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Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

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Computers, Materials & Continua 2022年第12期73卷 6367-6391页

作者： farhan amin Gyu Sang Choi Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The Internet of Things(IoT)has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional *** network analysis(SNA)is a good example that has recently gained a lot of scientific *** has its roots in social and economic research,as well as the evaluation of network science,such as graph *** in this area have subverted predefined theories,offering revolutionary ones regarding interconnected networks,and they have highlighted the mystery of six degrees of separation with confirmation of the small-world *** motivation of this study is to understand and capture the clustering properties of large networks and social *** present a network growth model in this paper and build a scale-free artificial social network with controllable clustering *** random walk technique is paired with a triangle generating scheme in our proposed *** a result,the clustering controlmechanism and preferential attachment(PA)have been *** research builds on the present random walk *** took numerous measurements for validation,including degree behavior and the measure of clustering decay in terms of node degree,among other ***,we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods,and hence it could be a viable alternative for societal evolution.

关键词： Social networks small-world networks network generation models graph theory random walk network design social network analysis

Automated Service Search Model for the Social Internet of Things

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Computers, Materials & Continua 2022年第9期72卷 5871-5888页

作者： farhan amin Seong Oun Hwang Department of Computer Engineering Gachon UniversitySeongnam13120Korea

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service *** SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human *** IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest *** proliferation of offered services led to difficulties during service customization and service *** problem is known as service *** selection of suitable service that fits the requirements of applications and objects is a challenging *** address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the *** the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global *** employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality *** distributed nature of our navigation model results in high scalability and short navigation *** verified the efficacy of our model on a real-world SIoT-related *** experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

关键词： Social internet of things service discovery local navigability object discovery query generation model

Big Data Analytics Using Graph Signal Processing

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Computers, Materials & Continua 2023年第1期74卷 489-502页

作者： farhan amin Omar M.Barukab Gyu Sang Choi Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Computing and Information Technology-Rabigh King Abdulaziz UniversityJeddahSaudi Arabia

The networks are fundamental to our modern world and they appear throughout science and *** to a massive amount of data presents a unique opportunity to the researcher’s *** networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep ***,this paper initiates a discussion on graph signal processing for large-scale data *** first provide a comprehensive overview of core ideas in Graph signal processing(GSP)and their connection to conventional digital signal processing(DSP).We then summarize recent developments in developing basic GSP tools,including methods for graph filtering or graph learning,graph signal,graph Fourier transform(GFT),spectrum,graph frequency,*** filtering is a basic task that allows for isolating the contribution of individual frequencies and therefore enables the removal of *** then consider a graph filter as a model that helps to extend the application of GSP methods to large *** show the suitability and the effeteness,we first created a noisy graph signal and then applied it to the *** several rounds of simulation *** see that the filtered signal appears to be smoother and is closer to the original noise-free distance-based *** using this example application,we thoroughly demonstrated that graph filtration is efficient for big data analytics.

关键词： Big data data science big data processing graph signal processing social networks

Advanced Community Identification Model for Social Networks

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Computers, Materials & Continua 2021年第11期69卷 1687-1707页

作者： farhan amin Jin-Ghoo Choi Gyu Sang Choi Department of Computer Engineering Gachon UniversityGyeonggi-do13120Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Community detection in social networks is a hard problem because of the size,and the need of a deep understanding of network structure and *** several methods with significant effort in this direction have been devised,an outstanding open problem is the unknown number of communities,it is generally believed that the role of influential nodes that are surrounded by neighbors is very *** addition,the similarity among nodes inside the same cluster is greater than among nodes from other ***,the global and local methods of community detection have been getting more ***,in this study,we propose an advanced communitydetection model for social networks in order to identify network communities based on global and local *** proposed model initially detects the most influential nodes by using an Eigen score then performs local expansion powered by label *** process is conducted with the same color till nodes reach maximum ***,the communities are formed,and a clear community graph is displayed to the *** proposed model is completely parameter-free,and therefore,no prior information is required,such as the number of communities,*** perform simulations and experiments using well-known synthetic and real network benchmarks,and compare them with well-known state-of-the-art *** results prove that our model is efficient in all aspects,because it quickly identifies communities in the ***,it can easily be used for friendship recommendations or in business recommendation systems.

关键词： Community detection social network analysis complex networks

Correlation between Electrodiagnostic Study and Magnetic Resonance Imaging in Lumbar Radiculopathy Patients in a Tertiary Care Hospital

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Case Reports in Clinical Medicine 2023年第10期12卷 363-370页

作者： farhan Murtaza Samana Haider Amna amin Aroosa Zahid Atiq Ur Rehman Radiology and Neurophysiology Department Shifa International Hospital Islamabad Pakistan

Background: Involvement of lumbar spinal nerve root, revealed as pain, numbness or weakness in the lower limbs. Typically caused by the compression of nerve at the spine level. Objective: The purpose of the study was to examine the patients with clinically presumed lumbar radiculopathy and find the correlation between their electrodiagnostic study and magnetic resonance imaging. Setting, duration and study type: Retrospective cross-sectional study of one year (January 2019 - February 2020) in Shifa International Hospital Islamabad. Methods: A total of 96 patients with clinically suspected lumbar radiculopathy were included. Chi-square test, international business machines (IBM) SPSS rendition 21.0 was applied on the clinical information, electrodiagnostic study and MRI were coordinated and affectability and particularity were judged. Selected patients were undergone both electrodiagnostic study and magnetic imaging resonance in the selected 1-year span. The study investigated correlation between both diagnostic tools in lumbar radiculopathy patients. Expected outcomes: Anatomical specificity in seen through magnetic resonance imaging while physiological through electrodiagnostic study, which may not correlate in the evaluation of lumbar radiculopathy.

关键词： Electrodiagnostic Radiculopathy Myotome Atrophy Spondylolisthesis Spinal Ligament Hypertrophy