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  • Open Access

    ARTICLE

    IoT Information Status Using Data Fusion and Feature Extraction Method

    S. S. Saranya*, N. Sabiyath Fatima

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1857-1874, 2022, DOI:10.32604/cmc.2022.019621

    Abstract The Internet of Things (IoT) role is instrumental in the technological advancement of the healthcare industry. Both the hardware and the core level of software platforms are the progress resulted from the accompaniment of Medicine 4.0. Healthcare IoT systems are the emergence of this foresight. The communication systems between the sensing nodes and the processors; and the processing algorithms to produce output obtained from the data collected by the sensors are the major empowering technologies. At present, many new technologies supplement these empowering technologies. So, in this research work, a practical feature extraction and classification… More >

  • Open Access

    ARTICLE

    Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic

    Iram Mushtaq1, Muhammad Umer1, Muhammad Imran2, Inzamam Mashood Nasir3, Ghulam Muhammad4,*, Mohammad Shorfuzzaman5

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 59-72, 2022, DOI:10.32604/cmc.2022.019337

    Abstract During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of… More >

  • Open Access

    ARTICLE

    Structured Graded Lung Rehabilitation for Children with Mechanical Ventilation

    Lei Ren1, Jing Hu2, Mei Li1,*, Ling Zhang2, Jinyue Xia3

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 139-150, 2022, DOI:10.32604/csse.2022.018640

    Abstract Lung rehabilitation is safe and feasible, and it has positive benefits in weaning the machine as soon as possible, shortening the time of hospitalization and improving the prognosis of children with mechanical ventilation. However, at present, the traditional medical concept is deep-rooted, and doctors' understanding of early rehabilitation is inadequate. It is necessary to make in-depth exploration in the relevant guidelines and expert consensus to formulate standardized early rehabilitation diagnosis and treatment procedures and standards for mechanically ventilated children. In the paper, a structured graded lung rehabilitation program is constructed for children with mechanical ventilation… More >

  • Open Access

    ARTICLE

    Breeding Potential of Some Exotic Tomato Lines: A Combined Study of Morphological Variability, Genetic Divergence, and Association of Traits

    Shafiul Islam, Lutful Hassan, Mohammad Anwar Hossain

    Phyton-International Journal of Experimental Botany, Vol.91, No.1, pp. 97-114, 2022, DOI:10.32604/phyton.2022.017251

    Abstract Tomato (Solanum lycopersicum L.) is called ‘the poor man’s orange’ due to its low price and improved nutritional values. An experiment was conducted to study the breeding potential of some exotic tomato lines by assessing various qualitative and quantitative traits conferring yield and quality attributes. Among the qualitative traits, greater variability was observed for growth type, stem hairiness, and fruit shape and size. A determinate growth habit was observed in the genotype AVTO9802 while the genotype AVTO0102 produced yellow color fruits. A significant (p ≤ 0.01) variation was also observed for the studied quantitative traits. Based on… More >

  • Open Access

    ARTICLE

    Impact of Financial Technology on Regional Green Finance

    Zheng Liu1, Juanjuan Song1, Hui Wu2,*, Xiaomin Gu2, Yuanjun Zhao3, Xiaoguang Yue4, Lihua Shi1

    Computer Systems Science and Engineering, Vol.39, No.3, pp. 391-401, 2021, DOI:10.32604/csse.2021.014527

    Abstract Finance is the core of modern economy, and a strong country cannot do without the support of financial system. With the rapid development of economy and society, the traditional financial services can not support the increasingly large and complex economic system. As a brand-new format, financial technology can help the financial industry to restructure and upgrade. At the same time, as an international consensus, green development is the only way for China to achieve sustainable development. Therefore, it is of great practical significance to study the impact of finance on the regional development of green… More >

  • Open Access

    ARTICLE

    Forecasting Model of Photovoltaic Power Based on KPCA-MCS-DCNN

    Huizhi Gou1,2,*, Yuncai Ning1

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 803-822, 2021, DOI:10.32604/cmes.2021.015922

