• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of radiological science and technology
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• v.38 no.3
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• pp.295-304
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• 2015

This study intended to examine the correlation of career self-regulation (plan and check-up, positive thinking, career feedback, environment formation for career) and career identity (career decision, indecisiveness, career indecision) caused by parental career support (informative, emotional, financial, and empirical) among freshmen, sophomores, and juniors in the radiotechnology department. For assessment, a survey was conducted and according to the results, there existed correlation as follows. Regarding parental career support, emotional support is plan and check-up (r=.25, p<.001), Career feedback (r=.54, p<.001), and positive thinking (r=.46, p<.001) showed high positive correlation while informative support showed correlation in all factors showing high correlation with environment formation for career (r=.22, p<.001), plan and check-up (r=.20, p<.001), career feedback (r=.24, p<.001), and positive thinking (r=.26, p<.001). Financial support career feedback (r=.33, p<.001) and positive thinking (r=.34, p<.001) showed somewhat higher correlation. All factors of environment formation for career (r=.18, p<.001), plan and check-up (r=.25, p<.001), career feedback (r=.37, p<.001), and positive thinking (r=.30, p<.001) showed high correlation. Informative support showed high correlation only with career decision (r=.27, p<.001) and financial support also showed high correlation only with career decision (r=.18, p<.001). Also, empirical support was somewhat highly correlated only with career decision (r=.23, p<.001). Regarding school-year difference depending on parental career support, there was significant difference between emotional support (F=8.52, p<.001), financial support (F=8.97, p<.001), and empirical support (F=5.36, p<.05) while informative support was dismissed. Regarding school-year difference depending on career self-regulation, there was significant difference between career feedback (F=8.48, p<.001) and positive thinking (F=16.29, p<.001) while environment formation for career and plan and check-up were dismissed. Regarding school-year difference depending on career identity, there was significant difference between career indecision (F=4.01, p<.05) and career decision (F=11.72, p<.001) while indecisiveness was dismissed. According to the analysis results, parents' active support to their child like respecting and listening to their opinion on career, provision of career related experience or information, and provision of necessary financial aid for their study or academic preparation made the students plan and exploring their career, examine accomplishment progress, have positive idea to realize their objectives. In addition, the students were able to establish the objective of their career by forming the environment that helped them realize their objectives by seeking advices and encouragement from surroundings. Meanwhile, the parents' attitude to respect and listen to their child's career related opinion affected their career decision and indecision. Although informative support helped the students' career decision, financial and empirical support caused effect only to career decision.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.111-131
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• 2015

There are only a handful number of research conducted on pattern analysis of corporate distress as compared with research for bankruptcy prediction. The few that exists mainly focus on audited firms because financial data collection is easier for these firms. But in reality, corporate financial distress is a far more common and critical phenomenon for non-audited firms which are mainly comprised of small and medium sized firms. The purpose of this paper is to classify non-audited firms under distress according to their financial ratio using data mining; Self-Organizing Map (SOM). SOM is a type of artificial neural network that is trained using unsupervised learning to produce a lower dimensional discretized representation of the input space of the training samples, called a map. SOM is different from other artificial neural networks as it applies competitive learning as opposed to error-correction learning such as backpropagation with gradient descent, and in the sense that it uses a neighborhood function to preserve the topological properties of the input space. It is one of the popular and successful clustering algorithm. In this study, we classify types of financial distress firms, specially, non-audited firms. In the empirical test, we collect 10 financial ratios of 100 non-audited firms under distress in 2004 for the previous two years (2002 and 2003). Using these financial ratios and the SOM algorithm, five distinct patterns were distinguished. In pattern 1, financial distress was very serious in almost all financial ratios. 12% of the firms are included in these patterns. In pattern 2, financial distress was weak in almost financial ratios. 14% of the firms are included in pattern 2. In pattern 3, growth ratio was the worst among all patterns. It is speculated that the firms of this pattern may be under distress due to severe competition in their industries. Approximately 30% of the firms fell into this group. In pattern 4, the growth ratio was higher than any other pattern but the cash ratio and profitability ratio were not at the level of the growth ratio. It is concluded that the firms of this pattern were under distress in pursuit of expanding their business. About 25% of the firms were in this pattern. Last, pattern 5 encompassed very solvent firms. Perhaps firms of this pattern were distressed due to a bad short-term strategic decision or due to problems with the enterpriser of the firms. Approximately 18% of the firms were under this pattern. This study has the academic and empirical contribution. In the perspectives of the academic contribution, non-audited companies that tend to be easily bankrupt and have the unstructured or easily manipulated financial data are classified by the data mining technology (Self-Organizing Map) rather than big sized audited firms that have the well prepared and reliable financial data. In the perspectives of the empirical one, even though the financial data of the non-audited firms are conducted to analyze, it is useful for find out the first order symptom of financial distress, which makes us to forecast the prediction of bankruptcy of the firms and to manage the early warning and alert signal. These are the academic and empirical contribution of this study. The limitation of this research is to analyze only 100 corporates due to the difficulty of collecting the financial data of the non-audited firms, which make us to be hard to proceed to the analysis by the category or size difference. Also, non-financial qualitative data is crucial for the analysis of bankruptcy. Thus, the non-financial qualitative factor is taken into account for the next study. This study sheds some light on the non-audited small and medium sized firms' distress prediction in the future.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.65-72
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• 2013

