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Wenjun Li¹, Siyang Zhang¹, Guangwei Wu², Aldosary Saad³, Amr Tolba^3,4, Gwang-jun Kim^5,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4215-4231, 2022, DOI:10.32604/cmc.2022.024204
Abstract Recently, the development of Industrial Internet of Things has taken the advantage of 5G network to be more powerful and more intelligent. However, the upgrading of 5G network will cause a variety of issues increase, one of them is the increased cost of coverage. In this paper, we propose a sustainable wireless sensor networks system, which avoids the problems brought by 5G network system to some extent. In this system, deploying relays and selecting routing are for the sake of communication and charging. The main aim is to minimize the total energy-cost of communication under the precondition, where each terminal… More >

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899

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Chafaa Hamrouni^1,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4233-4248, 2022, DOI:10.32604/cmc.2022.023453
Abstract This research contributes to small satellite system development based on electromagnetic modeling and an integrated meta-materials antenna networks design for multimedia transmission contents. It includes an adaptive nonsingular mode tracking control design for small satellites systems using fuzzy waveless antenna networks. By analyzing and modeling based on electromagnetic methods, propagation properties of guided waves from metallic structures with simple or complex forms charge partially or entirely by anisotropic materials such as metamaterials. We propose a system control rule to omit uncertainties, including the inevitable approximation errors resulting from the finite number of fuzzy signal power value basis functions in antenna… More >

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713

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Muhammad Irfan¹, Ali Raza^2,*, Faisal Althobiani³, Nasir Ayub^4,5, Muhammad Idrees⁶, Zain Ali⁷, Kashif Rizwan⁴, Abdullah Saeed Alwadie¹, Saleh Mohammed Ghonaim³, Hesham Abdushkour³, Saifur Rahman¹, Omar Alshorman¹, Samar Alqhtani⁸
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4249-4265, 2022, DOI:10.32604/cmc.2022.025863
Abstract In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and complexity of the data, the… More >

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778

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Jaber S. Alzahrani¹, Reem M. Alshehri², Mohammad Alamgeer³, Anwer Mustafa Hilal^4,*, Abdelwahed Motwakel⁴, Ishfaq Yaseen⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4267-4281, 2022, DOI:10.32604/cmc.2022.027369
Abstract Recently, medical data classification becomes a hot research topic among healthcare professionals and research communities, which assist in the disease diagnosis and decision making process. The latest developments of artificial intelligence (AI) approaches paves a way for the design of effective medical data classification models. At the same time, the existence of numerous features in the medical dataset poses a curse of dimensionality problem. For resolving the issues, this article introduces a novel feature subset selection with artificial intelligence based classification model for biomedical data (FSS-AICBD) technique. The FSS-AICBD technique intends to derive a useful set of features and thereby… More >

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613

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Soban Arshad¹, Khalid Iqbal^1,*, Sheneela Naz², Sadaf Yasmin¹, Zobia Rehman²
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4283-4301, 2022, DOI:10.32604/cmc.2022.025442
Abstract Telecom industry relies on churn prediction models to retain their customers. These prediction models help in precise and right time recognition of future switching by a group of customers to other service providers. Retention not only contributes to the profit of an organization, but it is also important for upholding a position in the competitive market. In the past, numerous churn prediction models have been proposed, but the current models have a number of flaws that prevent them from being used in real-world large-scale telecom datasets. These schemes, fail to incorporate frequently changing requirements. Data sparsity, noisy data, and the… More >

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691

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Saman Riaz¹, Ali Arshad², Shahab S. Band^3,*, Amir Mosavi⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819
Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by using a Model consisting of… More >

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573

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Mahmoud Ragab^1,2,3,*, Abdullah Addas⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4323-4337, 2022, DOI:10.32604/cmc.2022.026602
Abstract Due to the advanced development in the multimedia-on-demand traffic in different forms of audio, video, and images, has extremely moved on the vision of the Internet of Things (IoT) from scalar to Internet of Multimedia Things (IoMT). Since Unmanned Aerial Vehicles (UAVs) generates a massive quantity of the multimedia data, it becomes a part of IoMT, which are commonly employed in diverse application areas, especially for capturing remote sensing (RS) images. At the same time, the interpretation of the captured RS image also plays a crucial issue, which can be addressed by the multi-label classification and Computational Linguistics based image… More >

