• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.374-382
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• 2021

In the present study, we analyzed the decay rate and nutrient dynamics during leaf litter decomposition of Pinus densiflora and Pinus thunbergii in Gongju for 60 months, from 2014 to 2019. P. thunbergii leaf litter decomposed faster than that of P. densiflora. The decay constant of P. densiflora and P. thunbergii leaf litter after 60 months was 3.02 and 3.59, respectively. The initial C/N ratio of P. densiflora and P. thunbergii leaf litter were 14.4 and 14.5, respectively. After 60 months, C/N ratio of decomposing P. densiflora and P. thunbergii leaf litter decreased to 2.26 and 3.0, respectively. The initial C/P ratio of P. densiflora and P. thunbergii leaf litter were 144.1 and 111.3. After 60 months elapsed, the C/P ratio of decomposing P. densiflora and P. thunbergii leaf litter decreased to 40.1 and 45.8, respectively. After 60 months, the percentage of the remaining N, P, K, Ca, and Mg in decomposing P. densiflora leaf litter was 231.08, 130.13, 35.68, 48.58, and 36.03%, respectively. After 60 months, the percentage of the remaining N, P, K, Ca, and Mg in decomposing P. thunbergii leaf litter was 143.91, 74.02, 28.59, 45.08, and 44.99%, respectively. The findings of the present study provide an insight into the forest ecosystem function of coniferous forests through the analysis of the amount of nutrient transfer into the soil through a long-term decomposition process; this information is intended to be used as basic data for preparing counter measures for future climate and ecosystem changes.

• Journal of Plant Biotechnology
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• v.45 no.4
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• pp.382-391
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• 2018

The objective of this study was to determine the most effective medium condition of shoot proliferation and root formation for the efficient in vitro micropropagation of M.26 (Malus pumila Mill). Simple sequence repeat (SSR) markers were used to analyze the genetic diversity of micro-propagated and greenhouse grown M.26. Shoot proliferation was carried out in MS (Murashige and Skoog) containing benzyladenin (BA, $0.5{\sim}5.0mg{\cdot}L^{-1}$) and thidiazuron (TDZ, $0.01{\sim}0.1mg{\cdot}L^{-1}$). The highest number of shoots (10.67 shoots per explant) was induced by adding BA at a concentration $1.0mg{\cdot}L^{-1}$. TDZ treatments caused higher hyperhydricity rate in cultured explants than in BA treatments. There was no significant effect of both BA and auxin on shoot proliferation, and the optimum proliferation medium for M.26 was MS medium containing $1.0mg{\cdot}L^{-1}$ BA. To find a suitable medium composition for shoot rooting, we tested different concentrations indole-3-butyric acid (IBA) and ${\alpha}$-naphthaleneacetic acid ($0.5{\sim}5.0mg{\cdot}L^{-1}$), MS medium (1/4-1), sucrose ($0{\sim}30g{\cdot}L^{-1}$). The shoots showed good rooting on half-strength MS medium containing $1.0mg{\cdot}L^{-1}$ IBA and $15-20g{\cdot}L^{-1}$ sucrose. The rooting rate (100%), number of roots (10.45 ~ 13.60 roots per explant), root length (7.41 ~ 8.33 cm), and shoot length (4.93 ~ 5.38 cm) were good on this medium. Fifteen SSR primers were detected in a total of 30 alleles in 20 micro-propagated plantlets, all SSR profiles from micro-propagated plantlets were monomorphic and similar to greenhouse grown control plantlet M.26 plant. The results indicated that M.26 micro-propagated plantlets were genetically stable.

