• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.119-134
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• 2018

Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.672-678
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• 2015

The types of hazardous and noxious substances (HNS) being transported by sea in Korea are at about 6,000, HNS transport volume accounts for 19% of total tonnage shipped in Korea, and the increase rate of seaborne HNS trade in Korea is 2.5 times higher than the average increase rate of the world seaborne HNS trade. Reflecting this trend, HNS spill incidents have been frequently reported in Korean waters, and there are increasing social demands to develop HNS management technology for the preparedness, response, post-treatment and restoration in relation to HNS spill incidents at sea. In this study, a risk-based HNS prioritization system was developed and an HNS risk database was built with evaluation indices such as sea transport volume, physicochemical properties, toxicities, persistency, and bioaccumulation. Risk scores for human health and marine environments were calculated by multiplying scores for toxicity and exposure. The top-20 substances in the list of HNS were tabulated, and Aniline was ranked first place, but it needs to be managed not by individuals but by HNS groups with similar score levels. Limitations were identified in obtaining data of chronic toxicity and marine ecotoxicity due to lack of testing data. It is necessary to study on marine ecotoxicological test in the near future. Moreover, the priority list of HNS is expected to be utilized in the development of HNS management technology and the relevant technologies, after the expert's review process and making up for the lack of test data in the current research results.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.795-805
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• 2021

In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m³/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.17-31
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• 2006

In this paper, passport recognition and face verification methods which can automatically recognize passport codes and discriminate forgery passports to improve efficiency and systematic control of immigration management are proposed. Adjusting the slant is very important for recognition of characters and face verification since slanted passport images can bring various unwanted effects to the recognition of individual codes and faces. Therefore, after smearing the passport image, the longest extracted string of characters is selected. The angle adjustment can be conducted by using the slant of the straight and horizontal line that connects the center of thickness between left and right parts of the string. Extracting passport codes is done by Sobel operator, horizontal smearing, and 8-neighborhood contour tracking algorithm. The string of codes can be transformed into binary format by applying repeating binary method to the area of the extracted passport code strings. The string codes are restored by applying CDM mask to the binary string area and individual codes are extracted by 8-neighborhood contour tracking algerian. The proposed RBF network is applied to the middle layer of RBF network by using the fuzzy logic connection operator and proposing the enhanced fuzzy ART algorithm that dynamically controls the vigilance parameter. The face is authenticated by measuring the similarity between the feature vector of the facial image from the passport and feature vector of the facial image from the database that is constructed with PCA algorithm. After several tests using a forged passport and the passport with slanted images, the proposed method was proven to be effective in recognizing passport codes and verifying facial images.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.2
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• pp.228-232
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• 2016

As the quantity of HNS sea trasport and the number of HNS accidents at sea are increasing recently, the importance of HNS management is emphasized so that we try to develop marine accident case standard code for making HNS accidents at sea databased systemically in this study. First and foremost, we draw the related requisites of essential accident reports along with internal and external decrees and established statistics of classified items for conducting study, and we referred to analogous standard codes obtained from developed countries in order to research code design. Code design is set like 'Accident occurrence ${\rightarrow}$ The initial accident information ${\rightarrow}$ Accident response ${\rightarrow}$ Accident investigation' in accordance with the general flow of marine HNS accidents of in which the accident information is input and queried. We classified initial accident information into the items of five categories and constructed "Preliminary Information Code(P.I.C.)". In addition we constructed accident response in two categories and accident investigation in three categories that get possible after the accident occurrence as called "Full Information(F.I.C.)", including the P.I.C. It is represented in 3 kinds of steps on each topic by departmentalizing the classified majority as classified middle class and classified minority. As a result of coding marine HNS accident and of the code to a typical example of marine HNS accident, HNS accident was ascertained to be represented sufficiently well. We expect that it is feasible to predict possible trouble or accident henceforward by applying code, and also consider that it is valuable to the preparedness, response and restoration in relation to HNS accidents at sea by managing systemically the data of marine HNS accidents which will occur in the future.

