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  • Open Access

    ARTICLE

    Detecting Driver Distraction Using Deep-Learning Approach

    Khalid A. AlShalfan1, Mohammed Zakariah2,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 689-704, 2021, DOI:10.32604/cmc.2021.015989

    Abstract Currently, distracted driving is among the most important causes of traffic accidents. Consequently, intelligent vehicle driving systems have become increasingly important. Recently, interest in driver-assistance systems that detect driver actions and help them drive safely has increased. In these studies, although some distinct data types, such as the physical conditions of the driver, audio and visual features, and vehicle information, are used, the primary data source is images of the driver that include the face, arms, and hands taken with a camera inside the car. In this study, an architecture based on a convolution neural network (CNN) is proposed to… More >

  • Open Access

    ARTICLE

    Ensemble Machine Learning Based Identification of Pediatric Epilepsy

    Shamsah Majed Alotaibi1, Atta-ur-Rahman1, Mohammed Imran Basheer1, Muhammad Adnan Khan2,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 149-165, 2021, DOI:10.32604/cmc.2021.015976

    Abstract Epilepsy is a type of brain disorder that causes recurrent seizures. It is the second most common neurological disease after Alzheimer’s. The effects of epilepsy in children are serious, since it causes a slower growth rate and a failure to develop certain skills. In the medical field, specialists record brain activity using an Electroencephalogram (EEG) to observe the epileptic seizures. The detection of these seizures is performed by specialists, but the results might not be accurate due to human errors; therefore, automated detection of epileptic pediatric seizures might be the optimal solution. This paper investigates the detection of epileptic seizures… More >

  • Open Access

    ARTICLE

    Genetic Algorithm Routing Protocol for Mobile Ad Hoc Network

    Raed Alsaqour1, Saif Kamal2, Maha Abdelhaq3,*, Yazan Al Jeroudi4

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 941-960, 2021, DOI:10.32604/cmc.2021.015921

    Abstract Mobile ad hoc network (MANET) is a dynamically reconfigurable wireless network with time-variable infrastructure. Given that nodes are highly mobile, MANET’s topology often changes. These changes increase the difficulty in finding the routes that the packets use when they are routed. This study proposes an algorithm called genetic algorithm-based location-aided routing (GALAR) to enhance the MANET routing protocol efficiency. The GALAR algorithm maintains an adaptive update of the node location information by adding the transmitting node location information to the routing packet and selecting the transmitting node to carry the packets to their destination. The GALAR was constructed based on… More >

  • Open Access

    ARTICLE

    Tamper Detection and Localization for Quranic Text Watermarking Scheme Based on Hybrid Technique

    Ali A. R. Alkhafaji*, Nilam Nur Amir Sjarif, M. A. Shahidan, Nurulhuda Firdaus Mohd Azmi, Haslina Md Sarkan, Suriayati Chuprat

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 77-102, 2021, DOI:10.32604/cmc.2021.015770

    Abstract The text of the Quran is principally dependent on the Arabic language. Therefore, improving the security and reliability of the Quran’s text when it is exchanged via internet networks has become one of the most difficult challenges that researchers face today. Consequently, the diacritical marks in the Holy Quran which represent Arabic vowels () known as the kashida (or “extended letters”) must be protected from changes. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR), and Normalized Cross-Correlation (NCC); thus, the location for tamper… More >

  • Open Access

    ARTICLE

    Deep Learning Multimodal for Unstructured and Semi-Structured Textual Documents Classification

    Nany Katamesh, Osama Abu-Elnasr*, Samir Elmougy

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 589-606, 2021, DOI:10.32604/cmc.2021.015761

    Abstract Due to the availability of a huge number of electronic text documents from a variety of sources representing unstructured and semi-structured information, the document classification task becomes an interesting area for controlling data behavior. This paper presents a document classification multimodal for categorizing textual semi-structured and unstructured documents. The multimodal implements several individual deep learning models such as Deep Neural Networks (DNN), Recurrent Convolutional Neural Networks (RCNN) and Bidirectional-LSTM (Bi-LSTM). The Stacked Ensemble based meta-model technique is used to combine the results of the individual classifiers to produce better results, compared to those reached by any of the above mentioned… More >

