Objectives : To review the meaning of Open-Close-Pivot and its transition over time. Methods : Annotations and explanations in chapters where the theory of Open-Close-Pivot originated from in the "Suwen(素問)" and "Lingshu(靈樞)" were examined, followed by philological examination of key physicians. Results & Conclusions : Yang Shang Shan(楊上善) compared the 'Open-Close-Pivot' to a door. Wang Bing(王冰) explained it's movement and stillness to be the principle behind the Three-Yin-Three-Yang's threefold division. Wang Ji(汪機), in "XuSuwenChao(續素問鈔)" explained its physiological function as the entering and exiting of Ying Wei(營衛), and its scope to be exterior, interior, and center. Ma Shi(馬蒔) stratified it similar to "Shanghanlun(傷寒論)"'s six stages, while Wu Kun(吳崑) categorized Shaoyang(少陽) as being in-between exterior and interior. Zhang Jing Yue(張景岳) suggested a standard for the entering-exiting and exterior-interior-center concepts of the Open-Close-Pivot. Zhang Zhi Cong(張志聰) argued a theory of Open-Close-Pivot that emphasized the meaning of Three-Yin-Three-Yang, while Gao Shi Zong(高士宗) explained the relationship between Open, Close, Pivot and the functioning process. Shi Shou Tang(石壽棠) explained the physiology and pathology in the actions among Open-Close-Pivot with a focus on Pivot. Ke Qin(柯琴) applied Open-Close-Pivot to "Shanghanlun(傷寒論)" and used it as the basic principle to the Six Channel Ground Theory(六經地面說), also clinically applying it in the identification and treatment of the Six Channel patterns. Conclusions : Counting based word embedding methods seems to be more effective than.
Purpose Based on the development of artificial intelligence and big data technologies, the RegTech has been emerged to reduce regulatory costs and to enable efficient supervision by regulatory bodies. The word RegTech is a combination of regulation and technology, which means using the technological methods to facilitate the implementation of regulations and to make efficient surveillance and supervision of regulations. The purpose of this study is to describe the recent adoption of RegTech and to provide basic examples of applying RegTech to capital market regulations. Design/methodology/approach English-based ontology and deep learning technologies are quite developed in practice, and it will not be difficult to expand it to European or Latin American languages that are grammatically similar to English. However, it is not easy to use it in most Asian languages such as Korean, which have different grammatical rules. In addition, in the early stages of adoption, companies, financial institutions and regulators will not be familiar with this machine-based reporting system. There is a need to establish an ecosystem which facilitates the adoption of RegTech by consulting and supporting the stakeholders. In this paper, we provide a simple example that shows a procedure of applying RegTech to recognize and interpret Korean language-based capital market regulations. Specifically, we present the process of converting sentences in regulations into a meta-language through the morpheme analyses. We next conduct deep learning analyses to determine whether a regulatory sentence exists in each regulatory paragraph. Findings This study illustrates the applicability of RegTech-based ontology and deep learning technologies in Korean-based capital market regulations.
The first step of this study is to collect appropriate words from the list of words in the relationship. All vocabularies that are unfamiliar-but capable of guessing the meaning and expressing interpersonal relationships-were collected from three Korean dictionaries. Consequently, a compilation of 2,725 words was created; overlapping words were selected; and 910 words were chosen. Only grammatical forms were found; however, words with similar meanings-or identical meanings-were also found, and a reclassification process was required to reflect this. These procedures were repeated seven times, resulting in a total of 249 words being screened. However, due to the characteristics of this study, the number of words needs to be reduced because the meaning of words is more specific and summarized, and the overall interpersonal aspect is well expressed. Therefore, the process of reclassifying 249 words by their familiarity and appropriateness was subsequently undertaken, and the word with the highest level of familiarity and appropriateness was finally selected.
Journal of The Korean Society of Integrative Medicine
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v.9
no.4
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pp.167-181
/
2021
Purpose : This study was conducted to investigate whether phonetic complexity affected the type and frequency of articulation errors and the acoustic duration of consonants and words produced by children with functional articulation and phonological disorders. Methods : The participants in this study were 20 children with functional articulation and phonological disorders and 20 children without such disorders who were between 3 years 7 months old and 4 years 11 months old. The participants were asked to name what they saw in pictures and their responses were recorded. The types and frequencies of articulation errors and the acoustic duration of words were analyzed and words were categorized as being of either 'high' or 'low' phonetic complexity. The acoustic duration of initial and final consonants and vowels following initial consonants were compared between the groups according to articulatory complexity. Results : Children with functional articulation and phonological disorders produced articulation errors more frequently when saying high complexity words and had longer word duration when saying low-complexity words than children without such disorders. There was no major difference in initial and final consonant duration between the groups. but the main effect of articulatory complexity on the duration of both consonants was significant. Conclusion : These results suggest that the articulatory-phonic structure of words influences the speech motor control ability of children with functional articulation and phonological disorders. When articulating consonants, children with functional articulation and phonological disorders had speech motor control ability similar to that of children without such disorders.
