• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.141-150
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• 2012

This paper suggests a critical path search algorithm that can easily draw PERT/GANTT chart which manages and plans a project schedule. In order to evaluate a critical path that determines the project schedule, Critical Path Method (CPM) is generally utilized. However, CPM undergoes 5 stages to calculate the critical path for a network diagram that is previously designed according to correlative relationship and execution period of project execution activities. And it may not correctly evaluate $T_E$ (The Earliest Time), since it does not suggest the way how to determine the sequence of the nodes activities that calculate the $T_E$. Also, the sequence of the network diagram activities obtained from CPM cannot be visually represented, and hence Lucko suggested an algorithm which undergoes 9 stages. On the other hand, the suggested algorithm, first of all, decides the sequence in advance, by reallocating the nodes into levels after Breadth-First Search of the network diagram that is previously designed. Next, it randomly chooses nodes of each level and immediately determines the critical path only after calculation of $T_E$. Finally, it enables the representation of the execution sequence of the project activity to be seen precisely visual by means of a small movement of $T_E$ of the nodes that are not belonging to the critical path, on basis of the $T_E$ of the nodes which belong to the critical path. The suggested algorithm has been proved its applicability to 10 real project data. It is able to get the critical path from all the projects, and precisely and visually represented the execution sequence of the activities. Also, this has advantages of, firstly, reducing 5 stages of CPM into 1, simplifying Lucko's 9 stages into 2 stages that are used to clearly express the execution sequence of the activities, and directly converting the representation into PERT/GANTT chart.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.264-273
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• 2012

This cross-sectional study was investigated musculoskeletal discomfort symptoms and related factors on some middle high school teachers. Self-questionnaire of KOSHA CODE H-30-2003 was done with 250 teachers from 1st to 15th October, 2010, the data from 231 teachers (68 male, 163 female) was statistically analyzed to search the factors related to musculoskeletal discomfort symptoms. According to NIOSH rate of musculoskeletal discomfort symptoms by body parts was 36.8%. Musculoskeletal discomfort symptoms related to age, school types, subjective health status, housekeeping time, VDT work time and regular rest. After adjusting for related variables, odds ratio (OR) of musculoskeletal discomfort symptoms was correlation significantly to subjective health status unhealthy (OR 11.75, 95% Confidence Interval, CI, 3.56-378.78). In addition, ORs (95% CI) of age (40-49) and housekeeping time (${\geq}3$) were 4.63 (1.82-26.18) and 4.33 (1.97-19.34). Analysis of the factors influencing the musculoskeletal discomfort symptoms vary in different parts of the body. The most discomfort symptoms by parts was neck (26.0%) and shoulder (30.0%). In the neck region was related to subjective health status and regular rest. In the shoulder and waist region was subjective health status and sex. Age was wrist/finger, leg/foot was related to subjective health status, sex and VDT work time. Age, school types, subjective health status, housekeeping time, VDT work time and regular rest related to musculoskeletal discomfort symptoms and the most discomfort symptoms by parts was neck and shoulder.

• Journal of the Korean Society of Costume
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• v.31
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• pp.145-164
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• 1997

Cinema costume can stimulate the public to synchronize with and replicate what they see in the movies. Especially when the public thinks the stars in the movies . Especially when the public thinks the stars in the movies are beautiful or dramatic the styles of cinema costumes powerfully affect them. Thus cinema costume designers quickey become fashion designers. Edith Head who strongly believed cinema costumes to be an effective means of portraying the Character's personality and psychological make-up was an innovative designer whose costumes manifested this belief. She enhanced the character's individual image and distinction for the public through her artistic design in costumes. She adapted a realistic approach but her costumes invariably produced aesthetic ef-fects. Since the Academy Awards added the category of costume design she led the field with 35 nominations and eight oscars during 33 years of her productive work. Edith head was a dominant figure in costume design; her creations were highly renowned as an art form while they gained popularity. The purpose of this study was to reveal the ef-fects of Edith Head's cinema costume designs on fashion. This study was also to emphasize the powerful influence on ashion of cinema costume and cinema costume designers in general. The study was done through literature movies for which she created costumes fashion magazines and Edith Head's original sketches. The influence of Edith Head's costume de-sign on fashion is as follows: 1. She introduced and lead the casual fashion in the 1950's combining simplicity and sophistication. 2. She altered uniforms and reconstructed public clothing for multiple functions. 3. She rearranged high school prom dresses through the movie 'A Place in the Sun" to en-hance characteristic of each gender and the Dandy Look of the 1930's into men's apparel in the 1970's through the movie "The Sting" 4. She expanded the traditional style in the 1940's and became a leader in ecological style. 5. She adapted glitter from astronaut's ap-parel into public clothing. 6. She resturctured Sabrina Pants in the 1960's to accentuate the individuals strength by overcoming one's weakness without minimi-zing it's aesthetic appeal and reintroduced the pants in the 1990's. 7. She introduced elegant negligees to gen-eral public and maintained it in the public do-main. As it is revealed Edith Head's costume de-sign not only impacted the field of fashion dur-ing her time but also is presently influencing modern fashion throughout the world as it is witnessed by repeated reintroduction of her fashion styles. Reviewing her cinema costumes it is concluded that cinema costumes it is concluded that cinema costumes powerfully af-fect the public through a visual channel more than any other routes. Cinema costumes can become the origin of fashion by stimulating the public to synchronize with and replicate what they see in the movies. Since cinema costumes can launch fashion trend it requires further research. Based on what is revealed in this study. it would be beneficial to examine how cinema costumes affect people socially and culturally and how they could provide resources for re-search in fashion trends. It is also the writers opinion that there should be more designers such as Edith head who could lead the field of costume design into the twenty-first century.

