• Economic and Environmental Geology
• /
• v.56 no.6
• /
• pp.697-714
• /
• 2023

The Tracksite of Cretaceous Dinosaurs and Pterosaurs in Jeongchon, Jinju was discovered in late 2017 during the construction of the Ppuri industry complex. This site is a natural heritage site with a high paleontological value, as it preserves fossils of various types of dinosaurs, pterosaurs, and animal traces at a dense concentration. In this study, we surveyed that physical weathering such as joint, crack, scaling, exfoliation, and fragmentation occurred through field research in the fossil site, and conducted basic research on conservation science to reduce the damage. To this end, among the eight levels identified after excavation, the rocks of Level 3, which yielded a large number of theropod footprint fossils, and Level 4, which yielded pterosaur footprint fossils, were analyzed for material characteristics and evaluation of the effectiveness of consolidation and adhesion. This results showed that the rocks in the Level 3 stratum were dark gray siltstone and the rocks in the Level 4 stratum were dark gray shale, which contained a large amount of calcite and were composed of quartz, plagioclase, mica, alkali feldspar, and other clay minerals, which are likely to be damaged by rainfall under external conditions. As a result of conducting an artificial weathering experiment by dividing the probationary sample into four groups: untreated, consolidation treatment, anti-swelling treatment, and adhesive treatment, the consolidation and the swelling inhibitor showed an effect immediately after treatment, but did not show a blocking effect under a freezing-thawing environment. The adhesive showed that the adhesive effect was maintained even under freezing-thawing conditions. In order to preserve the fossil sites at Jeongchon in the future, in addition to temporary measures to block the inflow of moisture, practical measures such as the construction of protective facilities should be prepared.

• Economic and Environmental Geology
• /
• v.56 no.6
• /
• pp.715-728
• /
• 2023

Tracksite of pterosaurs, birds, and dinosaurs in Chungmugong-dong in Jinju was designated as a natural monument in 2011 and is known as the world's largest in terms of the number and density of pterosaur footprints. This site has been managed by installing protection buildings to conserve in 2018. About 17% of the footprints of pterosaur, theropod, and ornithopod in this site under management in the 2nd protection building are of great academic value, but observation of footprints has difficulties due to continuous physical and chemical damage. In particular, the accumulation of milk-white contaminants is formed by the gypsum and air pollutant complex. Gypsum remains evaporated with a plate or columnar shape in the process of water circulation around the 2nd protection building, and the dust is from through the inflow of the gallery windows. The aqueous solution of gypsum, consisting of calcium from the lower bed and sulfur from grass growth, is catchmented into the groundwater from the area behind the protection building. Pollen and a few minerals other constituents of contaminants, go through the gallery window, which makes it difficult to expel dust. To conserve the fossil-bearing beds from two contaminants of different origins, controlling the water and atmospheric circulation of the 2nd protection building and removing the contaminants continuously is necessary. When cleaning contaminants, the steam cleaning method is sufficiently effective for powder-shaped milk-white contaminants. The fossil-bearing bed consists of dark gray shale with high laser absorption power; the laser cleaning method accompanies physical loss to fossils and sedimentary structures; therefore, avoiding it as much as possible is desirable.

• Science of Emotion and Sensibility
• /
• v.26 no.3
• /
• pp.149-160
• /
• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.4 no.1
• /
• pp.31-71
• /
• 1968

