• Korean Management Science Review
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• v.27 no.3
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• pp.43-70
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• 2010

Influences of convergent services on the overall industry has become noticeable. Various services are becoming to converge into a single platform because of ever-hanging needs of digital service users. However, few studies have investigated how users' perception of convergent services as well as the quality of experience that service users have while using the convergent services. Therefore, this study aims at identifying perceived patterns of convergent services by IPTV users, which is one of the representative convergent-ervice platforms. It also aims at identifying the impact of perceived convergence pattern on the relationship between goal congruency among individual services and the quality of user experience. Two empirical studies were conducted to accomplish the research goals. We have constructed two prototypes of convergent digital services in the IPTV environment and conducted controlled experiments to verify the research hypotheses. The results indicate that design similarities of two services substantially influence the perceived patterns of convergent services. It was also found that the perceived convergent patterns have significant moderating effects on the impact of perceived goal congruence upon the quality of user experience. This paper ends with limitations as well as implications of the study results.

• Convergence Security Journal
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• v.15 no.6_2
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• pp.3-10
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• 2015

Recent massive data breaches or major security incidents show that threats posed by insiders have greatly increased over time. Especially, authorized insiders can cause more serious problems than external hackers can. Therefore there is a growing need to introduce a system that can monitor the insider threats in real time and prevent data breaches or security incidents in early-stage. In this paper, we propose a EITMS(Enterprise Insider-Threats Management System). EITMS detects the abnormal behaviors of authorized insiders based on the normal patterns made from their roles, duties and private activities. And, in order to prevent breaches and incidents in early-stage, a scoring system that can visualize the insider threats is also included.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.4
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• pp.113-117
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• 2013

This paper describes a new technology to develop the character recognition technology based on pattern recognition for non-contacting inspection optical lens slant or precision parts, and including external form state of lens or electronic parts for the performance verification, this development can achieve badness finding. And, establish to existing reflex data because inputting surface badness degree of scratch's standard specification condition directly, and error designed to distinguish from product more than schedule error to badness product by normalcy product within schedule extent after calculate the error comparing actuality measurement reflex data and standard reflex data mutually. Developed system to smallest 1 pixel unit though measuring is possible 1 pixel as $37{\mu}m{\times}37{\mu}m$ ($0.1369{\times}10-4mm^2$) the accuracy to $1.5{\times}10-4mm$ minutely measuring is possible performance verification and trust ability through an experiment prove.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.520-537
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• 2019

This paper proposes a system that can detect the data leakage pattern using a convolutional neural network based on defining the behaviors of leaking data. In this case, the leakage detection scenario of data leakage is composed of the patterns of occurrence of security logs by administration and related patterns between the security logs that are analyzed by association relationship analysis. This proposed system then detects whether the data is leaked through the convolutional neural network using an insider malicious behavior graph. Since each graph is drawn according to the leakage detection scenario of a data leakage, the system can identify the criminal insider along with the source of malicious behavior according to the results of the convolutional neural network. The results of the performance experiment using a virtual scenario show that even if a new malicious pattern that has not been previously defined is inputted into the data leakage detection system, it is possible to determine whether the data has been leaked. In addition, as compared with other data leakage detection systems, it can be seen that the proposed system is able to detect data leakage more flexibly.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.243-247
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• 2019

The purpose of this study was to determine the effect of climbing exercise program on the spinal alignment and balance ability of students in 20's. The subjects of this study were 30 university students. Experimental group was performed climbing program combined with upper and lower extremity pattern for three times per week, during six weeks. A Self-efficacy questionnaire was used assess the self-confidence, individdual confidence, or belifes in specific tasks. The results of comparison of variations in each group showed that there was a significant difference in the training group(p<0.05). Climbing exercise program combined with upper and lower extremity pattern is effective for improvement of the self-efficay. So, these study results will be useful as reference date for improvement of the self-efficay.

