Medhat A. Tawfeek^1,2,*, Saad Alanazi¹, A. A. Abd El-Aziz^3,4

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6091-6106, 2022, DOI:10.32604/cmc.2022.028391

Abstract The alignment operation between many protein sequences or DNA sequences related to the scientific bioinformatics application is very complex. There is a trade-off in the objectives in the existing techniques of Multiple Sequence Alignment (MSA). The techniques that concern with speed ignore accuracy, whereas techniques that concern with accuracy ignore speed. The term alignment means to get the similarity in different sequences with high accuracy. The more growing number of sequences leads to a very complex and complicated problem. Because of the emergence; rapid development; and dependence on gene sequencing, sequence alignment has become important in every biological relationship analysis… More >

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 >

Farhan Amin, Seong Oun Hwang^*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5871-5888, 2022, DOI:10.32604/cmc.2022.028342

Abstract The social internet of things (SIoT) is one of the emerging paradigms that was proposed to solve the problems of network service discovery, navigability, and service composition. The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings. In IoT, an object can offer multiple services and different objects can offer the same services with different parameters and interest factors. The proliferation of offered services led to difficulties during service customization and service filtering. This problem is known as service explosion. The selection of suitable service that fits the requirements… More >

Md. Maniruzzaman¹, Jungpil Shin^1,*, Md. Al Mehedi Hasan¹, Akira Yasumura²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5179-5195, 2022, DOI:10.32604/cmc.2022.028339

Abstract Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric and neurobehavioral disorders in children, affecting 11% of children worldwide. This study aimed to propose a machine learning (ML)-based algorithm for discriminating ADHD from healthy children using their electroencephalography (EEG) signals. The study included 61 children with ADHD and 60 healthy children aged 7–12 years. Different morphological and time-domain features were extracted from EEG signals. The t-test (p-value < 0.05) and least absolute shrinkage and selection operator (LASSO) were used to select potential features of children with ADHD and enhance the classification accuracy. The selected potential features were… More >

Kamal ElDahshan¹, Eman Selim², Ahmed Ismail Ebada², Mohamed Abouhawwash^3,4, Yunyoung Nam^5,*, Gamal Behery²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5149-5164, 2022, DOI:10.32604/cmc.2022.028326

Abstract Currently, relational database management systems (RDBMSs) face different challenges in application development due to the massive growth of unstructured and semi-structured data. This introduced new DBMS categories, known as not only structured query language (NoSQL) DBMSs, which do not adhere to the relational model. The migration from relational databases to NoSQL databases is challenging due to the data complexity. This study aims to enhance the storage performance of RDBMSs in handling a variety of data. The paper presents two approaches. The first approach proposes a convenient representation of unstructured data storage. Several extensive experiments were implemented to assess the efficiency… More >

Huanrong Tang¹, Changlin Hu¹, Tianming Liu², Jianquan Ouyang^1,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5395-5413, 2022, DOI:10.32604/cmc.2022.028284

Abstract In response to problems in the centralized storage of personal resumes on third-party recruitment platforms, such as inadequate privacy protection, inability of individuals to accurately authorize downloads, and inability to determine who downloaded the resume and when, this study proposes a blockchain-based framework for secure storage and sharing of resumes. Users can employ an authorized access mechanism to protect their privacy rights. The proposed framework uses smart contracts, interplanetary file system, symmetric encryption, and digital signatures to protect, verify, and share resumes. Encryption keys are split and stored in multiple depositories through secret-sharing technology to improve the security of these… More >

Muhammad Akram¹, Muhammad Waseem Iqbal^2,*, Syed Ashraf Ali³, Muhammad Usman Ashraf⁴, Khalid Alsubhi⁵, Hani Moaiteq Aljahdali⁶

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6061-6077, 2022, DOI:10.32604/cmc.2022.028272

Abstract In cipher algorithms, the encryption and decryption are based on the same key. There are some limitations in cipher algorithms, for example in polyalphabetic substitution cipher the key size must be equal to plaintext otherwise it will be repeated and if the key is known then encryption becomes useless. This paper aims to improve the said limitations by designing of Triple key security algorithm (TKS) in which the key is modified on polyalphabetic substitution cipher to maintain the size of the key and plaintext. Each plaintext character is substituted by an alternative message. The mode of substitution is transformed cyclically… More >

Rania M Tawfik¹, Hazem A. A. Nomer², M. Saeed Darweesh^1,*, Ali Wagdy Mohamed^3,4, Hassan Mostafa^5,6

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5999-6013, 2022, DOI:10.32604/cmc.2022.028234

Abstract Unmanned Aerial Vehicles (UAVs) provide a reliable and energy-efficient solution for data collection from the Narrowband Internet of Things (NB-IoT) devices. However, the UAV’s deployment optimization, including locations of the UAV’s stop points, is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection efficiently. In this regard, this paper proposes Gaining-Sharing Knowledge (GSK) algorithm for optimizing the UAV’s deployment. In GSK, the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire deployment. The superiority of… More >

Shaher Alshammrei¹, Sahbi Boubaker^2,*, Lioua Kolsi^1,3

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5939-5954, 2022, DOI:10.32604/cmc.2022.028165

Abstract Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots (MRs) in both research and education. In this paper, an optimal collision-free algorithm is designed and implemented practically based on an improved Dijkstra algorithm. To achieve this research objectives, first, the MR obstacle-free environment is modeled as a diagraph including nodes, edges and weights. Second, Dijkstra algorithm is used offline to generate the shortest path driving the MR from a starting point to a target point. During its movement, the robot should follow the previously obtained path and stop at each node to test if there… More >

Heewon Chung, Jinseok Lee^*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5607-5628, 2022, DOI:10.32604/cmc.2022.028154

Abstract For the classification problem in practice, one of the challenging issues is to obtain enough labeled data for training. Moreover, even if such labeled data has been sufficiently accumulated, most datasets often exhibit long-tailed distribution with heavy class imbalance, which results in a biased model towards a majority class. To alleviate such class imbalance, semi-supervised learning methods using additional unlabeled data have been considered. However, as a matter of course, the accuracy is much lower than that from supervised learning. In this study, under the assumption that additional unlabeled data is available, we propose the iterative semi-supervised learning algorithms, which… More >