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625

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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 >

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733

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ARTICLE

Noureen Fatima¹, Rashid Jahangir², Ghulam Mujtaba¹, Adnan Akhunzada^3,*, Zahid Hussain Shaikh⁴, Faiza Qureshi¹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4357-4374, 2022, DOI:10.32604/cmc.2022.023830
Abstract The Coronavirus Disease 2019 (COVID-19) pandemic poses the worldwide challenges surpassing the boundaries of country, religion, race, and economy. The current benchmark method for the detection of COVID-19 is the reverse transcription polymerase chain reaction (RT-PCR) testing. Nevertheless, this testing method is accurate enough for the diagnosis of COVID-19. However, it is time-consuming, expensive, expert-dependent, and violates social distancing. In this paper, this research proposed an effective multi-modality-based and feature fusion-based (MMFF) COVID-19 detection technique through deep neural networks. In multi-modality, we have utilized the cough samples, breathe samples and sound samples of healthy as well as COVID-19 patients from… More >

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581

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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 >

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651

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M. Sandeep Kumar¹, Mohammad Zubair Khan^2,*, Sukumar Rajendran¹, Ayman Noor³, A. Stephen Dass¹, J. Prabhu¹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4397-4409, 2022, DOI:10.32604/cmc.2022.025865
Abstract Diabetics is one of the world’s most common diseases which are caused by continued high levels of blood sugar. The risk of diabetics can be lowered if the diabetic is found at the early stage. In recent days, several machine learning models were developed to predict the diabetic presence at an early stage. In this paper, we propose an embedded-based machine learning model that combines the split-vote method and instance duplication to leverage an imbalanced dataset called PIMA Indian to increase the prediction of diabetics. The proposed method uses both the concept of over-sampling and under-sampling along with model weighting… More >

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637

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Dokyung Hwang¹, Hyeonmin Ro¹, Naejoung Kwak², Jinsang Hwang³, Dongju Kim^1,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378
Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important to detect facial and mask… More >

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1112

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533

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ARTICLE

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 >

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1151

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561

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Ankur Dumka¹, Parag Verma², Rajesh Singh³, Anuj Bhardwaj⁴, Khalid Alsubhi⁵, Divya Anand^6,7,*, Irene Delgado Noya^7,8, Silvia Aparicio Obregon^7,9
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4453-4466, 2022, DOI:10.32604/cmc.2022.023974
Abstract In December 2019, a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology pneumonia. The outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9, 2020, named Novel Coronavirus 2019 (nCoV-2019). This nCoV-2019 is now known as COVID-19. There is a big list of infections of this coronavirus which is present in the form of a big family. This virus can cause several diseases that usually develop with a serious problem. According to the World… More >

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1066

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586

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Ye-Eun Kim¹, Min-Gyu Kim², Hwankuk Kim^2,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4467-4488, 2022, DOI:10.32604/cmc.2022.026581
Abstract As Internet of Things (IoT) devices with security issues are connected to 5G mobile networks, the importance of IoT Botnet detection research in mobile network environments is increasing. However, the existing research focused on AI-based IoT Botnet detection research in wired network environments. In addition, the existing research related to IoT Botnet detection in ML-based mobile network environments have been conducted up to 4G. Therefore, this paper conducts a study on ML-based IoT Botnet traffic detection in the 5G core network. The binary and multiclass classification was performed to compare simple normal/malicious detection and normal/three-type IoT Botnet malware detection. In… More >

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806

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1

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ARTICLE

Li Xu^1,2,*, Ruzhen Lou¹, Chuanbin Zhang¹, Bo Lang³, Weiyue Ding⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4489-4507, 2022, DOI:10.32604/cmc.2022.027400
Abstract In the heavy clutter environment, the information capacity is large, the relationships among information are complicated, and track initiation often has a high false alarm rate or missing alarm rate. Obviously, it is a difficult task to get a high-quality track initiation in the limited measurement cycles. This paper studies the multi-target track initiation in heavy clutter. At first, a relaxed logic-based clutter filter algorithm is presented. In the algorithm, the raw measurement is filtered by using the relaxed logic method. We not only design a kind of incremental and adaptive filtering gate, but also add the angle extrapolation based… More >

