• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.117-129
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• 2015

As the Internet becomes ubiquitous, a large volume of information is posted on the Internet with exponential growth every day. Accordingly, it is not unusual that investors in stock markets gather and compile firm-specific or market-wide information through online searches. Importantly, it becomes easier for investors to acquire value-relevant information for their investment decision with the help of powerful search tools on the Internet. Our study examines whether or not the Internet helps investors assess a firm's value better by using firm-level data over long periods spanning from January 2004 to December 2013. To this end, we construct weekly-based search volume for information technology (IT) services firms on the Internet. We limit our focus to IT firms since they are often equipped with intangible assets and relatively less recognized to the public which makes them hard-to measure. To obtain the information on those firms, investors are more likely to consult the Internet and use the information to appreciate the firms more accurately and eventually improve their investment decisions. Prior studies have shown that changes in search volumes can reflect the various aspects of the complex human behaviors and forecast near-term values of economic indicators, including automobile sales, unemployment claims, and etc. Moreover, search volume of firm names or stock ticker symbols has been used as a direct proxy of individual investors' attention in financial markets since, different from indirect measures such as turnover and extreme returns, they can reveal and quantify the interest of investors in an objective way. Following this line of research, this study aims to gauge whether the information retrieved from the Internet is value relevant in assessing a firm. We also use search volume for analysis but, distinguished from prior studies, explore its impact on return comovements with market returns. Given that a firm's returns tend to comove with market returns excessively when investors are less informed about the firm, we empirically test the value of information by examining the association between Internet searches and the extent to which a firm's returns comove. Our results show that Internet searches are negatively associated with return comovements as expected. When sample is split by the size of firms, the impact of Internet searches on return comovements is shown to be greater for large firms than small ones. Interestingly, we find a greater impact of Internet searches on return comovements for years from 2009 to 2013 than earlier years possibly due to more aggressive and informative exploit of Internet searches in obtaining financial information. We also complement our analyses by examining the association between return volatility and Internet search volumes. If Internet searches capture investors' attention associated with a change in firm-specific fundamentals such as new product releases, stock splits and so on, a firm's return volatility is likely to increase while search results can provide value-relevant information to investors. Our results suggest that in general, an increase in the volume of Internet searches is not positively associated with return volatility. However, we find a positive association between Internet searches and return volatility when the sample is limited to larger firms. A stronger result from larger firms implies that investors still pay less attention to the information obtained from Internet searches for small firms while the information is value relevant in assessing stock values. However, we do find any systematic differences in the magnitude of Internet searches impact on return volatility by time periods. Taken together, our results shed new light on the value of information searched from the Internet in assessing stock values. Given the informational role of the Internet in stock markets, we believe the results would guide investors to exploit Internet search tools to be better informed, as a result improving their investment decisions.

• Radiation Oncology Journal
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• v.22 no.4
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• pp.288-297
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• 2004

Puporse: The aims of this study were to evaluate the change of $[^18F]fluoromisonidazole$($[^18F]FMISO$) uptake in C3H mouse squamous cell carcinoma-VII (SCC-VII) treated with mild hyperthermia ($42^{circ}C$) and nicotinamide and to assess the biodistribution of the markers in normal tissues under similar conditions. Methods and Materials: $[^18F]FMISO$ was producedby our hospital. Female C3H mice with a C3H SCC-VII tumor grown on their extremities were used. Tumors were size matched. Non-anaesthetized, tumor-bearing mice underwent control or mild hyperthermia at $42^{circ}C$ for 60 min with nicotinamide (50 mg/kg i.p. injected) and were examined by gamma counter, autoradiography and animal PET scan 3 hours after tracer i.v. injected with breathing room air, The biodistribution of these agents were obtained at 3 h after $[^18F]FMISO$ injection. Blood, tumor, muscle, heart, lung, liver, kidney, brain, bone, spleen, and intestine were removed, counted for radioactivity and weighed. The tumor and liver were frozen and cut with a cryomicrotome into 10- um sections. The spatial distribution of radioactivity from the tissue sections was determined with digital autoradiography. Results: The mild hyperthermia with nicotinamide treatment had only slight effects on the biodistribution of either marker in normal tissues. We observed that the whole tumor radioactivity uptake ratios were higher in the control mice than in the mild hyperthermia with nicotinamide treated mice for $[^18F]FMISO$ ($1.56{\pm}1.03$ vs. $0.67{\pm}0.30$; p=0.063). In addition, autoradiography and animal PET scan demonstrated that the area and intensity of $[^18F]FMISO$ uptake was significantly decreased. Conclusion: Mild hyperthermla and nicotinamide significantly improved tumor hypoxia using $[^18F]FMISO$ and this uptake reflected tumor hypoxic status.

• FLOWER RESEARCH JOURNAL
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• v.16 no.4
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• pp.299-303
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• 2008

An Oriental lily cultivar 'Pacific Wave' was released in 2007 at National Institute of Horticultural and Herbal Science, Rural Development Administration (RDA), Suwon, Korea. The crossing was made in 1999 between Oriental lily 'Simplon', an outward-facing and white colored cultivar, and 'Spinoza', pink colored cultivar. The first selection was done in 2003 with a line of 'O-03-16'. Multiplication and bulb growth, and performance test was conducted from 2004 to 2006. This selection was later on given as 'Pacific Wave' in 2007 at NHRI. Flowering time of 'Pacific Wave' in plastics house culture is mid June and grows average 115 cm. Flowers are upward-facing with 20.1 cm in diameter and white with yellow centered (RHS W155C + Y9A). Mean petal length and width is 12.2 cm and 4.2 cm, respectively. Leaves are 12.3 cm long, 2.9 cm wide. The throat color is green. It shows gray and purple stigma, and red brown pollen. The weight and size of bulb is 82.5 g and 19.6 cm, respectively. Year-round flowering can be by storing the bulb under -1 to $-2^{\circ}C$ conditions. It is necessary to add calcium to the fertilizer or remove side scales to prevent leaf scorch. It is needed to control Botrytis disease in summer wet season.

• Korean Journal of Breeding Science
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• v.43 no.6
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• pp.581-586
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• 2011

'Cheongdam' is a japonica rice variety developed from a cross between SR19200-HB826-34, a line of good germination ability and shoot emergence at low temperature and Juanbyeo, good quality and direct-seeding adaptable cultivar by the rice breeding team of National Institute of Crop Science, RDA in 2006. This variety has 153 days of total growth duration from seeding to maturity in direct-seeding, and 160 days of growth duration from seeding to maturity in transplanting. This is erect plant type with culm length of 74 cm, thick culm, and green leaves. It has large panicle shape with 126 and 140 spikelets per panicle in direct-seeding and transplanting, respectively. Milled rice is transluscent and medium in grain size of non-glutinous endosperm. This variety is susceptible to leaf and neck blast, bacterial blight, stripe virus disease and brown planthopper. The yield potential of 'Cheongdam' is 5.84 MT/ha at ordinary transplanting culture and 5.62 MT/ha and 5.89 MT/ha at wet direct-seeding and dry direct-seeding cultures, respectively in the local adaptability test for three years. 'Cheongdam' would be adaptable to middle and southern plain of Korea for direct-seeding culture and transplanting rice culture.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.