• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.1-17
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• 2019

In this study, the surveys were carried out from October (2016) to October (2017) along the tidal flat of Geunso Bay, Taean Peninsula of the western edge of Korea. The sampling trips were carried out for a total of 16 times, once or twice a month. In order to investigate the monthly variation of the microphytobenthos (MPB) biomass, community composition and photo-physiology were analyzed by HPLC (High performance liquid chromatography). The total chlorophyll a (TChl a) concentrations used as an indicator of biomass of MPB in the upper 1 cm sediment layer ranged from 40.4 to $218.9mg\;m^{-2}$ throughout the sampling period. TChl a concentrations showed the maximum level on $24^{th}$ of February and remained high throughout March after which it started to declined. The biomass of MPB showed high values in winter and low values in summer. The monthly variations of Phaeophorbide a concentrations suggested that the low grazing intensity of the predator in the winter may have partly attributed to the MPB winter blooming. As a result of monthly variations of the MPB community composition using the major marker pigments, the concentrations of fucoxanthin, the marker pigment of benthic diatoms, were the highest throughout the year. The concentrations of most of the marker pigments except for chlorophyll b (chlorophytes) and peridinin (dinoflagellates) increased in winter. However, the concentrations of fucoxanthin increased the highest, and the relative ratios of the major marker pigments to TChl a except fucoxanthin decreased during the same period. The vertical distribution of Chl a and oxygen concentrations in the sediments using a fluorometer and an oxygen micro-optode Chl a concentrations decreased with oxygen concentrations with increasing depth of the sediment layers. Moreover, this tendency became more apparent in winter. The Chl a was uniformly vertical down to 12 mm from May to July, but the oxygen concentration distribution in May decreased sharply below 1 mm. The increase in phaeophorbide a concentration observed at this time is likely to be caused by increased oxygen consumption of zoobenthic grazing activities. This could be presumed that MPB cells are transported downward by bioturbation of zoobenthos. The relative ratios (DT/(DD+DT)) obtained with diadinoxanthin (DD) and diatoxanthin (DT), which are often used as indicators of photo-adaptation of MPB, decreased from October to March and increased in May. This indicated that there were monthly differences in activity of Xanthophyll cycle as well.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.157-167
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• 2009

Recently, the leakage of confidential information and personal information is taking place on the Internet more frequently than ever before. Most of such online security incidents are caused by attacks on vulnerabilities in web applications developed carelessly. It is impossible to detect an attack on a web application with existing firewalls and intrusion detection systems. Besides, the signature-based detection has a limited capability in detecting new threats. Therefore, many researches concerning the method to detect attacks on web applications are employing anomaly-based detection methods that use the web traffic analysis. Much research about anomaly-based detection through the normal web traffic analysis focus on three problems - the method to accurately analyze given web traffic, system performance needed for inspecting application payload of the packet required to detect attack on application layer and the maintenance and costs of lots of network security devices newly installed. The UTM(Unified Threat Management) system, a suggested solution for the problem, had a goal of resolving all of security problems at a time, but is not being widely used due to its low efficiency and high costs. Besides, the web filter that performs one of the functions of the UTM system, can not adequately detect a variety of recent sophisticated attacks on web applications. In order to resolve such problems, studies are being carried out on the web application firewall to introduce a new network security system. As such studies focus on speeding up packet processing by depending on high-priced hardware, the costs to deploy a web application firewall are rising. In addition, the current anomaly-based detection technologies that do not take into account the characteristics of the web application is causing lots of false positives and false negatives. In order to reduce false positives and false negatives, this study suggested a realtime anomaly detection method based on the analysis of the length of parameter value contained in the web client's request. In addition, it designed and suggested a WAF(Web Application Firewall) that can be applied to a low-priced system or legacy system to process application data without the help of an exclusive hardware. Furthermore, it suggested a method to resolve sluggish performance attributed to copying packets into application area for application data processing, Consequently, this study provide to deploy an effective web application firewall at a low cost at the moment when the deployment of an additional security system was considered burdened due to lots of network security systems currently used.

• 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 Food Hygiene and Safety
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• v.20 no.4
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• pp.258-266
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• 2005

Licorice Extract and Erythritol, food additives used in korea, are widely used in foods as sweetener. Its application for use in food is regulated by the standard and specification for food additives but official analytical method far determination of these sweetener in food has not been established. Accordingly, we has been carried out to set up analytical method of the glycyrrhizic acid in several foods by the way of thin layer chromatography and high performance liquid chromatography glycyrrhizic acid is qualitative anaylsis technique consists of clean-up with a sep-pak $C_{18}$ cartridge, separation of the sweeteners by Silica gel 60 F254 TLC plate using 1-butanol:4Nammonia solution:ethanol (50:20:10) as mobile solvent. Also, the quantitative analysis for glycyrrhizic acid, was performed using Capcell prk $C_{18}$ column at wavelength 254nm and DW:Acetonitrile (62:38 (pH2.5)) as mobile phase. and we has been carried out to set up analytical method of the erythritol in several foods by the way of high performance liquid chromatography. erythritol is qualitative anaylsis technique consists of clean-up with a DW and hexane. The quantitative analysis for erythritol, was performed using Asahipak NH2P-50 column, Rl and DW:Acetonitrile (25:75) as mobile phase. The glycyrrhizic acid results determined as glycyrrhizic acid in 105 items were as follows; N.D$\∼$48.7ppm for 18 items in soy sauce, N.D$\∼$5.3ppm for 12 items in sauce, N.D$\∼$988.93ppm for 15 items in health food, N.D$\∼$180.7ppm for 26 items in beverages, N.D$\∼$2.6ppm for 8 items in alcoholic beverages repectively and ND for 63 items in the ethers. The erythritol results determined as erythritol in 52 items were as follows; N.D$\∼$155.6ppm for 13 items in gm, N.D$\∼$398.1ppm for 12 items in health foods repectively and ND for 45 items in the others.

