Ali Raza^1,2,*, Dumitru Baleanu^3,4, Muhammad Rafiq⁵, Syed Zaheer Abbas⁶, Abubakar Siddique⁶, Umer Javed⁸, Mehvish Naz⁷, Arooj Fatima⁶, Tayyba Munawar⁶, Hira Batool⁶, Zaighum Nazir⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3621-3634, 2022, DOI:10.32604/cmc.2022.023286

Abstract Cancer is a common term for many diseases that can affect any part of the body. In 2020, ten million people will die due to cancer. A worldwide leading cause of death is cancer by the World Health Organization (WHO) report. Interaction of cancer cells, viral therapy, and immune response are identified in this model. Mathematical and computational modeling is an effective tool to predict the dynamics of cancer virotherapy. The cell population is categorized into three parts like uninfected cells (x), infected cells (y), virus-free cells (v), and immune cells (z). The modeling of cancer-like diseases is based on… More >

Prohim Tam¹, Sa Math¹, Ahyoung Lee², Seokhoon Kim^1,3,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3319-3335, 2022, DOI:10.32604/cmc.2022.023215

Abstract Federated learning (FL) activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging processes. However, in large-scale heterogeneous Internet of Things (IoT) cellular networks, massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled significantly. This paper introduces the system model of converging software-defined networking (SDN) and network functions virtualization (NFV) to enable device/resource abstractions and provide NFV-enabled edge FL (eFL) aggregation servers for advancing automation and controllability. Multi-agent deep Q-networks (MADQNs) target to enforce a self-learning softwarization, optimize resource allocation… More >

Wenzheng Yu¹, Jintao Cui², Yang Gao¹, Mingxuan Zhu¹, Li Shao³, Yanbo Shen^4,5,*, Xiaozhao Zhang⁶, Chen Guo⁷, Hanxiaoya Zhang⁸

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3635-3646, 2022, DOI:10.32604/cmc.2022.023195

Abstract Land desertification is a widely concerned ecological environment problem. Studying the evolution trend of desertification types is of great significance to prevent and control land desertification. In this study, we applied the decision tree classification method, to study the land area and temporal and spatial change law of different types of desertification in the North Bank of Qinghai Lake area from 1987 to 2014, based on the current land use situation and TM remote sensing image data of Haiyan County, Qinghai Province, The results show that the area of mild desertification land and moderate desertification land in the study area… More >

Lelisa Adeba Jilcha¹, Jin Kwak^2,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2883-2899, 2022, DOI:10.32604/cmc.2022.023167

Abstract In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement. Billions of dollars are lost annually because of this illegal act. The current most effective trend to tackle this problem is believed to be blocking those websites, particularly through affiliated government bodies. To do so, an effective detection mechanism is a necessary first step. Some researchers have used various approaches to analyze the possible common features of suspected piracy websites. For instance, most of these websites serve online advertisement, which is considered as their main source of revenue. In… More >

Sudan Prasad Uprety, Seung Ryul Jeong^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3937-3952, 2022, DOI:10.32604/cmc.2022.023127

Abstract Artificial intelligent based dialog systems are getting attention from both business and academic communities. The key parts for such intelligent chatbot systems are domain classification, intent detection, and named entity recognition. Various supervised, unsupervised, and hybrid approaches are used to detect each field. Such intelligent systems, also called natural language understanding systems analyze user requests in sequential order: domain classification, intent, and entity recognition based on the semantic rules of the classified domain. This sequential approach propagates the downstream error; i.e., if the domain classification model fails to classify the domain, intent and entity recognition fail. Furthermore, training such intelligent… More >

Prachi Agrawal¹, Khalid Alnowibet², Ali Wagdy Mohamed^3,4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

Walid Aydi^1,3,*, Fuad S. Alduais^2,4

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4033-4050, 2022, DOI:10.32604/cmc.2022.023119

Abstract The Weibull distribution is regarded as among the finest in the family of failure distributions. One of the most commonly used parameters of the Weibull distribution (WD) is the ordinary least squares (OLS) technique, which is useful in reliability and lifetime modeling. In this study, we propose an approach based on the ordinary least squares and the multilayer perceptron (MLP) neural network called the OLSMLP that is based on the resilience of the OLS method. The MLP solves the problem of heteroscedasticity that distorts the estimation of the parameters of the WD due to the presence of outliers, and eases… More >

Md Abdus Samad^1,2, Dong-You Choi^1,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3127-3143, 2022, DOI:10.32604/cmc.2022.023086

Abstract In present-day society, train tunnels are extensively used as a means of transportation. Therefore, to ensure safety, streamlined train operations, and uninterrupted internet access inside train tunnels, reliable wave propagation modeling is required. We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea. The measured path loss and the received signal strength were modeled with the Close-In (CI), Floating intercept (FI), CI model with a frequency-weighted path loss exponent (CIF), and alpha-beta-gamma (ABG) models, where the model parameters were determined using minimum mean square error (MMSE) methods. The measured and the… More >

Haeri Kim¹, Jong-Moon Chung^1,2,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3589-3605, 2022, DOI:10.32604/cmc.2022.023073

Abstract The development of Vehicular Ad-hoc Network (VANET) technology is helping Intelligent Transportation System (ITS) services to become a reality. Vehicles can use VANETs to communicate safety messages on the road (while driving) and can inform their location and share road condition information in real-time. However, intentional and unintentional (e.g., packet/frame collision) wireless signal jamming can occur, which will degrade the quality of communication over the channel, preventing the reception of safety messages, and thereby posing a safety hazard to the vehicle's passengers. In this paper, VANET jamming detection applying Support Vector Machine (SVM) machine learning technology is used to classify… More >

Mohd Anul Haq^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2363-2381, 2022, DOI:10.32604/cmc.2022.023059

Abstract Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing rainfall pattern is an essential aspect of assessing the impact of climate change on water resources planning and management. Climate change affected the entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being a climatic indicator. The water coming from Himalayan rivers is essential for 1.4 billion people living downstream. Earlier studies either modeled temperature or rainfall for the Himalayan area; however, the combined influence of both in a long-term analysis was not performed utilizing Deep… More >