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Search Results (29)
  • Open Access

    ARTICLE

    Numerical Analysis of Novel Coronavirus (2019-nCov) Pandemic Model with Advection

    Shumaila Azam1, Nauman Ahmed1,6, Ali Raza2, Muhammad Sajid Iqbal1, Muhammad Rafiq3, Ilyas Khan4,*, Kottakkaran Sooppy Nisar5, Muhammad Ozair Ahmad1, Zafar Iqbal1,6

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2933-2953, 2021, DOI:10.32604/cmc.2021.012396

    Abstract Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics,… More >

  • Open Access

    ARTICLE

    A Model Transformation Approach for Detecting Distancing Violations in Weighted Graphs

    Ahmad F. Subahi*

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 13-39, 2021, DOI:10.32604/csse.2021.014376

    Abstract This work presents the design of an Internet of Things (IoT) edge-based system based on model transformation and complete weighted graph to detect violations of social distancing measures in indoor public places. A wireless sensor network based on Bluetooth Low Energy is introduced as the infrastructure of the proposed design. A hybrid model transformation strategy for generating a graph database to represent groups of people is presented as a core middleware layer of the detecting system’s proposed architectural design. A Neo4j graph database is used as a target implementation generated from the proposed transformational system to store all captured real-time… More >

  • Open Access

    ARTICLE

    Intelligent Prediction Approach for Diabetic Retinopathy Using Deep Learning Based Convolutional Neural Networks Algorithm by Means of Retina Photographs

    G. Arun Sampaul Thomas1, Y. Harold Robinson2, E. Golden Julie3, Vimal Shanmuganathan4, Seungmin Rho5, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1613-1629, 2021, DOI:10.32604/cmc.2020.013443

    Abstract Retinopathy is a human eye disease that causes changes in retinal blood vessels that leads to bleed, leak fluid and vision impairment. Symptoms of retinopathy are blurred vision, changes in color perception, red spots, and eye pain and it cannot be detected with a naked eye. In this paper, a new methodology based on Convolutional Neural Networks (CNN) is developed and proposed to intelligent retinopathy prediction and give a decision about the presence of retinopathy with automatic diabetic retinopathy screening with accurate diagnoses. The CNN model is trained by different images of eyes that have retinopathy and those which do… More >

  • Open Access

    ARTICLE

    A Longest Matching Resource Mapping Algorithm with State Compression Dynamic Programming Optimization

    Zhang Min, Teng Haibin, Jiang Ming, Wen Tao, Tang Jingfan

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 625-635, 2019, DOI:10.31209/2019.100000117

    Abstract Mapping from sentence phrases to knowledge graph resources is an important step for applications such as search engines, automatic question answering systems based on acknowledge base and knowledge graphs. The existing solution maps a simple phrase to a knowledge graph resource strictly or approximately from the text. However, it is difficult to detect phrases and map the composite semantic resource. This paper proposes a longest matching resource mapping scheme to solve this problem, namely, to find the longest substring in a sentence that can match the knowledge base resource. Based on this scheme, we propose an optimization algorithm based on… More >

  • Open Access

    ARTICLE

    Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme

    Yueqi Hou1, Xiaolong Liang1, 2, Lyulong He1, Jiaqiang Zhang1, *, Jie Zhu3, Baoxiang Ren3

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1335-1349, 2020, DOI:10.32604/cmc.2020.06869

    Abstract Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications. This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme. The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors. We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously. The acceleration constraint is… More >

  • Open Access

    ARTICLE

    Integrated Condition Monitoring of Large Captive Power Plants and Aluminum Smelters

    J.K. Mohanty1, A. Adarsh2, P.R. Dash1, K. Parida1, P.K. Pradhan1,*

    Sound & Vibration, Vol.53, No.5, pp. 223-235, 2019, DOI:10.32604/sv.2019.07737

    Abstract Condition monitoring is implementation of the advanced diagnostic techniques to reduce downtime and to increase the efficiency and reliability. The research is for determining the usage of advanced techniques like Vibration analysis, Oil analysis and Thermography to diagnose ensuing problems of the Plant and Machinery at an early stage and plan to take corrective and preventive actions to eliminate the forthcoming breakdown and enhancing the reliability of the system. Nowadays, the most of the industries have adopted the condition monitoring techniques as a part of support system to the basic maintenance strategies. Major condition monitoring technique they follow is Vibration… More >

  • Open Access

    ARTICLE

    Vegetal cover estimated by digital photographs related to biomass in a grassland site in northern Mexico

    Gutiérrez-Guzmán UN1, E Castellanos-Pérez1, JJ Q uiñones-Vera1, JS Serrato-Corona1, JJ Martínez-Ríos1, I Orona-Castillo1, I Chairez-Hernández2

    Phyton-International Journal of Experimental Botany, Vol.84, No.2, pp. 312-318, 2015, DOI:10.32604/phyton.2015.84.312

    Abstract A regression model was used to determine the relationship between aerial herbaceous biomass and vegetation coverage estimated by digital images. Four samplings (n=36 each date) of vegetation cover and herbaceous biomass were performed during the growing season in 2011 in a grassland dominated by Bouteloua gracilis in La Cieneguilla, Municipality of Villa Hidalgo, Durango. Average production of dry biomass was 37.36 ± 9.66 g/m2, and mean vegetation cover 30.02%. Dry biomass data were tested for normality using the test of Kolmogorov Smirnov, finding a lack of fit. The data were subjected to a logarithmic transformation and the model Ln(y) =… More >

  • Open Access

    ARTICLE

    Combining Lumped Parameter Bond Graphs with Finite Element Shafts in a Gearbox Model

    J. Choi1, M.D. Bryant2

    CMES-Computer Modeling in Engineering & Sciences, Vol.3, No.4, pp. 431-446, 2002, DOI:10.3970/cmes.2002.003.431

    Abstract This paper presents an updated bond graph model of a gearbox, which now includes bending of shafts. The gearbox system has an input shaft, layshaft, output shaft, spur gears, bearings, and housing. The bond graph model integrates separate sub-models into a composite model. Sub-modules include tooth-to-tooth contact, rotor dynamics of shafts, global dynamics of the gearbox housing structure, and shaft bending modeled by finite element modeling. The tooth-to-tooth model includes tooth bending; shaft torsion; gear inertia; conversion of gear torque into tooth forces; tooth contact mechanics; and multiple tooth contact. To analyze shaft dynamics more precisely, elementary finite element theory… More >

  • Open Access

    ARTICLE

    Seed Selection for Data Offloading Based on Social and Interest Graphs

    Ying Li1, Jianbo Li1,*, Jianwei Chen1, Minchao Lu1, Caoyuan Li2,3

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 571-587, 2018, DOI:10.32604/cmc.2018.02851

    Abstract The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic. The principle behind it is to select a few important users as seeds for data sharing. The three critical steps are detailed as follows. We first explore individual interests of users by the construction of user profiles, on which an interest graph is built by Gaussian graphical modeling. We then apply the extreme value theory to threshold the encounter duration of user pairs. So, a contact graph… More >

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