• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.191-204
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• 2015

According to the '2013 Performance Assessment Report on the Financial Program' from the National Assembly Budget Office, the unfilled recruitment ratio of Software(SW) Developers in South Korea was 25% in the 2012 fiscal year. Moreover, the unfilled recruitment ratio of highly-qualified SW developers reaches almost 80%. This phenomenon is intensified in small and medium enterprises consisting of less than 300 employees. Young job-seekers in South Korea are increasingly avoiding becoming a SW developer and even the current SW developers want to change careers, which hinders the national development of IT industries. The Korean government has recently realized the problem and implemented policies to foster young SW developers. Due to this effort, it has become easier to find young SW developers at the beginning-level. However, it is still hard to recruit highly-qualified SW developers for many IT companies. This is because in order to become a SW developing expert, having a long term experiences are important. Thus, improving job continuity intentions of current SW developers is more important than fostering new SW developers. Therefore, this study surveyed the job continuity intentions of SW developers and analyzed the factors associated with them. As a method, we carried out a survey from September 2014 to October 2014, which was targeted on 130 SW developers who were working in IT industries in South Korea. We gathered the demographic information and characteristics of the respondents, work environments of a SW industry, and social positions for SW developers. Afterward, a regression analysis and a decision tree method were performed to analyze the data. These two methods are widely used data mining techniques, which have explanation ability and are mutually complementary. We first performed a linear regression method to find the important factors assaociated with a job continuity intension of SW developers. The result showed that an 'expected age' to work as a SW developer were the most significant factor associated with the job continuity intention. We supposed that the major cause of this phenomenon is the structural problem of IT industries in South Korea, which requires SW developers to change the work field from developing area to management as they are promoted. Also, a 'motivation' to become a SW developer and a 'personality (introverted tendency)' of a SW developer are highly importantly factors associated with the job continuity intention. Next, the decision tree method was performed to extract the characteristics of highly motivated developers and the low motivated ones. We used well-known C4.5 algorithm for decision tree analysis. The results showed that 'motivation', 'personality', and 'expected age' were also important factors influencing the job continuity intentions, which was similar to the results of the regression analysis. In addition to that, the 'ability to learn' new technology was a crucial factor for the decision rules of job continuity. In other words, a person with high ability to learn new technology tends to work as a SW developer for a longer period of time. The decision rule also showed that a 'social position' of SW developers and a 'prospect' of SW industry were minor factors influencing job continuity intensions. On the other hand, 'type of an employment (regular position/ non-regular position)' and 'type of company (ordering company/ service providing company)' did not affect the job continuity intension in both methods. In this research, we demonstrated the job continuity intentions of SW developers, who were actually working at IT companies in South Korea, and we analyzed the factors associated with them. These results can be used for human resource management in many IT companies when recruiting or fostering highly-qualified SW experts. It can also help to build SW developer fostering policy and to solve the problem of unfilled recruitment of SW Developers in South Korea.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.119-133
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• 2020

