The Basic Connotation and Practice Path of College Students’ Spiritual Life and Common Prosperity

Common prosperity is the essence of socialism, and common prosperity of spiritual life is the due meaning of common prosperity. When young people prosper, the country prospers, and when young people are strong, the country is strong. College students, as builders and successors of the great practice of socialism with Chinese characteristics, promote the common prosperity of college students’ spiritual life is necessary for the rejuvenation of the great responsibility of the nation, and meets the realistic expectations of college students’ needs for a better life. New era, new journey. In the face of great changes unseen in a century, contemporary college students should grasp the importance of ideals, beliefs, moral cultivation and cultural self-confidence, so as to construct a learning consciousness, implement socialist core values, strengthen ideological and political education, carry forward the great spirit of struggle, and finally realize the common prosperity of college students’ spiritual life. This is of great significance for China to build a great modern socialist country and realize the great rejuvenation of the Chinese nation

Data acquisition via RS-232 and universal serial bus from a field programmable gate array

A Field Programmable Gate Array (FPGA) offers a flexible solution for transferring data obtained from hardware to a PC for analysis and storage. Traditionally, an RS-232 serial interface is used to connect hardware to the PC. The RS-232 protocol is straightforward to implement with minimum hardware support. However, the presence of the Universal Serial Bus (USB) protocol has largely replaced traditional RS-232 communications, mainly due to a higher data rate and ease of configuration. In this thesis, models for the FPGA to send data in memory via RS-232 and USB were developed, as well as programs on the PC to accept those data streams. By using timing alone (no bidirectional communication), the RS-232 model could send data up to 36.9 kbps where as the USB model achieved a data rate of 702.6 kbps. By using the TXE pin and writing data only when the chip was ready, a 3.17 Mbps transfer rate was achieved.http://archive.org/details/datacquisitionvi109454496US Navy (USN) author.Approved for public release; distribution is unlimited

GIS-Based Local Ordered Weighted Averaging: A Case Study in London, Ontario

GIS-based multicriteria analysis is a procedure for combining a set of criterion maps and associated criterion weights to obtain overall value for each spatial unit (location) in the study area. Ordered Weighted Averaging (OWA) is a generic algorithm of the multicriteria analysis. It has been integrated into GIS and applied for tackling a wide range of spatial problems. However, the conventional OWA method is based on an assumption of spatial homogeneity of its parameters. Therefore, it is referred to as a global model. This thesis proposes a local form OWA. The local model is based on the range sensitivity principle. A case study of examining spatial patterns of socioeconomic status in London, Ontario is presented. The results show that there are substantial differences between the spatial patterns generated by the global and local OWA methods

Optimal linear estimation under unknown nonlinear transform

Linear regression studies the problem of estimating a model parameter $\beta^* \in \mathbb{R}^p$, from $n$ observations $\{(y_i,\mathbf{x}_i)\}_{i=1}^n$ from linear model $y_i = \langle \mathbf{x}_i,\beta^* \rangle + \epsilon_i$. We consider a significant generalization in which the relationship between $\langle \mathbf{x}_i,\beta^* \rangle$ and $y_i$ is noisy, quantized to a single bit, potentially nonlinear, noninvertible, as well as unknown. This model is known as the single-index model in statistics, and, among other things, it represents a significant generalization of one-bit compressed sensing. We propose a novel spectral-based estimation procedure and show that we can recover $\beta^*$ in settings (i.e., classes of link function $f$) where previous algorithms fail. In general, our algorithm requires only very mild restrictions on the (unknown) functional relationship between $y_i$ and $\langle \mathbf{x}_i,\beta^* \rangle$. We also consider the high dimensional setting where $\beta^*$ is sparse ,and introduce a two-stage nonconvex framework that addresses estimation challenges in high dimensional regimes where $p \gg n$. For a broad class of link functions between $\langle \mathbf{x}_i,\beta^* \rangle$ and $y_i$, we establish minimax lower bounds that demonstrate the optimality of our estimators in both the classical and high dimensional regimes.Comment: 25 pages, 3 figure