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Authors: Wang, Jin

Article Type: Research Article

Abstract: Facing COVID-19 epidemic, many countries have recently strengthened epidemic prevention and control measures. The reliability of safety management is of great significance to personnel management and control during the COVID-19 epidemic period. The focus of security management of early warning is to monitor and identify the moving target. The current optical flow method is vulnerable to the influence of light changes and background movement, and it is not very accurate for moving target detection in dynamic complex background. In this paper, aiming at the traditional Lucas Kanade optical flow method, the inter frame difference method, mean shift clustering algorithm and …morphological processing are combined to optimize and improve on the original basis, so that the moving target detection effect in both simple and complex environments is significantly improved. At the same time, the improved algorithm also reduces the execution time to a certain extent, and has a certain resistance to noise interference such as light changes. This has a certain ability test value for personnel control during the epidemic. Show more

Keywords: Lucas Kanade optical flow method, COVID-19, mean shift algorithm, security management, moving target

DOI: 10.3233/JIFS-189293

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8953-8960, 2020

Authors: Wang, Jin

Article Type: Research Article

Abstract: With the advent of the era of big data and artificial intelligence, e-commerce enterprises have used a large number of advanced technologies and knowledge management methods to improve work efficiency. In the context of e-commerce, the innovation of enterprise marketing management model has become one of the important contents of the company’s business development in the e-commerce era. Focusing on the core concept of “e-commerce marketing model innovation”, this paper conducts a comprehensive and systematic research on the e-commerce marketing model innovation of enterprise e-commerce, and focuses on the two aspects of e-commerce marketing model innovation and e-commerce model performance …evaluation. The purpose of this paper is to understand the importance of innovation factors in the innovation of e-commerce marketing models through questionnaires, so as to provide new ideas for the innovation path of e-commerce marketing models. This paper adopts the questionnaire survey method and data analysis method. According to the survey results, 39, 31, 33, and 35 of the respondents believe that market positioning, business strategy, marketing promotion, and operation management should be prioritized as innovative elements, among which market positioning accounts for a relatively high proportion, followed by operation management. It can be seen that most of the respondents believe that in order to innovate the marketing model of e-commerce, we must start from the aspects of market positioning, business strategy, marketing promotion, and operation management. Combined with the era background and related content of big data and artificial intelligence, this paper studies e-commerce and marketing models, so as to provide new ideas for the innovative path of e-commerce marketing models. Show more

Keywords: Big data, artificial intelligence, e-commerce, marketing model

DOI: 10.3233/JCM-226152

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 5, pp. 1721-1727, 2022

Authors: Liu, Shuo | Wang, Jin

Article Type: Research Article

Abstract: Based on the analysis of the artificial intelligence education informatization teaching model for the training of ice and snow talents, this article first builds an artificial intelligence education informatization teaching model, reads and organizes a large number of documents such as big data and personalized teaching of ice and snow talent training. It needs to analyze the existing problems and condense the relevant concepts of educational big data, personalized teaching. We personalized teaching systems based on big data and elaborate on the related theoretical basis. It constructed a visual analysis framework for artificial intelligence teaching data, discussed the realization process …and mechanism of data visualization of mixed ice and snow talent cultivation from the two dimensions of timeliness and media form, and introduced the mixed data of numerical and text for visual processing methods. We discussed the interactive presentation process of the visualization results. The research explores the impact of artificial intelligence on the elements of ice and snow talent training instruction design one by one and uses the paradigm migration analysis framework to prove that the ice and snow talent training instruction design paradigm in the context of artificial intelligence has produced a migration. Show more

Keywords: Bingxue talent training, artificial intelligence, education informatization, model construction and analysis

DOI: 10.3233/JIFS-189380

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3421-3431, 2021

Authors: Wang, Jin-Yun | Liu, Ye-Zheng | Wang, Jin-Kun

Article Type: Research Article

Abstract: The stability and self-adaption for combination texts must be processed in Web Texts Environment. Therefore a language and technology method for self-adapting environment of web texts is needed. To do this, we have built an adaptive data-stream method in which the abnormal data mining process is started. The resource consumption of abnormal data in a text includes the resource consumption of error text and the total resource consumptions of relating with the previously executed texts which are dependent on the error text. In this paper an adaptive data-stream method is applied to implement the Abnormal Data Mining in Web Texts …Environment. Proved by simulation verification, we proposed this adaptive data-stream method is efficient for solving the problem of abnormal data mining in web texts environment. Show more

Keywords: Self-adaption, text environment, state transition, data mining

DOI: 10.3233/JCM-160623

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 16, no. 2, pp. 361-368, 2016

Authors: Su, Gang | Mao, Binchen | Wang, Jin

Article Type: Research Article

Abstract: We have implemented a novel gapped-alignment algorithm to compare Position Frequency Matrices (PFMs) for Transcription Factor Binding Sites. The application compares an input PFM with those collected from public databases and outputs similarity scores, sequence alignments and related PFM clusters. MACO is freely accessible on a web server located at www.nicemice.cn/bioinfo/MACO. Source code is distributed upon request to the authors.

