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  • Open Access

    ARTICLE

    A Secure Multiparty Quantum Homomorphic Encryption Scheme

    Jing-Wen Zhang1, Xiu-Bo Chen1,*, Gang Xu2,3, Heng-Ji Li4, Ya-Lan Wang5, Li-Hua Miao6, Yi-Xian Yang1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2835-2848, 2022, DOI:10.32604/cmc.2022.029125

    Abstract The significant advantage of the quantum homomorphic encryption scheme is to ensure the perfect security of quantum private data. In this paper, a novel secure multiparty quantum homomorphic encryption scheme is proposed, which can complete arbitrary quantum computation on the private data of multiple clients without decryption by an almost dishonest server. Firstly, each client obtains a secure encryption key through the measurement device independent quantum key distribution protocol and encrypts the private data by using the encryption operator and key. Secondly, with the help of the almost dishonest server, the non-maximally entangled states are pre-shared between the client and… More >

  • Open Access

    ARTICLE

    Maintain Optimal Configurations for Large Configurable Systems Using Multi-Objective Optimization

    Muhammad Abid Jamil1,*, Deafallah Alsadie1, Mohamed K. Nour1, Normi Sham Awang Abu Bakar2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4407-4422, 2022, DOI:10.32604/cmc.2022.029096

    Abstract To improve the maintenance and quality of software product lines, efficient configurations techniques have been proposed. Nevertheless, due to the complexity of derived and configured products in a product line, the configuration process of the software product line (SPL) becomes time-consuming and costly. Each product line consists of a various number of feature models that need to be tested. The different approaches have been presented by Search-based software engineering (SBSE) to resolve the software engineering issues into computational solutions using some metaheuristic approach. Hence, multiobjective evolutionary algorithms help to optimize the configuration process of SPL. In this paper, different multi-objective… More >

  • Open Access

    ARTICLE

    TMTACS: Two-Tier Multi-Trust-Based Algorithm to Countermeasure the Sybil Attacks

    Meena Bharti1,*, Shaveta Rani2, Paramjeet Singh2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3497-3512, 2022, DOI:10.32604/cmc.2022.029072

    Abstract Mobile Ad hoc Networks (MANETs) have always been vulnerable to Sybil attacks in which users create fake nodes to trick the system into thinking they’re authentic. These fake nodes need to be detected and deactivated for security reasons, to avoid harming the data collected by various applications. The MANET is an emerging field that promotes trust management among devices. Transparency is becoming more essential in the communication process, which is why clear and honest communication strategies are needed. Trust Management allows for MANET devices with different security protocols to connect. If a device finds difficulty in sending a message to… More >

  • Open Access

    ARTICLE

    LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis

    Yassir Edrees Almalki1, Maida Khalid2, Sharifa Khalid Alduraibi3, Qudsia Yousaf2, Maryam Zaffar2, Shoayea Mohessen Almutiri4, Muhammad Irfan5, Mohammad Abd Alkhalik Basha6, Alaa Khalid Alduraibi3, Abdulrahman Manaa Alamri7, Khalaf Alshamrani8, Hassan A. Alshamrani8,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4103-4121, 2022, DOI:10.32604/cmc.2022.029039

    Abstract Since reporting cases of breast cancer are on the rise all over the world. Especially in regions such as Pakistan, Saudi Arabia, and the United States. Efficient methods for the early detection and diagnosis of breast cancer are needed. The usual diagnosis procedures followed by physicians has been updated with modern diagnostic approaches that include computer-aided support for better accuracy. Machine learning based practices has increased the accuracy and efficiency of medical diagnosis, which has helped save lives of many patients. There is much research in the field of medical imaging diagnostics that can be applied to the variety of… More >

  • Open Access

    ARTICLE

    Cache Memory Design for Single Bit Architecture with Different Sense Amplifiers

    Reeya Agrawal1,*, Anjan Kumar1, Salman A. AlQahtani2, Mashael Maashi3, Osamah Ibrahim Khalaf4, Theyazn H. H. Aldhyani5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2313-2331, 2022, DOI:10.32604/cmc.2022.029019

    Abstract Most modern microprocessors have one or two levels of on-chip caches to make things run faster, but this is not always the case. Most of the time, these caches are made of static random access memory cells. They take up a lot of space on the chip and use a lot of electricity. A lot of the time, low power is more important than several aspects. This is true for phones and tablets. Cache memory design for single bit architecture consists of six transistors static random access memory cell, a circuit of write driver, and sense amplifiers (such as voltage… More >

