Mehdi Hassan^1,*, Safdar Ali², Muhammad Sanaullah³, Khuram Shahzad⁴, Sadaf Mushtaq^5,6, Rashda Abbasi⁶, Zulqurnain Ali⁴, Hani Alquhayz⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2743-2760, 2022, DOI:10.32604/cmc.2022.020055 - 27 September 2021

Abstract Cancer is the second deadliest human disease worldwide with high mortality rate. Rehabilitation and treatment of this disease requires precise and automatic assessment of effective drug response and control system. Prediction of treated and untreated cancerous cell line is one of the most challenging problems for precise and targeted drug delivery and response. A novel approach is proposed for prediction of drug treated and untreated cancer cell line automatically by employing modified Deep neural networks. Human hepatocellular carcinoma (HepG2) cells are exposed to anticancer drug functionalized CFO@BTO nanoparticles developed by our lab. Prediction models are… More >

Mohamed Abdel-Basset¹, Abduallah Gamal¹, Rehab Mohamed¹, Mohamed Abouhawwash^2,3,*, Abdulwahab Almutairi⁴, Osama M. ELkomy¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4053-4073, 2022, DOI:10.32604/cmc.2022.020048 - 27 September 2021

Abstract There are several challenges that hospitals are facing according to the emergency department (ED). The main two issues are department capacity and lead time. However, the lack of consensus on performance criteria to evaluate ED increases the complication of this process. Thus, this study aims to evaluate the efficiency of the emergency department in 20 Egyptian hospitals (12 private and 8 general hospitals) based on 13 performance metrics. This research suggests an integrated evaluation model assess ED under a framework of plithogenic theory. The proposed framework addressed uncertainty and ambiguity in information with an efficient… More >

Wadhah Zeyad Tareq^*, Mehmet Fatih Amasyali

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2401-2414, 2022, DOI:10.32604/cmc.2022.020036 - 27 September 2021

Abstract The main idea of reinforcement learning is evaluating the chosen action depending on the current reward. According to this concept, many algorithms achieved proper performance on classic Atari 2600 games. The main challenge is when the reward is sparse or missing. Such environments are complex exploration environments like Montezuma’s Revenge, Pitfall, and Private Eye games. Approaches built to deal with such challenges were very demanding. This work introduced a different reward system that enables the simple classical algorithm to learn fast and achieve high performance in hard exploration environments. Moreover, we added some simple enhancements… More >

Myoung-hun Han^1,2, Bong-Soo Roh¹, Kyungwoo Kim¹, Dae-Hoon Kwon¹, Jae-Hyun Ham¹, KyungHyun Yoon², Sanghyun Seo^3,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2381-2399, 2022, DOI:10.32604/cmc.2022.020029 - 27 September 2021

Abstract An important requirement in a military domain is a highly reliable mobility management method, especially when components of the networks are moving in tactical network environments. To increase reliability, the mobility management technology of the tactical network should be able to reflect the characteristics of the tactical network, such as a limited environment, failure, and hierarchical unit structure. In this paper, we propose a proxy-based hierarchical distributed mobility management scheme, which is highly focused on tactical networks. Considering the characteristics of tactical networks, the proposed scheme is composed of the following: 1) a proxy-based method, More >

Tallat Jabeen^1,2, Ishrat Jabeen¹, Humaira Ashraf², Nz Jhanjhi^3,*, Mamoona Humayun⁴, Mehedi Masud⁵, Sultan Aljahdali⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2365-2380, 2022, DOI:10.32604/cmc.2022.020016 - 27 September 2021

Abstract COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through person-to-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors… More >

Kanika¹, Jimmy Singla¹, Ali Kashif Bashir², Yunyoung Nam^3,*, Najam UI Hasan⁴, Usman Tariq⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2861-2877, 2022, DOI:10.32604/cmc.2022.019990 - 27 September 2021

Abstract With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem.… More >

Muhammad Junaid^1,*, Adnan Sohail¹, Monagi H. Alkinani², Adeel Ahmed³, Mehmood Ahmed³, Faisal Rehman⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3985-4007, 2022, DOI:10.32604/cmc.2022.019962 - 27 September 2021

Abstract Metaheuristic approaches in cloud computing have shown significant results due to their multi-objective advantages. These approaches are now considering hybrid metaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several factors. The critical factors such as execution time, throughput time, response time, energy consumption, SLA violations, communication overhead, makespan, and migration time need careful attention while designing such dynamic algorithms. To improve such factors, an optimized multi-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization (CSO) with machine learning classifiers such… More >

Jibran Mir¹, Azhar Mahmood^2,*, Shaheen Khatoon³

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3491-3509, 2022, DOI:10.32604/cmc.2022.019952 - 27 September 2021

Abstract Aspect's extraction is a critical task in aspect-based sentiment analysis, including explicit and implicit aspects identification. While extensive research has identified explicit aspects, little effort has been put forward on implicit aspects extraction due to the complexity of the problem. Moreover, existing research on implicit aspect identification is widely carried out on product reviews targeting specific aspects while neglecting sentences’ dependency problems. Therefore, in this paper, a multi-level knowledge engineering approach for identifying implicit movie aspects is proposed. The proposed method first identifies explicit aspects using a variant of BiLSTM and CRF (Bidirectional Long Short… More >

S. Sathiya Devi¹, S. Vidivelli^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3049-3066, 2022, DOI:10.32604/cmc.2022.019917 - 27 September 2021

Abstract Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer. The present research work is useful in image processing for characterizing shape and gray-scale complexity. The proposed Modified Differential Box Counting (MDBC) extract Fractal features such as Fractal Dimension (FD), Lacunarity, and Succolarity for shape characterization. In traditional DBC method, the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels. The problem is overcome by the proposed MDBC method that uses box over counting and… More >

Walaa Gad^1,*, Anas Alokla¹, Waleed Nazih², Mustafa Aref¹, Abdel-badeeh Salem¹

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3117-3132, 2022, DOI:10.32604/cmc.2022.019884 - 27 September 2021

Abstract Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar language. Pseudo-code explains and describes the content of the code without using syntax or programming language technologies. However, writing Pseudo-code to each code instruction is laborious. Recently, neural machine translation is used to generate textual descriptions for the source code. In this paper, a novel deep learning-based transformer (DLBT) model is proposed for automatic Pseudo-code generation from the source code. The proposed model uses deep learning which is based on Neural Machine Translation (NMT)… More >