To clarify the breeding behavior of the hybrids between tropical and temperate area rice varieties, investigations were made on heading days and grain sterility. In this study, crosses were made in half way diallel involving 7 varieties: 2 photoperied sensitive Indicas, 2 less sensitive intermediate Indicas, 1 Ponlai Japonica and 2 high temperature sensitive Japonicas. The parents and $F_1$s were grown under 10 hours and 14 hours daylength controlled conditions at both IRRI(International Rice Research Institute, N$14^{\circ}$17') and Suwon(N$37^{\circ}$16'). F2s with their parents were grown at IRRI in the short day season, and at Suwon under natural conditions. Fa lines with their parents were grown at Suwon under natural conditions. Observations were made for heading days and sterility. The results are summarized as follow; 1. Heading days : 1. For the $F_1$s, earliness showed dominance or overdominance to lateness under the 10 hours condition, and dominance or partial dominance under the 14 hours conditions, at both IRRI and Suwon. 2. For the $F_2$s grown at IRRI during the shortday season earliness appeared to be dominant over lateness and segregation was not distinct and continuous. In the early season culture of $F_2$s at Suwon earliness showed partial dominance or was intermediate. In the proper season culture of $F_2$s lateness showed partial dominance or was intermediate. 3. In the combinations between late parental varieties which do not head at Suwon, transgressive segregants bearing effective panicles were obtained. 4. The crosses of parental varieties having long basic vegetative growth duration showed bigger variance in heading days, and significant correlation was found between of parental varieties and the mean coefficient of variance for parental arrays. 5. The means of heading days of F2 populations were significantly correlated with those of $F_1$ or mid-parents. The means of F 8 lines were also highly correlated with the means of $F_2$s, but, the means of $F_3$ lines grown at Suwon and of their parental $F_2$ individual, grown at IRRI were not correlated. 6. A faint heritability was calculated from the regression of $F_3$ lines grown at Suwon on the $F_2$ individuals grown at IRRI for most combinations, especially in the combinations involving shortday sensitive varieties. This implies low efficiency for the selection of heading days of $F_2$ individuals at IRRI to be grown in lines at Suwon. 7. No significant reciprocal effects were measured for $F_1$ and $F_2$ mean heading days. 8. Partitioning the observed photoperiod sensitivity. into two components, parental array mean md the deviation from this array mean, the parental photoperiod sensitivity contributing to the hybrids was measured in terms of general and specific combining ability for photoperiod sensitivity. 9. The photoperiod sensitivity of $F_1$s was higher than that of the parents, and it decreased as the generation progressed in most combinations of tested varieties. 10. The response of heading days to difference of temperature was weaker for $F_1$ hybrids than for the parents. The differences of temperature responses between the longday and shortday treatments were specific for the variety. 2. Sterility : 1. The $F_1$ sterility was specific for the combinations and not correlated to the parental sterility. The sterility of $F_1$s grown under the 10 hours condition was higher than of those grown under 14 hours. These results were the same at both locations, IRRI and Suwon. 2. The high sterile combinations in $F_1$ showed high sterility in $F_2$. The combinations between a high photoperiod sensitive variety and a high temperature sensitive variety showed high sterility and wider variance. 3. The mean sterility of $F_2$s was lower than of $F_1$s and the mean of $F_3$ lines was lower than of $F_2$s. Sterility decreased as the generation progressed, and the differences of $F_3$ sterility of different combinations were not significant. 4. A faint correlation between grain sterility and pollen sterility was observed in $F_2$ populations. 5. No significant reciprocal effects were measured in $F_1$ and $F_2$ sterility. 6. Following Griffing's method, specific combining ability effects were higher than general combining ability effects, especially in the combinations between highly photoperiod sensitive varieties and highly temperature sensitive varieties. 7. No distinct correlations were found between $F_2$ individual sterility grown at IRRI and $F_3$ line sterility grown at Suwon. 8. No distinct correlations were observed between heading days and sterility of $F_2$ individuals.

• 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.

• Journal of Korean Society of Forest Science
• /
• v.16 no.1
• /
• pp.1-32
• /
• 1972

