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  • Open Access


    Different Deficit Irrigation Lower Limits and Irrigation Quotas Affect the Yield and Water Use Efficiency of Winter Wheat by Regulating Photosynthetic Characteristics

    Huiqin Li, Mingzhi Zhang*, Na Xiao, Haijian Yang

    Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3211-3236, 2023, DOI:10.32604/phyton.2023.031003

    Abstract To determine suitable thresholds for deficit irrigation of winter wheat in the well-irrigated area of the Huang-Huai-Hai Plain, we investigated the effects of different deficit irrigation lower limits and quotas on the photosynthetic characteristics and grain yield of winter wheat. Four irrigation lower limits were set for initiating irrigation (i.e., light drought (LD, 50%, 55%, 60% and 50% of field holding capacity (FC) at the seedling-regreening, jointing, heading and filling-ripening stages, respectively), medium drought (MD, 40%, 50%, 55% and 45% of FC at the same stages, respectively), adequate moisture (CK1, 60%, 65%, 70% and 60% of FC at the same… More >

  • Open Access


    Improving the Transmission Efficiency of a WSN with the IACO Algorithm

    Wen-Tsai Sung1, Sung-Jung Hsiao2,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1061-1076, 2023, DOI:10.32604/csse.2023.032700

    Abstract The goal of this study is to reduce the energy consumption of the sensing network and enhance the overall life cycle of the network. This study proposes a data fusion algorithm for wireless sensor networks based on improved ant colony optimization (IACO) to reduce the amount of data transmitted by wireless sensor networks (WSN). This study updates pheromones for multiple optimal routes to improve the global optimal route in search function. The algorithm proposed in this study can reduce node energy consumption, improve network load balancing and prolong network life cycle. Through data fusion, regression analysis model and information processing… More >

  • Open Access


    Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

    Wasif Akbar1, Adbul Mannan2, Qaisar Shaheen3,*, Mohammad Hijji4, Muhammad Anwar5, Muhammad Ayaz6

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6269-6286, 2023, DOI:10.32604/cmc.2023.036141

    Abstract Machine Learning (ML) has changed clinical diagnostic procedures drastically. Especially in Cardiovascular Diseases (CVD), the use of ML is indispensable to reducing human errors. Enormous studies focused on disease prediction but depending on multiple parameters, further investigations are required to upgrade the clinical procedures. Multi-layered implementation of ML also called Deep Learning (DL) has unfolded new horizons in the field of clinical diagnostics. DL formulates reliable accuracy with big datasets but the reverse is the case with small datasets. This paper proposed a novel method that deals with the issue of less data dimensionality. Inspired by the regression analysis, the… More >

  • Open Access


    Logistic Regression with Elliptical Curve Cryptography to Establish Secure IoT

    J. R. Arunkumar1,*, S. Velmurugan2, Balarengadurai Chinnaiah3, G. Charulatha4, M. Ramkumar Prabhu4, A. Prabhu Chakkaravarthy5

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2635-2645, 2023, DOI:10.32604/csse.2023.031605

    Abstract Nowadays, Wireless Sensor Network (WSN) is a modern technology with a wide range of applications and greatly attractive benefits, for example, self-governing, low expenditure on execution and data communication, long-term function, and unsupervised access to the network. The Internet of Things (IoT) is an attractive, exciting paradigm. By applying communication technologies in sensors and supervising features, WSNs have initiated communication between the IoT devices. Though IoT offers access to the highest amount of information collected through WSNs, it leads to privacy management problems. Hence, this paper provides a Logistic Regression machine learning with the Elliptical Curve Cryptography technique (LRECC) to… More >

  • Open Access


    Time Series Forecasting Fusion Network Model Based on Prophet and Improved LSTM

    Weifeng Liu1,2, Xin Yu1,*, Qinyang Zhao3, Guang Cheng2, Xiaobing Hou1, Shengqi He4

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3199-3219, 2023, DOI:10.32604/cmc.2023.032595

