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  • Open Access

    PROCEEDINGS

    A Fast Direct Boundary Element Method for 3D Acoustic Problems Based on Hierarchical Matrices

    Ruoyan Li1,2, Yijun Liu1,*, Wenjing Ye2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09472

    Abstract The boundary element method (BEM) for acoustic problems is a numerical method based on solving the discretized boundary integral equation (BIE) corresponding to the Helmholtz equation. A fast direct BEM for 3D acoustic problems is proposed in this paper, which is more suitable for broadband acoustic simulation of complex structures, such as in the design and analysis of acoustic metamaterials. The main idea of the fast direct solver is based on the hierarchical off-diagonal low-rank (HODLR) matrix, randomized interpolative decomposition and fast matrix inversion formula. Several numerical examples in solving both interior and exterior acoustic problems are presented in this… More >

  • Open Access

    ARTICLE

    Hybridized Intelligent Neural Network Optimization Model for Forecasting Prices of Rubber in Malaysia

    Shehab Abdulhabib Alzaeemi1, Saratha Sathasivam2,*, Majid Khan bin Majahar Ali2, K. G. Tay1, Muraly Velavan3

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1471-1491, 2023, DOI:10.32604/csse.2023.037366

    Abstract Rubber producers, consumers, traders, and those who are involved in the rubber industry face major risks of rubber price fluctuations. As a result, decision-makers are required to make an accurate estimation of the price of rubber. This paper aims to propose hybrid intelligent models, which can be utilized to forecast the price of rubber in Malaysia by employing monthly Malaysia’s rubber pricing data, spanning from January 2016 to March 2021. The projected hybrid model consists of different algorithms with the symbolic Radial Basis Functions Neural Network k-Satisfiability Logic Mining (RBFNN-kSAT). These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony… More >

  • Open Access

    ARTICLE

    Computation of PoA for Selfish Node Detection and Resource Allocation Using Game Theory

    S. Kanmani1,*, M. Murali2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2583-2598, 2023, DOI:10.32604/csse.2023.037265

    Abstract The introduction of new technologies has increased communication network coverage and the number of associating nodes in dynamic communication networks (DCN). As the network has the characteristics like decentralized and dynamic, few nodes in the network may not associate with other nodes. These uncooperative nodes also known as selfish nodes corrupt the performance of the cooperative nodes. Namely, the nodes cause congestion, high delay, security concerns, and resource depletion. This study presents an effective selfish node detection method to address these problems. The Price of Anarchy (PoA) and the Price of Stability (PoS) in Game Theory with the Presence of… More >

  • Open Access

    ARTICLE

    Towards Intelligent Detection and Classification of Rice Plant Diseases Based on Leaf Image Dataset

    Fawad Ali Shah1, Habib Akbar1, Abid Ali2,3, Parveen Amna4, Maha Aljohani5, Eman A. Aldhahri6, Harun Jamil7,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1385-1413, 2023, DOI:10.32604/csse.2023.036144

    Abstract The detection of rice leaf disease is significant because, as an agricultural and rice exporter country, Pakistan needs to advance in production and lower the risk of diseases. In this rapid globalization era, information technology has increased. A sensing system is mandatory to detect rice diseases using Artificial Intelligence (AI). It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases. Deep Neural Network (DNN) is a novel technique that will help detect disease present on a rice leave because DNN is also considered… More >

  • Open Access

    ARTICLE

    TCD5 Enhances the Photosynthesis Capacity, Increases the Panicle Number and the Yield in Rice

    Jing Yang1,2, Yufeng Wang2, Zhanghua Hu3, Xiaoping Chen4, Yanjun Dong5,*, Sheng Teng1,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2649-2663, 2023, DOI:10.32604/phyton.2023.030710

    Abstract Improvement of photosynthetic efficiency is a major approach to increase crop yield potential. Previously, we cloned a gene encoding the chloroplast-located putative monooxygenase TCD5, which is essential in plastid development under low temperature in rice (Oryza sativa L.). In this study, the effects of TCD5 on the photosynthesis and the yields were investigated in rice. Two sets of genetic materials with three levels of TCD5 expression, including tcd5 mutant or TCD5 RNAi transgenic lines and TCD5 over-expression transgenic lines in Jiahua1 and Nipponbare backgrounds, were used in the field trails of multi-locations and multi-years. TCD5 positively affected the panicle number… More >