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563

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Elias Hossain¹, Md. Shazzad Hossain², Md. Selim Hossain³, Sabila Al Jannat⁴, Moontahina Huda⁵, Sameer Alsharif⁶, Osama S. Faragallah⁷, Mahmoud M. A. Eid⁸, Ahmed Nabih Zaki Rashed^9,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4509-4523, 2022, DOI:10.32604/cmc.2022.025977
Abstract Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, and the 3D U-Net scored 97.99% among the different methods of deep learning. It is to be mentioned that traditional Convolutional Neural Network (CNN) gives 97.90% accuracy on top of the 3D MRI. In expansion, the image fusion approach combines the multimodal images and makes a fused image to extricate… More >

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1239

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645

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Haijun Geng^1,2, Zikun Jin¹, Jiangyuan Yao^3,*, Han Zhang⁴, Zhiguo Hu⁶, Bo Yang⁵, Yingije Guo⁷, Wei Wang¹, Qidong Zhang¹, Guoao Duan⁸
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4525-4540, 2022, DOI:10.32604/cmc.2022.027725
Abstract Network failures are unavoidable and occur frequently. When the network fails, intra-domain routing protocols deploying on the Internet need to undergo a long convergence process. During this period, a large number of messages are discarded, which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers (ISP). Therefore, improving the availability of intra-domain routing is a trending research question to be solved. Industry usually employs routing protection algorithms to improve intra-domain routing availability. However, existing routing protection schemes compute as many backup paths as possible to reduce message loss due to… More >

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1032

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562

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ARTICLE

Manar Ahmed Hamza^1,*, Noha Negm², Shaha Al-Otaibi³, Amel A. Alhussan⁴, Mesfer Al Duhayyim⁵, Fuad Ali Mohammed Al-Yarimi², Mohammed Rizwanullah¹, Ishfaq Yaseen¹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4541-4555, 2022, DOI:10.32604/cmc.2022.027048
Abstract Machine learning (ML) becomes a familiar topic among decision makers in several domains, particularly healthcare. Effective design of ML models assists to detect and classify the occurrence of diseases using healthcare data. Besides, the parameter tuning of the ML models is also essential to accomplish effective classification results. This article develops a novel red colobuses monkey optimization with kernel extreme learning machine (RCMO-KELM) technique for epileptic seizure detection and classification. The proposed RCMO-KELM technique initially extracts the chaotic, time, and frequency domain features in the actual EEG signals. In addition, the min-max normalization approach is employed for the pre-processing of… More >

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939

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622

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ARTICLE

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 >

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638

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Ayman A. El-Saleh¹, Abdulraqeb Alhammadi^2,*, Ibraheem Shayea³, Azizul Azizan⁴, Wan Haslina Hassan²
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4571-4587, 2022, DOI:10.32604/cmc.2022.024642
Abstract Mobile broadband (MBB) networks are expanding rapidly to deliver higher data speeds. The fifth-generation cellular network promises enhanced-MBB with high-speed data rates, low power connectivity, and ultra-low latency video streaming. However, existing cellular networks are unable to perform well due to high latency and low bandwidth, which degrades the performance of various applications. As a result, monitoring and evaluation of the performance of these network-supported services is critical. Mobile network providers optimize and monitor their network performance to ensure the highest quality of service to their end-users. This paper proposes a Bayesian model to estimate the minimum opinion score (MOS)… More >

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963

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576

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Souad Larabi-Marie-Sainte¹, Eatedal Alabdulkreem², Mohammad Alamgeer³, Mohamed K Nour⁴, Anwer Mustafa Hilal^5,*, Mesfer Al Duhayyim⁶, Abdelwahed Motwakel⁵, Ishfaq Yaseen⁵
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4589-4601, 2022, DOI:10.32604/cmc.2022.027922
Abstract Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. The CBADL-BEESC model performs feature… More >