In this study, the early suicide prevention program was applied to the elementary school students and compared the prior & post effect of the program, and verified the status of psychology change like emotional status, or temptation to take a suicide, and presented the possibility as a suicide prevention program. The period of adolescence is the very unstable period in the process of growth being cognitively immature, emotionally impulsive period. It is the period emotionally unstable and unpredictable possible to select the method of suicide as an extreme method to escape the reality, or impulsive problem solving against small conflict or dispute situation. Many stress of the student such as recent nuclear family, expectation of parents to their children, education problem, socio-environmental elements, individual psychological factor lead students to the extreme activity of suicide in recent days. In this study, the scope of stress experienced in the elementary school as well as idea and degree of temptation regarding suicide by the suicide prevention program were identified, and through prevention program such as meditation training, breath training and through experience of anger control, emotion-expression, self overcome and establish positive self-identity and make understanding Self-control, Self-esteem & preciousness of life based on which the effect to suicide prevention was analyzed. The study was made targeting 51 students of 2 classes of 6th grade of elementary school of Goyang-si and processed 30 minutes every morning focused on through experience & activity of the principle & method of brain science. The data was collected for 20 times before starting morning class by using Suicide Probability Scale(herein SPS-A) designed to predict effectively suicide Probability, suicide risk prediction scale, surveyed by 7 areas such as Positive outlook, Within the family closeness, Impulsivity, Interpersonal hostility, Hopelessness, Hopelessness syndrome, suicide accident. Analytical methods and validation was used the Wilcoxon's signed rank test using SPSS Program. Though the process of program in short period, but there was a effective and positive results in the 7 areas in the average comparison. But in the t-test result, there was a different outcome. It indicated changes in the 3 questionnaires (No.7, No.14, No.19) out of 31 SPS-A questionnaires, and there was a no change to the rest item. It also indicated more changes of the students in the class A than class B. And in case of the class A students, psychological changes were verified in the areas of Hopelessness syndrome, suicide accident among 7 areas after the program was processed. Through this study, it could be verified that different results could be derived depending on the Student tendency, program professional(teacher in charge, processing lecturer). The suicide prevention program presented in this article can be a help in learning and suicide prevention with consistent systematization, activation through emotion and impulse control based on emotional stress relief and positive self-identity recovery, stabilization of brain waves, and let the short period program not to be died out but to be continued connecting from childhood to adolescence capable to make surrounding environment for spiritual, physical healthy growth for which this could be an effective program for suicide prevention of the social problem.

• Journal of Gifted/Talented Education
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• v.23 no.2
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• pp.161-175
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• 2013

The purpose of this study is to investigate the differences of perception on giftedness between homeroom teachers and teachers of the gifted. The data was collected from 13 homeroom teachers and 8 teachers of gifted students. It was analyzed using recommendation letters, and shorthand notes about giftedness. The results of the study were as follows: most homeroom teachers used awards, learning attitude, presentation of self and school achievements for defined giftedness and preferred an exemplary student with task commitment but often overlooked motivation. The teachers of the gifted preferred motivation and self-satisfaction but not other social and affective characteristics. Also homeroom teachers thought that education condition is important, while the teachers of the gifted believed it was not an all important element. These differences will hurt the credibility in the selection or gifted students because homeroom teachers and teachers of the gifted use different words and expressions in their assessments of the same students. Therefore, I believe more needs to be done to encourage homeroom teachers to better understand gifted children through training programs.

• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.13-23
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• 2014

For this paper, we developed a game-addiction therapy program for students with gaming addiction based on multiple intelligences (MI) and verified its effects. The participants were 54 elementary students selected through a game addiction test in Incheon City, Korea. We tested the students' MI to facilitate program development. the students with gaming addiction showed strengths in the Bodily-kinesthetic, Naturalist, and Spatial intelligences whilst showing weaknesses in the Logical-mathematical, Intrapersonal, and Interpersonal intelligences as opposed to normal students who had opposite results. We arranged the program around various gaming and playing activities to engage their stronger intelligences; we added activities to address their weakness (i.e., Logical-mathematical, Intrapersonal, and Interpersonal intelligences). This study has shown that this program lowered the game immersion level of the students and was helpful in turning their attention to other activities. There were significant differences between pretest and posttest game addiction scores (p<0.001). Their weekly gaming time and computer usage decreased rapidly. Satisfaction with the game addiction therapy program based on MI was very high.

