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  • Open Access

    ARTICLE

    Color and Gloss Changes of a Lignin-Based Polyurethane Coating under Accelerated Weathering

    Fatemeh Hassani Khorshidi1, Saeed Kazemi Najafi1, Farhood Najafi2,*, Antonio Pizzi3,*, Dick Sandberg4, Rabi Behrooz1

    Journal of Renewable Materials, Vol.12, No.2, pp. 305-323, 2024, DOI:10.32604/jrm.2023.043953

    Abstract The purpose of this research study was to investigate the properties of polyurethane coatings based on lignin nano-particles. For this purpose, the prepared coatings were applied to pine wood surfaces and weathered artificially. Subsequently, color and gloss of the coatings were measured before and after the weathering test. Field emission scanning electron microscopy (FE-SEM) micrographs prepared from the coatings showed that the average size of nano-particles in the polyurethane substrate was approximately 500 nm. Nuclear magnetic resonance (13C-NMR) spectroscopy showed that strong urethane bonds were formed in the nano-lignin-based polyurethane. Differential calorimetric analysis (DSC) test revealed that the glass-transition temperature… More > Graphic Abstract

    Color and Gloss Changes of a Lignin-Based Polyurethane Coating under Accelerated Weathering

  • Open Access

    ARTICLE

    Analysis of CLARANS Algorithm for Weather Data Based on Spark

    Jiahao Zhang, Honglin Wang*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2427-2441, 2023, DOI:10.32604/cmc.2023.038462

    Abstract With the rapid development of technology, processing the explosive growth of meteorological data on traditional standalone computing has become increasingly time-consuming, which cannot meet the demands of scientific research and business. Therefore, this paper proposes the implementation of the parallel Clustering Large Application based upon RANdomized Search (CLARANS) clustering algorithm on the Spark cloud computing platform to cluster China’s climate regions using meteorological data from 1988 to 2018. The aim is to address the challenge of applying clustering algorithms to large datasets. In this paper, the morphological similarity distance is adopted as the similarity measurement standard instead of Euclidean distance,… More >

  • Open Access

    ARTICLE

    T_GRASP: Optimization Algorithm of Ship Avoiding Typhoon Route

    Yingxian Huang, Xueyan Ding, Yanan Zhang, Leiming Yan*

    Journal of Quantum Computing, Vol.4, No.2, pp. 85-95, 2022, DOI:10.32604/jqc.2022.031436

    Abstract A GRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation. One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon. Currently, the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise. The distribution of heavy winds and waves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution, which significantly enhances the challenge of the captain’s preparation for avoiding typhoon navigation. It is now… More >

  • Open Access

    ARTICLE

    Artificial Neural Network-Based Development of an Efficient Energy Management Strategy for Office Building

    Payal Soni, J. Subhashini*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1225-1242, 2023, DOI:10.32604/iasc.2023.038155

    Abstract In the current context, a smart grid has replaced the conventional grid through intelligent energy management, integration of renewable energy sources (RES) and two-way communication infrastructures from power generation to distribution. Energy management from the distribution side is a critical problem for balancing load demand. A unique energy management strategy (EMS) is being developed for office building equipment. That includes renewable energy integration, automation, and control based on the Artificial Neural Network (ANN) system using Matlab Simulink. This strategy reduces electric power consumption and balances the load demand of the traditional grid. This strategy is developed by taking inputs from… More >

  • Open Access

    ARTICLE

    Wind Speed Prediction Using Chicken Swarm Optimization with Deep Learning Model

    R. Surendran1,*, Youseef Alotaibi2, Ahmad F. Subahi3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3371-3386, 2023, DOI:10.32604/csse.2023.034465

    Abstract High precision and reliable wind speed forecasting have become a challenge for meteorologists. Convective events, namely, strong winds, thunderstorms, and tornadoes, along with large hail, are natural calamities that disturb daily life. For accurate prediction of wind speed and overcoming its uncertainty of change, several prediction approaches have been presented over the last few decades. As wind speed series have higher volatility and nonlinearity, it is urgent to present cutting-edge artificial intelligence (AI) technology. In this aspect, this paper presents an intelligent wind speed prediction using chicken swarm optimization with the hybrid deep learning (IWSP-CSODL) method. The presented IWSP-CSODL model… More >