  • Open Access

    ARTICLE

    Optimal and Robust Power System Stabilizers in a Multi Machine System

    Mehrdad Ahmadi Kamarposhti1,*, Hassan Shokouhandeh2, Ilhami Colak3, Kei Eguchi4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4139-4156, 2022, DOI:10.32604/cmc.2022.029011

    Abstract One method for eliminating oscillations in power systems is using stabilizers. By applying an appropriate control signal in the excitation system of a generator, a power system stabilizer improves the dynamic stability of power systems. However, the issue that is of high importance is the correct design of these stabilizers. These stabilizers must be designed to have proper performance when operating conditions change. When designed incorrectly, not only they do not improve the stability margin, but also increase the oscillations. In this paper, the robust design of power system stabilizers on a four-machine power system has been performed. For this… More >

  • Open Access

    ARTICLE

    Natural Language Processing with Optimal Deep Learning Based Fake News Classification

    Sara A. Althubiti1, Fayadh Alenezi2, Romany F. Mansour3,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3529-3544, 2022, DOI:10.32604/cmc.2022.028981

    Abstract The recent advancements made in World Wide Web and social networking have eased the spread of fake news among people at a faster rate. At most of the times, the intention of fake news is to misinform the people and make manipulated societal insights. The spread of low-quality news in social networking sites has a negative influence upon people as well as the society. In order to overcome the ever-increasing dissemination of fake news, automated detection models are developed using Artificial Intelligence (AI) and Machine Learning (ML) methods. The latest advancements in Deep Learning (DL) models and complex Natural Language… More >

  • Open Access

    ARTICLE

    A Novel Metaheuristic Algorithm: The Team Competition and Cooperation Optimization Algorithm

    Tao Wu1, Xinyu Wu1, Jingjue Chen1, Xi Chen2,*, Amir Homayoon Ashrafzadeh3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2879-2896, 2022, DOI:10.32604/cmc.2022.028942

    Abstract Metaheuristic algorithm is a generalization of heuristic algorithm that can be applied to almost all optimization problems. For optimization problems, metaheuristic algorithm is one of the methods to find its optimal solution or approximate solution under limited conditions. Most of the existing metaheuristic algorithms are designed for serial systems. Meanwhile, existing algorithms still have a lot of room for improvement in convergence speed, robustness, and performance. To address these issues, this paper proposes an easily parallelizable metaheuristic optimization algorithm called team competition and cooperation optimization (TCCO) inspired by the process of human team cooperation and competition. The proposed algorithm attempts… More >

  • Open Access

    ARTICLE

    Efficient Segmentation Approach for Different Medical Image Modalities

    Walid El-Shafai1,2, Amira A. Mahmoud1, El-Sayed M. El-Rabaie1, Taha E. Taha1, Osama F. Zahran1, Adel S. El-Fishawy1, Naglaa F. Soliman3, Amel A. Alhussan4,*, Fathi E. Abd El-Samie1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3119-3135, 2022, DOI:10.32604/cmc.2022.028935

    Abstract This paper presents a study of the segmentation of medical images. The paper provides a solid introduction to image enhancement along with image segmentation fundamentals. In the first step, the morphological operations are employed to ensure image detail protection and noise-immunity. The objective of using morphological operations is to remove the defects in the texture of the image. Secondly, the Fuzzy C-Means (FCM) clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster centers. The proposed technique is very simple to implement and significantly… More >

  • Open Access

    ARTICLE

    Criss-Cross Attentional Siamese Networks for Object Tracking

    Zhangdong Wang1, Jiaohua Qin1,*, Xuyu Xiang1, Yun Tan1, Neal N. Xiong2

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2931-2946, 2022, DOI:10.32604/cmc.2022.028896

    Abstract Visual object tracking is a hot topic in recent years. In the meanwhile, Siamese networks have attracted extensive attention in this field because of its balanced precision and speed. However, most of the Siamese network methods can only distinguish foreground from the non-semantic background. The fine-tuning and retraining of fully-convolutional Siamese networks for object tracking(SiamFC) can achieve higher precision under interferences, but the tracking accuracy is still not ideal, especially in the environment with more target interferences, dim light, and shadows. In this paper, we propose criss-cross attentional Siamese networks for object tracking (SiamCC). To solve the imbalance between foreground… More >

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