• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.99-118
• /
• 2015

Object-oriented programming languages have been widely selected for developing modern information systems. The use of concepts relating to object-oriented (OO, in short) programming has reduced efforts of reusing pre-existing codes, and the OO concepts have been proved to be a useful in interpreting system requirements. In line with this, we have witnessed that a modern conceptual modeling approach supports features of object-oriented programming. Unified Modeling Language or UML becomes one of de-facto standards for information system designers since the language provides a set of visual diagrams, comprehensive frameworks and flexible expressions. In a modeling process, UML users need to consider relationships between classes. Based on an explicit and clear representation of classes, the conceptual model from UML garners necessarily attributes and methods for guiding software engineers. Especially, identifying an association between a class of part and a class of whole is included in the standard grammar of UML. The representation of part-whole relationship is natural in a real world domain since many physical objects are perceived as part-whole relationship. In addition, even abstract concepts such as roles are easily identified by part-whole perception. It seems that a representation of part-whole in UML is reasonable and useful. However, it should be admitted that the use of UML is limited due to the lack of practical guidelines on how to identify a part-whole relationship and how to classify it into an aggregate- or a composite-association. Research efforts on developing the procedure knowledge is meaningful and timely in that misleading perception to part-whole relationship is hard to be filtered out in an initial conceptual modeling thus resulting in deterioration of system usability. The current method on identifying and classifying part-whole relationships is mainly counting on linguistic expression. This simple approach is rooted in the idea that a phrase of representing has-a constructs a par-whole perception between objects. If the relationship is strong, the association is classified as a composite association of part-whole relationship. In other cases, the relationship is an aggregate association. Admittedly, linguistic expressions contain clues for part-whole relationships; therefore, the approach is reasonable and cost-effective in general. Nevertheless, it does not cover concerns on accuracy and theoretical legitimacy. Research efforts on developing guidelines for part-whole identification and classification has not been accumulated sufficient achievements to solve this issue. The purpose of this study is to provide step-by-step guidelines for identifying and classifying part-whole relationships in the context of UML use. Based on the theoretical work on Meta-model Formalization, self-check forms that help conceptual modelers work on part-whole classes are developed. To evaluate the performance of suggested idea, an experiment approach was adopted. The findings show that UML users obtain better results with the guidelines based on Meta-model Formalization compared to a natural language classification scheme conventionally recommended by UML theorists. This study contributed to the stream of research effort about part-whole relationships by extending applicability of Meta-model Formalization. Compared to traditional approaches that target to establish criterion for evaluating a result of conceptual modeling, this study expands the scope to a process of modeling. Traditional theories on evaluation of part-whole relationship in the context of conceptual modeling aim to rule out incomplete or wrong representations. It is posed that qualification is still important; but, the lack of consideration on providing a practical alternative may reduce appropriateness of posterior inspection for modelers who want to reduce errors or misperceptions about part-whole identification and classification. The findings of this study can be further developed by introducing more comprehensive variables and real-world settings. In addition, it is highly recommended to replicate and extend the suggested idea of utilizing Meta-model formalization by creating different alternative forms of guidelines including plugins for integrated development environments.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.4
• /
• pp.853-860
• /
• 2007

In this modern era, human beings lead their life in complex environment where there are lots of parameters such as temperature, light, smell, sound, visual stimulus etc. that play important role for quality life. These parameters affect physical and mental behavior of a human being immensely. To ensure quality life the demand for quality products is always associated with human emotion and sensibility. Due to human sensibility and emotion involvement with quality life, the design stages of any kind of product must include some certain features related with emotion and sensibility. The cues for optimizing artificial environment are the physiological responses of human in that environment. The conventional approach of environmental physiology is to measure the relationship between environmental physical parameters and human psychological parameters under artificial conditions. Using that approach we tried to design an artificial environment for our daily lives and activities associated with both physiological and psychological behavior. We developed the technique to present the mock environment and software to measure and evaluate sensibility physiologically or psychologically and a simulator to measure and evaluate sensibility that can be utilized for large scale industrial production and design of environment. Simulator to measure and analyze human sensibility (SMAS) was constructed, which was utilized to estimate human sensibility and to simulate living and office environment.

