• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.85-94
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• 2009

For the purpose of analysing the capability (knowledge, experience, and ability) of CM at Risk in the major construction company in korea, this study performed questionnaire survey with experts in the companies. Based on the analysis of the survey, the study was found as follows. 1) It is needed to increase the capability of preconstruction services, such as project management plan/manual, contract documents, value engineering, alternative analysis, time management, and claim. 2) Despite of gap of the capability between the present and the future CM services, the study concluded that the capability is sufficient to perform CM at Risk project in the major construction company.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.1 s.160
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• pp.21-32
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• 2007

The purpose of this study is to establish the idea of sustainable slow design by analyzing literatures and preceding cases, based on the external elements of a design including forms, the methods of expression, materials and colors. This study reviewed the previous literature of books and pictures related to the research for case studies and content analysis. fashion books, magazines, and web-sites published from 2000 to 2005 were analyzed for this research. The sustainable slow design trends in fashion can be summarized as follow. The first is a timeless style which has sustain ability in design independently of the versatile fads and relies on functionality, serving the purpose of design. One of the examples is both clothes designed by Burberry and suits by Chanel. The second is a hand-touch style which the more time for outputs can be positively tolerated, in favor on eco-friendly design through the techniques of manual arts. The third is a renewable design which the combined values of design with reuse and renewal result in recreation of past ecology as shown in the technique of designs by mix & match. The forth is a transformable design which features the multi-purpose and multi-forms, eventually extending the lift cycle of products. As a result of analysis of the four designs above, it can be inferred that the representation of past styles, the mixture of old design with new design, the appropriate combination of conventional fabrics with advanced ones, the ecological trends of sports look was emerging.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1010-1014
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• 2010

Article-related product recommender system is an emerging e-commerce service which recommends items based on association in contexts between items and articles. Current services recommend based on the similarity between tags of articles and items, which is deficient not only due to the high cost in manual tagging but also low accuracies in recommendation. As a component of novel article-related item recommender system, we propose a new method for tagging item images based on pre-defined categories. We suggest a hypernetwork-based algorithm for learning association between images, which is represented by visual words, and categories of products. Learned hypernetwork are used to assign multiple tags to unlabeled item images. We show the ability of our method with a product set of real-world online shopping-mall including 1,251 product images with 10 categories. Experimental results not only show that the proposed method has competitive tagging performance compared with other classifiers but also present that the proposed multi-tagging method based on hypernetworks improves the accuracy of tagging.

• Anxiety and mood
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• v.7 no.1
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• pp.40-47
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• 2011

Objective : This study aimed to investigate the prevalence of obsessive-compulsive disorder (OCD) in schizophrenia, and the relationship among OCD, severity of psychopathology, and social function in stable patients with chronic schizophrenia. Methods : We interviewed 138 symptom-stable inpatients who had been on a constant dose of antipsychotics for at least 1 month prior and diagnosed as chronic schizophrenia. Subsequently, patients were classified according to the existence of OCD as investigated using the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I) and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Further, all clinical and demographic data was investigated. To investigate potential interrelationships, the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Korea-Positive and Negative Symptom Scale (K-PANSS), and the Korean Personal and Social Performance (K-PSP) were used. An independent ttest and Chi-square test were used to compare groups and a Pearson's correlation coefficient was used to assess the relationship between the Y-BOCS and other clinical rating scales. Results : The prevalence of OCD in schizophrenia patients was 18.1%. Patients with schizophrenia and OCD exhibited significantly earlier onset of schizophrenia, more severe psychiatric symptoms, and lower personal and social performance ability as compared to those without OCD. There was no significant relationship among Y-BOCS, K-PANSS, and K-PSP. Conclusion : We found that comorbid OCD was relatively more frequent in patients with schizophrenia. An investigation involving larger samples of schizophrenia patients with OCD with respect to social function and thus, the effect on quality of life is required.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.521-524
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• 2009

Everyone can easily acquire learning materials on web environment that rapidly develops. Because the importance of English education has been emphasized day by day, many English education systems are introduced. However, previous most English education systems support only single user mode, and cannot deal with a newly coined word such as 'WIKIPEDIA'. In order to lead a user's learning ability with interest and enjoyment, this paper propose an online English word game system implementing a 'scrabble' board game. The proposed English word game system has the following characteristics. First, the proposed system supports both single user mode and multi user mode with a virtual user based on artificial intelligence. Second, the proposed system can recognize newly coined words such as 'WIKIPEDIA' by using NEVER Open API dictionary. Third, the proposed system offers familiar user interface so that a user can play the game without any manual. Therefore, it is expected that the proposed system can help users to learn English words with interest and enjoyment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.341-348
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• 2020

