• Journal of Food Hygiene and Safety
• /
• v.34 no.1
• /
• pp.22-29
• /
• 2019

Validamycin A is an aminoglycoside fungicide produced by Streptomyces hygroscopicus that inhibits trehalase. The purpose of this study was to develop a method for detecting validamycin A in agricultural samples to establish MRL values for use in Korea. The validamycin A residues in samples were extracted using methanol/water (50/50, v/v) and purified with a hydrophilic-lipophilic balance (HLB) cartridges. The analyte was quantified and confirmed by liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive ion mode using multiple reaction monitoring (MRM). Matrix-matched calibration curves were linear over the calibration ranges (0.005~0.5 ng) into a blank extract with $R^2$ > 0.99. The limits of detection and quantification were 0.005 and 0.01 mg/kg, respectively. For validation validamycin A, recovery studies were carried out three different concentration levels (LOQ, $LOQ{\times}10$, $LOQ{\times}50$, n = 5) with five replicates at each level. The average recovery range was from 72.5~118.3%, with relative standard deviation (RSD) less than 10.3%. All values were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the NIFDS (National Institute of Food and Drug Safety) guideline (2016). Therefore, the proposed analytical method is accurate, effective and sensitive for validamycin A determination in agricultural commodities.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.50-63
• /
• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.

• Journal of Intelligence and Information Systems
• /
• v.24 no.4
• /
• pp.219-240
• /
• 2018

Sentiment analysis, which is one of the text mining techniques, is a method for extracting subjective content embedded in text documents. Recently, the sentiment analysis methods have been widely used in many fields. As good examples, data-driven surveys are based on analyzing the subjectivity of text data posted by users and market researches are conducted by analyzing users' review posts to quantify users' reputation on a target product. The basic method of sentiment analysis is to use sentiment dictionary (or lexicon), a list of sentiment vocabularies with positive, neutral, or negative semantics. In general, the meaning of many sentiment words is likely to be different across domains. For example, a sentiment word, 'sad' indicates negative meaning in many fields but a movie. In order to perform accurate sentiment analysis, we need to build the sentiment dictionary for a given domain. However, such a method of building the sentiment lexicon is time-consuming and various sentiment vocabularies are not included without the use of general-purpose sentiment lexicon. In order to address this problem, several studies have been carried out to construct the sentiment lexicon suitable for a specific domain based on 'OPEN HANGUL' and 'SentiWordNet', which are general-purpose sentiment lexicons. However, OPEN HANGUL is no longer being serviced and SentiWordNet does not work well because of language difference in the process of converting Korean word into English word. There are restrictions on the use of such general-purpose sentiment lexicons as seed data for building the sentiment lexicon for a specific domain. In this article, we construct 'KNU Korean Sentiment Lexicon (KNU-KSL)', a new general-purpose Korean sentiment dictionary that is more advanced than existing general-purpose lexicons. The proposed dictionary, which is a list of domain-independent sentiment words such as 'thank you', 'worthy', and 'impressed', is built to quickly construct the sentiment dictionary for a target domain. Especially, it constructs sentiment vocabularies by analyzing the glosses contained in Standard Korean Language Dictionary (SKLD) by the following procedures: First, we propose a sentiment classification model based on Bidirectional Long Short-Term Memory (Bi-LSTM). Second, the proposed deep learning model automatically classifies each of glosses to either positive or negative meaning. Third, positive words and phrases are extracted from the glosses classified as positive meaning, while negative words and phrases are extracted from the glosses classified as negative meaning. Our experimental results show that the average accuracy of the proposed sentiment classification model is up to 89.45%. In addition, the sentiment dictionary is more extended using various external sources including SentiWordNet, SenticNet, Emotional Verbs, and Sentiment Lexicon 0603. Furthermore, we add sentiment information about frequently used coined words and emoticons that are used mainly on the Web. The KNU-KSL contains a total of 14,843 sentiment vocabularies, each of which is one of 1-grams, 2-grams, phrases, and sentence patterns. Unlike existing sentiment dictionaries, it is composed of words that are not affected by particular domains. The recent trend on sentiment analysis is to use deep learning technique without sentiment dictionaries. The importance of developing sentiment dictionaries is declined gradually. However, one of recent studies shows that the words in the sentiment dictionary can be used as features of deep learning models, resulting in the sentiment analysis performed with higher accuracy (Teng, Z., 2016). This result indicates that the sentiment dictionary is used not only for sentiment analysis but also as features of deep learning models for improving accuracy. The proposed dictionary can be used as a basic data for constructing the sentiment lexicon of a particular domain and as features of deep learning models. It is also useful to automatically and quickly build large training sets for deep learning models.

