Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machi...Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machine learning methods has recently been used for facilitating ERSI.This paper presents a new approach to improve ERSI by adopting support vector machines,which are proven to be effective tools in pattern classification and regression,on the basis of the spatial distribution of electromagnetic radiation sources.Spatial information is converted from 3D cubes to 1D vectors with subscripts as inputs in order to simplify the model.The model is trained with 187 500 data sets in order to enable it to identify the types of radiation source types with an accuracy of up to 99.9%.The influence of parameters(e.g.,penalty parameter,reflection and noise from the ambient environment,and the scaling method for the input data) are discussed.The proposed method has good performance in noisy and reverberant environment.It has an identification accuracy of 82.15% when the signal-to-noise ratio is 20 dB.The proposed method has better accuracy in a noisy environment than artificial neural networks.Given that each Electromagnetic(EM) source has unique spatial characteristics,this method can be used for EM source identification and EM interference diagnostics.展开更多
The purpose of this study is to explore the urban morphological aspects of cities governed by the juridical regime of emphyteusis, a recurrent situation in the northeastern part of the state of Silo Paulo, Brazil, wit...The purpose of this study is to explore the urban morphological aspects of cities governed by the juridical regime of emphyteusis, a recurrent situation in the northeastern part of the state of Silo Paulo, Brazil, with special attention to the city of Ribeirao Preto. The concession of lands to the Catholic Church was a recurring practice in Brazil during the colonial and imperial periods, when the cities were being established. As these lands were intended for the formation of patrimonial goods to show the devotion of the residents to a Catholic saint, the lands were not allowed to be commercialized. The tenure reveals a relation in which there is an owner--the landlord--who has direct control of the urban land. This owner allows another--the leaseholder--the useful domain of the land, thus giving the latter the right to use the land, the obligation to pay an annual tax and the responsibility to give the owner a percentage of the sales generated from the land. In 1845, farmers donated a tract of land to be used to glorify Silo Sebastiao. This land is now the city of Ribeirao Preto, and it is this conjuncture that defined the structure and the transformation of the original urban form of the current city.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.61201024
文摘Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machine learning methods has recently been used for facilitating ERSI.This paper presents a new approach to improve ERSI by adopting support vector machines,which are proven to be effective tools in pattern classification and regression,on the basis of the spatial distribution of electromagnetic radiation sources.Spatial information is converted from 3D cubes to 1D vectors with subscripts as inputs in order to simplify the model.The model is trained with 187 500 data sets in order to enable it to identify the types of radiation source types with an accuracy of up to 99.9%.The influence of parameters(e.g.,penalty parameter,reflection and noise from the ambient environment,and the scaling method for the input data) are discussed.The proposed method has good performance in noisy and reverberant environment.It has an identification accuracy of 82.15% when the signal-to-noise ratio is 20 dB.The proposed method has better accuracy in a noisy environment than artificial neural networks.Given that each Electromagnetic(EM) source has unique spatial characteristics,this method can be used for EM source identification and EM interference diagnostics.
文摘The purpose of this study is to explore the urban morphological aspects of cities governed by the juridical regime of emphyteusis, a recurrent situation in the northeastern part of the state of Silo Paulo, Brazil, with special attention to the city of Ribeirao Preto. The concession of lands to the Catholic Church was a recurring practice in Brazil during the colonial and imperial periods, when the cities were being established. As these lands were intended for the formation of patrimonial goods to show the devotion of the residents to a Catholic saint, the lands were not allowed to be commercialized. The tenure reveals a relation in which there is an owner--the landlord--who has direct control of the urban land. This owner allows another--the leaseholder--the useful domain of the land, thus giving the latter the right to use the land, the obligation to pay an annual tax and the responsibility to give the owner a percentage of the sales generated from the land. In 1845, farmers donated a tract of land to be used to glorify Silo Sebastiao. This land is now the city of Ribeirao Preto, and it is this conjuncture that defined the structure and the transformation of the original urban form of the current city.
