• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.34-48
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• 2024

As global supply chain risks proliferate unpredictably, the high interdependence of port and logistics industry intensifies the risk burden. This study conducted fundamental research to explore diverse safety issues in domestic ports. Utilizing news article data about Busan Port, we employed LDA topic modeling and time-series linear regression to understand key safety trends. Over the past 30 years, Busan Port faced nine major safety issues-maritime safety, import cargo inspection, labor strikes, and natural disasters emerged cyclically. Major port safety issues in Busan Port are primarily characterized by an unpredictable nature, falling under socio-environmental and natural phenomena types, indicating a significant impact of global uncertainty. Therefore, systematic policies need to be formulated based on identified port safety issues to enhance port safety in Busan Port. Additionally, there is a need to strengthen the resilience of port safety for unpredictable risk situations. In conclusion, advanced research activities are necessary to promote port safety enhancement in response to dynamically changing social conditions.

• Korean Chemical Engineering Research
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• v.52 no.3
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• pp.321-327
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• 2014

Polymer dispersed liquid crystal lenses of the cell gap of $11{\mu}m$ and $30{\mu}m$ were made from a uniformly dispersed mixture of 40 wt% NOA65 prepolymer - 60 wt% E7 liquid crystal with the variations of the additional photoinitiator. The photoinitiator, benzophenone of 5.0 wt% was originally in the commercial prepolymer NOA65. In this works, the influence of the benzophenone amount intentionally added in the commercial NOA65 on the electrical properties of polymer dispersed liquid crystal lens for smart electronic glasses. The additional quantities of the photoinitiator were 1, 2, 4, 8 and 16 wt% of the weight of NOA65 - E7 mixture. All the electro-optical properties of the sample with added benzophenone such as the driving voltage, the slope of the linear region, the response time and contrast ratio were more improved than that of commercial NOA65 only. These improvements were due to the increase of the average size of E7 liquid crystal droplets in the samples with the increase of the added benzophenon amount. The liquid crystal droplet size was increased from $5.3{\mu}m$ to $12.2{\mu}m$ when the photoinitiator was added from 0 wt% to 8 wt%. At the same concentration range of the photoinitiator, the driving voltage was ranged from 11.1 V to 17.3 V. The slopes of the linear region were in the range of 10.35~13.96 %T/V, which were more enhanced than that of NOA65 without the additional benzophenone. In particular, though the deteriorations by cell gap of $11{\mu}m$ were so effective to offset the influence of the added benzophenone for both rising and falling response time, it is confirmed that there were still somewhat improvement by the additional benzophenone. Response time and contrast ratios of all the samples with excess benzophenone were slightly enhanced.

• Journal of Preventive Medicine and Public Health
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• v.9 no.1
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• pp.55-64
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• 1976

This paper presents the results of a survey for the causes of sensori-neural hearing impairment in Korea, The subjects were 1,676 children of total 2,928 enrolled in 16 Deaf Schools; two schools in each area of Seoul, Busan, Kyoungbook, Kyoungnam, Kyounggi and Chunbug, and each one in Chungnam, Chungbug, Chunnam and Jaeju. The data were collected by questionaire with 28 items distributed to their parents. The filling in the check lists were performed by their class teachers, interviewer, for 18 months from September, 1975 to february, 1976. The questionable or missed problems were reaffirmed. The results obtained were as follows. Most of the reasons, 78.5% were acquired characters that could be developed during pregnant period, the time of delivery and the time of after birth. The pure hereditary reasons except the cases complexed with one or two were only 11.3%. Those who could not be defined with any reasons were 10.2%. Among the acquired causes, 5.8% of total subjects were developed for pregnancy: 3.3%, during delivery; and 69.7%, after birth. In the pregnant period, the drug intoxications were 2.4% of total subjects, several diseases such as influenja, bleeding, surgical operation, venereal diseases and rubella etc. were about one percent, and the accompanied with some symptoms of pregnancy intoxication and traumatic events were 2.4%, During time, the cases with delayed rhythmical pain were 16 persons, the immaturities were 11, the asphyxial cases were nine, the errors of forceps delivery were seven, the cases of low body weight inspite of full term were four, the cases with cesarian section were three, the head injuries were two, and the accompanied with three kinds of above reasons were three. During after birth, the cases with acute communicable diseases were 35.4% of total subjects, the fever unknown origin were 16.1%, the chronic otitis media were 3.7%, the meningitis were 3.5%, the gastric and nutritional diseases were 3.5%, the drug intoxications were 4.8%, the blood diseases were 0.3% and the other causes were 2.2%. Here by acute communicable diseases, some importants were measle, 10.1% of total subjects; meningitis, 7.3%; convulsion with some reasons, 4.9%; poliomyelitis. 3.2%; encephalitis, 2.4%; and mumps, rubella, pertusis, scarlet fever, and small pox were somewhat played a role in. Among 59 cases with train diseases, 53 were concussion by the accidents, such as traffic and falling or sliping down etc., the cerebral paralysis and hydrocephalus were two, respectively. And the blood diseases were severe newjaundice in all five cases. If we were summarized with the above mentioned, most of the hearing impairments were introduced by the combined reasons with familial or hereditary factors and the acquired, than by a simple disease. Among the congenital or hereditary hearing impairments classified to now a day, we suppose that the many cases with the acquired causes during pregnancy, delivery and after birth were complexed. Subsequently, the maternal and child health should be more and more developed in our country, also.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Korean Society of Forest Science
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• v.40 no.1
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• pp.25-34
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• 1978

