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  • Open Access

    ARTICLE

    Analysis of Social Media Impact on Stock Price Movements Using Machine Learning Anomaly Detection

    Richard Cruz1, Johnson Kinyua1,*, Charles Mutigwe2

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

    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 this paper, machine learning models… More >

  • Open Access

    ARTICLE

    Response of Contrasting Rice Genotypes to Zinc Sources under Saline Conditions

    Muhammad Jan1,*, Muhammad Anwar-Ul-Haq2, Talha Javed3, Sadam Hussain4,*, 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

    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 mg kg−1 soil) was… More >

  • Open Access

    ARTICLE

    Melatonin Promotes Rice Seed Germination under Drought Stress by Regulating Antioxidant Capacity

    Luqian Zhang1,#, Xilin Fang1,#, Nan Yu1, Jun Chen1, Haodong Wang1, Quansheng Shen1, Guanghui Chen2,*, Yue Wang1,*

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

    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 effectively improve the germination potential,… More >

  • Open Access

    ARTICLE

    Introgression of Drought Tolerance into Elite Basmati Rice Variety through Marker-Assisted Backcrossing

    Muhammad Sabar1,2,#, Shahzad Amir Naveed1,3,4,#,*, Shahid Masood Shah5, Abdul Rehman Khan5, Muhammad Musaddiq Shah6, Tahir Awan1, Muhammad Ramzan Khan3, Zaheer Abbas3, Muhammad Arif1,7,*

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

    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 PCR based QTL linked SSR… More >

  • Open Access

    ARTICLE

    Materials Selection of Thermoplastic Matrices of Natural Fibre Composites for Cyclist Helmet Using an Integration of DMAIC Approach in Six Sigma Method Together with Grey Relational Analysis Approach

    N. A. Maidin1,2, S. M. Sapuan1,*, 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

    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 implemented utilising two distinct decision-making… More >

  • Open Access

    ARTICLE

    A Multimodel Transfer-Learning-Based Car Price Prediction Model with an Automatic Fuzzy Logic Parameter Optimizer

    Ping-Huan Kuo1,2, Sing-Yan Chen1, Her-Terng Yau1,2,*

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

    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 were used as the input… More >

  • Open Access

    ARTICLE

    Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

    Hae Sun Jung1, Seon Hong Lee1, Haein Lee1, Jang Hyun Kim2,*

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

    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 to estimate and compare the… More >

  • Open Access

    ARTICLE

    A Deep Learning Ensemble Method for Forecasting Daily Crude Oil Price Based on Snapshot Ensemble of Transformer Model

    Ahmed Fathalla1, Zakaria Alameer2, Mohamed Abbas3, Ahmed Ali4,5,*

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

    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 learning and statistical models for… More >

  • Open Access

    ARTICLE

    Price Prediction of Seasonal Items Using Time Series Analysis

    Ahmed Salah1,2, Mahmoud Bekhit3, Esraa Eldesouky4,5, Ahmed Ali4,6,*, Ahmed Fathalla7

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 445-460, 2023, DOI:10.32604/csse.2023.035254

    Abstract The price prediction task is a well-studied problem due to its impact on the business domain. There are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change, but there is very limited work to study the price prediction of seasonal goods (e.g., Christmas gifts). Seasonal items’ prices have different patterns than normal items; this can be linked to the offers and discounted prices of seasonal items. This lack of research studies motivates the current work to investigate the problem of seasonal items’ prices as a time series task.… More >

  • Open Access

    ARTICLE

    Lack of Tocopherol Inhibits Rice Growth by Triggering an Ectopic Stress Response and the Accumulation of DELLA Protein

    Di Wang1,#,*, Hao Gao1,#, Jian Wang1, Baoshan Cheng1, Gang Li1, Weijun Xu1, Xi Liu2,3,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1173-1183, 2023, DOI:10.32604/phyton.2023.026526

    Abstract Although tocopherols are essential for rice development, the molecular details by which their absence affects development remain to be determined. To study how tocopherols function during rice development, we performed a transcriptome deep sequencing (RNA-seq) analysis of the rice cultivar Nipponbare (Nip) and the tocopherol-deficient mutant small grain and dwarf 1-2 (sgd1-2). We identified 563 differentially expressed genes that were enriched in Gene Ontology categories associated with metabolism, stress, cellular responses, and transcriptional regulation. We determined that the total fatty acid composition of Nip and sgd1-2 was comparable, although cell membrane penetrability in sgd1-2 was significantly higher than in Nip… More >

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