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Jaeyong Kang¹, Chul-Su Kim², Jeong Won Kang³, Jeonghwan Gwak^1,4,5,6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1-14, 2022, DOI:10.32604/cmc.2022.023641 - 18 May 2022
Abstract The anomaly detection of the brake operating unit (BOU) in the brake systems on metro vehicle is critical for the safety and reliability of the trains. On the other hand, current periodic inspection and maintenance are unable to detect anomalies in an early stage. Also, building an accurate and stable system for detecting anomalies is extremely difficult. Therefore, we present an efficient model that use an ensemble of recurrent autoencoders to accurately detect the BOU abnormalities of metro trains. This is the first proposal to employ an ensemble deep learning technique to detect BOU abnormalities… More >

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Khalid Hamid¹, Muhammad Waseem Iqbal^2,*, Abaid Ur Rehman Virk³, Muhammad Usman Ashraf⁴, Ahmed Mohammed Alghamdi⁵, Adel A. Bahaddad⁶, Khalid Ali Almarhabi⁷
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 15-31, 2022, DOI:10.32604/cmc.2022.028406 - 18 May 2022
Abstract Any number that can be uniquely determined by a graph is called a graph invariant. During the last twenty years’ countless mathematical graph invariants have been characterized and utilized for correlation analysis. However, no reliable examination has been embraced to decide, how much these invariants are related with a network graph or molecular graph. In this paper, it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science, mathematics, chemistry, pharmacy, informatics and biology in context with physical and chemical structures and networks, because k-banhatti sombor More >

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Waleed El Nahal¹, Hatim G. Zaini², Raghad H. Zaini³, Sherif S. M. Ghoneim^4,*, Ashraf Mohamed Ali Hassan⁵
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 33-50, 2022, DOI:10.32604/cmc.2022.028190 - 18 May 2022
Abstract Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for… More >

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Qi He¹, Wenlong Li¹, Zengzhou Hao², Guohua Liu³, Dongmei Huang¹, Wei Song^1,*, Huifang Xu⁴, Fayez Alqahtani⁵, Jeong-Uk Kim⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 51-67, 2022, DOI:10.32604/cmc.2022.026771 - 18 May 2022
Abstract Sea surface temperature (SST) is closely related to global climate change, ocean ecosystem, and ocean disaster. Accurate prediction of SST is an urgent and challenging task. With a vast amount of ocean monitoring data are continually collected, data-driven methods for SST time-series prediction show promising results. However, they are limited by neglecting complex interactions between SST and other ocean environmental factors, such as air temperature and wind speed. This paper uses multi-factor time series SST data to propose a sequence-to-sequence network with two-module attention (TMA-Seq2seq) for long-term time series SST prediction. Specifically, TMA-Seq2seq is an… More >

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936

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Hyun Sook Rhee^*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 69-85, 2022, DOI:10.32604/cmc.2022.026751 - 18 May 2022
Abstract As the use of cloud storage for various services increases, the amount of private personal information along with data stored in the cloud storage is also increasing. To remotely use the data stored on the cloud storage, the data to be stored needs to be encrypted for this reason. Since “searchable encryption” is enable to search on the encrypted data without any decryption, it is one of convenient solutions for secure data management. A public key encryption with keyword search (for short, PEKS) is one of searchable encryptions. Abdalla et al. firstly defined IND-CCA security… More >

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1207

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Bassam A. Y. Alqaralleh^1,*, Fahad Aldhaban¹, Anas Abukaraki², Esam A. AlQaralleh³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 87-101, 2022, DOI:10.32604/cmc.2022.026729 - 18 May 2022
Abstract Diabetic Retinopathy (DR) has become a widespread illness among diabetics across the globe. Retinal fundus images are generally used by physicians to detect and classify the stages of DR. Since manual examination of DR images is a time-consuming process with the risks of biased results, automated tools using Artificial Intelligence (AI) to diagnose the disease have become essential. In this view, the current study develops an Optimal Deep Learning-enabled Fusion-based Diabetic Retinopathy Detection and Classification (ODL-FDRDC) technique. The intention of the proposed ODL-FDRDC technique is to identify DR and categorize its different grades using retinal More >

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967

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Apinya Innok¹, Chittapon Keawin², Peerapong Uthansakul^2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 103-118, 2022, DOI:10.32604/cmc.2022.027106 - 18 May 2022
Abstract In communication channel estimation, the Least Square (LS) technique has long been a widely accepted and commonly used principle. This is because the simple calculation method is compared with other channel estimation methods. The Minimum Mean Squares Error (MMSE), which is developed later, is devised as the next step because the goal is to reduce the error rate in the communication system from the conventional LS technique which still has a higher error rate. These channel estimations are very important to modern communication systems, especially massive MIMO. Evaluating the massive MIMO channel is one of… More >

