Harsh Goud¹, Prakash Chandra Sharma², Kashif Nisar^3,7,*, Muhammad Reazul Haque⁴, Ag. Asri Ag. Ibrahim³, Narendra Singh Yadav², Pankaj Swarnkar⁵, Manoj Gupta⁶, Laxmi Chand⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3481-3492, 2022, DOI:10.32604/cmc.2022.019764

Abstract Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set… More >

S. Vimal¹, S. Nalini^2,*, K. Anguraj³, T. Chelladurai⁴

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1907-1921, 2022, DOI:10.32604/iasc.2022.025219

Abstract Recent advancements in hardware and networking technologies have resulted in a large growth in the number of Internet of Things (IoT) devices connected to the Internet, which is likely to continue growing in the coming years. Traditional security solutions are insufficiently suited to the IoT context due to the restrictions and diversity of the resources available to objects. Security techniques such as intrusion detection and authentication are considered to be effective. Additionally, the decentralised and distributed nature of Blockchain technology makes it an excellent solution for overcoming the security issue. This paper proposes a chaotic bird swarm algorithm (CBSA)-based clustering… More >

M. Anuradha^1,*, G. Mani², T. Shanthi³, N. R. Nagarajan⁴, P. Suresh⁵, C. Bharatiraja⁶

Computer Systems Science and Engineering, Vol.43, No.1, pp. 381-396, 2022, DOI:10.32604/csse.2022.023321

Abstract In the digital area, Internet of Things (IoT) and connected objects generate a huge quantity of data traffic which feeds big data analytic models to discover hidden patterns and detect abnormal traffic. Though IoT networks are popular and widely employed in real world applications, security in IoT networks remains a challenging problem. Conventional intrusion detection systems (IDS) cannot be employed in IoT networks owing to the limitations in resources and complexity. Therefore, this paper concentrates on the design of intelligent metaheuristic optimization based feature selection with deep learning (IMFSDL) based classification model, called IMFSDL-IDS for IoT networks. The proposed IMFSDL-IDS… 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

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 >

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

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 model is carried out with… 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

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 IGSS-DHOA which schedules in such… More >

S. Manikandan^1,*, B. Nagaraj²

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

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 model and achieve the effective… 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

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 results or machine learning (ML)… 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

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 by the use of clustering… 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

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 proposed FHDF-TCIA model encompasses a… More >