• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.159-164
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• 2024

The domestic petroleum market is highly sensitive to changes in international oil prices. So, it is important to identify and respond to those changes. In particular, it is necessary to clearly understand the factors causing the price fluctuations of gasoline, which exhibits high consumption. International gasoline prices are influenced by global factors such as gasoline supplies, geopolitical events, and fluctuations in the U.S. dollar. However, previous studies have only focused on gasoline supplies. In this study, we explore the causal relationship between economic indicators and international gasoline prices using various machine learning-based regression models. First, we collect data on various global economic indicators. Second, we perform data preprocessing. Third, we model using Multiple linear regression, Ridge regression, and Lasso(Least Absolute Shrinkage and Selection Operator) regression. The multiple linear regression model showed the highest accuracy at 96.73% in test sets. As a result, Our Multiple linear regression model showed the highest accuracy at 96.73% in test sets. We will expect that our proposed model will be helpful for domestic economic stability and energy policy decisions.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.323-330
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• 2024

He reality is that the college life culture of college students is gradually changing as we enter the AI era. In addition, in the aftermath of the MZ generation's employment difficulties and unemployment difficulties, freshmen begin to worry about their future from college entrance. Therefore, it is necessary to design a college life that can lead to employment from a careful plan for an efficient life in college. This study attempted to suggest a direction for college freshmen to find their career direction, starting with self-exploration, and helping them settle down in college life. In addition, a program was developed with a focus on understanding others and communicating human relationships toward fostering communities, starting with self-understanding. Weeks 1 to 5 were composed of getting to know each other, weeks 6 to 10 were made up of me, we, and weeks 11 to 15 were made up of our future. First, a program was developed so that you can understand yourself and plan your own career path based on this, present your own vision, and specify your future to draw a blueprint.We expect that the research results will contribute to the maturation of career attitudes of students participating in college life planning classes, smooth communication, reduction of school and department dropout rates, and encouragement of satisfaction and pride in school.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.483-490
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• 2012

In parallel with advancement of the industrial society and accompanied quality-of-life improvement, jewelry is now rather viewed as one of common accessories used in daily life, than as a luxurious item as treated before change of perception about it in the past, attracting thus gradually multiplying demand for it. Thanks to rapid spread of multi media like the Internet, an increasing number of people have come to develop great liking for exceptional design and unique format of jewelry products. Following drain of their reserves, natural gems are unlikely to meet the demand for them fully in the future. As a consequence, it seems essential to rely on synthetic, artificial, imitation jewelry or organic substances and quasi-mineral in amorphous structure for substitute jewelry. Since synthetic jewelry has such a great potential as substitute jewelry, it is expected to maximize added value to jewelry if and when accompanied with development of creative design and upgrading of processing technology for jewelry, in addition to various types of synthetic jewelry and glass that have been already put in use as substitute substances. Synthetic jewelry is thus believed to be able to greatly contribute to progress of the jewelry industry. In many countries of the world, jewelry and gem industry has been regarded as one of promising sectors vital in enriching the national wealth. In this context, the Korean Ministry of Finance and Economy announced in July 2007 "an activating policy for the jewelry and gem industry, declaring to cultivate and grow it to be new engine for the nation's growth". The present paper thus aims to conduct a study exclusively on cutting design of synthetic jewelry as a part of measures to activate the jewelry industry in Korea. Efforts are made to develop designs for jewelry that are unique and different from the conventional stereotyped form of polishing and are added with color, pattern and fashionable cutting. Priority is given in this regard to designing jewelry that may attract general public and may be shared by public beyond the limit of conventional design for jewelry and producing products that stand in contrast with other products. By upgrading the quality of jewelry design, competitiveness of the jewelry industry may be ensured and the creative area of jewelry design may be expanded by far.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.1363-1373
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• 2009