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842

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Zhen-Zhen Li¹, Zi-Chen Li¹, Yi-Ru Sun^2,3,*, Haseeb Ahmad⁴, Gang Xu^5,6, Xiu-Bo Chen³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 119-132, 2022, DOI:10.32604/cmc.2022.027437 - 18 May 2022
Abstract As an innovative theory and technology, quantum network coding has become the research hotspot in quantum network communications. In this paper, a quantum remote state preparation scheme based on quantum network coding is proposed. Comparing with the general quantum remote state preparation schemes, our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network, by designing the appropriate encoding and decoding steps for quantum network coding. What is worth mentioning, from the network model, this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck… More >

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825

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Adel Hamdan Mohammad^1,*, Tariq Alwada’n², Omar Almomani³, Sami Smadi³, Nidhal ElOmari⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 133-150, 2022, DOI:10.32604/cmc.2022.027475 - 18 May 2022
Abstract Intrusion detection is a serious and complex problem. Undoubtedly due to a large number of attacks around the world, the concept of intrusion detection has become very important. This research proposes a multilayer bio-inspired feature selection model for intrusion detection using an optimized genetic algorithm. Furthermore, the proposed multilayer model consists of two layers (layers 1 and 2). At layer 1, three algorithms are used for the feature selection. The algorithms used are Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Firefly Optimization Algorithm (FFA). At the end of layer 1, a priority value… More >

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834

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Taek-Young Youn¹, Nam-Su Jho^2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 151-164, 2022, DOI:10.32604/cmc.2022.026653 - 18 May 2022
Abstract

Due to the development of 5G communication, many aspects of information technology (IT) services are changing. With the development of communication technologies such as 5G, it has become possible to provide IT services that were difficult to provide in the past. One of the services made possible through this change is cloud-based collaboration. In order to support secure collaboration over cloud, encryption technology to securely manage dynamic data is essential. However, since the existing encryption technology is not suitable for encryption of dynamic data, a new technology that can provide encryption for dynamic data is

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846

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Wenbin Bi¹, Fang Yu², Ning Cao^3,*, Russell Higgs⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 165-180, 2022, DOI:10.32604/cmc.2022.027776 - 18 May 2022
Abstract Load-time series data in mobile cloud computing of Internet of Vehicles (IoV) usually have linear and nonlinear composite characteristics. In order to accurately describe the dynamic change trend of such loads, this study designs a load prediction method by using the resource scheduling model for mobile cloud computing of IoV. Firstly, a chaotic analysis algorithm is implemented to process the load-time series, while some learning samples of load prediction are constructed. Secondly, a support vector machine (SVM) is used to establish a load prediction model, and an improved artificial bee colony (IABC) function is designed… More >

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822

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Pichaya Chaipanya^1,*, Supachai Kaewuam¹, Jiraphan Hirunruang¹, Wichaya Suntara¹, Nuchanart Santalunai², Samran Santalunai³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 181-198, 2022, DOI:10.32604/cmc.2022.028616 - 18 May 2022
Abstract This paper presents the single element dual band switched beam textile antenna. The antenna can operate at frequencies of 0.7 and 2.6 GHz using for 5G wireless communication applications. Textile fabric is considered to be used for substrate layer at the parts of a microstrip antenna for wireless body area network. The beam pattern of antenna can be switched into two directions by changing the position of shorted-circuit points at each edge of antenna. The main beam direction is 45°/225° when corner A is shorted while it steers at 135°/315° when corner B is shorted… More >

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967

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Minkyung Lee¹, Julian Jang-Jaccard², Jin Kwak^3,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 199-223, 2022, DOI:10.32604/cmc.2022.028495 - 18 May 2022
Abstract New technologies that take advantage of the emergence of massive Internet of Things (IoT) and a hyper-connected network environment have rapidly increased in recent years. These technologies are used in diverse environments, such as smart factories, digital healthcare, and smart grids, with increased security concerns. We intend to operate Security Orchestration, Automation and Response (SOAR) in various environments through new concept definitions as the need to detect and respond automatically to rapidly increasing security incidents without the intervention of security personnel has emerged. To facilitate the understanding of the security concern involved in this newly… More >

