Iftikhar Ahmad^1,*, Ambreen Shahnaz², Muhammad Asfand-e-Yar³, Wajeeha Khalil¹, Yasmin Bano¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 279-291, 2023, DOI:10.32604/cmc.2023.031344

Abstract The demand for cloud computing has increased manifold in the recent past. More specifically, on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs. The cloud service provider fulfills different user requirements using virtualization - where a single physical machine can host multiple Virtual Machines. Each virtual machine potentially represents a different user environment such as operating system, programming environment, and applications. However, these cloud services use a large amount of electrical energy and produce greenhouse gases. To reduce the electricity cost and greenhouse gases, energy efficient algorithms must be… More >

Zakir Hussain Ahmed^1,*, Naif Al-Otaibi¹, Abdullah Al-Tameem², Abdul Khader Jilani Saudagar²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1575-1605, 2023, DOI:10.32604/cmc.2023.031325

Abstract We study the capacitated vehicle routing problem (CVRP) which is a well-known NP-hard combinatorial optimization problem (COP). The aim of the problem is to serve different customers by a convoy of vehicles starting from a depot so that sum of the routing costs under their capacity constraints is minimized. Since the problem is very complicated, solving the problem using exact methods is almost impossible. So, one has to go for the heuristic/metaheuristic methods and genetic algorithm (GA) is broadly applied metaheuristic method to obtain near optimal solution to such COPs. So, this paper studies GAs to find solution to the… More >

Jasurbek Gulomov^1,*, Oussama Accouche², Rayimjon Aliev¹, Marc AZAB², Irodakhon Gulomova¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 575-590, 2023, DOI:10.32604/cmc.2023.031289

Abstract Today, it has become an important task to modify existing traditional silicon-based solar cell factory to produce high-efficiency silicon-based heterojunction solar cells, at a lower cost. Therefore, the aim of this paper is to analyze CH₃NH₃PbI₃ and ZnO materials as an emitter layer for p-type silicon wafer-based heterojunction solar cells. CH₃NH₃PbI₃ and ZnO can be synthesized using the cheap Sol-Gel method and can form n-type semiconductor. We propose to combine these two materials since CH₃NH₃PbI₃ is a great light absorber and ZnO has an optimal complex refractive index which can be used as antireflection material. The photoelectric parameters of n-CH₃NH₃PbI₃/p-Si,… More >

Jiangyuan Yao¹, Zheng Jiang², Kaiwen Zou², Shuhua Weng¹, Yaxin Li³, Deshun Li¹, Yahui Li^4,*, Xingcan Cao⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 293-311, 2023, DOI:10.32604/cmc.2023.031282

Abstract With the expansion of network services, large-scale networks have progressively become common. The network status changes rapidly in response to customer needs and configuration changes, so network configuration changes are also very frequent. However, no matter what changes, the network must ensure the correct conditions, such as isolating tenants from each other or guaranteeing essential services. Once changes occur, it is necessary to verify the after-changed network. Whereas, for the verification of large-scale network configuration changes, many current verifiers show poor efficiency. In order to solve the problem of multiple global verifications caused by frequent updates of local configurations in… More >

Gunnam Suryanarayana^1,*, D. Bhavana², P. E. S. N. Krishna Prasad³, M. M. K. Narasimha Reddy¹, Md Zia Ur Rahman²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1123-1137, 2023, DOI:10.32604/cmc.2023.031227

Abstract Single image super resolution (SISR) techniques produce images of high resolution (HR) as output from input images of low resolution (LR). Motivated by the effectiveness of deep learning methods, we provide a framework based on deep learning to achieve super resolution (SR) by utilizing deep singular-residual neural network (DSRNN) in training phase. Residuals are obtained from the difference between HR and LR images to generate LR-residual example pairs. Singular value decomposition (SVD) is applied to each LR-residual image pair to decompose into subbands of low and high frequency components. Later, DSRNN is trained on these subbands through input and output… More >

Hamayun Khan^1,*, Irfan Ud din², Arshad Ali³, Sami Alshmrany³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 965-981, 2023, DOI:10.32604/cmc.2023.031223

Abstract Increasing the life span and efficiency of Multiprocessor System on Chip (MPSoC) by reducing power and energy utilization has become a critical chip design challenge for multiprocessor systems. With the advancement of technology, the performance management of central processing unit (CPU) is changing. Power densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip size. When energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor (CMOS) circuits and reduces the speed by 10%–15% because excessive on-chip temperature shortens the chip’s life cycle. In this paper, we address the scheduling… More >

Mohammad Amaz Uddin¹, Mohammad Salah Uddin Chowdury¹, Mayeen Uddin Khandaker^2,*, Nissren Tamam³, Abdelmoneim Sulieman⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1709-1722, 2023, DOI:10.32604/cmc.2023.031177

Abstract Human speech indirectly represents the mental state or emotion of others. The use of Artificial Intelligence (AI)-based techniques may bring revolution in this modern era by recognizing emotion from speech. In this study, we introduced a robust method for emotion recognition from human speech using a well-performed preprocessing technique together with the deep learning-based mixed model consisting of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). About 2800 audio files were extracted from the Toronto emotional speech set (TESS) database for this study. A high pass and Savitzky Golay Filter have been used to obtain noise-free as well as… More >

Shehab Khan Noor¹, Arif Mawardi Ismail¹, Mohd Najib Mohd Yasin^1,*, Mohamed Nasrun Osman¹, Nurulazlina Ramli², Ali H. Rambe³, J. Iqbal^4,5

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2239-2259, 2023, DOI:10.32604/cmc.2023.031170

Abstract This article presents the generation of Orbital Angular Momentum (OAM) vortex waves with mode 1 using Uniform Circular Array (UCA) antenna. Two different designs, namely, UCA-1 (4-element array antenna) and UCA-2 (8-element array antenna), were designed and fabricated using FR-4 substrate to generate OAM mode 1 at 3.5 GHz (5G mid-band). The proposed antenna arrays comprised rectangular microstrip patch elements with inset fed technique. The elements were excited by a carefully designed feeding phase shift network to provide similar output energy at output ports with desired phase shift value. The generated OAM waves were confirmed by measuring the null in… More >

Mubarak Almutairi^*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1959-1983, 2023, DOI:10.32604/cmc.2023.031155

Abstract The development and use of Internet of Things (IoT) devices have grown significantly in recent years. Advanced IoT device characteristics are mainly to blame for the wide range of applications that may now be achieved with IoT devices. Corporations have begun to embrace the IoT concept. Identifying true and suitable devices, security faults that might be used for bad reasons, and administration of such devices are only a few of the issues that IoT, a new concept in technological progress, provides. In some ways, IoT device traffic differs from regular device traffic. Devices with particular features can be classified into… More >

Kun Ding¹, Lu Xu², Ming Liu¹, Xiaoxiong Zhang¹, Liu Liu¹, Daojian Zeng^2,*, Yuting Liu^1,3, Chen Jin⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 641-654, 2023, DOI:10.32604/cmc.2023.031052

Abstract Event detection (ED) is aimed at detecting event occurrences and categorizing them. This task has been previously solved via recognition and classification of event triggers (ETs), which are defined as the phrase or word most clearly expressing event occurrence. Thus, current approaches require both annotated triggers as well as event types in training data. Nevertheless, triggers are non-essential in ED, and it is time-wasting for annotators to identify the “most clearly” word from a sentence, particularly in longer sentences. To decrease manual effort, we evaluate event detection without triggers. We propose a novel framework that combines Type-aware Attention and Graph… More >