• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.54-75
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• 2011

PoC(Push-to-talk Over Cellular) is an integrated technology of group voice calls, video calls and internet based multimedia services. If a PoC user can not participate in the PoC session for various reasons such as an emergency situation, lack of battery capacity, then the user can use the PoC Box which has a similar functionality to the MM Box in the MMS(Multimedia Messaging Service). The RTSP(Real-Time Streaming Protocol) method is recommended to be used when there is a transmission session between the PoC box and a terminal. Since the existing VOD service uses a wired network, the packet size of RTSP-based VOD service is huge, however, the PoC service has wireless communication environments which have general characteristics to be used in RTSP method. Packet loss in a wired communication environments is relatively less than that in wireless communication environment, therefore, a buffering latency occurs in PoC service due to a play-out delay which means an asynchronous play of audio & video contents. Those problems make a user to be difficult to find the information they want when the media contents are played-out. In this paper, the following techniques and methods were proposed and their performance and superiority were verified through testing: cross-over dual reception buffering technique, advance partition multi-reception buffering technique, and on-demand multi-reception buffering technique, which are designed for effective picking up of information in media content being transmitted in short amount of time using RTSP when a user searches for media, as well as for reduction in playback delay; and same-priority packetization transmission method and priority-based packetization transmission method, which are media data packetization methods for transmission. From the simulation of functional evaluation, we could find that the proposed multiple receiving buffering and packetizing methods are superior, with respect to the media retrieval inclination, to the existing single receiving buffering method by 6-9 points from the viewpoint of effectiveness and excellence. Among them, especially, on-demand multiple receiving buffering technology with same-priority packetization transmission method is able to manage the media search inclination promptly to the requests of users by showing superiority of 3-24 points above compared to other combination methods. In addition, users could find the information they want much quickly since large amount of informations are received in a focused media retrieval period within a short time.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1849-1858
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• 2021

We analyzed the monthly and annual trends of the meteorological factors(wind speeds and directions and air temperatures) measured at an automated synoptic observation system (ASOS) and fine particle (PM₁₀ and PM_2.5) concentrations measured at the air quality monitoring systems(AQMSs) in Suwon. In addition, we investigated how the fine particle concentrations were related to the meteorological factors as well as urban morphological parameters (fractions of building volume and road area). We calculated the total volume of buildings and the total area of the roads in the area of 2 km × 2 km centered at each AQMS using the geographic information system and environmental geographic information system. The analysis of the meteorological factors showed that the dominant wind directions at the ASOS were westerly and northwesterly and that the average wind speed was strong in Spring. The measured fine particle concentrations were low in Summer and early Autumn (July to September) and high in Spring and Winter. In 2020, the annual mean fine particle concentration was lowest at most AQMSs. The fine particle concentrations were negatively and weakly correlated with the measured wind speeds and air temperatures (the correlation between PM_2.5 concentrations and air temperatures was relatively strong). In Suwon city, at least for 6 AQMSs except for the RAQMS 131116 and AQMS 131118, the PM₁₀ concentrations were affected mainly by the transport from outside rather than primary emission from mobile sources or wind speed decrease caused by buildings and, in the case of PM_2.5, vise versa.

• Journal of IKEEE
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• v.25 no.1
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• pp.156-167
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• 2021

In this paper, we propose a digital transceiver unit design for in-building of 5G optical repeaters that extends the coverage of 5G mobile communication network services and connects to a stable wireless network in a building. The digital transceiver unit for driving the proposed 5G optical repeater is composed of 4 blocks: a signal processing unit, an RF transceiver unit, an optical input/output unit, and a clock generation unit. The signal processing unit plays an important role, such as a combination of a basic operation of the CPRI interface, a 4-channel antenna signal, and response to external control commands. It also transmits and receives high-quality IQ data through the JESD204B interface. CFR and DPD blocks operate to protect the power amplifier. The RF transmitter/receiver converts the RF signal received from the antenna to AD, is transmitted to the signal processing unit through the JESD204B interface, and DA converts the digital signal transmitted from the signal processing unit to the JESD204B interface and transmits the RF signal to the antenna. The optical input/output unit converts an electric signal into an optical signal and transmits it, and converts the optical signal into an electric signal and receives it. The clock generator suppresses jitter of the synchronous clock supplied from the CPRI interface of the optical input/output unit, and supplies a stable synchronous clock to the signal processing unit and the RF transceiver. Before CPRI connection, a local clock is supplied to operate in a CPRI connection ready state. XCZU9CG-2FFVC900I of Xilinx's MPSoC series was used to evaluate the accuracy of the digital transceiver unit for driving the 5G optical repeater proposed in this paper, and Vivado 2018.3 was used as the design tool. The 5G optical repeater digital transceiver unit proposed in this paper converts the 5G RF signal input to the ADC into digital and transmits it to the JIG through CPRI and outputs the downlink data signal received from the JIG through the CPRI to the DAC. And evaluated the performance. The experimental results showed that flatness, Return Loss, Channel Power, ACLR, EVM, Frequency Error, etc. exceeded the target set value.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.257-269
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• 2021

