• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.71-88
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• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

• Journal of Sericultural and Entomological Science
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• v.16 no.1
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• pp.67-75
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• 1974

The studies are to know how much cocoon crops is damaged by the stained leaf with nicotine produced from the tobacco field cultivated in mulching system in spring season and by residual nicotine in autumn season. Furthermore, the new knowledges are to make both industries keep up with their development. In spring season mulberry Held is located higher on the West-North of tobacco held below 20 degrees of slope and with 36 per cent of East-South wind and 18 per cent of South wind blowing from tobacco fold to the mulberry fold. In addition, silkworm larvae are fed with the mulberry leaf produced in the different plots placing by the different distances, l0m, 25m, 50m, 80m, and loom far from the tobacco Held as a control and it is also considered that narcotic larvae including the dead larvae are not observed. On the other hand, it is noted that better leaf quality and abundant growth of mulberry tree is produced from the mulberry fold closer to the tobacco field and with a low slope. 1) Maximum weight of larval body at the 5th stage is damaged by the stained leaf with the nicotine up to 25m far from the tobacco held. 2) The larvae fed with the mulberry leaf in mulberry Held up to 25m far from the tobacco fold produce small number of the fresh cocoons per 1 liter. 3) Low single cocoon weight and low cocoon shell weight are produced by the poison damaged larvae fed with the mulberry. leaf up to 25m far from the tobacco field and weight of cocoon shell is damaged higher than the single cocoon weight. It is resulted in low percentage of cocoon shell. 4) Cocoon yield including the double cocoon from 10,000 larvae is decreased by the larvae fed with the stained leaf in the mulberry fold up to 25m far from the tobacco fold and 19 per cent of cocoon yield is decreased with 2.4kg of cocoon yield in l0m plot and with 2.5kg of cocoon yield in 25m plot at the first season and at the 2nd season with 1.8kg o( cocoon yield in l0m plot and with 11.5kg of cocoon yield in 25m plot, 11 per cent and 9 per cent of cocoon yield including double cocoon from 10,000 larvae is decreased, as compared with the control, respectively. With these results, it is observed that nicotine damage is occurred to the silkworm larvae if the larvae are fed with the leaf in the mulberry Held within 25m-50m far from the tobacco field.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.44-56
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• 2009