• The Journal of the Petrological Society of Korea
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• v.28 no.4
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• pp.319-345
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• 2019

Recently planification and effort for management, assessment and discovery of geological heritagesare being increasingly demanded with institutional strategies such as geopark, as their preservation is asked socially. In this study, we discovered geological heritages in the Jeolla Province and then performed assessment of the value and grading of them and finally suggested a promising and suitable site for the National Geopark. A total of 325 geological heritages are listed on literature review and then detailed description in field and assessment of the value for selected 158 geoheritages are completed. The assessment items are categorized into intrinsic value, subsidiary value, and preservation/management part. The intrinsic value is subdivided into scientific/educational value, composed of representativeness, rarity, geodiversity, typicality, reproducibility, and particularity, and geomorphological/landscape value composed of scale, naturality (integrity), scenery (aesthetic value). Also, subsidiary value consist of 7 subsections of soil function, ecological function, tourism value, geological resource, historical value, folk tale or legend and symbolic value, and accessibility, convenient facility (infrastructure), management condition (legal protection) is evaluated in preservation/management part. The heritages in the Jeolla Province subdivided into three types: 73 geological heritages, 42 geomorphological heritages, and 42 composite heritages. Based on points acquired in intrinsic value, all geological heritages are graded Class-I to -V. As a result, numbers of geoheritage belong to Class-I (protection at world level), -II (protection at national level), -III (nationdesignated management), -IV (involved management list), -V (candidate management list) are 12, 39, 52, 34, 21, respectively. Finally, we construct database based on Arc-GIS with all informations for each geological heritage and suggest three promising and suitable sites, 'Jirisan-Seomjingang Area' and 'south coast area of Jeolla Province', for the National Geopark.

• Korean Journal of Microbiology
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• v.42 no.1
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• pp.40-46
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• 2006

Galactose joined to glucose by a $\beta(1\rightarrow4)$ glycosidic bond makes lactose and this disaccharide is rich in milk. It is known that lacotse is hydrolyzed to each monomeric sugar by either lactase in human or $\beta-galactosidase$ in bacteria. Ingestion of milk by lactase-deficient persons causes a temporary diarrhea and subsequent chronic diarrhea results in colitis with chronic inflammation. We isolated a $\beta-galactosidase$ producing psycrotolerant strain AS-20 from near cattle shed and investigated the growth at various temperature conditions. Whereas Escherichia coli strains did not grow at $10^{\circ}C$, the AS-20 strain could grow well at this low temperature and showed optimal growth at $30^{\circ}C$. The isolated strain was identified as 97% Hafnia alvei by biochemical properties. This strain could ferment glucose, lacotse, maltose, mannitol, xylose, ONPG, rhamanose and L-arabinose, and decarboxylate lysin and ornithine. To confirm the identity of isolated strain we amplified 16S rDNA by PCR and searched similarity of the 1426 bp DNA sequcence with Genbank database. The strain AS-20 showed 99% similarity with Hafnia alvei. The activity of $\beta-galactosidase$ was 1.5 times higher when the cell was grown at 10 or $20^{\circ}C$ than at $30^{\circ}C$. The highest enzyme activity of AS-20 was also much higher than that of E. coli, which was grown at $30^{\circ}C$.

• Journal of Bio-Environment Control
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• v.24 no.4
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• pp.333-340
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• 2015

Because soils in reclaimed lands nearby coastal areas have much higher salinity and moisture content than soils in inland area, parts of greenhouses embedded in such soils are exposed to highly corrosive environments. Owing to the accelerated corrosion of galvanized steel pipes for substrucrture and structure of greenhouses in saline environments, repair and reinforcement technologies and efficient maintenance and management for the construction materials in such facilities are required. In this study, we measured the corrosion rates of the parts used for greenhouse construction that are exposed to the saline environment to obtain a basic database for the establishment of maintenance and reinforcement standards for greenhouse construction in reclaimed lands with soils with high salinity. All the test pipes were exposed to soil and water environments with 0, 0.1, 0.3, and 0.5% salinity during the observation period of 480 days. At the end of the observation period, salinity-dependent differences of corrosion rate between black-surface corrosion and relatively regular corrosion were clearly manifested in a visual assessment. For the soils in rice paddies, the corrosion growth rate increased with salinity (0.008, 0.027, 0.036, and $0.043mm{\cdot}yr^{-1}$ at 0, 0.1, 0.3, and 0.5% salinity, respectively). The results for the soils in agricultural fields are 0.0002, 0.039, 0.040, and $0.039mm{\cdot}yr^{-1}$ at 0, 0.1, 0.3, and 0.5% salinity, respectively. The higher corrosion rate of rice-paddy soil was associated with the relatively high proportion of fine particles in it, reflecting the general tendency of soils with evenly distributed fine particles. Hence, it was concluded that thorough measures should be taken to counteract pipe corrosion, given that besides high salinity, the soils in reclaimed lands are expected to have a higher proportion of fine particles than those in inland rice paddies and agricultural fields.