• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.145-158
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• 2016

This paper introduces a risk graph which is one method for determining the SIL as a measure of the effectiveness of signaling system. The purpose of this research is to make up for the weakness of the qualitative determination, which has input value ambiguity and a boundary problem in the SIL range. The fuzzy input valuable consists of consequence, exposure, avoidance and demand rate. The fuzzy inference produces forty eight fuzzy rule by adapting the calibrated risk graph in the IEC 61511. The Max-min composition is utilized for the fuzzy inference. The result of the fuzzy inference is the fuzzy value. Therefore, using the de-fuzzification method, the result should be converted to a crisp value that can be utilized for real projects. Ultimately, the safety requirement for hazard is identified by proposing a SIL result with a tolerable hazard rate. For the validation the results of the proposed method, the fuzzy risk graph model is compared with the safety analysis of the signaling system in CENELEC SC 9XA WG A10 report.

• Journal of Korean Philosophical Society
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• v.145
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• pp.325-350
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• 2018

The overemphasis of the priority of reason over will runs the risk of resulting in intellectual determinism. On the contrary, it is also unfair to underestimate the role of reason in Saint Thomas Aquinas' theory of the free will to avoid intellectual determinism. For, according to Thomas, "the will inclines to the good, insofar as it is an appetite, and it follows the judgment of the reason in the pursuit of the good, insofar as it is a 'rational' appetite." It is the objective of this article to show that, for Thomas, the idea of the free will is not contradictory to that of the will's following the judgment of reason. For this purpose, it is decisive to adequately evaluate the role of reason in Thomas's theory of the free will. This article therefore proves that in principle Thomas argues the priority of the will over reason as well as the freedom of the will, and that he nevertheless recognizes the role of reason which precedes the choice of the will by making the second-level judgment even when the will chooses not to follow the first-level judgement of reason. It is entirely up to the will to follow the judgement and order of reason or not. It explains the freedom of the will. But 'not to follow reason' is contradictory to the essential determination of the will as the 'rational' appetite. For from the will's not following reason, wrong-doing follows; the human act which does not conform to reason. This article therefore argues that for Thomas, the 'true' liberty of the will corresponding to its determination as the rational appetite consists in its following the rule and order of reason, not in acting against the judgement of reason.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Korean Security Journal
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• no.14
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• pp.413-429
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• 2007

The Guard over the royal household in the "Goryeo" era was the same as if was over the President or Ruler of a nation today. In those days, a king represented a nation and any threat to the safety of a king could bring the destruction of a nation and the dispersion of the people. by reviewing the change of the 2-Gun 6-Wi system of the era, it can be, summed up as follow, Ther will be suggestions. The Guard might focus on a king's personal safety in the wake of the system of the Silla and Taebong dynasties until the establishment of the Goryeo Dynasty's unique political system. "Goryeo" rebuilt the royal palace in Gyeonyeong-gun to take the shape of unified country after its accomplishment of unification of the late three countries, Then it was afraid of the rebellion and uprising of local powerful clans, The country put them under control and organized the local army with them in the era of Kings, Seongjong, through the kings, Seongjong and Gwangjong. The army system of "Goryeo" consisted of 2-Gun and 6-Wi, and 2-Gun placed above the 6-Wi played the role of the Royal guards, and among the organizations a certain army under the specific name of "Gyeonyong-gun" guarded the kings in the nearest position. An aristocratic culture enjoyed its golden age in the period of stability of the aristocracy of "Goryeo", but afterward in the confusion of the aristocratic disruption and incompatible confrontation the country lost its control, and faced military rebellions by treating civil officials well and ill-treating military officials The safety of kings become unstable with the grasping political power by the military officials, and "Dobang" was established in the era of Choi's family to grasp political power. In the era of Choi Woo, he gathered his men and organized his familys army with them and managed the personnel administration with the civil officials of "Jeongbang and Seobang under his command. Such a fact shows the similarity to today's task of guarding. Considering the facts that "Sambyeolcho, the military ground of the military-men-rule, was at the center of the struggling against Mongolia and that even after the fall of the military regime, they rebelled and fought against Mongolia to the end, we came to know that the nationalism in the era of the military era was great. In the transition of external situations from "Myeong" to "Won"(Chinese dynasties), the conflict between the old "Won"-friendly power and the new "Myeong"-friendly power caused the weakness of the power to guard the royal household, and "Goryeo" at last gave way to the newly rising "Joseon" led by Lee, Seong Gye who won the people's confidence.