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1340

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Hussein Abulkasim^1,*, Eatedal Alabdulkreem², Safwat Hamad³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 225-232, 2022, DOI:10.32604/cmc.2022.025727 - 18 May 2022
Abstract Quantum key agreement is a promising key establishing protocol that can play a significant role in securing 5G/6G communication networks. Recently, Liu et al. (Quantum Information Processing 18(8):1-10, 2019) proposed a multi-party quantum key agreement protocol based on four-qubit cluster states was proposed. The aim of their protocol is to agree on a shared secret key among multiple remote participants. Liu et al. employed four-qubit cluster states to be the quantum resources and the X operation to securely share a secret key. In addition, Liu et al.'s protocol guarantees that each participant makes an equal More >

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875

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K. Anitha¹, S. Srinivasan^2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 233-247, 2022, DOI:10.32604/cmc.2022.026542 - 18 May 2022
Abstract In India’s economy, agriculture has been the most significant contributor. Despite the fact that agriculture’s contribution is decreasing as the world’s population grows, it continues to be the most important source of employment with a little margin of difference. As a result, there is a pressing need to pick up the pace in order to achieve competitive, productive, diverse, and long-term agriculture. Plant disease misinterpretations can result in the incorrect application of pesticides, causing crop harm. As a result, early detection of infections is critical as well as cost-effective for farmers. To diagnose the disease… More >

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1168

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Prem Junsawang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Soheil Salahshour⁴, Thongchai Botmart^5,*, Wajaree Weera³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 249-263, 2022, DOI:10.32604/cmc.2022.028513 - 18 May 2022
Abstract The aim of these investigations is to find the numerical performances of the delay differential two-prey and one-predator system. The delay differential models are very significant and always difficult to solve the dynamical kind of ecological nonlinear two-prey and one-predator system. Therefore, a stochastic numerical paradigm based artificial neural network (ANN) along with the Levenberg-Marquardt backpropagation (L-MB) neural networks (NNs), i.e., L-MBNNs is proposed to solve the dynamical two-prey and one-predator model. Three different cases based on the dynamical two-prey and one-predator system have been discussed to check the correctness of the L-MBNNs. The statistic More >

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1370

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870

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ARTICLE

Jian Liu^1,*, Xiaodong Xia¹, Chunyang Han², Jiao Hui³, Jim Feng⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 265-278, 2022, DOI:10.32604/cmc.2022.029227 - 18 May 2022
Abstract As a common and high-risk type of disease, heart disease seriously threatens people’s health. At the same time, in the era of the Internet of Thing (IoT), smart medical device has strong practical significance for medical workers and patients because of its ability to assist in the diagnosis of diseases. Therefore, the research of real-time diagnosis and classification algorithms for arrhythmia can help to improve the diagnostic efficiency of diseases. In this paper, we design an automatic arrhythmia classification algorithm model based on Convolutional Neural Network (CNN) and Encoder-Decoder model. The model uses Long Short-Term More >

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947

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Fadia Ali Khan¹, Jameel Ahmed¹, Fehaid Alqahtani², Suliman A. Alsuhibany³, Fawad Ahmed⁴, Jawad Ahmad^5,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 279-294, 2022, DOI:10.32604/cmc.2022.028789 - 18 May 2022
Abstract In this paper, we present an image encryption scheme based on the multi-stage chaos-based image encryption algorithm. The method works on the principle of confusion and diffusion. The proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing schemes. Initially, an image (red, green, and blue components) is partitioned into blocks with an equal number of pixels. Each block is then processed with Tinkerbell Chaotic Map (TBCM) to get shuffled pixels and shuffled blocks. Composite Fractal Function (CFF) change the value of pixels of each color component More >

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Mohammed Gollapalli¹, Atta-ur-Rahman^2,*, Dhiaa Musleh², Nehad Ibrahim², Muhammad Adnan Khan³, Sagheer Abbas⁴, Ayesha Atta⁵, Muhammad Aftab Khan⁶, Mehwash Farooqui⁶, Tahir Iqbal⁷, Mohammed Salih Ahmed⁶, Mohammed Imran B. Ahmed⁶, Dakheel Almoqbil⁸, Majd Nabeel², Abdullah Omer²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 295-310, 2022, DOI:10.32604/cmc.2022.027925 - 18 May 2022
Abstract The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems. Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide. Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road. To address this overwhelming problem, in this article, a cloud-based intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach. The aim of the study… More >

