Majdy M. Eltahir¹, Ibrahim Abunadi², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal⁵, Adil Yousif⁶, Abdelwahed Motwakel⁵, Mesfer Al Duhayyim⁷, Manar Ahmed Hamza^5,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6257-6273, 2022, DOI:10.32604/cmc.2022.024312

Abstract Novel coronavirus 2019 (COVID-19) has affected the people's health, their lifestyle and economical status across the globe. The application of advanced Artificial Intelligence (AI) methods in combination with radiological imaging is useful in accurate detection of the disease. It also assists the physicians to take care of remote villages too. The current research paper proposes a novel automated COVID-19 analysis method with the help of Optimal Hybrid Feature Extraction (OHFE) and Optimal Deep Neural Network (ODNN) called OHFE-ODNN from chest x-ray images. The objective of the presented technique is for performing binary and multi-class classification of COVID-19 analysis from chest… More >

Rami Sameer Ahmad Al Kloub^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5151-5165, 2022, DOI:10.32604/cmc.2022.024309

Abstract Flood disasters can be reliably monitored using remote sensing photos with great spatiotemporal resolution. However, satellite revisit periods and extreme weather limit the use of high spatial resolution images. As a result, this research provides a method for combining Landsat and MODIS pictures to produce high spatiotemporal imagery for flood disaster monitoring. Using the spatial and temporal adaptive reflectance fusion model (STARFM), the spatial and temporal reflectance unmixing model (STRUM), and three prominent algorithms of flexible spatiotemporal data fusion (FSDAF), Landsat fusion images are created by fusing MODIS and Landsat images. Then, to extract flood information, utilize a support vector… More >

M. R. Sivagar^1,*, N. Prabakaran²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5765-5781, 2022, DOI:10.32604/cmc.2022.024273

Abstract In present scenario of wireless communications, Long Term Evolution (LTE) based network technology is evolved and provides consistent data delivery with high speed and minimal delay through mobile devices. The traffic management and effective utilization of network resources are the key factors of LTE models. Moreover, there are some major issues in LTE that are to be considered are effective load scheduling and traffic management. Through LTE is a depraved technology, it is been suffering from these issues. On addressing that, this paper develops an Elite Opposition based Spider Monkey Optimization Framework for Efficient Load Balancing (SMO-ELB). In this model,… More >

Riad Alharbey¹, Ameen Banjar¹, Yahia Said^2,3,*, Mohamed Atri⁴, Abdulrahman Alshdadi¹, Mohamed Abid⁵

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6275-6291, 2022, DOI:10.32604/cmc.2022.024272

Abstract Hajj and Umrah are two main religious duties for Muslims. To help faithfuls to perform their religious duties comfortably in overcrowded areas, a crowd management system is a must to control the entering and exiting for each place. Since the number of people is very high, an intelligent crowd management system can be developed to reduce human effort and accelerate the management process. In this work, we propose a crowd management process based on detecting, tracking, and counting human faces using Artificial Intelligence techniques. Human detection and counting will be performed to calculate the number of existing visitors and face… More >

Shariq Bashir^1,*, Owais Ahmed Malik², Daphne Teck Ching Lai²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6165-6181, 2022, DOI:10.32604/cmc.2022.024269

Abstract Traditional wireless sensor networks (WSNs) are not suitable for rough terrains that are difficult or impossible to access by humans. Smart dust is a technology that works with the combination of many tiny sensors which is highly useful for obtaining remote sensing information from rough terrains. The tiny sensors are sprinkled in large numbers on rough terrains using airborne distribution through drones or aircraft without manually setting their locations. Although it is clear that a number of remote sensing applications can benefit from this technology, but the small size of smart dust fundamentally restricts the integration of advanced hardware on… More >

Reya Sharma¹, Baijnath Kaushik¹, Naveen Kumar Gondhi¹, Muhammad Tahir^2,*, Mohammad Khalid Imam Rahmani²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5855-5873, 2022, DOI:10.32604/cmc.2022.024232

Abstract Even though several advances have been made in recent years, handwritten script recognition is still a challenging task in the pattern recognition domain. This field has gained much interest lately due to its diverse application potentials. Nowadays, different methods are available for automatic script recognition. Among most of the reported script recognition techniques, deep neural networks have achieved impressive results and outperformed the classical machine learning algorithms. However, the process of designing such networks right from scratch intuitively appears to incur a significant amount of trial and error, which renders them unfeasible. This approach often requires manual intervention with domain… More >

Mohammad Arifin Rahman Khan^1,*, Mohammed Golam Kaosar², Mohammad Shorfuzzaman³, Kire Jakimoski⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5491-5509, 2022, DOI:10.32604/cmc.2022.024212

Abstract There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets, smartphones, and laptops. The rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased demand. One solution to the problem is the emergence of fifth-generation (5G) wireless communication, which can address the challenges by offering very broad wireless area capacity and potential cut-power consumption. The application of small cells is the fundamental mechanism for the 5G… More >

Ahmed Hamza Osman^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6307-6331, 2022, DOI:10.32604/cmc.2022.024145

Abstract This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical applications. The proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chest X-ray images through Two Step-As clustering algorithm with rich filter families, abstraction and weight-sharing properties. In contrast to the generally used transformational learning approach, the proposed model was trained before and after clustering. The compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to each new group, with each… More >

Hyeji Roh, Sheungmin Oh, Hajun Song, Jinseo Han, Sangsoon Lim^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5717-5732, 2022, DOI:10.32604/cmc.2022.024135

Abstract With the development of the Internet of Things (IoT), diverse wireless devices are increasing rapidly. Those devices have different wireless interfaces that generate incompatible wireless signals. Each signal has its own physical characteristics with signal modulation and demodulation scheme. When there exist different wireless devices, they can suffer from severe Cross-Technology Interferences (CTI). To reduce the communication overhead due to the CTI in the real IoT environment, a central coordinator can be able to detect and identify wireless signals existing in the same communication areas. This paper investigates how to classify various radio signals using Convolutional Neural Networks (CNN), Long… More >

Muhammad Javid Iqbal^1,2, Ihsan Ullah^2,*, Muhammad Ali², Atiq Ahmed², Waheed Noor², Abdul Basit²

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5381-5397, 2022, DOI:10.32604/cmc.2022.024116

Abstract Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service providers. Since Internet was not designed for such services during its inception, such a service poses some serious challenges including cost and scalability. Peer-to-Peer (P2P) Internet Protocol Television (IPTV) is an application-level distributed paradigm to offer live video contents. In terms of ease of deployment, it has emerged as a serious alternative to client server, Content Delivery Network (CDN) and IP multicast solutions. Nevertheless, P2P approach has struggled to provide the desired streaming quality due to a number of… More >