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  • Open Access

    ARTICLE

    Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

    Muhammad Mateen Yaqoob1, Waqar Khurshid1, Leo Liu2, Syed Zulqarnain Arif1, Imran Ali Khan1, Osman Khalid1,*, Raheel Nawaz2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1089-1103, 2022, DOI:10.32604/cmc.2022.024798

    Abstract Wireless Body Area Network (WBAN) technologies are emerging with extensive applications in several domains. Health is a fascinating domain of WBAN for smart monitoring of a patient's condition. An important factor to consider in WBAN is a node's lifetime. Improving the lifetime of nodes is critical to address many issues, such as utility and reliability. Existing routing protocols have addressed the energy conservation problem but considered only a few parameters, thus affecting their performance. Moreover, most of the existing schemes did not consider traffic prioritization which is critical in WBANs. In this paper, an adaptive multi-cost routing protocol is proposed… More >

  • Open Access

    ARTICLE

    Intelligent Deep Learning Model for Privacy Preserving IIoT on 6G Environment

    Anwer Mustafa Hilal1,*, Jaber S. Alzahrani2, Ibrahim Abunadi3, Nadhem Nemri4, Fahd N. Al-Wesabi5,6, Abdelwahed Motwakel1, Ishfaq Yaseen1, Abu Sarwar Zamani1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 333-348, 2022, DOI:10.32604/cmc.2022.024794

    Abstract In recent times, Industrial Internet of Things (IIoT) experiences a high risk of cyber attacks which needs to be resolved. Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks. Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network, the performance arrived at, in existing studies still needs improvement. In this scenario, the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT (PPBDL-IIoT) on 6G environment. The proposed PPBDL-IIoT technique aims at identifying the existence of… More >

  • Open Access

    ARTICLE

    Directional Wideband Wearable Antenna with Circular Parasitic Element for Microwave Imaging Applications

    N. A. Koma'rudin1, Z. Zakaria1,*, A. A. Althuwayb2, H. Lago3, H. Alsariera1, H. Nornikman1, A. J. A. Al-Gburi1, P. J. Soh4,5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 983-998, 2022, DOI:10.32604/cmc.2022.024782

    Abstract This work proposes a wideband and unidirectional antenna consisting of dual layer of coplanar waveguide based on the circular parasitic element technique. The design procedure is implemented in three stages: Design A, which operates at 3.94 GHz with a bandwidth of 3.83 GHz and a fractional bandwidth (FBW) of 97.2%; Design B, which operates at 3.98 GHz with a bandwidth of 0.66 GHz (FBW of 56.53%); and Design C as the final antenna. The final Design C is designed to resonate at several frequencies between 2.89 and 7.0 GHz for microwave imaging applications with a bandwidth of 4.11 GHz (79.8%)… More >

  • Open Access

    ARTICLE

    Enhancement of Biomass Material Characterization Images Using an Improved U-Net

    Zuozheng Lian1, Hong Zhao2,*, Qianjun Zhang1, Haizhen Wang1, E. Erdun3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1515-1528, 2022, DOI:10.32604/cmc.2022.024779

    Abstract For scanning electron microscopes with high resolution and a strong electric field, biomass materials under observation are prone to radiation damage from the electron beam. This results in blurred or non-viable images, which affect further observation of material microscopic morphology and characterization. Restoring blurred images to their original sharpness is still a challenging problem in image processing. Traditional methods can't effectively separate image context dependency and texture information, affect the effect of image enhancement and deblurring, and are prone to gradient disappearance during model training, resulting in great difficulty in model training. In this paper, we propose the use of… More >

  • Open Access

    ARTICLE

    Encryption with Image Steganography Based Data Hiding Technique in IIoT Environment

    Mahmoud Ragab1,2,3,*, Samah Alshehri4, Hani A. Alhadrami5,6,7, Faris Kateb1, Ehab Bahaudien Ashary8, S. Abdel-khalek9,10

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1323-1338, 2022, DOI:10.32604/cmc.2022.024775

    Abstract Rapid advancements of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) pose serious security issues by revealing secret data. Therefore, security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time. Practically, AI techniques can be utilized to design image steganographic techniques in IIoT. In addition, encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access. In order to accomplish secure data transmission in IIoT environment, this study presents novel encryption with image steganography based data hiding technique (EIS-DHT) for… More >