Impulse purchasing is defined as an immediate purchase with no pre-shopping intentions. Previous studies of impulse buying have focused primarily on factors linked to marketing mix variables, situational factors, and consumer demographics and traits. In previous studies, marketing mix variables such as product category, product type, and atmospheric factors including advertising, coupons, sales events, promotional stimuli at the point of sale, and media format have been used to evaluate product information. Some authors have also focused on situational factors surrounding the consumer. Factors such as the availability of credit card usage, time available, transportability of the products, and the presence and number of shopping companions were found to have a positive impact on impulse buying and/or impulse tendency. Research has also been conducted to evaluate the effects of individual characteristics such as the age, gender, and educational level of the consumer, as well as perceived crowding, stimulation, and the need for touch, on impulse purchasing. In summary, previous studies have found that all products can be purchased impulsively (Vohs and Faber, 2007), that situational factors affect and/or at least facilitate impulse purchasing behavior, and that various individual traits are closely linked to impulse buying. The recent introduction of new distribution channels such as home shopping channels, discount stores, and Internet stores that are open 24 hours a day increases the probability of impulse purchasing. However, previous literature has focused predominantly on situational and marketing variables and thus studies that consider critical consumer characteristics are still lacking. To fill this gap in the literature, the present study builds on this third tradition of research and focuses on individual trait variables, which have rarely been studied. More specifically, the current study investigates whether impulse buying tendency has a positive impact on impulse buying behavior, and evaluates how consumer characteristics such as the need for cognitive closure (NFCC), psychological wellbeing, and susceptibility to interpersonal influences affect the tendency of consumers towards impulse buying. The survey results reveal that while consumer affective impulsivity has a strong positive impact on impulse buying behavior, cognitive impulsivity has no impact on impulse buying behavior. Furthermore, affective impulse buying tendency is driven by sub-components of NFCC such as decisiveness and discomfort with ambiguity, psychological wellbeing constructs such as environmental control and purpose in life, and by normative and informational influences. In addition, cognitive impulse tendency is driven by sub-components of NFCC such as decisiveness, discomfort with ambiguity, and close-mindedness, and the psychological wellbeing constructs of environmental control, as well as normative and informational influences. The present study has significant theoretical implications. First, affective impulsivity has a strong impact on impulse purchase behavior. Previous studies based on affectivity and flow theories proposed that low to moderate levels of impulsivity are driven by reduced self-control or a failure of self-regulatory mechanisms. The present study confirms the above proposition. Second, the present study also contributes to the literature by confirming that impulse buying tendency can be viewed as a two-dimensional concept with both affective and cognitive dimensions, and illustrates that impulse purchase behavior is explained mainly by affective impulsivity, not by cognitive impulsivity. Third, the current study accommodates new constructs such as psychological wellbeing and NFCC as potential influencing factors in the research model, thereby contributing to the existing literature. Fourth, by incorporating multi-dimensional concepts such as psychological wellbeing and NFCC, more diverse aspects of consumer information processing can be evaluated. Fifth, the current study also extends the existing literature by confirming the two competing routes of normative and informational influences. Normative influence occurs when individuals conform to the expectations of others or to enhance his/her self-image. Whereas informational influence occurs when individuals search for information from knowledgeable others or making inferences based upon observations of the behavior of others. The present study shows that these two competing routes of social influence can be attributed to different sources of influence power. The current study also has many practical implications. First, it suggests that people with affective impulsivity may be primary targets to whom companies should pay closer attention. Cultivating a more amenable and mood-elevating shopping environment will appeal to this segment. Second, the present results demonstrate that NFCC is closely related to the cognitive dimension of impulsivity. These people are driven by careless thoughts, not by feelings or excitement. Rational advertising at the point of purchase will attract these customers. Third, people susceptible to normative influences are another potential target market. Retailers and manufacturers could appeal to this segment by advertising their products and/or services as products that can be used to identify with or conform to the expectations of others in the aspiration group. However, retailers should avoid targeting people susceptible to informational influences as a segment market. These people are engaged in an extensive information search relevant to their purchase, and therefore more elaborate, long-term rational advertising messages, which can be internalized into these consumers' thought processes, will appeal to this segment. The current findings should be interpreted with caution for several reasons. The study used a small convenience sample, and only investigated behavior in two dimensions. Accordingly, future studies should incorporate a sample with more diverse characteristics and measure different aspects of behavior. Future studies should also investigate personality traits closely related to affectivity theories. Trait variables such as sensory curiosity, interpersonal curiosity, and atmospheric responsiveness are interesting areas for future investigation.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.39-49
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• 2018

"Annals of The Joseon Dynasty" is a book recording the Joseon Dynasty's historical facts in an annalistic format. The King's amusement activities through "Annals of The Joseon Dynasty" which were established by the Ye-ak(禮樂) system were analyzed. The results are as follows. The king's amusement activities that were performed during the Joseon Dynasty period could be classified as state banquets, military banquets, and banquets for play. The analysis of the king's amusement activity was divided into five stages. The characteristic of [1 period : King Taejo~Sejo(Yejong)] was dominated the military banquets of the Goryeo Dynasty. Neo-Confucianism is the establishment of political and social turning of the ballast, considerations of military culture, culture, and Hoeryeyeon Jinpungjeong, a cloud of dust and elders banquets such as Giroyeon and Yangnoyeon on the nature of the party. A lasting ordinance was institutionalized[2 period : King Seongjong~Jungjong]. In the chopper and jeongyujaeran, Hong Kyung Rae led a royal amusement activities are stagnant, often produce isolated storage compute in the gloomy situation[3 period : King Injong~Hyeonjong]. Revival period is pride of the amusement activity through the culture of Joseon Dynasty royal culture [4 period : King Sukjong~Jeongjo]. The throne, crashed due to political power is an ebb of royal amusement activities, while also rapidly waning[5 period : King Seonjo~Seonjong]. During the early Joseon Dynasty, hunting took place around the forest area northeast of Hanyang and during King Seongjong's period, it took place closer to the capital city, while in Lord Yeonsan's period, it was expanded to a 39 kilometer radius area from the palace, and banquets such as various forms of entertainment of Cheoyongmu, and Flower-viewing. The Joseon kings who enjoyed hunting were King Sejong, Sejo, Seongjong, Yeonsan, and Jungjong. Most of hunting objects were tigers, bears, deer and roe deer, leopards, boars, their animals and falconry took, and the purpose of the hunting was to perform ancestral rites to the royal ancestry or the royal tombs. Lord Yeonsan's hunting activities had negative effects after King Jungjong the king's hunting activity decreased sharply. However, there were also positive aspects of Lord Yeonsan's Prohibition of cutting woods ect. In conclusion, the expansion of the King's garden(庭:courtyard${\rightarrow}$園:privacy garden${\rightarrow}$苑:king's garden${\rightarrow}$苑?:national hunting park) is evident which starts from formal and informal activities that took place in Oejo, Chijo, and Yeonjo, which went further to the separate and secret gardens, and then even further, thus setting the amusement activity area as a 39 kilometer radius range from Hanyang.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Korean Journal of Heritage: History & Science
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• v.44 no.1
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• pp.72-105
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• 2011

