• The Journal of the Korea institute of electronic communication sciences
• /
• 제10권6호
• /
• pp.677-682
• /
• 2015

The mnemonic-system in numbers is helped you to remember numbers. In this mnemonic-system, a graph or image is a rather neat mnemonic. In graph-based systems, there are many ways such as dot, line, bar, and etc to represent a mnemonic system. Mnemonics aim to translate information into a form that the brain can retain better than its original form. This is the same in the mnemonic-system in numbers. Alternative methods in mnemonic-system for numbers are a image. In this paper, we suggest a simple graph algorithm and arranged image algorithm for the mnemonic-system in numbers, and show comparative results based on the retention of the mnemonic system about two methods.

• The Journal of the Korea institute of electronic communication sciences
• /
• 제12권3호
• /
• pp.471-476
• /
• 2017

It is very useful to use the mnemonic-system to remember numbers easily. In the mnemonic-system associated with these numbers, the utilization of the corresponding images helps to identify numbers easily. In previous studies related to mnemonic-system, we suggested a method that gave the automatic array function that resulted in a simplified array algorithm and an array of image algorithms arranged in relation to the array of images. This methodology has found that the user has a long way to take the time to familiarize themselves with the image and the number of responses. In this study, we suggest dividing the numbers based on the size and color of the scale, based on the size of the images determined to improve these shortcomings.

• Journal of The Korean Association For Science Education
• /
• 제38권5호
• /
• pp.753-763
• /
• 2018

The image of scientists that learners have has an important impact on science learning and on science-related career choices. The image of the scientist was mainly analyzed using the drawing analysis method. Drawing analysis has limitations on drawing, mainly analyzing the external image of scientist. Science teachers' images of scientists and their perception of science-related careers are important factors in students' science learning and science-related career choices. However, research on science teachers is lacking. Therefore, the purpose of this study is to investigate the usefulness of measurement tools by developing and applying a scientist image measurement tool through the semantic analysis method, and to discuss the educational implications of the research by investigating the image of scientists and science-related professions of secondary pre-service science teachers. The subjects of the study were 79 male and 55 female for a total of 134 students in the 2nd and 3rd grades majoring in science education at a teachers college. The results of the research show that the image measurement tool consisted of four components: 'ability,' 'evaluation,' 'activity,' and 'emotion,' in 24 items. As a result of applying the developed measurement tool to the secondary pre-service science teachers, the image of the 'evaluation,' 'ability,' and 'activity' elements of the scientist were high, but 'emotion' was low. There was no statistically significant difference according to gender. It is found that science-related career perceive them as 'hard,' 'professional,' 'smart,' and 'complex.' In particular, male students perceive themselves as 'hard and difficult' while female students perceive it as 'challenging and complicated'. Finally, we discussed the usefulness of using the image measurement tool of the scientists, the image of the scientists of the secondary pre-service science teachers, and the educational implications on science-related career.

• Science of Emotion and Sensibility
• /
• 제15권1호
• /
• pp.87-96
• /
• 2012

This paper proposes a Image retrieval system that searches the closest images to the user's emotional need and displays images with higher ratings of color harmony from Moon-Spencer's Color Harmony Theory first. Once an emotional adjective is placed, the system searches for images with colors that contain more elements derived from Aesthetic Measure results and displays in such order. In order to test reliability of the proposed emotion retrieval method based on Moon-Spencer's Color Harmony Theory, this study compared the order of Aesthetic Measure results with the user satisfaction ratings using 200 sample images. The analysis demonstrated that the participants' average satisfaction on 15 emotion adjectives selected for the study was 5.0 on a 7-point Likert scale. Correlation analyses were performed to test the consistency the orders between Aesthetic Measure values and user satisfaction ratings. Positive correlations above R=.5 were observed in all 14 emotion words except "Clear". These findings prove the potential of the proposed emotion retrieval system based on Moon-Spencer's Color Harmony Theory to effectively reflect user emotion in such visual stimulus search as image database.

• Journal of The Korean Association of Information Education
• /
• 제21권5호
• /
• pp.527-535
• /
• 2017

In this study, we analyzed the image of artificial intelligence recognized by elementary students using semantic differential scale. First, we extracted 23 pairs of image adjectives related to perception of artificial intelligence. Adjectives were classified into three types related to recognition, emotion and ability and 827 elementary students were examined. Image factors were classified into four factors: convenience, technological progress, human-friendliness, and concern. As a result, they showed a clear image that artificial intelligence is clever, new, and complex but exciting. In comparison with variables, female students, coding experience and older students thought that artificial intelligence was more human-friendly and technological progressive.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 한국컴퓨터정보학회 2018년도 제57차 동계학술대회논문집 26권1호
• /
• pp.183-184
• /
• 2018

