Transilvania is a province of the actual state of Romania, geographically situated in the middle of the country, in the inner arch of the Carpathians. Starting with the 10th century, the territory of Transilvania beca...Transilvania is a province of the actual state of Romania, geographically situated in the middle of the country, in the inner arch of the Carpathians. Starting with the 10th century, the territory of Transilvania became attractive for the neighboring Hungarian royalty and later on, in the 1 lth century it was annexed into Hungary. For a better control of the newly annexed territory and in order to convert the orthodox population to Catholicism, the Hungarian rulers brought the Szeklers to Transilvania and two centuries later, German originating populations, from Rhine, Luxemburg, and Saxony （the name of Sas people, or Saxon of Transilvania derives from ＂Saxony＂）. The aim of this paper is to focus on the Sighisoara County, namely on the easement of certain areas for temporary or permanent maintenance or use by the church and hospitals in the region. That was a common practice in Medieval Europe aimed at ensuring the survival means for these institutions. However, it was not the only one to serve this goal. There were also donations on behalf of various people or allocations of money by the county authorities. The documents attesting this are unpublished, unedited and are to be found in the archives of the Brasov County, Budapest, and Vienna. They are the stepping stone of this paper and hence, they grant its originality. The objectives of the paper are to bring arguments in favor of the thesis that community money was directed towards meeting the needs of the hospitals, as well as towards supporting the widows, the orphans, and the needy ones. Worth noting in this respect is the management of the funds ceded to the church and county hospitals and that actually benefitted the whole community. Moreover, the paper also emphasizes the role played by education, since the latter is an important landmark for a community＇s development level展开更多
Subspace modeling plays an important role in face recognition. Independent Component Analysis （ICA）, a multivariable statistical analysis technique, can be seen as an extension of traditional Principal Com- ponent A...Subspace modeling plays an important role in face recognition. Independent Component Analysis （ICA）, a multivariable statistical analysis technique, can be seen as an extension of traditional Principal Com- ponent Analysis （PCA） technique, which addresses high order statistics as well as second order statistics. In this paper, a new scheme of subspace-based representation called Discriminant Independent Component Analysis （DICA） is proposed, which combines the strength＂ of unsupervised learning of ICA and supcrvised learning of Linear Discriminant Analysis （LDA）, and efficiently enhances the generalization ability of ICA-based representation method. Based on DICA subspace analysis, a set of optimal vectors called ＂discriminant independent faces＂ are learned from face samples. The effectiveness of our method is demonstrated by performance comparisons with some popular methods such as ICA, PCA, and PCA＋LDA. On the large scale database of IIS, significant improvements are observed when there are fewer training samples per person available.展开更多
文摘Transilvania is a province of the actual state of Romania, geographically situated in the middle of the country, in the inner arch of the Carpathians. Starting with the 10th century, the territory of Transilvania became attractive for the neighboring Hungarian royalty and later on, in the 1 lth century it was annexed into Hungary. For a better control of the newly annexed territory and in order to convert the orthodox population to Catholicism, the Hungarian rulers brought the Szeklers to Transilvania and two centuries later, German originating populations, from Rhine, Luxemburg, and Saxony （the name of Sas people, or Saxon of Transilvania derives from ＂Saxony＂）. The aim of this paper is to focus on the Sighisoara County, namely on the easement of certain areas for temporary or permanent maintenance or use by the church and hospitals in the region. That was a common practice in Medieval Europe aimed at ensuring the survival means for these institutions. However, it was not the only one to serve this goal. There were also donations on behalf of various people or allocations of money by the county authorities. The documents attesting this are unpublished, unedited and are to be found in the archives of the Brasov County, Budapest, and Vienna. They are the stepping stone of this paper and hence, they grant its originality. The objectives of the paper are to bring arguments in favor of the thesis that community money was directed towards meeting the needs of the hospitals, as well as towards supporting the widows, the orphans, and the needy ones. Worth noting in this respect is the management of the funds ceded to the church and county hospitals and that actually benefitted the whole community. Moreover, the paper also emphasizes the role played by education, since the latter is an important landmark for a community＇s development level
基金Supported by the Key Project of the National Natural Science Foundation of China(No.90104030)the National Natural Science Foundation of China(No.60401015)
文摘Subspace modeling plays an important role in face recognition. Independent Component Analysis （ICA）, a multivariable statistical analysis technique, can be seen as an extension of traditional Principal Com- ponent Analysis （PCA） technique, which addresses high order statistics as well as second order statistics. In this paper, a new scheme of subspace-based representation called Discriminant Independent Component Analysis （DICA） is proposed, which combines the strength＂ of unsupervised learning of ICA and supcrvised learning of Linear Discriminant Analysis （LDA）, and efficiently enhances the generalization ability of ICA-based representation method. Based on DICA subspace analysis, a set of optimal vectors called ＂discriminant independent faces＂ are learned from face samples. The effectiveness of our method is demonstrated by performance comparisons with some popular methods such as ICA, PCA, and PCA＋LDA. On the large scale database of IIS, significant improvements are observed when there are fewer training samples per person available.
