新媒体杂志(英文)最新文献_第6页

Edge Detection Based on Generative Adversarial Networks 基于生成对抗网络的边缘检测

新媒体杂志(英文) Pub Date : 2020-01-01 DOI: 10.32604/jnm.2020.010062

Xiaoyan Chen, Jiahuan Chen, Zhongcheng Sha

引用次数: 1

Analysis and Prediction of New Media Information Dissemination of Police Microblog 警察微博新媒体信息传播分析与预测

新媒体杂志(英文) Pub Date : 2020-01-01 DOI: 10.32604/jnm.2020.010125

Leyao Chen, Lei Hong, Jiaying Liu

{"title":"Analysis and Prediction of New Media Information Dissemination of Police Microblog","authors":"Leyao Chen, Lei Hong, Jiaying Liu","doi":"10.32604/jnm.2020.010125","DOIUrl":"https://doi.org/10.32604/jnm.2020.010125","url":null,"abstract":": This paper aims to analyze the microblog data published by the official account in a certain province of China, and finds out the rule of Weibo that is easier to be forwarded in the new police media perspective. In this paper, a new topic-based model is proposed. Firstly, the LDA topic clustering algorithm is used to extract the topic categories with forwarding heat from the microblogs with high forwarding numbers, then the Naive Bayesian algorithm is used to topic categories. The sample data is processed to predict the type of microblog forwarding. In order to evaluate this method, a large number of microblog online data is used to analysis. The experimental results show that the proposed method can accurately predict the forwarding of Weibo. on this, we propose an experimental method to predict the forwarding behavior of Weibo. The method is based on the LDA model and is modeled using the Naïve Bayes algorithm for prediction. Experiments show that there are two popular forwarding themes in public security police microblog: social hotspot case notification and life safety. From the final recall and precision of the model, this experimental method has certain accurate prediction ability. Through the predictions of the model, the life warning class (preventing fraud, etc.) is the most popular type of microblog tweets that can be forwarded by users. It can be seen from the displayed topic category keywords that the user forwards relevant content before and after the college entrance examination.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795403","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: 1

An Intelligent Tumors Coding Method Based on Drools 基于Drools的智能肿瘤编码方法

新媒体杂志(英文) Pub Date : 2020-01-01 DOI: 10.32604/jnm.2020.010135

P. Yang, Gang Liu, Xiaoyu Li, Li Qin, Xiaoxia Liu

{"title":"An Intelligent Tumors Coding Method Based on Drools","authors":"P. Yang, Gang Liu, Xiaoyu Li, Li Qin, Xiaoxia Liu","doi":"10.32604/jnm.2020.010135","DOIUrl":"https://doi.org/10.32604/jnm.2020.010135","url":null,"abstract":"In order to solve the problems of low efficiency and heavy workload of tumor coding in hospitals, we proposed a Drools-based intelligent tumors coding method. At present, most tumor hospitals use manual coding, the trained coders follow the main diagnosis selection rules to select the main diagnosis from the discharge diagnosis of the tumor patients, and then code all the discharge diagnoses according to the coding rules. Owing to different coders have different familiarity with the main diagnosis selection rules and ICD-10 disease coding, it will reduce the efficiency of the artificial coding results and affect the quality of the whole medical record. We first analyze the ICD library information, doctor's diagnostic information, radiotherapy information or chemotherapy information, surgery information, hospitalization information and other related information, and then generated Drools rule files based on the main diagnostic selection principles and coding principles, we also combined the text similarity analysis algorithm to construct an intelligent diagnostic information coding method. Practice shows that the coding method can be used to make the work efficiently and at the same time obtain the coding results which meet the standard and have high accuracy, so that the coders can be free from the repeated work and pay more attention to coding quality control and the coding logic adjustment.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795489","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: 3

Research on Prediction Methods of Energy Consumption Data 能源消费数据预测方法研究

新媒体杂志(英文) Pub Date : 2020-01-01 DOI: 10.32604/jnm.2020.09889

Ning Chen, Naernaer Xialihaer, Weiliang Kong, Jiping Ren

引用次数: 5

Overview of Digital Image Restoration 数字图像恢复概述

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/jnm.2019.05803

Wei Chen, Tingzhu Sun, Fangming Bi, Tongfeng Sun, Chaogang Tang, Biruk Assefa

引用次数: 3

Multi-Label Chinese Comments Categorization: Comparison of Multi-Label Learning Algorithms 多标签中文评论分类:多标签学习算法的比较

