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  • Open Access

    ARTICLE

    Effects of PEG200 on the Properties and Performance of PVDF Membranes in the Separation of MethanolWater Mixtures by Pervaporation

    DIPESHKUMAR D. KACHHADIYA, Z.V.P. MURTHY*

    Journal of Polymer Materials, Vol.38, No.1-2, pp. 49-61, 2021, DOI:10.32381/JPM.2021.38.1-2.5

    Abstract The conventional process for methanol-water separation like distillation consumes about 60 % of total energy. As an alternative, researchers have developed a membrane-based separation process for alcohol-water mixtures separation. However, there is a big challenge for researches to separate alcohol-water aqueous mixtures using a polymeric membrane because of swelling. In the present work, the aim is to separate methanol from water by pervaporation using polymeric membranes made up of polyvinylidenefluroide (PVDF) and polyethylene glycol (PEG200) modified PVDF membranes. The membranes were characterized by thermogravimetry analysis (TGA), field emission scanning electron microscopy (FE-SEM), and Fourier-transform infrared spectroscopy (FTIR). A study on… More >

  • Open Access

    ARTICLE

    Cybersecurity Threats Detection Using Optimized Machine Learning Frameworks

    Nadir Omer1,*, Ahmed H. Samak2, Ahmed I. Taloba3,4, Rasha M. Abd El-Aziz3,5

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 77-95, 2024, DOI:10.32604/csse.2023.039265

    Abstract Today’s world depends on the Internet to meet all its daily needs. The usage of the Internet is growing rapidly. The world is using the Internet more frequently than ever. The hazards of harmful attacks have also increased due to the growing reliance on the Internet. Hazards to cyber security are actions taken by someone with malicious intent to steal data, destroy computer systems, or disrupt them. Due to rising cyber security concerns, cyber security has emerged as the key component in the fight against all online threats, forgeries, and assaults. A device capable of identifying network irregularities and cyber-attacks… More >

  • Open Access

    ARTICLE

    Nuclei Segmentation in Histopathology Images Using Structure-Preserving Color Normalization Based Ensemble Deep Learning Frameworks

    Manas Ranjan Prusty1, Rishi Dinesh2, Hariket Sukesh Kumar Sheth2, Alapati Lakshmi Viswanath2, Sandeep Kumar Satapathy2,3,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3077-3094, 2023, DOI:10.32604/cmc.2023.042718

    Abstract This paper presents a novel computerized technique for the segmentation of nuclei in hematoxylin and eosin (H&E) stained histopathology images. The purpose of this study is to overcome the challenges faced in automated nuclei segmentation due to the diversity of nuclei structures that arise from differences in tissue types and staining protocols, as well as the segmentation of variable-sized and overlapping nuclei. To this extent, the approach proposed in this study uses an ensemble of the UNet architecture with various Convolutional Neural Networks (CNN) architectures as encoder backbones, along with stain normalization and test time augmentation, to improve segmentation accuracy.… More >

  • Open Access

    ARTICLE

    Unmanned Aerial Vehicle Multi-Access Edge Computing as Security Enabler for Next-Gen 5G Security Frameworks

    Jaime Ortiz Córdoba, Alejandro Molina Zarca*, Antonio Skármeta

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2307-2333, 2023, DOI:10.32604/iasc.2023.039607

    Abstract 5G/Beyond 5G (B5G) networks provide connectivity to many heterogeneous devices, raising significant security and operational issues and making traditional infrastructure management increasingly complex. In this regard, new frameworks such as Anastacia-H2020 or INSPIRE-5GPlus automate the management of next-generation infrastructures, especially regarding policy-based security, abstraction, flexibility, and extensibility. This paper presents the design, workflow, and implementation of a security solution based on Unmanned Aerial Vehicles (UAVs), able to extend 5G/B5G security framework capabilities with UAV features like dynamic service provisioning in specific geographic areas. The proposed solution allows enforcing UAV security policies in proactive and reactive ways to automate UAV dynamic… More >

  • Open Access

    ARTICLE

    Comparative Analysis of COVID-19 Detection Methods Based on Neural Network

    Inès Hilali-Jaghdam1,*, Azhari A Elhag2, Anis Ben Ishak3, Bushra M. Elamin Elnaim4, Omer Eltag Mohammed Elhag5, Feda Muhammed Abuhaimed1, S. Abdel-Khalek2,6

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1127-1150, 2023, DOI:10.32604/cmc.2023.038915

    Abstract In 2019, the novel coronavirus disease 2019 (COVID-19) ravaged the world. As of July 2021, there are about 192 million infected people worldwide and 4.1365 million deaths. At present, the new coronavirus is still spreading and circulating in many places around the world, especially since the emergence of Delta variant strains has increased the risk of the COVID-19 pandemic again. The symptoms of COVID-19 are diverse, and most patients have mild symptoms, with fever, dry cough, and fatigue as the main manifestations, and about 15.7% to 32.0% of patients will develop severe symptoms. Patients are screened in hospitals or primary… More >