• Journal of Practical Agriculture & Fisheries Research
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• v.4 no.1
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• pp.119-127
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• 2002

This study was conducted to develop the heat exchanger by utilizing the heat energy of underground water(15℃), which might be used for cooling and heating system of the agricultural facilities. We developed the heat exchanger, parallel type plat fin tube made of Aluminum(Al 6063), which was named Aloo-Heat(No. of The registration design : 0247164, by Korean Intellectual property Office). The fin of exchanger was design of the granulated surface for minimizing fouling factor and dew forms, and also placed parallel to the tube in order to minimized the resistance of flows. 1. Aloo-heat was designed to have 0.03m for inside diameter, 0.036m for outside diameter of tube, 0.0012m for thickness of fin and 0.032m for length of plat fin. 2. t was also designed to have 1.5248m²/m for outside area of heat transfer, 0.0942m²/m for inside area contacting hot liquid, and the ratio (Ra) was 16.1869. 3. Efficiency of the fin was 93 percentage when fin length was 0.032m, and the fin thickness satisfied equation $\frac{h{\rho}}{k}$< 0.2 when it was 0.0012m. 4. According to the performance test of Aloo-heat, as the temperature and rate increased, the heating value also increased, heating value was 504kJ/h·m and 6,048kJ/h·m when it was 60℃, 10 𝑙/min and 80℃, 40 𝑙/min respectively. 5. The test of heating value was confident, because correlation value(R²) was 0.9898 for the temperature and 0.9721 for flow rate of hot liquid, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.142-150
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• 2023

As global warming continues, the time of invasion of Spodoptera frugiperda has been advanced and the inflow rate has been increasing, leading to great increases in damage to crops. In this study, in order to minimize crop damage caused by S. frugiperda, the control period was set for corn fields through control thresholds, and the control effects according to the chemical spraying methods were investigated in forage corn filed. Even under the condition of 4% injury level during the corn silking stage, the damage rate of ear was 70%, showing an aspect of extensive damage. The economic injury level of S. frugiperda second instar larvae was shown to be 0.7 larvae per stalk, and the control threshold level was shown to be 0.6 larvae. The income was calculated by applying the corn wholesale unit price, and according to the result, even under the condition of injury level of 4%, there was a loss of KRW 895,221/10a, and the higher the injury level, the greater the decrease in income. To control S. frugiperda, the insecticidal effects of 10 single formulations registered for S. frugiperda were tested, and according to the results, four types(emamectin benzoate, chlorantraniliprole, indoxacarb, and spinetoram) showed high insecticidal activity not lower than 93.3%, and three types (chloran- traniliprole, spinetoram, and indoxacarb) were considered to be effective in controlling S. frugiperda as they showed high residual effects through insecticidal effect persistence tests. Therefore, conventional control and aerial control were conducted twice at 7-day intervals with indoxacarb SC and chlorantraniliprol WP, which show high activity against S. frugiperda, respectively, prior to the silking of forage corn. As a result, conventional control showed higher control values, 46.3%p in the case of indoxacarb SC and 21.7%p in the case of chlorantraniliprol WP, than aerial control through the primary control. In the secondary control too, higher control values of 26.7%p in the case of indoxacarb SC and 40.4%p in the case of chlorantraniliprol WP were found in conventional control than in aerial control. Therefore, it is considered necessary to prepare measures to improve the control effects in the recent situation where alternative methods for manpower control are widely used.

• Journal of Embryo Transfer
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• v.26 no.1
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• pp.19-25
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• 2011

