• Korean Journal of Environment and Ecology
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• v.27 no.1
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• pp.99-112
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• 2013

This study aims to show the changes of characteristics of vegetation structure for 20 years(1991~2010) in Naejangsan National Park. As a result of analysis of actual vegetation, the mixed community of Quercus variabilis and Quercus serrata was distributed with 56.1%, and Q. variabilis community showed in southern steep slope with 17.6%. Pinus densiflora community(5.8%) was observed on the ridge and Carpinu tschonoskii community distributed in the slope of the valley with 6.6%. Zelkova serrata and Prunus sargentii community were distributed in valley. The classification by TWINSPAN, ordination by DCA considering importance percentage and property of vegetation class were divided into 4 communities, which are community I(P. densiflora-Q. variabilis community), community II(Q. variabilis community), community III(C. tschonoskii community) and community IV(Mixed deciduous broad-leaved trees community). The age of Pinus densiflora was 32years old and Q. serrata was 36 years old in the community I, that of Q. variabilis was 64 years old in the community II, Q. serrata was 46 years old and C. tschonoskii was 45 years old in the community III, and Acer palmatum was 54 years old and Cornus controversa was 47 years old in the community IV. As the result of Shannon's index of species diversity, the community Iwas ranged from 0.9751 to 1.4199, community II was ranged from 1.0765 to 1.3278, community III was ranged from 1.0353 to 1.2881, and community IV was ranged from 1.1412 to 1.3807. The change of vegetation structure analyzed through the comparison with results of studies carried out 20 years ago were natural selection of P. densiflora, expansion of Quercus spp. and increase of C. tschonoskii. Especially, A. palmatum is dominated by Q. variabilis in canopy layer like the result of study 20 years ago. A. palmatum was analysed by 14.6% in the canopy layer of only mixed deciduous broad-leaved trees community. As a result of analysis of habitat property of Q. variabilis and A. palmatum, Q. variabilis was distributed in dry area with the low value of pH, O.M., exchangeable cations and Avail. P, and A. palmatum was located in the wet valley with huge value of nourishment. The tendency of reduction of bio-diversity by Sasa borealis is same as previous study but, the distributed areas were reduced in Naejangsan area.

• Journal of Wetlands Research
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• v.17 no.2
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• pp.124-129
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• 2015

In order to get as ecological basic data for river restoration, vegetation investigation was conducted in natural river and analysed it synecological methods, such as ordination cluster. 29 plant communities units were identified and the major dominant plant communites were Quercus mongolica community, Pinus densiflora community, Populus davidiana community, Q. variabilis community and Prunus sargentii community. River vegetations were classified into ravine and gorge forest type and riverine softwood forest type. Ravine and gorge forest was dominanted by hardwood which located in steep slope and in high elevation, and riverine softwood forest by softwood, salix spp. Naturality was an important criterion for the selection of rivers, so many of the selected rivers are located in the upper stream and mid stream rather than the lower stream, where more human intervention is involved. Plant communities were consisted of hardwood forest(44 plots, 92%) and softwood forest(4 plot, 8%), respectively. PCA with total layer data showed 5 groups of communities: Q. mongolica community group, Prunus sargentii community group, Pinus densiflora community group, Prunus sargentii community - Pinus densiflora community group and the rest communities group. PCA with tree layer showed 3 groups: Q. mongolica community group, Prunus sargentii community group, and the rest community group. Cluster analysis also a showed a similar communities group to PCA ordination, but Magnolia sieboldii community and Prunus sargentii community were distinguished from the PCA result. From the result, it can be concluded that the plant communities of riparian be divided into hardwood and softwood forest by statistical techniques. It was appropriate to plant species such as Quercus mongolica, Pinus densiflora, Populus davidiana, Quercus variabilis and Prunus sargentii, at levee zone and high water level. And Sliax spp. were appropriate for planted plants at waterfront and low water level. The herb species to be planted on the floodplain were recommanded in the species composition co-occurred with the woody species.

• Journal of Sericultural and Entomological Science
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• v.3
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• pp.1-11
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• 1963