본 연구는 두 집단지성의 가장 대표적인 서비스인 네이버 지식iN과 위키피디아의 구조적, 경험적 차이를 바탕으로 생산의 차원에서 생산 주기, 생산 참여자, 생산물의 모델을 설정하고, 새롭게 탄생하는 지식을 중심으로 검증함으로써 최종 지식 소비 행위를 반영한 각각의 종합모델을 도출하였다. 우리는 웹에서 집단지성의 일상화를 확인할 수 있다. 지식 획득 매체가 매스미디어에서 인터넷으로 변화하는 과정에서 등장한 포털 및 검색사이트는 지식의 생산이 전문가패러다임에서 소비자 중심으로 재편될 수 있는 가능성을 열어주었다. 그리고 이러한 생산 방식의 변화는 '지식'의 개념 역시 변화시키고 있다. 즉, 집단지성이라는 새로운 웹2.0의 현상이 지식생산방식을 변화시키고 변화된 지식생산방식은 '지식'자체를 변화시킨다는 이론적 가설을 도출할 수 있는 것이다. 본 연구는 이러한 새로운 현상들을 분석하기 위해서는 먼저 보다 엄밀하게 집단지성의 개념을 규정할 필요성에 출발하였다. 현재 집단지성이라는 이름으로 불리면서 급격히 성장하고 있는 위키 방식의 인터넷 서비스와 지식검색 방식의 인터넷 서비스를 비교함으로써 보다 정교한 집단지성의 모델을 구축하고자 하였다. 위키형 집단지성과 지식검색형 집단지성의 차이점은 경험적으로도 뚜렷하게 확인할 수 있다. 본 연구는 이러한 경험적 차이와 기존의 문헌에서 밝혀진 사실들을 바탕으로 두 서비스의 지식생산 방식을 생산플로우, 생산참여자 성향, 생산물(지식)의 성향과 같이 세 영역으로 나누어 각각의 가설 모델을 설정하고 이 모델을 선정된 질의어를 바탕으로 검증한 뒤에 최종적인 모델을 도출하는 방식으로 진행되었다. 지식검색형 집단지성은 '질문-답변-채택'의 구조이고, 그 구조 속에서 '질문기-답변기-순서화기'를 거쳐 하나의 지식 덩어리인 'K-let'을 생산한다. 생산된 'K-let'들은 지식검색서비스의 데이터베이스에 축적되고, 이는 공통된 질의어를 기준으로 소비자들에 의해서 검색되어 소비된다. 하나의 질문에 대해 여러 개의 답변들이 존재하고, 답변자의 성향은 크게 전문성과 체계성을 바탕으로 한 전문가형 답변자와 경험적이고 의견지향적인 대화형 답변자로 나눠진다. 다수의 네티즌들의 참여에 의해서 지식의 생산이 진행되므로 질문의 성향 역시 사실, 의견, 경험 등 다양한 스펙트럼을 가지는 모델로 설정하였다. 반면에 위키형 집단지성은 개방형 플랫폼을 바탕으로 한 백과사전의 형식이며, 이러한 형식 속에서 최초의 개념어 등록과 다수의 편집활동을 거치면서 완성되지 않는 하나의 아티클인 'W-let'을 생산한다. 이러한 'W-let'은 생성 초기에 소수에 의한 활발한 내용 입력 활동으로 어느 정도의 안정화를 거친 후에는 꾸준한 다수의 수정활동을 통해서 'W-let'의 생명력을 유지함으로써 지식의 실제적인 변화를 반영한다. 생산된 'W-let'들은 위키형 집단지성 서비스의 데이터베이스에 축적되고, 이것들은 내부링크를 통해서 모두 연결되어 있다. 백과사전 형식으로 하나의 개념어를 설명하는 하나의 아티클은 오로지 사실적인 지식들로만 구성되나 내부링크와 외부링크를 통해서 다양한 스펙트럼을 가지는 모델로 설정하였다. 위와 같이 설정된 모델을 바탕으로 공통된 질의어 및 개념어를 선정하여 각각의 서비스에 노출시켰다. 이를 통해서 얻어진 각 서비스의 데이터베이스에 축적된 모든 데이터들 중에서 일정한 기간을 기준으로 각각의 모델 검증에 필요한 데이터를 추출하여 분석하는 방식으로 진행되었다. 그 결과 지식검색형 집단지성에서는 '질문-답변-채택'의 생산 구조 속에 다수가 참여하여 질문-채택답변-기타답변으로 배열되어 있는 완성된 형태의 K-let들을 지속적으로 생산하며 비슷한 성향을 가진 K-let들이 반복적으로 생산되어 지식검색 데이터베이스에 누적된다. 지식 소비자들은 질의어 검색을 통해서 다양한 K-let들을 선택하여 비교, 검토한 후에 선택된 K-let들의 배열은 해체되어 소비자들에 의해서 재배열됨을 발견할 수 있었다. 이에 지식검색형 집단지성이란 다수의 의해서 생산되고 누적된 지식들이 소비자의 검색과 선택에 의해 해체되어 재배열되는 지식의 맞춤화 과정이라고 정의내릴 수 있었다. 반면에 위키형 집단지성에서는 '내용입력-미세수정' 구조 속에서 생명력 있는 W-let을 생성한다. W-let은 백과사전처럼 정리되어 내부링크를 통해서 서로 연결되고, 외부링크를 통해 확장되고, 지식소비자들은 검색을 통해 최초의 W-let에 도달한 후에 링크를 선택함으로써 지식을 확장시킴을 검증할 수 있었다. 따라서 위키형 집단지성이란 다수의 의해서 생산되고 정리된 지식들이 소비자의 검색과 링크에 의해 무한히 확장되는 지식의 확대 재생산되는 과정이라고 정의 내릴 수 있다. 결국, 현재의 집단지성이란 지식이 다수의 참여로 생산됨으로써 개인에게 맞춤화되고, 끊임없이 확대 재생산되는 과정을 의미한다. 그리고 이러한 집단지성의 방식은 지식이라는 현재의 차원을 넘어서 정치, 경제를 비롯한 사회의 전 영역으로 점차적으로 확대되어갈 것이다. 앞으로 연구들은 두 가지 모델이 혼재되어 있는 현재의 집단지성이 어떠한 새로운 모델을 만들면서 다른 영역으로 확장되어갈 것인지에 대해서 초점을 맞춰 나가야할 것이다.