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917

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623

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Tao Zhang¹, Shaokui Gu¹, Jinxing Niu^1,*, Yi Cao²
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4603-4614, 2022, DOI:10.32604/cmc.2022.027079
Abstract Traditional three-dimensional (3D) image reconstruction method, which highly dependent on the environment and has poor reconstruction effect, is easy to lead to mismatch and poor real-time performance. The accuracy of feature extraction from multiple images affects the reliability and real-time performance of 3D reconstruction technology. To solve the problem, a multi-view image 3D reconstruction algorithm based on self-encoding convolutional neural network is proposed in this paper. The algorithm first extracts the feature information of multiple two-dimensional (2D) images based on scale and rotation invariance parameters of Scale-invariant feature transform (SIFT) operator. Secondly, self-encoding learning neural network is introduced into the… More >

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604

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Erssa Arif^1,*, Syed Khuram Shahzad², Muhammad Waseem Iqbal³, Muhammad Arfan Jaffar⁴, Abdullah S. Alshahrani⁵, Ahmed Alghamdi⁶
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4615-4630, 2022, DOI:10.32604/cmc.2022.027571
Abstract The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution cameras that minimize the idealism.… More >

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863

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1079

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Yazeed Qasaymeh^*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4631-4643, 2022, DOI:10.32604/cmc.2022.026111
Abstract In this study, a compact 2 × 2 interlaced sequentially rotated dual-polarized dielectric-resonator antenna array is proposed for 5.8 GHz applications. The array is composed of a novel unit elements that are made of rectangular dielectric resonator (RDR) coupled to an eye slot for generating the orthogonal modes, and to acquire circular polarization (CP) radiation. For the purpose of miniaturization and achieving dual polarized resonance, the array is fed by two interlaced ports and each port excites two radiating elements. The first port feeds horizontal elements to obtain left hand circular polarization (LHCP). The second port feeds vertical elements to obtain right hand… More >

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658

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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 >

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1042

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593

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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 >

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696

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Mohammed Hadwan^1,2,3,*, Mohammed A. Al-Hagery⁴, Mohammed Al-Sarem⁵, Faisal Saeed^5,6
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4675-4689, 2022, DOI:10.32604/cmc.2022.027311
Abstract Different types of pandemics that have appeared from time to time have changed many aspects of daily life. Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown. The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store. A huge number of reviews are written daily by users to express their opinions, which include significant information to improve these applications. The manual processing and extracting of information from users’ reviews is an… More >

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672

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Bassam A. Y. Alqaralleh^1,*, Fahad Aldhaban¹, Esam A. AlQarallehs², Ahmad H. Al-Omari³
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4691-4707, 2022, DOI:10.32604/cmc.2022.026556
Abstract Cyber-attacks on cyber-physical systems (CPSs) resulted to sensing and actuation misbehavior, severe damage to physical object, and safety risk. Machine learning (ML) models have been presented to hinder cyberattacks on the CPS environment; however, the non-existence of labelled data from new attacks makes their detection quite interesting. Intrusion Detection System (IDS) is a commonly utilized to detect and classify the existence of intrusions in the CPS environment, which acts as an important part in secure CPS environment. Latest developments in deep learning (DL) and explainable artificial intelligence (XAI) stimulate new IDSs to manage cyberattacks with minimum complexity and high sophistication.… More >

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985

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612

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Zhenzhou Wang¹, Shao Cui¹, Xiang Wang^1,*, JiaFeng Tian²
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4709-4725, 2022, DOI:10.32604/cmc.2022.027767
Abstract To generate realistic three-dimensional animation of virtual character, capturing real facial expression is the primary task. Due to diverse facial expressions and complex background, facial landmarks recognized by existing strategies have the problem of deviations and low accuracy. Therefore, a method for facial expression capture based on two-stage neural network is proposed in this paper which takes advantage of improved multi-task cascaded convolutional networks (MTCNN) and high-resolution network. Firstly, the convolution operation of traditional MTCNN is improved. The face information in the input image is quickly filtered by feature fusion in the first stage and Octave Convolution instead of the… More >

