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2. Wireless technologies and the Internet of Things

Author

Pachouri, Vikrant, primary, Kathuria, Samta, additional, Pandey, Shweta, additional, Singh, Rajesh, additional, Gehlot, Anita, additional, Akram, Shaik Vaseem, additional, Malik, Praveen Kumar, additional, and Yasmeen, Safia, additional

Published
2023
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13. Node Multi-Attribute Network Community Healthcare Detection Based on Graphical Matrix Factorization.

Author

Alferaidi, Ali, Yadav, Kusum, Yasmeen, Safia, Alharbi, Yasser, Viriyasitavat, Wattana, Dhiman, Gaurav, and Kaur, Amandeep

Subjects
MATRIX decomposition, INFORMATION networks, COLLABORATIVE learning, LOCAL mass media, SOCIAL networks, VIRTUAL communities
Abstract

The significance of community structure in complex networks, such as social, biological, and online networks, has been widely recognized. Detecting communities in social media networks typically relies on two sources of information: the network's topological structure and node attributes. Incorporating rich node content attribute information poses both flexibility and challenges for community detection. Traditional approaches either focus on mining one information source or linearly combining results from both sources, which fails to effectively fuse the information. This paper introduces a practical collaborative learning approach that explores the multi-dimensional attribute characteristics of nodes to facilitate community division. By leveraging graphical matrix decomposition, the proposed algorithm, CDGMF, improves the effectiveness and robustness of community detection. Experimental results demonstrate the method's ability to effectively utilize node attribute information for guiding community detection, resulting in higher-quality community divisions. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Construction and Piloting of Attitude Towards Research Participation Scale for University Students

Author

Khan,Khatib Ahmad, Aigerim,Danabekova, Zhao,Xueqing, Adil,Adnan, Ghayas,Saba, Yasmeen,Safia, Khalid,Kinza, Tahir,Ammara, Khan,Khatib Ahmad, Aigerim,Danabekova, Zhao,Xueqing, Adil,Adnan, Ghayas,Saba, Yasmeen,Safia, Khalid,Kinza, and Tahir,Ammara

Abstract

Khatib Ahmad Khan,1 Danabekova Aigerim,2 Zhao Xueqing,2 Adnan Adil,3 Saba Ghayas,3 Safia Yasmeen,3 Kinza Khalid,3 Ammara Tahir3 1School of Oriental Studies, Xian International Studies University, Xi’an, People’s Republic of China; 2School of Chinese Language and Literature, Shaanxi Normal University, Xi’an, People’s Republic of China; 3Department of Psychology, University of Sargodha, Sargodha, Punjab, PakistanCorrespondence: Saba GhayasDepartment of Psychology, University of Sargodha, Sargodha, Punjab, PakistanEmail Saba.ghayas@uos.edu.pkIntroduction: Attitude toward participation in the research plays an important role in the quality of any research. Therefore, researchers aimed at construction and piloting of scale to measure attitude toward research participation for university students.Method and Results: In Study I, an initial pool of items was generated on the basis of literature review, semi-structured interviews and expert opinions. After ensuring content validity and finalizing items with the help of experts, the scale was applied on a sample of 426 university students including both men (n = 114) and women (n = 312) with age range of 17– 30. Exploratory factor analysis revealed the two factor structure was with 60.33% cumulative variance. The factors revealed were positive attitude and negative attitude toward research with alpha reliability of 0.84 for positive attitude while 0.76 for negative attitude. In Study II, confirmatory factor analysis revealed excellent model fit indices with two factor structure. Study III was meant to provide evidence of construct validity. Positive correlation showed exploration and curiosity with positive attitude toward research and negative correlation of exploration and curiosity with negative attitude toward research participation provided strong evidence for convergent validity. While non-significant correlation of attitude toward research with religiosity confirmed the divergent validity of the scale.Conclus

Published
2021

17. Encrypted images in a V‐BLASTassisted SC‐FDMAwireless communication system

Author

Hasan, Mohammad Kamrul, Hosain, Md. Sarwar, Ahmed, Md. Kawsar, Islam, Shayla, Aledaily, Arwa N., Yasmeen, Safia, and Zainul Ariffin, Khairul Akram

Abstract

The internet of things (IoT) relies on fifth generation (5G) networks as the foundation for interconnecting devices. Wireless networks are an essential component of 5G‐IoT technology, as they provide the means to interconnect devices and transmit data wirelessly. The performance of the wireless network, including its capacity, integrity, bandwidth, and latency, is critical in ensuring the reliable and secure transmission of data in 5G‐IoT. 5G is being developed with the goal of delivering exceptionally high capacity, solid integrity, high bandwidth, and low latency. With the development and innovation of new approaches for 5G‐IoT, new significant security and privacy concerns are certain to arise. As a result, secure data transmission mechanisms will be required as the foundation for 5G‐IoT technologies in order to solve these emerging difficulties. Deoxyribonucleic acid (DNA) cryptograms encrypt data by utilizing it as a carrier and biological technology. On an 8 by 8 multiantenna single carrier frequency division multiple access (SC‐FDMA) wireless system, we evaluate and compare the performance of DNA sine map‐based encrypted images using three different modulation algorithms: 16‐QAM, 16‐PSK, and 16‐DPSK. We also determine the bit error rate (BER) value for different signal to noise ratio (SNR) by analyzing the decrypted image's modulation performance. The methods minimum mean square error (MMSE), minimum mean error square successive interference cancelation (MMSE‐SIC), and zero‐forcing (ZF) are utilized for signal detection. Simulations in MATLAB reveal that the system is very effective and reliable when tested with MMSE‐SIC signal detection, 16‐QAM modulation, and low‐density parity check (LDPC) channel coding. This article presents the following main contributions: A comprehensive evaluation of the performance of DNA sine map‐based encrypted images using three distinct detection techniques.A novel approach for enhancing the security of image data through DNA cryptograms.Identification of the limitations of existing techniques in securing 5G‐IoT networks.Development of a more robust system for secure data transmission in 5G‐IoT networks, as demonstrated through MATLAB simulations.

Published
2024
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