Haykel Marouani^1,2, Omar Al-mutiri^1,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 537-571, 2022, DOI:10.32604/cmc.2022.020098

Abstract The study of optimization methods for reliability–redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability–redundancy allocation problems. Results from a literature survey show the best… More >

Muhammad Shahid Bhatti^1,*, Azmat Ullah¹, Rohaya Latip², Abid Sohail¹, Anum Riaz¹, Rohail Hassan³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 125-141, 2022, DOI:10.32604/cmc.2022.020083

Abstract Text classification of low resource language is always a trivial and challenging problem. This paper discusses the process of Urdu news classification and Urdu documents similarity. Urdu is one of the most famous spoken languages in Asia. The implementation of computational methodologies for text classification has increased over time. However, Urdu language has not much experimented with research, it does not have readily available datasets, which turn out to be the primary reason behind limited research and applying the latest methodologies to the Urdu. To overcome these obstacles, a medium-sized dataset having six categories is collected from authentic Pakistani news… More >

P. N. Palanisamy^*, N. Malmurugan

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921

Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of… More >

Muhammad Ahmad^1,*, M. Arfan Jaffar¹, Fawad Nasim¹, Tehreem Masood¹, Sheeraz Akram²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 735-752, 2022, DOI:10.32604/cmc.2022.019691

Abstract

Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion. Particle Swarm Optimization (PSO) algorithm… More >

R. D. Pubudu L. Indrasiri¹, Ernesto Lee², Vaibhav Rupapara³, Furqan Rustam⁴, Imran Ashraf^5,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 489-515, 2022, DOI:10.32604/cmc.2022.019636

Abstract Malicious traffic detection over the internet is one of the challenging areas for researchers to protect network infrastructures from any malicious activity. Several shortcomings of a network system can be leveraged by an attacker to get unauthorized access through malicious traffic. Safeguard from such attacks requires an efficient automatic system that can detect malicious traffic timely and avoid system damage. Currently, many automated systems can detect malicious activity, however, the efficacy and accuracy need further improvement to detect malicious traffic from multi-domain systems. The present study focuses on the detection of malicious traffic with high accuracy using machine learning techniques.… More >

Seungwoon Lee¹, Woogeun Kil¹, Byeong-hee Roh^1,*, SJ Kim², Jin-suk Kang³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 51-69, 2022, DOI:10.32604/cmc.2022.019635

Abstract There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific… More >

Nadia H. Alsulami^1,*, Amani T. Jamal¹, Lamiaa A. Elrefaei²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 85-108, 2022, DOI:10.32604/cmc.2022.019450

Abstract Lip-reading technologies are rapidly progressing following the breakthrough of deep learning. It plays a vital role in its many applications, such as: human-machine communication practices or security applications. In this paper, we propose to develop an effective lip-reading recognition model for Arabic visual speech recognition by implementing deep learning algorithms. The Arabic visual datasets that have been collected contains 2400 records of Arabic digits and 960 records of Arabic phrases from 24 native speakers. The primary purpose is to provide a high-performance model in terms of enhancing the preprocessing phase. Firstly, we extract keyframes from our dataset. Secondly, we produce… More >

Sumaya Alkubaisi^1,*, Said Ghoul², Oguz Ata¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1249-1262, 2022, DOI:10.32604/cmc.2022.019434

Abstract Most large-scale systems including self-adaptive systems utilize feature models (FMs) to represent their complex architectures and benefit from the reuse of commonalities and variability information. Self-adaptive systems (SASs) are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite contexts. However, reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and resources. The process of configuration reuse can be a better alternative to some contexts to reduce computational time, effort and error-prone. Nevertheless, systems’ complexity can be reduced while the development process of systems by reusing elements or components. FMs… More >

Ruchun Jia^1,*, Yang Xin², Bo Liu³, Qin Qin⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1221-1232, 2022, DOI:10.32604/cmc.2022.019318

Abstract Data is the last defense line of security, in order to prevent data loss, no matter where the data is stored, copied or transmitted, it is necessary to accurately detect the data type, and further clarify the form and encryption structure of the data transmission process to ensure the accuracy of the data, so as to prevent data leakage, take the data characteristics as the core, use transparent encryption and decryption technology as the leading, and According to the data element characteristics such as identity authentication, authority management, outgoing management, file audit and external device management, the terminal data is… More >

A. F. Mohamed^1,2, J. Abu Alsoud¹, Mujahed Al-Dhaifallah^3,*, Hegazy Rezk^4,5, Mohamed K. Hassan^1,6

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 71-83, 2022, DOI:10.32604/cmc.2022.019257

Abstract In power plants, flue gases can cause severe corrosion damage in metallic parts such as flue ducts, heat exchangers, and boilers. Coating is an effective technique to prevent this damage. A robust fuzzy model of the surface roughness (R_a and R_z) of flue gas ducts coated by protective composite coating from epoxy and nanoparticles was constructed based on the experimental dataset. The proposed model consists of four nanoparticles (ZnO, ZrO₂, SiO₂, and NiO) with 2%, 4%, 6%, and 8%, respectively. Response surface methodology (RSM) was used to optimize the process parameters and identify the optimal conditions for minimum surface roughness… More >