Alexander Tcherepnin, a prominent Russian composer living in Paris for most of his life, left an indelible mark on music of the 20th century, reflecting a journey through various musical genres while maintaining an evolving yet internally consistent compositional style. This dissertation explores Tcherepnin's Op. 71, Seven Songs on Chinese Poems, employing an interdisciplinary approach that combines historical analysis with a detailed examination of its musical complexities. Focussing on the historical context illuminates how a new generation of Russian emigré composers navigated the challenges of their living circumstances while embracing the ideology of Eurasia in their musical compositions. Simultaneously, I offer musical analyses that reveal the ways in which Tcherepnin weaves musical folkloric elements into distinctive musical textures, demonstrating his profound appreciation for and insightful understanding of Chinese poetry. Composed in the aftermath of World War II and premiered at the 1946 Prague Spring Festival, the Op. 71 song cycle exemplifies Tcherepnin's pioneering exploration of vocal expressions in Chinese music, reflecting an innovative synthesis of Chinese musical elements acquired during his 1934–37 stay in China. For Tcherepnin, musical folklore transcends mere musical vocabulary; for his compositional approach actually shapes a unique Eurasian musical narrative as a musical response and intervention. Tcherepnin's recognition today remains limited despite his significant contributions, particularly in the vocal genre. The research goals of this dissertation aim to rectify this oversight by showcasing Tcherepnin's innovative embrace of folk idioms, thus enhancing our understanding of his dynamic life and legitimate artistic legacy.

Masters of Science / The multivariate two-sample tests provide a means to test the match between two multivariate distributions. Although many tests exist in the literature, relatively little is known about the relative power of these procedures. The studies reported in the thesis contrasts the effectiveness, in terms of power, of seven such tests with a Monte Carlo study. The relative power of the tests was investigated against location, scale, and correlation alternatives. Samples were drawn from bivariate exponential, normal and uniform populations. Results from the power studies show that there is no single test which is the most powerful in all situations. The use of particular test statistics is recommended for specific alternatives. A possible supplementary non-parametric graphical procedure, such as the Depth-Depth plot, can be recommended for diagnosing possible differences between the multivariate samples, if the null hypothesis is rejected. As an example of the utility of the procedures for real data, the multivariate two-sample tests were applied to photometric data of twenty galactic globular clusters. The results from the analyses support the recommendations associated with specific test statistics.

計算機模型可以描述複雜的物理現象，然而這些模型應用在科學研究時其運算需要很長的時間，而且要有特定的實驗設計才能了解現象的本質。在有缺少一個或數個主效應的情形下，因子設計是不適合的，因為在缺少主效應下時其重複實驗不但不能估計誤差，只是產生重複實驗。雖然已經有學者提出許多可替代的設計，但是大部份設計的計算還是很累贅。本篇論文所提出的一些設計是從旋轉平面的二維因子設計發展而來，這些旋轉因子的設計很容易建構而且保有許多標準因子設計中吸引人的性質：（1）在每個維度的投影是均等空間投影；（2）在迴歸模型中，估計效應是不相關的（即正交的）。這些設計被稱為最大化最小拉丁超方陣，其設計與近期學者建構的最小化內點間距離的準則是同等的。 關鍵字：有效相關（(Effect Correaltion）、拉丁超方陣（Latin Hypercube）、最大化最小距離（Maximin Distance）、最大化最小內點距離（Minimum Interpoint Distance） / Computer models can describe complicated physical phenomena. To use these models for scientific investigation, however, their generally long running times and mostly deterministic nature require a special designed experiment. Standard factorial designs are inadequate; in the absence of one or more main effects, their replication cannot be used to estimate error but instead produces redundancy. A number of alternative designs have been proposed, but many can be burdensome computationally. This paper presents a class of designs developed from the rotation of a two-dimensional factorial design in the plane. These rotated factorial designs are very easy to construct and preserve many of the attractive properties of standard factorial designs: they have equally-spaced projections to univariate dimensions and uncorrelated regression effect estimates (orthogonality) . They also rate comparably to maximin Latin hypercube designs by the minimum interpoint distance criterion used in the latter "s construction. Key Word : Effect Correlation, Latin Hypercube, Maximin Distance, Minimum Interpoint Distance