• Journal of the Korean Institute of Oriental Medical Informatics
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• v.14 no.1
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• pp.19-42
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• 2008

Blood-Letting Therapy is a rational and ecological medical treatment by which we can heal most of the diseases by removing the static blood which precipitates in the blood vessel and blocks the flowing of blood. And the static blood is the generic term for the injurious, bad, dead and precipitated blood which is blocked the capillary vessel. The Yellow Emperor's Canon of Internal Medicine says that "the patient is treated with drugs internally and stone acupuncture externally. "In the old texts, the blood-letting therapy is mentioned as blood-letting, network vessel pricking, bloodletting, pricking, and arousing pulses etc and it is noted down as the method of network vessel pricking in 'On the Application of Needles' of Spiritual Pivot. Nine-pricking therapy, twelve-pricking therapy and five-pricking therapy are recorded in the methods of network vessel pricking and among them, the method of squeezing blood after pricking the affected part is explained as the network vessel pricking. There are four methods of network vessel pricking, pricking, picking, cluster needling and scatter-pricking and they are fluidly applied to the various symptoms of diseases. In 'On Discriminative Treating for Patients of Different Regions' in Elementary Questions, Ki-baek emphasizes "most of the local people, there are black in skin and loose in striate, and their diseases are mostly of carbuncle kind. It is suitable to treat the disease with stone therapy to prick with stone, so the stone therapy is transmitted from the east. "And in 'On the Corresponding Relation Between the Eum and Yang of Man and All Things' in Elementary Questions, when the Emperor asked Ki-Back, he answered "sthenia means the sthenia of evil, and deficiency means the deficiency of healthy energy. When the blood is sthenic, the evil should be discharged by pricking when out letting the blood; deficiency of vital energy is the asthenia of channels and network vessels, so the energy should drain from the channel which is not deficient, to replenish. "And in this case we can use the methods of 'Breaking out the static bloods', 'driving out the static bloods', blood-letting'. With this we can infer that the blood-letting therapy is made use of the important medical treatments from the ancient times. Especially in referring to the principles of treatment in The Yellow Emperor's Canon of Internal Medicine, it mostly alluded to acupuncture therapies and only eleven times to medicinal treatments. This is to verify that the blood-letting therapy formed the foundation of the medical art. In Dong's Therapy of Acupuncture-Moxibustion and Bloodletting, Dong Kyeong-Chang gave emphasis on the points that there must be extravasated bloods without exception in the serious illnesses which is old, unnatural, accompanying acute pains and so we can revive our body‘s sprit by circulating 'gi' and static blood piled up in the network vessel, regulating the weakness and strength, and controling the disharmony of the internal organs. The blood-letting therapy has effect on the orifice in emergency, such as fore draining, freeing network vessels, harmonizing gi and blood, relieving pain, dispersing swelling and concretion, sedation, resolving toxin as well as strengthening the heart, relieving itching. So it has distinguished effect on all kinds of medical treatment to the modern people. But by the change of social customs and the confucianism of confucius - it is widely spread on the period of North and South Dynasties, 'Wi' and 'Jin' in china and the period of the Three States in korea - The blood-letting therapy which was regarded as the most important medicinal treatment withered rapidly. And Confucius accentuated the importance of our body and all its members, loyalty and filial piety and banned any damage of our body under no circumstances. As a result of it, the therapy of blood-letting had a rapid decrease and barely kept itself in existence in both countries. What is worse, at the period of Japanese colonial rule of korea and our nation's founding of early stage, it has been withered by the high-handed policy to change Oriental Medicine into modern medical science. So the therapy of blood-letting barely kept itself in existence in some Buddhist temples. Another case, it has handed down as a old-fashioned quick fix in folk remedies. But all kinds of the contamination of heavy metals and the misuses of antibiotics are widely spread nowadays, which increased diseases of adult people and incurable diseases as modern society unavoidably made its way into a highly industrial society. To make us more miserable, the western medical science - the antibiotics and surgical operation medical science - already reveals itself into a limit. The necessity of a new medical science which can give a security to the patients who are suffering from the diseases of adult people and the incurable diseases is especially come into the force nowadays. In view of the results after bibliographically studying on the blood-letting Therapy in Elementary Questions of the Yellow Emperor's Canon of Internal Medicine, the blood-letting therapy has acted for the important Oriental medicinal science and has been clarified the prominent effects on the diseases of adult people and the incurable diseases. So it is regarded as an appropriate thing that we lay out a determined theory of the blood-letting therapy and of course prevent the unwanted side effects from inappropriate medicinal treatments, and make full use of clinic by elevating the curative value and that we win back our self-respect of medical treatment which is dominated from the western medical science and ultimately contribute to national medical welfare.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.