• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of The Korean Association For Science Education
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• v.22 no.4
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• pp.779-795
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• 2002

Internet, a world wide network of computers, is considered as a sea of information because it allows people to share information beyond the barriors of time and space. However, in spite of the unmeasurable potential applications of the internet, its use in the field of biology education has been extremely limited mainly due to the scarcity of good biology-related sites. In order to provide useful guidelines for constructing user-friendly study sites, which can help high school students with different intellectual levels to study biology, comparative studies were performed on selected educational sites. Initially, hundreds of related sites were examined, and, subsequently, four distinct sites were selected not only because they are well organized, but also because each is unique in its contents. Also, a survey was carried out against the users of each site. The survey results indicated that the high school students regard the web-based biology study tools as effective teaching methods although there might be some bias in criteria for selecting target sites. In addition to the detailed biology topics and the related biology informations, multimedia data including pictures, animations and movies are found to be one of the important ingredients for desirable biology study sites. Thus, the inclusion of multimedia components should also be considered when developing a systematic biology study site. Overall, the role of the cyber space is expected to become more and more important. Since the development of the user-satisfied and self-guided sites require interdisciplinary collaborational efforts which should be made to promote extensive communication among teachers, education professionals, and computer engineers. Furthermore, the introduction of good biology study sites to the students by their teachers is also important factor for the successful web-based education.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.1
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• pp.59-73
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• 2023

Objective : To examine changes in participation patterns of children with Autism Spectrum Disorder (ASD) in play activities during COVID-19 by reviewing relevant literature. Methods : This scoping review was conducted via five steps. we created a research question and searched for relevant literature published in English through CINAHL, PubMed, ERIC, MEDLINE, Google Scholar and Google search engine. After selecting the literature based on inclusion criteria, data were charted based on 10 items (i.e., author name, journal name, publication year, nation, authors' majors, research method, participant' age and gender as well as quantitative and qualitative results of study). The results were analyzed using descriptive numerical and thematic analyses. Results : After reviewing 437 articles and 152 websites, six articles were included. Theses articles were conducted by experts from various fields and countries. Five themes were highlighted in selected articles: COVID-19 resulted in (1) decreased time of outdoor play, (2) increased play time on screen, (3) increased time spent with family, (4) increased sensory difficulties, and (5) recommendations for services for children with disabilities and during COVID-19. Conclusion : This study suggests telerehabilitation programs about parental behavior strategies in order to solve difficulties in which children with ASD may experience when participating in play activities during disasters. Study results can be used as fundamental evidence to emphasize importance of play activities and to systematize role of occupational therapists and service guidelines for supporting play activities of children with disabilities in disasters.

• Korean Journal of School Psychology
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• v.15 no.3
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• pp.399-431
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• 2018

The purpose of this study was to summarize the empirical literature on implementation of positive behavior support (PBS) within a multi-tiered system of supports in American and Korean schools and to compare its key features and outcomes in an attempt to suggest future directions for development of a Korean school-wide PBS model and implementation manuals as well as directions for future research. Twenty-four American articles and 11 Korean articles (total 35 articles) that reported the outcomes of implementation of PBS at a tier 1 and/or tier 2, or tier 3 level and that met established inclusion criteria were analyzed using systematic procedures. Comparisons were made in the areas of key features and outcomes of PBS in addition to general methodology (e.g., participants, design, implementation duration, dependent measures) at each tier of PBS. The results indicated that positive outcomes for student behavior and other areas were reported across tiers in all American and Korean studies. At the tier 1 level, teaching expectations and rules were the primary focus of PBS in American and Korean schools. However, Korean schools focused on modifying the school and classroom environments and teaching social skills whereas American schools focused on teacher training on standardized interventions or curricular by experts and teacher support during implementation of PBS. At the tier 2 level, more American studies reported implementation of tier 2 interventions within school-wide PBS, and Check/In Check/Out (CICO) was found to be the most commonly used tier 2 intervention. The results also indicated that in comparison to Korean schools, American schools were more likely to use systematic screening tools or procedures to identify students who need tier 2 interventions and more likely to promote parental involvement with implementing interventions. At the tier 3 level, more Korean studies reported the outcomes of individualized interventions, but more American studies reported that designing individualized intervention plans based on comprehensive functional behavior assessment results and establishment of systematic screening systems were focused when implementing individualized interventions. Furthermore, few Korean studies reported the assessment of procedural integrity, social validity, and contextual fit in implementing PBS across tiers, indicating the need for development of valid instruments that could be used in assessing these areas. Based on these results, limitations of the study and suggestions for future research are discussed.