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943

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534

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Ali Raza^*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4727-4740, 2022, DOI:10.32604/cmc.2022.027044
Abstract The design of evolutionary approaches has a vital role in the recent development of scientific literature. To tackle highly nonlinear complex problems, nonlinear ordinary differential equations, partial differential equations, stochastic differential equations, and many more may called computational algorithms. The rotavirus causes may include severe diarrhea, vomiting, and fever leading to rapid dehydration. By the report of the World Health Organization (WHO), approximately 600,000 children die worldwide each year, 80 percent of whom live in developing countries. Two million children are hospitalized each year. In Asia, up to 45 percent of the children hospitalized for diarrhea may be infected with… More >

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854

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545

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Letao Gao^1,*, Xiaoming Wang², Tao Wang³, Mengyu Chang⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4741-4754, 2022, DOI:10.32604/cmc.2022.027204
Abstract In the research field of bearing fault diagnosis, classical deep learning models have the problems of too many parameters and high computing cost. In addition, the classical deep learning models are not effective in the scenario of small data. In recent years, deep forest is proposed, which has less hyper parameters and adaptive depth of deep model. In addition, weighted deep forest (WDF) is proposed to further improve deep forest by assigning weights for decisions trees based on the accuracy of each decision tree. In this paper, weighted deep forest model-based bearing fault diagnosis method (WDBM) is proposed. The WDBM… More >

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1013

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622

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Shahzad Nazir¹, Muhammad Asif^1,*, Shahbaz Ahmad¹, Hanan Aljuaid², Shahbaz Ahmad¹, Yazeed Ghadi³, Zubair nawaz⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4755-4769, 2022, DOI:10.32604/cmc.2022.026145
Abstract Social media provide digitally interactional technologies to facilitate information sharing and exchanging individuals. Precisely, in case of disasters, a massive corpus is placed on platforms such as Twitter. Eyewitness accounts can benefit humanitarian organizations and agencies, but identifying the eyewitness Tweets related to the disaster from millions of Tweets is difficult. Different approaches have been developed to address this kind of problem. The recent state-of-the-art system was based on a manually created dictionary and this approach was further refined by introducing linguistic rules. However, these approaches suffer from limitations as they are dataset-dependent and not scalable. In this paper, we… More >

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618

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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 >

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Yanyan Han^1,2, Jiangping Yu³, Guangyu Hu⁴, Chenglei Pan⁴, Dingbang Xie⁵, Chao Guo^1,2,6,*, Abdul Waheed⁷
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4789-4802, 2022, DOI:10.32604/cmc.2022.027496
Abstract Verifiable secret sharing mainly solves the cheating behavior between malicious participants and the ground control center in the satellite network. The verification stage can verify the effectiveness of secret shares issued by the ground control center to each participant and verify the effectiveness of secret shares shown by participants. We use a lot of difficult assumptions based on mathematical problems in the verification stage, such as solving the difficult problem of the discrete logarithm, large integer prime factorization, and so on. Compared with other verifiable secret sharing schemes designed for difficult problems under the same security, the verifiable secret sharing… More >

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Chulwon Lee¹, Kyungho Lee^2,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4803-4816, 2022, DOI:10.32604/cmc.2022.025310
Abstract The damage caused by malicious software is increasing owing to the COVID-19 pandemic, such as ransomware attacks on information technology and operational technology systems based on corporate networks and social infrastructures and spear-phishing attacks on business or research institutes. Recently, several studies have been conducted to prevent further phishing emails in the workplace because malware attacks employ emails as the primary means of penetration. However, according to the latest research, there appears to be a limitation in blocking email spoofing through advanced blocking systems such as spam email filtering solutions and advanced persistent threat systems. Therefore, experts believe that it… More >

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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 >

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Yassir Edrees Almalki1¹, Ahmad Shaf², Tariq Ali², Muhammad Aamir², Sharifa Khalid Alduraibi³, Shoayea Mohessen Almutiri⁴, Muhammad Irfan⁵, Mohammad Abd Alkhalik Basha⁶, Alaa Khalid Alduraibi³, Abdulrahman Manaa Alamri⁷, Muhammad Zeeshan Azam⁸, Khalaf Alshamrani^9,*, Hassan A. Alshamrani⁹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4833-4851, 2022, DOI:10.32604/cmc.2022.027111
Abstract Breast cancer (BC) is the most common cause of women’s deaths worldwide. The mammography technique is the most important modality for the detection of BC. To detect abnormalities in mammographic images, the Breast Imaging Reporting and Data System (BI-RADs) is used as a baseline. The correct allocation of BI-RADs categories for mammographic images is always an interesting task, even for specialists. In this work, to detect and classify the mammogram images in BI-RADs, a novel hybrid model is presented using a convolutional neural network (CNN) with the integration of a support vector machine (SVM). The dataset used in this research… More >