Keywords: Position Frequency Matrix (PFM), gap, alignment, transcription factor binding site (TFBS)

Citation: In Silico Biology, vol. 6, no. 4, pp. 307-310, 2006

Authors: Wang, Jin-liang | Ni, Shao-xiang

Article Type: Research Article

Abstract: Taking Huize County as an example, the paper analyzed the landscape structure(landscape element structure, landscape type structure, landscape spatial structure, landscape succession structure) and the relations between landscape structure and land use. It was pointed out that the agriculture should be developed in harmony with the landscape structure in the study area.

Keywords: landscape structure, land use, agriculture, Yurman Province, China

Citation: Journal of Environmental Sciences, vol. 12, no. 3, pp. 355-360, 2000

Authors: Hui, Kanghua | Ji, Yu | Wang, Jin

Article Type: Research Article

Abstract: Recommender systems have been very important components to prevent people from dwelling in the overwhelming information. In this paper we analyze the difference between item-based recommendation algorithms and SVR-based collaborative filtering algorithms, and it can be found that item-based method performs much better while the data is not sparse significantly, and SVR-based method performs better while the data is dense and small. On this premise we propose a method that can combine the advantages of these two methods by predicting a small part of ratings using SVR method firstly and then predicting the rest of ratings using the item-based algorithm, …which can solve the problem of data sparsity to certain extend. Finally, we evaluate our results compared with the benchmark on different datasets and prove our method’s advantages. Show more

Keywords: Support vector regression, item-based recommendation, collaborative filtering, data sparsity

DOI: 10.3233/JCM-193767

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. 4, pp. 1055-1063, 2019

Authors: Xu, Shuzhen | Wang, Jin | Zhu, Qing

Article Type: Research Article

Abstract: Motivated by a widely studied computer vision task: image inpainting, we became interested in a less concerned problem image outpainting. By which, contents beyond the image boundaries may be extrapolated. In recent years, deep learning methods have achieved remarkable improvements in image inpainting, these techniques can be considered to be applied to image outpainting as solutions. However, many of these inpainting methods generate image blocks generally resulting in blur or smooth. Recently, hallucinating edges for the missing holes before completion has been proved to be a state-of-the-art image inpainting method. Refer to the aforementioned method, we propose a three-phase outpainting …model that consists of an edge generation phase, an image expansion phase and a refinement phase. In order to depict the edge lines more accurately, we adopt a comparatively effective focal loss for edge prediction. An optimization stage with a refinement network is also added since large portions outside the image need to be inferred, and discriminator in this stage works on a decreased patch size with a coarse-to-fine fashion. In addition, with recursive outpainting, an image could be expanded arbitrarily. Experiments show that an image can be effectively expanded by our method, and our outpainting method of predicting edges and then coloring is generally superior to other methods both quantitatively and qualitatively. Show more

Keywords: Outpainting, edge detector, generative adversarial network, focal loss

DOI: 10.3233/JIFS-191310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 371-381, 2020

Authors: Xu, Shuzhen | Wang, Jin | Zhu, Qing

Article Type: Correction

DOI: 10.3233/JIFS-189529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3819-3819, 2021

Authors: Zhang, Tao | Li, Shizheng | Wang, Jin

Article Type: Research Article

Abstract: China has proposed medical couplet body to alleviate residents’ difficulties in seeking medical treatment, and the future development ability of medical couplet body has gradually become a research interest. On the basis of prospect theory, this study constructs a comprehensive evaluation index system with qualitative and quantitative indexes, clear hierarchy, and diverse attribute characteristics. The development ability of medical couplet body is also comprehensively and systematically evaluated. In addition, the evidential reasoning method is proposed on the basis of the equivalent transformation of prospect value. Furthermore, the validity and feasibility of the model are proven through experiments, and the influence …of decision makers’ risk attitude on the evaluation results is discussed. Show more

Keywords: Medical couplet body, prospect theory, evidence reasoning

DOI: 10.3233/JIFS-200883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 137-154, 2021