• Fashion & Textile Research Journal
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• v.11 no.4
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• pp.583-591
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• 2009

The purpose of this study was to examine the sportswear purchase decision factors and brand preference of college students. The subjects in this study were 614 college students who were selected by cluster random sampling from Daegu and North Gyeongsang Province. The collected data were analyzed by crosstab analysis, and the findings of the study were as follows: If a sportswear company has college students as a target market, first, the company needs to consider design and utility. Second, the company needs to expand internet sale while maintaining a strategy for centering on speciality shop and department store as for a sale of sportswear. Third, the college students themselves have a right of choice according to purchasing sportswear. Thus, a distribution company requires a direct marketing strategy targeting college students. Fourth, simple design of adding a fashion trend is needed. Fifth, the sportswear company needs to expand production and sale in jumpers and trousers based on T-shirts. Sixth, color in sportswear needs to be composed of design based on gray or black color. In order for a sportswear company to be adjusted to the global market environment here after, it requires an effort to continuously grasp consumers' trend and to apply new design and color. Also, the company will be able to be equipped with competitive edge by producing diversely functional products that are demanded by the segmented market.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.837-846
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• 2012

This paper presents a watermarking scheme based on the perspective distance for the secure mash-up service. The proposed scheme embeds the watermark of the location information of satellite image and the user information using edge color histogram, which is dissimilar to general digital image. Therefore, this scheme can trace the illegal distributor and can protect private information of user through the watermarking scheme that is adaptive to satellite image. Experimental results verified that our scheme has the invisibility and also the robustness against geometric attacks of rotation and translation.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of Drive and Control
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• v.18 no.2
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• pp.20-31
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• 2021

An excavator is a construction machine that can perform various tasks such as trenching, piping, excavating, slope cutting, grading, and rock demolishing. In the 2010s, unmanned construction equipment using ICT technology was continuously developed. In this paper, the path design process was studied to implement the output data of the decision stage, and the path design algorithm was developed. For example, the output data of the decision stage were terrain data around the excavator, excavator mechanism information, excavator hydraulic information, the position and posture of the bucket at key points, the speed of the desired bucket path, and the required excavation volume. The result of the path design was the movement of the hydraulic cylinder, boom arm, bucket, and bucket edge. The core functions of the path design algorithm are the function of avoiding impact during the excavation process, the function to calculate the excavation depth that satisfies the required excavation volume, and the function that allows the bucket to pass through the main points of the excavation process while maintaining the speed of the desired path. In particular, in the process of developing the last function, the node tracking method expressed in the path design table was newly developed. The path design algorithm was verified as this path design satisfied the JCMAS H02 requirement.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.458-470
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• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.1-14
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• 2020

Leading the fourth industrial revolution era requires science and technology strategies that establish original research directions at the national level. To this end, it is necessary to look at the research and development activities for the fourth industrial revolution of technology-leading countries. In this study, the research programs of the U.S. Intelligence Advanced Research Projects Activity(IARPA), an organization focusing on cutting edge research on science and technology information such as artificial intelligence, are investigated by using network analysis. The findings show that, resolving around the information identification and forecasting, decision making and cybersecurity clusters, IARPA's research programs largely focus on finding hidden information and predicting specific events, supporting decision making by considering changes in and outside organizations or establishing cybersecurity. Also, this study finds that China and Japan, representative technology-leading Asian countries, refer to the research programs of IARPA to establish their science and technology policies. The results of this study suggest implications for Korea's science and technology policies in response to the fourth industrial revolution era.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5B
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• pp.317-326
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• 2012

Recently, many researchers have studied to solve the energy consumption of network equipments since the interest of Green IT has been increased. In this paper, we apply Low Power Idle (LPI) to OBS network to reduce energy consumption of network devices. Many previous researches have focused on maximizing the sleep time of network equipments to increase the energy saving efficiency of LPI. But transition overhead caused by LPI might not only depreciate the performance of energy saving but also increase packet delay. In this paper, Transition Decision (TD) algorithm is proposed to improve energy saving efficiency by reducing the number of unnecessary transition and guarantee the required QoS such as packet delay. To evaluate the performance of proposed algorithm, we model OBS edge router with LPI by OPNET and analyze the performance of the proposed algorithm in views of energy saving, transition count and average packet delay.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.65-68
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• 2005

In this paper, an algorithm to extract bar-space area is suggested. In a section of bar-code space area the threshold value is computed, and bar and space are extracted according to threshold value. PDF417 is used everyday life and printed in many different materials. The printed PDF417 is especially influenced by various light source. The decision of bar and space is very hard under the change of illumination. The fixed threshold value to distinguish the bar and space can not be applied. in these cases, The proposed algorithm is developed to investigate variable threshold. The variable threshold can be obtained by simple calculation.