• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.1-21
• /
• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

• Journal of Internet Computing and Services
• /
• v.5 no.5
• /
• pp.1-15
• /
• 2004

In this paper, we explain the design and implementation of GWB(Gene WorkBench), which is a web-based, integrated system for efficiently managing and analyzing genomic sequences, Most existing software systems handling genomic sequences rarely provide both managing facilities and analyzing facilities. The analysis programs also tend to be unit programs that include just single or some part of the required functions. Moreover, these programs are widely distributed over Internet and require different execution environments. As lots of manual and conversion works are required for using these programs together, many life science researchers suffer great inconveniences. in order to overcome the problems of existing systems and provide a more convenient one for helping genomic researches in effective ways, this paper integrates both managing facilities and analyzing facilities into a single system called GWB. Most important issues regarding the design of GWB are how to integrate many different analysis programs into a single software system, and how to provide data or databases of different formats required to run these programs. In order to address these issues, GWB integrates different analysis programs byusing common input/output interfaces called wrappers, suggests a common format of genomic sequence data, organizes local databases consisting of a relational database and an indexed sequential file, and provides facilities for converting data among several well-known different formats and exporting local databases into XML files.

• Journal of Korean Society of Forest Science
• /
• v.94 no.6
• /
• pp.488-495
• /
• 2005

This study was conducted to understand the influences of forest structure on throughfall, stemflow and interception loss. The study plots included the natural old-growth deciduous, Pinus koraiensis and Abies holophylla forests in Gwangneung and the rehabilitated young mixed forest in Yangju, Gyeonggido. The Pinus koraiensis and Abies hotophylla had been planted in 1976. The rehabilitated young mixed forest had been established to control erosion in 1974. Total and net rainfall were monitored from March, 2003 to October, 2004. Tipping bucket rain gauge recorded total rainfall. Throughfall and stemflow were measured by custom-made tipping bucket and CR10X data logger at each $10m{\times}10m$ plots at intervals of 30 minutes. Interception loss in the Pinus koraiensis plot were most as 37.2% of total rainfall and least as 22.6% in the rehabilitated young mixed forest. Stemflow in the rehabilitated young mixed forest was 10.7% of total rainfall and stemflow in the Pinus koraiensis plot was 2.4%. The average throughfall ratio ranged from 66% to 77% depending on the canopy coverage. The relationship of stemflow and total rainfall represented in a linear regression equation though the variation of data was large. The ratio of stemflow-conversion was 2% of total rainfall in the Pinus koraiensis plot and 12% in the rehabilitated young mixed forest, respectively. The stem storage of the natural old-growth deciduous was the largest of 0.21 mm whereas that of the Pinus koraiensis plot was the least of 0.003 mm. A deciduous forest produced stemflow more than a coniferous forest due to a smooth bark and steeply angled branches. Interception loss of all study plots increased linearly as total rainfall increased. The distribution of interception loss data related in total rainfall became wider in a deciduous forest than a coniferous. It resulted from seasonality of leaf area index in a deciduous forest. As considered above results, it was confirmed that there were great differences of throughfall, stemflow and interception loss depending on forest stand structures. The simulation model for predicting interception loss must have parameters such as forest stand characteristics and LAI in order to describe the influence of forest structure on interception loss.

• Korean Chemical Engineering Research
• /
• v.50 no.3
• /
• pp.511-515
• /
• 2012

In this study, we used a commercial simulator to investigate the gasification characteristics of Roto coal in the partitioned fluidized-bed gasifier, which consists of 4 parts such as coal pyrolysis, char gasification, tar/oil gasification and char combustion. The heating medium was exchanged between the combustion part and the gasification part in order to supply the energy needed for pyrolysis and gasification. The correlation model from experimental data in relation to the reaction temperatures, the reaction gases and the coal feed rates was derived for the coal pyrolysis. The equilibrium model was used for the gasification and the combustion model for the char combustion. In order to compare the reaction behavior of the partitioned fluidized-bed gasifier, the single-bed gasifier was also simulated. The cold gas efficiency of both partitioned fluidized-bed gasifier and single-bed gasifier was almost the same. The $H_2$ and $CH_4$ contents of the syngas in the partitioned fluidized-bed gasifier slightly increased and the CO and $CO_2$ contents slightly decreased, compared with the singlebed gasifier. In order to verify the model, ten cases of the single-bed gasification experiment have been simulated. The contents of CO, $CO_2$, $CH_4$ in the syngas from the simulation corresponded with the experimental data while those of $H_2$ was slightly higher than experimental data, but the tendency of $H_2$ content in the syngas was similar to the experiments. In the coal conversion, the simulation results were higher than the experiments since equilibrium model was used for the gasification so that the residence time and contact time in the model is different from the experiments.

