• Korean Journal of Remote Sensing
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• v.31 no.1
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• pp.1-9
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• 2015

Mobility and cloud platform have become the dominant paradigm to develop web services dealing with huge and diverse digital contents for scientific solution or engineering application. These two trends are technically combined into mobile cloud computing environment taking beneficial points from each. The intention of this study is to design and implement a mobile cloud application for remotely sensed image fusion for the further practical geo-based mobile services. In this implementation, the system architecture consists of two parts: mobile web client and cloud application server. Mobile web client is for user interface regarding image fusion application processing and image visualization and for mobile web service of data listing and browsing. Cloud application server works on OpenStack, open source cloud platform. In this part, three server instances are generated as web server instance, tiling server instance, and fusion server instance. With metadata browsing of the processing data, image fusion by Bayesian approach is performed using functions within Orfeo Toolbox (OTB), open source remote sensing library. In addition, similarity of fused images with respect to input image set is estimated by histogram distance metrics. This result can be used as the reference criterion for user parameter choice on Bayesian image fusion. It is thought that the implementation strategy for mobile cloud application based on full open sources provides good points for a mobile service supporting specific remote sensing functions, besides image fusion schemes, by user demands to expand remote sensing application fields.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.848-854
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• 2000

Network management in TMN concerns to the operating system and communication equipments in network, and defines them as objects. GDMO(guidelines for the Definition of Managed Objects) is used to describe those objects. GDMO is not directly used for managing the network, but translated into a language with object-oriented paradigm. And GDMO refers to ASN.1(Abstract Syntax Notation One) for manage objects. This paper presents design and implementation techniques for the translator which automatically translates the specification of ASN.1 and GDMO to the object-oriented language for generating MIB(Managed object Instance Base). This system, unlike the existing source code generator, is designed to generate various object-oriented languages automatically, which are used to generate Managed object Instance Base(MIB). And the system includes various graphic user interface to enhance the development environment of ASn.1 and GDMO

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.14-21
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• 2005

Even though mainly statistical methods have been used in anomaly network intrusion detection, to detect various attack types, machine learning based anomaly detection was introduced. Machine learning based anomaly detection started from research applying traditional learning algorithms of artificial intelligence to intrusion detection. However, detection rates of these methods are not satisfactory. Especially, high false positive and repeated alarms about the same attack are problems. The main reason for this is that one packet is used as a basic learning unit. Most attacks consist of more than one packet. In addition, an attack does not lead to a consecutive packet stream. Therefore, with grouping of related packets, a new approach of group-based learning and detection is needed. This type of approach is similar to that of multiple-instance problems in the artificial intelligence community, which cannot clearly classify one instance, but classification of a group is possible. We suggest group generation algorithm grouping related packets, and a learning algorithm based on a unit of such group. To verify the usefulness of the suggested algorithm, 1998 DARPA data was used and the results show that our approach is quite useful.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.209-214
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• 2021

Panoptic segmentation, which is now widely used in computer vision such as medical image analysis, and autonomous driving, helps understanding an image with holistic view. It identifies each pixel by assigning a unique class ID, and an instance ID. Specifically, it can classify 'thing' from 'stuff', and provide pixel-wise results of semantic prediction and object detection. As a result, it can solve both semantic segmentation and instance segmentation tasks through a unified single model, producing two different contexts for two segmentation tasks. Semantic segmentation task focuses on how to obtain multi-scale features from large receptive field, without losing low-level features. On the other hand, instance segmentation task focuses on how to separate 'thing' from 'stuff' and how to produce the representation of detected objects. With the advances of both segmentation techniques, several panoptic segmentation models have been proposed. Many researchers try to solve discrepancy problems between results of two segmentation branches that can be caused on the boundary of the object. In this survey paper, we will introduce the concept of panoptic segmentation, categorize the existing method into two representative methods and explain how it is operated on two methods: top-down method and bottom-up method. Then, we will analyze the performance of various methods with experimental results.

