• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.

• Smart Media Journal
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• v.12 no.9
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• pp.159-170
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• 2023

It takes a lot of time and manpower to search for the missing. As part of the solution, a missing person search AI system was implemented using a YOLO-based model. In order to train object detection models, the model was learned by collecting recognition images (road fixation) of drone mobile objects from AI-Hub. Additional mountainous terrain datasets were also collected to evaluate performance in training datasets and other environments. In order to optimize the missing person search AI system, performance evaluation based on model size and hyperparameters and additional performance evaluation for concerns about overfitting were conducted. As a result of performance evaluation, it was confirmed that the YOLOv5-L model showed excellent performance, and the performance of the model was further improved by applying data augmentation techniques. Since then, the web service has been applied with the YOLOv5-L model that applies data augmentation techniques to increase the efficiency of searching for missing people.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.53-66
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• 2006

This paper proposes the combined image retrieval system that gives the same relevance as exhaustive search method while its performance can be considerably improved. This system is combined with two different retrieval methods and each gives the same results that full exhaustive search method does. Both of them are two-stage method. One uses condensation of feature vectors, and the other uses binary-tree clustering. These two methods extract the candidate images that always include correct answers at the first stage, and then filter out the incorrect images at the second stage. Inasmuch as these methods use equal algorithm, they can get the same result as full exhaustive search. The first method condenses the dimension of feature vectors, and it uses these condensed feature vectors to compute similarity of query and images in database. It can be found that there is an optimal condensation ratio which minimizes the overall retrieval time. The optimal ratio is applied to first stage of this method. Binary-tree clustering method, searching with recursive 2-means clustering, classifies each cluster dynamically with the same radius. For preserving relevance, its range of query has to be compensated at first stage. After candidate clusters were selected, final results are retrieved by computing similarities again at second stage. The proposed method is combined with above two methods. Because they are not dependent on each other, combined retrieval system can make a remarkable progress in performance.

• Journal of KIISE
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• v.43 no.1
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• pp.126-134
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• 2016

Due to the merits of OLED displays such as fast responsiveness, wide view angle, and power efficiency, their use has increased. However, despite the power efficiency of OLED displays, the portion of their power consumption among the total power consumption is still high since user interaction-based applications such as instant messaging, video play, and games are frequently used. Their power consumption varies significantly depending on the display contents and thus color transformation is one of the low-power techniques used in OLED displays. Prior low-power color transformation techniques have not been rigorously studied in terms of satisfaction of the human visual system, and have not considered optimal visual satisfaction and power consumption at the same time in relation to color transformation. In this paper, we propose a novel low-power color transformation technique which strictly considers human visual system-awareness as well as optimization of both visual satisfaction and power consumption in a balanced way. Experimental results show that the proposed technique achieves better human visual satisfaction in terms of visuality and also shows on average 13.4% and 22.4% improvement over a prior one in terms of power saving.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Korean Security Journal
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• no.13
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• pp.145-168
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• 2007

Like to change to the information-oriented society, the guard service needs to be changed. The communication and hardware technology develop rapidly and according to the internet environment change from cable to wireless, modern person can approach every kinds of information service using wireless communication machinery which can be moved such as laptop, computer, PDA, mobile phone and so on, LBS field which presents the needing information and service at anytime, anywhere, and which kinds of device expands it's territory all the more together with the appearance of ubiquitous concept. LBS use the chip in the mobile phone and make to confirm the position of the joining member anytime within several tens centimeters to hundreds meters. LBS can be divided by the service method which use mobile communication base station and apply satellite. Also each service type can be divided by location chase service, public safe service, location based information service and so on, and it is the part which will plan with guard service development. It will be prospected 8.460 hundred million in 2005 years and 16.561 hundred million in 2007 years scale of market. Like this situation, it can be guessed that the guard service has to change rapidly according to the LBS application. Study method chooses documentary review basically, and at first theory method mainly uses the second documentary examination which depends on learned journal and independent volume which published in the inside and the outside of the country, internet searching, other kinds of all study report, statute book, thesis which published at public order research institute of the Regional Police Headquarter, police operation data, data which related with statute, documents and statistical data which depend on private guard company and so on. So the purpose of the study gropes in accordance with the LBS application, and present the problems and improvement method to analyze indirect of manager side of operate guard adaptation service of LBS, government side which has to activate LBS, systematical, operation management, manpower management and education training which related with guard course side which has to study and educate in accordance with application of the new guard service, as well as intents to excellent quality service of guard.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.574-584
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• 2006