• Korean Journal of Heritage: History & Science
• /
• v.53 no.2
• /
• pp.254-269
• /
• 2020

The purpose of this study is to propose guidance for wall renewal that is appropriate for an ancient city wall through application of advanced research and theories in wall design. It is a streetscape improvement project which forms part of the "Ancient City Image Finding Project". Study methods consist of advanced research classification, wall design theory contemplation, and analysis of the significance of designated ancient city areas and the "Ancient City Image Finding Project" status. Based on these methods, case study candidates were selected, case status and problems were identified, and improvement proposals were analyzed by comparing various features. Advanced wall research was classified into six categories including analysis of wall characteristics; wall design principle applications; wall structure, color, shape, and application; modern reinterpretation; palace walls; and house, temple, and village walls. The wall is an element of the streetscape improvement component of the "Ancient City Image Finding Project", with the characteristic of providing preceding experience in visual and cognitive awareness than interior structure. Case candidates for ancient city wall improvement are based on the composition distribution of the special conservation district in each ancient city as well as the conservation promotion district. Ultimately, the surrounding village of Gongju-si Geumseong-Dong Songsanri-gil, adjacent to the Royal Tomb of King Muryeong, was selected as the candidate. The "Ancient City Image Finding Project" of the surrounding village of Gongju-si Geumseong-Dong Songsanri-gil began with new Hanok construction. However, wall maintenance did not begin concurrently with that new Hanok construction. Support and maintenance took place afterwards as an exterior maintenance project for roadside structures. If the Hanok and wall were evaluated and constructed at the same time, the wall would have been built in unison with the size and design of the Hanok. The layout of the main building and wall of the Hanok is deemed to be a structure that is closed tightly because of its spatial proximity and tall height. Songsan-ri-gil's wall design should create a calm, subtle, and peaceful atmosphere with shapes, colors, and materials that express ancient city characteristics, but it is in an awkward position due to its sharpness and narrowness. The cause of the problem at Gongju-si Geumseong-dong Songsanri-gil, the case candidate, is that it is lacking significantly in terms of the aesthetic factors that traditional walls should possess. First, aesthetic consciousness seems to have disappeared during the selection and application process of the wall's natural materials. Second, the level of completion in design and harmony is absent. Maintenance guidance after analyzing the cause of problems in ancient city wall maintenance at Gongju-si Geumseong-dong Songsanri-gil, the subject area of research, is as follows: First, the Hanok design and layout of the wall and main gate should be reviewed simultaneously. Second, the one-sided use of natural stone wall in the Hanok wall design should be reexamined. Third, a permanent system to coordinate the opinions of citizens and experts during the planning and design phases should be employed. Fourth and finally, the Hanok's individuality shall be collectivized and its value as a cultural asset representing the identity of the community shall be increased.

