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  • Open Access

    ARTICLE

    Intelligent Sign Language Recognition System for E-Learning Context

    Muhammad Jamil Hussain1, Ahmad Shaoor1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Tamara al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5327-5343, 2022, DOI:10.32604/cmc.2022.025953 - 21 April 2022

    Abstract In this research work, an efficient sign language recognition tool for e-learning has been proposed with a new type of feature set based on angle and lines. This feature set has the ability to increase the overall performance of machine learning algorithms in an efficient way. The hand gesture recognition based on these features has been implemented for usage in real-time. The feature set used hand landmarks, which were generated using media-pipe (MediaPipe) and open computer vision (openCV) on each frame of the incoming video. The overall algorithm has been tested on two well-known ASL-alphabet More >

  • Open Access

    ARTICLE

    Self-Care Assessment for Daily Living Using Machine Learning Mechanism

    Mouazma Batool1, Yazeed Yasin Ghadi2, Suliman A. Alsuhibany3, Tamara al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1747-1764, 2022, DOI:10.32604/cmc.2022.025112 - 24 February 2022

    Abstract Nowadays, activities of daily living (ADL) recognition system has been considered an important field of computer vision. Wearable and optical sensors are widely used to assess the daily living activities in healthy people and people with certain disorders. Although conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth (distance information) and visual cues has greatly enhanced the performance of activity recognition. In this paper, an RGB-D-based ADL recognition system has been presented. Initially, human silhouette has been extracted from the noisy background of RGB and depth images to track More >

  • Open Access

    ARTICLE

    Malware Detection Using Decision Tree Based SVM Classifier for IoT

    Anwer Mustafa Hilal1,*, Siwar Ben Haj Hassine2, Souad Larabi-Marie-Sainte3, Nadhem Nemri2, Mohamed K. Nour4, Abdelwahed Motwakel1, Abu Sarwar Zamani1, Mesfer Al Duhayyim5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 713-726, 2022, DOI:10.32604/cmc.2022.024501 - 24 February 2022

    Abstract The development in Information and Communication Technology has led to the evolution of new computing and communication environment. Technological revolution with Internet of Things (IoTs) has developed various applications in almost all domains from health care, education to entertainment with sensors and smart devices. One of the subsets of IoT is Internet of Medical things (IoMT) which connects medical devices, hardware and software applications through internet. IoMT enables secure wireless communication over the Internet to allow efficient analysis of medical data. With these smart advancements and exploitation of smart IoT devices in health care technology… More >

  • Open Access

    ARTICLE

    Decision Tree Based Key Management for Secure Group Communication

    P. Parthasarathi1,*, S. Shankar2

    Computer Systems Science and Engineering, Vol.42, No.2, pp. 561-575, 2022, DOI:10.32604/csse.2022.019561 - 04 January 2022

    Abstract Group communication is widely used by most of the emerging network applications like telecommunication, video conferencing, simulation applications, distributed and other interactive systems. Secured group communication plays a vital role in case of providing the integrity, authenticity, confidentiality, and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the group. In secure group communications, the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service, particularly in the… More >

  • Open Access

    ARTICLE

    BDLR: lncRNA identification using ensemble learning

    LEJUN GONG1,2,*, SHEHAI ZHOU1, JINGMEI CHEN1, YONGMIN LI1, LI ZHANG4, ZHIHONG GAO3

    BIOCELL, Vol.46, No.4, pp. 951-960, 2022, DOI:10.32604/biocell.2022.016625 - 15 December 2021

    Abstract Long non-coding RNAs (lncRNAs) play an important role in many life activities such as epigenetic material regulation, cell cycle regulation, dosage compensation and cell differentiation regulation, and are associated with many human diseases. There are many limitations in identifying and annotating lncRNAs using traditional biological experimental methods. With the development of high-throughput sequencing technology, it is of great practical significance to identify the lncRNAs from massive RNA sequence data using machine learning method. Based on the Bagging method and Decision Tree algorithm in ensemble learning, this paper proposes a method of lncRNAs gene sequence identification More >

  • Open Access

    ARTICLE

    Classification of Parkinson Disease Based on Patient’s Voice Signal Using Machine Learning