    Abstract Time series forecasting and analysis are widely used in many fields and application scenarios. Time series historical data reflects the change pattern and trend, which can serve the application and decision in each application scenario to a certain extent. In this paper, we select the time series prediction problem in the atmospheric environment scenario to start the application research. In terms of data support, we obtain the data of nearly 3500 vehicles in some cities in China from Runwoda Research Institute, focusing on the major pollutant emission data of non-road mobile machinery and high emission vehicles in Beijing and Bozhou,… More >

  • Open Access


    Joint Energy Predication and Gathering Data in Wireless Rechargeable Sensor Network

    I. Vallirathi1,*, S. Ebenezer Juliet2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2349-2360, 2023, DOI:10.32604/csse.2023.024864

    Abstract Wireless Sensor Network (WSNs) is an infrastructure-less wireless network deployed in an increasing number of wireless sensors in an ad-hoc manner. As the sensor nodes could be powered using batteries, the development of WSN energy constraints is considered to be a key issue. In wireless sensor networks (WSNs), wireless mobile chargers (MCs) conquer such issues mainly, energy shortages. The proposed work is to produce an energy-efficient recharge method for Wireless Rechargeable Sensor Network (WRSN), which results in a longer lifespan of the network by reducing charging delay and maintaining the residual energy of the sensor. In this algorithm, each node… More >

  • Open Access


    Prediction of Residential Building’s Solar Installation Energy Demand in Morocco Using Multiple Linear Regression Analysis

    Nada Yamoul1,*, Latifa Dlimi1, Baraka Achraf Chakir2

    Energy Engineering, Vol.119, No.5, pp. 2135-2148, 2022, DOI:10.32604/ee.2022.020005

    Abstract The building sector is one of the main energy-consuming sectors in Morocco. In fact, it accounts for 33% of the final consumption of energy and records a high increase in the annual consumption of energy caused by further planned large-scale projects. Indeed, the energy consumption of the building sector is experiencing a significant acceleration justified by the rapid need for the development of housing stock, wich is estimated at an average increase of 1,5% per year; furthermore, tant is an estimated increase of about 6,4%. In this sense, building constitutes an important potential source for rationalizing both energy consumption and… More >

  • Open Access


    Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

    Feslin Anish Mon Solomon1,*, Godfrey Winster Sathianesan2, R. Ramesh3

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1125-1142, 2023, DOI:10.32604/csse.2023.024292

    Abstract Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This is applied greatly in business enterprises and government sectors for delivering the services to their customers, clients and citizens. But, the interaction is successful only based on the trust that each device has on another. Thus trust is very much essential for a social network. As Internet of Things have access over sensitive information, it urges to many threats that lead data management to risk. This issue is addressed by trust management that help to take decision about trustworthiness… More >

  • Open Access


    Restoration of Wind Speed in Qinzhou, Guangxi during Typhoon Rammasun

    Aodi Fu1, Mingxuan Zhu2, Wenzheng Yu1,*, Xin Yao1, Hanxiaoya Zhang3

    Journal on Big Data, Vol.4, No.1, pp. 77-86, 2022, DOI:10.32604/jbd.2022.027477

    Abstract In 2014, Typhoon Rammasun invaded Qinzhou, Guangxi, causing damage to the wind tower sensor at 80 m in Qinzhou. In order to restore the wind speed at 80 m at that time, this paper was based on the hourly average wind speed data of the wind tower and meteorological station from 2017–2019, and constructed the wind speed related model of Meteorological Station and the wind measuring tower in Qinzhou, Moreover, this paper Based on the hourly average wind speed data of Qinzhou Meteorological Station in 2014, Restored the hourly average wind speed of the anemometer tower during Rammasun landfalled. The results showed… More >

  • Open Access


    A Method for Detecting Non-Mask Wearers Based on Regression Analysis

    Dokyung Hwang1, Hyeonmin Ro1, Naejoung Kwak2, Jinsang Hwang3, Dongju Kim1,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378

    Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important to detect facial and mask… More >

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