Mesfer Al Duhayyim¹, Fahd N. Al-Wesabi², Radwa Marzouk³, Manar Ahmed Hamza⁴, Anwer Mustafa Hilal^4,*, Majdy M. Eltahir²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1443-1457, 2022, DOI:10.32604/cmc.2022.021873

Abstract Latest advancements made in the processing abilities of smart devices have resulted in the designing of Intelligent Internet of Things (IoT) environment. This advanced environment enables the nodes to connect, collect, perceive, and examine useful data from its surroundings. Wireless Multimedia Surveillance Networks (WMSNs) form a vital part in IoT-assisted environment since it contains visual sensors that examine the surroundings from a number of overlapping views by capturing the images incessantly. Since IoT devices generate a massive quantity of digital media, it is therefore required to save the media, especially images, in a secure way. In order to achieve security,… More >

Afiya Kiran¹, Ahmad Karim^2,*, Yasser Obaid Alharbi³, Diaa Mohammed Uliyan³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 183-197, 2022, DOI:10.32604/cmc.2022.021860

Abstract Wireless Sensor Networks (WSNs) can be termed as an auto-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and motion etc. WSNs may comprise thousands of Internet of Things (IoT) devices to sense and collect data from its surrounding, process the data and take an automated and mechanized decision. On the other side the proliferation of these devices will soon cause radio spectrum shortage. So, to facilitate these networks, we integrate Cognitive Radio (CR) functionality in these networks. CR can sense the unutilized spectrum of licensed users and then use these empty… More >

R. Joshua Samuel Raj¹, M. Varalatchoumy², V. L. Helen Josephine³, A. Jegatheesan⁴, Seifedine Kadry⁵, Maytham N. Meqdad⁶, Yunyoung Nam^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1095-1109, 2022, DOI:10.32604/cmc.2022.021859

Abstract Internet of Things (IoT) is transforming the technical setting of conventional systems and finds applicability in smart cities, smart healthcare, smart industry, etc. In addition, the application areas relating to the IoT enabled models are resource-limited and necessitate crisp responses, low latencies, and high bandwidth, which are beyond their abilities. Cloud computing (CC) is treated as a resource-rich solution to the above mentioned challenges. But the intrinsic high latency of CC makes it nonviable. The longer latency degrades the outcome of IoT based smart systems. CC is an emergent dispersed, inexpensive computing pattern with massive assembly of heterogeneous autonomous systems.… More >

Talha Imtiaz Baig^1,*, Yaser Daanial Khan¹, Talha Mahboob Alam², Bharat Biswal³, Hanan Aljuaid⁴, Durdana Qaiser Gillani⁵

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 215-230, 2022, DOI:10.32604/cmc.2022.021849

Abstract Lysine Lipoylation is a protective and conserved Post Translational Modification (PTM) in proteomics research like prokaryotes and eukaryotes. It is connected with many biological processes and closely linked with many metabolic diseases. To develop a perfect and accurate classification model for identifying lipoylation sites at the protein level, the computational methods and several other factors play a key role in this purpose. Usually, most of the techniques and different traditional experimental models have a very high cost. They are time-consuming; so, it is required to construct a predictor model to extract lysine lipoylation sites. This study proposes a model that… More >

Imran Khan¹, Fahd N. Al-Wesabi², Marwa Obayya³, Anwer Mustafa Hilal⁴, Manar Ahmed Hamza⁴, Mohammed Rizwanullah⁴, Fahad Ahmed Al-Zahrani⁵, Hirofumi Amano⁶, Samih M. Mostafa^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 697-715, 2022, DOI:10.32604/cmc.2022.021847

Abstract With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU’ service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the spectrum utilization. Spectrum sensing… More >

Alaa A. El-Demerdash, Sherif E. Hussein, John FW Zaki^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 941-959, 2022, DOI:10.32604/cmc.2022.021839

Abstract Sentiment analysis attracts the attention of Egyptian Decision-makers in the education sector. It offers a viable method to assess education quality services based on the students’ feedback as well as that provides an understanding of their needs. As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels, this research uses a dataset for tweets' sentiments to assess a few machine learning techniques. After dataset preprocessing to remove symbols, necessary stemming and lemmatization is performed for features extraction. This is followed by several machine learning techniques and a proposed Long Short-Term Memory… More >

Wei Pei¹, Yan Li¹, Siuly Siuly^1,*, Peng Wen²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 889-905, 2022, DOI:10.32604/cmc.2022.021830

Abstract Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases. This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography (EEG), electrocardiogram (ECG), electromyogram (EMG), and electrooculogram (EOG). Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods. Traditional hand-crafted feature extraction methods choose features manually from raw data, which is tedious, and these features are limited in their ability to balance efficiency and accuracy. Moreover, most of the existing works on sleep staging are either single… More >

Nipun Chhabra^*, Manju Bala, Vrajesh Sharma

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2019-2035, 2022, DOI:10.32604/cmc.2022.021797

Abstract Cloud computing technology is the culmination of technical advancements in computer networks, hardware and software capabilities that collectively gave rise to computing as a utility. It offers a plethora of utilities to its clients worldwide in a very cost-effective way and this feature is enticing users/companies to migrate their infrastructure to cloud platform. Swayed by its gigantic capacity and easy access clients are uploading replicated data on cloud resulting in an unnecessary crunch of storage in datacenters. Many data compression techniques came to rescue but none could serve the purpose for the capacity as large as a cloud, hence, researches… More >

Manoj Kumar^*, Suman

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1641-1660, 2022, DOI:10.32604/cmc.2022.021793

Abstract Cloud computing has gained widespread popularity over the last decade. Scheduling problem in cloud computing is prejudiced due to enormous demands of cloud users. Meta-heuristic techniques in cloud computing have exhibited high performance in comparison to traditional scheduling algorithms. This paper presents a novel hybrid Nesterov Accelerated Gradient-based Cuckoo Search Algorithm (NAGCSA) to address the scheduling issue in cloud computing. Nesterov Accelerated Gradient can address trapping at local minima in CSA by updating the position using future approximation. The local search in the proposed algorithm is performed by using Nesterov Accelerated Gradient, while the global search is performed by using… More >

P. Suresh^1,*, R. H. Aswathy¹, Sridevi Arumugam², Amani Abdulrahman Albraikan³, Fahd N. Al-Wesabi⁴, Anwer Mustafa Hilal⁵, Mohammad Alamgeer⁶

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1713-1728, 2022, DOI:10.32604/cmc.2022.021789

Abstract In India, water wastage in agricultural fields becomes a challenging issue and it is needed to minimize the loss of water in the irrigation process. Since the conventional irrigation system needs massive quantity of water utilization, a smart irrigation system can be designed with the help of recent technologies such as machine learning (ML) and the Internet of Things (IoT). With this motivation, this paper designs a novel IoT enabled deep learning enabled smart irrigation system (IoTDL-SIS) technique. The goal of the IoTDL-SIS technique focuses on the design of smart irrigation techniques for effectual water utilization with less human interventions.… More >