{"title":"Studies of Terahertz Sources and Their Applications","authors":"Sukhmander Singh, Shravan Kumar Meena, Ashish Tyagi, Sanjeev Kumar, Man Raj Meena, Sujit Kumar Saini","doi":"10.5772/intechopen.101685","DOIUrl":"https://doi.org/10.5772/intechopen.101685","url":null,"abstract":"The contributed chapter discuss the applications of terahertz radiations and its generation mechanism through laser plasma interactions. The methods of generation of terahertz radiations from plasma wake field acceleration, higher harmonic generation and the laser beat wave plasma frequency are reviewed. The nonlinear current density oscillate the plasma at beat wave frequency under the effect of ponderomotive force and excite the terahertz radiation at beat wave frequency. The current state of the arts of the methods of generation has been incorporated. The mathematical expression of ponderomotive force has been derived under the influence of gradient of laser fields. In additions, the future challenge and their overcomes are also been discussed.","PeriodicalId":320216,"journal":{"name":"Intelligent Electronics and Circuits - Terahertz, IRS, and Beyond [Working Title]","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124733252","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}
{"title":"Prediction of Large Scale Spatio-temporal Traffic Flow Data with New Graph Convolution Model","authors":"Ke Wang, Tongtong Shi, Rui He, Wubei Yuan","doi":"10.5772/intechopen.101756","DOIUrl":"https://doi.org/10.5772/intechopen.101756","url":null,"abstract":"Prompt and accurate prediction of traffic flow is quite useful. It will help traffic administrator to analyze the road occupancy status and formulate dynamic and flexible traffic control in advance to improve the road capacity. It can also provide more precise navigation guidance for the road users in future. However, it is hard to predict spatiotemporal traffic flow data in large scale promptly with high accuracy caused by complex interrelation and nonlinear dynamic nature. With development of deep learning and other technologies, many prediction networks could predict traffic flow with accumulated historical data in time series. In consideration of the regional characteristics of traffic flow, the emerging Graph Convolutional Network (GCN) model is systematically introduced with representative applications. Those successful applications provide a possible way to contribute fast and proper traffic control strategies that could relieve traffic pressure, reduce potential conflict, fasten emergency response, etc.","PeriodicalId":320216,"journal":{"name":"Intelligent Electronics and Circuits - Terahertz, IRS, and Beyond [Working Title]","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133287970","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}