• Korean Journal of Heritage: History & Science
• /
• v.42 no.1
• /
• pp.122-142
• /
• 2009

This study explored all domestic and international theories for maintenance and health enhancement of an old and big tree, and carried out the anatomical survey of the operation part of the tree toward he current status of domestic surgery and the perception survey of an expert group, and drew out following conclusion through the process of suggesting its reform plan. First, as a result of analyzing the correlation of the 67 subject trees with their ages, growth status. surroundings, it revealed that they were closely related to positional characteristic, damage size, whereas were little related to materials by fillers. Second, the size of the affected part was the most frequent at the bough sheared part under $0.09m^2$, and the hollow size by position(part) was the biggest at 'root + stem' starting from the behind of the main root and stem As a result of analyzing the correlation, the same result was elicited at the group with low correlation. Third, the problem was serious in charging the fillers (especially urethane) in the big hollow or exposed root produced at the behind of the root and stem part, or surface-processing it. The benefit by charging the hollow part was analyzed as not so much. Fourth, the surface-processing of fillers currently used (artificial bark) is mainly 'epoxy+woven fabric+cork', but it is not flexible, so it has brought forth problems of frequent cracks and cracked surface at the joint part with the treetextured part. Fifth, the correlation with the external status of the operated part was very high with the closeness, surface condition, formation of adhesive tissue and internal survey result. Sixth, the most influential thing on flushing by the wrong management of an old and big tree was banking, and a wrong pruning was the source of the ground part damage. In pruning a small bough can easily recover itself from its damage as its formation of adhesive tissue when it is cut by a standard method. Seventh, the parameters affecting the times of related business handling of an old and big tree are 'the need of the conscious reform of the manager and related business'. Eighth, a reform plan in an institutional aspect can include the arrangement of the law and organization of the old and big tree management and preservation at an institutional aspect. This study for preparing a reform plan through the status survey of the designated old and big tree, has a limit inducing a reform plan based on the status survey through individual research, and a weak point suggesting grounds by any statistical data. This can be complemented by subsequent studies.

• Korean Journal of Heritage: History & Science
• /
• v.41 no.1
• /
• pp.5-19
• /
• 2008

Thirty six samples of Western asia glass vessel shards which were excavated from South Mound of Hwangnamdaechong were each measured for thickness, pore size and specific gravity and analyzed for ten major compositions and thirteen trace elements. The glass samples with colorless, greenish blue and dark purple blue were well classified by principal component analysis(PCA). All glass shards of Hwangnamdaechong belonged to Soda glass system ($Na_2O-CaO-SiO_2$) which have the range of 14~17% $Na_2O$ and 5~6% CaO. The corelation coefficients of (MgO, $K_2O$) and (MnO, CuO) showed above 0.90. The concentrations of thirteen trace elements apparently differentiated from colorless, greenish blue and dark blue glasses. We found that thirteen trace elements were very important indices for studying raw material of glass and the origin of glass making. Colorless glass : The specific gravity is $1.50{\pm}0.04$. Circle or oval circle pores are observed with regular direction in internal zone and the longest one is about 0.35 mm. The raw material of sodium must be the plant ash because sodium glasses contain HCLA(High CaO, Low $Al_2O_3$) and HMK(high MgO, high $K_2O$) and suggested to Sasanian glass. The total amount of coloring agent of colorless glass is below 1 % which is too small to attribute to the color. Greenish blue glass : The specific gravity is $1.58{\pm}0.04$. The fine pores which are 0.1~0.2mm are dispersed in internal zone. Sodium glasses are distributed to HCLA and HMK. Therefore the greenish blue glass also have used plant ash for raw material of sodium with the same as colorless glass. It was also suggested to the glass of Sasanian. The total amount of coloring agent of greenish blue glass is about 4% under the influence of working MnO, $Fe_2O_3$ and CuO. Dark purple blue glass : The specific gravity is $1.48{\pm}0.19$. There are rarely pores in internal zone. They are distributed to HCLA and LMK(Low MgO, Low $K_2O$) and suggested to Roman glass. The raw material of sodium is estimated to natron. The total amount of coloring agents of greenish blue is about 3% by $Fe_2O_3$ and CuO. These studies for western asia glass shards from South Mound of Hwangnamdaechong could be used in the future as the standard data which could be compared with those of other several graves in Korea and dispersed in foreign areas.

