Amal Al-Rasheed¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Abdullah Mohamed⁴, Anwer Mustafa Hilal^5,*, Abdelwahed Motwakel⁵, Abu Sarwar Zamani⁵, Mohamed I. Eldesouki⁶

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3275-3290, 2022, DOI:10.32604/cmc.2022.029823

Abstract The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various sources. The developments of artificial intelligence (AI) and machine learning (ML) models assist in the effectual design of medical data classification models. Therefore, this article concentrates on the development of optimal Stacked Long Short Term Memory Sequence-to-Sequence Autoencoder (OSAE-LSTM) model for biomedical data classification. The presented OSAE-LSTM model intends to classify the biomedical data for the existence of diseases. Primarily, the OSAE-LSTM model involves min-max normalization based pre-processing to scale the data into uniform format.… More >

Hassen Mestiri^1,2,3,*, Imen Barraj^1,4,5, Mohsen Machhout³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4051-4066, 2022, DOI:10.32604/cmc.2022.029794

Abstract Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure security. Due to significant resource constraints, these devices are limited in their capabilities. The increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection attacks. SystemC is a good choice for Electronic System Level (ESL) modeling since it enables models to run at a faster rate. To enable fault injection and detection inside a SystemC cryptographic model, however, the model’s source code must be updated. Without altering the source code, Aspect-Oriented Programming (AOP)… More >

Haikuo Peng¹, Yun Tan^1,*, Hao Tang², Ling Tan², Xuyu Xiang¹, Yongjun Wang², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2757-2771, 2022, DOI:10.32604/cmc.2022.029727

Abstract Aortic dissection (AD) is one of the most serious diseases with high mortality, and its diagnosis mainly depends on computed tomography (CT) results. Most existing automatic diagnosis methods of AD are only suitable for AD recognition, which usually require preselection of CT images and cannot be further classified to different types. In this work, we constructed a dataset of 105 cases with a total of 49021 slices, including 31043 slices expert-level annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning. The proposed region of interest (RoI) extraction algorithm based on sequence information (RESI) can… More >

Trong Hieu Luu¹, Phan Nguyen Ky Phuc^2,*, Zhiqiu Yu³, Duy Dung Pham¹, Huu Trong Cao¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3251-3262, 2022, DOI:10.32604/cmc.2022.029663

Abstract In recent years, the COVID-19 pandemic has negatively impacted all aspects of social life. Due to ease in the infected method, i.e., through small liquid particles from the mouth or the nose when people cough, sneeze, speak, sing, or breathe, the virus can quickly spread and create severe problems for people’s health. According to some research as well as World Health Organization (WHO) recommendation, one of the most economical and effective methods to prevent the spread of the pandemic is to ask people to wear the face mask in the public space. A face mask will help prevent the droplet… More >

Jianhua Luo, Yuhang Zhou^*, Hua Li, Xi Chen, Xigong Xia

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2473-2484, 2022, DOI:10.32604/cmc.2022.029640

Abstract Combined with equipment activities such as combat readiness, training, exercises and management, it is proposed that the design of equipment in-service assessment subjects should follow the principles of combination, stage and operability. Focusing on the design of equipment in-service assessment subjects, a design method for in-service assessment subjects based on the combination of trial and training mode is proposed. Based on the actual use of high-equipment use management and training and the established indicator system, the army’s bottom-level equipment activity subjects and bottom-level assessments are combined. The indicators are mapped and analyzed. Through multiple rounds of iterations, the mapping relationship… More >

Tao Li¹, Di Wu¹, Rui Han², Jinyue Xia³, Yongjun Ren^4,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3721-3739, 2022, DOI:10.32604/cmc.2022.029619

Abstract As an important maritime hub, Bohai Sea Bay provides great convenience for shipping and suffers from sea ice disasters of different severity every winter, which greatly affects the socio-economic and development of the region. Therefore, this paper uses FY-4A (a weather satellite) data to study sea ice in the Bohai Sea. After processing the data for land removal and cloud detection, it combines multi-channel threshold method and adaptive threshold algorithm to realize the recognition of Bohai Sea ice under clear sky conditions. The random forests classification algorithm is introduced in sea ice identification, which can achieve a certain effect of… More >

Atif Ikram^1,2,*, Masita Abdul Jalil¹, Amir Bin Ngah¹, Nadeem Iqbal², Nazri Kama⁴, Azri Azmi⁴, Ahmad Salman Khan³, Yasir Mahmood^3,4, Assad Alzayed⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3827-3845, 2022, DOI:10.32604/cmc.2022.029609

Abstract Properly created and securely communicated, non-disclosure agreement (NDA) can resolve most of the common disputes related to outsourcing of offshore software maintenance (OSMO). Occasionally, these NDAs are in the form of images. Since the work is done offshore, these agreements or images must be shared through the Internet or stored over the cloud. The breach of privacy, on the other hand, is a potential threat for the image owners as both the Internet and cloud servers are not void of danger. This article proposes a novel algorithm for securing the NDAs in the form of images. As an agreement is… More >

Manar Ahmed Hamza^1,*, Hadil Shaiba², Radwa Marzouk³, Ahmad Alhindi⁴, Mashael M. Asiri⁵, Ishfaq Yaseen¹, Abdelwahed Motwakel¹, Mohammed Rizwanullah¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3235-3250, 2022, DOI:10.32604/cmc.2022.029604

Abstract Environmental sustainability is the rate of renewable resource harvesting, pollution control, and non-renewable resource exhaustion. Air pollution is a significant issue confronted by the environment particularly by highly populated countries like India. Due to increased population, the number of vehicles also continues to increase. Each vehicle has its individual emission rate; however, the issue arises when the emission rate crosses the standard value and the quality of the air gets degraded. Owing to the technological advances in machine learning (ML), it is possible to develop prediction approaches to monitor and control pollution using real time data. With the development of… More >

Jeonghwan Im¹, Hyuk-Yoon Kwon^2,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3333-3350, 2022, DOI:10.32604/cmc.2022.029566

Abstract The key-value store can provide flexibility of data types because it does not need to specify the data types to be stored in advance and can store any types of data as the value of the key-value pair. Various types of studies have been conducted to improve the performance of the key-value store while maintaining its flexibility. However, the research efforts storing the large-scale values such as multimedia data files (e.g., images or videos) in the key-value store were limited. In this study, we propose a new key-value store, WR-Store++ aiming to store the large-scale values stably. Specifically, it provides… More >

Bakhytzhan Kulambayev^1,*, Gulbakhram Beissenova^2,3, Nazbek Katayev⁴, Bayan Abduraimova⁵, Lyazzat Zhaidakbayeva², Alua Sarbassova⁶, Oxana Akhmetova⁷, Sapar Issayev⁴, Laura Suleimenova⁸, Syrym Kasenov⁶, Kunsulu Shadinova⁹, Abay Shyrakbaev¹⁰

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3403-3418, 2022, DOI:10.32604/cmc.2022.029544

Abstract Timely detection and elimination of damage in areas with excessive vehicle loading can reduce the risk of road accidents. Currently, various methods of photo and video surveillance are used to monitor the condition of the road surface. The manual approach to evaluation and analysis of the received data can take a protracted period of time. Thus, it is necessary to improve the procedures for inspection and assessment of the condition of control objects with the help of computer vision and deep learning techniques. In this paper, we propose a model based on Mask Region-based Convolutional Neural Network (Mask R-CNN) architecture… More >