By means of the interspecific hybridization in the Sub-genus Diploxylon of the Genus Pinus, $F_1$ hybrids of Pinus rigida${\times}$elliottii, Pinus rigida${\times}$radiata, P. rigida${\times}$serotina and P. densiflora${\times}$thunbergii had been produced. And on the basis of the crossabilities of these hybrids the taxonomic affinities of these pines were examined. And the needle characteristics of these hybrid and the occurence of phenolic substances in these $F_1$ hybrid were also investigated to see the potential usefulness of these characteristics for the diagnosis of the taxonomic affinity. And, the growth performances of the $F_1$ hybrids have also been compared with those of parental species. In order to contribute to the establishment of the hybrid seed orchard the introgression phenomena between P. densiflora and P. thunbergii in the eastern coastal area have also been investigated along with the investigation of the heterozygosity of plus trees of P. densiflora growing in the clone bank in Suwon. And the results were summarized as follows. 1. On the basis of crossabilities as well as on the taxonomic affinities according to the systems of Shaw, Pilger and Duffield, it has been proven that the parental species of those hybrids are of close affinities and range of the fertile hybrid seed production rate was as high as 28-58% in the best hybrid combination (Table 13). 2. Among those hybrids, the ${\times}$ Pinus, rigiserotina hybrid seemed to be most promising in the growth performance exhibiting 109-155% more volume growth compared to the seed parent with the statistic significance of 1% level (Tables 16 and 17). 3. Notwithstanding the fact that the all of the pollen parents are cold tender, all hybrids exhibit cold hardiness as much as their seed parent and it seems to suggest that the characteristics of cold hardiness were transmitted from the seed parent. 4. Though a striking difference in needle length was observed between the parental species of each hybrid, it was difficult to distinguish each hybrid from their seed parent by the needle length except ${\times}$P. rigiserotina which is characterized by long needle which is 65% more longer than the needle of the seed parent (Table 21). 5. With regard to the anatomical characteristics of needle, the hypoderm is apparently thicker in most of the $F_1$ hybrid pines and the characteristics of resin canals are dominated by medial in most $F_1$ hybrid. And, the fibrovascular bundles were apart as were in their seed parent. Therefore it was found to be possible to distinguish the hybrids pines from their parents by the needle characteristics. And, it is to be noticed that the ${\times}$P. densithunbergii was more close to the pollen parent having RDI value of 0.73 (Fig.l, Table 22). 6. It has been demonstrated that ${\times}$P. rigielliottii, ${\times}$P. rigiradiata and ${\times}$P. rigitaeda have a phenolic substance (No.7) of light yellow at Rf-0.46, same as their seed parent, but no trace of phenolic substance was observed in their pollen parent. This fact will serve as an important criteria for early identification of hybridity in progeny testing. However, the fact that both of ${\times}$P. rigiserotina and ${\times}$P. densithunbergii exhibit the same reactions of phenolic substances as well their parental species seems to indicate the close affinities between the parental species of the respective hybrid (Fig.2, Table 23). 7. The separation and the reaction of phenolic substance developed on TLC were found to be same in the same species showing no variations between the individuals, and no variations due to tree part of sampling, tree age or pollen sources. And the reaction was also observed regardless of the not varied by the kind of developing solvent whether it is Aceton-Chloroform (3:7 v/v) or Benzene-Methanol-Acetic acid (90:16:8 v/v). 8. The introgression phenomena of natural Pinus densifiora stand in both east and west coastal area indicates that the major part of the red pines investigated are all heterozygous and the heterozygosity of pines are higher in the west coast than in the east coast(Tables 24 and 25). 9. Based on the RDI, among the plus trees of Pinus densiflora selected in Korea and Japan as well, no pure P. densiflora has been found. Since all of the sample trees of Pinus densiflora were found to be as heterozygous bearing part of the characteristics of P. thunbergii, those red pines were considered to be natural heterotic hybrid pines(Figs. 3 and 4. Tables 26 and 27).

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.45-69
• /
• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.95-108
• /
• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Journal of Korean Society of Forest Science
• /
• v.13 no.1
• /
• pp.67-78
• /
• 1971

