• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.33-38
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• 2018

Recently, we are trying to predict the emotion from various information and to convey the emotion information that the supervisor wants to inform the audience. In addition, audiences intend to understand the flow of emotions through various information of non-dialogue parts, such as cinematography, scene background, background sound and so on. In this paper, we propose to extract emotions by mixing not only the context of scripts but also the cinematography information such as color, background sound, composition, arrangement and so on. In other words, we propose an emotional prediction system that learns and distinguishes various emotional expression techniques into dialogue and non-dialogue regions, contributes to the completeness of the movie, and quickly applies them to new changes. The precision of the proposed system is improved by about 5.1% and 0.4%, and the recall is improved by about 4.3% and 1.6%, respectively, when compared with the modified n-gram and morphological analysis.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.269-275
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• 2022

As artificial intelligence services targeting humans increase, social demands are increasing that artificial intelligence should also be made on an ethical basis. Following this trend, the government and businesses are preparing policies and norms related to artificial intelligence ethics. In order to establish reasonable policies and norms, the first step is to understand the public's perceptions. In this paper, social data and news comments were collected and analyzed to understand the public's perception related to artificial intelligence and ethics. Interest analysis, emotional analysis, and discourse analysis were performed and visualized on the collected datasets. As a result of the analysis, interest in "artificial intelligence ethics" and "artificial intelligence" favorability showed an inversely proportional correlation. As a result of discourse analysis, the biggest issue was "personal information leakage," and it also showed a discourse on contamination and deflection of learning data and whether computer-made artificial intelligence should be given a legal personality. This study can be used as data to grasp the public's perception when preparing artificial intelligence ethical norms and policies.

• Journal of Korean Elementary Science Education
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• v.41 no.1
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• pp.93-105
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• 2022

This study investigated the aspects of how three preservice elementary school teachers conducted the data-text transforming discourses in their science simulation teaching and how their epistemological conversations worked for learners' construction of scientific knowledge. Three preservice teachers, who had presented simulation teaching on the seasonal change of constellations, participated in the study. The results revealed that one preservice teacher, who had implemented the transforming discourses of data-to-evidence and model-to-explanation, appeared to facilitate learners' knowledge construction. The other two preservice teachers had difficulty helping learners construct science knowledge due to their lack of transforming discourses. What we should consider for improving preservice elementary school teachers' teaching competencies was discussed based on a detailed comparison of three cases of preservice teachers' data-text transforming.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.1-8
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• 2009

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle timc-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference teaming and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.355-355
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• 2022

기후변화에 의한 이상가뭄 발생 등을 대비하기 위한 비상용수 또는 대체수자원으로서의 지하수 개발수요가 증가하는 추세에 따라 기저유량 확보 및 수질 개선 방안을 수립하는 것은 지속가능한 수자원 이용·관리 측면에 있어서 매우 중요하다. 지하수 및 기저유량 확보 및 수질 개선을 위해서는 지표-지하수 통합 관리가 필요하며 이를 기반으로 지하수 및 기저유량 변동에 대한 인과관계 파악 및 구체적인 조사가 필요하다. 따라서 본 연구에서는 지표-지하수에 대한 계절적·시공간적 변동성을 잘 모의할 수 있는 통합 모델을 기반으로 지하수위 변동을 포함한 물수지 분석과 장·단기 유출해석이 정량적으로 분석하고자 하였으며, 평창군 대화면, 만대지구, 신둔천 유역을 대상으로 간벌, BMP, LID를 비롯한 다양한 시나리오에 따른 기저유량 및 수질변화 그리고 오염특성 파악을 수행하였다. 본 연구에서는 지표-지하수 통합 모델링을 위하여 SWAT-MODFLOW 모형을 활용하였으며, 간벌 시나리오의 경우 모형 Source code를 수정하여 간벌의 효과를 모의할 수 있도록 수정하였다. 또한 BMP와 LID의 경우 각 HRU별로 저감시설에 대한 효율 및 매개변수 조정을 통해 효율을 모의하였다. 모형의 입력자료 구축을 위하여 지표 모형의 경우 DEM, 토지이용도, 토양도를 활용하였으며, 지하수 모형의 경우 지하수기초조사자료에 수록된 수리전도도, 비산출율, 비보유율 조사결과를 활용하여 입력자료를 구축하였다. 그 결과 간벌시나리오의 경우 건기시 최소 6.7% 이상의 하천유량, 22.56% 이상의 기저유량, 그리고 0.3 m 이상의 지하수위 확보가 가능한 것으로 나타났다. BMP의 경우 유역면적의 약 7%에 BMP가 설치된 것으로 나타났으며, 이에 따른 하천 말단 SS저감효율은 6.7%로 나타났으나 유량에서는 큰 차이를 나타내지 못하였다. 마지막으로 LID시나리오의 경우 적용 소유역의 강우시 평균유량이 약 29% 감소하였으며 건기시 평균 기저유량이 약 44%이상, 평균 BFI는 약 0.13 증가한 것으로 나타났다.

