• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Knowledge Management Research
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• v.23 no.4
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• pp.91-112
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• 2022

In order to improve the quality of consumption in senior generation, it is necessary to build trust in the digital consumption environment. However, there are limitations from previous researches on consumption in the digital environment that has mainly focused on Millennial and Z generations. Therefore, this study aims to examine the antecedents of digital consumption trust and to explore the market segments of senior generation created by the dynamics of these antecedents. In addition, in order to provide practical implications, we investigate the difference in the level of perceived digital consumption trust using segmentation. This study, therefore, used 2021 Korea's consumer life index data conducted by the Korea Consumer Agency for general consumers, and only consumer data of 60s and older are extracted for the analysis. As a result, we confirm from the main results that the three antecedents, consumer competency, perceived corporate responsibility, and local community's problem-solving environment, are significant in building the digital consumption trust in the senior generation. It is academically significant in this aspect to look at approaches to improve senior customers' trust in digital consumption circumstances by dividing generations because generations exhibit varying levels of understanding of online consumption or digital consumption conditions. It is academically significant in this aspect to look at approaches to improve senior customers' trust in digital consumption circumstances by dividing generations because generations exhibit varying levels of understanding of online consumption or digital consumption conditions. Additionally, it is proposed as a practical implication that it should be managed so that significant improvements of customers, businesses, and regional public institutions are developed in order to allow the senior consumers to prepare trusted digital consumption circumstances.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Korea journal of population studies
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• v.23 no.2
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• pp.79-112
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• 2000

This study was focused on the contrasting pattern of part-time employment between Japan and Taiwan where the environments are similar in terms of expanding service industries and increasing flexibility of labor. In Japan, the expansion of part-time employment and its feminization have occurred, whereas they have not at all in Taiwan. The purpose of this study was to examine the reasons behind this phenomena, and to explore what relations they might have with the supply of women\`s labor in each country. Data analysis showed the following results. First, when the phenomena of part-time employment in Japan and Taiwan are summarized as \`active\` and \`inactive\` models, the difference could be explained by a structure-oriented approach rather than an individual-oriented approach. In other words, the difference between the two countries is mainly because of the structural characteristics of the labor market. a combination of capitalism and patriarchy, and an effect of state welfare and family policies rather than a \`voluntaristic choice\` due tn household work and child rearing. In light of this. the labor market segmentation and flexibility of labor theory in particular provided a useful frame for explanation. Second, with regard to the supply of women\`s labor, the difference between Japan and Taiwan could be found in the structure of the labor market and in family response strategies. The large corporation-oriented and strictly divided labor market structure in Japan activated part-time employment and its feminization, whereas, the small family-oriented businesses and less divided labor market in Taiwan supported the continuity of full-time employment of married women. There was also a room for informal employment in Taiwan which made part-time employment unnecessary. This study showed that even within similar environments of expanding service industry and pursuing flexibility of labor different measures and adaptations were possible. The case of Taiwan in particular, showed the significance of an informal labor market which was a part of industrialization process and a strategy of producing various products through a subcontracting network.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.6
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• pp.894-902
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• 2016

The purpose of this study was to analyze the attributes considered as important by parents in the selection of laver for infants through conjoint analysis techniques. A total of 917 questionnaires were distributed in January 2016, of which 211 were completed (23.0%). Statistical data analyses were performed using SPSS/Win 21.0 for descriptive statistics and conjoint analysis. The conjoint design was applied to evaluate the hypothetical laver for infants. According to the analysis of attributes and levels of laver for infants, the relative importance of each attribute was follows: seasoning (26.55%), flavor (19.33%), texture (18.75%), oil (15.15%), size (10.61%), and certification (9.61%). The results of the conjoint analysis indicate that parents raising infants preferred laver with the characteristics of non-seasoning, general flavor, softness, half-size, organic certification, and perilla oil. The most preferred laver for infants gained a 53.7% potential market share from choice simulation compared with laver being sold. Using utility and relative importance, the laver market for infants was classified into two segments. As a result of market segmentation, parents of cluster 1 preferred the laver model being sold (soy seasoning) while parents of cluster 2 preferred the optimized laver model (non-seasoning).

