Danyang Zheng, Jinchen Xv, Feng Yue, Qiming Du, Zhiheng Wang, Zheng Shan^*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048956

Abstract As cloud quantum computing gains broader acceptance, a growing quantity of researchers are directing their focus towards this domain. Nevertheless, the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity, which in turn hampers users from achieving optimal satisfaction. Therefore, cloud quantum computing service providers require a unified analysis and scheduling framework for their quantum resources and user jobs to meet the ever-growing usage demands. This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment. The framework addresses the issue of limited quantum computing resources in cloud environments and ensures… More >

Shuai Zhou¹, Dazhi Wang^1,*, Yongliang Ni², Keling Song², Yanming Li²

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048859

Abstract In the process of identifying parameters for a permanent magnet synchronous motor, the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration, resulting in low parameter accuracy. This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function. This approach addresses the topic of particle swarm optimization in parameter identification from two perspectives. Firstly, the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function, making the extreme point… More >

Husam Ahmad Al Hamad^*, Mohammad Shehab^*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048527

Abstract Recognizing handwritten characters remains a critical and formidable challenge within the realm of computer vision. Although considerable strides have been made in enhancing English handwritten character recognition through various techniques, deciphering Arabic handwritten characters is particularly intricate. This complexity arises from the diverse array of writing styles among individuals, coupled with the various shapes that a single character can take when positioned differently within document images, rendering the task more perplexing. In this study, a novel segmentation method for Arabic handwritten scripts is suggested. This work aims to locate the local minima of the vertical and diagonal word image densities… More >

Dmitry Gura^1,2, Bo Dong^3,*, Duaa Mehiar⁴, Nidal Al Said⁵

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048238

Abstract The motivation for this study is that the quality of deep fakes is constantly improving, which leads to the need to develop new methods for their detection. The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection, which is then used as input to the CNN. The customized Convolutional Neural Network method is the date augmented-based CNN model to generate ‘fake data’ or ‘fake images’. This study was carried out using Python and its libraries. We used 242 films from the dataset gathered by the Deep Fake Detection Challenge, of which 199… More >

Chunhua Wang^1,2, Wenqian Shang^1,2,*, Tong Yi^3,*, Haibin Zhu⁴

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048135

Abstract The advent of self-attention mechanisms within Transformer models has significantly propelled the advancement of deep learning algorithms, yielding outstanding achievements across diverse domains. Nonetheless, self-attention mechanisms falter when applied to datasets with intricate semantic content and extensive dependency structures. In response, this paper introduces a Diffusion Sampling and Label-Driven Co-attention Neural Network (DSLD), which adopts a diffusion sampling method to capture more comprehensive semantic information of the data. Additionally, the model leverages the joint correlation information of labels and data to introduce the computation of text representation, correcting semantic representation biases in the data, and increasing the accuracy of semantic… More >

Jun Li^1,2, Minqing Zhang^1,2,*, Ke Niu¹, Yingnan Zhang¹, Xiaoyuan Yang^1,2

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.048095

Abstract Among steganalysis techniques, detection against MV (motion vector) domain-based video steganography in the HEVC (High Efficiency Video Coding) standard remains a challenging issue. For the purpose of improving the detection performance, this paper proposes a steganalysis method that can perfectly detect MV-based steganography in HEVC. Firstly, we define the local optimality of MVP (Motion Vector Prediction) based on the technology of AMVP (Advanced Motion Vector Prediction). Secondly, we analyze that in HEVC video, message embedding either using MVP index or MVD (Motion Vector Difference) may destroy the above optimality of MVP. And then, we define the optimal rate of MVP… More >

Maher Alharby^*

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.050425

Abstract Cloud computing has emerged as a viable alternative to traditional computing infrastructures, offering various benefits. However, the adoption of cloud storage poses significant risks to data secrecy and integrity. This article presents an effective mechanism to preserve the secrecy and integrity of data stored on the public cloud by leveraging blockchain technology, smart contracts, and cryptographic primitives. The proposed approach utilizes a Solidity-based smart contract as an auditor for maintaining and verifying the integrity of outsourced data. To preserve data secrecy, symmetric encryption systems are employed to encrypt user data before outsourcing it. An extensive performance analysis is conducted to… More >

Farah Mohammad^1,*, Saad Al-Ahmadi², Jalal Al-Muhtadi^1,2

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042873

Abstract Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity users. It hinders the economic growth of utility companies, poses electrical risks, and impacts the high energy costs borne by consumers. The development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data, including information on client consumption, which may be used to identify electricity theft using machine learning and deep learning techniques. Moreover, there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and… More >

YUANYUAN LI¹, BITAO ZHANG¹, ZILONG CUI¹, PEIJIAN FAN¹, SHAOXIAN WANG^1,2,*

BIOCELL, Vol., , DOI:10.32604/biocell.2024.048820

Abstract Background: Depression is becoming increasingly prevalent around the world, imposing a substantial burden on individuals, families, as well as society. Quercetin is known to be highly effective in treating depression. However, additional research is needed to dissect the mechanisms of its anti-depressive effects. Methods: For this study, Sprague-Dawley (SD) rats were randomized into the control, model, quercetin, or fluoxetine group. The latter three groups were exposed to chronic unpredictable mild stress (CUMS) for 42 d. The first two groups received saline solution daily via oral gavage. Meanwhile, the quercetin group was orally administered a quercetin suspension (52.08 mg/kg) every day,… More >

Yang Cao^1,*, Jianshu Liu², Xuhui Meng¹

Frontiers in Heat and Mass Transfer, Vol., , DOI:10.32604/fhmt.2024.051208

Abstract Boiling heat transfer, as an efficient heat transfer approach, that can absorb a large amount of latent heat during the vaporization, is especially suitable for heat transfer occasions with high heat flux demands. Experimental studies show that the surface tension coefficient of pure water can be reduced sharply (up to 25%) when it is magnetized by a magnetic field applied externally. In this paper, magnetized water (MW) was used as the work fluid to conduct boiling heat transfer experiments, to explore the influence of magnetization on the boiling characteristics of pure water. The electromagnetic device was used to magnetize water,… More >