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Yazan Al-Issa¹, Ali Mohammad Alqudah^2,*, Hiam Alquran^3,2, Ahmed Al Issa⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 311-326, 2022, DOI:10.32604/cmc.2022.025750 - 18 May 2022
Abstract Pulmonary diseases are common throughout the world, especially in developing countries. These diseases include chronic obstructive pulmonary diseases, pneumonia, asthma, tuberculosis, fibrosis, and recently COVID-19. In general, pulmonary diseases have a similar footprint on chest radiographs which makes them difficult to discriminate even for expert radiologists. In recent years, many image processing techniques and artificial intelligence models have been developed to quickly and accurately diagnose lung diseases. In this paper, the performance of four popular pretrained models (namely VGG16, DenseNet201, DarkNet19, and XceptionNet) in distinguishing between different pulmonary diseases was analyzed. To the best of… More >

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916

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Hanan Abdullah Mengash¹, Radwa Marzouk¹, Siwar Ben Haj Hassine², Anwer Mustafa Hilal^3,*, Ishfaq Yaseen³, Abdelwahed Motwakel³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 327-342, 2022, DOI:10.32604/cmc.2022.026464 - 18 May 2022
Abstract Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise… More >

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851

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Sankar Sennan¹, Digvijay Pandey^2,*, Youseef Alotaibi³, Saleh Alghamdi⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 343-361, 2022, DOI:10.32604/cmc.2022.028334 - 18 May 2022
Abstract In the present scenario, Deep Learning (DL) is one of the most popular research algorithms to increase the accuracy of data analysis. Due to intra-class differences and inter-class variation, image classification is one of the most difficult jobs in image processing. Plant or spinach recognition or classification is one of the deep learning applications through its leaf. Spinach is more critical for human skin, bone, and hair, etc. It provides vitamins, iron, minerals, and protein. It is beneficial for diet and is readily available in people's surroundings. Many researchers have proposed various machine learning and… More >

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962

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Wenzheng Yu¹, Aodi Fu¹, Li Shao², Haitao Liu², Xin Yao^1,*, Tianliang Chen², Hanxiaoya Zhang³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 363-379, 2022, DOI:10.32604/cmc.2022.027009 - 18 May 2022
Abstract This paper mainly was based on the average temperature, precipitation, humidity, and wind direction of Gangcha county from 1960 to 2013. By using wavelet analysis and Mann-Kendall (M-K) mutation analysis, specifically analyzed the climate change characteristics in the lake basin area of Gangcha county. The result showed that the climatic change in the lake basin area of Gangcha county is noticeable. The average temperature, average minimum temperature, average maximum temperature, and evaporation showed an increasing trend. But the evaporation in the study area was higher than precipitation. The average relative humidity showed a decreasing trend.… More >

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911

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Mahmoud Ragab^1,2,3,*, Maha Farouk S. Sabir⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 381-395, 2022, DOI:10.32604/cmc.2022.027327 - 18 May 2022
Abstract In recent years, Smart City Infrastructures (SCI) have become familiar whereas intelligent models have been designed to improve the quality of living in smart cities. Simultaneously, anomaly detection in SCI has become a hot research topic and is widely explored to enhance the safety of pedestrians. The increasing popularity of video surveillance system and drastic increase in the amount of collected videos make the conventional physical investigation method to identify abnormal actions, a laborious process. In this background, Deep Learning (DL) models can be used in the detection of anomalies found through video surveillance systems.… More >

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773

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Sujit Goswami^1,*, Sujit Kumar Mandal¹, Soumen Banerjee²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 397-410, 2022, DOI:10.32604/cmc.2022.025657 - 18 May 2022
Abstract In this paper a novel, compact, microstrip-fed, quad-band monopole antenna is presented for the application of Global System for Mobile communication (GSM 900), Worldwide Interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). The proposed antenna comprises of a sickle-shaped structure with four circular arc strips, and a modified rectangular ground plane. The four strips of the antenna are independently responsible for the four different resonant frequencies of the operating bands and can be tuned separately to control the radiation performance. The proposed quad-band antenna is designed to resonate at 940 MHz for GSM More >

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Shalermchon Tangwachirapan, Wanwisa Thaiwirot^*, Prayoot Akkaraekthalin
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 411-431, 2022, DOI:10.32604/cmc.2022.028294 - 18 May 2022
Abstract This paper presents the design and analysis of antipodal Vivaldi antennas (AVAs) for breast cancer detection. In order to enhance the antenna gain, different techniques such as using the uniform and non-uniform corrugation, expanding the dielectric substrate and adding the parasitic patch are applied to original AVA. The design procedure of two developed AVA structures i.e., AVA with non-uniform corrugation and AVA with parasitic patch are presented. The proposed AVAs are designed on inexpensive FR4 substrate. The AVA with non-uniform corrugation has compact dimension of mm² or , where is wavelength of the lowest operating frequency.… More >

