• Journal of The Korean Association For Science Education
• /
• v.28 no.6
• /
• pp.565-578
• /
• 2008

The purpose of this study is to search for the factors that influence students' understanding of the nature of science through the experience of the cognitive processes of authentic open inquiries. The freshmen of a science high school practiced authentic open inquiries reflecting epistemological characteristics of authentic science. The case study was conducted with four focus students who were successful or unsuccessful at learning the nature of science during the authentic open inquiry activity. Questions that the focus students asked during the inquiries as well as students' answers to pre- and post-VNOS (C type) were analysed, and then elaborated in the semi-structured interview. The findings suggest that open inquiry activities provide the inquiry contexts that help science high school students to understand the nature of science, and that the characteristics of students' cognition influence the understanding of the nature of science. For instance, designing experiments with their own research questions had an influence on the students' understanding about the scientific methods and the diversity of research types, and drawing conclusions from their own data made students experience scientific reasoning. In addition, the experience of collecting anomalous data helped students to understand the role of inferences in generating scientific knowledge and the creative nature of scientific knowledge. In this inquiry context, the reflective thinking that came from proactive discussion among students, made students think about the validity of the designing experiments and interpreting data, and helped them to understand the uncertain nature of reasoning and the diverse nature of scientific methods. Moreover, divergent thinking linked to analogical thinking helped students to understand the creative nature of science.

• Journal of the Korean Institute of Gas
• /
• v.28 no.2
• /
• pp.93-104
• /
• 2024

Facility diagnosis is essential for the smooth operation and life extension of rotating equipment used in industrial sites. Compared to other diagnostic methods, vibration diagnosis can find most of the initial defects, such as unbalance, alignment failure, bearing defects and resonance, compared to other diagnostic methods. Therefore, vibration analysis is the most commonly used facility diagnosis method in industrial sites, and is usefully used as a predictive preservation (PdM) technology to manage the condition of the facility. However, since the vibration diagnosis method is performed based on experience based on the standard, it is carried out by experts. Therefore, it is intended to contribute to the reliability of the facility by establishing a system that anyone can easily judge defects by establishing a vibration diagnosis method performed based on experience as a knowledgeable code system. An algorithm was developed based on the ISO-20816 standard for vibration measurement, and the reliability was verified by comparing the results of vibration measurement at various demonstration sites such as petrochemical plant compressors, hydrogen charging stations, and industrial machinery with the results of analysis using a development system. The developed algorithm can contribute to predictive maintenance (PdM) technology that anyone can diagnose the condition of the rotating machine at industrial sites and identify defects early to replace parts at the exact time of replacement. Furthermore, it is expected that it will contribute to reducing maintenance costs and downtime due to the failure of rotating machines when applied to various industrial sites such as oil refining facilities, transportation, production facilities, and aviation facilities.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.37 no.2
• /
• pp.14-25
• /
• 2009

We live in an age which is exponentially growing as the knowledge paradigm is changing. New sites are subject to contemporary landscape architecture function as "fields" in which this hybrid aspect is both actively practiced and becoming a catalyst for change in the area of landscape architecture. With this as its background, this study attempts to deal with how the aspect of integration in environmental design is manifested. For this purpose, the tendencies for the discussion of integration in various fields of practice were examined: planning theories, urban theories, architecture, public environment, engineering, and landscape architecture. As yet, the discussions of interdisciplinary integration, which occur in practice in these respective fields, mainly tend to be oriented toward the effective implementation of the merits of other related fields. Seen from these examples of practice, integrated design approaches can be found in the following three aspects: design objects, respective professional areas, and methodologies of approaches and design. In terms of design objects, the positions of individual design subjects present themselves as most obvious, and integration or combination of the physical targets that come to exist through design can be easily seen. Most examples of integration turn out to be this, in almost every case of which the theme and the target of expression are integrated via a small number of certain methods. In terms of professional areas, what can be mainly evidenced is how the individual subject acts when the subject designs. The strong points of professionals from each field seem to create synergy, achieving through integration optimum results. In terms of methodologies of approaches and design, there are attempts to create integrated approaches as ways of effective decision-making, in which case the integration of all of the interest parties is of primary concern. As yet, few instances have been found in which integrated design has had enough strength to be seen as a concrete design methodology based on practical examples. However, it is encouraging that theoretical approaches and the necessity for integrated design have been identified from multiple perspectives, and that a practical movement such as landscape urbanism has come into active being. The authors of this study find this point in time to be ripe for discussions on integrated practices in terms of environmental design, on the basis of the synthetic approaches mentioned above.