• Journal of Food Hygiene and Safety
• /
• v.34 no.3
• /
• pp.227-234
• /
• 2019

An analytical method was developed for the determination of oxytetracycline in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). After the samples were extracted with methanol, the extracts were adjusted to pH 4 by formic acid and sodium chloride was added to remove water. Dispersive solid phase extraction (d-SPE) cleanup was carried out using $MgSO_4$ (anhydrous magnesium sulfate), PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed with LC-MS/MS using ESI (electrospray ionization) in positive ion MRM (multiple reaction monitoring) mode. The matrix-matched calibration curves were constructed using six levels ($0.001{\sim}0.25{\mu}g/mL$) and coefficient of determination ($r^2$) was above 0.99. Recovery results at three concentrations (LOQ, $10{\times}LOQ$, and $50{\times}LOQ$, n=5) were from 80.0 to 108.2% with relative standard deviations (RSDs) less than of 11.4%. For inter-laboratory validation, the average recovery was in the range of 83.5~103.2% and the coefficient of variation (CV) was below 14.1%. All results satisfied the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and the Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for oxytetracycline determination in agricultural commodities. This study could be useful for safety management of oxytetracycline residues in agricultural products.

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

• The Journal of Engineering Geology
• /
• v.29 no.1
• /
• pp.51-68
• /
• 2019

This study performs to evaluate adaptability of seashore filtering type seawater-intake which adapts dua1 filter well alternative for direct seawater-intake. This study varies filter condition of seashore free surface aquifer which is composed of sand layer then installs real size dual filter well and single filter well to evaluate water permeability and proper pumping amount according to filter condition. According to result of step aquifer test, it is analysed that 110.3% synergy effect of water permeability coefficient is happened compare to single filter since dual filter well has better improvement. dual filter has higher water permeability coefficient compare to same pumping amount, this means dual filter has more improved water permeability than single filter. According to analysis result of continuous aquifer test, it is evaluated that dual filter well (SD1200) has higher water permeability than single filter well (SS800) by analysis of water permeability coefficient using monitoring well and gauging well, it is also analysed dual filter has 110.7% synergy effect of water permeability coefficient. As a evaluation result of pumping amount according to analysis of water level dropping rate, it is analysed that dual filter well increased 122.8% pumping amount compare to single filter well when water level dropping is 2.0 m. As a result of calculating proper pumping amount using water level dropping rate, it is analysed that dual filter well shows 136.0% higher pumping amount compare to single filter well. It is evaluated that proper pumping amount has 122.8~160% improvement compare to single filter, pumping amount improvement rate is 139.6% compare to averaged single filter. In other words, about 40% water intake efficiency can be improved by just installation of dual filter compare to normal well. Proper pumping amount of dual filter well using inflection point is 2843.3 L/min and it is evaluated that daily seawater intake amount is about $4,100m^3/day$ (${\fallingdotseq}4094.3m^3/day$) in one hole of dual filter well. Since it is possible to intake plenty of water in one hole, higher adaptability is anticipated. In case of intaking seawater using dual filter well, no worries regarding damages on facilities caused by natural disaster such as severe weather or typhoon, improvement of pollution is anticipated due to seashore sand layer acts like filter. Therefore, It can be alternative of environmental issue for existing seawater intake technique, can save maintenance expenses related to installation fee or damages and has excellent adaptability in economic aspect. The result of this study will be utilized as a basic data of site demonstration test for adaptation of riverside filtered water of upcoming dual filter well and this study is also anticipated to present standard of well design and construction related to riverside filter and seashore filter technique.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.109-125
• /
• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• Journal of the Korean Geotechnical Society
• /
• v.35 no.5
• /
• pp.5-19
• /
• 2019