• Smart Media Journal
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• v.12 no.9
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• pp.81-88
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• 2023

Recently, communication through online is increasing due to the spread of non-face-to-face services due to COVID-19. In non-face-to-face situations, the other person's opinions and emotions are recognized through modalities such as text, speech, and images. Currently, research on multimodal emotion recognition that combines various modalities is actively underway. Among them, emotion recognition using speech data is attracting attention as a means of understanding emotions through sound and language information, but most of the time, emotions are recognized using a single speech feature value. However, because a variety of emotions exist in a complex manner in a conversation, a method for recognizing multiple emotions is needed. Therefore, in this paper, we propose a multi-emotion regression model that extracts feature vectors after preprocessing speech data to recognize complex, inherent emotions and takes into account the passage of time.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.101-112
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• 2024

In this paper, we present EDF (Event Data Factory), an interactive tool designed to assist event log generation for process mining. EDF integrates various data connectors to improve its capability to assist users in connecting to diverse data sources. Our tool employs low-code/no-code technology, along with graph-based visualization, to help non-expert users understand process flow and enhance the user experience. By utilizing metadata information, EDF allows users to efficiently generate an event log containing case, activity, and timestamp attributes. Through log quality metrics, our tool enables users to assess the generated event log quality. We implement EDF under a cloud-based architecture and run a performance evaluation. Our case study and results demonstrate the usability and applicability of EDF. Finally, an observational study confirms that EDF is easy to use and beneficial, expanding small and medium-sized enterprises' (SMEs) access to process mining applications.

• Korean Journal of Biological Psychiatry
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• v.4 no.1
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• pp.84-94
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• 1997

This study was done to examine changes of plasma homovanillic acid(HVA), 5-hydroxyindoleacetic acid(5-HIAA), and HVA/5-HIAA ratio during an 8-week clozapine trial and to investigate the relationship between the plasma monoamine metabolites and treatment responses. Twenty-seven chronic schizophrenic patiens were treated for 8 weeks with clozapine. The psychopathology was assessed at baseline just clozapine trial and then every 2 weeks until the end of 8-week clozapine treatment using the Positive and Negative Syndrome Scale(PANSS) and the Clinical Global Impression scale(CGI). The plasma HVA and 5-HIAA levels were measured also biweekly using high preformance liquid chromatography with electrochemical detection method. Plasma HVA and 5-HIAA levels were significantly decreased during a 8-week clozapine treatment, although plasma HVA/5-HIAA ratio showed no significant change. The changes of plasma HVA levels were in significant correlations with the changes of PANSS positive scores, of general psychophathology scores, and changes of total socres. The changes of plasma 5-HIAA levels were in signfificant correlations with the changes of PANSS negative scores. But the changes of plasma HVA/5-HIAA ratio had no significant correlation with any PANSS subscale score changes. 48% of the patients treated with clozapine was categorized as responders, who showed at least a 20% decrease in PANSS total socre and a CGI severity score of mildly ill or less(${\leq}3$) at the end pint of the study. The baseline plasma HVA levels and HVA/5-HIAA ratio were significantly higher in responders(N=13) than in nonresponders (N=14). But no significant difference in baseline levels of plasma 5-HIAA was found between responders and nonresponders. At the end point of the study, there was significant difference in the change of plasma HVA between responders(40.3% decrement) and nonresponders(3.1% increment). But no signficant differences in the change of plasma 5-HIAA and the change of plasma HVA/5-HIAA ratio between responders and nonresponders were observed. These results suggest that the antipsychotic effect of clozapine on positive symptoms may be associated with dopaminergic blocking activity, and that on negative symptoms may be associated with serotonergic blocking activity. The baseline plasma HVA levels and the change of HVA levels from baseline may be useful predictors of treatment response with clozapine.