This study explores the value of the Dicentra spectabilis community as a nature reserve in provincial forests at San 1-2, Daea-ri, Dongsang-myeon, Wanju-gun, Jellabuk-do, also known as Gamakgol, while defining the appropriateness of its living environment and eventually providing basic information to protect this area. For these reasons, we investigated 'morphological and biological features of Dicentra spectabilis' and the 'present situation and problems of designing a herbaceous nature reserve in Korea.' Furthermore, we researched and analyzed the solar, soil and vegetation condition here through a field study in order to comprehend its nature reserve value. The result is as follows. According to the analytic result for information on the domestic wild Dicentra spectabilis community, it is evenly spread throughout mountainous areas, and there is one particularly outstanding in size in Wanju Gamakgol. Upon the findings from literature and the field study about its dispersion, Gamakgol has been discovered as an ideal district for Dicentra spectabilis since it meets all the conditions this plant requires to grow vigorously, such as a quasi-high altitude and rich precipitation during its period of active growth duration in May. Dicentra spectabilis grows in rocky soil ranging from 300~375m above sea level, 344.5m on average, towards the north, northwest and dominantly in the northeast. The mean inclination degree is $19.5^{\circ}$. Also, upon findings from analyzing solar conditions, the average light intensity during its growth duration, from Apr. to Aug., is 30,810lux on average and it tends to increase, as it gets closer to the end. This plant requires around 14,000~18,000lux while growing, but once bloomed, fruits develop regardless of the degree of brightness. The soil pH has shown a slight difference between the topsoil, at 5.2~6.1, and subsoil, at 5.2~6.2. Its mean pH is 5.54 for topsoil and 5.58 for subsoil. These results are very typical for Dicentra spectabilis to grow in, and other comparative areas also present similar conditions. Given the facts, the character of the soil in Gamakgol has been evaluated to have high stability. Analysis of its vegetation environment shows a wide variation of taxa numbering from 13 to 52 depending on area. The total number of taxa is 126 and they are a homogenous group while showing a variety of species as well. The Dicentra spectabilis community in the Daea-ri Arboretum is an herbaceous community consisting of dominantly Dicentra spectabilis, Cardamine leucantha, Boehmeria tricuspi and Impatiens textori while having many differential species such as Impatiens textori, Pueraria thunbergiana, Rubus crataegifolius vs Staphylea bumalda, Securinega suffruticosa, and Actinidia polygama. It suggests that it is a typical subcolony divided by topographic features and soil humidity. Considering the above results on a comprehensive level, this area is an excellent habitat for wild Dicentra spectabilis providing beautiful viewing enjoyment. Additionally, it is the largest wild colony of Dicentra spectabilis in Korea whose climate, topography, soil conditions and vegetation environment can secure sustainability as a wild habitat of Dicentra spectabilis. Therefore, We have determined that the Gamakgol community should be re-examined as natural asset owing to its established habitat conditions and sustainability.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.163-170
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• 2014