• The Journal of Art Theory & Practice
• /
• no.8
• /
• pp.33-58
• /
• 2009

This paper examines four genre paintings on the subject of child education by Jean-Baptiste-Sim${\'{e}}$on Chardin(1699-1779). The Governess, The Diligent Mother, Saying Grace, and The Morning Toilette garnered critical attention after they were exhibited in the Salon from 1739 to 1741. After the exhibition, the paintings were made into prints and frequently sold to members of the bourgeois class in Paris. The iconographical details of Chardin's genre paintings have, thus far, been compared to Dutch genre pictures of the seventeenth century. Further, most studies conducted on Chardin's paintings focus on formal analysis rather than the historical and social contexts. Through attempting social-contextual readings of Chardin's educational series, this paper argues that the significance of Chardin's painting series of child education lies in his representation of the ideal French bourgeois family and the standard of early childhood education in the eighteenth-century French Enlightenment period. In each of the four child education paintings, Chardin depicted a mother with children in a domestic space. Even though this theme derives from traditional Dutch genre paintings in the seventeenth century, the visual motifs, the pictorial atmosphere and the painting techniques of Chardin all project the social culture of eighteenth century France. Each painting in the child education series exemplifies respectively the attire of a French gentlemen, the social view on womanhood and the education of girls, newly established table manners, and the dressing up culture in a 'toilette' in eighteenth century France. Distinct from other educational scenes in previous genre paintings, Chardin accentuated the naive and innocent characteristics of a child and exemplified the mother's warmth toward that child in her tender facial expressions and gesturing. These kinds of expressions illustrate the newly structured standard of education in the French Enlightenment period. Whereas medieval people viewed children as immature and useless, people in the eighteenth century began to recognize children for their more positive features. They compared children to a blank piece of paper (tabula rasa), which signified children's innocence, and suggested that children possess neither good nor bad virtues. This positive perspective on children slowly transformed the pedagogical methods. Teaching manuals instructed governesses and mothers to respect each child's personality rather than be strict and harsh to them. Children were also allotted more playtimes, which explains the display of various toys in the backgrounds of Chardin's series of four paintings. Concurrently, the interior, where this exemplary education was executed, alludes to the virtue of the bourgeois's moderate and thrifty daily life in eighteenth century France. While other contemporary painters preferred to depict the extravagant living space of a French bourgeoisie, Chardin portrayed a rather modest and cozy home interior. In contrast to the highly decorated living space of aristocrats, he presented the realistic, humble domestic space of a bourgeois, filled with modern household objects. In addition, the mother is exceptionally clad in working clothes instead of fashionable dresses of the moment. Fit to take care of household affairs and children, the mother represents the ideal virtues of a bourgeois family. It can be concluded that the four genre paintings of child education by Chardin articulate the new standards of juvenile education in eighteenth century France as well as the highly recognized social virtues between French bourgeois families. Thus, Chardin's series of child education would have functioned as a demonstration of the ideal living standards of the bourgeois class and their emphasis on early childhood education in the French Enlightenment period.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.29 no.4
• /
• pp.27-39
• /
• 2011

The study on Musan twelve peaks of Yongho garden in Jinju, Gyeongnam was anticipated to provide data and implication for reproducing similar spaces and modern changes in terms of design factor since it is the prototype of traditional mount for overcoming monotonous geographical features and intriguing changes and interests. The study analyzed and interpreted the symbolism of twelve peaks, principles of space composition and function and effect of visual construction that were pursued by the builder in terms of landscape view, which results are as following. The center of Yongho garden, Yonghoji(龍虎池) is a typical man-made pond for a supportive feng shui feature. It is a supporting equipment to complete the state of feng shui, and the result of strengthening the completion through the connection with the dragon-related name of the place. The shape of Musan twelve peaks looks like an oval form of Geumseongsan(金星山), 2~3.5m in height and 6~12m in diameter. Peaks are estimated as 1.5~3.7m(2.4m in average) in height, $35{\sim}138m^2$($73.4m^2$ in average) in area, and $30.7{\sim}115.0m^3$($62.5m^3$ in average) in volume. Given that Yonghojeong(龍虎亭), Soseon(小船), the site of main building and Yongsanjae(龍山齋) stand in line, Yonghoji was presumed as the state of enlightenment through ascribing the meaning to virtue and secularity. For the intention of realizing Musan twelve peaks, the builder probably had mounted twelve peaks forming the body of dragons with crossing the point corresponding to a head of tiger, and located Musan twelve peaks and Yonghojeong with a representation of dragons holding Cintamani rising into the sky in the center. The middle area near Musan twelve peaks surrounded by peaks like Geumseongsan running north and south shows a multi-structure of multilayer, maintaining the similarity centering on Yonghoji. It is considered the intention of mount planned at the time of Musan twelve peaks construction, caused by similar form harmony. Internalization of progressive realization through concealment and exposure, enframement effect and spatial order like prospect-refuge theory in the mount of Musan twelve peaks is considered the reflection of the intention to increase depth of the view and expectancy through the various degree of exposure and surroundings of each peak and the colorful combination of viewing and shutting. The "closed view" by Musan twelve peaks creates interesting, vivid and attractive recognition of the view, which is more effective in bringing depth of the view and interests in terms of the geographical design, particularly the area around Yonghoji. Moreover, it was identified that the combination of peaks can be formed resulted from the view configuration concerning the location through multilayer effect reveals an island through the other one when viewed from Yonghojeong.

