A Distributive Comparison of Enterprise Size in Korea and Taiwan

Research to date on the economic development of the Republic of Korea and Taiwan has frequently contrasted the two economies by depicting the former as centered on large-scale enterprises and the latter on small and medium-size enterprises (SMEs). The purpose of this study is to see if the appropriateness of this perception will also be verified by the statistical data. In Section I the authors utilized census data on the Korean and Taiwanese manufacturing sectors to compare the distribution pattern of the sizes of enterprises in the two economies. However, on examining the available data for making this comparison, the authors discovered that for Korea the statistics provided are those at the level of the establishment (a physical unit engaging in industrial activities such as a factory, workshop, office, or mine) while the statistics for Taiwan are those at the enterprise level. Mindful of this difference, the authors looked at the portion of the economy accounted for by large-scale establishments in Korea that employed 500 workers or more and by enterprises in Taiwan employing the same number of workers, and they discovered that the portion that these large-scale businesses account for, especially in the area of output, has steadily declined since the 1980s. When comparing the share of total production that these large-scale establishments/enterprises account for in the two economies, the authors concluded that those in Korea accounted for a larger share of that economy's production than did their counterparts in Taiwan. The authors then compared the portion of the economy accounted for by establishments in Korea and enterprises in Taiwan that employed less than ten workers, and they found that the portion of the two economies that these very small-scale production units accounted for has also been on the decline. Section II compares the portions of the two economies accounted for by large business groups. After comparing the percentage of GDP accounted for by the total sales of these business groups, the authors found that large business groups in Korea have played a far more important role in Korean economy than has been the case for such groups in Taiwan. This difference in the importance of such business groups in the two economies has also played an significant part in fostering the perceived dichotomy of large-scale enterprises playing the important role in Korea versus SMEs being the important players in Taiwan. Section III compares the percentage of total exports accounted for by SMEs, and shows that SMEs in Taiwan account for a larger share of exports than do their counterparts in Korea. This section also shows that in Taiwan the share of export sales for SMEs has consistently exceeded that for non-SMEs, while in Korea the relationship between enterprise size and the rate of export sales has been directly proportional. This difference in the size of the major export players is another factor fostering the perception of the Korean economy being centered on big business while Taiwan's is on SMEs. Although there were difficulties and limitations when comparing the data of the two economies, the statistical comparison undertaken in this study shows that in general big business has played the major role in the development of the Korean economy while in Taiwan's economic development this role has been played by SMEs. Thus the statistical data also verifies the perceived dichotomy of these two economies.

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The epresentativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.

YPD™, PombePD™ and WormPD™: model organism volumes of the BioKnowledge™ Library, an integrated resource for protein information

The BioKnowledge Library is a relational database and web site (http://www.proteome.com) composed of protein-specific information collected from the scientific literature. Each Protein Report on the web site summarizes and displays published information about a single protein, including its biochemical function, role in the cell and in the whole organism, localization, mutant phenotype and genetic interactions, regulation, domains and motifs, interactions with other proteins and other relevant data. This report describes four species-specific volumes of the BioKnowledge Library, concerned with the model organisms Saccharo­myces cerevisiae (YPD), Schizosaccharomyces pombe (PombePD) and Caenorhabditis elegans (WormPD), and with the fungal pathogen Candida albicans (CalPD™). Protein Reports of each species are unified in format, easily searchable and extensively cross-referenced between species. The relevance of these comprehensively curated resources to analysis of proteins in other species is discussed, and is illustrated by a survey of model organism proteins that have similarity to human proteins involved in disease.

Bathymetric Terrain Model of the Puerto Rico Trench and the Northeastern Caribbean Region for Marine Geological Investigations

Multibeam bathymetric data collected in the Puerto Rico Trench and northeastern Caribbean region are compiled into a seamless bathymetric terrain model for broad-scale geological investigations of the trench system. These data, collected during eight separate surveys between 2002 and 2013 and covering almost 180,000 square kilometers, are published here in large-format map sheet and digital spatial data. This report describes the common multibeam data collection and processing methods used to produce the bathymetric terrain model and corresponding data-source polygon. Details documenting the complete provenance of the data are provided in the metadata in the Data Catalog section.