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  • Open Access

    ARTICLE

    SSABA: Search Step Adjustment Based Algorithm

    Fatemeh Ahmadi Zeidabadi1, Ali Dehghani2, Mohammad Dehghani3, Zeinab Montazeri4, Štěpán Hubálovský5, Pavel Trojovský3,*, Gaurav Dhiman6

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4237-4256, 2022, DOI:10.32604/cmc.2022.023682

    Abstract Finding the suitable solution to optimization problems is a fundamental challenge in various sciences. Optimization algorithms are one of the effective stochastic methods in solving optimization problems. In this paper, a new stochastic optimization algorithm called Search Step Adjustment Based Algorithm (SSABA) is presented to provide quasi-optimal solutions to various optimization problems. In the initial iterations of the algorithm, the step index is set to the highest value for a comprehensive search of the search space. Then, with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer to the global optimal, the… More >

  • Open Access

    ARTICLE

    Transfer Learning-based Computer-aided Diagnosis System for Predicting Grades of Diabetic Retinopathy

    Qaisar Abbas1,*, Mostafa E. A. Ibrahim1,2, Abdul Rauf Baig1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4573-4590, 2022, DOI:10.32604/cmc.2022.023670

    Abstract Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists and time-consuming. Therefore, many computer-aided diagnosis (CAD) systems were developed to automate this screening process of DR. In this paper, a CAD-DR system is proposed based on preprocessing and a pre-train transfer learning-based convolutional neural network (PCNN) to recognize the five stages of DR through retinal fundus images. To develop this CAD-DR system, a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related lesions and then a standard… More >

  • Open Access

    ARTICLE

    Energy-Efficient Scheduling for a Cognitive IoT-Based Early Warning System

    Saeed Ahmed1,2, Noor Gul1,3, Jahangir Khan4, Junsu Kim1, Su Min Kim1,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5061-5082, 2022, DOI:10.32604/cmc.2022.023639

    Abstract Flash floods are deemed the most fatal and disastrous natural hazards globally due to their prompt onset that requires a short prime time for emergency response. Cognitive Internet of things (CIoT) technologies including inherent characteristics of cognitive radio (CR) are potential candidates to develop a monitoring and early warning system (MEWS) that helps in efficiently utilizing the short response time to save lives during flash floods. However, most CIoT devices are battery-limited and thus, it reduces the lifetime of the MEWS. To tackle these problems, we propose a CIoT-based MEWS to slash the fatalities of flash floods. To extend the… More >

  • Open Access

    ARTICLE

    Efficient Computer Aided Diagnosis System for Hepatic Tumors Using Computed Tomography Scans

    Yasmeen Al-Saeed1,2, Wael A. Gab-Allah1, Hassan Soliman1, Maysoon F. Abulkhair3, Wafaa M. Shalash4, Mohammed Elmogy1,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4871-4894, 2022, DOI:10.32604/cmc.2022.023638

    Abstract One of the leading causes of mortality worldwide is liver cancer. The earlier the detection of hepatic tumors, the lower the mortality rate. This paper introduces a computer-aided diagnosis system to extract hepatic tumors from computed tomography scans and classify them into malignant or benign tumors. Segmenting hepatic tumors from computed tomography scans is considered a challenging task due to the fuzziness in the liver pixel range, intensity values overlap between the liver and neighboring organs, high noise from computed tomography scanner, and large variance in tumors shapes. The proposed method consists of three main stages; liver segmentation using Fast… More >

  • 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

    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, there is a need for… 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

    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 real news using fuzzy logic.… 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

    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 an instantaneous reactive and active… 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

    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 presents novel method for the… 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

    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 state of the agent with… 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

    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 see the fall into the… More >

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