Purpose : If electron, chosen for superficial oncotherapy, was applied with bolus, it could work as an important factor to a therapy result by showing a drastic change in surface dose. Hence the calculation value and the actual measurement value of surface dose of Treatment Planning System (TPS) according to four variables influencing surface dose when using bolus on an electron therapy were compared and analyzed in this paper. Materials and Methods : Four variables which frequently occur during the actual therapies (A: bolus thickness - 3, 5, 10 mm, B: field size - $6{\time}6$, $10{\time}10$, $15{\time}15cm2$, C: energy - 6, 9, 12 MeV, D: gantry angle - $0^{\circ}$, $15^{\circ}$) were set to compare the actual measurement value with TPS(Pinnacle 9.2, philips, USA). A computed tomography (lightspeed ultra 16, General Electric, USA) was performed using 16 cm-thick solid water phantom without bolus and total 54 beams where A, B, C, and D were combined after creating 3, 5 and 10 mm bolus on TPS were planned for a therapy. At this moment SSD 100 cm, 300 MU was investigated and measured twice repeatedly by placing it on iso-center by using EBT3 film(International Specialty Products, NJ, USA) to compare and analyze the actual measurement value and TPS. Measured film was analyzed with each average value and standard deviation value using digital flat bed scanner (Expression 10000XL, EPSON, USA) and dose density analyzing system (Complete Version 6.1, RIT, USA). Results : For the values according to the thickness of bolus, the actual measured values for 3, 5 and 10 mm were 101.41%, 99.58% and 101.28% higher respectively than the calculation values of TPS and the standard deviations were 0.0219, 0.0115 and 0.0190 respectively. The actual values according to the field size were $6{\time}6$, $10{\time}10$ and $15{\time}15cm2$ which were 99.63%, 101.40% and 101.24% higher respectively than the calculation values and the standard deviations were 0.0138, 0.0176 and 0.0220. The values according to energy were 6, 9, and 12 MeV which were 99.72%, 100.60% and 101.96% higher respectively and the standard deviations were 0.0200, 0.0160 and 0.0164. The actual measurement value according to beam angle were measured 100.45% and 101.07% higher at $0^{\circ}$ and $15^{\circ}$ respectively and standard deviations were 0.0199 and 0.0190 so they were measured 0.62% higher at $15^{\circ}$ than $0^{\circ}$. Conclusion : As a result of analyzing the calculation value of TPS and measurement value according to the used variables in this paper, the values calculated with TPS on 5 mm bolus, $6{\time}6cm2$ field size and low-energy electron at $0^{\circ}$ gantry angle were closer to the measured values, however, it showed a modest difference within the error bound of maximum 2%. If it was beyond the bounds of variables selected in this paper using electron and bolus simultaneously, the actual measurement value could differ from TPS according to each variable, therefore QA for the accurate surface dose would have to be performed.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.93-104
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• 2017