  • Open Access

    REVIEW

    Explainable Artificial Intelligence–A New Step towards the Trust in Medical Diagnosis with AI Frameworks: A Review

    Nilkanth Mukund Deshpande1,2, Shilpa Gite6,7,*, Biswajeet Pradhan3,4,5, Mazen Ebraheem Assiri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 843-872, 2022, DOI:10.32604/cmes.2022.021225

    Abstract Machine learning (ML) has emerged as a critical enabling tool in the sciences and industry in recent years. Today’s machine learning algorithms can achieve outstanding performance on an expanding variety of complex tasks–thanks to advancements in technique, the availability of enormous databases, and improved computing power. Deep learning models are at the forefront of this advancement. However, because of their nested nonlinear structure, these strong models are termed as “black boxes,” as they provide no information about how they arrive at their conclusions. Such a lack of transparencies may be unacceptable in many applications, such as the medical domain. A… More >

  • Open Access

    ARTICLE

    Effective Frameworks Based on Infinite Mixture Model for Real-World Applications

    Norah Saleh Alghamdi1, Sami Bourouis2,*, Nizar Bouguila3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1139-1156, 2022, DOI:10.32604/cmc.2022.022959

    Abstract Interest in automated data classification and identification systems has increased over the past years in conjunction with the high demand for artificial intelligence and security applications. In particular, recognizing human activities with accurate results have become a topic of high interest. Although the current tools have reached remarkable successes, it is still a challenging problem due to various uncontrolled environments and conditions. In this paper two statistical frameworks based on nonparametric hierarchical Bayesian models and Gamma distribution are proposed to solve some real-world applications. In particular, two nonparametric hierarchical Bayesian models based on Dirichlet process and Pitman-Yor process are developed.… More >

  • Open Access

    ARTICLE

    Facile Preparation of Fe–N–C Oxygen Reduction Electrocatalysts from Metal Organic Frameworks for Zn-Air Battery

    Chengcheng Wang1,2,*, Dawei Luo1, Bingxue Hou3, Mortaza Gholizadeh4, Zanxiong Tan1, Xiaojie Han1

    Journal of Renewable Materials, Vol.10, No.5, pp. 1337-1348, 2022, DOI:10.32604/jrm.2022.018770

    Abstract It is critical to study efficient, stable oxygen reduction reaction (ORR) electrocatalysts due to insufficient stability and expensive price of Pt/C catalysts for Zn-air batteries. Fe–N–C electrocatalysts was synthesized by a facile solvent-green method and the efficiency of Fe–N–C optimized was studied as potential ORR electrocatalysts under alkaline condition. Results indicated that it had excellent ORR activity with E1/2 of 0.93 V, which was competitive to that of Pt/C-JM under the same conditions. Moreover, the assembled Zn-air battery exhibited discharge potential and charge potential of 1.2 V, 2.32 V at 5 mA cm2 with high stability, respectively. Overall, all results illustrated… More > Graphic Abstract

    Facile Preparation of Fe–N–C Oxygen Reduction Electrocatalysts from Metal Organic Frameworks for Zn-Air Battery

  • Open Access

    ARTICLE

    A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

    Wael Said1, Elsayed Mostafa1,*, M. M. Hassan1, Ayman Mohamed Mostafa2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3193-3209, 2022, DOI:10.32604/cmc.2022.023554

    Abstract User's data is considered as a vital asset of several organizations. Migrating data to the cloud computing is not an easy decision for any organization due to the privacy and security concerns. Service providers must ensure that both data and applications that will be stored on the cloud should be protected in a secure environment. The data stored on the public cloud will be vulnerable to outside and inside attacks. This paper provides interactive multi-layer authentication frameworks for securing user identities on the cloud. Different access control policies are applied for verifying users on the cloud. A security mechanism is… More >

  • Open Access

    ABSTRACT

    HYDROGEN STORAGE IN CARBON NANOSTRUCTURES AND ORGANIC FRAMEWORKS

    Gotthard Seifert, Aliezer Martinez Mesa, Sergei Yurchenko, Bassem Assfour1, Thomas Heine3, Sergei Patchkovsk

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.18, No.1, pp. 21-22, 2011, DOI:10.3970/icces.2011.018.021

    Abstract In this study structural characteristics of several carbon based nanostructures and organic frameworks as metal organic frameworks (MOF) and covalent organic frameworks (COF) on the hydrogen abundance in the material are investigated with the quantized liquid density functional theory (QLDFT), Molecular Dynamics (MD) and Grand Canonical Monte Carlo (GCMC). We applied these theories to evaluate the hydrogen storage capacities of nanoporous materials: Compact storage of hydrogen is the key challenge facing adoption of hydrogen as fuel for mobile applications. A promising approach to increase the storage densities is the adsorption of molecular hydrogen in porous environments. We have studied in… More >

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