The measures of contour-terracing with sod has been executed as a major measures for hillside erosion control works for a long time in Korea. It is, however, recognized that pair terracings make a new slope-face having the more steeper degree of slope between the upper and the lower terraces on hillsides and it also does not contribute for establishing the natural vegetation-cover by penetration of pioneer seeds on the slope faces or cut-faces of hillsides. The study was therefore conducted in connection with the above problems on the cut-face having slope of $40^{\circ}$ and 1.6 meter in slope length with clay soils. Plot allocation for the experiment consists of 3 kinds of 3 replica plots having each $1.6m^2$ of slope area, i. e., the control plot with direct seeding on slopes only ($T_1$), the covering plot with the straw-mats after seeding on slopes ($T_2$) and the seeding plot after covering with the straw-mats. ($T_3$). The main results obtained may be summarized as follows : 1. Effects of the straw-mat mulchings on surface soil loss control:-The total amount of soil losses from each treatments are measured as 4,651 gr from $T_1$, 163 gr. from $T_2$ and 2,891 gr. from $T_3$ treatment respectively. (Refer to table No. 2, 3 and 4). In short, it is recognized that effect of $T_2$ treatment is compared as 28.5 times than that of $T_1$ treatment and 17.7 times than that of $T_3$ treatment respectively. Effect of $T_3$ treatment compared with $T_1$ treatment is also such recognizable as 1.6 times in control of surface soil losses on a slope face. 2. Effect of the straw-mat mulchings on soil moisture content on slopes; -Average per cent of surface soil moisture content by treatments show as 21.60 at the $T_1$, 23.04 at the $T_2$ and 22.21 at the $T_3$ treatment respectively and that of subsurface soil moisture content by treatment show as 23.81 at the $T_1$, 26.16 at the $T_2$ and 24.81 at the $T_3$ treatment respectively. The variance of soil moisture content by treatments was highly significant (Refer table No. 7, 8 and 9). 3. Effect of the straw-mat mulchings on vegetation establishment;-Average numbers of germination by treatments are counted as 237 Nos. at the $T_1$, 246 Nos. at the $T_2$ and 262 Nos. at the $T_3$ treatment plots and the vegetation coverage on ground was almost same as about 90% of covers in all treatments. This effect is more or less lower than that of surface soil erosion control. 4. Regarding the effect on surface soil erosion control, the straw-mat mulchings would be effective as a new measures for control of soil erosion on erosion susceptible lands such slope-faced bare-lands as cut-fill faces, mass-movement faces and bare hillsides.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.18 no.1
• /
• pp.1-8
• /
• 2015

To evaluate accuracy and precision of determination of total alkalinity ($Alk_T$) and carbon dioxide ($TCO_2$) derived from present study, experiment was applied with $CO_2$ CRM (Batch 132, Scripps Institution of Oceanography; $Alk_T=2229.24{\pm}0.39{\mu}mol/kg$, $TCO_2=2032.65{\pm}0.45{\mu}mol/kg$). As the result, average concentration of $Alk_T$ and $TCO_2$ was $2354.09{\mu}mol/kg$ (~5.6% difference with $CO_2$ CRM) and $2089.60{\mu}mol/kg$ (~2.3% difference with $CO_2$ CRM), respectively. For previous method (Gran Titration) by addition $NaHCO_3$ to deionized water($Alk_T$ $2023.33{\mu}mol/kg$), average concentration was $2193.39{\mu}mol/kg$ (sd=57.15, n=7). Whereas, average concentration was $2017.02{\mu}mol/kg$ (sd=10.98, n=7) for the present study. Recovery yield experiments of total alkalinity in deionized water and seawater were implemented by addition of $NaHCO_3$. The recovery yield of deionized water in the range 0 to $4952.39{\mu}mol/kg$ was 100.8% ($R^2$=0.999), and seawater in the range 0 to $2041.32{\mu}mol/kg$ was 102.3% ($R^2$=0.999). Comparison of $pCO_2$ sensor (PSI $CO_2-Pro^{TM}$) with present method showed very meaningful correlation coefficient ($R^2$=0.977) in the range of 427 to $705{\mu}atm$ and 9.16 to $15.24{\mu}mol/kg$ throught elapsed time for two weeks. Field experiment of diurnal variation of total carbon dioxide was accomplished at Sachon harbor in the coastal waters of East Sea of Korea. Concentration of $Alk_T$ and $TCO_2$ was increased during night, and decreased during daylight hours. The results showed mirror type between $TCO_2$ and dissolved oxygen, which was attributable to photosynthesis and respiration of phytoplankton. Also, open ocean field study was performed to obtain vertical profile of $Alk_T$ and $TCO_2$ in C-C zone (Clarion-Clipperton Fracture Zone), Northeastern Pacific. Average concentrations of $Alk_T$ in the surface mixed layer (0~60 m) and deeper layer below 200 m were $2422.38{\mu}mol/kg$ (sd=78.73, n=20) and $2465.87{\mu}mol/kg$ (sd=57.68, n=103), respectively. And average concentrations of $TCO_2$ were $2134.47{\mu}mol/kg$ (sd=65.4, n=20) and $2431.87{\mu}mol/kg$ (sd=65.02, n=103) in the same depth ranges such as $Alk_T$. Vertical distributions of $Alk_T$ and $TCO_2$ concentrations tended to increase with depth, and analyzed concentrations showed slightly higher than those of previous studies in this area.