This treatise is to set up a fundamental condition of checking silk lousiness and to set up a new improving method of cocoon bave lousiness after super refining treatment. It is also studied whether silk lousiness can be eliminated through the observation of the silk gland, or the lousiness can be able to improve through such a study. The conclusions obtained in this paper are as follows. 1. Silk lousiness is able to be observed most properly when the light direction and the fiber direction are parallel in plan view of the silk cloth and the greater the angle between them is, the less the lousiness is observed. When, however, the angle is greater than some specific angle(30$^{\circ}$), no more lousiness is observed. This specific angle is named by the author as Lousiness Horizontal Critical Angle. 2. Silk lousiness can be observed when the angle of light incidence against the silk cloth is six degrees, while the larger the angle is, the less the lousiness is observed. When, however, the angle is greater than same specific angle(45$^{\circ}$) the lousiness disappears. Such a specific angle is named by the author as Lousiness Vertical Critical Angle. 3. The best textile composition to decrease lousiness defect is plan weave, while twill and satin weave show more lousiness with the same silk fiber. 4. Lousiness was classified as Lousiness A, B, ana C of which A was the general lousiness, B was the group type, and C was the glucose type and the standard photographs for the lousiness grading of these types were prepared. 5. The proper soap-refining hours of silk for lousiness test was eight hours. 6. The greater the difference of fiber diameter between the cocoon single bave and the splitend was, the more lousiness was composed. The normal splitends were measured as 1/4-1/5 of the main fiber. 7. The lousiness was found at the cocoon shape ends more than other parts, and found at the middle cocoon layer than other layer which was imagined to be as a result of poor uniform bave spinning of silk worm. 8. Female cocoon had more lousiness than the male cocoon. 9. It was found that there was a great possibility to have the splitends through the observation of the anatomical silkgland, and the author reached a conclusion that the lousiness can be improved to a certain degree only by the elimination of abnormal silk gland from the breeding aspects. 10. The cocoon bave of the offspring after super refining lousiness test and selection showed more improved lousiness defect than that of the parents.

• Korean Journal of Poultry Science
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• v.13 no.1
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• pp.1-14
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• 1986

The subject of this study was to obtain some genetic information for developing superior layer chickens. Heterosis and combining ability effects were estimated with 5,759 progenies of full diallel crosses of 6 strains in White Leghorn. Fertility, hatchability, brooder-house viability, rearing- house viability, laying-house viability, age at 1st egg laying, body weight at 1st egg laying, average egg weight, hen-day egg production, hen-housed egg production, and feed conversion were investigated and analyzed into heterosis effect, general combining ability, specific combining ability and reciprocal effect by Grilling's model I. The results obtained were summarized as follows; 1. The general performance of each traits was 94.76% in fertility, 74.05% in hatchability, 97.47% in brooder-house viability, 99.72% in rearing-house viability, 93.81% in laying-house viability, 150 day in the age at 1st egg laying, 1,505g in the body weight at 1st egg laying, 60.08g in average egg weight, 77.11% in hen-day egg production, 269.8 eggs in hen-housed egg Production, and 2.44 in feed conversion. 2. The heterosis effects were estimated to -0.66%, 9.58%, 0.26%, 1.83%, -3.87%, 3.63%, 0.96%, 4.23%, 6.4%, and -0.8%, in fertility, hatchability, brooder-house viability, laying-house viability, the age at 1st egg laying, the body weight at 1st egg laying, average egg weight, hen-day egg Production, hen-housed egg production and feed conversion, respectively. 3. The results obtained from analysis of combining ability were as follows ; 1) Estimates of general combining ability, specific combining ability and reciprocal effects were not high in fertility. It was considered that fertility was mainly affected by environmental factors. In the hatchability, the general combining ability was more important than specific combining ability and reciprocal effects, and the superior strains were K and V which the additive genetic effects were very high. 2) In the brooder-house viability and laying-house viability, specific combining ability and reciprocal effects appeared to be important and the combinations of K${\times}$A and A${\times}$K were very superior. 3) In the feed conversion and average egg weight, general combining ability was more important compared with specific combining ability and reciprocal effects. On the basis of combining ability the superior strains were F, K and B in feed conversion, F and B in the average egg weight. 4) General combining ability, specific combining ability and reciprocal effects were important in the age at 1st egg laying and the combination of V ${\times}$F, F${\times}$K and B${\times}$F were very useful on the basis of these effects. In the body weight at 1st egg laying, general combining ability was more important than specific combining ability and reciprocal effects, relatively. The K, F and E strains were recommended to develop the light strain in the body weight at 1st egg laying. 5) General combining ability, specific combining ability and reciprocal effects were important in the hen-day egg production and hen-housed egg production. The combinations of F${\times}$K, A${\times}$K, and K${\times}$A were proper for developing these traits. 4. In general, high general combining ability effects were estimated for hatchability, body weight at 1st egg laying, average egg weight, hen-day egg production, hen-housed egg production, and feed conversion and high specific combining ability effects for brooder-house viability, laying house viability, age at 1st egg laying, hen-day egg production and hen-housed egg production, and high reciprocal effects for the age at 1st egg laying.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.1
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• pp.118-128
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• 2016