• Korean Journal of Poultry Science
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• v.38 no.1
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• pp.59-69
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• 2011

This study was conducted to investigate the effects of dietary supplementation of CS682, a fermentation product of Actinomycetae(Nocardia sp. CS682), and its commercial product DSC682$^{(R)}$ on the performance, blood parameters, intestinal microflora, and immune response in laying hens. Hy-Line Brown$^{(R)}$ laying hens were housed in two bird cages. Feeding trial lasted 5 wk under 16.5 h:7.5 h(L:D) lighting regimen. In Exp.1, a total of 480 birds of 86 wk old were assigned to four dietary treatments: Control, Antibiotics (6 ppm avilamycin), CS682-0.1 (CS682 0.1%) and CS682-1.0 (CS682 1.0% supplementation). Each treatment was replicated five times with 24 birds (or 12 cages) per replication. In Exp. 2, a total of 1,000 birds of 26 wk old were assigned to five dietary treatments: Control, Antibiotics (6 ppm avilamycin), DCS682-0.05 (DCS682 0.05%), DCS682-0.1 (DCS682 0.1%), DCS682-0.2 (DCS682 0.2% supplementation). Each treatment was replicated five times with 40 birds (or 20 cages) per replication. In Exp. 1, there were no significant differences among treatments in egg production, egg weight, broken & soft egg production, feed intake, and feed conversion ratio. Also, there were no significant differences among treatments in eggshell thickness, eggshell color and Haugh unit. However, eggshell strength was significantly (p<0.05) greater in CS682 and Antibiotics treatments than Control, and egg yolk color was significantly (p<0.05) higher in CS682-1.0 than Control. In Exp. 2, feed intake was significantly (p<0.05) lower in DSC682-0.05 than Control. Lightness(L) of Hunter Lab color of eggshell of DCS and Antibiotics treatments was significantly (p<0.05) lower than Control. Egg yolk color of DCS 0.1 and 0.2 treatments was significantly (p<0.05) higher than Control. Haugh unit increased significantly (p<0.05) in Antibiotics and DCS682-0.1 treatments. The immunoglobulin levels of plasma (IgG and IgA) and eggyolk (IgY) were not significantly affected by treatments. Antibiotics and CS682 or DCS682 treatments significantly (p<0.05 or 0.01) influenced some of the erythrocytes and leukocytes parameters in blood. In Exp.1, mean corpuscular volume (MCV) decreased by CS682 treatments and mean corpuscular hemoglobin (MCH) was highest in Antibiotics treatments. In Exp.2, the level of monocyte (MO) decreased in DCS682-0.10 and 0.20 treatments. The cfu of C. perfringens and S. typhimurium in small intestinal content were highest in Control and lowest in Antibiotics in both experiments. In Exp. 2, DSC682-0.05 and -0.1 treatments were highest and Antibiotic treatment was lowest in Lactobacilli spp. The results of the present layer experiments indicated that supplementation of 0.1~0.2% CS682 or DCS682 may increase eggshell strength, color of eggshell and eggyolk, Haugh unit, and control harmful intestinal microbes.

• Korean Journal of Poultry Science
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• v.17 no.3
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• pp.179-191
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• 1990