• The Korean Journal of Malacology
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• v.30 no.2
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• pp.155-163
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• 2014

Serpins are a group of proteins involved in the regulation of serine and other type of proteases, and have been identified in many kinds of organisms from invertebrates to vertebrates. Serpins are known to regulate the proteolytic cascades of the innate immune pathways in addition to their roles in blood coagulation, angiogenesis, fibrinolysis, inflammation and tumor suppression. In this study, we have isolated two partial serpin gene fragments from expressed sequence tags (ESTs) of Nesiohelix samarangae. Dotplot analysis indicates that they are of two different types, Ns-serpin type 1 and Ns-serpin type 2. Ns-serpin type 1 has 819 bp coding region (272 amino acids), whereas Ns-serpin type 2 has 555 bp coding region (185 amino acids). Molecular phylogenetic analysis shows that the identified serpins have high similarities to their counterparts in the California see slug, Aplysia californica. Yet, the precise biological and immunological roles of these Ns-serpins remain to be further investigated using RNA interference and other molecular techniques.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.39-50
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• 2015

In information retrieval process through search engine, some users want to retrieve several documents that are corresponding with specific time period situation. For example, if user wants to search a document that contains the situation before 'Japanese invasions of Korea era', he may use the keyword 'Japanese invasions of Korea' by using searching query. Then, search engine gives all of documents about 'Japanese invasions of Korea' disregarding time period in order. It makes user to do an additional work. In addition, a large percentage of cases which is related to historical documents have different time period between generation date of a document and record time of contents. If time period in document contents can be extracted, it may facilitate effective information for retrieval and various applications. Consequently, we pursue a research extracting time period of Joseon era's historical documents by using historic literature for Joseon era in order to deduct the time period corresponding with document content in this paper. We define historical objects based on historic literature that was collected from web and confirm a possibility of extracting time period of web document by machine learning techniques. In addition to the machine learning techniques, we propose and apply the similarity filtering based on the comparison between the historical objects. Finally, we'll evaluate the result of temporal indexing accuracy and improvement.

• Journal of Digital Contents Society
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• v.12 no.4
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• pp.457-465
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• 2011

The annual R&D investment in Korea increased by an average of 12.2percent during the last 5 years. Therefore, prevention of duplicate projects being performed became an important factor in promoting the efficiency of R&D investment and the originality of R&D projects. On measuring the similarity of projects, the measurement model used to estimate the accuracy of the similarity is crucial. In this paper, we propose an advanced measurement model on checking the similarity of R&D projects for promoting the efficiency of R&D investment. The proposed model is made up of the following steps for the model measurement, sampling and analyzing. During the sampling step, we append the abstract of R&D reports on the search engine based on document vector. We then measure the similarity on projects to use research title network which is consists of the compound keyword and the weight of items on during the analysis. The proposed method improved the accuracy for measuring the similarity of projects by an average of 0.19 over the existing search engine and by 9.25 over the simple keyword search on R&D projects. On searching the similarity with the appending conditions and high sampling, it improved the accuracy of measuring the similarity of R&D projects.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.4
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• pp.371-376
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• 2012

