Park, Hyunah;Tae, Moonyoung;Huh, Youngjin;Lee, Joonhwan
Journal of the HCI Society of Korea
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v.14
no.1
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pp.15-22
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2019
The purpose of this study is to investigate the users' expectation and expectation gap about the attributes of smart speaker as an intelligent agent, ie autonomy, sociality, responsiveness, activeness, time continuity, goal orientation. To this end, semi-structured interviews were conducted for smart speaker users and analyzed based on ground theory. Result has shown that people have huge expectation gap about the sociality and human-likeness of smart speakers, due to limitations in technology. The responsiveness of smart speakers was found to have positive expectation gap. For the memory of time-sequential information, there was an ambivalent expectation gap depending on the degree of information sensitivity and presentation method. We also found that there was a low expectation level for autonomous aspects of smart speakers. In addition, proactive aspects were preferred only when appropriate for the context. This study presents implications for designing a way to interact with smart speakers and managing expectations.
Park, Kyung-Yong;Kim, Gil-Tae;Kim, Tae-Min;Ji, Won-Gil;Kwag, Byung-Chang
Land and Housing Review
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v.13
no.3
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pp.107-113
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2022
With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.
Journal of the Korea Society of Computer and Information
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v.28
no.2
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pp.227-234
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2023
In this paper, we developed a design thinking-based artificial intelligence education program for middle school students and applied it to verify the impact on creative problem-solving skills. The inspection tool used the Creative Problem Solving Profile Inventory (CPSPI), an inspection tool for measuring creative thinking type ability based on the CPS theory of Hwasun Lee, Jungmin Pyo, Insoo Choe(2014). CPSPI included the steps of evaluating cognitive preferences and cognitive abilities by supplementing the limitations of existing tests, and sharing and persuading one's ideas with others. Before and after applying the design thinking-based artificial intelligence education program, as a result of analyzing the creative problem-solving ability, it increased significantly in all areas. As a result of analyzing the creative problem-solving ability of middle school students, significant results were found in the areas of Problem Detection and Analysis, Idea Generation, Action plan, Execution, Persuasion and Communication. The effect of design thinking was confirmed as a teaching and learning method to improve creative problem-solving ability in artificial intelligence education.
This study was a randomized before-and-after design of 17 subjects in the experimental group and 17 subjects in the control group to investigate the effects of listening to relaxing music on the mood state and autonomic nervous system, that is, heart rate of hospitalized patients with mental illness. The collected data were analyzed with SPSS V15.0. There was a statistically significant difference between the two groups in mood state and autonomic nervous system, that is heart rate and the effect of listening to relaxation music was objectively verified(<.05). among the subdomains of mood states, tension(<.00), depression (<.00), vitality (<.03), fatigue () <.01), excluding anger (>.39) and confusion (>.33) showed a significant difference, proving that it is an effective intervention method applied to hospitalized mentally ill patients. In the future, we would like to suggest long-term intervention research and development and application, and research on the effect of mood change and heart rate using individual preferred music.
The study aims to identify unmet needs, barriers, and constraints in reproductive health education for adolescent girls in Luwero, Uganda. The study included a survey of 55 young women (aged 14-26) in the region and interviews with 40 stakeholders, including teachers and healthcare workers. Results showed that the majority of respondents (87%) rely on schools for reproductive health information, preferring health institutions (58%) for reproductive health services. Over half of respondents encountered obstacles accessing relevant information due to limited resources and cultural barriers and emphasized the significance of schools and health institutions as essential health information sources. Schools and health institutions need to collaborate to enhance reproductive health education for young women's accessibility.
Journal of the Korea Academia-Industrial cooperation Society
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v.16
no.1
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pp.165-172
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2015
The purpose of this study was to identify the effect of Genibo program robot-based learning(R-Learning) on a pre-schooler's mental state. To achieve above study purpose, the subject of this study was selected 46(teacher 2, five years old pre-schooler 44) from pre-school childrens in Kyongki Y city(R-Learning activity participants group 21: boys 10, girls 11. non-participants 25: boys 13, girls 12). R-Learning program is consist of 5 field about 20 contents using Genibo robot, were applied to the experimental group and the pre-post test was conducted using the EQ assessment tool and observations. The data were analyzed by t-test using the SPSS(ver 18.0) program. The results were as follows: First, the exposure of robots to pre-schoolers in practical situation has shown positive influence to the children's emotional well-being. Positive improvements were observed in the four sub categories of the EQ assessment after exposure. Second, the Genibo used for this study, is a biomimetic AI based robot mimicking the behavior of a pet dog. This is related more or less to the specifications of a pre-school education where animals are used as a 'friendly medium' to facilitate the learning process. Third, the robot exposure gave benefit to all the ones in the sample, regardless of sex. Furthermore, It is suggested that promising potential for robots to be utilized as a new educational media plus facilitator, R-Learning is related more or less to the specifications of a pre-school education where animals are used as a 'friendly medium' to facilitate the learning process, and when applying them for education, stereotyping the likes of sex is overrated - instead, the focus should be more on the pre-schoolers' / childrens' individual traits, learning curve differences and alike.
This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.
Byung-Chang Kwag;Won-Gil Ji;Sung-Ze Yi;Gil-Tae Kim
Land and Housing Review
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v.14
no.3
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pp.125-135
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2023
In South Korea, it has been increased the necessity of supplying housing services to meet the needs and desires of various residents by reflecting various demographic and social changes. In particular, various smart device has been widely utilized in South Korea and the smart technologies, such as artificial intelligence and the Internet of Things has been developed rapidly. These smart technologies could support smart housing that allows residents to easily and comfortably employ residential services. However, it is necessary to improve the awareness of users in order to spread the smart housing residential services connected to smart technologies. For this reason, this study observed changes in users' perceptions of smart housing residential service technology using Living Lab. As a result, after experiencing the Living Lab, users' awareness of smart housing housing service increased, and it was observed that the preferred housing service technology was more detailed than before the Living Lab experience. This study shows that it is important to raise users' awareness for the dissemination of smart housing residential service technology, and that Living Lab can be an effective means for this purpose.
Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.
The purpose of this study was to investigate quality characteristics of the meat batter containing dietary fiber extracted rice bran. The formulations of meat batters were manufactured in a model system with 2% raw rice bran and 2, 4, 6% levels of dietary fiber extracted rice bran, respectively. The proximate compositions of dietary fiber extracted rice bran were 53.27% dietary fiber, 6.10% crude fat, 22.99% crude protein, 12.78% crude moisture, and 7.41% crude ash. Compared with control of uncooked meat batter, the pH value of all treatments were significantly different(p<0.05). The pH of cooked meat batter were similar to uncooked meat batter. $CIE\;L^*-\;and\;CIE\;b^*-value$ of uncooked meat batter containing dietary fiber extracted rice bran were lower than control, but CIE $a^*-value$ of treatment was higher than those in control(p<0.05). All treatments had significantly lower cooking loss and emulsion stability than control(p<0.05). Compared with control, viscosity of the treatments containing dietary fiber extracted rice bran were observed significantly higher than those in control (p<0.05). And then hardness, cohesiveness, gumminess, and chewiness of treatments were higher than in control(p<0.05). Conclusively, the results of this study showed that addition of dietary fiber extracted rice bran affected the high quality properties of meat batter.
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