Fama asserted that in an efficient market, we can't make a trading rule that consistently outperforms the average stock market returns. This study aims to suggest a machine learning algorithm to improve the trading performance of an intraday short volatility strategy applying asymmetric volatility spillover effect, and analyze its trading performance improvement. Generally stock market volatility has a negative relation with stock market return and the Korean stock market volatility is influenced by the US stock market volatility. This volatility spillover effect is asymmetric. The asymmetric volatility spillover effect refers to the phenomenon that the US stock market volatility up and down differently influence the next day's volatility of the Korean stock market. We collected the S&P 500 index, VIX, KOSPI 200 index, and V-KOSPI 200 from 2008 to 2018. We found the negative relation between the S&P 500 and VIX, and the KOSPI 200 and V-KOSPI 200. We also documented the strong volatility spillover effect from the VIX to the V-KOSPI 200. Interestingly, the asymmetric volatility spillover was also found. Whereas the VIX up is fully reflected in the opening volatility of the V-KOSPI 200, the VIX down influences partially in the opening volatility and its influence lasts to the Korean market close. If the stock market is efficient, there is no reason why there exists the asymmetric volatility spillover effect. It is a counter example of the efficient market hypothesis. To utilize this type of anomalous volatility spillover pattern, we analyzed the intraday volatility selling strategy. This strategy sells short the Korean volatility market in the morning after the US stock market volatility closes down and takes no position in the volatility market after the VIX closes up. It produced profit every year between 2008 and 2018 and the percent profitable is 68%. The trading performance showed the higher average annual return of 129% relative to the benchmark average annual return of 33%. The maximum draw down, MDD, is -41%, which is lower than that of benchmark -101%. The Sharpe ratio 0.32 of SVS strategy is much greater than the Sharpe ratio 0.08 of the Benchmark strategy. The Sharpe ratio simultaneously considers return and risk and is calculated as return divided by risk. Therefore, high Sharpe ratio means high performance when comparing different strategies with different risk and return structure. Real world trading gives rise to the trading costs including brokerage cost and slippage cost. When the trading cost is considered, the performance difference between 76% and -10% average annual returns becomes clear. To improve the performance of the suggested volatility trading strategy, we used the well-known SVM algorithm. Input variables include the VIX close to close return at day t-1, the VIX open to close return at day t-1, the VK open return at day t, and output is the up and down classification of the VK open to close return at day t. The training period is from 2008 to 2014 and the testing period is from 2015 to 2018. The kernel functions are linear function, radial basis function, and polynomial function. We suggested the modified-short volatility strategy that sells the VK in the morning when the SVM output is Down and takes no position when the SVM output is Up. The trading performance was remarkably improved. The 5-year testing period trading results of the m-SVS strategy showed very high profit and low risk relative to the benchmark SVS strategy. The annual return of the m-SVS strategy is 123% and it is higher than that of SVS strategy. The risk factor, MDD, was also significantly improved from -41% to -29%.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Nutrition and Health
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• v.42 no.8
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• pp.770-783
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• 2009

The school foodservice was quantitatively extended by policy of government all the while. There was carried out the survey of customer satisfaction about school foodservice by the ministry of education, science, and technology since 2006 years. Therefore, the purpose of this study was to grasp an improvement of the scores of school foodservice' quality attributes and satisfaction as compared with the preceding year by respondents and school type (elementary school, middle school, and high school). An annual survey was practiced to respondents (students, parents, and faculty) on september 2007 years and 2008 years in 16 cities and provinces. The statistics was analyzed to descriptive analysis and t-test for SPSS 12.0. The scores of school foodservice' quality attributes and overall customer satisfaction were almost increased to students, parents, and faculty and especially, big elevation in middle school. There was big increased the quality attributes such as 'providing information on foodservice', 'pleasant foodservice environment', 'kindness offered by employee' in elementary school, middle school, and high school to total respondents. An overall satisfaction in school foodservice was improved from 69.2 score to 71.9 score. On students, scores of overall satisfaction was increased from 72.9 to 74.0 as students of elementary school and from 61.5 to 65.8 as students of middle school (p < .001). Therefore, for improvement and development of school foodservice, there should be a necessary for an operator of school foodservice and an office of education to make an effort.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.33 no.4
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• pp.251-262
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• 2007

