Anabi Hilary Kelechi¹, Mohammed H. Alsharif², Anya Chukwudi-eke Anya³, Mathias U. Bonet¹, Samson Aiyudubie Uyi¹, Peerapong Uthansakul^4,*, Jamel Nebhen⁵, Ayman A. Aly⁶

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2405-2424, 2021, DOI:10.32604/cmc.2021.018686

Abstract Water is one of the needs with remarkable significance to man and other living things. Water quality management is a concept based on the continuous monitoring of water quality. The monitoring scheme aims to accumulate data to make decisions on water resource descriptions, identify real and emergent issues involving water pollution, formulate priorities, and plan for water quality management. The regularly considered parameters when conducting water quality monitoring are turbidity, pH, temperature, conductivity, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, ammonia, and metal ions. The usual method employed in capturing these water parameters is the manual collection and sending… More >

Mohamed Esmail Karar^1,2, Omar Reyad^1,3, Mohammed Abd-Elnaby⁴, Abdel-Haleem Abdel-Aty^5,6, Marwa Ahmed Shouman^7,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2295-2312, 2021, DOI:10.32604/cmc.2021.018671

Abstract Lightweight deep convolutional neural networks (CNNs) present a good solution to achieve fast and accurate image-guided diagnostic procedures of COVID-19 patients. Recently, advantages of portable Ultrasound (US) imaging such as simplicity and safe procedures have attracted many radiologists for scanning suspected COVID-19 cases. In this paper, a new framework of lightweight deep learning classifiers, namely COVID-LWNet is proposed to identify COVID-19 and pneumonia abnormalities in US images. Compared to traditional deep learning models, lightweight CNNs showed significant performance of real-time vision applications by using mobile devices with limited hardware resources. Four main lightweight deep learning models, namely MobileNets, ShuffleNets, MENet… More >

Dah-Jing Jwo^*, Ming-Hsuan Lee

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2387-2403, 2021, DOI:10.32604/cmc.2021.018670

Abstract In this paper, the integrity monitoring algorithm based on a Kalman filter (KF) based rate detector is employed in the vector tracking loop (VTL) of the Global Positioning System (GPS) receiver. In the VTL approach, the extended Kalman filter (EKF) simultaneously tracks the received signals and estimates the receiver’s position, velocity, etc. In contrast to the scalar tracking loop (STL) that uses the independent parallel tracking loop approach, the VTL technique uses the correlation of each satellite signal and user dynamics and thus reduces the risk of loss lock of signals. Although the VTL scheme provides several important advantages, the… More >

Fahd N. Al-Wesabi^1,2,*, Murad A. Almekhlafi³, Mohammed Abdullah Al-Hagery⁴, Mohammad Alamgeer⁵, Khalid Mahmood⁵, Majdy M. Eltahir⁵, Ali M. Al-Sharafi^2,6, Amin M. El-Kustaban⁷

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1995-2011, 2021, DOI:10.32604/cmc.2021.018644

Abstract Renewable energy is one of the essential elements of the social and economic development in any civilized country. The use of fossil fuels and the non-renewable form of energy has many adverse effects on the most of ecosystems. Given the high potential of renewable energy sources in Yemen and the absence of similar studies in the region, this study aimed to examine the wind energy potential of Hodeidah-Yemen Republic by analyzing wind characteristics and assessment, determining the available power density, and calculate the wind energy extracted at different heights. The average wind speed of Hodeidah was obtained only for the… More >

R. Sowmyalakshmi^1,*, Mohamed Ibrahim Waly², Mohamed Yacin Sikkandar², T. Jayasankar¹, Sayed Sayeed Ahmad³, Rashmi Rani³, Suresh Chavhan^4,5

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2245-2260, 2021, DOI:10.32604/cmc.2021.018636