  • Open Access

    ARTICLE

    Hybrid Metamodeling/Metaheuristic Assisted Multi-Transmitters Placement Planning

    Amir Parnianifard1, Muhammad Saadi2, Manus Pengnoo1, Muhammad Ali Imran3, Sattam Al Otaibi4, Pruk Sasithong1, Pisit Vanichchanunt5, Tuchsanai Polysuwan6, Lunchakorn Wuttisittikulkij1,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 569-587, 2021, DOI:10.32604/cmc.2021.015730

    Abstract With every passing day, the demand for data traffic is increasing, and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently. Cell sizes are shrinking with every upcoming communication generation, which makes base station placement planning even more complex and cumbersome. In order to make the next-generation cost-effective, it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service. This paper aims at the development… More >

  • Open Access

    ARTICLE

    Numerical Solutions for Heat Transfer of An Unsteady Cavity with Viscous Heating

    H. F. Wong1,2, Muhammad Sohail3, Z. Siri1, N. F. M. Noor1,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 319-336, 2021, DOI:10.32604/cmc.2021.015710

    Abstract The mechanism of viscous heating of a Newtonian fluid filled inside a cavity under the effect of an external applied force on the top lid is evaluated numerically in this exploration. The investigation is carried out by assuming a two-dimensional laminar in-compressible fluid flow subject to Neumann boundary conditions throughout the numerical iterations in a transient analysis. All the walls of the square cavity are perfectly insulated and the top moving lid produces a constant finite heat flux even though the fluid flow attains the steady-state condition. The objective is to examine the effects of viscous heating in the fully… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Hybrid Intelligent Intrusion Detection System

    Muhammad Ashfaq Khan1,2, Yangwoo Kim1,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 671-687, 2021, DOI:10.32604/cmc.2021.015647

    Abstract Machine learning (ML) algorithms are often used to design effective intrusion detection (ID) systems for appropriate mitigation and effective detection of malicious cyber threats at the host and network levels. However, cybersecurity attacks are still increasing. An ID system can play a vital role in detecting such threats. Existing ID systems are unable to detect malicious threats, primarily because they adopt approaches that are based on traditional ML techniques, which are less concerned with the accurate classification and feature selection. Thus, developing an accurate and intelligent ID system is a priority. The main objective of this study was to develop… More >

  • Open Access

    ARTICLE

    Dealing with the Class Imbalance Problem in the Detection of Fake Job Descriptions

    Minh Thanh Vo1, Anh H. Vo2, Trang Nguyen3, Rohit Sharma4, Tuong Le2,5,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 521-535, 2021, DOI:10.32604/cmc.2021.015645

    Abstract In recent years, the detection of fake job descriptions has become increasingly necessary because social networking has changed the way people access burgeoning information in the internet age. Identifying fraud in job descriptions can help jobseekers to avoid many of the risks of job hunting. However, the problem of detecting fake job descriptions comes up against the problem of class imbalance when the number of genuine jobs exceeds the number of fake jobs. This causes a reduction in the predictability and performance of traditional machine learning models. We therefore present an efficient framework that uses an oversampling technique called FJD-OT… More >

  • Open Access

    ARTICLE

    An End-to-End Authentication Scheme for Healthcare IoT Systems Using WMSN

    Shadi Nashwan*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 607-642, 2021, DOI:10.32604/cmc.2021.015597

    Abstract The healthcare internet of things (IoT) system has dramatically reshaped this important industry sector. This system employs the latest technology of IoT and wireless medical sensor networks to support the reliable connection of patients and healthcare providers. The goal is the remote monitoring of a patient’s physiological data by physicians. Moreover, this system can reduce the number and expenses of healthcare centers, make up for the shortage of healthcare centers in remote areas, enable consultation with expert physicians around the world, and increase the health awareness of communities. The major challenges that affect the rapid deployment and widespread acceptance of… More >

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