  • Open Access

    ARTICLE

    Improvements in Weather Forecasting Technique Using Cognitive Internet of Things

    Kaushlendra Yadav*, Anuj Singh, Arvind Kumar Tiwari

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3767-3782, 2023, DOI:10.32604/csse.2023.033991

    Abstract Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate. However, effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and technology. The primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any damage. Currently, most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the atmosphere. In this work, sensors are used to collect real-time data for a particular location to capture the… More >

  • Open Access

    ARTICLE

    Evaluation of Weathering Performance of Rosin-Copper Based Treated Wood

    Thi Thanh Hien Nguyen1,*, Nho Quyet Tran2, Thi Minh Nguyet Nguyen1, Hien Mai Trinh1, Xuan Phuong Le1, Trong Kien Nguyen1

    Journal of Renewable Materials, Vol.10, No.11, pp. 2765-2780, 2022, DOI:10.32604/jrm.2022.019634

    Abstract This study aimed to evaluate the effect of natural weathering on some surface characteristics and mechanical properties of Styrax wood treated with mixtures of 1.0%, 2.0%, or 4.0% rosin sizing agent and 3% copper sulfate. Wood samples after treatment were exposed to outdoor conditions for one year and changes in color, glossiness, weight loss, compression strength parallel to grain (CSPG), modulus of rupture (MOR), and modulus of elasticity (MOE) were investigated after 6 and 12-month of natural weathering. The results showed that rosin-copper treatment could improve color stability and gloss of samples after weathering. Mass losses of all rosin-copper treated… More > Graphic Abstract

    Evaluation of Weathering Performance of Rosin-Copper Based Treated Wood

  • Open Access

    ARTICLE

    Weather Forecasting Prediction Using Ensemble Machine Learning for Big Data Applications

    Hadil Shaiba1, Radwa Marzouk2, Mohamed K Nour3, Noha Negm4,5, Anwer Mustafa Hilal6,*, Abdullah Mohamed7, Abdelwahed Motwakel6, Ishfaq Yaseen6, Abu Sarwar Zamani6, Mohammed Rizwanullah6

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3367-3382, 2022, DOI:10.32604/cmc.2022.030067

    Abstract The agricultural sector’s day-to-day operations, such as irrigation and sowing, are impacted by the weather. Therefore, weather constitutes a key role in all regular human activities. Weather forecasting must be accurate and precise to plan our activities and safeguard ourselves as well as our property from disasters. Rainfall, wind speed, humidity, wind direction, cloud, temperature, and other weather forecasting variables are used in this work for weather prediction. Many research works have been conducted on weather forecasting. The drawbacks of existing approaches are that they are less effective, inaccurate, and time-consuming. To overcome these issues, this paper proposes an enhanced… More >

  • Open Access

    ARTICLE

    Study on Recognition Method of Similar Weather Scenes in Terminal Area

    Ligang Yuan1,*, Jiazhi Jin1, Yan Xu2, Ningning Zhang3, Bing Zhang4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1171-1185, 2023, DOI:10.32604/csse.2023.027221

    Abstract Weather is a key factor affecting the control of air traffic. Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air traffic flow management. Current researches mostly use traditional machine learning methods to extract features of weather scenes, and clustering algorithms to divide similar scenes. Inspired by the excellent performance of deep learning in image recognition, this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering (IDCEC), which uses the combination of the encoding layer and the decoding layer to reduce the dimensionality… More >

  • Open Access

    ARTICLE

    Modeling of the Photovoltaic Module Operating Temperature for Various Weather Conditions in the Tropical Region

    Mame Cheikh Diouf1, Mactar Faye1,2,*, Ababacar Thiam1,2, Alphousseyni Ndiaye1,2, Vincent Sambou2

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.5, pp. 1275-1284, 2022, DOI:10.32604/fdmp.2022.021972

    Abstract The operating temperature is a critical factor affecting the performances of photovoltaic (PV) modules. In this work, relevant models are proposed for the prediction of this operating temperature using data (ambient temperature and solar irradiance) based on real measurements conducted in the tropical region. For each weather condition (categorized according to irradiance and temperature levels), the temperatures of the PV modules obtained using the proposed approach is compared with the corresponding experimentally measured value. The results show that the proposed models have a smaller Root Mean Squared Error than other models developed in the literature for all weather conditions, which… More >

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