Abstract In the recent years, microarray technology gained attention for concurrent monitoring of numerous microarray images. It remains a major challenge to process, store and transmit such huge volumes of microarray images. So, image compression techniques are used in the reduction of number of bits so that it can be stored and the images can be shared easily. Various techniques have been proposed in the past with applications in different domains. The current research paper presents a novel image compression technique i.e., optimized Linde–Buzo–Gray (OLBG) with Lempel Ziv Markov Algorithm (LZMA) coding technique called OLBG-LZMA for compressing microarray images without any… More >

Qian Sun^1,2, Gongxue Cheng^1,2, Xiaoyi Wang^1,2,*, Jiping Xu^1,2, Li Wang^1,2, Huiyan Zhang^1,2, Jiabin Yu^1,2, Ning Cao³, Ruichao Wang⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2749-2759, 2021, DOI:10.32604/cmc.2021.018633

Abstract Water quality sensor networks are widely used in water resource monitoring. However, due to the fact that the energy of these networks cannot be supplemented in time, it is necessary to study effective routing protocols to extend their lifecycle. To address the problem of limited resources, a routing optimization algorithm based on a small-world network model is proposed. In this paper, a small-world network model is introduced for water quality sensor networks, in which the short average path and large clustering coefficient of the model are used to construct a super link. A short average path can reduce the network’s… More >

Ahsan Aziz¹, Muhammad Attique¹, Usman Tariq², Yunyoung Nam^3,*, Muhammad Nazir¹, Chang-Won Jeong⁴, Reham R. Mostafa⁵, Rasha H. Sakr⁶

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2653-2670, 2021, DOI:10.32604/cmc.2021.018606

Abstract Owing to technological developments, Medical image analysis has received considerable attention in the rapid detection and classification of diseases. The brain is an essential organ in humans. Brain tumors cause loss of memory, vision, and name. In 2020, approximately 18,020 deaths occurred due to brain tumors. These cases can be minimized if a brain tumor is diagnosed at a very early stage. Computer vision researchers have introduced several techniques for brain tumor detection and classification. However, owing to many factors, this is still a challenging task. These challenges relate to the tumor size, the shape of a tumor, location of… More >

Abdullah Muhammad, Salwani Abdullah, Nor Samsiah Sani^*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1783-1799, 2021, DOI:10.32604/cmc.2021.018593

Abstract Feature selection and sentiment analysis are two common studies that are currently being conducted; consistent with the advancements in computing and growing the use of social media. High dimensional or large feature sets is a key issue in sentiment analysis as it can decrease the accuracy of sentiment classification and make it difficult to obtain the optimal subset of the features. Furthermore, most reviews from social media carry a lot of noise and irrelevant information. Therefore, this study proposes a new text-feature selection method that uses a combination of rough set theory (RST) and teaching-learning based optimization (TLBO), which is… More >

Yong-Woon Hwang, Im-Yeong Lee^*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1747-1764, 2021, DOI:10.32604/cmc.2021.018549

Abstract Recently, with the advancement of Information and Communications Technology (ICT), Internet of Things (IoT) has been connected to the cloud and used in industrial sectors, medical environments, and smart grids. However, if data is transmitted in plain text when collecting data in an IoT-cloud environment, it can be exposed to various security threats such as replay attacks and data forgery. Thus, digital signatures are required. Data integrity is ensured when a user (or a device) transmits data using a signature. In addition, the concept of data aggregation is important to efficiently collect data transmitted from multiple users (or a devices)… More >

Buddhadeva Sahoo^1,*, Sangram Keshari Routray², Pravat Kumar Rout², Mohammed M. Alhaider³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1851-1875, 2021, DOI:10.32604/cmc.2021.018535

Abstract This paper suggests a combined novel control strategy for DFIG based wind power systems (WPS) under both nonlinear and unbalanced load conditions. The combined control approach is designed by coordinating the machine side converter (MSC) and the load side converter (LSC) control approaches. The proposed MSC control approach is designed by using a model predictive control (MPC) approach to generate appropriate real and reactive power. The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation. It shows its superiority by eliminating the requirement of transformation, switching table, and the PWM… More >