Considering the natural phenomenon in which steep slopes ($65^{\circ}{\sim}85^{\circ}$) consisting of rock mass remain stable for decades, slopes steeper than 1:0.5 (the standard of slope angle for blast rock) may be applied in geotechnical conditions which are similar to those above at the design and initial construction stages. In the process of analysing the stability of a good to fair continuum rock slope that can be designed as a steep slope, a general method of estimating rock mass strength properties from design practice perspective was required. Practical and genealized engineering methods of determining the properties of a rock mass are important for a good continuum rock slope that can be designed as a steep slope. The Genealized Hoek-Brown (H-B) failure criterion and GSI (Geological Strength Index), which were revised and supplemented by Hoek et al. (2002), were assessed as rock mass characterization systems fully taking into account the effects of discontinuities, and were widely utilized as a method for calculating equivalent Mohr-Coulomb shear strength (balancing the areas) according to stress changes. The concept of calculating equivalent M-C shear strength according to the change of confining stress range was proposed, and on a slope, the equivalent shear strength changes sensitively with changes in the maximum confining stress (${{\sigma}^{\prime}}_{3max}$ or normal stress), making it difficult to use it in practical design. In this study, the method of estimating the strength properties (an iso-angle division method) that can be applied universally within the maximum confining stress range for a good to fair continuum rock mass slope is proposed by applying the H-B failure criterion. In order to assess the validity and applicability of the proposed method of estimating the shear strength (A), the rock slope, which is a study object, was selected as the type of rock (igneous, metamorphic, sedimentary) on the steep slope near the existing working design site. It is compared and analyzed with the equivalent M-C shear strength (balancing the areas) proposed by Hoek. The equivalent M-C shear strength of the balancing the areas method and iso-angle division method was estimated using the RocLab program (geotechnical properties calculation software based on the H-B failure criterion (2002)) by using the basic data of the laboratory rock triaxial compression test at the existing working design site and the face mapping of discontinuities on the rock slope of study area. The calculated equivalent M-C shear strength of the balancing the areas method was interlinked to show very large or small cohesion and internal friction angles (generally, greater than $45^{\circ}$). The equivalent M-C shear strength of the iso-angle division is in-between the equivalent M-C shear properties of the balancing the areas, and the internal friction angles show a range of $30^{\circ}$ to $42^{\circ}$. We compared and analyzed the shear strength (A) of the iso-angle division method at the study area with the shear strength (B) of the existing working design site with similar or the same grade RMR each other. The application of the proposed iso-angle division method was indirectly evaluated through the results of the stability analysis (limit equilibrium analysis and finite element analysis) applied with these the strength properties. The difference between A and B of the shear strength is about 10%. LEM results (in wet condition) showed that Fs (A) = 14.08~58.22 (average 32.9) and Fs (B) = 18.39~60.04 (average 32.2), which were similar in accordance with the same rock types. As a result of FEM, displacement (A) = 0.13~0.65 mm (average 0.27 mm) and displacement (B) = 0.14~1.07 mm (average 0.37 mm). Using the GSI and Hoek-Brown failure criterion, the significant result could be identified in the application evaluation. Therefore, the strength properties of rock mass estimated by the iso-angle division method could be applied with practical shear strength.