  • Open Access

    ARTICLE

    A Template Matching Based Feature Extraction for Activity Recognition

    Muhammad Hameed Siddiqi1,*, Helal Alshammari1, Amjad Ali2, Madallah Alruwaili1, Yousef Alhwaiti1, Saad Alanazi1, M. M. Kamruzzaman1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 611-634, 2022, DOI:10.32604/cmc.2022.024760

    Abstract Human activity recognition (HAR) can play a vital role in the monitoring of human activities, particularly for healthcare conscious individuals. The accuracy of HAR systems is completely reliant on the extraction of prominent features. Existing methods find it very challenging to extract optimal features due to the dynamic nature of activities, thereby reducing recognition performance. In this paper, we propose a robust feature extraction method for HAR systems based on template matching. Essentially, in this method, we want to associate a template of an activity frame or sub-frame comprising the corresponding silhouette. In this regard, the template is placed on… More >

  • Open Access

    ARTICLE

    Archery Algorithm: A Novel Stochastic Optimization Algorithm for Solving Optimization Problems

    Fatemeh Ahmadi Zeidabadi1, Mohammad Dehghani2, Pavel Trojovský2,*, Štěpán Hubálovský3, Victor Leiva4, Gaurav Dhiman5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 399-416, 2022, DOI:10.32604/cmc.2022.024736

    Abstract Finding a suitable solution to an optimization problem designed in science is a major challenge. Therefore, these must be addressed utilizing proper approaches. Based on a random search space, optimization algorithms can find acceptable solutions to problems. Archery Algorithm (AA) is a new stochastic approach for addressing optimization problems that is discussed in this study. The fundamental idea of developing the suggested AA is to imitate the archer's shooting behavior toward the target panel. The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the… More >

  • Open Access

    ARTICLE

    Compact Multibeam Array with Miniaturized Butler Matrix for 5G Applications

    Suleiman A. Babale1, Muhammad K. Ishfaq2,*, Ali Raza2, Jamal Nasir3, Ahmad Fayyaz3, Umer Ijaz2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 925-937, 2022, DOI:10.32604/cmc.2022.024711

    Abstract This paper presents the design and implementation of a miniaturized beam steering network that produces broadside beams when it is fed with a compact antenna array. Butler Matrix (BM) was used as the beam steering network. It was completely built from a miniaturized 3 dB hybrid-couplers in planar microstrip technology. It was configured by feeding the BM with a Planar Inverted-E Antenna (PIEA) array separated at 0.3 λ as against the 0.5 λ separation. This makes the BM produce a major radiation pattern at the broadside. Apart from the miniaturization, no modification was made from the BM side. However, employing effective… More >

  • Open Access

    ARTICLE

    Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

    Manar Ahmed Hamza1,*, Abdelzahir Abdelmaboud2, Souad Larabi-Marie-Sainte3, Haya Mesfer Alshahrani4, Mesfer Al Duhayyim5, Hamza Awad Ibrahim6, Mohammed Rizwanullah1, Ishfaq Yaseen1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1951-1965, 2022, DOI:10.32604/cmc.2022.024692

    Abstract Generally, software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software. But, the quality of test cases has a considerable influence on fault revealing capability of software testing activity. Test Case Prioritization (TCP) remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected (APFD) and time spent upon execution results. TCP is mainly intended to design a collection of test cases that can accomplish early optimization using preferred characteristics. The studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection… More >

  • Open Access

    ARTICLE

    Artificial Intelligence-Based Fusion Model for Paddy Leaf Disease Detection and Classification

    Ahmed S. Almasoud1, Abdelzahir Abdelmaboud2, Taiseer Abdalla Elfadil Eisa3, Mesfer Al Duhayyim4, Asma Abbas Hassan Elnour5, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6, Abu Sarwar Zamani6

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1391-1407, 2022, DOI:10.32604/cmc.2022.024618

    Abstract In agriculture, rice plant disease diagnosis has become a challenging issue, and early identification of this disease can avoid huge loss incurred from less crop productivity. Some of the recently-developed computer vision and Deep Learning (DL) approaches can be commonly employed in designing effective models for rice plant disease detection and classification processes. With this motivation, the current research work devises an Efficient Deep Learning based Fusion Model for Rice Plant Disease (EDLFM-RPD) detection and classification. The aim of the proposed EDLFM-RPD technique is to detect and classify different kinds of rice plant diseases in a proficient manner. In addition,… More >

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