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/jnm.2019.06238

Jiahui He, Chaozhi Wang, Hongyu Wu, Leiming Yan, Christian Lu

{"title":"Multi-Label Chinese Comments Categorization: Comparison of Multi-Label Learning Algorithms","authors":"Jiahui He, Chaozhi Wang, Hongyu Wu, Leiming Yan, Christian Lu","doi":"10.32604/jnm.2019.06238","DOIUrl":"https://doi.org/10.32604/jnm.2019.06238","url":null,"abstract":"Multi-label text categorization refers to the problem of categorizing text through a multi-label learning algorithm. Text classification for Asian languages such as Chinese is different from work for other languages such as English which use spaces to separate words. Before classifying text, it is necessary to perform a word segmentation operation to convert a continuous language into a list of separate words and then convert it into a vector of a certain dimension. Generally, multi-label learning algorithms can be divided into two categories, problem transformation methods and adapted algorithms. This work will use customer's comments about some hotels as a training data set, which contains labels for all aspects of the hotel evaluation, aiming to analyze and compare the performance of various multi-label learning algorithms on Chinese text classification. The experiment involves three basic methods of problem transformation methods: Support Vector Machine, Random Forest, k-Nearest-Neighbor; and one adapted algorithm of Convolutional Neural Network. The experimental results show that the Support Vector Machine has better performance.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69794966","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: 4

Ground-Based Cloud Recognition Based on Dense_SIFT Features 基于Dense_SIFT特征的地面云识别

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/JNM.2019.05937

Zhizheng Zhang, Jing Feng, Jun Yan, Xiaolei Wang, Xiaocun Shu

引用次数: 3

Review on Video Object Tracking Based on Deep Learning 基于深度学习的视频目标跟踪研究综述

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/jnm.2019.06253

Fangming Bi, Xin Ma, Wei Chen, Weidong Fang, Huayi Chen, Jingru Li, Biruk Assefa

{"title":"Review on Video Object Tracking Based on Deep Learning","authors":"Fangming Bi, Xin Ma, Wei Chen, Weidong Fang, Huayi Chen, Jingru Li, Biruk Assefa","doi":"10.32604/jnm.2019.06253","DOIUrl":"https://doi.org/10.32604/jnm.2019.06253","url":null,"abstract":": Video object tracking is an important research topic of computer vision, which finds a wide range of applications in video surveillance, robotics, human-computer interaction and so on. Although many moving object tracking algorithms have been proposed, there are still many difficulties in the actual tracking process, such as illumination change, occlusion, motion blurring, scale change, self-change and so on. Therefore, the development of object tracking technology is still challenging. The emergence of deep learning theory and method provides a new opportunity for the research of object tracking, and it is also the main theoretical framework for the research of moving object tracking algorithm in this paper. In this paper, the existing deep tracking-based target tracking algorithms are classified and sorted out. Based on the previous knowledge and my own understanding, several solutions are proposed for the existing methods. In addition, the existing deep learning target tracking method is still difficult to meet the requirements of real-time, how to design the network and tracking process to achieve speed and effect improvement, there is still a lot of research space.","PeriodicalId":69198,"journal":{"name":"新媒体杂志(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69795060","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: 14

Preservation Mechanism of Network Electronic Records Based on Broadcast-Storage Network in Urban Construction 城市建设中基于广播存储网络的网络电子档案保存机制

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/jnm.2019.05920

Fujian Zhu, Yongjun Ren, Qirun Wang, Jinyue Xia

引用次数: 0

LDPC Code’s Decoding Algorithms for Wireless Sensor Network: a Brief Review 无线传感器网络LDPC码译码算法综述

新媒体杂志(英文) Pub Date : 2019-01-01 DOI: 10.32604/JNM.2019.05786

Weidong Fang, Wuxiong Zhang, Lianhai Shan, Biruk Assefa, Wei Chen

引用次数: 2