• The Journal of Art Theory & Practice
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• no.3
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• pp.85-106
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• 2005

As biennale exhibitions has been expanded into all of the world since 1990s, these trends of blockbuster exhibitions have caused several problems. For instance, some major curators monopolized most global size exhibitions despite of a variety of cultural and historical backgrounds. Besides, due to a strong connection between these curators and their own artists, the young emerging artists' opportunities tend to be reduced as a result of the power game. In addition, major curators' power have influence on the exhibition style as well as on the theme itself. Some artists who did not involved that kind of huge scale exhibitions dispute that the direction of the exhibition is concentrating on the curator's interest instead of artists or viewers. Although these dissatisfactions could not portray correctly the process of organizing and managing system of a biennale exhibition, those biennale exhibitions held in recent have shown tautologic discourses without any passion and positive attitude direct to the exploitation of our society as a vanguard. In the process of comparing several kinds of biennale exhibitions, I could find that some artists who participated several biennale exhibitions at the same time did not present their creative vision, although the triumph of an exhibition was typically measured by the amount of visitors. Thus, the aim of this article is to prove that the biennale can show us new cultural discourse as well as progressive method of understanding our times. Is biennale producing the real 'global standard'? If biennale has done it, could this global standard present upto-date paradigm for the unique exhibition system? Is biennale providing an useful opportunity for the understanding and communicating of contemporary art through the recontextualization which is pronounced by the publicity of curator and organizing committee? How can we find the distinctive strategy from each biennale exhibition including Venice Biennale? Biennale, as a blockbuster exhibition, always requires a degree of hype, otherwise it would not be a special event and would not attract a big enough audience. It is the actual reason why major biennale exhibitions seem to be similar artistic events. Unfortunately, it seems that the excess of biennale exhibitions might bring about the lack of contents. In this case, the biennale syndrome would being a kind of the center of poverty, in spite of the visual splendor. After all, following the global standard may not be a matter of great importance now. What really matters is how each biennale exhibition which started under the different conditions can search their own identity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.293-302
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• 2019

This study systematically analyzed computer-based driving intervention programs for seniors, to provide the academic background for driving intervention for seniors. Articles published from January 2009 till December 2018 were researched and analyzed. 'PubMed, Google Scholar, and Science Direct' were used to search articles published overseas, and 'RISS, KERIS, and KISS' searched for articles published in Korea. Based on the inclusion and exclusion criteria, totally 359 papers were retrieved, and 10 articles were finally analyzed; 8 articles (80%) were evidence level I, and 2 articles (20%) were evidence level III. Amongst the computer-based interventions, driving simulators (70%) were the most common, followed by two video image training (20%) and one Nintendo Wii program (10%). In most studies, driving simulators trained the cognitive and visual abilities of seniors and enhanced their abilities to cope with risk situations under various simulated circumstances. Other interventions were also reported to have a positive effect. For evaluating elderly drivers, the driving performance evaluation using a driving simulator was the most common; in addition, evaluations of attention, space-time ability, cognitive function, risk perception, depression and anxiety were also commonly used. We believe that it is appropriate to employ computer-based driving intervention programs for seniors to train and evaluate various domains. We expect that these interventions can be used as an effective tool for safe driving.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.115-168
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• 2018

An amendment to Japanese Civil Aeronautics Act came into effect December 10, 2015. The Act prohibits flying drones over residential areas or areas surrounding an airport without permission from the Minister of Land, Infrastructure and Transportation. Flying drones during night time and during an event is also prohibited. The term "UAV" or "UA" means any aeroplane, rotorcraft, glider or airship which cannot accommodate any person on board and can be remotely or automatically piloted (Excluding those lighter than a certain weight (200 grams). Any person who intends to operate a UAV is required to follow the operational conditions listed below, unless approved by the Minister of Land, Infrastructure, Transport and Tourism; (i) Operation of UAVs in the daytime, (ii) Operation of UAVs within Visual Line of Sight (VLOS), (iii) Maintenance of a certain operating distance between UAVs and persons or properties on the ground/water surface, (iv) Do not operate UAVs over event sites where many people gather, (v) Do not transport hazardous materials such as explosives by UAV, (vi) Do not drop any objects from UAVs. Requirements stated in "Airspace in which Flights are Prohibited" and "Operational Limitations" are not applied to flights for search and rescue operations by public organizations in case of accidents and disasters. This paper analyzes some issues as to regulations of UAVs in Korean Aviation Safety Act by comparing the regulations of UAVs in Japanese Civil Aeronautics Act. This paper, also, offers some implications and suggestions for regulations of UAVs under Korean Aviation Safety Act.

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

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.