Sonia¹, Kapil Sharma^1,*, Monika Bajaj²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1087-1101, 2023, DOI:10.32604/iasc.2023.026134

Abstract Big Data and artificial intelligence are used to transform businesses. Social networking sites have given a new dimension to online data. Social media platforms help gather massive amounts of data to reach a wide variety of customers using influence maximization technique for innovative ideas, products and services. This paper aims to develop a deep learning method that can identify the influential users in a network. This method combines the various aspects of a user into a single graph. In a social network, the most influential user is the most trusted user. These significant users are used for viral marketing as… More >

J. Rajalakshmi^*, S. Siva Ranjani

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1049-1063, 2022, DOI:10.32604/iasc.2022.025127

Abstract Recently many algorithms for allocation of power approaches have been suggested to increase the Energy Efficiency (EE) and Spectral Efficiency (EE) in the Distributed Antenna System (DAS). In addition, the method of conservation developed for the allocation of power is challenging for the enhancement because of their high complication during estimation. With the intention of increasing the EE and SE, the optimization of allocation of power is done on the basis of capacity of the antenna. The main goal is for the optimization of the power allocation to improve the spectral and energy efficiency with the increased capacity of the… More >

S. Priyadarsini^1,*, Carlos Andrés Tavera Romero², M. Mrunalini³, Ganga Rama Koteswara Rao⁴, Sudhakar Sengan⁵

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1517-1530, 2022, DOI:10.32604/iasc.2022.024786

Abstract A classification system is used for Benign Tumors (BT) and Malignant Tumors (MT) in the abdominal liver. Computed Tomography (CT) images based on enhanced RGS is proposed. Diagnosis of liver diseases based on observation using liver CT images is essential for surgery and treatment planning. Identifying the progression of cancerous regions and Classification into Benign Tumors and Malignant Tumors are essential for treating liver diseases. The manual process is time-consuming and leads to intra and inter-observer variability. Hence, an automatic method based on enhanced region growing is proposed for the Classification of Liver Tumors (LT). To enhance the Liver Region… More >

Fatemeh Ahmadi Zeidabadi¹, Ali Dehghani², Mohammad Dehghani³, Zeinab Montazeri⁴, Štěpán Hubálovský⁵, Pavel Trojovský^3,*, Gaurav Dhiman⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4237-4256, 2022, DOI:10.32604/cmc.2022.023682

Abstract Finding the suitable solution to optimization problems is a fundamental challenge in various sciences. Optimization algorithms are one of the effective stochastic methods in solving optimization problems. In this paper, a new stochastic optimization algorithm called Search Step Adjustment Based Algorithm (SSABA) is presented to provide quasi-optimal solutions to various optimization problems. In the initial iterations of the algorithm, the step index is set to the highest value for a comprehensive search of the search space. Then, with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer to the global optimal, the… More >

Mohammed Abd-Elnaby^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5099-5116, 2022, DOI:10.32604/cmc.2022.022020

Abstract Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and analysis of the joint impact… More >

Xiaoli He¹, Yu Song^2,3,*, Yu Xue⁴, Muhammad Owais⁵, Weijian Yang¹, Xinwen Cheng¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 195-212, 2022, DOI:10.32604/cmc.2022.017105

Abstract Spectrum resources are the precious and limited natural resources. In order to improve the utilization of spectrum resources and maximize the network throughput, this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonal multiple access (CRN-NOMA). NOMA, as the key technology of the fifth-generation communication (5G), can effectively increase the capacity of 5G networks. The optimization problem proposed in this paper aims to maximize the number of secondary users (SUs) accessing the system and the total throughput in the CRN-NOMA. Under the constraints of total power, minimum rate, interference and SINR, CRN-NOMA throughput is maximized by… More >

Mohammed Abd-Elnaby^*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 521-537, 2021, DOI:10.32604/cmc.2021.018351

Abstract Non-orthogonal multiple access (NOMA) is one of the leading technologies for 5G communication. User pairing (UP) and power allocation (PA) are the key controlling mechanisms for the optimization of the performance of NOMA systems. This paper presents a novel UP and PA (UPPA) technique for capacity and fairness maximization in NOMA called (CFM-UPPA). The impact of the power allocation coefficient and the ratio between the channel gains of the paired users on the sum-rate capacity and the fairness in NOMA is firstly investigated. Then, based on this investigation, the PA and UP algorithms of the CFM-UPPA technique are proposed. The… More >

Senbo Chen^{1, 3, *}, Wenan Tan^{1, 2}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807

Abstract The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence. Up to now, most of the research has tended to focus on monolayer network rather than on multiplex networks. But in the real world, most individuals usually exist in multiplex networks. Multiplex networks are substantially different as compared with those of a monolayer network. In this paper, we integrate the multi-relationship of agents in multiplex networks by considering the existing and relevant… More >

Xiaoli He^{1, 2}, Hong Jiang^{1, *}, Yu Song^{1, 3}, Muhammad Owais⁴

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1273-1296, 2020, DOI:10.32604/cmc.2020.09908

Abstract This paper investigates the power control and routing problem in the communication process of an energy harvesting (EH) multi-hop cognitive radio network (CRN). The secondary user (SU) nodes (i.e., source node and relay nodes) harvest energy from the environment and use the energy exclusively for transmitting data. The SU nodes (i.e., relay nodes) on the path, store and forward the received data to the destination node. We consider a real world scenario where the EH-SU node has only local causal knowledge, i.e., at any time, each EH-SU node only has knowledge of its own EH process, channel state and currently… More >

Bing Hu¹, Feng Xiang², Fan Wu³, Jian Liu⁴, Zhe Sun¹, Zhixin Sun^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1323-1344, 2019, DOI:10.32604/cmc.2019.06414

Abstract To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover,… More >