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.377-391
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• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.1
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• pp.133-146
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• 2012

University dining services have received less attention than commercial food services or other institutional food services. Marketing practitioners and researchers recognize the major impact that perceived value has on consumer behavior. The mediating role of value has not been verified in relation to satisfaction in university dining establishments, including Korea. This study intends to investigate the relationships among value, satisfaction and revisit intention of university dining attributes. This study also examines whether university dining service attributes dimensions influence value. Further, this study verifies the role of value as a mediator in the formation of customer satisfaction and revisit intention. Structural Equation Modeling has been applied to the collected data from students of three universities in Korea. The study resulted in that university dining attributes, such as food, menu and convenience, positively affected value of the university dining services. Further analysis with examination of indirect effects confirmed the positive impact of value on satisfaction in university dining services. This study verified the mediating role of value on satisfaction as student's satisfaction is enhanced through the elevation of value of university food services. Enhanced satisfaction via value also led to improvement in revisit intention. This study contributes to the academia by verifying the mediating role of value in the formation of customer satisfaction in a university dining context. This study also offers practical implications to the industry, such as suggestions on developing strategies for value-added products and services to the university dining establishments. This value research for university dining services is also meaningful by triggering future research on market segmentation, product differentiation and positioning policies. In the long run, improving value and satisfaction with university dining services need to be realized to enhance overall college experiences and other competitive advantages, such as student recruitment and enrollment, student academic evaluations, and university reputation.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.431-438
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• 2020

In this paper, the method to extract lip contour by multiple threshold is proposed. Spyridonos et. el. proposed a method to extract lip contour. First step is get Q image from transform of RGB into YIQ. Second step is to find lip corner points by change point detection and split Q image into upper and lower part by corner points. The candidate lip contour can be obtained by apply threshold to Q image. From the candidate contour, feature variance is calculated and the contour with maximum variance is adopted as final contour. The feature variance 'D' is based on the absolute difference near the contour points. The conventional method has 3 problems. The first one is related to lip corner point. Calculation of variance depends on much skin pixels and therefore the accuracy decreases and have effect on the split for Q image. Second, there is no analysis for color systems except YIQ. YIQ is a good however, other color systems such as HVS, CIELUV, YCrCb would be considered. Final problem is related to selection of optimal contour. In selection process, they used maximum of average feature variance for the pixels near the contour points. The maximum of variance causes reduction of extracted contour compared to ground contours. To solve the first problem, the proposed method excludes some of skin pixels and got 30% performance increase. For the second problem, HSV, CIELUV, YCrCb coordinate systems are tested and found there is no relation between the conventional method and dependency to color systems. For the final problem, maximum of total sum for the feature variance is adopted rather than the maximum of average feature variance and got 46% performance increase. By combine all the solutions, the proposed method gives 2 times in accuracy and stability than conventional method.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.257-267
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• 2023

Purpose. The purpose of the study was to fabricate a prototype robotic simulator for dental education, to test whether it could simulate mandibular movements, and to assess the possibility of the stimulator responding to stimuli during dental practice. Materials and methods. A virtual simulator model was developed based on segmentation of the hard tissues using cone-beam computed tomography (CBCT) data. The simulator frame was 3D printed using polylactic acid (PLA) material, and dentiforms and silicone face skin were also inserted. Servo actuators were used to control the movements of the simulator, and the simulator's response to dental stimuli was created by pressure and water level sensors. A water level test was performed to determine the specific threshold of the water level sensor. The mandibular movements and mandibular range of motion of the simulator were tested through computer simulation and the actual model. Results. The prototype robotic simulator consisted of an operational unit, an upper body with an electric device, a head with a temporomandibular joint (TMJ) and dentiforms. The TMJ of the simulator was capable of driving two degrees of freedom, implementing rotational and translational movements. In the water level test, the specific threshold of the water level sensor was 10.35 ml. The mandibular range of motion of the simulator was 50 mm in both computer simulation and the actual model. Conclusion. Although further advancements are still required to improve its efficiency and stability, the upper-body prototype simulator has the potential to be useful in dental practice education.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.