• The Korean Journal of Coaching Psychology
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• v.7 no.3
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• pp.1-26
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• 2023

This study aims to explore how professors at community colleges are experiencing career guidance for their students, uncovering key components related to causes, phenomena, contexts, coping strategies, etc., and deriving a paradigm model to structurally. To achieve this objective, focus group interviews were conducted with a total of 23 community college professors, and the results were analyzed using the grounded theory method (Strauss & Corbin, 1998). The analysis yielded 17 categories and 31 subcategories. The central phenomenon in the career guidance of community college professors was categorized into two groups: the distress experience in career guidance and attitude changes toward interactions with students..Three categories of causal conditions contributing to the occurrence of the central phenomenon were identified: professors' lack of expertise in career guidance, students' scope and needs for career guidance, and students' low interest and expectations. Additionally, four contextual conditions corresponding to special situations or circumstances that contributed to the central phenomenon were identified: increasing demand for career guidance, excessive burden and time constraints for career guidance, lack of communication about career guidance at the institutional level, and limitations within the career guidance support system. Furthermore, the study uncovered patterns of action-interaction, mediating conditions, and outcomes. This study is expected to contribute to a better understanding of the actual experiences of college professors in the career guidance process, and to stimulate consideration of the types of support required for effective career guidance for college professors in the future.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.49-55
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• 2024

This study aims to develop a three-sentence speech screening test to evaluate speech development in 4-year-old children and provide standards for comparison with peers. Screening tests were conducted on 24 children each in the first and second halves of 4 years old. The screening test results showed a correlation of .7 with the existing speech disorder evaluation test results. We compared whether there was a difference between the two groups of 4-year-old in the phonological development indicators and error patterns obtained through the screening test. The developmental indicators of the children in the second half were high, but there were no statistically significant differences. The Korean Speech Sound Analysis Tool (KSAT) was used for all analyses, and the automatic analysis results and contents of the clinician's manual analysis were compared. The degree of agreement between the automatic and manual error pattern analyses was 93.63%. The significance of this study is that the standard of speech of a 4-year-old child of the speech screening test according to three sentences at the level of elicited sentences, and the applicability of the KSAT were reviewed in both clinical and research fields.

• Korean Journal of Optics and Photonics
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• v.35 no.4
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• pp.175-183
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• 2024

Research into optical signal processing using photonic integrated circuits (PICs) has been actively pursued in various fields, including optical communication, optical sensors, and quantum optics. Among the materials used in PIC fabrication, polymers have attracted significant interest due to their unique characteristics. To fabricate polymer-based PICs, establishing an accurate manufacturing process for the cross-sectional structure of an optical waveguide is crucial. For stable device performance and high yield in mass production, a process with high reproducibility and a wide tolerance for variation is necessary. This study proposes an efficient method for fabricating polymer optical-waveguide devices by introducing the atomic layer deposition (ALD) process. Compared to conventional photoresist or metal-film deposition methods, the ALD process enables more precise fabrication of the optical waveguide's core structure. Polyimide optical waveguides with a core size of 1.8 × 1.6 ㎛² are fabricated using the ALD process, and their propagation losses are measured. Additionally, a multimode interference (MMI) optical-waveguide power-splitter device is fabricated and characterized. Throughout the fabrication, no cracking issues are observed in the etching-mask layer, the vertical profiles of the waveguide patterns are excellent, and the propagation loss is below 1.5 dB/cm. These results confirm that the ALD process is a suitable method for the mass production of high-quality polymer photonic devices.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• Journal of Korean Home Economics Education Association
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• v.19 no.1 s.43
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• pp.99-114
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• 2007

This study aims at investigating how middle school students perceive the content of the 'Me and My Family Relations' unit in the technology and home economics textbook, act on such perceptions and how this connects with their healthy family relations. In addition, the study also points at inquiring into what kind of differences and mutual influences can be found in the above-mentioned three factors according to family environment. With this objective. this research has analyzed survey data conducted on 401 7th grade middle school students residing in Incheon Greater city, collected by the random sampling method. The findings are as follow: First, the students were found to have positive perceptions on the 'family relations and communication' unit in the technology and home economics text book. However. they were also found to perceive that the content was not as realizable in their everyday family lives. Second, the number of students who perceived their family lives to be healthy was found to be quite high. The students perceived their family lives to be healthy projecting from such aspects as the degree of gratification and affection, extent of family bonding, communication patterns, and problem solving abilities, in the same order. In addition, the higher the families' socio-economic level, and in the cases that the students had working mothers and the fathers held higher degrees, the degree to which the families were perceived to be healthy was higher. Third, in investigating the influence that such factors as the students' family environment, the degree that students perceived the text book content positively, and the degree that the students perceive the content to be realizable have on healthy family relations, among these factors, the students' perceived degree of how healthy their family relations are had the most bearing over the above-mentioned factors. The second influential factor on how healthy family relations are was the family's affectional environment, found to be more influential than such factors as family type, the mother's employment status, living standards, and the parents' educational level. On the other hand, the perceived level of realizability was found to have a lower influence on the students' family relations than the perceived positivity.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.305-316
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• 2013

To find out if modern roundabout is still effective under drivers behavior and driving conditions in Busan Metropolitan City, the effects before and after introduction of roundabout were analyzed. According to analysis on velocity profile at roundabout, velocity deviation decreased, and average vehicle speed was close to design speed. As a result, it has been confirmed that most roundabouts were properly built. In terms of traffic operation, average vehicle speed improved by 87.2% when a traffic intersection was replaced by a roundabout. therefore, it has been found out that the introduction of roundabout has a positive effect on increasing vehicle speed by reducing traffic congestion. In addition, annual benefits expected from the replacement from a traffic intersection to a roundabout were KRW 872 million as follows; KRW 410 million in traffic communication, KRW 39 million in transportation safety, KRW 255 million in energy saving, KRW 95 million in reduction of air pollution and KRW 73 million in reduction of traffic signal installation cost. In other words, if 10% (193 spots) of all traffic intersections (1,926 spots in total) in Busan City are replaced by roundabouts, the municipal authority would be able to save about KRW 168.3 billion. According to analysis on the benefits expected from the installation of roundabouts compared to the investment cost for traffic intersections, about KRW 679 million could be saved per roundabout. Considering 10% of all traffic intersections in the City of Busan, about KRW 131 billion could be saved annually. The traffic accidents in roundabout usually occur because drivers aren't aware of right-of-way rules. Once the right-of-way rules settle, the number of traffic accidents would significantly decrease. In addition, it is urgent to promote education and campaign for drivers, pedestrians and bikers on the roundabout.