• Advances in nano research
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• v.14 no.5
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• pp.409-419
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• 2023

Tracking the motion of tennis balls is a challenging task in using cameras around the tennis court. The most important instance of the tennis trajectory is the time of impact and touch the court which in some cases could not be detected precisely. In the present study, we aim to present a novel design of tennis balls equipped with nano-sensors to detect the touch of the ball to the court. In the impact instance, tennis ball receives significant acceleration and change in the linear momentum. This large acceleration could deform a small-beam structure with piezoelectric layer to produce voltage. The voltage could further be utilized to produce infrared waves which could be easily detected by infrared detection sensors installed on the same video cameras or separately near the tennis court. Therefore, the exact time of the impact could be achieved with higher accuracy than image analyzing method. A detailed dynamical property of such sensors is discussed using nonlinear beam equations. The results show that within the acceleration range of tennis ball during an impact, the piezoelectric patches of the nano-sensors in the tennis ball could produce enough voltages to propagate infrared waves to be detected by infrared detectors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.549-551
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• 2006

Vehicle License Plate Recognition System reads information from vehicles license plate using image detection devices. Of many applications provided by Vehicle License Plate Recognition System, some, such as speed enforcing system, can be problematic when the system incorrectly scans letters or numbers from a vehicle's license plate. Using Cautious Classifier avoids such problems by discarding the scanned information when the confidence level is doubted to be low. This study develops the License Plate Recognition System using Cautious Classifier and investigates effectiveness of applying the Weighted Instance Method to improve the performance of Cautious Classifier.

• Management Science and Financial Engineering
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• v.20 no.1
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• pp.17-19
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• 2014

In this paper, we consider an interesting variant of the inverse minimum traveling salesman problem. Given an instance (G, w) of the minimum traveling salesman problem defined on a metric space, we fix a specified Hamiltonian cycle $HC_0$. The task is then to adjust the edge cost vector w to w' so that the new cost vector w' satisfies the triangle inequality condition and $HC_0$ can be returned by the minimum spanning tree algorithm in the TSP-instance defined with w'. The objective is to minimize the total deviation between the original and the new cost vectors with respect to the $L_1$-norm. We call this problem the inverse metric traveling salesman problem against the minimum spanning tree algorithm and show that it is closely related to the inverse metric spanning tree problem.

• English Language & Literature Teaching
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• v.11 no.4
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• pp.97-120
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• 2005

Production and perception of second language sounds are typically influenced by second language learners' native language sounds. In this study we investigate how the Korean language influences Korean speakers' production of English alphabets. In the experiment conducted to prepare for this study 16 native speakers of Korean pronounced English alphabets. Then three native speakers of English evaluated the Korean subjects' pronunciation of them. The results show that the Korean subjects' native language (i.e., Korean) influences their production of the English alphabets. When Korean has sounds corresponding to English alphabets, the English subjects rate the Korean subjects' production of them good. For instance, Korean has voiceless stop phonemes, hence their production of English alphabets was rated good by the English subjects. The Korean subjects' production of English alphabets containing the sounds that do not exist in Korean was rated poor by the English subjects. For instance, Korean does not have voiced fricative phonemes, hence their production of English alphabets was rated poor.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.216-221
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• 2008

기업 업무활동의 글로벌화가 가속화 되어감에 따라 글로벌 요인을 반영한 통합 시스템의 구비가 절실하게 요구되고 있는 시점이다. 많은 기업들이 프로세스 경쟁력 강화를 위해 ERP 시스템을 구축해오고 있다. 기존의 ERP 시스템은 단위 사업장 중심의 프로세스 및 시스템 운영을 근간으로 하고 있기 때문에 글로벌 비즈니스 프로세스 및 시스템 운영에 대한 고려가 부족하다. 성공적인 글로벌 ERP의 통합을 위해서는 글로벌 표준화와 글로벌 IT 요건을 고려한 체계적인 구축방법론이 필요하다. 하지만 국내외를 막론하고 체계적으로 정리된 글로벌 ERP 구축 방법론은 제시가 부족한 실정이다. 본 논문에서는 글로벌 비즈니스의 효율적인 실행을 위한 표준 설계, 글로벌 IT 요건을 고려한 ERP 구축, 글로벌 시스템운영을 위한 관리방안을 포괄한 통합적인 접근법으로 효과적인 글로벌 ERP 구축을 위한 가이드 라인을 제시하였다.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.729-732
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• 2005

This paper describes a time-spatial domain model for simulating raw data acquisition of space-borne SAR system. The position, velocity and attitude information of the platform at a certain time instance is used for deriving sensor-target model. Ground target is modelled by a set of point scatters with reflectivity and two-dimensional ground coordinates. The signal received by SAR is calculated for each slow and fast time instance by integrating the reflectivity and phase values from all target point scatters. Different from frequency domain simulation algorithms, the proposed time domain algorithm can provide fully physical modelling of SAR raw data simulation without any assumptions or approximations.