• Journal of the Korean Applied Science and Technology
• /
• v.39 no.1
• /
• pp.63-73
• /
• 2022

The aim of this study was to cluster according to the bone age of elementary school students in order to analyze the physique, physical fitness, and skeletal maturation of each cluter group and to provide basic data for the balanced development of elementary school students through data analysis. The subjects of this study were 2243 students aged 8 to 13 years, and the skeletal maturation were calculated by applying them to the TW3 method score conversion table after the X-ray films were taken. A total of 2 components in physique were measured using a stadiometer(Hanebio, Korea, 2021) and the Inbody 270(Biospace, Korea, 2019), and a total of 7 components in physical fitness, which included muscular strength(Hand Grip Strength), balance(Bass Stick Test), agility(Plate Tapping), power(Standing Long Jump), flexibility(Sit&Reach), muscular endurance(Sit-Up), and cardiovascular endurance(Shuttle Run) were measured as well. K-Means clustering method, cross-tabulation analysis, and one-way variable analysis(ANOVA) were conducted for data processing using the SPSS PC/Program(Version 26.0) and Bristics Studio Tool, and it was considered significant at the level of p< .05. The results of this study may be summarized as follow. First, as a result of clustering using three components of skeletal maturation: retarded, normal, and advanced, cluster 1(Retarded) showed excellence in muscular strength, balance, and agility. cluster 2(Normal) showed poor flexibility, whereas cluster 3(Advanced) showed excellence in muscular strength. Second, as a result of analyzing the differences in physique according to the clustering of elementary school students by their individual characteristics, cluster 3(Advanced) showed excellence in height, weight, and body fat percentage. Third, as a result of analyzing the differences in physical fitness according to the clustering of elementary school students by their individual characteristics, cluster 3(Advanced) showed excellence in Hand Grip Strength(Left, Right), whereas cluster 1(Retarded) showed excellence in Bass Stick Test, and cluster 3(Advanced) showed excellence in Standing Long Jump.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.33-54
• /
• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

• Korean Journal of Poultry Science
• /
• v.39 no.4
• /
• pp.305-310
• /
• 2012

This work was carried out to investigate performance and carcass yield of large-type broilers at different stocking densities. Treatments were T1 (9.1 birds/$m^2$), T2 (10.3 birds/$m^2$) and T3 (11.5 birds/$m^2$) by the stocking density. Four hundred eight 1-day-old Arbor Acre broiler chicks were used for six weeks (starter, 0~1 wks; earlier, 1~3 wks; finisher, 3~6 wks) and divided into 3 treatments (4 replications/treatment, 30, 34 or 38 birds/replication). Research indexes were rearing viability ratio, body weight, body weight gain, feed intake, feed conversion ratio, production efficiency factor and carcass ratio. Rearing viability ratio (%) was 89% or more for all treatments and there was no significant difference on weekly rearing viability ratio (%). Body weight of T2 was the greatest and that of T3 was the lowest at 1 weeks old (P<0.05). Body weight gain of T2 was the greatest and that of T3 was the lowest at 0~1 weeks old (P<0.05). However, body weight gain of T3 was the greatest and that of T1 was the lowest at 1~2 weeks old (P<0.05). Body weight gain of T2 was the greatest as 3,031 g among treatments at 0~6 weeks old (P<0.05). Feed intakes of T1, T2 and T3 were 1,417 g, 1,265 g and 1,355 g, respectively, and that of T1 was the greatest among treatments (P<0.05). There was no significant difference on body weight, body weight gain and feed intake. Feed conversion ratio of T1 was the greatest among treatments at 1~2 wks, 3~4 wks and 0~6 wks old (P<0.05). Production efficiency factors of T1, T2 and T3 were 363.5, 388.3 and 358.3, respectively, and there was no significant difference among treatments. Wing meat ratio of T1 was the higher compared to other treatments at the age of 4 wk (P<0.05). There was no significant difference on carcass ratio and partial meat ratio among treatments. Neck meat ratio of T2 was the lowest among treatments (P<0.05). This result may provide the standard data of different stocking densities for large-type broiler and the further research is needed.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.63-83
• /
• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Progress in Medical Physics
• /
• v.27 no.2
• /
• pp.64-71
• /
• 2016