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Thai Hoang Tuyet Nhi¹, Chia-Nan Wang¹, Nguyen Van Thanh^2,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4853-4865, 2022, DOI:10.32604/cmc.2022.026374
Abstract Vietnam is one of Southeast Asian countries with a rapid GDP growth rate, ranging from 6.5% to 7% annually, leading to an average increase in energy demand of 11% per year. This demand creates many new opportunities in the energy industry, especially renewable energy, to ensure sustainable development in the future for the country with applications of solar energy growing at the present, and other opportunities to expand in the future. In Vietnam, thanks to favorable weather, climate, terrain characteristics and many preferential support policies, there are many great opportunities in the field of solar energy exploitation and application. Location… More >

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Wei Fang^1,2,*, Liang Shen¹, Victor S. Sheng³, Qiongying Xue¹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4867-4877, 2022, DOI:10.32604/cmc.2022.027197
Abstract Precipitation nowcasting is of great significance for severe convective weather warnings. Radar echo extrapolation is a commonly used precipitation nowcasting method. However, the traditional radar echo extrapolation methods are encountered with the dilemma of low prediction accuracy and extrapolation ambiguity. The reason is that those methods cannot retain important long-term information and fail to capture short-term motion information from the long-range data stream. In order to solve the above problems, we select the spatiotemporal long short-term memory (ST-LSTM) as the recurrent unit of the model and integrate the 3D convolution operation in it to strengthen the model's ability to capture… More >

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Walid El-Shafai^1,2, Ehab Mahmoud Mohamed^3,4,*, Medien Zeghid^3,5, Anas M. Ali^1,6, Moustafa H. Aly⁷
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4879-4896, 2022, DOI:10.32604/cmc.2022.028364
Abstract High-quality medical microscopic images used for diseases detection are expensive and difficult to store. Therefore, low-resolution images are favorable due to their low storage space and ease of sharing, where the images can be enlarged when needed using Super-Resolution (SR) techniques. However, it is important to maintain the shape and size of the medical images while enlarging them. One of the problems facing SR is that the performance of medical image diagnosis is very poor due to the deterioration of the reconstructed image resolution. Consequently, this paper suggests a multi-SR and classification framework based on Generative Adversarial Network (GAN) to… More >

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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 >

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Yangjae Lee¹, Sung Hoon Baek², Jung Taek Seo³, Ki-Woong Park^1,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4911-4929, 2022, DOI:10.32604/cmc.2022.026657
Abstract One of the latest technologies enabling remote control, operational efficiency upgrades, and real-time big-data monitoring in an industrial control system (ICS) is the IIoT-Cloud ICS, which integrates the Industrial Internet of Things (IIoT) and the cloud into the ICS. Although an ICS benefits from the application of IIoT and the cloud in terms of cost reduction, efficiency improvement, and real-time monitoring, the application of this technology to an ICS poses an unprecedented security risk by exposing its terminal devices to the outside world. An adversary can collect information regarding senders, recipients, and prime-time slots through traffic analysis and use it… More >

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Gang Li¹, Haoyang Sun¹, Zhenbing Li¹, Peiqi Wu¹, Daniele Inserra^1,*, Jian Su², Xiaochuan Fang³, Guangjun Wen¹
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4931-4944, 2022, DOI:10.32604/cmc.2022.026654
Abstract

In this paper, a dynamic multi-ary query tree (DMQT) anti-collision protocol for Radio Frequency Identification (RFID) systems is proposed for large scale passive RFID tag identification. The proposed DMQT protocol is based on an iterative process between the reader and tags which identifies the position of collision bits through map commands and dynamically encodes them to optimize slots allocation through query commands. In this way, the DMQT completely eliminates empty slots and greatly reduces collision slots, which in turn reduces the identification time and energy costs. In addition and differently to other known protocols, the DMQT does not need to… More >