In order to study the effects of supplementation of live yeast(Saccharomyces cerevisiae) on the performance of laying hens, five experiments were conducted. Two experiment were conducted during summer period, one with 37 wk old Dekalb-Delta strain laying birds(Exp. 1) and the other one with 100 wk old molted Nick Chick Brown laying birds(Esp.2) . In each experiment, 240 birds were divided into 12 groups of 20 birds each and randomly distributed. Each of the two experimental diets(Control 71 and 0.05% live yeast supplemented 72) was fed to 6 groups for 4 wks in Exp.1 and 3 wks in Exp.2. Three experiments were conducted during winter period, Exp.2 with 54 wk old Hy-Line strain laying birds, Exp.4 with 52 wk old Hy-Line strain laying birds, and Exp.5 with 36 wk old broiler breeder(Indian River strain). In each experiment, 540 birds were divided into 18 groups of 30 birds each and randomly distributed. Each of the 3 experimental diets(Control：$T_1$0.05% live yeast supplemented：$T_2$ and 0.1% live yeast supplemented ： T$_3$) was fed to 9 groups for 6 wks in Exp.3, 9 wks in Exp.4 and 4 wks in Exp.5. In Exp.4, Latin Square design was employed to determine the effects of switching feeds at 3 wk intervals. All hens were housed in cages of commercial farm and experimental diets were made with commercial layer feeds. In Experiment 1, egg production was significantly(P＜0.05) higher in $T_2$. Feed intake was significantly (P＜higher in 72 at 1st wk but 4 wk average was not significantly different. Feed efficiency was significantly(P＜0.01) better in 72 at End wk but 4 wk average was not significantly different. Other parameters, such as weight, soft egg production, cracked egg production and mortality were not significantly different. In Experiment 2, egg production was significantly(P＜0.05) higher in $T_2$. Feed efficiency was significantly (P＜0.05 and P＜0.01) better at End wk and 3rd wk but 3 wk average was not significantly different. Soft egg production was significantly(P＜0.05) higher in 72. Other parameters were not significantly different. In Experiment 3, egg productions were significantly(P＜0.05) different among treatments ： $T_3$ was higher than $T_1$ and $T_2$ was higher than $T_1$. Egg weight of $T_1$ and $T_2$was significantly(P＜0.05) heavier than $T_3$. Feed intake of $T_2$ and $T_3$ was significantly(P＜0.05) higher than $T_1$ at 6th wk but overall average was not significantly different. Soft egg production were significantly(P＜0.01) different among treatments：$T_1$ was higher than $T_3$ was higher than $T_2$. Feed efficiency cracked e99 Production and mortality were not signifcantly different. In Experiment 4, egg production tended to increase as the level of live yeast supplementation increased but they were not statistically different. In Experiment 5, egg production of broiler breeders of $T_3$ was significantly(P＜0.01) higher than $T_1$. Feed intake of $T_3$ was significantly(P＜0.05) greater than $T_1$ and $T_2$ at 3rd wk but overall average was not significantly different. Fertility and hatchability tended to be higher in the supplemented groups than in the control.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.6
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• pp.469-477
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• 2008

Purpose: The goal of this paper is to present the design and performance of a position encoding circuit for $16{\times}16$ array of position sensitive multi-anode photomultiplier tube for small animal PET scanners. This circuit which reduces the number of readout channels from 256 to 4 channels is based on a charge division method utilizing a resistor array. Materials and Methods: The position encoding circuit was simulated with PSpice before fabrication. The position encoding circuit reads out the signals from H9500 flat panel PMTs (Hamamatsu Photonics K.K., Japan) on which $1.5{\times}1.5{\times}7.0\;mm^3$ $L_{0.9}GSO$ ($Lu_{1.8}Gd_{0.2}SiO_{5}:Ce$) crystals were mounted. For coincidence detection, two different PET modules were used. One PET module consisted of a $29{\times}29\;L_{0.9}GSO$ crystal layer, and the other PET module two $28{\times}28$ and $29{\times}29\;L_{0.9}GSO$ crystal layers which have relative offsets by half a crystal pitch in x- and y-directions. The crystal mapping algorithm was also developed to identify crystals. Results: Each crystal was clearly visible in flood images. The crystal identification capability was enhanced further by changing the values of resistors near the edge of the resistor array. Energy resolutions of individual crystal were about 11.6%(SD 1.6). The flood images were segmented well with the proposed crystal mapping algorithm. Conclusion: The position encoding circuit resulted in a clear separation of crystals and sufficient energy resolutions with H9500 flat-panel PMT and $L_{0.9}GSO$ crystals. This circuit is good enough for use in small animal PET scanners.

• Journal of Food Hygiene and Safety
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• v.35 no.3
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• pp.225-233
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• 2020

By the standards and specifications for hygiene products, three test methods for formaldehyde are specified for each item type of hygiene product. After derivatization using acetylacetone and 2,4-dinitrophenylhydrazine (2,4-DNPH), formaldehyde is analyzed by spectrophotometer and high-performance liquid chromatography (HPLC). Validation of the three test methods was performed on tissue, diaper lining and waterproof layer, and panty liner products. The results of linearity (R²), limit of detection (LOD), limit of quantification (LOQ), recovery rate (%) and reproducibility (%), showed that all three methods are suitable for analyzing formaldehyde in hygiene products. After derivatization with 2,4-DNPH and cetylacetone, formaldehyde was analyzed at 0, 3, 6, 9, 24 and 48 hours by HPLC. Formaldehyde derivatized with 2,4-DNPH showed no statistically significant change in formaldehyde peak area over time (P>0.05). But, acetylacetone-derivatizated formaldehyde showed a negative correlation coefficient (r) over time (P<0.01). We investigated the residual amounts of formaldehyde in 205 hygiene products distributed in Busan. Among 74 disposable diaper products tested, 73 had low concentrations of formaldehyde (0.13-29.87 mg/kg). Moreover, formaldehyde was not detected in any of 78 tissue, 27 disposable paper towel, 12 disposable dishcloth, 7 paper cup, one brand of paper straw and 6 disposable napkin products.