This study aimed to secure basic data for the development and operation of well-aging education programs by analyzing the physical, mental, and socio-economic needs of well-aging education for successful aging. The research tool was developed as a questionnaire to investigate the perception of well aging and the needs of well-aging education in terms of physical, mental, and socio-economic aspects. In February 2021, 1949 adults over the age of 19 were surveyed through an online and mobile survey by Gallup Korea. Descriptive statistics analysis, variance analysis, Borich needs analysis, and IPA analysis were conducted to analyze the needs of well-aging education. The results revealed economic power, exercise, and chronic disease management to be high in terms of the overall priority of the education needs for well-aging, and infectious disease management, independence, and social responsibility were surveyed in the order of low education needs. In terms of economic power, education needs were highest among all age groups except for the middle-age group (35-49 years old), 82.4% of all respondents, and education needs for exercise and chronic disease management were highest in the middle-age group. Therefore, it is necessary to develop well-aging education programs for each life cycle. These results are expected to be used as empirical data in establishing a platform for developing and operating educational programs for well aging.

• Journal of Nutrition and Health
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• v.48 no.2
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• pp.180-191
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• 2015

Purpose: There is a lack of data on the energy cost of children's everyday activities, adult values are often used as surrogates. In addition, the influence of body weight on the energy cost of activity when expressed as metabolic equivalents (METs) has not been vigorously explored. Methods: In this study 20 elementary school students 9~12 years of age completed 18 various physical activities while energy expenditure was measured continuously using a portable telemetry gas exchange system ($K_4b^2$, Cosmed, Rome, Italy). Results: The average age was 10.4 years and the average height and weight was 145.1 cm and 43.6 kg, respectively. Oxygen consumption ($VO_2$), energy expenditure and METs at the time of resting of the subjects were 5.41 mL/kg/min, 1.44 kcal/kg/h, and 1.5 METs, respectively. METs values by 18 physical activities were as follows: Homework and reading books (1.6 METs), playing game with a mobile phone or video while sitting (1.6 METs), watching TV while sitting on a comfortable chair (1.7 METs), playing video game or mobile phone game while standing (1.9 METs), sweeping a room with a broom (2.7 METs) and playing a board game (2.8 METs) belong to light intensity physical activities. By contrary, speedy walking and running were 6.6 and 6.7 METs, respectively, which belong to high intensity physical activities over 6.0 METs. When the effect of body weight on physical activity energy expenditure was determined, $R^2$ values increased with 0.116 (playing a game at sitting), 0.176 (climbing up and down stairs), 0.246 (slow walking), and 0.455 (running), which showed that higher activity intensity increased explanation power of body weight on METs value. Conclusion: This study is important for direct evaluation of energy expenditure by physical activities of children, and it could be used directly for revising and complementing the existing activity classification table to fit for children.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.31-54
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• 2007

The exchange between buyers and sellers in the industrial market is changing from short-term to long-term relationships. Long-term relationships are governed mainly by formal contracts or informal agreements, but many scholars are now asserting that controlling relationship by using formal contracts under environmental dynamism is inappropriate. In this case, partners will depend on each other's flexibility or interdependence. The former, flexibility, provides a general frame of reference, order, and standards against which to guide and assess appropriate behavior in dynamic and ambiguous situations, thus motivating the value-oriented performance goals shared between partners. It is based on social sacrifices, which can potentially minimize any opportunistic behaviors. The later, interdependence, means that each firm possesses a high level of dependence in an dynamic channel relationship. When interdependence is high in magnitude and symmetric, each firm enjoys a high level of power and the bonds between the firms should be reasonably strong. Strong shared power is likely to promote commitment because of the common interests, attention, and support found in such channel relationships. This study deals with environmental dynamism in high-tech industry. Firms in the high-tech industry regard it as a key success factor to successfully cope with environmental changes. However, due to the lack of studies dealing with environmental dynamism and supply chain commitment in the high-tech industry, it is very difficult to find effective strategies to cope with them. This paper presents the results of an empirical study on the relationship between environmental dynamism and supply chain commitment in the high-tech industry. We examined the effects of consumer, competitor, and technological dynamism on supply chain commitment. Additionally, we examined the moderating effects of flexibility and dependence of supply chains. This study was confined to the type of high-tech industry which has the characteristics of rapid technology change and short product lifecycle. Flexibility among the firms of this industry, having the characteristic of hard and fast growth, is more important here than among any other industry. Thus, a variety of environmental dynamism can affect a supply chain relationship. The industries targeted industries were electronic parts, metal product, computer, electric machine, automobile, and medical precision manufacturing industries. Data was collected as follows. During the survey, the researchers managed to obtain the list of parts suppliers of 2 companies, N and L, with an international competitiveness in the mobile phone manufacturing industry; and of the suppliers in a business relationship with S company, a semiconductor manufacturing company. They were asked to respond to the survey via telephone and e-mail. During the two month period of February-April 2006, we were able to collect data from 44 companies. The respondents were restricted to direct dealing authorities and subcontractor company (the supplier) staff with at least three months of dealing experience with a manufacture (an industrial material buyer). The measurement validation procedures included scale reliability; discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than.70. A series of exploratory factor analyses was conducted. We conducted confirmatory factor analyses to assess the validity of our measurements. A series of chi-square difference tests were conducted so that the discriminant validity could be ensured. For each pair, we estimated two models-an unconstrained model and a constrained model-and compared the two model fits. All these tests supported discriminant validity. Also, all items loaded significantly on their respective constructs, providing support for convergent validity. We then examined composite reliability and average variance extracted (AVE). The composite reliability of each construct was greater than.70. The AVE of each construct was greater than.50. According to the multiple regression analysis, customer dynamism had a negative effect and competitor dynamism had a positive effect on a supplier's commitment. In addition, flexibility and dependence had significant moderating effects on customer and competitor dynamism. On the other hand, all hypotheses about technological dynamism had no significant effects on commitment. In other words, technological dynamism had no direct effect on supplier's commitment and was not moderated by the flexibility and dependence of the supply chain. This study makes its contribution in the point of view that this is a rare study on environmental dynamism and supply chain commitment in the field of high-tech industry. Especially, this study verified the effects of three sectors of environmental dynamism on supplier's commitment. Also, it empirically tested how the effects were moderated by flexibility and dependence. The results showed that flexibility and interdependence had a role to strengthen supplier's commitment under environmental dynamism in high-tech industry. Thus relationship managers in high-tech industry should make supply chain relationship flexible and interdependent. The limitations of the study are as follows; First, about the research setting, the study was conducted with high-tech industry, in which the direction of the change in the power balance of supply chain dyads is usually determined by manufacturers. So we have a difficulty with generalization. We need to control the power structure between partners in a future study. Secondly, about flexibility, we treated it throughout the paper as positive, but it can also be negative, i.e. violating an agreement or moving, but in the wrong direction, etc. Therefore we need to investigate the multi-dimensionality of flexibility in future research.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Korea Science and Art Forum
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• v.32
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• pp.319-334
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• 2018

