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  • Open Access

    ARTICLE

    User Interface-Based Repeated Sequence Detection Method for Authentication

    Shin Jin Kang1, Soo Kyun Kim2,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2573-2588, 2023, DOI:10.32604/iasc.2023.029893

    Abstract In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our cognitive mouse-and-keystroke dynamics system can… More >

  • Open Access

    ARTICLE

    Mortality and Long-Term Outcome of Neonates with Congenital Heart Disease and Acute Perinatal Stroke: A Population-Based Case-Control Study

    Eszter Vojcek1,2,*, V. Anna Gyarmathy3,4, Rozsa Graf5, Anna M. Laszlo6, Laszlo Ablonczy7, Zsolt Prodan7, Istvan Seri1,8

    Congenital Heart Disease, Vol.17, No.4, pp. 447-461, 2022, DOI:10.32604/chd.2022.022274

    Abstract Objective: Neonates with congenital heart disease (CHD) and perinatal stroke have high mortality and survivors are at risk for poor long-term neurodevelopmental outcome. The aim of this study was to assess the risk factors and outcome of neonates with both CHD and MRI-confirmed perinatal stroke (Study Group) and compare those to the risk factors and outcome of infants matched for CHD without stroke (Control-1) and of infants matched for MRI-confirmed stroke without CHD (Control-2). Methods: We conducted a population-based case-control study enrolling 28 term neonates with CHD and MRI-confirmed acute perinatal stroke born between 2007–2017 in the Central-Hungarian Region. Each… More > Graphic Abstract

    Mortality and Long-Term Outcome of Neonates with Congenital Heart Disease and Acute Perinatal Stroke: A Population-Based Case-Control Study

  • Open Access

    ARTICLE

    A Smart Room to Promote Autonomy of Disabled People due to Stroke

    Moeiz Miraoui1,2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799

    Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the door for visitors after their… More >

  • Open Access

    REVIEW

    Virtual Reality Neurorehabilitation

    Zhihan Lv1,*, Jinkang Guo2

    International Journal of Mental Health Promotion, Vol.24, No.3, pp. 287-310, 2022, DOI:10.32604/ijmhp.2022.019829

    Abstract The present work investigates the application of virtual reality (VR) technology to neurorehabilitation. By consulting a wealth of data, the advantages of VR in neurorehabilitation are introduced, followed by the application status of VR in the rehabilitation of stroke patients, Parkinson’s patients, mental and psychological diseases. Besides, many research experiments on the application of VR technology in rehabilitation medicine at the present stage are investigated. The results indicate that compared with traditional balance training, the VR-based neurological rehabilitation training method can more effectively ease the tilt degree and strengthen the trunk control ability and balance function of patients with post-stroke… More >

  • Open Access

    VIEWPOINT

    Prognostic, diagnostic and therapeutic potential of endothelial progenitor cells for patients with ischaemic stroke: Hype or Hope

    ULVI BAYRAKTUTAN*

    BIOCELL, Vol.46, No.7, pp. 1593-1598, 2022, DOI:10.32604/biocell.2022.018679

    Abstract Ischaemic stroke is a debilitating disease with immense personal, societal and economic impact. Thrombolysis with recombinant tissue plasminogen activator remains the only approved pharmacotherapy for this disease. As each year less than 1% of eligible patients receive this therapy worldwide, efficacious new therapeutics are desperately needed. Emerging evidence suggest endothelial progenitor cells (EPCs), capable of repairing damaged vasculature, as one such therapeutics. However, questions regarding their optimal dose, delivery route and in vivo survivability remain largely unanswered. Outgrowth endothelial cells, generated in large numbers by ex vivo expansion of EPCs, enable effective assessment of these issues and may eventually serve… More >

  • Open Access

    ARTICLE

    Deep Learning and Machine Learning for Early Detection of Stroke and Haemorrhage

    Zeyad Ghaleb Al-Mekhlafi1, Ebrahim Mohammed Senan2, Taha H. Rassem3, Badiea Abdulkarem Mohammed4,5,*, Nasrin M. Makbol5, Adwan Alownie Alanazi1, Tariq S. Almurayziq1, Fuad A. Ghaleb6

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 775-796, 2022, DOI:10.32604/cmc.2022.024492