    Imran Ahmed1, Sultan Aljahdali2, Muhammad Shakeel Khan1, Sanaa Kaddoura3,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 705-722, 2022, DOI:10.32604/iasc.2022.022037 - 17 November 2021

    Abstract Parkinson’s disease (PD) is a nervous system disorder first described as a neurological condition in 1817. It is one of the more prevalent diseases in the elderly, and Alzheimer’s is the second most common neurodegenerative illness. It impacts the patient’s movement. Symptoms start gradually with tremors, stiffness in movement, and speech and voice disorders. Researches proved that 89% of patients with Parkinson’s has speech disorder including uncertain articulation, hoarse and breathy voice and monotone pitch. The cause behind this voice change is the reduction of dopamine due to damage of neurons in the substantia nigra… More >

  • Open Access

    ARTICLE

    DDoS Detection in SDN using Machine Learning Techniques

    Muhammad Waqas Nadeem, Hock Guan Goh*, Vasaki Ponnusamy, Yichiet Aun

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 771-789, 2022, DOI:10.32604/cmc.2022.021669 - 03 November 2021

    Abstract Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and network operation over a network infrastructure. The SDN controller is considered as the operating system of the SDN based network infrastructure, and it is responsible for executing the different network applications and maintaining the network services and functionalities. Despite all its tremendous capabilities, the SDN face many security issues due to the complexity of the SDN architecture. Distributed denial of services (DDoS) is a common attack on SDN due to its centralized architecture, especially at the control layer of… More >

  • Open Access

    ARTICLE

    Process Optimization Method for Day Ward Based on Bayesian Decision-Tree

    Ting Chen1, Kai Pu2, Lanzhen Bian3, Min Rao4, Jing Hu5, Rugang Lu1,*, Jinyue Xia6

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 513-523, 2022, DOI:10.32604/iasc.2022.022510 - 26 October 2021

    Abstract The day surgery management mode is mainly decentralized management, with clinical departments as the unit, and with reference to the experience of inter project operation management in benchmark hospitals, the empirical management is implemented. With the development of day surgery, the extensive decentralized management mode has been unable to meet the needs of the current day surgery development situation. At first, the paper carefully analyzes the existing problems in the day surgery process in the day ward of the Children’s Hospital of Nanjing Medical University. And then, the concerns of doctors, nurses, anesthesiologists and other… More >

  • Open Access

    ARTICLE

    Prediction of Suitable Candidates for COVID-19 Vaccination

    R. Sujatha1, B. Venkata Siva Krishna1, Jyotir Moy Chatterjee2, P. Rahul Naidu1, NZ Jhanjhi3,*, Challa Charita1, Eza Nerin Mariya1, Mohammed Baz4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 525-541, 2022, DOI:10.32604/iasc.2022.021216 - 26 October 2021

    Abstract In the current times, COVID-19 has taken a handful of people’s lives. So, vaccination is crucial for everyone to avoid the spread of the disease. However, not every vaccine will be perfect or will get success for everyone. In the present work, we have analyzed the data from the Vaccine Adverse Event Reporting System and understood that the vaccines given to the people might or might not work considering certain demographic factors like age, gender, and multiple other variables like the state of living, etc. This variable is considered because it explains the unmentioned variables… More >

  • Open Access

    ARTICLE

    SDN Based DDos Mitigating Approach Using Traffic Entropy for IoT Network

    Muhammad Ibrahim1, Muhammad Hanif2, Shabir Ahmad3, Faisal Jamil1, Tayyaba Sehar2, YunJung Lee4, DoHyeun Kim1,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5651-5665, 2022, DOI:10.32604/cmc.2022.017772 - 11 October 2021

    Abstract The Internet of Things (IoT) has been widely adopted in various domains including smart cities, healthcare, smart factories, etc. In the last few years, the fitness industry has been reshaped by the introduction of smart fitness solutions for individuals as well as fitness gyms. The IoT fitness devices collect trainee data that is being used for various decision-making. However, it will face numerous security and privacy issues towards its realization. This work focuses on IoT security, especially DoS/DDoS attacks. In this paper, we have proposed a novel blockchain-enabled protocol (BEP) that uses the notion of… More >

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