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862

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Chih-Wen Chang^*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 433-451, 2022, DOI:10.32604/cmc.2022.027021 - 18 May 2022
Abstract We retrieve unknown nonlinear large space-time dependent forces burdened with the vibrating nonlinear Euler-Bernoulli beams under varied boundary data, comprising two-end fixed, cantilevered, clamped-hinged, and simply supported conditions in this study. Even though some researchers used several schemes to overcome these forward problems of Euler-Bernoulli beams; however, an effective numerical algorithm to solve these inverse problems is still not available. We cope with the homogeneous boundary conditions, initial data, and final time datum for each type of nonlinear beam by employing a variety of boundary shape functions. The unknown nonlinear large external force can be… More >

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Ibrahim M. Mehedi^1,2,*, Abdulah Jeza Aljohani^1,2, Ubaid M. Al-Saggaf^1,2, Ahmed I. Iskanderani¹, Thangam Palaniswamy¹, Mohamed Mahmoud³, Mohammed J. Abdulaal¹, Muhammad Bilal^1,2, Waleed Alasmary⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 453-463, 2022, DOI:10.32604/cmc.2022.022921 - 18 May 2022
Abstract This paper describes a system designed for linear servo cart systems that employs an integral-based Linear Active Disturbance Rejection Control (ILADRC) scheme to detect and respond to disturbances. The upgrade in this control technique provides extensive immunity to uncertainties, attenuation, internal disturbances, and external sources of noise. The fundamental technology base of LADRC is Extended State Observer (ESO). LADRC, when combined with Integral action, becomes a hybrid control technique, namely ILADRC. Setpoint tracking is based on Bode’s Ideal Transfer Function (BITF) in this proposed ILADRC technique. This proves to be a very robust and appropriate More >

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Linshan Shen¹, Ye Tian^1,*, Liguo Zhang^1,2, Guisheng Yin¹, Tong Shuai³, Shuo Liang³, Zhuofei Wu⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 465-476, 2022, DOI:10.32604/cmc.2022.027488 - 18 May 2022
Abstract The semi-supervised deep learning technology driven by a small part of labeled data and a large amount of unlabeled data has achieved excellent performance in the field of image processing. However, the existing semi-supervised learning techniques are all carried out under the assumption that the labeled data and the unlabeled data are in the same distribution, and its performance is mainly due to the two being in the same distribution state. When there is out-of-class data in unlabeled data, its performance will be affected. In practical applications, it is difficult to ensure that unlabeled data… More >

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E. Laxmi Lydia¹, T. M. Nithya², K. Vijayalakshmi³, Jeya Prakash Kadambaajan⁴, Gyanendra Prasad Joshi⁵, Sung Won Kim^6,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 477-492, 2022, DOI:10.32604/cmc.2022.025939 - 18 May 2022
Abstract Wireless sensor networks (WSN) encompass a set of inexpensive and battery powered sensor nodes, commonly employed for data gathering and tracking applications. Optimal energy utilization of the nodes in WSN is essential to capture data effectively and transmit them to destination. The latest developments of energy efficient clustering techniques can be widely applied to accomplish energy efficiency in the network. In this aspect, this paper presents an enhanced Archimedes optimization based cluster head selection (EAOA-CHS) approach for WSN. The goal of the EAOA-CHS method is to optimally choose the CHs from the available nodes in… More >

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Muhammad Zubair Rehman¹, Muhammad Aamir^2,*, Nazri Mohd. Nawi³, Abdullah Khan⁴, Saima Anwar Lashari⁵, Siyab Khan⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 493-511, 2022, DOI:10.32604/cmc.2022.021787 - 18 May 2022
Abstract

Recently, many researchers have used nature inspired metaheuristic algorithms due to their ability to perform optimally on complex problems. To solve problems in a simple way, in the recent era bat algorithm has become famous due to its high tendency towards convergence to the global optimum most of the time. But, still the standard bat with random walk has a problem of getting stuck in local minima. In order to solve this problem, this research proposed bat algorithm with levy flight random walk. Then, the proposed Bat with Levy flight algorithm is further hybridized with