• Fire Science and Engineering
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• v.33 no.6
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• pp.35-42
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• 2019

The aim of this study is to investigate the direction of improvement of safety experience education through the analysis of the evacuation time experiment. For the study, test subjects were divided into groups of similar body size and weight. The test subjects were directly experienced four evacuation devices, and the experience time was measured. As a result of the analysis of the total time from the installation of the evacuation device to the escape, the time was measured in the order of Descending Life Line-Tilt-Down Rescue Line-Vertical Escape Chute-air safety mat. In the case of evaluating the evacuation time using evacuation mechanisms, the evacuation time was measured in the order of air safety mat-Tilt-Tilt-Down Rescue Line-Descending Life Line-Vertical Escape Chute. In the first and second experiments of the Descending Life Line, time differences were observed. The escape time using the Descending Life Line was reduced in the second experiment than in the first experiment. As shown in this result, education through experience has shown that behavioral confidence and time can be managed. The conclusion of this study is that the goal of safety education is to minimize human life and property damage. Therefore, in order to bring this effect to more people, it is necessary to make efforts to keep self-safe through experiential education.

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.83-89
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• 2020

This paper describes the effects of Novel Engineering(NE) on improvement of creative problem-solving abilities. We performed two classes for control and experience group. They are all 5th grade students. Core concept of the NE lesson is ecosystem and interaction with 8 hours long. We designed a lesson able to integrate subjects like Korean, Science and Practical Arts. Then we performed pre-and-post t-test on creative problem-solving ability. The experimental results showed that NE lesson has a high effects on 4 sub-elements like self conviction and independence, diffusion thinking, critical thinking and motivational component. The research showed that NE class is a good teaching-learning method to cultivate various competencies for our children. NE is a convergence learning model integrating various problem-solving paradigms ever researched. Thus we expect that NE is a foundation for convergence curriculum model to lead our children to their future and get settled to all schools.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.243-250
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• 2020

In this paper, we propose an effective software education scheme for universities. The key idea of this software education scheme is to analyze software curriculum of QS world university rankings Top 10, SW-oriented university, and regional main national university. And based on the results, we propose five improvements for the effective SW education method of universities. The first is to enhance the adaptability of the industry by developing courses based on the SW developer's job analysis in the curriculum development process. Second, it is necessary to strengthen the curriculum of the 4th industrial revolution core technologies(cloud computing, big data, virtual/augmented reality, Internet of things, etc.) and integrate them with various fields such as medical, bio, sensor, human, and cognitive science. Third, programming language education should be included in software convergence course after basic syntax education to implement projects in various fields. In addition, the curriculum for developing system programming developers and back-end developers should be strengthened rather than application program developers. Fourth, it offers opportunities to participate in industrial projects by reinforcing courses such as capstone design and comprehensive design, which enables product-based self-directed learning. Fifth, it is necessary to develop university-specific curriculum based on local industry by reinforcing internship or industry-academic program that can acquire skills in local industry field.

• Culinary science and hospitality research
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• v.22 no.4
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• pp.37-50
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• 2016

This study aims to examine the effect that the degree of knowledge about country-of-origin labeling on country-of-origin labeling work performance, which is a culinary staff task. This study is also intended to analyze differences in knowledge depending on hours of origin labeling education, and the moderating effect of education hours in the relationship between knowledge and performance. This study targeted culinary staff members working in ten five-star hotels in Seoul. A total of 205 self-administered questionnaires were distributed from November 14th to 27th, 2014, and 240 questionnaires(98.4%) were used for analysis after the exclusion of 4 with unreliable responses. Based on the data collected, frequency analysis, reliability test, exploratory factor analysis, simple regression analysis, t-test and moderating regression analysis were conducted using SPSS 18.0 program. The study findings are as follows. Culinary staff knowledge of origin labeling had a significantly positive effect on job performance and the degree of knowledge was higher in the group that attended one to two-hour periods of education. This suggests a differences in knowledge depending on the hours of education, which then had a moderating effect on the relationship between knowledge and performance. In conclusion, in order to improve knowledge of country-of-origin labeling and the level of performance, there is a need to increase education hours and enable culinary staff memebers to learn more knowledge and apply it to actual tasks. Based on these results, the limitation of the study and the direction of future research were also discussed.