2016 7th International Conference on Computer Science and Information Technology (CSIT)最新文献_第4页

Towards Query By Text Example for pattern spotting in historical documents 基于文本查询的历史文档模式识别方法

2016 7th International Conference on Computer Science and Information Technology (CSIT) Pub Date : 2016-07-01 DOI: 10.1109/CSIT.2016.7549479

A. Cheddad

引用次数: 3

Towards a selfie social network with automatically generated sentiment-bearing hashtags 走向一个带有自动生成情感标签的自拍社交网络

2016 7th International Conference on Computer Science and Information Technology (CSIT) Pub Date : 2016-07-01 DOI: 10.1109/CSIT.2016.7549481

Sara Tedmori, Rashed Al-Lahaseh

{"title":"Towards a selfie social network with automatically generated sentiment-bearing hashtags","authors":"Sara Tedmori, Rashed Al-Lahaseh","doi":"10.1109/CSIT.2016.7549481","DOIUrl":"https://doi.org/10.1109/CSIT.2016.7549481","url":null,"abstract":"Web 2.0 has witnessed increased focus on more user generated content and eventually on data analyzed and queried in meaningful ways. Selfies, a new form of user-generated content, have become an important part of the visual communication in social media. A large portion of images posted on some social networks are selfies. Behind each of these selfies lie the sentiments of the person in the photo posted. The authors of this paper believe that adding quantified sentiment indicators to these selfies can be a valuable addition to not only the social network users but also to the many networks already in existence. Motivated by the idea, the authors propose an addition to social networks that automatically captures the sentiments expressed in selfies as they are being posted. The captured sentiments are then presented along with the selfies' on the users' timeline. In this research, the authors propose Momented, a selfie social network. Momented works by tracking the sentiments expressed in the selfies posted on the Momented social network. Based on the emotions tracked from a particular selfie, the system automatically generates sentiment bearing hashtags. Tthe selfie along with the automatically generated hash tags are posted on the user's dashboard timeline.","PeriodicalId":210905,"journal":{"name":"2016 7th International Conference on Computer Science and Information Technology (CSIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114228363","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

Comparison between the MFCC and DWT applied to the roadway classification MFCC与DWT在巷道分类中的应用比较

2016 7th International Conference on Computer Science and Information Technology (CSIT) Pub Date : 2016-07-01 DOI: 10.1109/CSIT.2016.7549469

Mohamed Atibi, Issam Atouf, M. Boussaa, A. Bennis

{"title":"Comparison between the MFCC and DWT applied to the roadway classification","authors":"Mohamed Atibi, Issam Atouf, M. Boussaa, A. Bennis","doi":"10.1109/CSIT.2016.7549469","DOIUrl":"https://doi.org/10.1109/CSIT.2016.7549469","url":null,"abstract":"Currently, in the field of road safety, research is moving towards the use of electronic driving support systems that are capable of simulating human perception. These systems have more and more facilities, flexibilities and human development, to respond effectively against the delicate situations in the real world, which require the development of more efficient, fast, accurate signal processing and decision algorithms. This paper presents a classification of intelligent real-time roadway into 4 classes: asphalt, gravel, snow-covered road, stone road. This system combines between a descriptor, the acoustic signal produced by the tire-road friction, based either on the Mel Frequency Cepstrum Coefficient algorithm or on the Discrete Wavelet Transform algorithm and a classifier of artificial neuron like Multilayer Perception network. This paper also presents a comparison of results obtained in terms of execution time and in terms of the correct classification for the 2 systems: a system consisting of Mel Frequency Cepstrum Coefficient descriptor and an artificial neuron network classifier Multilayer Perception type and another system composed of a Discrete Wavelet Transform descriptor and the same type of classifier.","PeriodicalId":210905,"journal":{"name":"2016 7th International Conference on Computer Science and Information Technology (CSIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132628532","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: 7

Analysis of the correlation between class stability and maintainability 类稳定性与可维护性的相关性分析

2016 7th International Conference on Computer Science and Information Technology (CSIT) Pub Date : 2016-07-01 DOI: 10.1109/CSIT.2016.7549472

A. Baqais, M. Amro, M. Alshayeb

引用次数: 3