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Long Guo¹, Dongsheng Sun^1,*, Abdul Waheed², Huijie Gao³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 513-532, 2022, DOI:10.32604/cmc.2022.028211 - 18 May 2022
Abstract Under the background of “Internet plus” rapid development, the agricultural logistics industry should apply information technology to every link of the agricultural product logistics industry chain. By making full use of the decision making module of the agricultural logistics information system, we can realize the full sharing of information and data resources, which makes the decision-making scheme of the agricultural logistics information system more optimized. In real economic society, the uncertainty and mismatch between the customer’s logistics service demand and the logistics service capability that the logistics service function provider can provide, that is, when… More >

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930

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Mahmoud Ragab^1,2,3,*, Hesham A. Abdushkour⁴, Alaa F. Nahhas⁵, Wajdi H. Aljedaibi⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 533-546, 2022, DOI:10.32604/cmc.2022.028856 - 18 May 2022
Abstract Lung cancer is the main cause of cancer related death owing to its destructive nature and postponed detection at advanced stages. Early recognition of lung cancer is essential to increase the survival rate of persons and it remains a crucial problem in the healthcare sector. Computer aided diagnosis (CAD) models can be designed to effectually identify and classify the existence of lung cancer using medical images. The recently developed deep learning (DL) models find a way for accurate lung nodule classification process. Therefore, this article presents a deer hunting optimization with deep convolutional neural network… More >

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Kun-Lin Tsai^1,2,*, Li-Woei Chen³, Fang-Yie Leu^4,5, Chuan-Tian Wu¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 547-562, 2022, DOI:10.32604/cmc.2022.026557 - 18 May 2022
Abstract Secure data communication is an essential requirement for an Internet of Things (IoT) system. Especially in Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) systems, when important data are hacked, it may induce property loss or life hazard. Even though many IoT-related communication protocols are equipped with secure policies, they still have some security weaknesses in their IoT systems. LoRaWAN is one of the low power wide-area network protocols, and it adopts Advanced Encryption Standard (AES) to provide message integrity and confidentiality. However, LoRaWAN's encryption key update scheme can be further improved.… More >

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821

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Wenzheng Yu¹, Yang Gao¹, Zhengyu Yuan¹, Xin Yao^1,*, Mingxuan Zhu¹, Hanxiaoya Zhang²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 563-576, 2022, DOI:10.32604/cmc.2022.027008 - 18 May 2022
Abstract

Poisson-Gumbel joint distribution model uses maximum wind speed corresponding to multiple typhoons to construct sample sequence. Thresholds are usually used to filter sample sequences to make them more consistent with Poisson distribution. However, few studies have discussed the threshold setting and its impact on Poisson-Gumbel joint distribution model. In this study, a sample sequence based on the data of Qinzhou meteorological station from 2005 to 2018 were constructed. We set 0%, 5%, 10%, 20% and 30% gradient thresholds. Then, we analyzed the influence of threshold change on the calculation results of maximum wind speed in

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766

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Olga Ussatova^1,2, Aidana Zhumabekova^1,*, Yenlik Begimbayeva^2,3, Eric T. Matson⁴, Nikita Ussatov⁵
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 577-594, 2022, DOI:10.32604/cmc.2022.026552 - 18 May 2022
Abstract The fast development of Internet technologies ignited the growth of techniques for information security that protect data, networks, systems, and applications from various threats. There are many types of threats. The dedicated denial of service attack (DDoS) is one of the most serious and widespread attacks on Internet resources. This attack is intended to paralyze the victim's system and cause the service to fail. This work is devoted to the classification of DDoS attacks in the special network environment called Software-Defined Networking (SDN) using machine learning algorithms. The analyzed dataset included instances of two classes:… More >

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2038

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1306

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Tuan Nguyen Kim^1,*, Duy Ho Ngoc², Nikolay A. Moldovyan³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 595-610, 2022, DOI:10.32604/cmc.2022.023168 - 18 May 2022
Abstract There have been many digital signature schemes were developed based on the discrete logarithm problem on a finite field. In this study, we use the elliptic curve discrete logarithm problem to build new collective signature schemes. The cryptosystem on elliptic curve allows to generate digital signatures with the same level of security as other cryptosystems but with smaller keys. To extend practical applicability and enhance the security level of the group signature protocols, we propose two new types of collective digital signature schemes based on the discrete logarithm problem on the elliptic curve: i) the More >

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916

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1

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Nur Syazreen Ahmad^*, Jia Hui Teo, Patrick Goh
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 611-628, 2022, DOI:10.32604/cmc.2022.025823 - 18 May 2022
Abstract A single-channel electroencephalography (EEG) device, despite being widely accepted due to convenience, ease of deployment and suitability for use in complex environments, typically poses a great challenge for reactive brain-computer interface (BCI) applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles. In this study, a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control… More >