The purpose of this study is to present efficient methods of preserving and managing the fish shelter forest in Mulgun-ri on the southern coast of Korea on the basis of its humanistic, sociological and ecological characteristics. The study object is Korean natural monument No. 150, which is presumed to have been forested by descendants of Jeonju Lee Family who settled there, and village rituals are held every October to pray for the peace of the village. The forest is managed by Namhae-gun as a historical and cultural resource as well as its disaster-preventing, economic, and environmental and ecological functions. The linear form of the area is $23,962.6m^2$ and farmland(48.5%) and urbanization area(38.2%) are extensively located in its periphery area. Actual vegetation was sub-classified into three types of land according to use pressure and whether or not damage was done: land where its stratification was formed; land where it was restored, and the land where it was damaged. Plant communities were sub-classified into Aphananthe aspera community(I) and Zelkova serrata community(II) which had a low use pressure; Z. serrata-Chionanthus retusa-A. aspera community(III) and A. aspera-Z. serrata community(IV) which had a high use pressure; and Celtis sinensis-A. aspera community(V) whose underlayer was damaged by use. Fragmentation of the forest is under way and its inside vegetation growth is hampered due to the installation of traffic and resting facilities such as the through roads costal roads, wooden-deck walkways, parking lots, washstands, etc. As a restoration management plan for this, the following were required: an establishment of preferred restoration area; a selection of restoration vegetation species; and an appropriate restoration method. The damaged area($7,868.2m^2$) will have to be set up as the preferred restoration area; seedlings of restored vegetation species should be raised with dominant species within the forest(i.e., Z. serrata, A. aspera, C. sinensis, and C. retusa) as their 'mother trees' for the benefit of for the next-generation forest; and sub-tree and shrub layer should be complementarily planted with 5 and 115 trees(unit $100m^2$) respectively to facilitate the formation of a multi-layered vegetation structure. In addition, resting facilities scattered inside the forest should be demolished; and indiscriminate use of them should be controlled; management and monitoring should be carried out so that the area can be preserved and restored as a deciduous broad-leaved forest.

• Journal of the korean academy of Pediatric Dentistry
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• v.35 no.3
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• pp.456-468
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• 2008

This study was performed to evaluate the quality of newly offered dentin bonding system($AdheSE^{(R)}$ One) by comparing the degree of microleakage measured with those of several conventional adhesive materials(AQ Bond Plus and $Adper^{TM}$ Single Bond 2). The quality of hybrid layer and resin tags was analyzed by observing restoration/ tooth interface under SEM. All-in-one system is in the limelight for having advantage of reducing chair time of children with difficult behavior pattern. Therefore the possibility of clinical application of All-in-one system was evaluated. The results obtained are as follows; 1. At the enamel margin, group II(AQ Bond Plus) showed the highest value of microleakage, and the other groups showed decreased value in order of group III($AdheSE^{(R)}$ One) and I($Adper^{TM}$ Single Bond 2). There was statistically significant difference between group II and the others(p<0.05), and no statistical difference was found between group I and III. 2. At the dentin margin, microleakage value was increased in order of group II, I, III and significant difference between all groups(p<0.05). 3. In group I and III, microleakage value measured at the enamel margin was significantly lower than that seen at the dentin margin(p<0.05), and there was no statistical difference in group II. 4. Resin tags observed under SEM were very weak and tangled in group II and III while the strong and thick tags were observed in group I. In conclusion, careful case selection and accurate clinical application is recommended in using AQ Bond Plus and $AdheSE^{(R)}$ One, giving consideration of the results showing its higher microleakage and weaker strength than $Adper^{TM}$ Single Bond 2.

• Korean Journal of Poultry Science
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• v.20 no.1
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• pp.1-9
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• 1993

This study carried out to build up new synthetic egg production lines which had sex-linked gene for feather color sexing and also superior combining ability for producing the best commercial chicks. The closed flock breeding method was utilized to improve the general performances in the first experiment and combining ability for heterosis was tested for new synthetic line in the second experimental year. In order to test for the egg production ability in cross breeds synthetic lines, the crossing of B$\times$4 B$\times$C, two imported strains and two domestic strains as controls were compared for the general performances. There was on difference in mortality, body weight to 56 weeks of age. Sexual maturity was delayed about 10 days by comparing with other reports, except 153 days of the Manina White, but no difference among mating systems in this experiment. The hen housed egg production in B$\times$A, B$\times$C was 186.3, 191.3 respectively and it was better than the other controls, except ISA imported lines. The hen-day egg production of B$\times$A, B$\times$C was better than other controls, with 75.7%, 76.8% respectively. In the average egg weight, the B$\times$C cross breed was highest with 64.5g. As the sex of hatching chicks was identified by difference of feather color, the genetic composition of synthetic lines must be homogenized. The feather color of female chicks was brown and that of male was silver (99%), In conclusion, the egg production ability of B$\times$A, B$\times$C cross breeds was superior to the imported and domestic lines. Therefore, it suggest that the synthetic lines with sex-linked gene might be utilized for improving egg production performances.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.