Recently, ISO/IEC 23000 (also known as 'MPEG-A') has proposed a new file format called 'MAF(Multimedia Application File Format)[1]' which provides a capability of integrating/storing the widely-used compression standards for audio and video and the metadata in MPEG-7 form into a single file format. However, it is still very hard to verify the usefulness of MPEG-A in the real applications because there is still no real system that fully implements this standard. In this thesis, a design and implementation of a multimedia retrieval system based on MPEG-A standard on PC and mobile device is presented. Furthermore, an extension of MPEG-A for describing the metadata for video is also proposed. It is selected and defined as a subset of MPEG-7 MDS[4] and TV-anytime[5] for video that is useful and manageable in the mobile environments. In order to design the multimedia retrieval system based on MPEG-A, we define the system requirements in terms of portability, extensibility, compatibility, adaptability, efficiency. Based on these requirements, we design the system which composed of 3 layers: Application Layer, Middleware Layer, Platform Layer. The proposed system consists of two sub-parts, client-part and server-part. The client-part consists of MAF authoring tool, MAP player tool and MAF searching tool which allow users to create, play and search the MAF files, respectively. The server-part is composed of modules to store and manage the MAF files and metadata extracted from MAF files. We show the usefulness of the proposed system by implementing the client system both on MS-Windows platform on desk-top computer and WIPI platform on mobile phone, and validate whether it to satisfy all the system requirements. The proposed system can be used to verify the specification in the MPEG-A, and to proves the usefulness of MPEG-A in the real application.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.640-655
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• 2014

Many of today's video systems have additional depth camera to provide extra features such as 3D support. Thanks to these changes made in multimedia system, it is now much easier to obtain depth information of the video. Depth information can be used in various areas such as object classification, background area recognition, and so on. With depth information, we can achieve even higher coding efficiency compared to only using conventional method. Thus, in this paper, we propose the 2D video coding algorithm which uses depth information on top of the next generation 2D video codec HEVC. Background area can be recognized with depth information and by performing HEVC with it, coding complexity can be reduced. If current CU is background area, we propose the following three methods, 1) Earlier stop split structure of CU with PU SKIP mode, 2) Limiting split structure of CU with CU information in temporal position, 3) Limiting the range of motion searching. We implement our proposal using HEVC HM 12.0 reference software. With these methods results shows that encoding complexity is reduced more than 40% with only 0.5% BD-Bitrate loss. Especially, in case of video acquired through the Kinect developed by Microsoft Corp., encoding complexity is reduced by max 53% without a loss of quality. So, it is expected that these techniques can apply real-time online communication, mobile or handheld video service and so on.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.309-317
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• 2012

Objective: The aim of this paper is to inquire into the influences form factors and control types affect a search time and comfort at list menu of full touch phone. Background: Various studies have been proceeded that are related to the optimum touch area for enhancing usability of control and legibility in mobile touch device. In the environment of list menu which is widely used to provide various information effectively, however, not only comprehensive consideration for legibility and control is to be seek but also research for control type which is to scroll a list. Method: This study executed form factor experiment to inquire into the influence that font size, height of row and fixed area affect searching time and comfort in the while information processing even if the information on the list is unsorted in alphabetical order. Among the result of form factor experiment, control type experiment was executed by selecting shortest performance time, highest legibility comfort and control comfort. Control type experiment was implemented to figure out the influence which existing flicking type, scrolling bar type, newly established button page type and button raw types affect performance time and subjective comfort depending on location of the information. Results: Font size 12pt, height of row 7mm and fixed area 15mm was shortest performance time and got highest comfort and legibility score in form factor experiment. A Button page which was newly proposed type was shortest performance time and got highest comprehensive comfort in control type experiment. Conclusion: Form factor experiment showed similar results with the study through reading a long passage of character or controlling a grid icon type. However, height of row turned out to affect not only touch area for control but also legibility by ruling space between the lines. Button page type which was newly proposed showed shortest performance time and got highest comprehensive comfort. Because Button page type needs few finger movements than other control types and implements search in the fixed form, unlikely other type which list keeps moving. Application: This study should be applied in deciding form factors and control type for scroll when designing a list menu of full touch phone.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.10
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• pp.17-28
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• 2008

Rapid transmission of packets is important in mobile ad hoc networks. Therefore, a flooding algorithm which can guarantee a short delay is useful in various ways of packet transmission. Flooding algorithm is one of the packet transmission methods that broadcasts a packet to all nodes within a transmission range. It does not rebroadcast the same packet which is already received from other nodes. Basically, flooding algorithm's advantages are that it simply writes an address and a sequence number in a packet, and it can be adapted for topological changes easily. However, the basic flooding algorithm has a shortcoming that causes excessive traffic because all nodes transmit a packet at least once. To solve this problem, research about flooding algorithms that constrains duplicated transmission of packets based on probabilistic and geographical information is going on. However, the existing algorithm cannot guarantee short delay and low traffic. To reduce a delay, in this paper we propose a flooding scheme where a node which receives a broadcasted packet chooses and allocates a priority to one of its neighbor nodes and then the node transmits the packet promptly to the node to whom the priority was given. Moreover, we propose a totally fresh a roach to constrain duplicated transmission by searching a node that already received the same packet by using node's geographical position information. Lastly, we compare the performance of the proposed algorithm with the existing algorithm through simulation. The results show that the proposed algorithm can distribute packets through a lower number of total packet transmissions and faster delivery time than the existing algorithm.