Open Access
ARTICLE
K. Karthikeyan*, P. Madhavan
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4183-4197, 2022, DOI:10.32604/cmc.2022.019802
Abstract With the rapid growth of Internet of Things (IoT) based models, and the lack amount of data makes cloud computing resources insufficient. Hence, edge computing-based techniques are becoming more popular in present research domains that makes data storage, and processing effective at the network edges. There are several advanced features like parallel processing and data perception are available in edge computing. Still, there are some challenges in providing privacy and data security over networks. To solve the security issues in Edge Computing, Hash-based Message Authentication Code (HMAC) algorithm is used to provide solutions for preserving data from various attacks that… More >
Open Access
ARTICLE
Sami Ullah Khan1, Babar Nazir1, Muhammad Hanif2,*, Akhtar Ali3, Sardar Alam1, Usman Habib4
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4199-4220, 2022, DOI:10.32604/cmc.2022.020852
（This article belongs to this Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)
Abstract The cloud service level agreement (SLA) manage the relationship between service providers and consumers in cloud computing. SLA is an integral and critical part of modern era IT vendors and communication contracts. Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers, the SLA emerges as a key aspect between the consumers and providers. Continuous monitoring of Quality of Service (QoS) attributes is required to implement SLAs because of the complex nature of cloud communication. Many other factors, such as user reliability, satisfaction, and penalty on violations are also taken into account. Currently, there… More >
Open Access
ARTICLE
José Escorcia-Gutierrez1,*, Romany F. Mansour2, Kelvin Beleño3, Javier Jiménez-Cabas4, Meglys Pérez1, Natasha Madera1, Kevin Velasquez1
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4221-4235, 2022, DOI:10.32604/cmc.2022.022322
Abstract Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic process. At the same time, breast cancer becomes the deadliest disease among women and can be detected by the use of different imaging techniques. Digital mammograms can be used for the earlier identification and diagnostic of breast cancer to minimize the death rate. But the proper identification of breast cancer has mainly relied on the mammography findings and results to increased false positives. For resolving the issues of false positives of breast cancer diagnosis, this paper presents an automated deep learning based breast cancer… More >
Open Access
ARTICLE
Fatemeh Ahmadi Zeidabadi1, Ali Dehghani2, Mohammad Dehghani3, Zeinab Montazeri4, Štěpán Hubálovský5, Pavel Trojovský3,*, Gaurav Dhiman6
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4237-4256, 2022, DOI:10.32604/cmc.2022.023682
（This article belongs to this Special Issue: AI-Aided Innovative Cryptographic Techniques for Futuristic Secure Computing Systems)
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 >
Open Access
ARTICLE
Sukanta Ghosh1, Amar Singh1, Kavita2,*, N. Z. Jhanjhi3, Mehedi Masud4, Sultan Aljahdali4
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4257-4274, 2022, DOI:10.32604/cmc.2022.023414
Abstract Automatic plant classification through plant leaf is a classical problem in Computer Vision. Plants classification is challenging due to the introduction of new species with a similar pattern and look-a-like. Many efforts are made to automate plant classification using plant leaf, plant flower, bark, or stem. After much effort, it has been proven that leaf is the most reliable source for plant classification. But it is challenging to identify a plant with the help of leaf structure because plant leaf shows similarity in morphological variations, like sizes, textures, shapes, and venation. Therefore, it is required to normalize all plant leaves… More >
Open Access
ARTICLE
Waleed Rafique1, Ayesha Khan2, Ahmad Almogren3, Jehangir Arshad1, Adnan Yousaf4, Mujtaba Hussain Jaffery1, Ateeq Ur Rehman5, Muhammad Shafiq6,*
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4275-4293, 2022, DOI:10.32604/cmc.2022.023588
Abstract An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active… More >
Open Access
ARTICLE
Broderick Crawford1,*, Ricardo Soto1, Hanns de la Fuente Mella1, Claudio Elortegui1, Wenceslao Palma1, Claudio Torres-Rojas1, Claudia Vasconcellos-Gaete2, Marcelo Becerra1, Javier Peña1, Sanjay Misra3
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068
（This article belongs to this Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which usually has much better sensory… More >
Open Access
ARTICLE
Turki M. Alanazi, Ahmed Ben Atitallah*
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4319-4335, 2022, DOI:10.32604/cmc.2022.022988
Abstract As the newest standard, the High Efficiency Video Coding (HEVC) is specially designed to minimize the bitrate for video data transfer and to support High Definition (HD) and ULTRA HD video resolutions at the cost of increasing computational complexity relative to earlier standards like the H.264. Therefore, real-time video decoding with HEVC decoder becomes a challenging task. However, the Dequantization and Inverse Transform (DE/IT) are one of the computationally intensive modules in the HEVC decoder which are used to reconstruct the residual block. Thus, in this paper, a unified hardware architecture is proposed to implement the HEVC DE/IT module for… More >
Open Access
ARTICLE
Muhammad Luqman Mohd-Shafie1,*, Wan Mohd Nasir Wan Kadir1, Muhammad Khatibsyarbini1, Mohd Adham Isa1, Israr Ghani1, Husni Ruslai2
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4337-4354, 2022, DOI:10.32604/cmc.2022.023803
Abstract Testing is an integral part of software development. Current fast-paced system developments have rendered traditional testing techniques obsolete. Therefore, automated testing techniques are needed to adapt to such system developments speed. Model-based testing (MBT) is a technique that uses system models to generate and execute test cases automatically. It was identified that the test data generation (TDG) in many existing model-based test case generation (MB-TCG) approaches were still manual. An automatic and effective TDG can further reduce testing cost while detecting more faults. This study proposes an automated TDG approach in MB-TCG using the extended finite state machine model (EFSM).… More >
Open Access
ARTICLE
Aurora Gonzalez-Vidal1, Fernando Terroso-Sáenz2,*, Antonio Skarmeta1
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4355-4375, 2022, DOI:10.32604/cmc.2022.021492
Abstract Nowadays, the anticipation of parking-space demand is an instrumental service in order to reduce traffic congestion levels in urban spaces. The purpose of our work is to study, design and develop a parking-availability predictor that extracts the knowledge from human mobility data, based on the anonymized human displacements of an urban area, and also from weather conditions. Most of the existing solutions for this prediction take as contextual data the current road-traffic state defined at very high temporal or spatial resolution. However, access to this type of fine-grained location data is usually quite limited due to several economic or privacy-related… More >
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