Ali E. Takieldeen¹, El-Sayed M. El-kenawy^1,2, Mohammed Hadwan^3,4,5,*, Rokaia M. Zaki^6,7

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1465-1481, 2022, DOI:10.32604/cmc.2022.026026 - 24 February 2022

Abstract Dipper throated optimization (DTO) algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird. DTO has its unique hunting technique by performing rapid bowing movements. To show the efficiency of the proposed algorithm, DTO is tested and compared to the algorithms of Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Genetic Algorithm (GA) based on the seven unimodal benchmark functions. Then, ANOVA and Wilcoxon rank-sum tests are performed to confirm the effectiveness of the DTO compared to other optimization techniques. Additionally, to demonstrate the proposed More >

Manar Ahmed Hamza^1,*, 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 - 24 February 2022

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… More >

Souad Larabi-Marie-Sainte¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Amani Abdulrahman Albraikan⁵, Manar Ahmed Hamza^6,*, Abdelwahed Motwakel⁶, Ishfaq Yaseen⁶, Mesfer Al Duhayyim⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1293-1308, 2022, DOI:10.32604/cmc.2022.024585 - 24 February 2022

Abstract Snake Robots (SR) have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments, a characteristic not found in other kinds of robots (like wheeled or legged robots). Underwater Snake Robots (USR) establish a bioinspired solution in the domain of underwater robotics. It is a key challenge to increase the motion efficiency in underwater robots, with respect to forwarding speed, by enhancing the locomotion method. At the same time, energy efficiency is also considered as a crucial issue for long-term automation of the systems. In this aspect,… More >

Amani Abdulrahman Albraikan¹, Siwar Ben Haj Hassine², Suliman Mohamed Fati³, Fahd N. Al-Wesabi^2,4, Anwer Mustafa Hilal^5,*, Abdelwahed Motwakel⁵, Manar Ahmed Hamza⁵, Mesfer Al Duhayyim⁶

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 907-923, 2022, DOI:10.32604/cmc.2022.024488 - 24 February 2022

Abstract Cyberbullying (CB) is a distressing online behavior that disturbs mental health significantly. Earlier studies have employed statistical and Machine Learning (ML) techniques for CB detection. With this motivation, the current paper presents an Optimal Deep Learning-based Cyberbullying Detection and Classification (ODL-CDC) technique for CB detection in social networks. The proposed ODL-CDC technique involves different processes such as pre-processing, prediction, and hyperparameter optimization. In addition, GloVe approach is employed in the generation of word embedding. Besides, the pre-processed data is fed into Bidirectional Gated Recurrent Neural Network (BiGRNN) model for prediction. Moreover, hyperparameter tuning of BiGRNN More >

Mesfer Al Duhayyim¹, Majdy M. Eltahir², Imène Issaoui³, Fahd N. Al-Wesabi^2,4, Anwer Mustafa Hilal⁵, Fuad Ali Mohammed Al-Yarimi², Manar Ahmed Hamza^5,*, Abu Sarwar Zamani⁵

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 181-195, 2022, DOI:10.32604/cmc.2022.024206 - 24 February 2022

Abstract The grid environment is a dynamic, heterogeneous, and changeable computing system that distributes various services amongst different clients. To attain the benefits of collaborative resource sharing in Grid computing, a novel and proficient grid resource management system (RMS) is essential. Therefore, detection of an appropriate resource for the presented task is a difficult task. Several scientists have presented algorithms for mapping tasks to the resource. Few of them focus on fault tolerance, user fulfillment, and load balancing. With this motivation, this study designs an intelligent grid scheduling scheme using deer hunting optimization algorithm (DHOA), called More >

S. Manikandan^1,*, B. Nagaraj²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 761-775, 2022, DOI:10.32604/iasc.2022.023398 - 08 February 2022

Abstract Weather forecasting is primarily related to the prediction of weather conditions that becomes highly important in diverse applications like drought discovery, severe weather forecast, climate monitoring, agriculture, aviation, telecommunication, etc. Data-driven computer modelling with Artificial Neural Networks (ANN) can be used to solve non-linear problems. Presently, Deep Learning (DL) based weather forecasting models can be designed to accomplish reasonable predictive performance. In this aspect, this study presents a Hyper Parameter Tuned Bidirectional Gated Recurrent Neural Network (HPT-BiGRNN) technique for weather forecasting. The HPT-BiGRNN technique aims to utilize the past weather data for training the BiGRNN… More >

Mahmoud Ragab^1,2,3,*, Khalid Eljaaly⁴, Maha Farouk S. Sabir⁵, Ehab Bahaudien Ashary⁶, S. M. Abo-Dahab^7,8, E. M. Khalil^3,9

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658 - 14 January 2022

Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier… More >

Mohammed Hadwan^1,2,3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5545-5559, 2022, DOI:10.32604/cmc.2022.024512 - 14 January 2022

Abstract A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in… More >

Ahmed S. Almasoud¹, Siwar Ben Haj Hassine², Nadhem NEMRI², Fahd N. Al-Wesabi^2,3, Manar Ahmed Hamza^4,*, Anwer Mustafa Hilal⁴, Abdelwahed Motwakel⁴, Mesfer Al Duhayyim⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5311-5325, 2022, DOI:10.32604/cmc.2022.024500 - 14 January 2022

Abstract The sixth-generation (6G) wireless communication networks are anticipated in integrating aerial, terrestrial, and maritime communication into a robust system to accomplish trustworthy, quick, and low latency needs. It enables to achieve maximum throughput and delay for several applications. Besides, the evolution of 6G leads to the design of unmanned aerial vehicles (UAVs) in providing inexpensive and effective solutions in various application areas such as healthcare, environment monitoring, and so on. In the UAV network, effective data collection with restricted energy capacity poses a major issue to achieving high quality network communication. It can be addressed… More >

Esam A. AlQaralleh¹, Halah Nassif², Bassam A. Y. Alqaralleh^2,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5477-5490, 2022, DOI:10.32604/cmc.2022.024364 - 14 January 2022

Abstract Tongue diagnosis is a novel and non-invasive approach commonly employed to carry out the supplementary diagnosis over the globe. Recently, several deep learning (DL) based tongue color image analysis models have existed in the literature for the effective detection of diseases. This paper presents a fusion of handcrafted with deep features based tongue color image analysis (FHDF-TCIA) technique to biomedical applications. The proposed FDHF-TCIA technique aims to investigate the tongue images using fusion model, and thereby determines the existence of disease. Primarily, the FHDF-TCIA technique comprises Gaussian filtering based preprocessing to eradicate the noise. The More >