An Edwards curve cryptography (EdCC) core supporting point scalar multiplication (PSM) on Edwards curves of Edwards25519 and Edwards448 was designed. For area-efficient implementation, finite field multiplier based on word-based Montgomery multiplication algorithm was designed, and the extended twisted Edwards coordinates system was adopted to implement point operations without division operation. As a result of synthesizing the EdCC core with 100 MHz clock, it was implemented with 24,073 equivalent gates and 11 kbits RAM, and the maximum operating frequency was estimated to be 285 MHz. The evaluation results show that the EdCC core can compute 299 and 66 PSMs per second on Edwards25519 and Edwards448 curves, respectively. Compared to the ECC core with similar structure, the number of clock cycles required for 256-bit PSM was reduced by about 60%, resulting in 7.3 times improvement in computational performance.
Journal of the Korea Institute of Information and Communication Engineering
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v.24
no.2
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pp.172-178
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2020
In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.
Such is an elective affinity between literary studies and psychoanalysis that the latter sometime serves as a form of literary pedagogy. The affinity mainly consists in their shared concern for language. The signification of language in psychoanalysis is much similar to that of literature. Many of psychoanalytic terms and theoretical tenets bear witness to its dependence clinically on speech phenomena and theoretically on language in general. It is most true of Sigmund Freud, for whom the unconscious is in effect the linguistic unconscious. The Freudian unconscious, compressing and displacing through images and ideas, works as a text for psychoanalysis, which approach has not only paved one of the ways to poststructuralist anti-essentialism but with which literary studies also feel uncanny familiarity. Freudian psychoanalysis, starting empirically from clinical observations, discovers that words exist independent of meanings in the form of things in the unconscious system. Out of the various sensory elements of a word-thing, in psychoanalytic terms, the auditory is central. Now with the auditory imagination cultivated in the clinic, Freud figures out compression and displacement as the chief unconscious works, of which my main argument is that they are based phonetically on heteronym and homonym associations respectively. Compression and displacement work to be masks, which excites Freud's sense of challenge: his is a kind of poststructuralist approach, in the sense that the closed interrelatedness of words without external referents determines the signification in a given situation. But the works of compression and displacement, viewed in auditory terms rather than mapped on to metaphor and metonymy, can provide a new insight for a literary reading of Freud. Pursuing Freud's auditory imagination is not only an attempt to read his writing as literary text rather than for theoretical discussion, but also an experiment with the possibility of literary reading of a theoretical text in the age of after-theory.
Journal of the Korea Institute of Information and Communication Engineering
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v.25
no.1
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pp.1-7
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2021
Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.
Many researchers have analyzed the relationship between the financial success patterns of a motion picture and many other factors, such as the production cost, marketing, stars, awards, reviews, genre, and rating. Through these studies, many researchers and investors concluded that big budgets to make a blockbuster movie can serve as an insurance policy to meet their ROI; thus the box office is dominated by blockbuster movies. High-budget blockbuster movies are more likely to receive attention because these movies are more recognizable given their high expenses for production and casting. Therefore, audiences choose blockbusters in an effort to reduce the searching cost and to mitigate the possibility of a regrettable choice. This behavior of consumers, in turn, causes distributors to allocate screens for blockbusters, resulting in "concentration of blockbuster consumption." As such, low-budget films cannot easily become popular due to the lack of distribution. Indeed, low-budget films released on a small number of screens often end up becoming dismal failures. However, there are exceptional examples which are contrary to the general idea in the movie industry that a big budget and showings on a large number of screens can guarantee the success of a movie. Although researchers have attempted to analyze the performances of movies with small budgets, such movies are likely to be regarded as outliers and then be entirely discarded, as they are far from the 'three-sigma' range, especially given that previous research methodologies could not explain the financial success of such unique examples. This study attempts to explain the financial success at the box office of low-budget movies by applying the concept of the tunnel effect in quantum mechanics, as the phenomenon found in the movie industry is similar to a particle's movement in quantum physics. The tunneling effect is a phenomenon by which a particle without enough energy to pass over a potential barrier tunnels through it. Adopting the analogy, this study draws a tunneling probability function and cultural constant to forecast other outliers using the Schrödinger equation. Moreover, the study finds that word-of-mouth creates in the movie industry this phenomenon of finding outliers.
Since movies are experience goods, consumers are easily influenced by other consumers' behavior. For moviegoers, box office rank is the most credible and easily accessible information. Many studies have found that the relationship between a movie's box office rank and its revenue departs from the Pareto distribution, and this phenomenon has been named "increasing returns to information." The primary objective of the current research is to apply the empirical model proposed by De Vany and Walls (1996) to the Korean movie market in order to examine whether the same phenomenon prevails in the Korean movie market. The other purpose of the present study is to provide managers with useful implications about the release timing of a movie by finding different curvatures that depend upon seasonality. The empirical test on the Korean movie market shows similar results as prior studies conducted on the U.S., Hong Kong, and U.K. movie markets. The phenomenon of increasing returns is generated by information transmission among consumers, which makes some movies become blockbusters and others bombs. The proposed model can also be interpreted in such a way that a change in the rank has a nonlinear effect on the movie's performance. If a movie climbs up the chart, it would be rewarded more than its proportion. On the other hand, if a movie falls down in the ranks, its performance would drop rapidly. The research result also indicates that the phenomenon of increasing returns occurs differently depending on when the movies are released. Since the tendency of the increasing returns to information is stronger during the peak seasons, movie marketers should decide upon the release timing of a movie based on its competitiveness. If a movie has substantial potential to incur positive word-of-mouth, it would be more reasonable to release the movie during the peak season to enjoy increasing returns. Otherwise, a movie should be released during the low season to minimize the risk of being dropped from the chart.
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