• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.47-56
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• 2009

Effective detection and correction of outliers of raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning system (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposed a locally weighted regression (LWR) based filtering method for individual vehicle speed data. An important feature of this study was to propose a technique to generate synthetic outliers for more systematic evaluation of the proposed method. It was identified by performance evaluations that the proposed LWR-based method outperformed an exponential smoothing. The proposed method is expected to be effectively utilized for filtering out raw individual vehicle speed data.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.235-238
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• 2009

The character design is part of a culture. That is, it is not just an object but it reflects the cultural tendency and context where it is visualized. It's potential as a cultural medium of communication become pervasive in the field. One of good sources of characters is the classics which represent the nation's culture and history. The topic of this presentation is to show how a character in the Buddhist story, the Monkey King, designed differently in different context. For the purpose, the animation on the Monkey King in China, Japan and Korea are reviewed and analyzed. The result shows that the same animation character has been designed in different way in different context and it reflects the cultural tendency of the country. For example, Koreans tend to emphasize the global feature of the character. In case of Chinese, however, the character designer emphasizes traditional value. Finally, the designer in Japan tries to put their cultural element in detailed part of the character that makes it appeal to the public.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.669-676
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• 2006

In this paper, we present a new framework and stream synchronization mechanism to effectively support developing real-time multimedia streaming services by using a real-time object model named TMO (Time-triggered Message-triggered Object). The purpose of the framework is twofold. Firstly, the framework helps developers to design complex distributed real-time multimedia streaming services. Secondly, it supports timely streaming facilities. In order to achieve these goals, our framework is consist of Multimedia Streaming TMO, MMStreaming TMO Support Library and TMO Support Middleware. The time-triggered spontaneous feature of the MMStream TMO and a global-time based synchronization scheme is used as a regulator against the irregular deliveries and processing of media units caused by QoS non-guaranteed systems and communication channels. In conclusion, timely service capability of our framework is expected to contributed to overall enhancement of the real-time multimedia streaming.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.441-458
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• 2006

Culture is an indispensable element in modern society in improving the quality of life for city dwellers and stimulating the urbanization. The conspicuous emergence of cultural cities, which is a new paradigm, can be understood in that context. Global cities are pursuing cultural cities, and autonomous regions in Korea are also pushing ahead with the urbanization which combines cultural elements. Specifically, Nam-gu of Incheon has set an example of successful cultural city for other autonomous regions. The cultural environmental policy of Nam-gu is deemed to have retained the infrastructure, cultural urban landscape and living space, and a plenty of contents. The real significance of cultural city lies in the pursuit of sustainable urban development as a culture-friendly city. For that, the direction of cultural environmental city has to be firmly set, and related law and system should be strengthened. Above all, it is critical to pursue human-oriented cultural city by showing citizens what roles they have to play, setting the right direction, and improving the partnership.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.5 no.2
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• pp.269-279
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• 1998

In nursing research that the data is collected through clinical observation, analysis of clinical recording or coding of interpersonal interaction in clinical areas, testing and reporting interrater reliability is very important to assure reliable results. Procedures for interrater reliability in these studies should follow two steps. The first step is to determine unitizing reliability, which is defined as consistency in the identification of same data elements in the record by two or more raters reviewing the same record. Unitizing reliability have been rarely reported in previous studies. Unitizing reliability should be tested before progressing to the next step as precondition. Next step is to determine interpretive reliability. Cohen's kappa is a preferable method of calculating the extent of agreement between observer or judges because it provides beyond-chance agreement. Despite its usefulness, kappa can sometimes present paradoxical conclusions and can be difficult to interpret. These difficulties result from the feature of kappa which is affected in complex ways by the presence of bias between observers and by true prevalence of certain categories. Therefore, percentage agreement should be reported with kappa for adequate interpretation of kappa. The presence of bias should be assessed using the bias index and the effect of prevalence should be assessed using the prevalence index. Researchers have been reported only global reliability reflecting the extent to which coders can consistently use the whole coding system across all categories. Category-by-category reliability also need to be reported to inform the possibility that some categories are harder to use than others.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.595-597
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• 2015

In recent years, global Internet of Things is being fostered by strategic industry in major countries (IoT: Internet of Things) technology is the future Internet -based context-aware infrastructure capable of communication between objects and things. Existing technology was only a single device control via P2M (Puman to Machine) method and simple sensor data to someone directly control the devices down command. However, a kind of IoT Machine Socialization of devices, each device uses an internal feature information, and M2M (Machine to Machine) devices in ways that expand the overall scenario collaboration system through the Device Manager. In this paper, an algorithm of the whole system of the Machine Socialization for changing the system of the conventional system of P2M by M2M, and analysis.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.133-140
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• 2011

Recently, Web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hash techniques are used for the image registration, management and retrieval as the identifier and many researches have been performed to raise the hash performance. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which based on histogram bin population method. So far, many researches have proven that image hashing techniques based on histogram are robust image processing and geometrical attack. We modified existing image hashing method developed by our research team. The main idea is that it makes more fluent hash string if we have histogram bin of specific length as shown in the body of paper. Finally, we can raise the magnitude of hash string within same context or feature and strengthen the robustness of hash.