In this study, the antioxidative effects, inhibitory effects on elastase, and components of Aspalathus linearis extracts were investigated. The free radical (1,1-diphenyl-2-picrylhydrazyl, DPPH) scavenging activities ($FSC_{50}$) of extract/fractions of Aspalathus linearis were in the order: 50 % ethanol extract ($11.50\;{\mu}g/mL$) < deglycosylated flavonoid aglycone fraction ($8.47\;{\mu}g/mL$) < ethylacetate fraction ($4.76\;{\mu}g/mL$). Reactive oxygen species (ROS) scavenging activities ($OSC_{50}$) of some Aspalathus linearis extracts on ROS generated in $Fe^{3+}-EDTA/H_2O_2$ system were investigated using the luminol-dependent chemiluminescence assay. The order of ROS scavenging activities were ethylacetate fraction ($OSC_{50},\;4.58\;{\mu}g/mL$) < deglycosylated flavonoid aglycone fraction ($2.20\;{\mu}g/mL$) < 50 % ethanol extract ($1.09\;{\mu}g/mL$). 50 % Ethanol extract showed the most prominent scavenging activity. The protective effects of extract/fractions of Aspalathus linearis on the rose-bengal sensitized photohemolysis of human erythrocytes were investigated. The Aspalathus linearis extracts suppressed photohemolysis in a concentration dependent manner, particularly 50 % ethanol extract exhibited the most prominent celluar protective effect (${\tau}_{50}$, 272.00 min at $50\;{\mu}g/mL$). Aglycone fractions obtained from the deglycosylation reaction of ethylacetate fraction among the Aspalathus linearis extracts, showed 3 bands in TLC and 3 peaks in HPLC experiments (360 nm). Three components were identified as luteolin (composition ratio, 18.24 %), quercetin (58.79), and kaempferol (22.97). TLC chromatogram of ethylacetate fraction of Aspalathus linearis extract revealed 7 bands and HPLC chromatogram showed 9 peaks, which were identified as isoorientin (composition ratio, 14.71 %), orientin (28.84 %), vitexin (5.63 %), rutin and isovitexin (12.73 %), hyperoside (9.24 %), isoquercitrin (5.40 %), luteolin (1.48 %), quercetin (17.61 %) and kaempferol (4.59 %) in the order of elution time. The inhibitory effect of aglycone fraction on elastase ($IC_{50},\;9.08\;{\mu}g/mL$) was very high. These results indicate that extract/fractions of Aspalathus linearis can function as antioxidants in biological systems, particularly skin exposed to UV radiation by scavenging $^1O_2$ and other ROS, and protect cellular membranes against ROS. And component analysis of Aspalathus linearis extract and inhibitory activity on elastase of the aglycone fraction could be applicable to new functional cosmetics for smoothing wrinkles.

• Journal of Chest Surgery
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• v.32 no.2
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• pp.97-107
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• 1999

Background: This study was designed to develop a Korean version of the heparin-coated vascular bypass shunt by using a physical dispersing technique. The safety and effectiveness of the thrombo-resistant shunt were tested in experimental animals. Material and Method: A bypass shunt model was constructed on the descending thoracic aorta of 21 adult mongrel dogs(17.5-25 kg). The animals were divided into groups of no-treatment(CONTROL group; n=3), no-treatment with systemic heparinization(HEPARIN group; n=6), Gott heparin shunt (GOTT group; n=6), or Korean heparin shunt(KIST group; n=6). Parameters observed were complete blood cell counts, coagulation profiles, kidney and liver function(BUN/Cr and AST/ ALT), and surface scanning electron microscope(SSEM) findings. Blood was sampled from the aortic blood distal to the shunt and was compared before the bypass and at 2 hours after the bypass. Result: There were no differences between the groups before the bypass. At bypass 2 hours, platelet level increased in the HEPARIN and GOTT groups(p<0.05), but there were no differences between the groups. Changes in other blood cell counts were insignificant between the groups. Activated clotting time, activated partial thromboplastin time, and thrombin time were prolonged in the HEPARIN group(p<0.05) and differences between the groups were significant(p<0.005). Prothrombin time increased in the GOTT group(p<0.05) without having any differences between the groups. Changes in fibrinogen level were insignificant between the groups. Antithrombin III levels were increased in the HEPARIN and KIST groups(p<0.05), and the inter-group differences were also significant(p<0.05). Protein C level decreased in the HEPARIN group(p<0.05) without having any differences between the groups. BUN levels increased in all groups, especially in the HEPARIN and KIST groups(p<0.05), but there were no differences between the groups. Changes of Cr, AST, and ALT levels were insignificant between the groups. SSEM findings revealed severe aggregation of platelets and other cellular elements in the CONTROL group, and the HEPARIN group showed more adherence of the cellular elements than the GOTT or KIST group. Conclusion: Above results show that the heparin-coated bypass shunts(either GOTT or KIST) can suppress thrombus formation on the surface without inducing bleeding tendencies, while systemic heparinization(HEPARIN) may not be able to block activation of the coagulation system on the surface in contact with foreign materials but increases the bleeding tendencies. We also conclude that the thrombo-resistant effects of the Korean version of heparin shunt(KIST) are similar to those of the commercialized heparin shunt(GOTT).