    Abstract Stroke and cerebral haemorrhage are the second leading causes of death in the world after ischaemic heart disease. In this work, a dataset containing medical, physiological and environmental tests for stroke was used to evaluate the efficacy of machine learning, deep learning and a hybrid technique between deep learning and machine learning on the Magnetic Resonance Imaging (MRI) dataset for cerebral haemorrhage. In the first dataset (medical records), two features, namely, diabetes and obesity, were created on the basis of the values of the corresponding features. The t-Distributed Stochastic Neighbour Embedding algorithm was applied to represent the high-dimensional dataset in… More >

  • Open Access

    ARTICLE

    Modified UNet Model for Brain Stroke Lesion Segmentation on Computed Tomography Images

    Batyrkhan Omarov1,2,3, Azhar Tursynova1,*, Octavian Postolache4, Khaled Gamry5, Aidar Batyrbekov5, Sapargali Aldeshov6,7, Zhanar Azhibekova9, Marat Nurtas5,8, Akbayan Aliyeva6, Kadrzhan Shiyapov10,11

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4701-4717, 2022, DOI:10.32604/cmc.2022.020998

    Abstract The task of segmentation of brain regions affected by ischemic stroke is help to tackle important challenges of modern stroke imaging analysis. Unfortunately, at the moment, the models for solving this problem using machine learning methods are far from ideal. In this paper, we consider a modified 3D UNet architecture to improve the quality of stroke segmentation based on 3D computed tomography images. We use the ISLES 2018 (Ischemic Stroke Lesion Segmentation Challenge 2018) open dataset to train and test the proposed model. Interpretation of the obtained results, as well as the ideas for further experiments are included in the… More >

  • Open Access

    ARTICLE

    Stroke Based Painterly Rendering with Mass Data through Auto Warping Generation

    Taemin Lee1, Beomsik Kim2, Sanghyun Seo3, Kyunghyun Yoon4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1441-1457, 2022, DOI:10.32604/cmes.2022.018010

    Abstract Painting is done according to the artist's style. The most representative of the style is the texture and shape of the brush stroke. Computer simulations allow the artist's painting to be produced by taking this stroke and pasting it onto the image. This is called stroke-based rendering. The quality of the result depends on the number or quality of this stroke, since the stroke is taken to create the image. It is not easy to render using a large amount of information, as there is a limit to having a stroke scanned. In this work, we intend to produce rendering… More >

  • Open Access

    ARTICLE

    Efficient Morphological Segmentation of Brain Hemorrhage Stroke Lesion Through MultiResUNet

    R. Shijitha1,*, P. Karthigaikumar2, A. Stanly Paul2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5233-5249, 2022, DOI:10.32604/cmc.2022.020227

    Abstract Brain Hemorrhagic stroke is a serious malady that is caused by the drop in blood flow through the brain and causes the brain to malfunction. Precise segmentation of brain hemorrhage is crucial, so an enhanced segmentation is carried out in this research work. The brain image of various patients has taken using an MRI scanner by the utilization of T1, T2, and FLAIR sequence. This work aims to segment the Brain Hemorrhagic stroke using deep learning-based Multi-resolution UNet (multires UNet) through morphological operations. It is hard to precisely segment the brain lesions to extract the existing region of stroke. This… More >

  • Open Access

    ARTICLE

    Neutrosophic N-Structures Applied to Sheffer Stroke BL-Algebras

    Tugce Katican1, Tahsin Oner1, Akbar Rezaei2,*, Florentin Smarandache3

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 355-372, 2021, DOI:10.32604/cmes.2021.016996

    Abstract In this paper, we introduce a neutrosophic N-subalgebra, a (ultra) neutrosophic N-filter, level sets of these neutrosophic N-structures and their properties on a Sheffer stroke BL-algebra. By defining a quasi-subalgebra of a Sheffer stroke BL-algebra, it is proved that the level set of neutrosophic N-subalgebras on the algebraic structure is its quasi-subalgebra and vice versa. Then we show that the family of all neutrosophic N-subalgebras of a Sheffer stroke BL-algebra forms a complete distributive lattice. After that a (ultra) neutrosophic N-filter of a Sheffer stroke BL-algebra is described, we demonstrate that every neutrosophic N-filter of a Sheffer stroke BL-algebra is… More >

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