On Two Simple and Effective Procedures for High Dimensional Classification of General Populations

In this paper, we generalize two criteria, the determinant-based and trace-based criteria proposed by Saranadasa (1993), to general populations for high dimensional classification. These two criteria compare some distances between a new observation and several different known groups. The determinant-based criterion performs well for correlated variables by integrating the covariance structure and is competitive to many other existing rules. The criterion however requires the measurement dimension be smaller than the sample size. The trace-based criterion in contrast, is an independence rule and effective in the "large dimension-small sample size" scenario. An appealing property of these two criteria is that their implementation is straightforward and there is no need for preliminary variable selection or use of turning parameters. Their asymptotic misclassification probabilities are derived using the theory of large dimensional random matrices. Their competitive performances are illustrated by intensive Monte Carlo experiments and a real data analysis.Comment: 5 figures; 22 pages. To appear in "Statistical Papers

Maps as a visual language: A Chinese perspective

One primary goal of cartographic research is to improve cartographic communication. Psychophysical and cognitive research has assisted our understanding of the map use process. The present study is from a perspective of maps as a visual language. This study hypothesizes that (1) the map symbol system constitutes a visual ideographic language and (2) cartographic communication may be improved by applying the methods of teaching visual ideographic languages as a second language. Chinese script originated in primitive drawings of concrete things--pictographs--and ideographs. These became stylized and combined, and were expanded greatly in number. Although the characters came to include phonetic symbols, the script can be used as a completely visual language and is not structured as a parallel to the phonetic language as are alphabetic languages. Furthermore, written Chinese is processed mentally much more holistically and requires more reader-origin organization than alphabetic languages. maps have all the fundamental attributes of Chinese writing. maps with their many non-phonetic symbols are essentially visual. Both cartographic symbols and early Chinese characters are often mimetic. To understand maps, symbols must be put into relation with other symbols that are not arranged linearly. Similarly, to understand Chinese, each. character must be put into relation with other characters that can be sequenced vertically or horizontally and left to right or right to left. Studies of teaching Chinese as a Second Language stress that a variety of approaches are necessary in teaching such a complex, high-level cognitive process. The basics of lexicon and syntax need rote learning, substitution exercises and much experience. All these components and approaches could be applied to a map use teaching programme. (Abstract shortened by UMI.

The trend of regional income disparity in the People's Republic of China

Based on recent updated statistical data that has become available since the People's Republic of China (PRC) implemented its first national economic census in 2004, this paper studies the trend of regional disparity both among and within the provinces of the PRC from 1978 to 2005. We find that compared with the 1990s, the expansive trend of inter-provincial disparities has slowed down and started to decrease somewhat since 2000. In 2004 and 2005, some statistical indicators, such as per capita GDP and per capita household consumption at current prices, show that regional disparities have declined to a certain extent. In addition to the great disparity among provinces, disparities within provinces are also very common in the PRC. Judged by some measurement indexes, income disparities within many provinces have even exceeded inter-provincial disparities. The results of decomposing the regional disparity into within-group and between-group components suggested that the urban-rural disparities are the main source of regional disparities. The results further suggested that disparities among the PRC's four regions, especially between the eastern region and the other regions, are mainly to blame for interprovincial disparities. Finally, this paper finds that changes in regional disparities in recent years can be attributed to many factors, including policies and regional specific factors as well as some cyclical factors. For this reason, we still cannot claim that the PRC's regional disparities have started a decline that will continue

An improved MOEA/D algorithm for multi-objective multicast routing with network coding

Network coding enables higher network throughput, more balanced traffic, and securer data transmission. However, complicated mathematical operations incur when packets are combined at intermediate nodes, which, if not operated properly, lead to very high network resource consumption and unacceptable delay. Therefore, it is of vital importance to minimize various network resources and end-to-end delays while exploiting promising benefits of network coding. Multicast has been used in increasingly more applications, such as video conferencing and remote education. In this paper the multicast routing problem with network coding is formulated as a multi-objective optimization problem (MOP), where the total coding cost, the total link cost and the end-to-end delay are minimized simultaneously. We adapt the multi-objective evolutionary algorithm based on decomposition (MOEA/D) for this MOP by hybridizing it with a population-based incremental learning technique which makes use of the global and historical information collected to provide additional guidance to the evolutionary search. Three new schemes are devised to facilitate the performance improvement, including a probability-based initialization scheme, a problem-specific population updating rule, and a hybridized reproduction operator. Experimental results clearly demonstrate that the proposed algorithm outperforms a number of state-of-the-art MOEAs regarding the solution quality and computational time

Optimized Live 4K Video Multicast

4K videos are becoming increasingly popular. However, despite advances in wireless technology, streaming 4K videos over mmWave to multiple users is facing significant challenges arising from directional communication, unpredictable channel fluctuation and high bandwidth requirements. This paper develops a novel 4K layered video multicast system. We (i) develop a video quality model for layered video coding, (ii) optimize resource allocation, scheduling, and beamforming based on the channel conditions of different users, and (iii) put forward a streaming strategy that uses fountain code to avoid redundancy across multicast groups and a Leaky-Bucket-based congestion control. We realize an end-to-end system on commodity-off-the-shelf (COTS) WiGig devices. We demonstrate the effectiveness of our system with extensive testbed experiments and emulation

Neural Video Recovery for Cloud Gaming

Cloud gaming is a multi-billion dollar industry. A client in cloud gaming sends its movement to the game server on the Internet, which renders and transmits the resulting video back. In order to provide a good gaming experience, a latency below 80 ms is required. This means that video rendering, encoding, transmission, decoding, and display have to finish within that time frame, which is especially challenging to achieve due to server overload, network congestion, and losses. In this paper, we propose a new method for recovering lost or corrupted video frames in cloud gaming. Unlike traditional video frame recovery, our approach uses game states to significantly enhance recovery accuracy and utilizes partially decoded frames to recover lost portions. We develop a holistic system that consists of (i) efficiently extracting game states, (ii) modifying H.264 video decoder to generate a mask to indicate which portions of video frames need recovery, and (iii) designing a novel neural network to recover either complete or partial video frames. Our approach is extensively evaluated using iPhone 12 and laptop implementations, and we demonstrate the utility of game states in the game video recovery and the effectiveness of our overall design