The experimental test was conducted for a heavy-duty DME bus in JE-05 exhaust gas test mode using a chassis dynamometer, exhaust gas analyzers, and a PM measurement system. The heavy-duty DME bus was not equipped with after-treatment systems such as DOC or DPF. The dynamic behavior, emission characteristics, and fuel economy of the bus were investigated with an 8.0-liter, 6-cylinder conventional diesel engine. The results showed that the dynamic behavior in DME mode was almost the same as in diesel mode. However, there was little difference among the two operation modes for $NO_x$ and CO emissions. THC emissions were lower for DME mode than for diesel mode. Also, the amount of PM emissions was remarkably lower than for the diesel mode because DME contains a greater amount of oxygen than diesel. The data showed that $CO_2$ emissions were almost similar in the two modes but fuel economy (calculated using heating value) was lower for DME mode than for diesel mode.

• The Journal of Fisheries Business Administration
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• v.37 no.1 s.70
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• pp.121-142
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• 2006

EU는 당면과제인 과잉 어획능력을 해소하기 위해 공동어업정책하 어업구조정책의 하나로 '다년도지도프로그램(Multi Annual Guidance Programmes: MAGPs)'을 시행해 왔다. 지난 1983년부터 2002년까지 시행된 MAGP는 EU의 어업구조정책의 핵심 요소이다. 이러한MAGP는 최초 EU의 공공원조계획을 위한 체제의 하나로 입안되었으며, 그 목적은 어선 톤수와 마력수에 대한 각 회원국 어선의 능력을 동결하고자 하는 것이었다. 회원국들은 $4{\sim}5$년 주기로 각 국의 어선개발에 대한 정밀한 계획을 세워야하며, 어선의 용량(총톤수와 엔진출력)과 어획노력에 관한 목표들을 달성하도록 되어 있다. 이러한 감소 목표들은 독립된 과학적 조사결과에 따라 EU 위원회에 제안되고, 공동체 선박등록부에 의거 각국의 프로그램에 대한 적정 실현여부를 감시받고 있다. 또한 각 회원국들은 매년 4월 1일까지 EU위원회에 당해 MAGP의 실현에 대한 진도보고서를 제출하는 식으로 운영되어 왔다. 현재까지 4개의 MAGP가 시행되었다. 제1세대 MAGP(1983-1986년)는 회원국들에 강제적인 것은 아닌 관계로 별다른 성과가 없었으나, 공동체 어선들간의 어획능력 증가 경쟁에 대한 제어의 표현으로 의미가 있었다. 제2세대 MAGP(1987-1991년)에서는 처음으로 진출입 제어를 위한 매우 제한된 법규정이 만들어졌으며, 제3세대 MAGP(1992-1996년)에서는 공동체 어선 감소의 실제목표를 수여하는 첫 번째 계획이었다. 그리고 이 계획은 약 15%정도의 매 우 실질적인 어획능력 감소를 이루었다. 가장 최근에 끝난 4세대 MAGP(1997-2002)는 공동어업정책의 개혁 시간을 주기 위하여 1년 연장되었으며, 이 시스템은 만약 어선의 어획구성상 감소되는 어족자원의 비율이 낮으면 그 자원을 보호하고자 하는 것이었으나, 그 성과는 매우 낮았다. 이 4세대 계획의 또 다른 중요한 혁신은 회원국이 그들의 어선의 활동규제와 크기를 결합시키거나, 또는 전적으로 표본어선의 수익성 분석을 통해 어획능력을 제거하고자 하는 것이다. 그러나 이 역시 관리와 통제의 곤란으로 별 다른 성과를 거두지 못한 것으로 평가받고 있다. 그러나 많은 어려움과 제도상 불완전함에도 불구하고 MAGP는 일정한 효과를 거둔 것으로 보고되고 있다. 즉 어획능력은 지난 20년동안 전체적으로 25% 가량 감소하였으며, 특히 오래되고 비효율적인 어선에 대한 감척으로 어획능력 감소에 기여한 것으로 평가되고 있다. 이들 프로그램은 특히 보조금을 통해 어선의 제3국 영구이전과 낡고 비효율적인 어선의 신조를 가속화시킨 것으로 보고되고 있다.