Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images

In this paper, we propose an L1 normalized graph based dimensionality reduction method for Hyperspectral images, called as L1-Scaling Cut (L1-SC). The underlying idea of this method is to generate the optimal projection matrix by retaining the original distribution of the data. Though L2-norm is generally preferred for computation, it is sensitive to noise and outliers. However, L1-norm is robust to them. Therefore, we obtain the optimal projection matrix by maximizing the ratio of between-class dispersion to within-class dispersion using L1-norm. Furthermore, an iterative algorithm is described to solve the optimization problem. The experimental results of the HSI classification confirm the effectiveness of the proposed L1-SC method on both noisy and noiseless data.Comment: European Signal Processing Conference 201

Platforms, network effects and small business dynamics in China : case study of the Shanzhai cell phone industry

This paper seeks to argue the significance of platforms on emerging markets through a case study of the Shanzhai cell phone industry in Shenzhen, China. In this industry, value chains are being driven by both the technology platforms and the market platforms. The former include MTK baseband chipset, and so-called Shared PCBA and Shared Mould. The latter include the North Huaqiang Market and the Purchasing and Money Platform. Technology platforms greatly reduced the technological barriers to entry for independent design houses and system integrators, while market platforms markedly improved their poor marketing and purchasing abilities. Due to factors such as social networks, supporting industries, informality and platform governance, strong network effects have been exhibited in the two types of platforms, which have not only fostered numerous start-ups, but have also led to effective exploitation of emerging markets.China, Electronic industries, Telephone, Network, Platform, Network effect, Shanzhai Cell Phone, Emerging markets

Distribution System of China\u27s Industrial Clusters: Case Study of Yiwu China Commodity City

This paper discusses the issue of upgrading industrial clusters from the perspective of external linkages. It is taken for granted that in most developing countries, due to the limited domestic market and poor traditional commercial networks, industrial clusters are able to upgrade only when they are involved in global value chains. However, the rise of China’s industrial clusters challenges this view. Historically, China has had a lot of industrial clusters with their own traditional commercial networks. This fact combined with its huge population resulted in the formation of a unique external linage to China’s industrial clusters after the socialist planning period ended. In concrete terms, since the 1980s, a traditional commercial institution . the transaction market . began to appear in most clusters. These markets within the clusters get connected to those in the cities due to interaction between traditional merchants and local governments. This has resulted in the formation of a powerful market network-based distribution system which has played a crucial role for China’s industrial clusters in responding to exploding domestic demand. This paper explains these features in detail, using Yiwu China Commodity City as a case study

Domestic Market-based Industrial Cluster Development in Modern China

China’s huge domestic market is constantly expanding, and is low-end demand oriented and highly dispersed. The domestic market-based development of China’s industrial cluster, however, is not only a quantitative expansion, but has also been accompanied with remarkable qualitative upgrading. Specialized markets are a microcosm that clearly indicate this paradoxical phenomenon. By analyzing three typical cases of industrial clusters that have specialized markets, this paper will make the case that under modern China’s market conditions, the local public sector is the crucial driving force for upgrading industrial clusters, which organize complicated transactions, promote quality control, and stimulate the division of labor