  • Open Access

    ARTICLE

    A Model Average Algorithm for Housing Price Forecast with Evaluation Interpretation

    Jintao Fu1, Yong Zhou1,*, Qian Qiu2, Guangwei Xu3, Neng Wan3

    Journal of Quantum Computing, Vol.4, No.3, pp. 147-163, 2022, DOI:10.32604/jqc.2022.038358

    Abstract In the field of computer research, the increase of data in result of societal progress has been remarkable, and the management of this data and the analysis of linked businesses have grown in popularity. There are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home prices. Using regression methods in machine learning to segment the data set, examine the major factors affecting it, and forecast home prices is the most popular method for examining pricing information. It is challenging to generate precise forecasts since many of the regression… More >

  • Open Access

    ARTICLE

    Cloning of and analysis of cadmium resistant in Potentilla sericea

    ZHENGHONG FENG1, BING GAO1, YU GAO2, JIANHUI WU1,*

    BIOCELL, Vol.47, No.7, pp. 1571-1582, 2023, DOI:10.32604/biocell.2023.029106

    Abstract Background:Potentilla sericea is a heavy metal hyperaccumulator landscaping plant. MYB transcription factors play an important role in regulating plant stress response to adversity. However, there are few studies on MYB transcription factors in stress tolerance in Potentilla sericea. In this study, the gene was successfully cloned from Potentilla sericea. Methods: Bioinformatic analysis and real-time quantitative PCR (qPCR) methods were used to evaluate this gene. The transgenic A. thaliana were obtained by flower dipping and the gene function was identified by determining physiological indicators under cadmium stress. Results: The open reading frame of is 942 bp, which encodes 313 amino acids… More >

  • Open Access

    ARTICLE

    Hyperparameter Optimization for Capsule Network Based Modified Hybrid Rice Optimization Algorithm

    Zhiwei Ye1, Ziqian Fang1, Zhina Song1,*, Haigang Sui2, Chunyan Yan1, Wen Zhou1, Mingwei Wang1

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2019-2035, 2023, DOI:10.32604/iasc.2023.039949

    Abstract Hyperparameters play a vital impact in the performance of most machine learning algorithms. It is a challenge for traditional methods to configure hyperparameters of the capsule network to obtain high-performance manually. Some swarm intelligence or evolutionary computation algorithms have been effectively employed to seek optimal hyperparameters as a combinatorial optimization problem. However, these algorithms are prone to get trapped in the local optimal solution as random search strategies are adopted. The inspiration for the hybrid rice optimization (HRO) algorithm is from the breeding technology of three-line hybrid rice in China, which has the advantages of easy implementation, less parameters and… More >

  • Open Access

    ARTICLE

    Modeling Price-Aware Session-Based Recommendation Based on Graph Neural Network

    Jian Feng*, Yuwen Wang, Shaojian Chen

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 397-413, 2023, DOI:10.32604/cmc.2023.038741

    Abstract Session-based Recommendation (SBR) aims to accurately recommend a list of items to users based on anonymous historical session sequences. Existing methods for SBR suffer from several limitations: SBR based on Graph Neural Network often has information loss when constructing session graphs; Inadequate consideration is given to influencing factors, such as item price, and users’ dynamic interest evolution is not taken into account. A new session recommendation model called Price-aware Session-based Recommendation (PASBR) is proposed to address these limitations. PASBR constructs session graphs by information lossless approaches to fully encode the original session information, then introduces item price as a new… More >

  • Open Access

    ARTICLE

    La relaxation psychanalytique Sapir : une expérience formatrice pour les soignants ?

    A.-M. Bourdot

    Psycho-Oncologie, Vol.16, No.1, pp. 206-211, 2022, DOI:10.3166/pson-2022-0186

    Abstract L’engouement pour les différentes approches corporelles dans le soin invite à les interroger comme expé- rience formatrice pour les soignants. Prenant pour appui la relaxation psychanalytique Sapir, nous désirons par les liens théoricocliniques en montrer l’intérêt pour questionner et ressentir la relation de soins. Pratiquée auprès des soignants, la relaxation psychanalytique Sapir permettrait d’éprouver l’engagement nécessaire à la relation de soins et les difficultés qu’elle engendre. More >

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