We develop a manufacture procedure for the production of a patient specific customized bolus (PSCB) using a 3D printer (3DP). The dosimetric accuracy of the 3D-PSCB is evaluated for electron beam therapy. In order to cover the required planning target volume (PTV), we select the proper electron beam energy and the field size through initial dose calculation using a treatment planning system. The PSCB is delineated based on the initial dose distribution. The dose calculation is repeated after applying the PSCB. We iteratively fine-tune the PSCB shape until the plan quality is sufficient to meet the required clinical criteria. Then the contour data of the PSCB is transferred to an in-house conversion software through the DICOMRT protocol. This contour data is converted into the 3DP data format, STereoLithography data format and then printed using a 3DP. Two virtual patients, having concave and convex shapes, were generated with a virtual PTV and an organ at risk (OAR). Then, two corresponding electron treatment plans with and without a PSCB were generated to evaluate the dosimetric effect of the PSCB. The dosimetric characteristics and dose volume histograms for the PTV and OAR are compared in both plans. Film dosimetry is performed to verify the dosimetric accuracy of the 3D-PSCB. The calculated planar dose distribution is compared to that measured using film dosimetry taken from the beam central axis. We compare the percent depth dose curve and gamma analysis (the dose difference is 3%, and the distance to agreement is 3 mm) results. No significant difference in the PTV dose is observed in the plan with the PSCB compared to that without the PSCB. The maximum, minimum, and mean doses of the OAR in the plan with the PSCB were significantly reduced by 9.7%, 36.6%, and 28.3%, respectively, compared to those in the plan without the PSCB. By applying the PSCB, the OAR volumes receiving 90% and 80% of the prescribed dose were reduced from $14.40cm^3$ to $0.1cm^3$ and from $42.6cm^3$ to $3.7cm^3$, respectively, in comparison to that without using the PSCB. The gamma pass rates of the concave and convex plans were 95% and 98%, respectively. A new procedure of the fabrication of a PSCB is developed using a 3DP. We confirm the usefulness and dosimetric accuracy of the 3D-PSCB for the clinical use. Thus, rapidly advancing 3DP technology is able to ease and expand clinical implementation of the PSCB.

• The Korean Journal of Physiology
• /
• v.1 no.1
• /
• pp.33-41
• /
• 1967

The metabolic patterns of C-1 and C-6-carbon atoms of glucose were observed in the tissue homogenates of the Ehrlich ascites tumor tissue which was incubated for 3 hours in the Dubnuff metabolic shaking incubator. $C^{14}-1-and\;C^{14}-6-glucose$ were used as tracers. The glucose media in which tissue homogenate was incubated was kept at a concentration of 200mg% glucose of carrier and appropriate amount of $C^{14}-1-or\;C^{14}-6-tracer$. At the end of 3 hour incubation, respiratory $CO_2$ samples trapped by alkaline which is placed in the tenter well of incubation flask were analyzed for the total $CO_2$ production rates and their radioactivities. The tissue homogenate samples after incubation were analyzed for their concentrations of glucose, lactate, pyruvate and glycogen and calculations were made on the glucose consumption rate, pyruvate and lactate accumulation rates. The following results were obtained. Data obtained in each group are as follows: 1. In the tissue homogenate, which was incubated with $C^{14}-1-glucose as a substrate, total $CO_2$ production rate averaged $19.0{\pm}5.0{\mu}M/hr/gm$ and the mean specific activity of respiratory $CO_2$ was $840{\pm}296\;cpm/mgC.$ Relative specific activity (RSA) which means the fraction of $CO_2$ derived from medium $C^{14}-1-glucose$ to total $CO_2$ production rate was calculated by ratio of SA of respiratory $CO_2$ and medium $C^{14}-1-glucose.$ RSA was $14.3{\pm}5.0%,$ Accordingly actual $CO_2$ production rate from medium $C^{14}-1-glucose$ showed a mean value of $2.79{\pm}1.35\;{\mu}m$ of which amount was equivalent to the mean value of total glucose consumption rate $(RGDco_2)$, namely, $5.1{\pm}1.3%.$ Lactate and pyruvate appearance rates averaged $7.13{\pm}1.26\;and\;0.21{\pm}0.02{\mu}M/hr/gm,$ respectively. Assuming that these 3 carbon compounds appeared in the medium were derived from glucose, calculations were made that relative glucose disappearance rate into lactate $(RGD_L)$ was $38.0{\pm}5.4%\;and\;RGD_P$ was $1.23{\pm}0.03%.$ Therefore, about 43.3% of the total glucose consumed were accounted for by conversion into the respiratory $CO_2$, lactate and pyruvate. 2. In the second group, which was incubated with $C^{14}-1-glucose$ as a substrate, glucose consumption rate, lactate and pyruvate appearance rates showed almost the same order as the values of the $C^{14}-1-glucose$ substrate group. However, RSA was remarkably decreased showing a mean value of $1.02{\pm}0.13%.$ This fact means that the C-6 carbon of glucose take the minor part in the oxidative metabolism of glucose. The glycogen level in both substrate tissue homogenate showed less than 0.3% of tissue weight. These low value suggested that there was an inhibition of carbohydrate synthesis in the Ehrlich ascites tumor tissue. 3. The catabolic pathway of glucose in the tumor tissue were analyzed on the basis of Bloom's principle from the values of RSA. It was found that in the tumor tissue more than 90% of $CO_2$ derived from glucose were oxidized via the alternate pathway other than principal EMP-TCA cycle such as hexose monophosphate pathway (HMP). From the data described above, it was assumed that in the Ehrlich tumor tissue anaerobic glycolysis proceeds normally although, the oxidation of products of anaerobic glycolysis via the TCA cycle is inhibited resulting in the accumulation of lactate and almost all of oxidative energy from glucose is released by oxidative pathway such as HMP.