Jargalsaikhan Narantuya^1,*, Jun-Sik Shin², Sun Park², JongWon Kim²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4375-4395, 2022, DOI:10.32604/cmc.2022.023318

Abstract As the complexity of deep learning (DL) networks and training data grows enormously, methods that scale with computation are becoming the future of artificial intelligence (AI) development. In this regard, the interplay between machine learning (ML) and high-performance computing (HPC) is an innovative paradigm to speed up the efficiency of AI research and development. However, building and operating an HPC/AI converged system require broad knowledge to leverage the latest computing, networking, and storage technologies. Moreover, an HPC-based AI computing environment needs an appropriate resource allocation and monitoring strategy to efficiently utilize the system resources. In this regard, we introduce a… More >

Bobbinpreet¹, Sultan Aljahdali^2,*, Tripti Sharma¹, Bhawna Goyal¹, Ayush Dogra³, Shubham Mahajan⁴, Amit Kant Pandit⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4771-4787, 2022, DOI:10.32604/cmc.2022.023150

Abstract In recent times, the images and videos have emerged as one of the most important information source depicting the real time scenarios. Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane. The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition. One of the application fields pertains to detection of diseases occurring in the plants, which are destroying the widespread fields. Traditionally the disease detection process was done by a… More >

Muhammad Faheem Saleem¹, Syed Muhammad Adnan Shah¹, Tahira Nazir¹, Awais Mehmood¹, Marriam Nawaz¹, Muhammad Attique Khan², Seifedine Kadry³, Arnab Majumdar⁴, Orawit Thinnukool^5,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5985-5997, 2022, DOI:10.32604/cmc.2022.023101

Abstract Signet Ring Cell (SRC) Carcinoma is among the dangerous types of cancers, and has a major contribution towards the death ratio caused by cancerous diseases. Detection and diagnosis of SRC carcinoma at earlier stages is a challenging, laborious, and costly task. Automatic detection of SRCs in a patient's body through medical imaging by incorporating computing technologies is a hot topic of research. In the presented framework, we propose a novel approach that performs the identification and segmentation of SRCs in the histological images by using a deep learning (DL) technique named Mask Region-based Convolutional Neural Network (Mask-RCNN). In the first… More >

A. Younes^1,*, M. Kh. Elnahary¹, Monagi H. Alkinani², Hamdy H. El-Sayed¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4339-4356, 2022, DOI:10.32604/cmc.2022.022824

Abstract Cloud computing is currently dominated within the space of high-performance distributed computing and it provides resource polling and on-demand services through the web. So, task scheduling problem becomes a very important analysis space within the field of a cloud computing environment as a result of user's services demand modification dynamically. The main purpose of task scheduling is to assign tasks to available processors to produce minimum schedule length without violating precedence restrictions. In heterogeneous multiprocessor systems, task assignments and schedules have a significant impact on system operation. Within the heuristic-based task scheduling algorithm, the different processes will lead to a… More >

Ngo Quang Trung, Nguyen Van Thanh^*, Nguyen Viet Tinh, Syed Tam Husain

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4557-4570, 2022, DOI:10.32604/cmc.2022.022417

Abstract The finance supply chain has always been a different supply chain compared to product supply chain being a service supply chain. Open Banking (OB) is one of the most important milestones since the beginning of financial technology innovation and service supply chain. As these are activities provided by traditional banks, non-bank financial institutions also provide financial service with access to consumer banking, transactional and other financial data to develop financial applications and services tailored to their customers. The development of financial technology, “Open banking”, promotes financial services to begin this transformation. However, evaluating and selecting open banking business partners from… More >

Hanan S. Gafel^*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6141-6153, 2022, DOI:10.32604/cmc.2022.017378

Abstract Magnetic field and the fractional Maxwell fluids’ impacts on peristaltic flows within a circular cylinder tube with heat transfer was evaluated while assuming that they are preset with a low-Reynolds number and a long wavelength. Utilizing, the fractional calculus method, the problem was solved analytically. It was deduced for temperature, axial velocity, tangential stress, and heat transfer coefficient. Many emerging parameters and their effects on the aspects of the flow were illustrated, and the outcomes were expressed via graphs. A special focus was dedicated to some criteria, such as the wave amplitude's effect, Hartman and Grashof numbers, radius and relaxation–retardation… More >

Yujiang Li^1,2, Chun Ding^1,2, Zhili Zhou^1,2,*

Journal of New Media, Vol.4, No.1, pp. 51-58, 2022, DOI:10.32604/jnm.2022.028775

Abstract With the development of new media technology, vehicle matching plays a further significant role in video surveillance systems. Recent methods explored the vehicle matching based on the feature extraction. Meanwhile, similarity metric learning also has achieved enormous progress in vehicle matching. But most of these methods are less effective in some realistic scenarios where vehicles usually be captured in different times. To address this cross-domain problem, we propose a cross-domain similarity metric learning method that utilizes the GAN to generate vehicle images with another domain and propose the two-channel Siamese network to learn a similarity metric from both domains (i.e.,… More >

Guwei Li¹, Zhou Li^1,*, Cong Zheng¹, Zhengyuan Li²

Journal of New Media, Vol.4, No.1, pp. 41-50, 2022, DOI:10.32604/jnm.2022.027883

Abstract Aiming at the safety problems of toxic, flammable and explosive chemicals used in middle school chemical experiments, such as human poisoning, skin corrosion, fire or explosion caused by improper experimental operation, a virtual simulation method of chemical experiments based on unity is proposed. Due to the need to analyze and compare the data in chemical experiments, summarize the experimental characteristics and data relevance. Therefore, based on the Apriori algorithm, this method deeply excavates the data obtained in the chemical experiment, uses Maya to model the experimental environment, uses unity to design the interactive functions in the experimental process, and uses… More >

Zhe Wang¹, Liguo Zhang^1,2,*, Tong Shuai³, Shuo Liang³, Sizhao Li^1,4

Journal of New Media, Vol.4, No.1, pp. 27-39, 2022, DOI:10.32604/jnm.2022.027826

Abstract Research shows that deep learning algorithms can effectively improve a single image's super-resolution quality. However, if the algorithm is solely focused on increasing network depth and the desired result is not achieved, difficulties in the training process are more likely to arise. Simultaneously, the function space that can be transferred from a low-resolution image to a high-resolution image is enormous, making finding a satisfactory solution difficult. In this paper, we propose a deep learning method for single image super-resolution. The MDRN network framework uses multi-scale residual blocks and dual learning to fully acquire features in low-resolution images. Finally, these features… More >

Hui Yu, Jinguang Wang^*

Journal of New Media, Vol.4, No.1, pp. 13-26, 2022, DOI:10.32604/jnm.2022.027312

Abstract With the speedy development of communication Internet and the widespread use of social multimedia, so many creators have published posts on social multimedia platforms that fake news detection has already been a challenging task. Although some works use deep learning methods to capture visual and textual information of posts, most existing methods cannot explicitly model the binary relations among image regions or text tokens to mine the global relation information in a modality deeply such as image or text. Moreover, they cannot fully exploit the supplementary cross-modal information, including image and text relations, to supplement and enrich each modality. In… More >