This research is a case study to make sure the enhancement of students' imagination and creativity through developing and applying the Literature-Art-Science Integrated Education Program. Its research object was totally 25 persons of 29 students of the 1st to the 4 th Grades from Gunsan Sulsan Elementary School. Its research period lasted for 4 months from September to December, 2017, and I, as the research place, used the art room at Gunsan Sulsan Elementary School. The programs were totally 10 sessions with a unit of 1 session per each grade for 2 hours from 1:00 to 3:00 in the afternoon from Monday through Friday. I fixed ten themes of this program-eight plane modeling, and two solid modeling, and finished the work of storytelling during summer vacation. And I arranged their levels as low:middle:high(3:5:2) ones. The former was 'A Film of Monster Gorilla'(L), 'Learning the Spirit of Gyeongju Choi's Family'(M), 'A Tale of My Friend Made of Natural Materials'(L), 'The Reading of My Dream'(M), 'Gathering the Objects in My Mobile'(M), 'A Mock Trial of Marrying Off'(M), 'Painting My Favorite Children's Poem'(H), and 'Painting My Favorite Children's Song'(H), and the latter was 'Seeking for a Bluebird in My Mind'(L), and 'Making My Cherished Object' (M). Then I used the unique art expression technique per each theme, which were in sequence marbling, Korean paper art, combine painting, collage, imaginary painting, imaginary painting, play dough art, imaginary painting techniques. And I delivered to the students the scientific knowledge in terms of growing or manufacturing processes of materials used for making artworks. Prior to and after the processing this program, I surveyed about the students' ability of integrated thinking and emotional experience by 'Figure B Type' and 'Figure A Type' of The Torrance Tests of Creative Thinking, and took statistics with the resultant data. And I executed a paired t-test in order to verify the significance of mean difference in the result of investigation with those data. From the analyzed result according to the elements of creativity and the mean quotients of creativity, there showed a significant difference (t=3.47, p<.01) in 'fluency', and also a significant difference(t=3.59, p<.01) in 'creativity.' Judging from the statistic values of two fields such as the student's ability of integrated thinking and emotional experience, I estimate that over the majority of the students showed the enhancement in self-confident creative expression as well as higher interest and concern through this program. The result that I arranged and analyzed the making process of artworks, the photos of the resultant, etc. as such is as follows : Firstly, from this program being proceeded as art-centered STEAM class, the student's systematic problem-solving ability was improved in his ability of integrated thinking to transform the literary contents into artistic one. Secondly, the student obtained the emotional experience such as interest in the class, self-confidence, intellectual satisfaction, self-fulfillment, etc. through art-centered STEAM class using ten art expression techniques. Thirdly, the student's mind willing to cooperate, communicate with his friends, and care for them was ripened in the process of problem-solving. Fourth, the student's self-confidence was further instilled when presenting famous artists and their artworks in the introduction and finale of ten art expression techniques. Likewise, the statistic values on the fields of student's ability of integrated thinking and emotional experience illustrate that over the majority of the students showed improvement in the ability of creative expression with confidence as well as higher interest and concern upon this program.