• Journal of Korean Dental Hygiene Science
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• v.6 no.1
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• pp.37-50
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• 2023

Background: This study investigated the structural relationships among justice, test anxiety, and school reliability s non-face-to-face tests of dental hygiene students. Methods: A survey was conducted with 267 dental hygiene students. The survey items included general characteristics, opinions on evaluation, the fairness of non-face-to-face tests (distributive, procedural, and interactional justice), school satisfaction, and school reliability. For statistical analysis, independent-sample t-tests, one-way ANOVA, and structural modeling analyses were performed. Results: Among factors that directly affected distributive justice and reliability towards non-face-to-face tests, the higher the interactional justice (β=0.401, p<0.001) and distributive justice (β=0.232, p=0.002) levels, the higher the school satisfaction. The higher the school satisfaction (β=0.606, p<0.001) and procedural justice (β=0.299, p<0.001) levels, the higher the perceived reliability of the school. Factors that indirectly affected school reliability included interactional justice (β=0.243, p=0.010) and distributive justice (β=0.141, p=0.010). Interactional justice (β=0.592, p=0.010) and distributive justice (β=0.208, p=0.010) were the factors affecting school satisfaction. Moreover, factors that influenced school reliability were distributive justice (β=0.56, p=0.010), interactional justice (β=0.332, p=0.010), procedural justice (β=0.229, p=0.010), and distributive justice (β=0.116, p=0.010). Conclusions: Students will trust and be satisfied with schools when schools and professors sufficiently provide information on face-to-face tests and ensure proper procedures to achieve reasonable grades as rewards for exerted time and effort. Furthermore, this study provides a reference base for developing a variety of content for fair, non-face-to-face tests, thereby allowing students to trust their schools.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.48-62
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• 2023

As seen in the recent K-pop craze, the size and influence of the Korean music industry is growing even bigger. At least 6,000 songs are released a year in the Korean music market, but not many can be said to have been successful. Many studies and attempts are being made to identify the factors that make the hit music. Commercial factors such as media exposure and promotion as well as the quality of music play an important role in the commercial success of music. Recently, there have been many marketing campaigns using Internet memes in the pop music industry, and Internet memes are activities or trends that spread in various forms, such as images and videos, as cultural units that spread among people. Depending on the Internet environment and the characteristics of digital communication, contents are expanded and reproduced in the form of various memes, which causes a greater response to consumers. Previously, the phenomenon of Internet memes has occurred naturally, but artists who are aware of the marketing effects have recently used it as an element of marketing. In this paper, the mediated effect of Internet memes in relation to the success factors of popular music was analyzed, and a prediction model reflecting them was proposed. As a result of the analysis, the factors with the mediated effect of 'cover effect' and 'challenge effect' were the same. Among the internal success factors, there were mediated effects in "Singer Recognition," the genres of "POP, Dance, Ballad, Trot and Electronica," and among the external success factors, mediated effects in "Planning Company Capacity," "The Number of Music Broadcasting Programs," and "The Number of News Articles." Predictive models reflecting cover effects and challenge effects showed F1-score at 0.6889 and 0.7692, respectively. This study is meaningful in that it has collected and analyzed actual chart data and presented commercial directions that can be used in practice, and found that there are many success factors of popular music and the mediating effects of Internet memes.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.

• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.