• Cartoon and Animation Studies
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• s.45
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• pp.397-415
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• 2016

This paper will investigate how animated practice can be a research form as practice-led research in an ethnography approach. This practice-led research will explore the issue of the construction of contemporary identities (based on the strange case of Dr. Jekyll and Mr. Hyde) and in particular, the Korean youth culture and identity, exemplified, for example, creation of 'avatars' in the virtual characters of animated online games such as Massively Multiplayer Online Role-playing Games (MMORPGs). In this proposed discussion, I will argue that the sudden period of change in contemporary Korea bears some resemblance to the Victorian era as explored in gothic fiction (e.g. Jekyll and Hyde). In this sense, my animation investigates the connection between the fictional Jekyll and Hyde and a real murder incident by a young Korean boy, which actually happened on the 16th November 2010, in SouthKorea.I will, therefore, construct this practice-led research to obtain the primary data consisted of online and offline practices in 'social ethnography'. These practices engage with specific Korean youth identity, comparing the 'avatar' with the real lives of participants. However, this paper will only focus on the (ethnographic) research process and strategy, using animated (visual) practices, rather than giving the meaning of the specific case of 'Korean-ness'. Eventually, I will explore the four different animated representations as it presents the distinctive animated realties or documentaries by online and offline practices. My intention is to visually interpret the issue of 'Korean-ness' within its socio-cultural context, adapting the convention and code of Jekyll and Hyde concept into an animated documentary in the 'virtual' world (auto-animated documentary by recording avatar interviews and online game footages) and the 'real' world (self-created animated documentary, based on real people and events).

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.200-213
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• 2008

H.264| MPEG-4 AVC is a new video codingstandard defined by JVT (Joint Video Team) which consists of ITU-T and ISO/IEC. Many techniques are adopted fur the compression efficiency: Especially, an intra prediction in an inter frame is one example but it leads to excessive amount of encoding time due to the decision of a candidate mode and a RDcost calculation. For this reason, a fast determination of the best intra prediction mode is the main issue for saving the encoding time. In this paper, by using the result of statistical relation between intra $16{\times}16$ and $4{\times}4$ intra predictions, the number of candidate modes for $4{\times}4$ intra prediction is reduced. Firstly, utilizing motion vector obtained after inter prediction, prediction of a block mode for each macroblock is made. If an intra prediction is needed, the correlation table between $16{\times}16$ and $4{\times}4$ intra predicted modes is created using the probability during each I frame-coding process. Secondly, using this result, the candidate modes for a $4{\times}4$ intra prediction that reaches a predefined specific probability value are only considered in the same GOP For the experiments, JM11.0, the reference software of H.264|MPEG-4 AVC is used and the experimental results show that the encoding time could be reduced by 51.24% in maximum with negligible amounts of PSNR drop and bitrate increase.