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1276

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882

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Zhijie Wang¹, Yue Zhao^1,*, Licheng Wu¹, Xiaojun Bi¹, Zhuoma Dawa², Qiang Ji³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 629-639, 2022, DOI:10.32604/cmc.2022.027092 - 18 May 2022
Abstract As one of Chinese minority languages, Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently. This, along with the relatively small Tibetan corpus, has resulted in an unsatisfying performance of Tibetan speech recognition based on an end-to-end model. This paper aims to achieve an accurate Tibetan speech recognition using a small amount of Tibetan training data. We demonstrate effective methods of Tibetan end-to-end speech recognition via cross-language transfer learning from three aspects: modeling unit selection, transfer learning method, and source language selection. Experimental results show that the More >

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1442

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1087

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Abdullah A. Asiri¹, Amna Iqbal², Javed Ferzund², Tariq Ali^2,*, Muhammad Aamir², Khalaf A. Alshamrani¹, Hassan A. Alshamrani¹, Fawaz F. Alqahtani¹, Muhammad Irfan³, Ali H. D. Alshehri¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 641-655, 2022, DOI:10.32604/cmc.2022.029000 - 18 May 2022
Abstract Abnormal growth of brain tissues is the real cause of brain tumor. Strategy for the diagnosis of brain tumor at initial stages is one of the key step for saving the life of a patient. The manual segmentation of brain tumor magnetic resonance images (MRIs) takes time and results vary significantly in low-level features. To address this issue, we have proposed a ResNet-50 feature extractor depended on multilevel deep convolutional neural network (CNN) for reliable images segmentation by considering the low-level features of MRI. In this model, we have extracted features through ResNet-50 architecture and… More >

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1386

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750

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Muhammad Islam Kamran¹, Muazzam A. Khan¹, Suliman A. Alsuhibany², Yazeed Yasin Ghadi³, Arshad⁴, Jameel Arif¹, Jawad Ahmad^5,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 657-672, 2022, DOI:10.32604/cmc.2022.028876 - 18 May 2022
Abstract The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation (4G) and 5th generation (5G) etc. Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way. Instead of the classical random walk, this paper proposes the quantum walk to achieve high image security. Classical random walk exhibits randomness due to the stochastic transitions between states, on the other hand, the quantum walk is more… More >

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825

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Shun Wang¹, Lin Qiao², Wei Fang³, Guodong Jing⁴, Victor S. Sheng⁵, Yong Zhang^1,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 673-687, 2022, DOI:10.32604/cmc.2022.028411 - 18 May 2022
Abstract PM2.5 concentration prediction is of great significance to environmental protection and human health. Achieving accurate prediction of PM2.5 concentration has become an important research task. However, PM2.5 pollutants can spread in the earth’s atmosphere, causing mutual influence between different cities. To effectively capture the air pollution relationship between cities, this paper proposes a novel spatiotemporal model combining graph attention neural network (GAT) and gated recurrent unit (GRU), named GAT-GRU for PM2.5 concentration prediction. Specifically, GAT is used to learn the spatial dependence of PM2.5 concentration data in different cities, and GRU is to extract the… More >

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1921

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1084

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G. Sheeba^1,*, T. M. Selvarajan²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 689-700, 2022, DOI:10.32604/cmc.2022.021781 - 18 May 2022
Abstract Wireless sensor networks (WSNs) are one of the most important improvements due to their remarkable capacities and their continuous growth in various applications. However, the lifetime of WSNs is very confined because of the delimited energy limit of their sensor nodes. This is the reason why energy conservation is considered the main exploration worry for WSNs. For this energy-efficient routing is required to save energy and to subsequently drag out the lifetime of WSNs. In this report we use the Ant Colony Optimization (ACO) method and are evaluated using the Genetic Algorithm (GA), based on… More >

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1311

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752

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Abdul Manan¹, Shahida Bashir¹, Abdul Majid^2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 701-717, 2022, DOI:10.32604/cmc.2022.027064 - 18 May 2022
Abstract The minimum vertex cover problem (MVCP) is a well-known combinatorial optimization problem of graph theory. The MVCP is an NP (nondeterministic polynomial) complete problem and it has an exponential growing complexity with respect to the size of a graph. No algorithm exits till date that can exactly solve the problem in a deterministic polynomial time scale. However, several algorithms are proposed that solve the problem approximately in a short polynomial time scale. Such algorithms are useful for large size graphs, for which exact solution of MVCP is impossible with current computational resources. The MVCP has… More >

