• Proceedings of the KOR-BRONCHOESO Conference
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• 1982.05a
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• pp.11.2-12
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• 1982

The major advancement in phonosurgery due to recent development of laryngomicrosurgery enabled more accurate diagnosis and treatment of patient with voice disorders. Among large proportion of voice disordered patients, prominent linear furrow running parallel along the free edge of vocal cord extending from the vocal process to anterior commissure can be seen as well as incomplete closure during phonation. These cases were illustrated and coined as sulcus vocalis by Salvi in 1901, since then other similar paper was reported in Europe and Japan, but has not been reported in Korea. The exact etiology and therapeutic methods of sulcus vocalis has not been elaborated. At Department of Otolaryngology of Yonsei University College of Medicine a series of voice analysis were performed among those 35 patients with sulcus vocalis visited to Vocal Dynamics Laboratory from May, 1981 to March, 1982. Following is the result of clinical statistical investgation and therapeutic modality. 1) The incidance of sulcus vocalis among 290 patients with voice disorder visited to Vocal Dynamics Laboratory was approximately 12%(35 cases). 2) Onset of this voice disorder was most frequent among patient under 10 year-old groups; 19 cases (54%) followed by second decade, third decade groups in decreasing frequency respectably. 3) The etiology of sulcus vocalis was mostly unknown. The sequelae after measle (4 cases) and severe upper respiratory infection (3 cases) and congenital deformity (2 cases) were the possible causes of sulcus vocalis. 4) These patients were involved bilaterally in 25 cases (71%), left side only in 8 cases (23%) and right side only in 2 cases (6%). 5) Almost all patients complained hoarseness and 7 patients were suffering from chronic laryngitis. 6) In aerodynamic analysis, Maximal Phonation Time was decreased in 20 cases (57%), Phonation Quotient was increased in 22 cases (63%) and Mean Air Flow Rate was increased in 23 cases (66%). 7) Among them, 33 cases were analyzed with stroboscopy. The findings were as follows; incomplete glottic closure during phonation in 31 cases (93%), regular vocal cord movement in whole cases, asymmetric cord movement in 4 cases (12%), decreased amplitude in 5 cases (21%) and small mucosal wave in 24 cases (73%). 8) Intracordal Teflon injection in 5 cases and Sulcusectomy in 1 cases were performed as therapeutic management, however, the therapeutic results were not effective except one case with Teflon injection.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.375-383
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• 2001

We extracted sea surface heights(SSH) from the TopexJPoseidon(T/P) radar altimeter data to compare with fhe SSH estimated from in-situ lide gauges(T/G) at Ulleungdo, Pohang, and SockcholMucko sites. Selection criteria such as wet/dry troposphere, ionosphere, and ocean tide were used to estimate accurate SSH. For time series analysis, the one-hour interval tide gauge SSHs were resampled al lO-day interval of the satellite SSHs. The ocean tide model applied in the altimeter data processing showed periodic aliasings of 175.5 day, 87.8 day, 62J day, 58.5 day, 49.5 day and 46.0 day, and, hence, the ZOO-day filtering was applied to reduce these spectral noises. Wavenumber correlation analysis was also applied to extract common components between the two SSHs, resulting in enhancing the correlation coefficient(CC) dramatically. The original CCs between the satenite and tide gauge SSHs are 0.46. 0.26, and 0.]5, respectively. Ulleungdo shows the largest cc bec;luase the site is far from the coast resulting in the minimun error in the satellite observations. The CCs were then increased to 0.59, 030, and 0.30, respectively, after 200.day filtering, and to 0.69, 0.63. and 0.59 after removing inversely correlative components using wavenumber correlation analysis. The CCs were greatly increased by 87, 227, and 460% when the wavenumber correlation analysis was followed by 2oo-day filtering, resulting in the final CCs of 0.86, 0.85, 0.84, respectively. It was found that the best SSHs were estimated when the two methods were applied to the original data. The low-pass filtered TIP SSHs were found to be well correlated with the TIG SSHs from tide gauges, and the best correlation results were found when we applied both low-pass filtering and spectral correlation analysis to the original SSHs.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.253-263
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• 2013

Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.

