• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.811-820
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• 2012

GNSS signal is vulnerable to jamming signal because of well-known signal structure and weak signal power. For these reasons, the need for analysis of jamming effects and anti-jamming techniques of is increasing. In this paper, a GNSS signal generator is designed which includes a radio wave propagation model for six kind of tactical environments and a body masking model for the reception environment of a vehicle. The radio wave propagation model for downtown, rural, forest, coastline, waste land and snow or ice area is designed using two-ray model. The body masking model is designed the effect which the antenna is affected by the reception environment of a vehicle and radiation pattern from a user configuration. The performance of generated signals from the GNSS signal generator considering reception environment of a vehicle is evaluated by a commercial GPS L1 receiver(NordNav) in normal and jamming environment. Also, the generated GNSS signal is compared to a commercial GPS L1 H/W based RF signal generator(STR4500). The results show that the designed GNSS signal generator in a normal environment compared to the same navigation performance. In jamming environment, it is shown that the body masking effect and GNSS signal acquisition and tracking loss in compliance with the jamming signal are precisely working in the reception environment of a vehicle.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.137-148
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• 2004

In this paper, we propose a new camera calibration method for rotating multi-view cameras to generate image-based panoramic 3D Virtual Environment. Since calibration accuracy worsens with an increase in distance between camera and calibration pattern, conventional camera calibration algorithms are not proper for panoramic 3D VE generation. To remedy the problem, a geometric relationship among all lenses of a multi-view camera is used for intra-camera calibration. Another geometric relationship among multiple cameras is used for inter-camera calibration. First camera parameters for all lenses of each multi-view camera we obtained by applying Tsai's algorithm. In intra-camera calibration, the extrinsic parameters are compensated by iteratively reducing discrepancy between estimated and actual distances. Estimated distances are calculated using extrinsic parameters for every lens. Inter-camera calibration arranges multiple cameras in a geometric relationship. It exploits Iterative Closet Point (ICP) algorithm using back-projected 3D point clouds. Finally, by repeatedly applying intra/inter-camera calibration to all lenses of rotating multi-view cameras, we can obtain improved extrinsic parameters at every rotated position for a middle-range distance. Consequently, the proposed method can be applied to stitching of 3D point cloud for panoramic 3D VE generation. Moreover, it may be adopted in various 3D AR applications.

• Journal of Environmental Impact Assessment
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• v.27 no.5
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• pp.475-488
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• 2018

Surveying urban tributary vegetation is based mainly on field sampling at present. The tributary vegetation survey integrating UAV NIR(Unmanned Aerial Vehicle Near Infrared Radiance) imagery and in-situ point photo has received only limited attentions from the field ecologist. The reason for this could be the largely undemonstrated applicability of UAV NIR imagery by the field ecologist as a monitoring tool for urban tributary vegetation. The principal advantage of UAV NIR imagery as a remote sensor is to provide, in a cost-effective manner, information required for a very narrow swath target such as urban tributary (10m width or so), utilizing very low altitude flight, real-time geo-referencing and stereo imaging. An exhaustive and realistic comparison of the two techniques was conducted, based on operational customer requirement of urban tributary vegetation survey: synoptic information, ground detail and quantitative data collection. UAV NIR imagery made it possible to identify area-wide patterns of the major plant communities subject to many different influences (e.g. artificial land use pattern), which cannot be acquired by traditional field sampling. Although field survey has already gained worldwide recognition by plant ecologists as a typical method of urban tributary vegetation monitoring, this approach did not provide a level of information that is either scientifically reliable or economically feasible in terms of urban tributary vegetation (e.g. remedial field works). It is anticipated that this research output could be used as a valuable reference for area-wide information obtained by UAV NIR imagery in urban tributary vegetation survey.

• Analytical Science and Technology
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• v.26 no.4
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• pp.245-255
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• 2013

Identification of paint on victim's clothing and a vehicle are valuable for forensic examination when investigating hit-and-run accidents. Automotive paints on clothes are used to prove a victim caused by traffic accident and to identify a suspected vehicle. The comparison of transferred paints between victim's vehicle and suspected vehicle can be an important evidence in reconstructing the accident situation and in discovering the truth. The paints such as white, yellow, red, blue, or black are hard to examine particle shape under a stereomicroscope because of it is not included aluminum, pearl, and mica flakes in the pigments. The aim of this study under forensic aspect is to compare pigment among basecoat layers of solid paints by identifying inorganic elemental compositions and binder resins of pigments using by micro-FT-IR and micro-XRF spectrometer. The pigment samples were analyzed by using two methods of FT-IR: Reflectance and ATR method. Two methods of FT-IR were useful in discriminating binder resins of pigments by comparing characteristic peaks and patterns of spectra. Also, XRF spectrometer could identify the elemental compositions in inorganic pigments of trace paints which are difficult to compare the identification by FT-IR.