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1445

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798

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Jie Chen¹, Chengsheng Yuan^1,2,*, Chen Cui², Zhihua Xia¹, Xingming Sun^1,3, Thangarajah Akilan⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 719-733, 2022, DOI:10.32604/cmc.2022.027984 - 18 May 2022
Abstract Fingerprint identification systems have been widely deployed in many occasions of our daily life. However, together with many advantages, they are still vulnerable to the presentation attack (PA) by some counterfeit fingerprints. To address challenges from PA, fingerprint liveness detection (FLD) technology has been proposed and gradually attracted people's attention. The vast majority of the FLD methods directly employ convolutional neural network (CNN), and rarely pay attention to the problem of over-parameterization and over-fitting of models, resulting in large calculation force of model deployment and poor model generalization. Aiming at filling this gap, this paper… More >

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1456

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1003

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Muhammad Abid Jamil^*, Mohamed K. Nour
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 735-747, 2022, DOI:10.32604/cmc.2022.028386 - 18 May 2022
Abstract Technical debt (TD) happens when project teams carry out technical decisions in favor of a short-term goal(s) in their projects, whether deliberately or unknowingly. TD must be properly managed to guarantee that its negative implications do not outweigh its advantages. A lot of research has been conducted to show that TD has evolved into a common problem with considerable financial burden. Test technical debt is the technical debt aspect of testing (or test debt). Test debt is a relatively new concept that has piqued the curiosity of the software industry in recent years. In this… More >

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1353

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848

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Doaa Sami Khafaga¹, Amel Ali Alhussan^1,*, El-Sayed M. El-kenawy^2,3, Ali E. Takieldeen³, Tarek M. Hassan⁴, Ehab A. Hegazy⁵, Elsayed Abdel Fattah Eid⁶, Abdelhameed Ibrahim⁷, Abdelaziz A. Abdelhamid^8,9
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 749-765, 2022, DOI:10.32604/cmc.2022.029605 - 18 May 2022
Abstract One of the most common kinds of cancer is breast cancer. The early detection of it may help lower its overall rates of mortality. In this paper, we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal images. The proposed approach starts with data preprocessing the input images and segmenting the significant regions of interest. In addition, to properly train the machine learning models, data augmentation is applied to increase the number of segmented regions using various scaling ratios. On the other hand, to extract the relevant features from the… More >

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2186

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1094

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Wei Chen¹, Caoyang Chen^1,*, Mi Liu¹, Xuhong Zhou², Haozhi Tan³, Mingliang Zhang⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 767-782, 2022, DOI:10.32604/cmc.2022.028571 - 18 May 2022
Abstract The present paper proposes a detection method for building exterior wall cracks since manual detection methods have high risk and low efficiency. The proposed method is based on Unmanned Aerial Vehicle (UAV) and computer vision technology. First, a crack dataset of 1920 images was established using UAV to collect the images of a residential building exterior wall under different lighting conditions. Second, the average crack detection precisions of different methods including the Single Shot MultiBox Detector, You Only Look Once v3, You Only Look Once v4, Faster Regional Convolutional Neural Network (R-CNN) and Mask R-CNN… More >

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1647

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1082

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Tuan Nguyen Kim^1,*, Duy Ho Ngoc², Nikolay A. Moldovyan³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 783-799, 2022, DOI:10.32604/cmc.2022.024677 - 18 May 2022
Abstract The representative collective digital signature scheme allows the creation of a unique collective signature on document M that represents an entire signing community consisting of many individual signers and many different signing groups, each signing group is represented by a group leader. On document M, a collective signature can be created using the representative digital signature scheme that represents an entire community consisting of individual signers and signing groups, each of which is represented by a group leader. The characteristic of this type of letter is that it consists of three elements (U, E, S),… More >

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762

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Mahmoud Ragab^1,2,3,*, Sultanah M. Alshammari⁴, Amer H. Asseri^2,5, Waleed K. Almutiry⁶
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 801-815, 2022, DOI:10.32604/cmc.2022.029140 - 18 May 2022
Abstract Brain cancer detection and classification is done utilizing distinct medical imaging modalities like computed tomography (CT), or magnetic resonance imaging (MRI). An automated brain cancer classification using computer aided diagnosis (CAD) models can be designed to assist radiologists. With the recent advancement in computer vision (CV) and deep learning (DL) models, it is possible to automatically detect the tumor from images using a computer-aided design. This study focuses on the design of automated Henry Gas Solubility Optimization with Fusion of Handcrafted and Deep Features (HGSO-FHDF) technique for brain cancer classification. The proposed HGSO-FHDF technique aims… More >

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