This study was carried out to evaluate the effect of early pregnant cow as donor for Ovum Pick-Up (OPU) derived oocyte aspiration and embryo production in Holstein heifers. Four non-pregnant and 2 pregnant Holstein heifers were used as donor and then carried out total 17 OPU session for 10 weeks (2 times per week). Recovered cumulus-oocyte-complexes (COCs) were classified into 4 grade by oocyte cytoplasm and cumulus cells and matured in vitro in TCM-199 supplemented with 10% FBS, 10 mg/ml FSH and 1 mg/ml estradiol in 5% $CO_2$ and over 99% humidity for 24 h. After 24 h co-incubation with post-thaw sperm, the presumed zygotes were cultured in CR1aa medium with 4 mg/ml BSA for 3 days and then changed CR1aa medium with 10% of FBS for another 3~4 days. The Mean number of aspirated follicles and collected oocytes in the early stage pregnant and non-pregnant heifers were $13.0{\pm}4.3$ and $10.6{\pm}3.9$, $5.4{\pm}3.4$ and $7.7{\pm}3.6$ per session, respectively. Rate of collected oocyte from aspirated follicles were 59.2% and 50.5%, respectively. The average number of good quality oocytes (Grade I and II) in the early stage pregnant and non-pregnant heifers was $3.7{\pm}2.7$ and $4.9{\pm}2.6$ (Mean${\pm}$SD). Cleavage and blastocyst developmental rates in Grade I and II were 22.2% and 25.5%, and then $1.7{\pm}0.9$ and $1.4{\pm}1.1$ blastocyst per session, respectively. In conclusion, OPU technology can be used in early stage pregnant and non-pregnant heifers without any problem and so applied OPU derived embryo production to maximize the ability of genetically valuable females.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• Journal of agricultural medicine and community health
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• v.29 no.1
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• pp.65-75
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• 2004

Objectives: Immunizations have been one of the most effective measures preventing from infectious diseases. It is quite important national infectious disease prevention policy to keep the immunizations rate high and monitor the immunizations rate continuously. To do this, Korean CDC introduced the National Immunization Registry Program(NIRP) which has been implementing since 2000 at the Public Health Centers(PHC). The National Immunization Registry Program will be near completed after sharing, connecting and transfering vaccination data between public and private sector. The aims of this study was to evaluate the immunization module of non-chart system in private clinic with health information system of public health center(made by POSDATA Co., LTD) and immunization registry program(made by BIT Computer Co., LTD). Methods: The analysis and survey were done by specialists in medical, health field, and health information fields from 2001. November to 2002. January. We made the analysis and recommendation about the immunization module of non-chart system in private clinic. Results and Conclusions: To make improvement on immunization module, the system will be revised on various function like receipt and registration, preliminary medical examination, reference and inquiry, registration of vaccine, print-out various sheet, function of transfer vaccination data, issue function of vaccination certification, function of reminder and recall, function of statistical calculation, and management of vaccine stock. There are needs of an accurate assessment of current immunization module on each private non-chart system. And further studies will be necessary to make it an accurate system under changing health policy related national immunization program. We hope that the result of this study may contribute to establish the National Immunization Registry Program.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1051-1054
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• 1993

