Parul Gandhi¹, Mohammad Zubair Khan², Ravi Kumar Sharma³, Omar H. Alhazmi², Surbhi Bhatia^4,*, Chinmay Chakraborty⁵

Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943 - 10 November 2021

Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software… More >

Dong Wang^1,*, Siwei Chen¹, Weigong Zhang¹, Danjie Du²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1837-1848, 2022, DOI:10.32604/cmc.2022.023033 - 03 November 2021

Abstract It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance, and that may cause serious accidents. Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation, how to make an effective early warning of rollover is still unsolved in practice. The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining. The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude… More >

Chih-Ta Yen^1,*, Cheng-Hong Liao²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679 - 03 November 2021

Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of More >

Ladathunya Pumkaew, Monthippa Uthansakul^*, Peerapong Uthansakul

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1547-1566, 2022, DOI:10.32604/cmc.2022.022556 - 03 November 2021

Abstract Nowadays, Visible Light Communication (VLC) is an attractive alternative technology for wireless communication because it can use some simple Light Emitting Diodes (LEDs) instead of antennas. Typically, indoor VLC is designed to transmit only one dataset through multiple LED beams at a time. As a result, the number of users per unit of time (throughput) is relatively low. Therefore, this paper proposes the design of an indoor VLC system using switched-beam technique through computer simulation. The LED lamps are designed to be arranged in a circular array and the signal can be transmitted through the… More >

Sang-Hyun Lee^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1987-1998, 2022, DOI:10.32604/cmc.2022.022554 - 03 November 2021

Abstract Currently, there are many limitations to classify images of small objects. In addition, there are limitations such as error detection due to external factors, and there is also a disadvantage that it is difficult to accurately distinguish between various objects. This paper uses a convolutional neural network (CNN) algorithm to recognize and classify object images of very small moths and obtain precise data images. A convolution neural network algorithm is used for image data classification, and the classified image is transformed into image data to learn the topological structure of the image. To improve the More >

Qaisar Abbas^1,*, Mostafa E.A. Ibrahim^1,2, Shakir Khan¹, Abdul Rauf Baig¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1999-2007, 2022, DOI:10.32604/cmc.2022.022553 - 03 November 2021

Abstract Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features. The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions. To get enhanced visual facial features in uncontrolled environment, three cameras are deployed on multiview points… More >

E. Ahila Devi¹, K. C. Ramya², K. Sathesh Kumar³, Sultan Ahmad⁴, Seifedine Kadry⁵, Hyung Ju Park⁶, Byeong-Gwon Kang^6,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1567-1580, 2022, DOI:10.32604/cmc.2022.022539 - 03 November 2021

Abstract A mobile ad hoc network (MANET) involves a group of wireless mobile nodes which create an impermanent network with no central authority and infrastructure. The nodes in the MANET are highly mobile and it results in adequate network topology, link loss, and increase the re-initialization of the route discovery process. Route planning in MANET is a multi-hop communication process due to the restricted transmission range of the nodes. Location aided routing (LAR) is one of the effective routing protocols in MANET which suffers from the issue of high energy consumption. Though few research works have… More >

Wafaa Alsaggaf^1,*, Felwa Abukhodair¹, Amani Tariq Jamal², Sayed Abdel-Khalek³, Romany F. Mansour⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1189-1203, 2022, DOI:10.32604/cmc.2022.022469 - 03 November 2021

Abstract In recent days, advancements in the Internet of Things (IoT) and cloud computing (CC) technologies have emerged in different application areas, particularly healthcare. The use of IoT devices in healthcare sector often generates large amount of data and also spent maximum energy for data transmission to the cloud server. Therefore, energy efficient clustering mechanism is needed to effectively reduce the energy consumption of IoT devices. At the same time, the advent of deep learning (DL) models helps to analyze the healthcare data in the cloud server for decision making. With this motivation, this paper presents… More >

Samah Ibrahim Alshathri^1,*, Desiree Juby Vincent², V. S. Hari²

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1371-1386, 2022, DOI:10.32604/cmc.2022.022458 - 03 November 2021

Abstract Invoice document digitization is crucial for efficient management in industries. The scanned invoice image is often noisy due to various reasons. This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method. A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network. In order to capture the most salient features of training samples, a undercomplete autoencoder is designed with non-linear encoder and decoder function. This autoencoder is regularized for… More >

Izzat Al-Darraji^1,2, Ayad A. Kakei², Ayad Ghany Ismaeel³, Georgios Tsaramirsis⁴, Fazal Qudus Khan⁵, Princy Randhawa⁶, Muath Alrammal⁴, Sadeeq Jan^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1011-1024, 2022, DOI:10.32604/cmc.2022.022451 - 03 November 2021

Abstract Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part. To address these issues, the Linear Matrix Inequalities (LMIs) and Parallel Distributed Compensation (PDC) approaches are implemented in the Takagy–Sugeno Fuzzy Model (T-SFM). We propose the following methodology; initially, the state space equations of the nonlinear manipulator model are derived. Next, a Takagy–Sugeno Fuzzy Model (T-SFM) technique is used for linearizing the state space More >