Nadia Mustaqim Ansari^1,*, Rashid Hussain², Sheeraz Arif³, Syed Sajjad Hussain⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1861-1875, 2022, DOI:10.32604/cmc.2022.023516

Abstract The security of Internet of Things (IoT) is a challenging task for researchers due to plethora of IoT networks. Side Channel Attacks (SCA) are one of the major concerns. The prime objective of SCA is to acquire the information by observing the power consumption, electromagnetic (EM) field, timing analysis, and acoustics of the device. Later, the attackers perform statistical functions to recover the key. Advanced Encryption Standard (AES) algorithm has proved to be a good security solution for constrained IoT devices. This paper implements a simulation model which is used to modify the AES algorithm using logical masking properties. This… More >

C. Pabitha^*, B. Vanathi

Computer Systems Science and Engineering, Vol.42, No.3, pp. 949-961, 2022, DOI:10.32604/csse.2022.021086

Abstract Skin is the largest body organ that is prone to the environment most specifically. Therefore the skin is susceptible to many damages, including burn damage. Burns can endanger life and are linked to high morbidity and mortality rates. Effective diagnosis with the help of accurate burn zone and wound depth evaluation is important for clinical efficacy. The following characteristics are associated with the skin burn wound, such as healing, infection, painand stress and keloid formation. Tissue regeneration also takes a significant amount of time for formation while considering skin healing after a burn injury. Deep neural networks can automatically assist… More >

Guangjun Sun, Chuting Wang, Lu Wang^*

Journal of Renewable Materials, Vol.10, No.6, pp. 1537-1553, 2022, DOI:10.32604/jrm.2022.018598

Abstract To investigate the temperature field and residual bearing capacity of the sandwich wall panels with GFRP skins and a wood-web core under a fire, three sandwich walls were tested. One of them was used for static load test and the other two for the one-side fire tests. Besides, temperature probe points were set on the sandwich walls to obtain the temperature distribution. Meanwhile, the model of the sandwich wall was established in the finite element software by the method of core material stiffness equivalent. The temperature distribution and performance reduction of materials were also considered. The residual bearing capacity of… More >

Saeed Iqbal^1,*, Adnan N. Qureshi¹, Ghulam Mustafa²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4915-4939, 2022, DOI:10.32604/cmc.2022.023178

Abstract Skin cancer (melanoma) is one of the most aggressive of the cancers and the prevalence has significantly increased due to increased exposure to ultraviolet radiation. Therefore, timely detection and management of the lesion is a critical consideration in order to improve lifestyle and reduce mortality. To this end, we have designed, implemented and analyzed a hybrid approach entailing convolutional neural networks (CNN) and local binary patterns (LBP). The experiments have been performed on publicly accessible datasets ISIC 2017, 2018 and 2019 (HAM10000) with data augmentation for in-distribution generalization. As a novel contribution, the CNN architecture is enhanced with an intelligible… More >

YUNLONG ZHANG^1,#, JINGWEI ZHANG^2,#, YU ZHU¹, BIN CAI^1,*

BIOCELL, Vol.46, No.5, pp. 1329-1338, 2022, DOI:10.32604/biocell.2022.015592

Abstract Diabetic patients often exhibit delayed or incomplete progress in the healing of acute wounds, owing to poor blood perfusion. Platelet-rich plasma (PRP) has attracted much attention as a means to improve wound healing, because it contains high growth factor concentrations. However, the burst-like release of PRP growth factors results in a short half-life of these therapeutic proteins, thus greatly limiting the therapeutic effect. In this study, we prepared PRP from human umbilical cord blood and developed an in situ photocrosslinkable PRP hydrogel glue (HNPRP) by adding a photoresponsive hyaluronic acid (HA-NB) into PRP. The HNPRP hydrogel allowed for controlled release… More >

Mustafa Kamal^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1239-1269, 2022, DOI:10.32604/cmes.2022.017532

