Sureka Sivavelu, Venkatesh Palanisamy^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3469-3487, 2024, DOI:10.32604/cmc.2024.047407

Abstract The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric… More >

Sherly Alphonse^1,*, S. Abinaya¹, Sourabh Paul²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3449-3467, 2024, DOI:10.32604/cmc.2024.046403

Abstract The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial antennas. The radiation cost and quality factor of the antenna are influenced by the size of the antenna. Metamaterial antennas allow for the circumvention of the bandwidth restriction for small antennas. Antenna parameters have recently been predicted using machine learning algorithms in existing literature. Machine learning can take the place of the manual process of experimenting to find the ideal simulated antenna parameters. The accuracy of the prediction will be primarily dependent on the model that is used. In this paper, a novel method… More >

Arshiya S. Ansari^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2865-2892, 2024, DOI:10.32604/cmc.2024.045908

Abstract Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look. Whereas vehicular ad hoc networks (VANETs), which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services, as they are an essential component of modern smart transportation systems. VANETs steganography has been suggested by many authors for secure, reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection. This paper aims to determine whether using steganography is possible to improve data security… More >

Sepehr Soltani¹, Ehsan Ghafourian², Reza Salehi³, Diego Martín^3,*, Milad Vahidi⁴

Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 93-108, 2024, DOI:10.32604/iasc.2024.042693

Abstract For many years, researchers have explored power allocation (PA) algorithms driven by models in wireless networks where multiple-user communications with interference are present. Nowadays, data-driven machine learning methods have become quite popular in analyzing wireless communication systems, which among them deep reinforcement learning (DRL) has a significant role in solving optimization issues under certain constraints. To this purpose, in this paper, we investigate the PA problem in a -user multiple access channels (MAC), where transmitters (e.g., mobile users) aim to send an independent message to a common receiver (e.g., base station) through wireless channels. To this end, we first train… More >

Karrar A. Hammoodi^1,*, Hayder A. Dhahad², Wissam H. Alawee³, Z. M. Omara⁴

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 217-262, 2024, DOI:10.32604/fhmt.2024.047329

Abstract In the face of an escalating global water crisis, countries worldwide grapple with the crippling effects of scarcity, jeopardizing economic progress and hindering societal advancement. Solar energy emerges as a beacon of hope, offering a sustainable and environmentally friendly solution to desalination. Solar distillation technology, harnessing the power of the sun, transforms seawater into freshwater, expanding the availability of this precious resource. Optimizing solar still performance under specific climatic conditions and evaluating different configurations is crucial for practical implementation and widespread adoption of solar energy. In this study, we conducted theoretical investigations on three distinct solar still configurations to evaluate… More > Graphic Abstract

Roba Tarek AbdelFatah^*, Irene S. Fahim, Mohamed Mahran Kasem

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 317-339, 2024, DOI:10.32604/fhmt.2023.044706

Abstract Parabolic trough solar collectors (PTCs) are among the most cost-efficient solar thermal technologies. They have several applications, such as feed heaters, boilers, steam generators, and electricity generators. A PTC is a concentrated solar power system that uses parabolic reflectors to focus sunlight onto a tube filled with heat-transfer fluid. PTCs performance can be investigated using optical and thermal mathematical models. These models calculate the amount of energy entering the receiver, the amount of usable collected energy, and the amount of heat loss due to convection and radiation. There are several methods and configurations that have been developed so far; however,… More > Graphic Abstract

S. H. Elhag^*

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 377-395, 2024, DOI:10.32604/fhmt.2023.044428

Abstract A review of the literature revealed that nanofluids are more effective in transferring heat than conventional fluids. Since there are significant gaps in the illumination of existing methods for enhancing heat transmission in nanomaterials, a thorough investigation of the previously outlined models is essential. The goal of the ongoing study is to determine whether the microscopic gold particles that are involved in mass and heat transmission drift in freely. The current study examines heat and mass transfer on 3D MHD Darcy–Forchheimer flow of Casson nanofluid-induced bio-convection past a stretched sheet. The inclusion of the nanoparticles is a result of their… More >

Je-Chin Han^*, Akhilesh P. Rallabandi

Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-21, 2010, DOI:10.5098/hmt.v1.1.3001

Abstract Film cooling is widely used to protect modern gas turbine blades and vanes from the ever increasing inlet temperatures. Film cooling involves a very complex turbulent flow-field, the characterization of which is necessary for reliable and economical design. Several experimental studies have focused on gas turbine blade, vane and end-wall film cooling over the past few decades. Measurements of heat transfer coefficients, film cooling effectiveness values and heat flux ratios using several different experimental methods have been reported. The emphasis of this current review is on the Pressure Sensitive Paint (PSP) mass transfer analogy to determine the film cooling effectiveness.… More >

Nasser Alshammari¹, Shumaila Shahzadi², Saad Awadh Alanazi^1,*, Shahid Naseem³, Muhammad Anwar³, Madallah Alruwaili⁴, Muhammad Rizwan Abid⁵, Omar Alruwaili⁴, Ahmed Alsayat¹, Fahad Ahmad^6,7

Computer Systems Science and Engineering, Vol.48, No.2, pp. 363-394, 2024, DOI:10.32604/csse.2023.040721

Abstract Software Defined Network (SDN) and Network Function Virtualization (NFV) technology promote several benefits to network operators, including reduced maintenance costs, increased network operational performance, simplified network lifecycle, and policies management. Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration (NFV MANO), and malicious attacks in different scenarios disrupt the NFV Orchestrator (NFVO) and Virtualized Infrastructure Manager (VIM) lifecycle management related to network services or individual Virtualized Network Function (VNF). This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order… More >

Ali Hamid Farea^1,*, Omar H. Alhazmi¹, Kerem Kucuk²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work. AI2AI employs AI techniques to… More >