• Journal of Chest Surgery
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• v.41 no.6
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• pp.679-686
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• 2008

Background: Cellular remnants in the bioprosthetic heart valve are known to be related to a host's immunologic response and they can form the nidus for calcification. The extracellular matrix of the decellularized valve tissue can also be used as a biological scaffold for cell attachment, endothelialization and tissue reconstitution. Thus, decellularization is the most important part in making a bioprosthetic valve and biological caffold. Many protocols and agents have been suggested for decellularization, yet there ave been few reports about the effect of a treatment with hypotonic solution prior to chemical or enzymatic treatment. This study investigated the effect of a treatment with hypotonic solution and the appropriate environments such as temperature, the treatment duration and the concentration of sodium dodecylsulfate (SDS) for achieving proper decellularization. Material and Method: Porcine aortic valves were decellularized with odium dodecylsulfate at various concentrations (0.25%, 0.5%), time durations (6, 12, 24 hours) and temperatures ($4^{\circ}C$, $20^{\circ}C$)(Group B). Same the number of porcine aortic valves (group A) was treated with hypotonic solution prior to SDS treatment at the same conditions. The duration of exposure to the hypotonic solution was 4, 7 and 14 hours and he temperature was $4^{\circ}C$ and $20^{\circ}C$, respectively. The degree of decellularization was analyzed by performing hematoxylin and eosin staining. Result: There were no differences in the degree of decellularization between the two concentrations (0.25% 0.5%) of SDS. Twenty four hours treatment with SDS revealed the best decellularization effect for both roups A and B at the temperature of $4^{\circ}C$, but there was no differences between the roups at $20^{\circ}C$. Treatment with hypotonic solution (group A) showed a better ecellularization effect at all the matched conditions. Fourteen hours treatment at $4^{\circ}C$ ith ypotonic solution prior to 80S treatment revealed the best decellularization effect. The treatment with hypotonic solution at $20^{\circ}C$ revealed a good decellularization effect, but his showed significant extracellular matrix destruction. Conclusion: The exposure of porcine heart valves to hypotonic solution prior to SDS treatment is highly effective for achieving decellularization. Osmotic treatment with hypotonic solution should be considered or achieving decellularization of porcine aortic valves. Further study should be carried out to see whether the treatment with hypotonic solution could reduce the exposure duration and concentration of chemical detergents, and also to evaluate how the structure of the extracellular matrix of the porcine valve is affected by the exposure to hypotonic solution.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.853-860
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• 2012

To estimate potential use of fly ash in reducing $CH_4$ and $CO_2$ emission from soil, $CH_4$ and $CO_2$ fluxes from a paddy soil mixed with fly ash at different rate (w/w; 0, 5, and 10%) in the presence and absence of fertilizer N ($(NH_4)_2SO_4$) addition were investigated in a laboratory incubation for 60 days under changing water regime from wetting to drying via transition. The mean $CH_4$ flux during the entire incubation period ranged from 0.59 to $1.68mg\;CH_4\;m^{-2}day^{-1}$ with a lower rate in the soil treated with N fertilizer due to suppression of $CH_4$ production by $SO_4^{2-}$ that acts as an electron acceptor, leading to decreases in electron availability for methanogen. Fly ash application reduced $CH_4$ flux by 37.5 and 33.0% in soils without and with N addition, respectively, probably due to retardation of $CH_4$ diffusion through soil pores by addition of fine-textured fly ash. In addition, as fly ash has a potential for $CO_2$ removal via carbonation (formation of carbonate precipitates) that decreases $CO_2$ availability that is a substrate for $CO_2$ reduction reaction (one of $CH_4$ generation pathways) is likely to be another mechanisms of $CH_4$ flux reduction by fly ash. Meanwhile, the mean $CO_2$ flux during the entire incubation period was between 0.64 and $0.90g\;CO_2\;m^{-2}day^{-1}$, and that of N treated soil was lower than that without N addition. Because N addition is likely to increase soil respiration, it is not straightforward to explain the results. However, it may be possible that our experiment did not account for the substantial amount of $CO_2$ produced by heterotrophs that were activated by N addition in earlier period than the measurement was initiated. Fly ash application also lowered $CO_2$ flux by up to 20% in the soil mixed with fly ash at 10% through $CO_2$ removal by the carbonation. At the whole picture, fly ash application at 10% decreased global warming potential of emitted $CH_4$ and $CO_2$ by about 20%. Therefore, our results suggest that fly ash application can be a soil management practice to reduce green house gas emission from paddy soils. Further studies under field conditions with rice cultivation are necessary to verify our findings.

