high-precision mm-wave spatial tag estimation from 2D virtual imaging 在无芯片 RFID 标签检测中利用深度学习:对二维虚拟成像中高精度毫米波空间标签估计的研究
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-01-03 DOI: 10.1080/24751839.2023.2300223
Tahmid Hasan Pranto, Mohammad Nabiluzzaman Neloy, Abdulla All Noman, Sheikh Wasif, Md. Abdul Wahab, R. Rahman
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引用次数: 0
On the performance of outage probability in cognitive NOMA random networks with hardware impairments 论有硬件损伤的认知 NOMA 随机网络中的中断概率性能
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-12-20 DOI: 10.1080/24751839.2023.2294570
Pham Thi Dan Ngoc, Tran Trung Duy, Nguyen Luong Nhat, Tan Hanh, Yeon Ho Chung, L. Tu
{"title":"On the performance of outage probability in cognitive NOMA random networks with hardware impairments","authors":"Pham Thi Dan Ngoc, Tran Trung Duy, Nguyen Luong Nhat, Tan Hanh, Yeon Ho Chung, L. Tu","doi":"10.1080/24751839.2023.2294570","DOIUrl":"https://doi.org/10.1080/24751839.2023.2294570","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"200 ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139170357","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: 0
Relay-assisted communication over a fluctuating two-ray fading channel 波动双射线衰减信道上的中继辅助通信
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-12-19 DOI: 10.1080/24751839.2023.2295094
H. Mehdi, Zakir Hussain, S. M. A. Saleem, Syed Areeb Ahmed
{"title":"Relay-assisted communication over a fluctuating two-ray fading channel","authors":"H. Mehdi, Zakir Hussain, S. M. A. Saleem, Syed Areeb Ahmed","doi":"10.1080/24751839.2023.2295094","DOIUrl":"https://doi.org/10.1080/24751839.2023.2295094","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":" 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962758","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: 0
Modified Caesar Cipher and Card Deck Shuffle Rearrangement Algorithm for Image Encryption 用于图像加密的修正凯撒密码和洗牌重排算法
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-11-26 DOI: 10.1080/24751839.2023.2285549
Dhairya Veera, Ramchandra S. Mangrulkar, Chetashri Bhadane, Kiran Bhowmick, P. Chavan
{"title":"Modified Caesar Cipher and Card Deck Shuffle Rearrangement Algorithm for Image Encryption","authors":"Dhairya Veera, Ramchandra S. Mangrulkar, Chetashri Bhadane, Kiran Bhowmick, P. Chavan","doi":"10.1080/24751839.2023.2285549","DOIUrl":"https://doi.org/10.1080/24751839.2023.2285549","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"176 12 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235458","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: 0
Application of data envelopment analysis to IT project evaluation, with special emphasis on the choice of inputs and outputs in the context of the organization in question 在信息技术项目评估中应用数据包络分析法,特别强调在有关组织的背景下选择投入和产出
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-11-26 DOI: 10.1080/24751839.2023.2286764
B. Gładysz, D. Despotis, D. Kuchta
{"title":"Application of data envelopment analysis to IT project evaluation, with special emphasis on the choice of inputs and outputs in the context of the organization in question","authors":"B. Gładysz, D. Despotis, D. Kuchta","doi":"10.1080/24751839.2023.2286764","DOIUrl":"https://doi.org/10.1080/24751839.2023.2286764","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"13 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235705","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: 0
Coverage probability of energy harvesting enabled LoRa networks with stochastic geometry 具有随机几何形状的能量采集 LoRa 网络的覆盖概率
IF 2.7 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-11-19 DOI: 10.1080/24751839.2023.2281144
Thi-Tuyet-Hai Nguyen, Tan N. Nguyen, Tran Trung Duy, Nguyen Hong Son, Tan Hanh, Minh Bui Vu, L. Tu
{"title":"Coverage probability of energy harvesting enabled LoRa networks with stochastic geometry","authors":"Thi-Tuyet-Hai Nguyen, Tan N. Nguyen, Tran Trung Duy, Nguyen Hong Son, Tan Hanh, Minh Bui Vu, L. Tu","doi":"10.1080/24751839.2023.2281144","DOIUrl":"https://doi.org/10.1080/24751839.2023.2281144","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"38 5","pages":""},"PeriodicalIF":2.7,"publicationDate":"2023-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139260425","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: 0
Lightweight authentication scheme based on Elliptic Curve El Gamal 基于椭圆曲线El - Gamal的轻量级认证方案
Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-11-14 DOI: 10.1080/24751839.2023.2281143
Sondes Baccouri, Hassene Farhat, Tarek Azzabi, Rabah Attia
Elliptic Curve Cryptography (ECC) is a promising cryptosystem as it presents the ideal choice for implementing public-key cryptography in resource-limited devices, such as those found in envisioned Internet of Things applications, e.g. wireless sensors. Elliptic Curve ElGamal (ECEG) is a renowned member of the ECC family. However, it requires encoding the message before encryption and decoding it after decryption. To better improve the processing time and to avoid sharing a lookup table, we propose, in this document, a new method that exchanges encoding parameters and authenticates endpoints at the same time. So, our new protocol ensures the authentication of communication parties and integrity of ephemeral encoding parameters. The robustness of our solution is proven by the Scyther tool. Experimental tests have been carried out, and the performance of the new methods is provided and compared with RSA and related work. Security and performance analysis show that our new scheme has achieved improved functionality and higher security while maintaining low computational.
