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This paper evaluates housing policy in the Republic of Korea over the past several decades, describes new challenges arising from the changing environment, and draws lessons for other countries. The most important goals of the housing policy have been to alleviate housing shortages and to stabilize housing prices. To achieve these goals, the government has been engaging the private sector while establishing public sector institutions and legal framework, providing developable land, and allocating housing units to intended target groups. Thanks to the sustained and massive provision of new housing since the 1980s, the country's absolute housing shortage has been resolved, and overall housing conditions have improved substantially. Since the turn of the new millennium, enhancing the housing welfare of low-income households and the underprivileged has been added to housing policy goals. The supply of public rental housing was increased, and a housing benefit was introduced to address the new policy goal, but more work needs to be done. Today, the Republic of Korea also faces new housing challenges regarding the country's demographic and socioeconomic changes.

The paper is concerned with South Korea's urban problems and prospects. After a brief review of this country's urbanization during its period of rapid growth, likely trends of urban growth during the remainder of the century are identified. Several closely related urban problems that Koreans must solve during the years ahead are analysed. (DÜI-Sen)

The successful decoding of kinematic variables from spike trains of motor cortical neurons is essential for cortical neural prosthesis. Spike trains from each single unit must be extracted from extracellular neural signals and, thus, spike detection and sorting procedure is indispensable but the detection and sorting may involve considerable error. Thus, a decoding algorithm should be robust with respect to spike train errors. Here, we show that spike train decoding algorithms employing nonlinear mapping, especially a support vector machine (SVM), may be more advantageous contrary to previous results which showed that an optimal linear filter is sufficient. The advantage became more conspicuous in the case of erroneous spike trains. Using the SVM, satisfactory training of the decoder could be achieved much more easily, compared to the case of using a multilayer perceptron, which has been employed in previous studies. Tests were performed on simulated spike trains from primary motor cortical neurons with a realistic distribution of preferred direction. The results suggest the possibility that a neuroprosthetic device with a low-quality spike sorting preprocessor can be achieved by adopting a spike train decoder that is robust to spike sorting errors. ; This research was supported by Regional Research Center Program which was conducted by the Ministry of Commerce, Industry and Energy of the Korean Government, and ERC program of MOST/KOSEF (grant #R11-2000-075-01001-0).

We prepared bulk samples of supercooled liquid water under pressure by isochoric heating of high-density amorphous ice to temperatures of 205 ± 10 kelvin, using an infrared femtosecond laser. Because the sample density is preserved during the ultrafast heating, we could estimate an initial internal pressure of 2.5 to 3.5 kilobar in the high-density liquid phase. After heating, the sample expanded rapidly, and we captured the resulting decompression process with femtosecond x-ray laser pulses at different pump-probe delay times. A discontinuous structural change occurred in which low-density liquid domains appeared and grew on time scales between 20 nanoseconds to 3 microseconds, whereas crystallization occurs on time scales of 3 to 50 microseconds. The dynamics of the two processes being separated by more than one order of magnitude provides support for a liquid-liquid transition in bulk supercooled water.