• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.4
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• pp.446-456
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• 2024

This paper addresses a novel approach to performance enhancement of the naval gun fire control system(FCS) by using the projectile tracking filter without any distortion of radar measurements. Under the assumption that the maneuvering between the projectile and the ship equipped with the radar is not quite large, this method is based on the concept of polar-coordinate target tracking, which separates the range estimation filter and the direction cosine estimation filter. Note that using polar-coordinates allows tracking to be performed in the same coordinate system from which the radar line-of-sight(LOS) measurements are obtained, unlike the conventional tracking process in Cartesian. Also, it is easy to implement in real-time and guarantees consistent estimates due to its linear filter structure. With the help of the above method, therefore, the proposed filter is able to improve the overall performance of FCS which requires stability of projectile estimates within a short engagement time. The effectiveness of the presented scheme is validated through computer simulations.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.512-517
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• 2007

There are several researches on 2D gaze tracking techniques for the 2D screen for the Human-Computer Interaction. However, the researches for the gaze-based interaction to the stereo images or contents are not reported. The 3D display techniques are emerging now for the reality service. Moreover, the 3D interaction techniques are much more needed in the 3D contents service environments. This paper addresses gaze-based 3D interaction techniques on stereo display, such as parallax barrier or lenticular stereo display. This paper presents our researches on 3D gaze estimation and gaze-based interaction to stereo display.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.379-385
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• 2020

The satellite employs an adaptive beamformer to efficiently detect various signals and to suppress multiple interference signals, simultaneously. Although the adaptive beamforming satellite system needs Angle-of-Arrival (AOA) information of the desired signal, it is difficult to estimate the signal AOAs on the satellite environment. However, the AOA estimation on the ground control tower is more efficient and accurate comparing to the satellite environment. In this paper, we propose an adaptive beamforming satellite system based on the signal location information on the ground, consisting on an angle estimator, an adaptive beamformer, and signal processing & D/B unit. The ground control tower estimates the accurate location of the signal source, and it sends the estimated coordinates of the desired signal to the satellite. The angle estimator mounted on the satellite calculates the desired signal AOA, based on the signal location information transmitted from the ground control center. The satellite beamformer detects the desired signal and suppresses unwanted signals based on the signal AOA calculated by the angle estimator. We provide computer simulation results to present the performance of the proposed satellite adaptive beamforming system based on the signal location information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.1
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• pp.45-53
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• 2000

The optimum operation of domestic wastewater treatment plant can give influence on operational cost and future expansion in Korea where has 93 operational domestic wastewater treatment plants. Also, the study on optimum operation can reduce operation cost and budget of municipalities whom have responsibility of wastewater treatment plant operation. In this study, 9 domestic wastewater treatment plants which can represent 93 plants in Korea have been selected and operational data are gathered. The collected data are inputted to computer simulator based on IAWQ's Activated Sludge Model No.1 and optimum operation methods are developed. Also, the electric power for aeration which has large portion of overall operation cost are calculated based on design and operation conditions and these are compared. In this study, it was found that design wastewater characteristics are 1.6 times higher than those of daily maximum except for E plant and that estimation methods for design wastewater characteristics have to be improved. Based on computer simulation, we found there is no need to operate all aeration tanks due to weak influent overall power for aeration can be reduced to about 43% of design one.

• The Journal of Korean Association of Computer Education
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• v.14 no.4
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• pp.63-70
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• 2011

Recommender systems, which predict and recommend items that may possibly draw users' interests, have been applied in various fields as e-commerce systems are widespread. Collaborative filtering, one of the major methodologies of recommender systems, recommends either items similar to those preferred by the user, or items preferred by the other similar user. Therefore, two problems determine its performance; one is correct estimation of similarity and the other is predicting the real rating of the recommended item. This study addresses the latter problem. Previous studies predict the real rating based on the mean of the ratings, but this study proposes a prediction based on the range of the ratings and investigates its performance through experiments. As a result, it is demonstrated that the proposed method improves the mean absolute error significantly, compared to the previous method.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1587-1598
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• 2000

For the object-based video compression at very low bit rate, vieo segmentation is an essential part. In this paper, we propose a temporal video segmentation algorithms for motion pictures which is based on blocks. The algorithm is composed of three steps: (1) the change-detection, (2) the block merging, and (3) the block segmentation. The first step separates the change-detected region from background. Here, a new method for removing the uncovered region without motion estimation is presented. The second step, which is further divided into three substeps, estimates motions for the change-detected region and merges blocks with similar motions. The merging conditions for each substep as criteria are also given. The final step, the block segmentation, segments the boundary block that is excluded from the second step on a pixel basis. After describing our algorithm in detail, several experimental results along the processing order are shown step by step. The results demonstrate that the proposed algorithm removes the uncovered region effectively and produced objects that are segmented well.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.27-35
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• 2016

Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance. They are applied in various fields such as inductive inferences, classifications, or regressions. However, by its characteristics, they cannot provide appropriate explanations how the classification results are derived. Therefore, there are plenty of actively discussed researches about interpreting trained black-box classifiers. In this paper, we propose a method to make a fuzzy logic-based classifier using extracted rules from the artificial neural network and support vector machine in order to interpret internal structures. As an object of classification, an anomalous propagation echo is selected which occurs frequently in radar data and becomes the problem in a precipitation estimation process. After applying a clustering method, learning dataset is generated from clusters. Using the learning dataset, artificial neural network and support vector machine are implemented. After that, decision trees for each classifier are generated. And they are used to implement simplified fuzzy logic-based classifiers by rule extraction and input selection. Finally, we can verify and compare performances. With actual occurrence cased of the anomalous propagation echo, we can determine the inner structures of the black-box classifiers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.639-640
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• 2006

Many companies in mechanical engineering fields have accumulated information of design and manufacturing. The Enterprise Resource Planning (ERP) and Product Data Management (PDM) systems help information gathering and data managing. However, these systems are not flexible to support suitable functionality for specific product because these systems deal with entire enterprise resources. To cope with this issue, a web-based design support system was constructed for the design process of automotive steel pulley. This system provided 1) search service for part design with key word and clustering map, and 2) estimation service of maximum stress. These services reduced design time by reducing iterative jobs with Computer Aided Design (CAD) and Computer Aided Engineering (CAE) for stress analysis, and by enhancing search for existing data of steel pulley.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.1-8
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• 2006

Network measurement is a vital part of network traffic engineering. In a network, the metric 'capacity' characterizes the maximum throughput the path can provide when there is no traffic load, or the minimum transmission rate among all links in a path. Pathrate is one of the most widely used network capacity measurement tools nowadays. It's famous for its accurate estimation result and non restriction of the temporal network traffic condition. After several years of development, its performance becomes more stable and reliable. Extant local modes detection algorithm in pathrate is based on statistic methodology histogram. This paper suggests a new algorithm for local modes detection based on ASH (Averaged Shifted Histogram). We have implemented this algorithm and will prove it can accomplish the same task as the original one with a better result.