椭圆曲线加密(ECC)是一种很有前途的加密系统,因为它为在资源有限的设备中实现公钥加密提供了理想的选择,例如在设想的物联网应用中发现的设备,例如无线传感器。椭圆曲线ElGamal (ECEG)是ECC家族中著名的成员。但是,它要求在加密之前对消息进行编码,在解密之后对消息进行解码。为了更好地改进处理时间并避免共享查找表,本文提出了一种同时交换编码参数和验证端点的新方法。因此,我们的协议保证了通信双方的身份验证和临时编码参数的完整性。Scyther工具证明了我们的解决方案的健壮性。进行了实验测试,给出了新方法的性能,并与RSA及相关工作进行了比较。安全性和性能分析表明,新方案在保持较低的计算量的同时,实现了更强的功能和更高的安全性。
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引用次数: 0
Feature selection in intrusion detection systems: a new hybrid fusion of Bat algorithm and Residue Number System 入侵检测系统中的特征选择:一种新的Bat算法与剩余数系统的混合融合
Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-11-06 DOI: 10.1080/24751839.2023.2272484
Yakub Kayode Saheed, Temitope Olubanjo Kehinde, Mustafa Ayobami Raji, Usman Ahmad Baba
This research introduces innovative approaches to enhance intrusion detection systems (IDSs) by addressing critical challenges in existing methods. Various machine-learning techniques, including nature-inspired metaheuristics, Bayesian algorithms, and swarm intelligence, have been proposed in the past for attribute selection and IDS performance improvement. However, these methods have often fallen short in terms of detection accuracy, detection rate, precision, and F-score. To tackle these issues, the paper presents a novel hybrid feature selection approach combining the Bat metaheuristic algorithm with the Residue Number System (RNS). Initially, the Bat algorithm is utilized to partition training data and eliminate irrelevant attributes. Recognizing the Bat algorithm's slower training and testing times, RNS is incorporated to enhance processing speed. Additionally, principal component analysis (PCA) is employed for feature extraction. In a second phase, RNS is excluded for feature selection, allowing the Bat algorithm to perform this task while PCA handles feature extraction. Subsequently, classification is conducted using naive bayes, and k-Nearest Neighbors. Experimental results demonstrate the remarkable effectiveness of combining RNS with the Bat algorithm, achieving outstanding detection rates, accuracy, and F-scores. Notably, the fusion approach doubles processing speed. The findings are further validated through benchmarking against existing intrusion detection methods, establishing their competitiveness.
本研究通过解决现有方法中的关键挑战,介绍了增强入侵检测系统(ids)的创新方法。过去已经提出了各种机器学习技术,包括自然启发的元启发式、贝叶斯算法和群体智能,用于属性选择和IDS性能改进。然而,这些方法在检测准确率、检出率、精密度和f分数方面往往存在不足。为了解决这些问题,本文提出了一种将Bat元启发式算法与剩余数系统(RNS)相结合的混合特征选择方法。首先利用Bat算法对训练数据进行分割,剔除不相关属性。考虑到Bat算法的训练和测试时间较慢,引入RNS来提高处理速度。此外,采用主成分分析(PCA)进行特征提取。在第二阶段,排除RNS进行特征选择,允许Bat算法执行此任务,而PCA处理特征提取。随后,使用朴素贝叶斯和k近邻进行分类。实验结果表明,RNS与Bat算法相结合的效果显著,检测率、准确率和f分数都很好。值得注意的是,融合方法将处理速度提高了一倍。通过对现有入侵检测方法的基准测试,进一步验证了研究结果,从而确立了它们的竞争力。
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引用次数: 0
Employing synthetic data for addressing the class imbalance in aspect-based sentiment classification 利用合成数据解决基于方面的情感分类中的类不平衡问题
Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-10-30 DOI: 10.1080/24751839.2023.2270824
Vaishali Ganganwar, Ratnavel Rajalakshmi
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引用次数: 0
Efficient near-field localization aided with reconfigurable intelligent surface using geometric dilution of precision 利用几何精度稀释辅助可重构智能曲面的高效近场定位
Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-10-26 DOI: 10.1080/24751839.2023.2272488
Abdulrahaman Kh. Alhafid, Sedki Younis, Y. E. Mohammed Ali
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引用次数: 0
期刊
Journal of Information and Telecommunication
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