CCS (Carbon Capture and Storage) is a technical process to capture $CO_2$ from industrial and energy-based sources, to transfer and sequestrate impressed $CO_2$ in geological formations, oceans, or mineral carbonates. However, potential $CO_2$ leakage exists and causes environmental problems. Thus, this study was conducted to analyze the spatial and temporal variations of $CO_2$ fluxes and concentrations after artificial $CO_2$ release. The Environmental Impact Evaluation Test Facility (EIT) was built in Eumseong, Korea in 2015. Approximately 34kg $CO_2$ /day/zone were injected at Zones 2, 3, and 4 among the total of 5 zones from October 26 to 30, 2015. $CO_2$ fluxes were measured every 30 minutes at the surface at 0m, 1.5m, 2.5m, and 10m from the $CO_2$ releasing well using LI-8100A until November 13, 2015, and $CO_2$ concentrations were measured once a day at 15cm, 30cm, and 60cm depths at every 0m, 1.5m, 2.5m, 5m, and 10m from the well using GA5000 until November 28, 2015. $CO_2$ flux at 0m from the well started increasing on the fifth day after $CO_2$ release started, and continued to increase until November 13 even though the artificial $CO_2$ release stopped. $CO_2$ fluxes measured at 2.5m, 5.0m, and 10m from the well were not significantly different with each other. On the other hand, soil $CO_2$ concentration was shown as 38.4% at 60cm depth at 0m from the well in Zone 3 on the next day after $CO_2$ release started. Soil $CO_2$ was horizontally spreaded overtime, and detected up to 5m away from the well in all zones until $CO_2$ release stopped. Also, soil $CO_2$ concentrations at 30cm and 60cm depths at 0m from the well were measured similarly as $50.6{\pm}25.4%$ and $55.3{\pm}25.6%$, respectively, followed by 30cm depth ($31.3{\pm}17.2%$) which was significantly lower than those measured at the other depths on the final day of $CO_2$ release period. Soil $CO_2$ concentrations at all depths in all zones were gradually decreased for about 1 month after $CO_2$ release stopped, but still higher than those of the first day after $CO_2$ release stared. In conclusion, the closer the distance from the well and the deeper the depth, the higher $CO_2$ fluxes and concentrations occurred. Also, long-term monitoring should be required because the leaked $CO_2$ gas can remains in the soil for a long time even if the leakage stopped.

• Korean Journal of Soil Science and Fertilizer
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• v.6 no.1
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• pp.17-26
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• 1973

A survey on nutrient recovery by rice plant was carried out countrywide in 1967 and 1968. The relationships between percent recovery of fertilizer nutrient and climatic zone or deposition mode, drainage grade, and texture of paddy soil profile, or chemical characteristics of surface soil were as follows. 1. The percent recovery of fertilizer nitrogen was highest in south and least in north, and that of potassium was highest in south and least in middle climatic zone. 2. Since the percent recovery of Phosphorus variates yearly with climatic zone, mode of deposition drainage grade or soil texture, it seemed to depend greatly on soil-weather interaction. 3. Nitrogen recovery was highest in alluvial colluvial (AC) and it was followed by alluvial (A), fluvomarine (FM) and old alluvial in decreasing order while potassium recovery was OA>AC>A>FM. 4. The greater the drainage was, the higher the nitrogen recovery. The recovery of potassium and phosphorus tended to show high in moderately well drain, and low in poorly and well drain. 5. Nitrogen recovery was highest in fine silty and gradually decreased with coarseness. That of potassium or phosphorus was greater in those below fine loamy than in those above coarse silty. 6. Nitrogen recovery was high in Jisan, Geugrag, and Sindab series, and low in Hwadong, Gyuam, Yongji and Hwabong series. 7. Nitrogen recovery showed significant positive correlation with the content of organic matter (OM), Ca, CEC of surface soil and only in the year of high phosphorus recovery it had significant negative correlation with soil phosphorus. Phosphorus recovery had significant posititive correlation with CEC, Mg or Ca. 8. Potassium recovery showed negative correlation with K/(Ca+Mg), P, OM or K while positive correlation with Ca, Mg, CEC but significant only with K/(Ca+Mg) in the year of low potassium recovery. In the year of high K recovery it showed positive correlation with P, OM, K/(Ca+Mg) or K while negative with CEC, Mg or Ca but significant only with P, OM or CEC. Soil potassium has significant positive correlation with soil OM and P only in the year of low potassium recovery. 9. The percent recovery of N, P or K showed negative correlation coefficient with pH without significant. 10. There was significant positive correlation between OM and P, K or K/(Ca+Mg), P and K or K/(Ca+Mg), K and K/(Ca+Mg), Mg or CEC, Ca and K/(Ca+Mg), Mg, CEC or pH, Mg and CEC while significant negative correlation between Mg and OM, P or K/(Ca+Mg), P and CEC, Ca and K/(Ca+Mg). 11. From the percent rcovery of fertilizer and soil chemical characteristics it was known that soil organic matter increase nitrogen uptake, that K uptake has closer relation to K/(Ca+Mg) than K, that Mg affects P ugtake, and that the annual difference of P and K recovery was partly explainable.