Abstract In general, simple subsystems like series or parallel are integrated to produce a complex hybrid system. The reliability of a system is determined by the reliability of its constituent components. It is often extremely difficult or impossible to get specific information about the component that caused the system to fail. Unknown failure causes are instances in which the actual cause of system failure is unknown. On the other side, thanks to current advanced technology based on computers, automation, and simulation, products have become incredibly dependable and trustworthy, and as a result, obtaining failure data for testing such exceptionally reliable items… More >

Darshan Babu L. Arasu¹, Ahmad Sufril Azlan Mohamed^1,*, Nur Intan Raihana Ruhaiyem¹, Nagaletchimee Annamalai², Syaheerah Lebai Lutfi¹, Mustafa M. Al Qudah¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 633-652, 2022, DOI:10.32604/cmes.2021.016985

Abstract Stress is a normal reaction of the human organism which triggered in situations that require a certain level of activation. This reaction has both positive and negative effects on everyone’s life. Therefore, stress management is of vital importance in maintaining the psychological balance of a person. Thermal-based imaging technique is becoming popular among researchers due to its non-contact conductive nature. Moreover, thermal-based imaging has shown promising results in detecting stress in a non-contact and non-invasive manner. Compared to other non-contact stress detection methods such as pupil dilation, keystroke behavior, social media interaction and voice modulation, thermal-based imaging provides better features… More >

Vatsala Anand¹, Sheifali Gupta¹, Deepika Koundal^2,*, Shubham Mahajan³, Amit Kant Pandit³, Atef Zaguia⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3145-3160, 2022, DOI:10.32604/cmc.2022.022788

Abstract Biomedical image analysis has been exploited considerably by recent technology involvements, carrying about a pattern shift towards ‘automation’ and ‘error free diagnosis’ classification methods with markedly improved accurate diagnosis productivity and cost effectiveness. This paper proposes an automated deep learning model to diagnose skin disease at an early stage by using Dermoscopy images. The proposed model has four convolutional layers, two maxpool layers, one fully connected layer and three dense layers. All the convolutional layers are using the kernel size of 3 * 3 whereas the maxpool layer is using the kernel size of 2 * 2. The dermoscopy images… More >

Amina Bibi¹, Muhamamd Attique Khan¹, Muhammad Younus Javed¹, Usman Tariq², Byeong-Gwon Kang³, Yunyoung Nam^3,*, Reham R. Mostafa⁴, Rasha H. Sakr⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2477-2495, 2022, DOI:10.32604/cmc.2022.018917

Abstract Background: In medical image analysis, the diagnosis of skin lesions remains a challenging task. Skin lesion is a common type of skin cancer that exists worldwide. Dermoscopy is one of the latest technologies used for the diagnosis of skin cancer. Challenges: Many computerized methods have been introduced in the literature to classify skin cancers. However, challenges remain such as imbalanced datasets, low contrast lesions, and the extraction of irrelevant or redundant features. Proposed Work: In this study, a new technique is proposed based on the conventional and deep learning framework. The proposed framework consists of two major tasks: lesion segmentation… More >

Juan Pablo Villa-Pulgarin¹, Anderson Alberto Ruales-Torres^1,2, Daniel Arias-Garzón¹, Mario Alejandro Bravo-Ortiz¹, Harold Brayan Arteaga-Arteaga¹, Alejandro Mora-Rubio¹, Jesus Alejandro Alzate-Grisales¹, Esteban Mercado-Ruiz¹, M. Hassaballah³, Simon Orozco-Arias^4,5, Oscar Cardona-Morales¹, Reinel Tabares-Soto^1,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2131-2148, 2022, DOI:10.32604/cmc.2022.019529

Abstract Skin cancer is one of the most severe diseases, and medical imaging is among the main tools for cancer diagnosis. The images provide information on the evolutionary stage, size, and location of tumor lesions. This paper focuses on the classification of skin lesion images considering a framework of four experiments to analyze the classification performance of Convolutional Neural Networks (CNNs) in distinguishing different skin lesions. The CNNs are based on transfer learning, taking advantage of ImageNet weights. Accordingly, in each experiment, different workflow stages are tested, including data augmentation and fine-tuning optimization. Three CNN models based on DenseNet-201, Inception-ResNet-V2, and… More >