The ability to extract useful information from an image, such as the human eye, is an interface technology essential for AI computer implementation. The building recognition technology has a lower recognition rate than other image recognition technologies due to the various building shapes, the ambient noise images according to the season, and the distortion by angle and distance. The computer vision based building recognition algorithms presented so far has limitations in discernment and expandability due to manual definition of building characteristics. This paper introduces the deep learning CNN (Convolutional Neural Network) model, and proposes new method to improve the recognition rate even by changes of building images caused by season, illumination, angle and perspective. This paper introduces the partial images that characterize the building, such as windows or wall images, and executes the training with whole building images. Experimental results show that the building recognition rate is improved by about 14% compared to the general CNN model.

• The Korean Journal of Franchise Management
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• v.10 no.3
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• pp.7-12
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• 2019

Purpose - This study examines the status of franchises and qualifications for franchising business, examines the franchising qualifications focusing on overseas cases, and suggests policy directions for strengthening the qualifications of franchising business. In order to achieve these purposes, the study reviewed the cases of USA, China, Australia, and United Kingdom franchising business law. Literature Review - According to the Fair Trade Commission, franchise is defined as a transactional relationship in which a franchiser provides certain support and education to franchisees in order to sell their goods and services more effectively. In addition, a franchise is a legally and financially independent business of franchisers and franchisees, and according to the concept of affiliates, it is necessary to define a franchise as a product and service marketing based on close and continuous collaboration. A franchiser can be defined as a company with the ability to develop a franchise system, create sustainable value based on it, and replicate "KNOW-HOW" to sellers. Case Study - This study examined the requirements for establishing a franchiser in the United States, China, Australia, and United Kingdom. In most countries, the requirements of franchisers must be operated for at least one year, which means that education, manual production, and continuity of stores should be checked. Suggestion - Based on Korea's population density and consumption sales index, we propose a screening system that registers through 2 + 1 systems, which require two stores to be operated for more than a year, by dividing Korea's commercial rights into two and a screening system instead of simple registration. In the case of a small franchisors, at least one franchsing retail store must be operated for at least one year, which should be applied to only one brand.

• The Journal of Internal Korean Medicine
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• v.42 no.2
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• pp.215-223
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• 2021

Objectives: The purpose of this study is to report the effects of Korean medicine treatment, including Onkyung-tang, on fibromyalgia. Methods: The patient was treated with herbal medicine, acupuncture, pharmacopuncture, and chuna manual therapy for 13 days. To evaluate the improvements, we used a numeric rating scale (NRS), the American College of Rheumatology Preliminary Diagnostic Criteria (ACR), the neck disability index (NDI), and the Oswestry disability index (ODI). Results: After treatment, the scores for the NRS, ACR, NDI, and ODI all decreased compared with baseline. Conclusion: This study suggests that Korean medicine treatment that includes Onkyung-tang can be effective in reducing pain and increasing ability to function in patients with fibromyalgia.

• Smart Structures and Systems
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• v.29 no.1
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• pp.117-127
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• 2022

Data anomalies seriously threaten the reliability of the bridge structural health monitoring system and may trigger system misjudgment. To overcome the above problem, an efficient and accurate data anomaly detection method is desiderated. Traditional anomaly detection methods extract various abnormal features as the key indicators to identify data anomalies. Then set thresholds artificially for various features to identify specific anomalies, which is the artificial experience method. However, limited by the poor generalization ability among sensors, this method often leads to high labor costs. Another approach to anomaly detection is a data-driven approach based on machine learning methods. Among these, the bidirectional long-short memory neural network (BiLSTM), as an effective classification method, excels at finding complex relationships in multivariate time series data. However, training unprocessed original signals often leads to low computation efficiency and poor convergence, for lacking appropriate feature selection. Therefore, this article combines the advantages of the two methods by proposing a deep learning method with manual experience statistical features fed into it. Experimental comparative studies illustrate that the BiLSTM model with appropriate feature input has an accuracy rate of over 87-94%. Meanwhile, this paper provides basic principles of data cleaning and discusses the typical features of various anomalies. Furthermore, the optimization strategies of the feature space selection based on artificial experience are also highlighted.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.