• Elastomers and Composites
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• v.57 no.4
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• pp.157-164
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• 2022

Representative bulletproof materials, such as aramid or ultra-high molecular weight polyethylene(UHMWPE), have excellent strength and modulus in the plane direction but are very vulnerable to forces applied in the thickness direction. This paper reports a study on the effects of reinforcement in the thickness direction when bulletproof composite fabrics are prepared to improve their performance. Aramid and UHMWPE fabrics were combined using the film-bonding, needle-punching, or stitching methods and then subjected to low-velocity projectile and ball-drop impact tests. The results of the low-velocity projectile test indicated that the backface signature(BFS) decreased by up to 29.2% in fabrics obtained via the film-bonding method. However, the weight of the film-bonded fabric increased by approximately 23% compared with that obtained by simple lamination, and the fabric stiffened on account of the binder. Flexibility, light weight for wearability, and excellent bulletproof performance are very important factors in the development of bulletproof materials. When the needle-punching method was used, the BFS increased as the fibers sustained damage by the needle. When the composite fabrics were combined by stitching, no significant difference in weight and thickness was observed, and the BFS showed similar results. When a diagonal stitching pattern was employed, the BFS decreased as the stitching density increased. By contrast, when a diamond stitching pattern was used, the fabric fibers were damaged and the BFS increased as the stitching density increased.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.275-281
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• 2016

In modern society, which boomed it became easier to obtain the necessary information to the emergence of a variety of smart devices. Due to this, the frequency of using the content based on the Web is growing rapidly. In addition, companies are turning into a production and modify the content using the CMS under the web-based. It can be a very important part to provide users with the content. Currently web services are designing a UI to the device and provided. To improve the ease of use, they are enhancing services only by survey and analysis of the patterns of all users. Most are designed without considering the UX only in the technical aspects. In this paper, to break the limits that apply to all users of the Web service pattern analysis, we propose a visualization system via the animation based on the individual user's movement patterns and usage patterns. Through this convergence is expected to be able to transform the web from the central manager to the user UX and the planning aspects researchers.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.162-167
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• 2015

This paper describes the reason and the problem solving for the double-layer pattern of a Daejeon correlator operated in Korea-Japan Correlation Center. When the electric power of an input signal in the correlator is charged small enough to be buried in the noise, it is hard to see a signal with a specific pattern in the input signal, but when the electric power is large, a specific one is reported to be seen. By comparing data from observation with one from software correlator, it was confirmed from the analysis using the AIPS software that the amplitude gain of a source signal was affected about 3%. Therefore, in order to solve the problem of double-layer patterns, we found that a problem in the memory management module responsible for both the data input and the data serialization of the correlator is a cause for the double-layer pattern detected periodically. In other words, while data is serialized and read repeatedly in the memory area assigned to serialize the data from the serialization module, redundant last data is generated and an overlap for the memory allocation is occurred. Therefore, by modifying the program of the FPGA memory sections on serialization module to correct the problem, we confirmed that double-layer pattern is disappeared and correlation results are normally acquired.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.131-139
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• 2016

Recognition of human motions has become a main area of computer vision due to its potential human-computer interface (HCI) and surveillance. Among those existing recognition techniques for human motions, head detection and tracking is basis for all human motion recognitions. Various approaches have been tried to detect and trace the position of human head in two-dimensional (2D) images precisely. However, it is still a challenging problem because the human appearance is too changeable by pose, and images are affected by illumination change. To enhance the performance of head detection and tracking, the real-time three-dimensional (3D) data acquisition sensors such as time-of-flight and Kinect depth sensor are recently used. In this paper, we propose an effective feature extraction method, called adaptive local binary pattern (ALBP), for depth image based applications. Contrasting to well-known conventional local binary pattern (LBP), the proposed ALBP cannot only extract shape information without texture in depth images, but also is invariant distance change in range images. We apply the proposed ALBP for head detection and tracking in depth images to show its effectiveness and its usefulness.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.991-995
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• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.