J. Comput. Methods Sci. Eng.最新文献

Retracted to: Design and dynamics simulation of vehicle active occupant restraint protection system 缩回到:车辆主动乘员约束保护系统的设计与动力学仿真

J. Comput. Methods Sci. Eng. Pub Date : 2023-08-01 DOI: 10.3233/jcm-239002

引用次数: 0

Looking to Personalize Gaze Estimation Using Transformers 寻找个性化的凝视估计使用变压器

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-30 DOI: 10.5626/jcse.2023.17.2.41

Seung-Hoon Choi, Donghyun Son, Yunjong Ha, Yonggyu Kim, Seonghu Hong, Taejung Park

引用次数: 0

Accurate Calibration and Scalable Bandwidth Sharing of Multi-Queue SSDs 多队列ssd的精确校准和可扩展带宽共享

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-30 DOI: 10.5626/jcse.2023.17.2.80

Hyeongseok Kang, Kanghee Kim

引用次数: 0

Using the Structure-Behavior Coalescence Method to Formalize the Action Flow Semantics of UML 2.0 Activity Diagrams 使用结构-行为合并方法形式化UML 2.0活动图的动作流语义

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-30 DOI: 10.5626/jcse.2023.17.2.60

W. H. Steve, Weicong Ma, W. Chao

引用次数: 0

Flip-OFDM Optical MIMO Based VLC System Using ML/DL Approach 基于ML/DL方法的Flip-OFDM光MIMO VLC系统

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-30 DOI: 10.5626/jcse.2023.17.2.71

M. Jha, P. Rubini, Navin Kumar

引用次数: 0

A classification and extraction method of attribute hybrid big data based on Naive Bayes algorithm 基于朴素贝叶斯算法的属性混合大数据分类提取方法

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-15 DOI: 10.3233/jcm-226802

Liantian Li, Ling Yang

{"title":"A classification and extraction method of attribute hybrid big data based on Naive Bayes algorithm","authors":"Liantian Li, Ling Yang","doi":"10.3233/jcm-226802","DOIUrl":"https://doi.org/10.3233/jcm-226802","url":null,"abstract":"In the identification of network text information, the existing technology is difficult to accurately extract and classify text information with high propagation speed and high update speed. In order to solve this problem, the research combines the Naive Bayes algorithm with the feature two-dimensional information gain weighting method, uses the feature weighting method to optimize the Naive Bayes algorithm, and calculates the dimension of different documents and data categories through a new feature operation method. The data gain between them can improve its classification performance, and the classification models are compared and analyzed in the actual Chinese and English databases. The research results show that the classification accuracy rates of the IGDC-DWNB model in the Sogou database, 20-newsgroup database, Fudan database and Ruster21578 database are 0.89, 0.89, 0.93, and 0.88, respectively, which are higher than other classification models in the same environment. It can be seen that the model designed in the research has higher classification accuracy, stronger overall performance, and stronger reliability and robustness in practical applications, which can provide a new development idea for big data classification technology.","PeriodicalId":14668,"journal":{"name":"J. Comput. Methods Sci. Eng.","volume":"30 1","pages":"1955-1970"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82446827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of patent quality on enterprises' export competitiveness under the background of big data and Internet of Things 大数据和物联网背景下专利质量对企业出口竞争力的影响

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-15 DOI: 10.3233/jcm-226784

Qi-Hui Zhang, Jie Jiang

{"title":"Impact of patent quality on enterprises' export competitiveness under the background of big data and Internet of Things","authors":"Qi-Hui Zhang, Jie Jiang","doi":"10.3233/jcm-226784","DOIUrl":"https://doi.org/10.3233/jcm-226784","url":null,"abstract":"After entering the new century, the role of science and technology and innovation in promoting economic development has become increasingly obvious, and the Chinese government has also attached great importance to patent management. With the joint efforts of the people of the whole country, the number of patent applications in China has been among the highest in the world for many consecutive years. However, from the perspective of patent quality, there is still a certain gap with developed countries, resulting in generally low efficiency for Chinese export enterprises. Therefore, it is of great significance to explore the relationship between the quality of patents and the competitiveness of exporting enterprises. Through variance calculation, we constructed a countermeasure system for using intellectual property rights to enhance competitiveness. The experimental results show that the patent quality is proportional to the competitiveness of export enterprises, and the higher the patent quality, the stronger the competitiveness of export enterprises. The development of this study further clarifies the important value of patent quality, which helps export enterprises adjust their development strategies and effectively enhance their competitiveness.","PeriodicalId":14668,"journal":{"name":"J. Comput. Methods Sci. Eng.","volume":"39 1","pages":"2153-2163"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90196685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Internet speech denoising method based on IGAN algorithm 基于IGAN算法的互联网语音去噪方法