• Journal of KIISE:Information Networking
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• v.32 no.5
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• pp.615-624
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• 2005

In Mobile IP, several types of messages - binding update, binding request and binding acknowledgement - are used to support user mobility. It is necessary to exchange those messages frequently for seamless mobility but it incurs both the increase of network overhead and poor usage of mobile node battery power Thus, we need a mechanism that the server detects users location and also copes with the problems effectively, which is our main concern in this paper Each user records all moving logs locally and periodically makes out profile based on them in HMIPv6. By using profile, estimated resident time can be computed whenever he enters an area and the time is set up as the binding update message lifetime. Of course, the more correct lifetime nay be obtained IP arrival time as well as average resident time Is considered in profile. Through extensive experiments, we measure the bandwidth usage for binding update messages by comparing the proposed schemes with that in HMIPv6. From the results, Gain gets over $80\%$ when mobile node stays more than 13 minutes in a subnet. Namely, we come to know that our schemes improve network usage and energy usage in mobile node by decreasing the number of messages while they also manage users locations like that in HMIPv6.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of Aquaculture
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• v.20 no.2
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• pp.90-95
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• 2007

Artificially-produced juvenile black sea bream, Acanthopagrus schlegeli (total length $10.4{\pm}1.1\;cm$, body weight $18.7{\pm}3.4\;g$) were released into the Gamak Bay in Korea. And their initial feeding habits and body compositions were compared with those of cultured fish (CUL) for a period of one month after release. The released black sea bream commenced feeding on the 1st day after release, and predation rate was more than 80% during the sampling period. The stomach content of fish was composed of mainly fishing bait and krill in fish sampled on 15th days after release; however, its content changed to the natural organisms such as algae and small crustaceans when the fish was sampled on 20th days after release. Crude lipid content of carcass of fish in the sampling station A (SA) were lower than that of fish in the initial, sampling station B (SB) and CUL for the 5th and 10th days after release. Carcass n-3 HUFA composition, total amino acid and essential amino acid contents of released fish showed high trend compared to that of cultured fish in 30th days after release. The released fish have the ability to adjust their feeding habits and biochemical metabolism to the natural environment within a short period even though they showed preference to artificial feed in the early days after release.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.27-40
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• 2020

In this paper, we investigate the correlation between the amount of English sentences that Korean English learners (L2ers) are exposed to and their sentence processing patterns by examining what Long Short-Term Memory (LSTM) language models (LMs) can learn about implicit syntactic relationship: that is, the filler-gap dependency. The filler-gap dependency refers to a relationship between a (wh-)filler, which is a wh-phrase like 'what' or 'who' overtly in clause-peripheral position, and its gap in clause-internal position, which is an invisible, empty syntactic position to be filled by the (wh-)filler for proper interpretation. Here to implement L2ers' English learning, we build LSTM LMs that in turn learn a subset of the known restrictions on the filler-gap dependency from English sentences in the L2 corpus that L2ers can potentially encounter in their English learning. Examining LSTM LMs' behaviors on controlled sentences designed with the filler-gap dependency, we show the characteristics of L2ers' sentence processing using the information-theoretic metric of surprisal that quantifies violations of the filler-gap dependency or wh-licensing interaction effects. Furthermore, comparing L2ers' LMs with native speakers' LM in light of processing the filler-gap dependency, we not only note that in their sentence processing both L2ers' LM and native speakers' LM can track abstract syntactic structures involved in the filler-gap dependency, but also show using linear mixed-effects regression models that there exist significant differences between them in processing such a dependency.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1597-1609
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• 2004

A lot of lipreading system has been proposed to compensate the rate of speech recognition dropped in a noisy environment. Previous lipreading systems work on some specific conditions such as artificial lighting and predefined background color. In this paper, we propose a real-time lipreading system which allows the motion of a speaker and relaxes the restriction on the condition for color and lighting. The proposed system extracts face and lip region from input video sequence captured with a common PC camera and essential visual information in real-time. It recognizes utterance words by using the visual information in real-time. It uses the hue histogram model to extract face and lip region. It uses mean shift algorithm to track the face of a moving speaker. It uses PCA(Principal Component Analysis) to extract the visual information for learning and testing. Also, it uses HMM(Hidden Markov Model) as a recognition algorithm. The experimental results show that our system could get the recognition rate of 90% in case of speaker dependent lipreading and increase the rate of speech recognition up to 40～85% according to the noise level when it is combined with audio speech recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.473-476
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• 2007

Location determination of mobile user via RSSI approach has received ample attention from researchers lately. However, it remains a challenging issue due to the complexities of RSSI signal propagation characteristics, which are easily exacerbated by the mobility of user. Hence, a segmentation-based linear spline interpolation method is proposed to cater for the dynamic fluctuation pattern of radio signal in complex environment. This optimization algorithm is proposed in addition to the current radiolocation's (CC2431, Chipcon, Norway) algorithm, which runs on IEEE802.15.4 standard. The enhancement algorithm involves four phases. First phase consists of calibration model in which RSSI values at different static locations are collected and processed to obtain the mean and standard deviation value for the predefined distance. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the user is moving. Distances are computed using the segmentation formula obtain in the first phase. In situation where RSSI value falls in more than one segment, the ambiguity of distance is solved by probability approach. The distance probability distribution function(pdf) for each distances are computed and distance with the highest pdf at a particular RSSI is the estimated distance. Finally, with the distances obtained from each reference node, an iterative trilateration algorithm is used for position estimation. Experiment results obtained position the proposed algorithm as a viable alternative for location tracking.