• Journal of Korea Foundry Society
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• v.42 no.6
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• pp.337-346
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• 2022

In order to optimize the solution treatment conditions of Al-7Si-(0.3~0.5)Mg-(0~0.5)Cu alloys, a series of heat treatment experiments were conducted under various solution treatment times up to 7 hours at 545℃, followed by a microstructural analysis using optical microscopy, FE-SEM, and Brinell hardness measurements. Rapid coarsening of eutectic Si particles was observed in the alloys during the first 3 hours of solution treatment but the size of those Si particles did not change at longer solution treatment conditions. Meanwhile, the degree of spheroidisation of eutectic Si particles increased until the solution treatment time was increased up to 7 hours. Q-Al5Cu2Mg8Si6 andθ-Al2Cu were observed in as-cast Cu-containing Al alloys but the intermetallic compounds were dissolved completely after 3 hours of solution treatment at 545℃. Depending on the initial Mg composition of the Al alloys, π-Al8FeMg3Si either disappeared in the alloy with 0.3wt% of Mg content after 5 hours of solution treatment or remained in the alloy with 0.5wt% of Mg content after 7 hours of solution treatment time. Mg and Cu content in the primary-α phase of the Al alloys increased until the solution treatment time reached 5 hours, which was in accordance with the dissolution behavior of Mg or Cu-containing intermetallic compounds with respect to the solution treatment time. From the results of microstructural changes in the Al-7Si-Mg-Cu alloys during solution treatment, it was concluded that at least 5 hours of solution treatment at 545℃ is required to maximize the age hardening effect of the present Al alloys. The same optimal solution treatment conditions could also be derived from Brinell hardness values of the present Al-7Si-Mg-Cu alloys measured at different solution treatment conditions.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.3
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• pp.132-145
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• 2016

In case of the seabed around and under gravity structures such as submerged breakwater is exposed to a large wave action long period, the excess pore pressure will be generated significantly due to pore volume change associated with rearrangement soil grains. This effect will lead a seabed liquefaction around and under structures as a result from decrease in the effective stress. Under the seabed liquefaction occurred and developed, the possibility of structure failure will be increased eventually. In this study, to evaluate the liquefaction potential on the seabed quantitatively, numerical analysis was conducted using the expanded 2-dimensional numerical wave tank model and the finite element elasto-plastic model. Under the condition of the regular wave field, the time and spatial series of the deformation of submerged breakwater, the pore water pressure (oscillatory and residual components) and pore water pressure ratio in the seabed were estimated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.4
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• pp.315-326
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• 2015

Temporal and spatial variations of surface water temperature in Jinju Bay for the period of 2010~2011 were studied using the data from temperature monitoring buoys deployed at 17 stations in the south coast of Korea. Water temperature shows the maximum late in January and the minimum early in August. Seasonal variation of water temperatures at the north part of the bay is smaller than the middle and the south. In summer, the lowest and the highest of maximum water temperature are distributed around Jijok Channel which is located at the south of the bay. The fluctuations of water temperatures at Noryang and Daebang Channel are smaller than others because of vertical mixing caused by passage of strong tidal currents. Wind and strong currents affect on the stratification of the surface water layer near Daebang Channel. High temperatures come in frequently around the north area when eastward constant flows appear at neap tide as blowing westerly in the springtime at Noryang Channel. Spectral analyses of temperature records show significant peaks at 7~20 day periods at Noryang Channel, 7~20 day and semidiurnal at the west coast of Changsun Island and Jijok Channel and 7~20 day and diurnal at the middle of the bay. Temperature fluctuation at Noryang Channel shows high coherence and has leading phase with those at other stations in the bay. However, the phase of temperature fluctuation at Noryang Channel falls behind that at Daebang Channel. Daebang Channel has an influence on the temperature fluctuation only at the west and middle part of the bay. Cross-correlation analyses for the temperature fluctuation show that Jinju Bay could be classified into six areas; Noryang Channel, the area of convergence and divergence at the north, Daebang Channel, the west coast of Changsun Island, the mixing area at the middle of the bay and the south inside of the bay, respectively.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.251-263
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• 2015

This study suggested a novel approach of estimating the optimal probability density function (OPDF) of the annual maximum rainfall time series (AMRT) combining the L-moment ratio diagram and the geographical information system. This study also reported several interesting geographical characteristics of the AMRT in Korea. To achieve this purpose, this study determined the OPDF of the AMRT with the duration of 1-, 3-, 6-, 12-, and 24-hours using the method of L-moment ratio diagram for each of the 67 rain gages in Korea. Then, a map with the Thiessen polygons of the 67 rain gages colored differently according the different type of the OPDF, was produced to analyze the spatial trend of the OPDF. In addition, this study produced the color maps which show the fitness of a given probability density function to represent the AMRT. The study found that (1) both L-skewness and L-kurtosis of the AMRT have clear geographical trends, which means that the extreme rainfall events are highly influenced by geography; (2) the impact of the altitude on these two rainfall statistics is greater for the mountaneous region than for the non-mountaneous region. In the mountaneous region, the areas with higher altitude are more likely to experience the less-frequent and strong rainfall events than the areas with lower altitude; (3) The most representative OPDFs of Korea except for the Southern edge are Generalized Extreme Value distribution and the Generalized Logistic distribution. The AMRT of southern edge of Korea was best represented by the Generalized Pareto distribution.