    Abstract Accurate photovoltaic (PV) power prediction can effectively help the power sector to make rational energy planning and dispatching decisions, promote PV consumption, make full use of renewable energy and alleviate energy problems. To address this research objective, this paper proposes a prediction model based on kernel principal component analysis (KPCA), modified cuckoo search algorithm (MCS) and deep convolutional neural networks (DCNN). Firstly, KPCA is utilized to reduce the dimension of the feature, which aims to reduce the redundant input vectors. Then using MCS to optimize the parameters of DCNN. Finally, the photovoltaic power forecasting method More >

  • Open Access

    ARTICLE

    Research on Forecasting Flowering Phase of Pear Tree Based on Neural Network

    Zhenzhou Wang1, Yinuo Ma1, Pingping Yu1,*, Ning Cao2, Heiner Dintera3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3431-3446, 2021, DOI:10.32604/cmc.2021.017729

    Abstract Predicting the blooming season of ornamental plants is significant for guiding adjustments in production decisions and providing viewing periods and routes. The current strategies for observation of ornamental plant booming periods are mainly based on manpower and experience, which have problems such as inaccurate recognition time, time-consuming and energy sapping. Therefore, this paper proposes a neural network-based method for predicting the flowering phase of pear tree. Firstly, based on the meteorological observation data of Shijiazhuang Meteorological Station from 2000 to 2019, three principal components (the temperature factor, weather factor, and humidity factor) with high correlation… More >

  • Open Access

    ARTICLE

    A Learning-based Static Malware Detection System with Integrated Feature

    Zhiguo Chen1,*, Xiaorui Zhang1,2, Sungryul Kim3

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 891-908, 2021, DOI:10.32604/iasc.2021.016933

    Abstract The rapid growth of malware poses a significant threat to the security of computer systems. Analysts now need to examine thousands of malware samples daily. It has become a challenging task to determine whether a program is a benign program or malware. Making accurate decisions about the program is crucial for anti-malware products. Precise malware detection techniques have become a popular issue in computer security. Traditional malware detection uses signature-based strategies, which are the most widespread method used in commercial anti-malware software. This method works well against known malware but cannot detect new malware. To… More >

  • Open Access

    ARTICLE

    Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data

    Samreen Naeem1, Wali Khan Mashwani2,*, Aqib Ali1,3, M. Irfan Uddin4, Marwan Mahmoud5, Farrukh Jamal6, Christophe Chesneau7

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3451-3461, 2021, DOI:10.32604/cmc.2021.015872

    Abstract This study proposes an approach based on machine learning to forecast currency exchange rates by applying sentiment analysis to messages on Twitter (called tweets). A dataset of the exchange rates between the United States Dollar (USD) and the Pakistani Rupee (PKR) was formed by collecting information from a forex website as well as a collection of tweets from the business community in Pakistan containing finance-related words. The dataset was collected in raw form, and was subjected to natural language processing by way of data preprocessing. Response variable labeling was then applied to the standardized dataset,… More >

  • Open Access

    ARTICLE

    A Combined Approach of Principal Component Analysis and Support Vector Machine for Early Development Phase Modeling of Ohrid Trout (Salmo Letnica)

    Sunil Kr. Jha1,*, Ivan Uzunov2, Xiaorui Zhang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 991-1009, 2021, DOI:10.32604/cmes.2021.011821

    Abstract Ohrid trout (Salamo letnica) is an endemic species of fish found in Lake Ohrid in the Former Yugoslav Republic of Macedonia (FYROM). The growth of Ohrid trout was examined in a controlled environment for a certain period, thereafter released into the lake to grow their natural population. The external features of the fish were measured regularly during the cultivation period in the laboratory to monitor their growth. The data mining methods-based computational model can be used for fast, accurate, reliable, automatic, and improved growth monitoring procedures and classification of Ohrid trout. With this motivation, a combined… More >

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