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  • Open Access

    ARTICLE

    FSpot: Fast and Efficient Video Encoding Workloads Over Amazon Spot Instances

    Anatoliy Zabrovskiy1,3, Prateek Agrawal1,2,*, Vladislav Kashansky1, Roland Kersche4, Christian Timmerer1,4, Radu Prodan1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5677-5697, 2022, DOI:10.32604/cmc.2022.023630 - 14 January 2022

    Abstract HTTP Adaptive Streaming (HAS) of video content is becoming an undivided part of the Internet and accounts for most of today's network traffic. Video compression technology plays a vital role in efficiently utilizing network channels, but encoding videos into multiple representations with selected encoding parameters is a significant challenge. However, video encoding is a computationally intensive and time-consuming operation that requires high-performance resources provided by on-premise infrastructures or public clouds. In turn, the public clouds, such as Amazon elastic compute cloud (EC2), provide hundreds of computing instances optimized for different purposes and clients’ budgets. Thus,… More >

  • Open Access

    ARTICLE

    Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network

    Dheeraj Kumar Dixit*, Amit Bhagat, Dharmendra Dangi

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5733-5750, 2022, DOI:10.32604/cmc.2022.023628 - 14 January 2022

    Abstract In recent years, social media platforms have gained immense popularity. As a result, there has been a tremendous increase in content on social media platforms. This content can be related to an individual's sentiments, thoughts, stories, advertisements, and news, among many other content types. With the recent increase in online content, the importance of identifying fake and real news has increased. Although, there is a lot of work present to detect fake news, a study on Fuzzy CRNN was not explored into this direction. In this work, a system is designed to classify fake and More >

  • Open Access

    ARTICLE

    Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

    Waleed Rafique1, Ayesha Khan2, Ahmad Almogren3, Jehangir Arshad1, Adnan Yousaf4, Mujtaba Hussain Jaffery1, Ateeq Ur Rehman5, Muhammad Shafiq6,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4275-4293, 2022, DOI:10.32604/cmc.2022.023588 - 14 January 2022

    Abstract An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for… More >

  • Open Access

    ARTICLE

    Decision Support System for Diagnosis of Irregular Fovea

    Ghulam Ali Mallah1, Jamil Ahmed1, Muhammad Irshad Nazeer2,*, Mazhar Ali Dootio3, Hidayatullah Shaikh1, Aadil Jameel1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5343-5353, 2022, DOI:10.32604/cmc.2022.023581 - 14 January 2022

    Abstract Detection of abnormalities in human eye is one of the well-established research areas of Machine Learning. Deep Learning techniques are widely used for the diagnosis of Retinal Diseases (RD). Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels (PBV). Retinopathy Images (RI) contains sufficient information to classify structural changes incurred upon PBV but Macular Features (MF) and Fovea Features (FF) are very difficult to detect because features of MF and FF could be found with Similar Color Movements (SCM) with minor variations. This paper… More >

  • Open Access

    ARTICLE

    Emotion Based Signal Enhancement Through Multisensory Integration Using Machine Learning

    Muhammad Adnan Khan1,2, Sagheer Abbas3, Ali Raza3, Faheem Khan4, T. Whangbo4,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5911-5931, 2022, DOI:10.32604/cmc.2022.023557 - 14 January 2022

    Abstract Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming signals. It is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place, the signal having more strength under the influence of emotions effects the response accordingly. Current research in multisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or depression. Therefore, there is a need to integrate the emotional More >

  • Open Access

    ARTICLE

    Man Overboard Detection System Using IoT for Navigation Model

    Hüseyin Gürüler1, Murat Altun1, Faheem Khan2, Taegkeun Whangbo2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4955-4969, 2022, DOI:10.32604/cmc.2022.023556 - 14 January 2022

    Abstract Security measures and contingency plans have been established in order to ensure human safety especially in the floating elements like ferry, ro-ro, catamaran, frigate, yacht that are the vehicles services for the purpose of logistic and passenger transport. In this paper, all processes in the event of Man overboard (MOB)are initiated for smart transportation. In MOB the falling person is totally dependent on the person who first saw the falling person. The main objective of this paper is to develop a solution to this significant problem. If a staff member or a passenger does not… More >

  • Open Access

    REVIEW

    Milestones of Wireless Communication Networks and Technology Prospect of Next Generation (6G)

    Mohammed H. Alsharif1, Md. Sanwar Hossain2, Abu Jahid3, Muhammad Asghar Khan4, Bong Jun Choi5,*, Samih M. Mostafa6,7

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4803-4818, 2022, DOI:10.32604/cmc.2022.023500 - 14 January 2022

    Abstract Since around 1980, a new generation of wireless technology has arisen approximately every 10 years. First-generation (1G) and second-generation (2G) began with voice and eventually introduced more and more data in third-generation (3G) and became highly popular in the fourth-generation (4G). To increase the data rate along with low latency and mass connectivity the fifth-generation (5G) networks are being installed from 2020. However, the 5G technology will not be able to fulfill the data demand at the end of this decade. Therefore, it is expected that 6G communication networks will rise, providing better services through… More >

  • Open Access

    ARTICLE

    Contrast Correction Using Hybrid Statistical Enhancement on Weld Defect Images

    Wan Azani Mustafa1,2,*, Haniza Yazid3, Ahmed Alkhayyat4, Mohd Aminudin Jamlos3, Hasliza A. Rahim3, Midhat Nabil Salimi5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5327-5342, 2022, DOI:10.32604/cmc.2022.023492 - 14 January 2022

    Abstract Luminosity and contrast variation problems are among the most challenging tasks in the image processing field, significantly improving image quality. Enhancement is implemented by adjusting the dark or bright intensity to improve the quality of the images and increase the segmentation performance. Recently, numerous methods had been proposed to normalise the luminosity and contrast variation. A new approach based on a direct technique using statistical data known as Hybrid Statistical Enhancement (HSE) is presented in this study. The HSE method uses the mean and standard deviation of a local and global neighbourhood and classified the… More >

  • Open Access

    ARTICLE

    SVM and KNN Based CNN Architectures for Plant Classification

    Sukanta Ghosh1, Amar Singh1, Kavita2,*, N. Z. Jhanjhi3, Mehedi Masud4, Sultan Aljahdali4

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4257-4274, 2022, DOI:10.32604/cmc.2022.023414 - 14 January 2022

    Abstract Automatic plant classification through plant leaf is a classical problem in Computer Vision. Plants classification is challenging due to the introduction of new species with a similar pattern and look-a-like. Many efforts are made to automate plant classification using plant leaf, plant flower, bark, or stem. After much effort, it has been proven that leaf is the most reliable source for plant classification. But it is challenging to identify a plant with the help of leaf structure because plant leaf shows similarity in morphological variations, like sizes, textures, shapes, and venation. Therefore, it is required… More >

  • Open Access

    ARTICLE

    Fruits and Vegetables Freshness Categorization Using Deep Learning

    Labiba Gillani Fahad1, Syed Fahad Tahir2,*, Usama Rasheed1, Hafsa Saqib1, Mehdi Hassan2, Hani Alquhayz3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5083-5098, 2022, DOI:10.32604/cmc.2022.023357 - 14 January 2022

    Abstract The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using… More >

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