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-15 DOI: 10.3233/jcm-226798

Sanchuan Luo

{"title":"Internet speech denoising method based on IGAN algorithm","authors":"Sanchuan Luo","doi":"10.3233/jcm-226798","DOIUrl":"https://doi.org/10.3233/jcm-226798","url":null,"abstract":"At present, to settle the question of excessive noise in the speech signal during the call of mobile devices in China, the research proposes that the Wiener filter and the generative adversarial network are combined into the IGAN algorithm. Firstly, the Wiener filter regularization algorithm is introduced to construct the preprocessing model of the speech signal; then the preprocessing model is fused with the generative adversarial network algorithm to construct the denoising model. Finally, the performance analysis and simulation experiments of the application effect of the model are carried out. The results show that in the experiment comparing IGAN with five traditional algorithms, when the SNR ratio is increased to 17.5 dB, the MOS and PESQ scores under the IGAN method can reach 4.9 and 3.5 respectively, and the DNN effect is second only to IGAN. Other algorithms perform poorly. Then compare the number of iterations and the loss value between the two. When the network voice signal begins to converge, the loss value corresponding to DNN is 1.132; while the loss value of IGAN is about 0.573, it can be found that the loss value of IGAN has dropped by half, which shows that IGAN Build the model with a smaller loss value. And IGAN tends to converge when iteratively is performed for about 200 times, and the average peak SNR can reach up to 33.85 dB, an increase of nearly 1.02 dB, and the effect is remarkable. This all shows that the IGAN algorithm has the best denoising performance for network speech signals, improves the denoising efficiency, and is conducive to obtaining a denoising signal with a higher fit with the clean signal, so that mobile devices can better serve the people.","PeriodicalId":14668,"journal":{"name":"J. Comput. Methods Sci. Eng.","volume":"21 1","pages":"1929-1940"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91052371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EEG signal recognition algorithm with sample entropy and pattern recognition 基于样本熵和模式识别的脑电信号识别算法

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-15 DOI: 10.3233/jcm-226794

Jinsong Tan, Zhuguo Ran, Chunjiang Wan

引用次数: 0

Multi-source heterogeneous data fusion model based on fuzzy mathematics 基于模糊数学的多源异构数据融合模型

J. Comput. Methods Sci. Eng. Pub Date : 2023-06-15 DOI: 10.3233/jcm-226796

Q. Zeng

{"title":"Multi-source heterogeneous data fusion model based on fuzzy mathematics","authors":"Q. Zeng","doi":"10.3233/jcm-226796","DOIUrl":"https://doi.org/10.3233/jcm-226796","url":null,"abstract":"Sensors as the sensing end of intelligent control can be used to collect various data instead of human beings. In the context of technological development, the variety of sensors leads to multiple and structurally unequal data sources, and fusion of these data becomes a problem for consideration. The study constructs an intuitionistic fuzzy transformation method to handle data with various attributes with the help of fuzzy mathematical concepts, which characterizes the data based on the hesitancy and ideal solutions under Gaussian distribution. Simulations of classical classification data show that the intuitionistic fuzzy transformation method can effectively differentiate the affiliation of data points in the dataset, and the results of 800 simulations show that the qualitative accuracy of the algorithm can reach 89%, while the causes of abnormal data are explored and it is found that the attributes of the dataset based on Gaussian distribution are too close to each other as the cause of misclassification; the algorithm is also optimized from multi-dimensional considerations, and a An optimization operator based on the distance method of superior and inferior solutions was constructed and simulated for several optimization paths. The results show that the study uses an optimization scheme that is significantly better than the existing fuzzy operator, and 800 times can improve the accuracy rate up to 95.23%, which is 14.01% higher than that of a single attribute. This indicates that the intuitionistic fuzzy algorithm of this study has some rationality and is able to fuse the data of multiple attributes of the sensor for determination and provide the necessary basis for decision making.","PeriodicalId":14668,"journal":{"name":"J. Comput. Methods Sci. Eng.","volume":"9 1","pages":"2165-2178"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84128383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0