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Elias Hossain¹, Abdulwahab Alazeb^2,*, Naif Al Mudawi², Sultan Almakdi², Mohammed Alshehri², M. Gazi Golam Faruque³, Wahidur Rahman³
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4945-4966, 2022, DOI:10.32604/cmc.2022.027058
Abstract Depression is a crippling affliction and affects millions of individuals around the world. In general, the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts, which results in lower costs and improved patient outcomes. However, this strategy can necessitate a lot of buy-in from a large number of people, as well as additional training and logistical considerations. Thus, utilizing the machine learning algorithms, patients with depression based on information generally present in a medical file were analyzed and predicted. The methodology of this proposed study is… More >

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Chao Li¹, Fan Li^1,2, Cheng Huang³, Lihua Yin^1,*, Tianjie Luo^1,2, Bin Wang⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4967-4982, 2022, DOI:10.32604/cmc.2022.023496
Abstract Delegation mechanism in Internet of Things (IoT) allows users to share some of their permissions with others. Cloud-based delegation solutions require that only the user who has registered in the cloud can be delegated permissions. It is not convenient when a permission is delegated to a large number of temporarily users. Therefore, some works like CapBAC delegate permissions locally in an offline way. However, this is difficult to revoke and modify the offline delegated permissions. In this work, we propose a traceable capability-based access control approach (TCAC) that can revoke and modify permissions by tracking the trajectories of permissions delegation.… More >

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Seon Hong Lee¹, Haein Lee¹, Jang Hyun Kim^2,*
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4983-4997, 2022, DOI:10.32604/cmc.2022.027943
Abstract Metaverse is one of the main technologies in the daily lives of several people, such as education, tour systems, and mobile application services. Particularly, the number of users of mobile metaverse applications is increasing owing to the merit of accessibility everywhere. To provide an improved service, it is important to analyze online reviews that contain user satisfaction. Several previous studies have utilized traditional methods, such as the structural equation model (SEM) and technology acceptance method (TAM) for exploring user satisfaction, using limited survey data. These methods may not be appropriate for analyzing the users of mobile applications. To overcome this… More >

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Songbin Li^1,*, Peng Liu¹, Qiandong Yan¹, Ruiling Qian²
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4999-5013, 2022, DOI:10.32604/cmc.2022.026498
Abstract Recent convolutional neural networks (CNNs) based deep learning has significantly promoted fire detection. Existing fire detection methods can efficiently recognize and locate the fire. However, the accurate flame boundary and shape information is hard to obtain by them, which makes it difficult to conduct automated fire region analysis, prediction, and early warning. To this end, we propose a fire semantic segmentation method based on Global Position Guidance (GPG) and Multi-path explicit Edge information Interaction (MEI). Specifically, to solve the problem of local segmentation errors in low-level feature space, a top-down global position guidance module is used to restrain the offset… More >

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Prem Junswang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Waleed Adel^4,5, Thongchai Botmart^6,*, Wajaree Weera⁶
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5015-5030, 2022, DOI:10.32604/cmc.2022.027523
Abstract The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving a novel fractional chaotic financial model that represents the effect of memory and chaos in the presented system. The method is constructed with the combination of the ANNs along with the Levenberg-Marquardt backpropagation (LMB), named the ANNs-LMB. This technique is tested for solving the novel problem for three cases of the fractional-order values and the obtained results are compared with the reference solution. Fifteen numbers neurons have been used to solve the fractional-order chaotic financial model. The selection of the… More >

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Hanguang Luo¹, Tao Zou^1,*, Chunming Wu², Dan Li³, Shunbin Li¹, Chu Chu⁴
CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5031-5040, 2022, DOI:10.32604/cmc.2022.027118
Abstract In the emerging Industrial Internet of Things (IIoT), authentication problems have become an urgent issue for massive resource-constrained devices because traditional costly security mechanisms are not suitable for them. The security protocol designed for resource-constrained systems should not only be secure but also efficient in terms of usage of energy, storage, and processing. Although recently many lightweight schemes have been proposed, to the best of our knowledge, they are unable to address the problem of privacy preservation with the resistance of Denial of Service (DoS) attacks in a practical way. In this paper, we propose a lightweight authentication protocol based… More >

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