기억법은 수치와 같은 어려운 정보를 기억하기 쉽도록 제안한 방법을 의미한다. 동영상 정보에 익숙해져 있는 세대에서도 수치정보를 기억하기는 매우 어렵다. 이에 관련 전문가들이 제안한 기억법을 익혀 적용해보면 기억률 향상의 결과를 확인할 수 있다. 본 연구에서는 수치 정보에 대해 이미지 정보와 매치하여 기억률 향상에 도움을 주는 구조를 제안하고자 한다. 이전 연구에서 모바일 환경에 적합한 앱을 개발하여 수치에 해당되는 이미지를 보여주는 형태를 제안하였다. 본 연구에서는 핸드폰 번호를 기준으로 앞 4자리와 뒤 4자리를 분리하여 적용한 방법을 설계한다. 비슷한 패턴의 이미지가 연속적으로 일정 숫자 이상 이어지는것 보다 다른 패턴으로 분리하여 제시함으로써 더 높은 기억률의 결과를 예상할 수 있다.

• Journal of Korea Entertainment Industry Association
• /
• 제14권7호
• /
• pp.429-437
• /
• 2020

This study is aimed at exploring the current state, necessity and activation of curriculum related to image making program in domestic colleges. To achieve this, an empirical survey was carried out to college students to provide basic data for the development of image making education program in the college curriculum as a measure to guide job interviews with them and improve interpersonal skills of employees-to-be. To achieve this, a survey was carried out to 400 college students in Gwangju and Jeonnam areas. The analysis was conducted to verify the collected data using SPSS v. 21.0 through the process of data coding and data cleaning. The results are as follows. First, the necessity of image making program curriculum showed that they needed the image making program in the college curriculum, the image making program curriculum to get a job and manage an image of employees-to-be after graduation, and other people's help to figure out the images objectively. Second, the educational importance of image making program showed that attitude (behavior) was the highest, followed by manners & greeting, look, speech, relationship, clothes, hairstyle, and makeup. In terms of the important educational factors of image making program, look was the highest, followed by makeup, hairstyle, attitude (behavior), relationship, speech, clothes, and manners & greeting, which look was the most important. Third, the educational influence of image making program showed that the influence on employment was the highest, followed by the influence on relationship, and the influence on life. Fourth, the educational activation of image making program showed that the appropriate educational time for image making program they want was from the second year. Education hours they want were once a week for one semester. And the curriculum they want was liberal arts or an optional course of liberal arts. In terms of image making program-related curriculum contents, manner & greeting was the highest, followed by makeup & coordination, job fair, education to acquire a skill qualification, and training for domestic companies, which their biggest wish was manner & greeting. And image making program leaders they want were major professors. In terms of image making program-related education, speech or voice was the highest, followed by education to analyze communication, education to analyze and practice matching hairstyles and makeup, Education on corporate interviews, and education on walking or posture correction, which their biggest wish was speech or voice and education to analyze communication.

• Journal of Information Management
• /
• 제40권2호
• /
• pp.71-94
• /
• 2009

Indexing images using traditional indexing methods like taxonomy is not always efficient because of its visual content. This study examined how to apply folksonomies to image retrieval. To do this, first, we developed a category model for image tags found in Flickr. The model includes five categories and seventeen subcategories. Second, in order to evaluate the usefulness of the model to represent the various image tags as well as to investigate the end-user tagging behavior, three researchers classified the sampled image tags(141 most popular tags, 105 tags on three individual tag clouds and 3,848 image tags assigned on 156 images) according to the model. Finally, based on the research results, we proposed three methods for efficient image retrieval: extending folksonomies by combining them with ontologies; improving image retrieval efficiency using visual content and folksonomies; and updating taxonomy using folksonomies.

• Science of Emotion and Sensibility
• /
• 제7권3호
• /
• pp.1-6
• /
• 2004

The algorithm developed in this paper allows us to generate or synthesize a large amount of data sets using only a small amount of signal features obtained from the original data set. Because the simulated density profiles of yarns retain the original features without a significant loss of information on the location of imperfections, the resulting fabric images are likely to resemble the original images. The data expansion system developed could generate a large area of fabric images by combining the Monte Carlo simulation and the wavelet sub-band exchange algorithm developed. The system has proven effective for simulating realistic fabric images by retaining the location of imperfections such as neps, thin and thick places.

• Journal of KIISE:Databases
• /
• 제36권5호
• /
• pp.366-373
• /
• 2009

In this paper, we propose a similarity search algorithm for image databases. One of the central problems regarding content-based image retrieval (CBIR) is the semantic gap between the low-level features computed automatically from images and the human interpretation of image content. Many search algorithms used in CBIR have used the Minkowski metric (or $L_p$-norm) to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information. Our new search algorithm tackles this problem by employing new similarity measures and ranking strategies that reflect the nonlinearity of human perception and contextual information. Our search algorithm yields superior experimental results on a real handwritten digit image database and demonstrates its effectiveness.