• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.208-215
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• 2003

For playing a multimedia presentation in a Internet, the case that the presentation QoS(Quality of Services) at a destination nay be different from the QoS of multimedia data at the source occurs frequently. In this case, the process of trancoding the multimedia data at the source Into the multimedia data satisfying the QoS at the destination should be requited. In addition, even the presentation description having the homogeneous QoS at both sides may have different transcoding paths due to the limitation of display terminals or network bandwidth. That is, for a multimedia description, it is required to regenerate a proper transcoding path whenever the displaying terminals or the network environment gets decided. And the delay time required to go through the transcoding path may affect the playability of the give presentation. Therefore it should be checked whether the presentation requiring a transcoding process is able to be played in a real time. In this paper, the algorithm for generating all the possible transcoding paths for a given multimedia description under a fixed set of transcoders and the network environment is proposed. The algorithm adopts the concept of QoS transition diagram to Prevent from a trancoding Path being cycled by the repetition of a cyclic Path which generates the same QoS of multimedia data as its input QoS. By eliminating all the cyclic Paths, the algorithm can guarantee the termination of the process. And for the playability check, a method of computing the transcoding time and the delay lime between logical data units are proposed.Finally all the proposed methods were implemented in the stream engine, called TransCore and the presentation-authoring tool, called VIP, we had developed. And the test results with sample scenarios were presented at the last.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.281-288
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• 2017

In Smart-cities, various types of integrated services must be linked to provide services to applications. Therefore, flexibility must be ensured between services so that various services can be efficiently provided. In order to secure the flexibility among services, it is very important to have a function to dynamically discover and invoke a desired service by searching for a semantic service by reflecting a recognized context through real-time context-aware in smart-cities. To date, quite a number of semantic service discovery techniques have been developed. However, they have not been verified as suitable for use in the smart-city domain. In this study, we tried to verify the existing ones to use a suitable one. We tested most of existing semantic service discovery techniques, but we found that none of them is suitable to our research. Therefore, we developed our own semantic service discovery technique. This paper introduces our work and presents the performance evaluation results that demonstrate that our developed works well and show good performance. For the performance evaluation, the experimental system was actually constructed and the real performance was measured. In the experiment, we implemented the semantic service discovery scenario that dynamically searches and calls the services needed to provide fire accident management services in smart cities.

• Information Systems Review
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• v.13 no.1
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• pp.33-59
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• 2011

Although online social network services widely used in human networking and recruiting industries, it is showing off its limitations in followings-it's hard to reach the status of seamless connection between offline and online; the incompletion and low credibility of the information came from non-face-to-face profile exchange; and the restraint of user autonomy due to centralized control. This paper defines the ubiquitous social network management which enables the seamless real-time face-to-face social interactions of the users based on WPAN (Wireless Personal Area Network) who share the same interest in real word and deduces a ubiquitous social network management framework based on it. As an instance of ubiquitous social network management, u-Recruiting service model will be designed and analyzed. The Analysis using the business model will be followed by the possible scenario of service model. The role, value proposition and potential benefits of the each participants in this service model and will be given as well. In order to evaluate relative advantages of the model suggested by this study, 6 cases will be compared.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.31-38
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• 2017

Recently with the rapid development of LBS (Location-based Services) technology, approaches of protecting user's location have gained tremendous attentions. For using LBS, users need to forward their real locations to LBS server. However, if the user sends his/her real location to LBS server, the server will have the all the information about user in LBS. Moreover, if the user opens it to LBS server for a long time, the trajectory of user may be released. In this paper, we propose GTC (Grid-based Trajectory Cloaking) method to address the privacy issue. Different from existing approaches, firstly the GTC method sets the predicting trajectory and divides the map into $2^n*2^n$ grid. After that we will generate cloaking regions according to user's desired privacy level. Finally the user sends them to LBS server randomly. The GTC method can make the cost of process less than sequential trajectory k-anonymity. Because of confusing the departure and destination, LBS server could not know the user's trajectory any more. Thus, we significantly improve the privacy level. evaluation results further verify the effectiveness and efficiency of our GTC method.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.66-77
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• 2006

In this paper, we researched the searching and tracking locations of a home resident using ON/OFF switches and sensors and designed a remote monitoring system. As an implementation environment, this system is developed on the base of the distributed object group framework we have developed from previous works. In order to trace the moving locations of a home resident, we firstly showed a home structure which attaches ON/OFF switches and sensors to home appliances and indoor facilities being fixed in home. Whenever a home resident opens/closes these objects, the signals operated from ON/OFF switches and sensors are sent to a home server system. In this time, the real locations of ON/OFF switches and sensors that the signals are being occurred must be the current location that he/she stays. A home server system provides the functionalities that map the real location of a resident in home to virtual location designed on remote desk-tops or terminals like PDAs, and that construct a healthcare database consisted of moving patterns, moving ranges, momentum for analyzing the given searching locations and times Finally, this system provides these information for remotely monitoring services.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.114-124
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• 2009

In this paper, we propose a practical TCP friendly rate control scheme that considers the minimum channel bandwidth of the network when transporting SVC (scalable video coding) video over IP netowrks such as Internet. RTP and RTCP is mainly designed for use with UDP (User Datagram Protocol) for real-time video transport over the Internet. TCP-friendly rate control was proposed to satisfy the demands of multimedia applications while being reasonably fair when competing for bandwidth with conventional TCP applications. However the rate control model of the conventional TCP-friendly rate control scheme does not consider the minimum channel bandwidth of the network. Thus the estimated channel bandwidth by the conventional rate control model might be quite different from the real channel bandwidth when the packet loss ratio of the network is very large. In this paper, we propose a modified TCP-friendly rate control scheme that considers the minimum channel bandwidth of the network. Based on the modified TCP-friendly rate control, we assign the minimum channel bandwidth to the base layer bitstream of SVC video, and remaining available bandwidth is allocated to the enhancement layer of SVC video for the TCP friendly scalable video transmission. It is shown by simulations that the modified TCP-friendly rate control scheme can be effectively used for a wider range of controlled bit rates depending on the packet loss ratio than the conventional TCP-friendly control scheme. Furthermore, the effectiveness of the proposed scheme in terms of objective video quality is proved by comparing PSNR performance with the conventional scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1077-1086
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• 2023

The searchable encryption model allows to selectively search for encrypted data stored on a remote server. In a real-world scenarios, the model must be able to support multiple search keywords, multiple data owners/users. In this paper, these models are referred to as Multi Ranked Searchable Encryption model. However, at the time this paper was written, the proposed models use fully-trusted trapdoor centers, some of which assume that the connection between the user and the trapdoor center is secure, which is unlikely that such assumptions will be kept in real life. In order to improve the practicality and security of these searchable encryption models, this paper proposes a new Multi Ranked Searchable Encryption model which uses random keywords to protect search words requested by the data downloader from an honest-but-curious trapdoor center with an external attacker without the assumptions. The attacker cannot distinguish whether two different search requests contain the same search keywords. In addition, experiments demonstrate that the proposed model achieves reasonable performance, even considering the overhead caused by adding this protection process.