• Journal of agricultural medicine and community health
• /
• v.26 no.2
• /
• pp.133-146
• /
• 2001

The purpose of this study was to investigate the treatment status and its related factors of the newly detected rural hypertensives through community health promotion program. A questionnaire survey and blood pressure measurement were performed to 6,977 residents of a rural area, and 282 hypertensives detected by blood pressure measurement were selected as subjects of the study. The study employed the health belief model as a hypothetical model. The major results of this study were as follows: The proportion of person experienced treatment among hypertensives was 12.0%. Treatment experience rate was significantly related with age and educational level(p<0.01). That is, if they were older, lower educational level, the treatment experience rate was higher. The major reasons of no treatment were 'they had not hypertensive symptoms ' (45.6%), 'their blood pressure was not high so much that they received treatment ' (43.2%). The chief facilities for treatment were public health institutions(57.9%) such as health center and health subcenter, and hospital/ clinics(29.8%). The treatment experience rate was higher when they had higher perceived severity for hypertension, lower perceived barrier to treatment, although statistically not significant. Treatment experience rate was significantly related with cues to action and health education experience(p<0.05). That is, if they had hypertension related symptoms such as headache previously, patients suffered from hypertension complication and health education experience for hypertension, the treatment experience rate was higher. In multiple logistic regression analysis for treatment experience, having a cerebrovascular patient in their acquaintance and the experience of health education for hypertension were significant variables. On consideration of above findings, it would to be essential to provide knowledge about hypertension and its treatment, and severity of hypertension complications through health education.

• Journal of the Korean earth science society
• /
• v.41 no.3
• /
• pp.248-260
• /
• 2020

Oceanic current maps introduced in science and earth science textbooks can offer a valuable opportunity for students to learn about rapid climate change and the role of currents associated with the global energy balance problem. Previously developed oceanic current maps in middle and high school textbooks under the 2007 and 2009-revised national curriculum contained various errors in terms of scientific accuracy. To resolve these problems, marine experts have constructed a unified oceanographic map of the oceans surrounding the Korean Peninsula. Since 2010, this process has involved a continuous, long-term consultation procedure. By extensively gathering opinions and through verification process, a representative and scientific oceanic current map was eventually constructed. Based on this, the educational oceanic current maps, targeting the comprehension of middle and high school students, were developed. These maps were incorporated into middle and high school textbooks in accordance with the revised 2015 curriculum. In this study, we analyzed the oceanic current maps of five middle school science textbooks and six earth science textbooks that were published in high school in 2019. Although all the oceanic current maps in the textbooks were unified based on the proposed scientific oceanic current maps, there were problems such as the omission of certain oceanic currents or the use of a combination of dotted and solid lines. Moreover, several textbooks were found to be using incorrect names for oceanic currents. This study suggests that oceanic current maps, produced by integrating scientific knowledge, should be visually accurate and utilized appropriately to avoid students' misconception.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.131-154
• /
• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of The Korean Association For Science Education
• /
• v.28 no.1
• /
• pp.1-14
• /
• 2008

The image of science is one of the recurrent topics in science education research. In particular, we believe that students' images of Doing-Science-Well could be used for identifying not only students' perceived goals of science learning, but also practical guidelines of effective science teaching. In this study, the students' images of Doing-Science-Well were investigated with the following two research questions: (i) what are student's images of Doing-Science-Well?; (ii) in what contexts do students perceive that someone is doing science well? Thirty seven students in a high school in Seoul, Korea were asked to write their personal experiences by which they realized that someone was doing science well. The main results of the study are the following: Firstly, the images of Doing-Science-Well could be categorized into 'Einstein type', 'Socrates type', 'MacGyver type' and six more types. Secondly, with regard to contexts, students tended to realize that somebody is doing science well in terms of two kinds of contexts: 4 physical contexts and 6 psychological contexts. The findings led us to develop a frame of judging Doing-Science-Well, which combines the types and two kinds of contexts. The frame illustrates the multiplicity of the images of Doing-Science-Well.