• Journal of the Korean Orthopaedic Association
• /
• v.54 no.5
• /
• pp.418-426
• /
• 2019

Purpose: This study analyzed the features of humeral head decentralization in large to massive rotator cuff tears with a shoulder dislocation in the elderly. Moreover, shoulder instability and treatment were reviewed. Materials and Methods: From May 2005 to February 2017, Group A containing 45 cases (45 patients) over 65 years old accompanied by a large or massive rotator cuff tear with a shoulder dislocation and Group B containing 45 cases (45 patients) without a shoulder dislocation were enrolled. The mean ages in Groups A and B were 73.2 and 72.1 years old, and the mean follow-up periods were 30.7 and 31.3 months, respectively. Twenty-one cases (46.7%) in Group A underwent rotator cuff repair, and 8 cases (17.8%) underwent concomitant rotator cuff repair with Bankart repair. Sixteen cases (35.6%) underwent reverse total shoulder arthroplasty for cuff tear arthropathy. 45 cases (100%) in Group B underwent rotator cuff repair. The off-the center and head elevation were measured in the preoperative magnetic resonance imaging (MRI) of Groups A and B. The preoperative and postoperative visual analogue scale (VAS) score, American Shoulder and Elbow Surgeons (ASES) score, and University of California Los Angeles (UCLA) score in Groups A and B were compared. Results: In Groups A and B, the mean off-the centers were posterior 7.41 mm and posterior 2.02 mm (p=0.03), and the mean head elevations were superior 6.66 mm and superior 2.44 mm (p=0.02), respectively. The mean ASES scores of Groups A and B were 32.8 and 33.4 before surgery, and 77.1 (p=0.02) and 78.1 (p=0.02) after surgery (p=0.18), respectively. The mean UCLA scores of Groups A and B were 13.1 and 12.8 before surgery, and 28.9 (p=0.02) and 29.5 (p=0.01) after surgery (p=0.15), respectively. Conclusion: Patients over 65 years old with a shoulder dislocation in large to massive rotator cuff tears had higher off-the center and head elevation on the preoperative MRI than those without a shoulder dislocation. This measurement can help predict preceding shoulder instability. Early rotator cuff repairs should be performed and other treatments, such as Bankart repair and reverse total shoulder arthroplasty, should also be considered.

• Korean Journal of Remote Sensing
• /
• v.39 no.3
• /
• pp.283-295
• /
• 2023

With the development of sensor and satellite technology, numerous high-resolution and multi-spectral satellite images have been available. Due to their wavelength-dependent reflection, transmission, and scattering characteristics, multi-spectral satellite images can provide complementary information for earth observation. In particular, the short-wave infrared (SWIR) band can penetrate certain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, which allows for a clearer view and more detailed information to be captured from hazed surfaces compared to the visible band. In this study, we proposed a multi-resolution transform-based image fusion method to combine visible and SWIR satellite images. The purpose of the fusion method is to generate a single integrated image that incorporates complementary information such as detailed background information from the visible band and land cover information in the haze region from the SWIR band. For this purpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which is a representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge that SWIR bands contain more information in pixels from the haze region. The proposed method was validated using very high-resolution satellite images from Worldview-3, containing multi-spectral visible and SWIR bands. The experimental data including hazed areas with limited visibility caused by smoke from wildfires was utilized to validate the penetration properties of the proposed fusion method. Both quantitative and visual evaluations were conducted using image quality assessment indices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from the visible bands.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.1-19
• /
• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.