• Radiation Oncology Journal
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• v.21 no.1
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• pp.54-65
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• 2003

Purpose : To analyze the gene expression Profiles of uterine ceulcal cancer, and its variation after radiation therapy, with or without concurrent chemotherapy, using a CDNA microarray. Materials and Methods :Sixteen patients, 8 with squamous ceil carcinomas of the uterine cervix, who were treated with radiation alone, and the other 8 treated w14h concurrent chemo-radiation, were Included in the study. Before the starling of the treatment, tumor biopsies were carried out, and the second time biopsies were peformed after a radiation dose of 16.2$\~$27 Gy. Three normal cervix tissues were used as a control group. The microarray experiments were peformed with 5 groups of the total RNAs extracted individually and then admixed as control, pre-radiation therapy alone, during-radiation therapy alone, pre-chemoradiation therapy, and during-chemoradlation therapy. The 33P-iabeled CDNAS were synthesized from the total RNAs of each group, by reverse transcription, and then they were hybridized to the CDNA microarray membrane. The gene expression of each microarrays was captured by the intensity of each spot produced by the radioactive isotopes. The pixels per spot were counted with an Arrayguage, and were exported to Microsoft Excel The data were normalized by the Z transformation, and the comparisons were peformed on the Z-ratio values calculated. Results : The expressions of 15 genes, including integrin linked kinase (ILK), CDC28 protein kinase 2, Spry 2, and ERK 3, were increased with the Z-ratio values of over 2.0 for the cervix cancer tissues compared to those for the normal controls. Those genes were involved In cell growth and proliferation, cell cycle control, or signal transduction. The expressions of the other 6 genes, Including G protein coupled receptor kinase 5, were decreased with the Z-ratio values of below -2.0. After the radiation thorapy, most of the genes, with a previously Increase expressions, represented the decreased expression profiles, and the genes, with the Z-ratio values of over 2.0, were cyclic nucleotlde gated channel and 3 Expressed sequence tags (EST). In the concurrent chemo-radiation group, the genes involved in cell growth and proliferation, cell cycle control, and signal transduction were shown to have increased expressions compared to the radiation therapy alone group. The expressions of genes involved in anglogenesis (angiopoietln-2), immune reactions (formyl peptide receptor-iike 1), and DNA repair (CAMP phosphodiesterase) were increased, however, the expression of gene involved In apoptosls (death associated protein kinase) was decreased. Conclusion : The different kinds of genes involved in the development and progression of cervical cancer were identified with the CDNA microarray, and the proposed theory is that the proliferation signal stalls with ILK, and is amplified with Spry 2 and MAPK signaling, and the cellular mitoses are Increased with the increased expression oi Cdc 2 and cell division kinases. After the radiation therapy, the expression profiles demonstrated 4he evidence of the decreased cancer cell proliferation. There was no sigificant difference in the morphological findings of cell death between the radiation therapy aione and the chemo-radiation groups In the second time biopsy specimen, however, the gene expression profiles were markedly different, and the mechanism at the molecular level needs further study.