Hui Xu, Yalin Hu^*, Weidong Cao, Longjie Han

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.039227

Abstract The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex. Traditional port-based or protocol-based network traffic identification methods are no longer suitable for today’s complex and changing networks. Recently, machine learning has been widely applied to network traffic recognition. Still, high-dimensional features and redundant data in network traffic can lead to slow convergence problems and low identification accuracy of network traffic recognition algorithms. Taking advantage of the faster optimization-seeking capability of the jumping spider optimization algorithm (JSOA), this paper proposes a jumping spider optimization algorithm that incorporates the harris hawk optimization (HHO) and… More >

Kainat Nazir¹, Tahir Mustafa Madni¹, Uzair Iqbal Janjua¹, Umer Javed², Muhammad Attique Khan³, Usman Tariq⁴, Jae-Hyuk Cha^5,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2861-2877, 2023, DOI:10.32604/cmc.2023.039181

Abstract Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved ones. Diagnosing a brain tumor usually begins with magnetic resonance imaging (MRI). The manual brain tumor diagnosis from the MRO images always requires an expert radiologist. However, this process is time-consuming and costly. Therefore, a computerized technique is required for brain tumor detection in MRI images. Using the MRI, a novel mechanism of the three-dimensional (3D) Kronecker convolution feature pyramid (KCFP) is used to segment brain tumors, resolving the pixel loss and weak processing of multi-scale lesions. A single dilation rate was replaced… More >

Nerejda Shehu^1,*, Christian Meierhofer¹, Anja Hennemuth^2,3, Markus Hüllebrand^2,3, Pavlo Yevtushenko³, Peter Ewert¹, Stefan Martinoff⁴, Heiko Stern¹

Congenital Heart Disease, Vol.18, No.4, pp. 461-474, 2023, DOI:10.32604/chd.2023.031075

Abstract Background: Pressure measurement in total cavopulmonary connection (TCPC) patients is a domain of cardiac catheterization. 4D velocity encoded cardiovascular magnetic resonance (4D–flow MRI) offers an alternative for assessment of even minor pressure differences. The scope of this study was to measure even minor pressure differences in the anastomosis of TCPC patients, who are clinically uncompromised. Methods: Twenty-four patients (median 15 years [8;34]) with TCPC were studied prospectively by 4D-flow MRI. Pressure differences between superior vena cava (SVC) and extracardiac conduit (C) to both right pulmonary artery (RPA) and left pulmonary artery (LPA) were assessed. Small fluid obstructions as vortices within… More > Graphic Abstract

Alaa Alsaheel, Reem Alhassoun, Reema Alrashed, Noura Almatrafi, Noura Almallouhi, Saleh Albahli^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2461-2482, 2023, DOI:10.32604/cmc.2023.040257

Abstract With the increasing use of deep learning technology, there is a growing concern over creating deep fake images and videos that can potentially be used for fraud. In healthcare, manipulating medical images could lead to misdiagnosis and potentially life-threatening consequences. Therefore, the primary purpose of this study is to explore the use of deep learning algorithms to detect deep fake images by solving the problem of recognizing the handling of samples of cancer and other diseases. Therefore, this research proposes a framework that leverages state-of-the-art deep convolutional neural networks (CNN) and a large dataset of authentic and deep fake medical… More >

Hui Zheng^1,2, Xiaohan Chen², Li Li², Dawei Qi¹, Jiale Wang¹, Jiaying Lou^1,*, Wenjun Wang^1,*

Journal of Renewable Materials, Vol.11, No.10, pp. 3693-3709, 2023, DOI:10.32604/jrm.2023.027748

Abstract The issue of plastic pollution has attracted widespread social attention. Gelatin is valued as a degradable bio-based material, especially as an edible active packaging material. However, the commonly used solution-casting filmforming technology limits the mass production of gelatin films. In order to improve the production efficiency and enhance the commercial value of gelatin films, in this study, fish gelatin (FG) particles were successfully blended with essential oils (EOs) to prepare active films by melt extrusion technique, a common method for commercial plastics, and applied to bread preservation. FG and EOs showed good compatibility with each other. The elongation at break… More > Graphic Abstract

Shahzad Noor Abbasi¹, Shahzaib Ashraf^1,*, M. Shazib Hameed¹, Sayed M. Eldin^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2795-2844, 2023, DOI:10.32604/cmes.2023.028963

Abstract The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making. The PFS is known to address the levels of participation and non-participation. To begin, we introduce the novel concept of a PFZN, which is a hybrid structure of Pythagorean fuzzy sets and the ZN. The PFZN is graded in terms of membership and non-membership, as well as reliability, which provides a strong advice in real-world decision support concerns. The PFZN is a useful tool for dealing with… More >

Abdul Haseeb¹, Muhammad Attique Khan^1,*, Faheem Shehzad¹, Majed Alhaisoni², Junaid Ali Khan¹, Taerang Kim³, Jae-Hyuk Cha³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529

Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >

Babangida Isyaku^1,2, Kamalrulnizam Bin Abu Bakar^2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1839-1879, 2023, DOI:10.32604/csse.2023.040456

Abstract Smart environments offer various services, including smart cities, e-healthcare, transportation, and wearable devices, generating multiple traffic flows with different Quality of Service (QoS) demands. Achieving the desired QoS with security in this heterogeneous environment can be challenging due to traffic flows and device management, unoptimized routing with resource awareness, and security threats. Software Defined Networks (SDN) can help manage these devices through centralized SDN controllers and address these challenges. Various schemes have been proposed to integrate SDN with emerging technologies for better resource utilization and security. Software Defined Wireless Body Area Networks (SDWBAN) and Software Defined Internet of Things (SDIoT)… More >

Abdul Qadir¹, Rabbia Mahum¹, Suliman Aladhadh^2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1365-1384, 2023, DOI:10.32604/csse.2023.037033

Abstract A considerable portion of the population now experiences osteoarthritis of the knee, spine, and hip due to lifestyle changes. Therefore, early treatment, recognition and prevention are essential to reduce damage; nevertheless, this time-consuming activity necessitates a variety of tests and in-depth analysis by physicians. To overcome the existing challenges in the early detection of Knee Osteoarthritis (KOA), an effective automated technique, prompt recognition, and correct categorization are required. This work suggests a method based on an improved deep learning algorithm that makes use of data from the knee images after segmentation to detect KOA and its severity using the Kellgren-Lawrence… More >

Jakkid Sanetuntikul¹, Borwon Narupai², Nawadon Petchwattana^3,*

Journal of Renewable Materials, Vol.11, No.9, pp. 3567-3582, 2023, DOI:10.32604/jrm.2023.029308

Abstract Wastes from polypropylene (PP) packages are accumulating every year because it is one of the most widely consumed and short lifecycle products. This paper aims to develop low thermal conductive and fire-retardant materials from post-consumer PP (pPP) packages. Ammonium polyphosphate (APP) and hollow glass microsphere (HGM) were further added to improve the fire retardancy and thermal conductivity of pPP. The influence of APP and HGM on the mechanical and thermal properties, fire retardancy and thermal conductivity of pPP were investigated and compared with that of virgin PP (vPP). HGM was constantly added at 5 wt% while the content of APP… More > Graphic Abstract