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  • Open Access

    ARTICLE

    Compact Bat Algorithm with Deep Learning Model for Biomedical EEG EyeState Classification

    Souad Larabi-Marie-Sainte1, Eatedal Alabdulkreem2, Mohammad Alamgeer3, Mohamed K Nour4, Anwer Mustafa Hilal5,*, Mesfer Al Duhayyim6, Abdelwahed Motwakel5, Ishfaq Yaseen5

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4589-4601, 2022, DOI:10.32604/cmc.2022.027922

    Abstract Electroencephalography (EEG) eye state classification becomes an essential tool to identify the cognitive state of humans. It can be used in several fields such as motor imagery recognition, drug effect detection, emotion categorization, seizure detection, etc. With the latest advances in deep learning (DL) models, it is possible to design an accurate and prompt EEG EyeState classification problem. In this view, this study presents a novel compact bat algorithm with deep learning model for biomedical EEG EyeState classification (CBADL-BEESC) model. The major intention of the CBADL-BEESC technique aims to categorize the presence of EEG EyeState. The CBADL-BEESC model performs feature… More >

  • Open Access

    ARTICLE

    Automatic Eyewitness Identification During Disasters by Forming a Feature-Word Dictionary

    Shahzad Nazir1, Muhammad Asif1,*, Shahbaz Ahmad1, Hanan Aljuaid2, Shahbaz Ahmad1, Yazeed Ghadi3, Zubair nawaz4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4755-4769, 2022, DOI:10.32604/cmc.2022.026145

    Abstract Social media provide digitally interactional technologies to facilitate information sharing and exchanging individuals. Precisely, in case of disasters, a massive corpus is placed on platforms such as Twitter. Eyewitness accounts can benefit humanitarian organizations and agencies, but identifying the eyewitness Tweets related to the disaster from millions of Tweets is difficult. Different approaches have been developed to address this kind of problem. The recent state-of-the-art system was based on a manually created dictionary and this approach was further refined by introducing linguistic rules. However, these approaches suffer from limitations as they are dataset-dependent and not scalable. In this paper, we… More >

  • Open Access

    ARTICLE

    The Effects of Fertilizers on Rabbiteye Blueberry (Vaccinium ashei Reade.) Root Distribution and Fruit Yield

    Xiaolan Guo1, Chenyan Liu1, Muhammad Shakeel2, Delu Wang1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.6, pp. 1289-1302, 2022, DOI:10.32604/phyton.2022.019774

    Abstract The root system plays an important role in the growth and development of blueberry. The aim of this study was to assess the impacts of different fertilizers on the root growth and root–yield relationship of blueberry to provide insight into the regulation of root growth and fruit yield by fertilizing from the perspective of the root system. Rabbiteye blueberry variety ‘Britewell’ as the test material, and six fertilizers, including BF, OR, CF, SF, HF, and RT were used in single-factor fertilization experiments to analyze the effects of different fertilizer treatments on the root morphology, root distribution, and fruit yield of… 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

    Modular Design Using Sustainable Luminescent Materials in Energy-Saving Reflective Cat’s Eyes for Public Road Safety Planning

    Lung-Yin Lin1, Yu-Shing Chang2,*

    Journal of Renewable Materials, Vol.10, No.5, pp. 1415-1437, 2022, DOI:10.32604/jrm.2022.018408

    Abstract Recently, there has been a global movement toward environmental protection and energy conservation through the design and development of new products in accordance with sustainable utilisation. In this study, rare earth luminescent materials were used owing to their active light emission and reusability. Additionally, solar light-emitting diode lights and car-light reflection were utilised to increase the recognition and reliability of reflective cat eyes. Along with carbon reduction, this can save energy and enhance road safety. This study considered the Theory of Inventive Problem Solving and a literature review to analyse the issues in existing products. Then, expert interviews were conducted… More >

  • Open Access

    ARTICLE

    Early Detection of Pancreatic Cancer Using Jaundiced Eye Images

    R. Reena Roy*, G. S. Anandha Mala

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 677-688, 2022, DOI:10.32604/csse.2022.016620

    Abstract Pancreatic cancer is one of the deadliest cancers, with less than 9% survival rates. Pancreatic Ductal Adeno Carcinoma (PDAC) is common with the general public affecting most people older than 45. Early detection of PDAC is often challenging because cancer symptoms will progress only at later stages (advanced stage). One of the earlier symptoms of PDAC is Jaundice. Patients with diabetes, obesity, and alcohol consumption are also at higher risk of having pancreatic cancer. A decision support system is developed to detect pancreatic cancer at an earlier stage to address this challenge. Features such as Mean Hue, Mean Saturation, Mean… More >

  • Open Access

    ARTICLE

    Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

    Shibli Nisar1, Muhammad Asghar Khan2,*, Fahad Algarni3, Abdul Wakeel1, M. Irfan Uddin4, Insaf Ullah2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376

    Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted mel frequency cepstral coefficients for… More >

  • Open Access

    ARTICLE

    Immersion Analysis Through Eye-Tracking and Audio in Virtual Reality

    Jihoon Lee, Nammee Moon*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 647-660, 2021, DOI:10.32604/cmc.2021.016712

    Abstract In this study, using Head Mounted Display (HMD), which is one of the biggest advantage of Virtual Reality (VR) environment, tracks the user’s gaze in 360° video content, and examines how the gaze pattern is distributed according to the user’s immersion. As a result of analyzing the gaze pattern distribution of contents with high user immersion and contents with low user immersion through a questionnaire, it was confirmed that the higher the immersion, the more the gaze distribution tends to be concentrated in the center of the screen. Through this experiment, we were able to understand the factors that make… More >

  • Open Access

    ARTICLE

    PotholeEye+: Deep-Learning Based Pavement Distress Detection System toward Smart Maintenance

    Juyoung Park1,*, Jung Hee Lee1, Junseong Bang2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 965-976, 2021, DOI:10.32604/cmes.2021.014669

    Abstract

    We propose a mobile system, called PotholeEye+, for automatically monitoring the surface of a roadway and detecting the pavement distress in real-time through analysis of a video. PotholeEye+ pre-processes the images, extracts features, and classifies the distress into a variety of types, while the road manager is driving. Every day for a year, we have tested PotholeEye+ on real highway involving real settings, a camera, a mini computer, a GPS receiver, and so on. Consequently, PotholeEye+ detected the pavement distress with accuracy of 92%, precision of 87% and recall 74% averagely during driving at an average speed of 110 km/h… More >

  • Open Access

    ARTICLE

    Improved Model of Eye Disease Recognition Based on VGG Model

    Ye Mu1,2,3,4, Yuheng Sun1, Tianli Hu1,2,3,4, He Gong1,2,3,4, Shijun Li1,2,3,4,*, Thobela Louis Tyasi5

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 729-737, 2021, DOI:10.32604/iasc.2021.016569

    Abstract The rapid development of computer vision technology and digital images has increased the potential for using image recognition for eye disease diagnosis. Many early screening and diagnosis methods for ocular diseases based on retinal images of the fundus have been proposed recently, but their accuracy is low. Therefore, it is important to develop and evaluate an improved VGG model for the recognition and classification of retinal fundus images. In response to these challenges, to solve the problem of accuracy and reliability of clinical algorithms in medical imaging this paper proposes an improved model for early recognition of ophthalmopathy in retinal… More >

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