Trial and demonslative reforestations were planted by Korea German Management Project at Ulju district in 1976. The follow results that were investigated at spring time in 1977 showed the different situation of winter damage according to site condition and species. 1. Picea abies was completely dried out in this district and its reason was to be thought as a winter damage by cold-dry wind. 2. Cryptomeria japonica was seriously damaged in comparing with Chamaecyparis obtusa and very seriously damaged on the wind-exposured site. So these species are also unsuitable species like Picea abies in this district. 3. The resistance ranking to winter dry wind damage were Picea, Cryptomeria, Chamaecyparis, ${\times}$ Pinus rigitaeda. Pinus rigida, Larix leptolepis and Alnus hirsuta. The falling leave species like larch in this district during winter were thought in necessary to select as the planting species for almost very little winter damage. 4. ${\times}$ Pinus rigitaeda to be showed as a suitable species in this district were also seriously damaged on exposured site and, Pinus rigida and Larix were also attacked with small damage. The potassium-phosphorus fertilizer dressing plots had a trend to reduce this winter damage until some level. 5. The winter climate can be devided into 10 zone in order to evaluate the right or wrong of suitable on the exotic species. The Yongnam region in eastern side of Sobaik mountain are far drier than the Honam region in western side of Sobaik mountain during winter time. Picea abies, Cryptomeria and Chamaecyparis originated in the high humidity winter climate are to be thought to be more suitable in the Honam region than the Yongnam region. Specially the suitable site of Picea abies should be only found in the region with high humidity and much precipitation except the Yongnam region.

• The Korean Society of Law and Medicine
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• v.21 no.1
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• pp.107-152
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• 2020

During the main ruling in 2019, a number of rulings that were of interest or meaningful were handed down, such as just because the complication of medical practice has occurred, there is no presumption of negligence, a case involving a fall accident in which a lot of culpability has recently been made. the death of a well-known singer that caused a sensation, a case about damages caused by MERS in 2015, which is more meaningful in connection with damages caused by COVID-19, an infectious disease that has recently hit the world, including Korea. In preaching the principles of the law, just because there has been a complication caused by medical practice, there is no presumption of negligence, 'The scope of the complication without presumption of negligence' was determined differently by the court, the court was not able to specify the criteria. Specific circumstances were presented to limit the responsibility of the medical institution while acknowledging the malpractice of the medical institution in relation to the fall accident. In relation to the scope of damages, judgment was made on issues related to the calculation of lost profits of medical malpractice; criteria for determining celebrities' daily income, criteria for determining daily income in case of receiving survivor's pension due to medical accident, an incident in which the daily income is denied if the labor capacity is already lost at the time of a medical accident. But, it seems that judgments should be made based on clearer and more reasonable standards. Related to Medical Advertise, specific logic of judgment was presented as to whether it was interpreted as being in accordance with the specific prohibition listed in Article 27 paragraph 3 of the Medical Law, which is the criterion for violation of the Medical Law, or if it constitutes a significant harm to the order of the medical market. In response to the prohibition of operating the multiple medical institutions, the Constitutional Court decided that it was constitutional because it did not violate the regulations on excessive funding, and rationally limited the scope of the prohibited 'redundant operation'. The Supreme Court ruled for the first time that even a medical institution established and operated in violation of the Medical Service Act did not make it impossible to receive all medical care benefits implemented by a medical institution under the National Health Insurance Act. Significant rulings were finalized that recognized the existence of specific protection obligations for the people of the country in the management of infectious diseases.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.1
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• pp.1-10
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• 1982

