Yin Liang^1,*, Gaoxu Xu¹, Sadaqat ur Rehman²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4645-4661, 2022, DOI:10.32604/cmc.2022.026999

Abstract Whole brain functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used in the diagnosis of brain disorders such as autism spectrum disorder (ASD). Recently, an increasing number of studies have focused on employing deep learning techniques to analyze FC patterns for brain disease classification. However, the high dimensionality of the FC features and the interpretation of deep learning results are issues that need to be addressed in the FC-based brain disease classification. In this paper, we proposed a multi-scale attention-based deep neural network (MSA-DNN) model to classify FC patterns for the ASD diagnosis.… More >

Ayman Massaoudi^*, Abdelwahed Berguiga, Ahlem Harchay

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4663-4673, 2022, DOI:10.32604/cmc.2022.026972

Abstract Smart irrigation system, also referred as precision irrigation system, is an attractive solution to save the limited water resources as well as to improve crop productivity and quality. In this work, by using Internet of things (IoT), we aim to design a smart irrigation system for olive groves. In such IoT system, a huge number of low-power and low-complexity devices (sensors, actuators) are interconnected. Thus, a great challenge is to satisfy the increasing demands in terms of spectral efficiency. Moreover, securing the IoT system is also a critical challenge, since several types of cybersecurity threats may pose. In this paper,… More >

Xin Zihao¹, Wang Hongyuan^1,*, Qi Pengyu¹, Du Weidong², Zhang Ji¹, Chen Fuhua³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5925-5938, 2022, DOI:10.32604/cmc.2022.026943

Abstract For a long time, the detection and extraction of printed surface defects has been a hot issue in the print industry. Nowadays, defect detection of a large number of products still relies on traditional image processing algorithms such as scale invariant feature transform (SIFT) and oriented fast and rotated brief (ORB), and researchers need to design algorithms for specific products. At present, a large number of defect detection algorithms based on object detection have been applied but need lots of labeling samples with defects. Besides, there are many kinds of defects in printed surface, so it is difficult to enumerate… More >

Shi Qiu¹, Bin Li^2,*, Tao Zhou³, Feng Li⁴, Ting Liang⁵

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4897-4910, 2022, DOI:10.32604/cmc.2022.026855

Abstract Lung is an important organ of human body. More and more people are suffering from lung diseases due to air pollution. These diseases are usually highly infectious. Such as lung tuberculosis, novel coronavirus COVID-19, etc. Lung nodule is a kind of high-density globular lesion in the lung. Physicians need to spend a lot of time and energy to observe the computed tomography image sequences to make a diagnosis, which is inefficient. For this reason, the use of computer-assisted diagnosis of lung nodules has become the current main trend. In the process of computer-aided diagnosis, how to reduce the false positive… More >

Lei Zhang^1,2,*, Shouzhi Huang^1,2, Zhaocai Du³, Guangyao Ouyang^1,2, Heping Chen⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4817-4832, 2022, DOI:10.32604/cmc.2022.026845

Abstract In this study, a hyper-redundant manipulator was designed for detection and searching in narrow spaces for aerospace and earthquake rescue applications. A forward kinematics equation for the hyper-redundant manipulator was derived using the homogeneous coordinate transformation method. Based on the modal function backbone curve method and the known path, an improved modal method for the backbone curves was proposed. First, the configuration of the backbone curve for the hyper-redundant manipulator was divided into two parts: a mode function curve segment of the mode function and a known path segment. By changing the discrete points along the known path, the backbone… More >

Esam A. AlQaralleh¹, Fahad Aldhaban², Halah Nasseif², Bassam A.Y. Alqaralleh^2,*, Tamer AbuKhalil³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5727-5740, 2022, DOI:10.32604/cmc.2022.026780

Abstract Recent technological advancements have been used to improve the quality of living in smart cities. At the same time, automated detection of vehicles can be utilized to reduce crime rate and improve public security. On the other hand, the automatic identification of vehicle license plate (LP) character becomes an essential process to recognize vehicles in real time scenarios, which can be achieved by the exploitation of optimal deep learning (DL) approaches. In this article, a novel hybrid metaheuristic optimization based deep learning model for automated license plate character recognition (HMODL-ALPCR) technique has been presented for smart city environments. The major… More >

Saraswathi Sivamani¹, Sun Il Chon¹, Do Yeon Choi¹, Dong Hoon Lee², Ji Hwan Park^1,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4433-4452, 2022, DOI:10.32604/cmc.2022.026759

Abstract Existing segmentation and augmentation techniques on convolutional neural network (CNN) has produced remarkable progress in object detection. However, the nominal accuracy and performance might be downturned with the photometric variation of images that are directly ignored in the training process, along with the context of the individual CNN algorithm. In this paper, we investigate the effect of a photometric variation like brightness and sharpness on different CNN. We observe that random augmentation of images weakens the performance unless the augmentation combines the weak limits of photometric variation. Our approach has been justified by the experimental result obtained from the PASCAL… More >

Yong Chen¹, Chao Xu^1,*, Jing Selena He², Sheng Xiao³, Fanfan Shen¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5251-5272, 2022, DOI:10.32604/cmc.2022.026750

Abstract With the continuous expansion of software applications, people's requirements for software quality are increasing. Software defect prediction is an important technology to improve software quality. It often encodes the software into several features and applies the machine learning method to build defect prediction classifiers, which can estimate the software areas is clean or buggy. However, the current encoding methods are mainly based on the traditional manual features or the AST of source code. Traditional manual features are difficult to reflect the deep semantics of programs, and there is a lot of noise information in AST, which affects the expression of… More >

Muhamad Erza Aminanto^1,2,*, Ibnu Rifqi Purbomukti³, Harry Chandra², Kwangjo Kim⁴

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5301-5314, 2022, DOI:10.32604/cmc.2022.026749

Abstract Internet of Things (IoT) networks leverage wireless communication protocols, which adversaries can exploit. Impersonation attacks, injection attacks, and flooding are several examples of different attacks existing in Wi-Fi networks. Intrusion Detection System (IDS) became one solution to distinguish those attacks from benign traffic. Deep learning techniques have been intensively utilized to classify the attacks. However, the main issue of utilizing deep learning models is projecting the data, notably tabular data, into an image. This study proposes a novel projection from wireless network attacks data into a grid-based image for feeding one of the Convolutional Neural Network (CNN) models, EfficientNet. We… More >

Mahmoud Ragab^1,2,3,*, Ashwag Albukhari^2,4

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5577-5591, 2022, DOI:10.32604/cmc.2022.026715

Abstract Colorectal cancer is one of the most commonly diagnosed cancers and it develops in the colon region of large intestine. The histopathologist generally investigates the colon biopsy at the time of colonoscopy or surgery. Early detection of colorectal cancer is helpful to maintain the concept of accumulating cancer cells. In medical practices, histopathological investigation of tissue specimens generally takes place in a conventional way, whereas automated tools that use Artificial Intelligence (AI) techniques can produce effective results in disease detection performance. In this background, the current study presents an Automated AI-empowered Colorectal Cancer Detection and Classification (AAI-CCDC) technique. The proposed… More >