• Trans-
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• v.7
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• pp.103-121
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• 2019

In some documentary films, there are interviews, but in some other ones, there aren't any. As for the documentaries with interviews, the director uses talking heads to suggest their own arguments and to have audience agree. It is evident that interviews play a key role since they lead the story of a human-related documentary. Some directors prefer interviews where directors' questions and interviewees' answers are both heard. On the other hand, there a re directors who carry out the story just by using the answers from the interviewees. Then, it becomes crucial that we understand both of these styles and have new perspectives when watching documentary films. Ethics has always been considered one of the most important factors in documentaries and since they are believed to be "true," the influence documentaries have on the society is enormous. However, possibilities of exaggerating or manipulating the "truth" always exist. Therefore, it is important for the audience to identify the intentions of the director. As a matter of fact, there have been countless researches being done, but it is difficult to find studies that discuss the ways interviews are used in documentary films. The two different styles mentioned above do have huge differences in terms of directing methods. Thus, taking a look at differences from diverse angles will help us better understand the essentials of documentary films. This study will take examples from the interviews in Michael Moore's (2002), (2007) and observe how the flow of interviews can change when the voice of the director gets involved. There will also be a close examination of interviews in Kim Ilran and Hong Ji Yoo's (2011), and (2005) directed by Jim Butterworth, Aeron Lubarsky, and Lisa Sleeth, as well as Sebastian Junger and Tim Hetherington's (2010). By a careful review, use of dissolve, cross-cutting, and flashback will be analyzed to show how different editing techniques have an impact on subjective views of the director.

• Journal of The Korean Association For Science Education
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• v.32 no.4
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• pp.555-569
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• 2012

Many science education research and practices are recently emphasizing the importance of collaborative learning. This study also understands learning in aspects of socio-cultural context, and regarded the creation of meaning in a same-age group as an important learning process. This is most especially true in the premise that the formation of roles in a collaborative learning is important for successful interactive learning. This study aims to find out how roles form in a group. For this purpose, university students participating in a group discussion activity about energy flow and circulation of material were selected as research participants. Discussions among the nine students in one group consisted of cognitive conversations on the topic and operational conversations for preparing a presentation. Video-clips of the discussions were made and transcribed. For the analysis, we developed a framework that includes four interaction functions (cognitive, organizational, meta-cognitive, operational), four action elements (question, simple answer, providing opinion, response to opinion), and two to four intention elements by each action elements. As a result, a total of nine roles were revealed through the interaction function and element; cognitive questioner, operational questioner, simple answerer, operational suggester, organizational commander, operational commander, cognitive explainer, terminator, reflective thinker. These roles are re-classified into seven utterance patterns by the utterance order and object, and they were categorized into three role groups (facilitating interaction, sustaining interaction, finishing interaction). The result means that role formation and function can have influence on learning and interaction. This study is meaningful to the suggestion to collaborative learning including project-based learning, investigation, club activity, and for the re-illumination of the role in an aspect of the interaction.