Yang Zhou, Chunjiao Fu, Yuting Zhai, Jian Li, Ziqi Jin, Yanlei Xu^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4501-4517, 2023, DOI:10.32604/cmc.2023.038446 - 31 March 2023

Abstract Accurate identification of rice diseases is crucial for controlling diseases and improving rice yield. To improve the classification accuracy of rice diseases, this paper proposed a classification and identification method based on an improved ShuffleNet V2 (GE-ShuffleNet) model. Firstly, the Ghost module is used to replace the convolution in the two basic unit modules of ShuffleNet V2, and the unimportant convolution is deleted from the two basic unit modules of ShuffleNet V2. The Hardswish activation function is applied to replace the ReLU activation function to improve the identification accuracy of the model. Secondly, an effective… More >

Zixiong Wang, Qiuying Chen, Sang-Joon Lee^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.037553 - 31 March 2023

Abstract The rapid expansion of the non-fungible token (NFT) market has attracted many investors. However, studies on the NFT price fluctuations have been relatively limited. To date, the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction. The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea, the world’s largest NFT marketplace. We used Python programs to collect data and summarized them as: NFT information, collection information, and related account information. AdaBoost and Random… More >

Richard Cruz¹, Johnson Kinyua^1,*, Charles Mutigwe²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3405-3423, 2023, DOI:10.32604/iasc.2023.035906 - 15 March 2023

Abstract The massive increase in the volume of data generated by individuals on social media microblog platforms such as Twitter and Reddit every day offers researchers unique opportunities to analyze financial markets from new perspectives. The meme stock mania of 2021 brought together stock traders and investors that were also active on social media. This mania was in good part driven by retail investors’ discussions on investment strategies that occurred on social media platforms such as Reddit during the COVID-19 lockdowns. The stock trades by these retail investors were then executed using services like Robinhood. In… More >

Muhammad Jan^1,*, Muhammad Anwar-Ul-Haq², Talha Javed³, Sadam Hussain^4,*, Ilyas Ahmad⁵, Muhammad Ashraf Sumrah⁶, Javed Iqbal⁷, Babar Hussain Babar⁸, Aqsa Hafeez⁹, Muhammad Aslam⁵, Muhammad Tahir Akbar¹⁰, Marjan Aziz⁶, Khadiga Alharbi¹¹, Izhar Ullah¹²

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1361-1375, 2023, DOI:10.32604/phyton.2023.026620 - 09 March 2023

Abstract Abiotic stresses are among the major limiting factors for plant growth and crop productivity. Among these, salinity is one of the major risk factors for plant growth and development in arid to semi-arid regions. Cultivation of salt tolerant crop genotypes is one of the imperative approaches to meet the food demand for increasing population. The current experiment was carried out to access the performance of different rice genotypes under salinity stress and Zinc (Zn) sources. Four rice genotypes were grown in a pot experiment and were exposed to salinity stress (7 dS m⁻¹), and Zn (15… More >

Luqian Zhang^1,#, Xilin Fang^1,#, Nan Yu¹, Jun Chen¹, Haodong Wang¹, Quansheng Shen¹, Guanghui Chen^2,*, Yue Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1571-1587, 2023, DOI:10.32604/phyton.2023.025481 - 09 March 2023

Abstract Drought stress is a serious threat to the germination of plant seeds and the growth of seedlings. Melatonin has been proven to play an important role in alleviating plant stress. However, its effect on seed germination under drought conditions is still poorly understood. Therefore, we studied the effects of melatonin on rice seed germination and physiological characteristics under drought stress. Rice seeds were treated with different concentrations of melatonin (i.e., 0, 20, 100, and 500 μM) and drought stress was simulated with 5% polyethylene glycol 6000 (PEG6000). The results showed that 100 μM melatonin can… More >

Muhammad Sabar^1,2,#, Shahzad Amir Naveed^1,3,4,#,*, Shahid Masood Shah⁵, Abdul Rehman Khan⁵, Muhammad Musaddiq Shah⁶, Tahir Awan¹, Muhammad Ramzan Khan³, Zaheer Abbas³, Muhammad Arif^1,7,*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1421-1438, 2023, DOI:10.32604/phyton.2023.025801 - 09 March 2023

Abstract Drought is one of the major abiotic threat to rice production in the context of climate change. Super Basmati is an elite, fine grain basmati rice variety grown in Punjab, Pakistan. Due to drought sensitive in nature, its yield has been facing an alarming situation in production because of gradual decrease in irrigated water for a couple of years. Three reported novel QTLs for drought tolerance were selected for incorporation into Super Basmati by employing marker assisted selection strategy. IR55419-04 with novel QTLs was used as a donor parent. Foreground selection was performed by applying… More >

N. A. Maidin^1,2, S. M. Sapuan^1,*, M. T. Mastura², M. Y. M. Zuhri¹

Journal of Renewable Materials, Vol.11, No.5, pp. 2381-2397, 2023, DOI:10.32604/jrm.2023.026549 - 13 February 2023

Abstract Natural fibre reinforced polymer composite (NFRPC) materials are gaining popularity in the modern world due to their eco-friendliness, lightweight nature, life-cycle superiority, biodegradability, low cost, and noble mechanical properties. Due to the wide variety of materials available that have comparable attributes and satisfy the requirements of the product design specification, material selection has become a crucial component of design for engineers. This paper discusses the study’s findings in choosing the suitable thermoplastic matrices of Natural Fibre Composites for Cyclist Helmet utilising the DMAIC, and GRA approaches. The results are based on integrating two decision methods More >

Ping-Huan Kuo^1,2, Sing-Yan Chen¹, Her-Terng Yau^1,2,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1577-1596, 2023, DOI:10.32604/csse.2023.036292 - 09 February 2023

Abstract Cars are regarded as an indispensable means of transportation in Taiwan. Several studies have indicated that the automotive industry has witnessed remarkable advances and that the market of used cars has rapidly expanded. In this study, a price prediction system for used BMW cars was developed. Nine parameters of used cars, including their model, registration year, and transmission style, were analyzed. The data obtained were then divided into three subsets. The first subset was used to compare the results of each algorithm. The predicted values produced by the two algorithms with the most satisfactory results… More >

Hae Sun Jung¹, Seon Hong Lee¹, Haein Lee¹, Jang Hyun Kim^2,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2231-2246, 2023, DOI:10.32604/csse.2023.034466 - 09 February 2023

Abstract Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market. As the history of the Bitcoin market is short and price volatility is high, studies have been conducted on the factors affecting changes in Bitcoin prices. Experiments have been conducted to predict Bitcoin prices using Twitter content. However, the amount of data was limited, and prices were predicted for only a short period (less than two years). In this study, data from Reddit and LexisNexis, covering a period of more than four years, were collected. These data were utilized… More >

Ahmed Fathalla¹, Zakaria Alameer², Mohamed Abbas³, Ahmed Ali^4,5,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 929-950, 2023, DOI:10.32604/csse.2023.035255 - 20 January 2023

Abstract The oil industries are an important part of a country’s economy. The crude oil’s price is influenced by a wide range of variables. Therefore, how accurately can countries predict its behavior and what predictors to employ are two main questions. In this view, we propose utilizing deep learning and ensemble learning techniques to boost crude oil’s price forecasting performance. The suggested method is based on a deep learning snapshot ensemble method of the Transformer model. To examine the superiority of the proposed model, this paper compares the proposed deep learning ensemble model against different machine More >