• Archives of design research
• /
• v.17 no.2
• /
• pp.425-436
• /
• 2004

A new design field called eDesign appears as if eBiz is an online related business in which an industrialized design creates the individual value added facing a digital revolution. The field of eDesign requires a special design process and management methodology regardless of the fact that human sensitivity will be satisfied through a dehumanized computer technique. However, it is the reality of eDesign that has been dependent upon a simple process or project management tool of general design. In this study, we develop an eDesign platform based on an eDesign process and template mainly focused on eBusiness in order to overcome the wrong situation. The template is a kind of document that has a standardization form. We aim to establish a general process through various case projects, store information using a necessary template, and use for the way of visual communication. We propose a standard of eDesign platform that can be widely applied to the field of design, medium and small enterprises focused on IT businesses or design-team through this project performed as an educational-industrial study. It makes it possible to get a detailed process methodology, which can be applied to many small design related companies that don't have their own process yet, and will be a scale for comparing their own process in which the company has a process of opened standard eDesign with it. In addition, it makes possible a systematic control of the own projects within and outside the firm, accumulating information for the firm through the database, and easy communication. Furthermore, it can be applied to check the process of the project as a checklist, and then it will reduce trial and error repeated for every project that has been done.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.109-130
• /
• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• 대한공업교육학회지
• /
• v.38 no.2
• /
• pp.89-113
• /
• 2013

The study started from the point that learners should be basically equipped to quickly respond to changes in demand for future human resources efficiently and effectively, and an attitude to take part in learning voluntarily should thus be cultivated. To this end, the author applied the TAI model based on a module as a class strategy to solve problems related to several classes occurred in specialized high schools. This application of the TAI model was also motivated by the necessity for designing an appropriate teaching-learning method that encourages improvement of self-learning capacity, consistent learning motivation, and willingness rather than external factors. Through this work, the author aims to heighten the interest of learners and improve endurance in learning. The study results are as follows. First, the learning unit was structuralized as a module and then learning stages were proceeded with so that capacity to adapt to learning would improve. The achievement standard (learning goal) was structuralized in a module type by analyzing and reorganizing the textbook considering the link between the actual practice field and a curriculum based on subject characteristics. Through the process of module type learning stages, the student's capacity to ascertain characteristics of units and to adapt to learning both improved. Second, through application of a TAI model based on a module, Self-Directed Learning capacity and capacity to adapt to a new field improved. By applying the module, Self-Directed Learning could be accomplished more effectively than in the existing passive learning environment. By grafting cooperative learning of the TAI model, students had greater interest and achievement in classes, self-confidence and community consciousness, and an opportunity to broaden their thinking. In particular, improvement of self-confidence is effective in cultivating the capacity required in industrial society to transcend the learning of simple functions and knowledge, as well as the capacity to adapt to new environments. Third, by solving tasks focused on fields related to industrial sites, not only actual survey capacity but also additional capacity to identify and solve tasks through various experiences improved. Furthermore, it was helpful for students to have interest and motivation about their own life and learning to cultivate the qualities and capacity to adapt to the working world where new knowledge and technology rapidly change. Fourth, by applying a standard-based assessment system for technical subjects introduced in 2012 to model design for learning plans, clearer and more objective assessment criteria were arranged, and individual learning through instruction at each achievement level could be accomplished. This improved achievement level of individual learners was helpful in reaching achievement goals at specific levels by overcoming the disadvantages of cooperative learning in each group.