Degree of grain shattering which is of varietal character is an important determinant for the magnitude of field loss of grains during harvest and threshing. Seven Indica \times Japonica progeny varieties and four Japonica varieties were subjected to measurements of tensile strength of grains, degree of grain shattering when panicles were dropped at 1.5m above concrete floor, and moisture content of grains (wet basis) during a period 35 to 63 days after heading. In addition, two varieties were tested for the relation of tensile strength of grains to the magnitude of field loss of grains in actual binder harvest. The 11 varieties differed conspicuously in tensile strength of grains and the degree of grain shattering: the weakest average tensile strength of grains of a variety was about 90g and the strongest about 250g with varying standard deviation of 30 to 60g. Three Indica \times Japonica varieties and one Japonica variety shattered I to 30% of the grains under the falling test. The threshold tensile strength of grains allowing grain shattering was estimated to be 180g on average for a sampling unit of 10 panicles, but only the grains having tensile strength weaker than 98g within the samples shattered. A decrease in average tensile strength by 10g below the threshold value corresponded to an increase of 3 to 5% in grain shattering. Most varieties did not change appreciably the tensile strength of grains and degree of grain shattering with delay in time of harvest and showed a negative correlation between the tensile strength and the moisture content of grains. The average tensile strength of grains was negatively correlated linearly with field loss in binder harvest. The average tensile strength for zero field loss in binder harvest was estimated to be 174g and a decrease in the average tensile strength by 10g corresponded to an increase of 40kg per hectare in field loss of grains. Instead of the average tensile strength of grains, the percentage of grains having tensile strength weaker than 100g is recommended as a criterion for the estimation of field loss of grains during harvesting operations as well as a basis of variety classification for grain shattering, since the standard deviation of tensile strength of grains varies much with variety and time of harvest, and individual grains having tensile strength stronger than 98 did not shatter practically.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.208-220
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• 2019

The seasonality of leaf fall has important implications for understanding the response of trees' phenology to climate change. In this study, we quantified the leaf fall pattern with a model to estimate the timing and speed of leaf litter according to species and considered the nutrient use strategy of canopy species. In the autumns of 2015 and 2016, leaf litter was collected periodically using 36 litter-traps from the deciduous forests in Gwangneung and sorted by species. The seasonal leaf fall pattern was estimated using the non-linear regression model of Dixon. Additionally, the resorption rate was calculated by analyzing the nitrogen concentration of the leaf litter at each collection time. The leaf litter generally began in early October and ended in mid-November depending on the species. At the peak time (T50) of leaf fall, on average, Carpinus laxiflora was first, and Quercus serrata was last. The rate of leaf fall was fastest (18.6 days) for Sorbus alnifolia in 2016 and slowest (40.8 days) for C. cordata in 2015. The nitrogen resorption rates at T50 were 0.45% for Q. serrata and 0.48% for C. laxiflora, and the resorption rate in 2015 with less precipitation was higher than in 2016. Since falling of leaf litter is affected by environmental factors such as temperature, precipitation, photoperiod, and $CO_2$ during the period attached foliage, the leaf fall pattern and nitrogen resorption differed year by year depending on the species. If we quantify the fall phenomena of deciduous trees and analyze them according to various conditions, we can predict whether the changes in leaf fall timing and speed due to climate change will prolong or shorten the growth period of trees. In addition, it may be possible to consider how this affects their nutrient use strategy.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.