The International Atomic Energy Agency's Statute in Article III.A.5 allows it“to establish and administer safeguards designed to ensure that special fissionable and other materials, services, equipment, facilities and information made available by the Agency or at its request or under its supervision or control are not used in such a way as to further any military purpose; and to apply safeguards, at the request of the parties, to any bilateral or multilateral arrangement, or at the request of a State, to any of that State's activities in the field of atomic energy”. Safeguards are essentially a technical means of verifying the fulfilment of political obligations undertaken by States and given a legal force in international agreements relating to the peaceful uses of nuclear energy. The main political objectives are: to assure the international community that States are complying with their non-proliferation and other peaceful undertakings; and to deter (a) the diversion of afeguarded nuclear materials to the production of nuclear explosives or for military purposes and (b) the misuse of safeguarded facilities with the aim of producing unsafeguarded nuclear material. It is clear that no international safeguards system can physically prevent diversion. The IAEA safeguards system is basically a verification measure designed to provide assurance in those cases in which diversion has not occurred. Verification is accomplished by two basic means: material accountancy and containment and surveillance measures. Nuclear material accountancy is the fundamental IAEA safeguards mechanism, while containment and surveillance serve as important complementary measures. Material accountancy refers to a collection of measurements and other determinations which enable the State and the Agency to maintain a current picture of the location and movement of nuclear material into and out of material balance areas, i. e. areas where all material entering or leaving is measurab e. A containment measure is one that is designed by taking advantage of structural characteristics, such as containers, tanks or pipes, etc. To establish the physical integrity of an area or item by preventing the undetected movement of nuclear material or equipment. Such measures involve the application of tamper-indicating or surveillance devices. Surveillance refers to both human and instrumental observation aimed at indicating the movement of nuclear material. The verification process consists of three over-lapping elements: (a) Provision by the State of information such as - design information describing nuclear installations; - accounting reports listing nuclear material inventories, receipts and shipments; - documents amplifying and clarifying reports, as applicable; - notification of international transfers of nuclear material. (b) Collection by the IAEA of information through inspection activities such as - verification of design information - examination of records and repo ts - measurement of nuclear material - examination of containment and surveillance measures - follow-up activities in case of unusual findings. (c) Evaluation of the information provided by the State and of that collected by inspectors to determine the completeness, accuracy and validity of the information provided by the State and to resolve any anomalies and discrepancies. To design an effective verification system, one must identify possible ways and means by which nuclear material could be diverted from peaceful uses, including means to conceal such diversions. These theoretical ways and means, which have become known as diversion strategies, are used as one of the basic inputs for the development of safeguards procedures, equipment and instrumentation. For analysis of implementation strategy purposes, it is assumed that non-compliance cannot be excluded a priori and that consequently there is a low but non-zero probability that a diversion could be attempted in all safeguards ituations. An important element of diversion strategies is the identification of various possible diversion paths; the amount, type and location of nuclear material involved, the physical route and conversion of the material that may take place, rate of removal and concealment methods, as appropriate. With regard to the physical route and conversion of nuclear material the following main categories may be considered: - unreported removal of nuclear material from an installation or during transit - unreported introduction of nuclear material into an installation - unreported transfer of nuclear material from one material balance area to another - unreported production of nuclear material, e. g. enrichment of uranium or production of plutonium - undeclared uses of the material within the installation. With respect to the amount of nuclear material that might be diverted in a given time (the diversion rate), the continuum between the following two limiting cases is cons dered: - one significant quantity or more in a short time, often known as abrupt diversion; and - one significant quantity or more per year, for example, by accumulation of smaller amounts each time to add up to a significant quantity over a period of one year, often called protracted diversion. Concealment methods may include: - restriction of access of inspectors - falsification of records, reports and other material balance areas - replacement of nuclear material, e. g. use of dummy objects - falsification of measurements or of their evaluation - interference with IAEA installed equipment.As a result of diversion and its concealment or other actions, anomalies will occur. All reasonable diversion routes, scenarios/strategies and concealment methods have to be taken into account in designing safeguards implementation strategies so as to provide sufficient opportunities for the IAEA to observe such anomalies. The safeguards approach for each facility will make a different use of these procedures, equipment and instrumentation according to the various diversion strategies which could be applicable to that facility and according to the detection and inspection goals which are applied. Postulated pathways sets of scenarios comprise those elements of diversion strategies which might be carried out at a facility or across a State's fuel cycle with declared or undeclared activities. All such factors, however, contain a degree of fuzziness that need a human judgment to make the ultimate conclusion that all material is being used for peaceful purposes. Safeguards has been traditionally based on verification of declared material and facilities using material accountancy as a fundamental measure. The strength of material accountancy is based on the fact that it allows to detect any diversion independent of the diversion route taken. Material accountancy detects a diversion after it actually happened and thus is powerless to physically prevent it and can only deter by the risk of early detection any contemplation by State authorities to carry out a diversion. Recently the IAEA has been faced with new challenges. To deal with these, various measures are being reconsidered to strengthen the safeguards system such as enhanced assessment of the completeness of the State's initial declaration of nuclear material and installations under its jurisdiction enhanced monitoring and analysis of open information and analysis of open information that may indicate inconsistencies with the State's safeguards obligations. Precise information vital for such enhanced assessments and analyses is normally not available or, if available, difficult and expensive collection of information would be necessary. Above all, realistic appraisal of truth needs sound human judgment.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.