• Journal of the Korean Chemical Society
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• v.63 no.3
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• pp.183-195
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• 2019

In this study, we investigated the characteristics of the authentic inquiry components in the inquiry tasks of Science Inquiry Experiments textbooks developed under the 2015 Revised National Curriculum. After classifying inquiry tasks by core concepts, we analyzed the cases that students autonomously planned or performed the authentic inquiry components. The results of the study revealed that investigating multiple materials component most frequently appeared in all units. However, generating research question, selecting variables, observing multiple variables and transforming observations components appeared in a few tasks of history and everyday science units as they were often guided or structured in textbooks. Controlling simple or complex variables, observing intervening variables and considering methodological flaws components rarely appeared in all units as most of textbooks did not consider or indicate explicitly. Authentic inquiry components of everyday science unit tended to be handled in small group activities. On the bases of the results, the implications for the development of the inquiry tasks of Science Inquiry Experiments textbooks are discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.451-461
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• 2024

Recently, various AI chatbots based on large language models have been released. Chatbots have the advantage of providing users with quick and easy information through interactive prompts, making them useful in various fields such as question answering, writing, and programming. However, a vulnerability in chatbots called "prompt injection attacks" has been proposed. This attack involves injecting instructions into the chatbot to violate predefined guidelines. Such attacks can be critical as they may lead to the leakage of confidential information within large language models or trigger other malicious activities. However, the vulnerability of Korean prompts has not been adequately validated. Therefore, in this paper, we aim to generate malicious Korean prompts and perform attacks on the popular chatbot to analyze their feasibility. To achieve this, we propose a system that automatically generates malicious Korean prompts by analyzing existing prompt injection attacks. Specifically, we focus on generating malicious prompts that induce harmful expressions from large language models and validate their effectiveness in practice.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.1
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• pp.97-110
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• 2001

An image exists in the thought of every subjective person and it exercises its influence over everything, having a great power in the real world. An positive image of the nurse has an influence on her faith, value and confidence, therefore increasing her job satisfaction, helping to upgrade her level of profession of nursing through qualitative nursing service as a result, considering the necessity of such an image when it comes to improvement of the profession, the confirmation of the image is indispensable to its evaluation of a speciality in nursing. This study is intended to help that improvement of the nursing profession in the present so that the total effort in every field of nursing is made and to offer basic material for developing a strategy to improve the image of nurses. This study is designed to investigate such an image descriptively. The subjects include 105 nurses, 60 doctors, 68 office workers, 88 medical engineers, 127 patients and there protectors with a total of 448 adapted with accidental sampling, who work at Y and W general hospital in Chonju. The measuring instrument consists of 40 question, with the researcher amended and made from on of Inja Song(1993), Donsoon Lee(1995), Ilsim yang(1998), and its Cronbach's alpha coefficient is .95. Data were collected from March 1 2000 to March 20, 2000 using self-reported questionnairs, analyzed with SPSS WIN 7.5 after encoding. The results are as follows: 1. Most of the subjects thinks the nursing as a hard, stressful, always busy job(more than 75%), and consider nurses as good-looking, supportive and responsible to co-workers to above average degree($50.0{\sim}74.9%$), especially it shows the idea that nursing is independently academic job and has come to fasten itself upon the public. But it shows below the everage($25.0%{\sim}49.9%$) in regard to self development as a specialist, affection for there job, an association activity, service to the community, high intelligence level and direct given patient nursing service. It also rated low as a recommendable job, independently nursing accomplishment, social position. 2. The nurses, patients and there protectors expressed more positive opinions than doctors, medical engineers, office workers about the image of the nurse(F=18.80, p=.00). This fact indicates that the former group evaluated the image similarly contrary to lowness of the latter. 3. In the study on what influenced upon the image, it defines to 79.8% by direct contact in the hospital or acquaintance with nurses, and 16.3% by mass media. 67.3% answered that they saw the image in a new light through hospitalization, which suggests an important source for the image management originates from caring for the quality of nursing service. Considering the evaluation of the image above, we need strategies to lead a unique professional knowledge and technological development, insurance of professional self-determination, high social position, participation in group activities, dedication to lifetime job, in order that nursing comes to expand as a professional occupation. Also, as for generating more positive images, we must take the quality of nursing service into account and offer and monitor correct information about the expanded role and function of the nurse continuously so that mass media reflect a more accurate image of nurses in general.

• Journal of Science Education
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• v.37 no.2
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• pp.323-337
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• 2013

The purpose of this study was to analyze the scientific reasoning ability during open-inquiry activities of science-gifted 2nd middle school students. Open-inquiry activity is similar to process of scientists' science knowledge generation. Identifying and analyzing the scientific reasoning process and the scientific reasoning ability during open-inquiry activities of science-gifted students, will be able to provide implications for future research. CSRI Matrix(Dolan & Grady, 2010) was used to analyze the complexity of the scientific reasoning ability. The higher degree of complexity of the scientific reasoning is similar to process of scientists' science knowledge generation. The results showed that each process of the open-inquiry activities were distributed by various steps of complexity of the scientific reasoning. Particularly, 'The generating questions' and 'Connecting data to the research question' were 'most complex' step in all teams. On the other side, 'Posing preliminary hypotheses', 'Selecting dependent and independent variables', 'Considering the limitations or flaws of their experiments' were low steps in most teams. And 'Communicating and defending findings' was distributed by most various steps of complexity of the scientific reasoning.