• (The) Research of the performance art and culture
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• no.42
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• pp.257-290
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• 2021

The Wonju Nongyo (agricultural work song) is geographically classified as eastern minyo (folk song) which has many distinctive, regional features such as tunes, forms and the use of a melodic line. There has been growing attention to the transmission value of the nongyo including the Wonju Eorirang of the Wonju Origol Nongyo and its region of origin. The Wonju Nongyo is of great value and worthy of preservation in the western part of Gangwon Province. For this reason, it seems fairer to say that a focus should be directed towards establishing the identity of the song and increasing the contextualisation of transmission. At the same time, the preservation association's efforts in passing the traditional song down and education activities fairly deserve equal attention. In addition to the way the folk songs are handed down, a discussion on the facilitation of their use will be required. An in-depth discussion about the restoration and use of the song will be encouraged in a multifaceted manner. Unfortunately, few of the previous literatures on nongyo has gone so far as to investigate Arirang as a separate research topic. In fact, the Wonju Origol Nongyo should be viewed as an intangible cultural asset that paved the way for performance artistry of the Korean agricultural work songs to be seen at a national folk art festival. From the perspective of regional characteristics (traditionally termed "tori"), the Wonju Eorirang represents the cultural value of the manners and customs of our locals which constitute unwritten and neglected literary property and musicality of the song. Particularly, a more attention should be paid to making a record of woodcutters and diversity of farmers' small cooperative groups. The existence of the Wonju Eorirang indicates that the melodies to which the song are sung in Nongyo are of infinite variety. A minyo-singer unfolds various journeys of life through various modes and structure of epic chants, ranging from first encounter, love to marriage, realistic problems to relationship with husband's family and death. The epic chant of the Wonju Origol Nongyo contains a rich variety of regional sentiments about life. In particular, the epic chants of the Galtteukgisor and Ssoeltteukgisori are a genius example of sexual satire and a sense of humor. In the past, the agricultural work songs were rhythmic songs served to synchronize physical movements in groups, coordinating tasks in upland farming and rice paddy with the usage of catchy, repetitive verses easy to pass down. The Wonju Origol Nongyo is a precursor of the work songs which took the farming activities a notch higher to be part of the excitement and festivals. In the context of transmission, a festival serves to demonstrate the value of history and life. The value of the Wonju Eorirang should be appreciated and a concerted effort should be made to find a way to facilitate the transmission of the folk song. A folk-singer is a traditional oral poet and a storyteller of minyo and the forms and species of melody solely depend on the signer. The combination of performance and witticism is shown by the singer freely expressing himself. The Origol Nongyo symbolizes ethnic arts cleverly combining playful effects such as tune, rhythm and old agricultural work of the region. It is to be hoped that much of the efforts is directed to designating such folk songs as the archetype of a cultural heritage. In terms of the foundation on which the folk songs are transmitted, the usage(Performance Content) of a community would be an alternative.

• Information Systems Review
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• v.20 no.2
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• pp.39-62
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• 2018

Thanks to the growth of computing power and the recent development of data analytics, researchers have started to work on the data produced by users through the Internet or social media. This study is in line with these recent research trends and attempts to adopt data analytical techniques. We focus on the impact of "internal marketing" factors on firm performance, which is typically studied through survey methodologies. We looked into the job review platform Jobplanet (www.jobplanet.co.kr), which is a website where employees and former employees anonymously review companies and their management. With web crawling processes, we collected over 40K data points and performed morphological analysis to classify employees' reviews for internal marketing data. We then implemented econometric analysis to see the relationship between internal marketing and market capitalization. Contrary to the findings of extant survey studies, internal marketing is positively related to a firm's market capitalization only within a limited area. In most of the areas, the relationships are negative. Particularly, female-friendly environment and human resource development (HRD) are the areas exhibiting positive relations with market capitalization in the manufacturing industry. In the service industry, most of the areas, such as employ welfare and work-life balance, are negatively related with market capitalization. When firm size is small (or the history is short), female-friendly environment positively affect firm performance. On the contrary, when firm size is big (or the history is long), most of the internal marketing factors are either negative or insignificant. We explain the theoretical contributions and managerial implications with these results.

• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.247-259
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• 2000

This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.