• The Journal of the Petrological Society of Korea
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• v.5 no.2
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• pp.188-199
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• 1996

Boeun granodiorite, which intruded into the metasedimentary rocks of the Ogcheon Group, show chemical natures of metaluminous and calc-alkaline. Generating and emplacing environment of the Boeun granodiorite would have been a active continental margin. Comparing to the contemporaneous Inje-Hongcheon granodiorite in the Gyeonggi massif, the Boeun granodiorite seems likely to have formed under more immature continental arc environment. Compositional changes of major, trace and rare earth elements in granodiorite and felsic dyke are not certain to indicate crystallization differentiation. From this fact, the simple fractional crystallization model would be in question to explain the magma process which controlled the formation of the Boeun granitic mass. The model calculations for Rayleigh fractionation, fractionation with variable major-component composition, assimilation-fractional crystallization (AFC) were carried out to examine the magma process of the mass. The results of former two models do not agree with the compositional variations in the mass. The AFC model can be, however, applied to the magma process. The conditions for AFC process are (1) composition of assimilated wallrock is similar to that of primary magma. (2) assimilating rate is similar to crystallizing rate, and (3) mass of assimilated wallrock is about 10% of that of the magma. These conditions deny a possibility that the assimilated wallrock was the metasedimentary rocks of the Ogcheon Group. This indicates that after having experienced the assimilation process in deeper crust, the granodiorite magma intruded into the Ogcheon group. Every model calculating suggests that the felsic dyke was differentiated not from the granodiorite magma, but from a different source magma.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.173-185
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• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.

• Journal of the Korean Chemical Society
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• v.66 no.5
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• pp.390-404
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• 2022

The purpose of this study was to analyze the characteristics and changes in epistemic thinking when an argument-based inquiry science class was applied in no face-to-face and face-to-face situations. Participants of this study were 113 8th grade students of four classes from a coed educational middle school in a metropolitan city. Data collection was made over one semester during which ten argument-based inquiry science lessons on five subjects were conducted in both no face-to-face and face-to-face context. As a result of comparing and analyzing students' epistemic thinking in the argumentation of each group's generating question stage, the no face-to-face classes showed higher understanding of contents and more evidence suggestion validity than face-to-face classes did. Claim validity and categories of process in argumentation were higher in face-to-face classes than No face-to-face classes. Students were able to improve their understanding of knowledge through writing by discussing rather than direct communication in no face-to-face situations, and in face-to-face situations, students showed that their thoughts were influenced by interpersonal relationships with the group members.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.495-507
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• 2023

Teachers often encounter challenges in supporting students with question generation and the development of investigation plans in sensemaking activities. A primary challenge stems from the ambiguity surrounding how students apply their conceptual understandings in this process. This study aims to explore how students apply their conceptual understandings to generate questions and design investigation processes in a sensemaking activity. Two types of student group activities were identified and examined for comparison: One focused on designing a process to achieve the goal of sensemaking, and the other focused on following the step-by-step scientific inquiry procedures. The design of investigation process in each group was concretized with epistemic criteria used for evaluating the designs. The students' use of conceptual understandings in discussions around each was then examined. The findings reveal three epistemic criteria employed in generating questions and designing investigation processes. First, the students examined the interestingness of natural phenomena, using their conceptual understandings of the structure and function of entities within natural phenomena to identify a target phenomenon. This process involved verifying their existing knowledge to determine the need for new understanding. The second criterion was the feasibility of investigating specific variables with the given resources. Here, the students relied on their conceptual understandings of the structure and function of entities corresponding to each variable to assess whether each variable could be investigated. The third epistemic criterion involved examining whether the factors of target phenomena expressed in everyday terms could be translated into observable variables capable of explaining the phenomena. Conceptual understandings related to the function of entities were used to translate everyday expressions into observable variables and vice versa. The students' conceptual understanding of a comprehensive mechanism was used to connect the elements of the phenomenon and use the elements as potential factors to explain the target phenomenon. In the case where the students focused on carrying out step-by-step procedures, data collection feasibility was the sole epistemic criterion guiding the design. This study contributes to elucidating how the process of a sensemaking activity can be developed in the science classroom and developing conceptual supports for designing sensemaking activities that align with students' perspectives.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.127-139
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• 2023

During the process of preparing for and initiating a startup, startup entrepreneurs allocate a significant amount of time to developing a business plan. Within this process, the documented business plan serves not only as a roadmap for the venture but also as a communication tool for capital acquisition and internal team collaboration. However, is the business plan, meticulously crafted by entrepreneurs, actually effective in generating startup performance? To answer this question, this study empirically analyzed the impact of a business plan on startup performance. Additionally, it examined how the relationship between the business plan and performance changes based on the satisfaction levels of entrepreneurs regarding the business plan. Through the analysis, the study validated the influence of the completeness of the business plan and entrepreneurial satisfaction on startup performance, and derived implications. To conduct the empirical analysis, a survey was conducted among 150 entrepreneurs. Regression analysis was performed to examine the relationship between the completeness of the business plan and performance, and the sample was further divided into two groups: startups with less than three years of operation and startups with three or more years of operation, for secondary analysis. The analysis results revealed that the completeness of the startup's business plan has a positive impact on both financial and non-financial performance. Furthermore, it is observed that the entrepreneur's satisfaction with the business plan had a moderating effect on the relationship between the business plan and financial performance. Moreover, for startups that are less than three years old, the entrepreneur's satisfaction with the business plan exhibits a moderating effect on the relationship between the completeness of the business plan and non-financial performance. This study holds significance as it reaffirms the importance of business plan development as a means to achieve sustainable growth for early-stage startups and empirically validates its significance. It is expected that this study will provide valuable insights for future startup entrepreneurs to better understand the importance of business planning and contribute to reducing the failure rate of early-stage startups.