• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1718-1721
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• 2020

This paper proposes a method to protect the copyright of creators' content shared through an online sharing platform in a legal battle. When creators upload their independent creation content to the online sharing platform, it automatically upload information necessary for copyright effect to this system. The data warehouse of this system is as a private blockchain for to ensure non-repudiation and transparency of the information. We present that the data warehouse is to build as Hyperledger Fabric in this paper. And We present the transaction data structure of the blockchain to prevent orphan works. We also dealt with how to build a website where users can conveniently check the data (copyright related information) of this blockchain.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.203-209
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• 2016

Among the various fields in the communications, navigation, and surveillance/air traffic management (CNS/ATM) scheme, the surveillance field, which includes an automatic dependent surveillance - broadcast (ADS-B) system and a multilateration (MLAT) system, is implemented using satellite and digital communications technology. These systems provide better performance than radar, but still incur position error. To reduce the error, we propose an efficient information fusion method called the reweighted convex combination method for ADS-B and MLAT systems. The reweighted convex combination method improves aircraft tracking performance compared to the original convex combination method by readjusting the weights given to these systems. In this paper, we prove that the reweighted convex combination method always provides better performance than the original convex combination method. Performance from the fusion of ADS-B and MLAT improves an average of 51.51% when compared to the original data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.5
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• pp.517-526
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• 2015

This paper presents the results of study for improving the reliability of quadrotor attitude control by applying a multi-sensor along with a data fusion algorithm. First, a mathematical model of the quadrotor dynamics was developed. Then, using the quadrotor mathematical model, simulations were performed using the improved reliability multi-sensor data as the inputs. From the simulation results, we designed a Gimbal-equipped quadrotor system. With the quadrotor in a hover state, we performed experiments according to the angle change of the user's specifications. We then calculated the attitude control data from the actual experimental data. Furthermore, with additional simulations, we verified the performance of the designed quadrotor attitude control system with multiple sensors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.223-235
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• 2020

In this study, we propose an approach for calibrating the elevation of a DEM (Digital Elevation Model), one of the key data in realizing unmanned aerial vehicle image-based precision agriculture. First of all, radiometric correction is performed on the orthophoto, and then ExG (Excess Green) is generated. The non-vegetation area is extracted based on the threshold value estimated by applying the Otsu method to ExG. Subsequently, the elevation of the DEM corresponding to the location of the non-vegetation area is extracted as EIFs (Elevation Invariant Features), which is data for elevation correction. The normalized Z-score is estimated based on the difference between the extracted EIFs to eliminate the outliers. Then, by constructing a linear regression model and correcting the elevation of the DEM, high-quality DEM is produced without GCPs (Ground Control Points). To verify the proposed method using a total of 10 DEMs, the maximum/minimum value, average/standard deviation before and after elevation correction were compared and analyzed. In addition, as a result of estimating the RMSE (Root Mean Square Error) by selecting the checkpoints, an average RMSE was derivsed as 0.35m. Comprehensively, it was confirmed that a high-quality DEM could be produced without GCPs.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of Internet of Things and Convergence
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• v.4 no.1
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• pp.1-5
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• 2018

This paper is concerned with the modeling and identification of time series data corrupted by noise. As modeling techniques, nonsingleton fuzzy logic system (NFLS) is employed for the modeling of corrupted time series. Main characteristic of the NFLS is a fuzzy system whose inputs are modeled as fuzzy number. So the NFLS is especially useful in cases where the available training data or the input data to the fuzzy logic system are corrupted by noise. Simulation results of the Mackey-Glass time series data will be demonstrated to show the performance of the modeling methods. As a result, NFLS does a much better job of modeling noisy time series data than does a traditional Mamdani FLS.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.127-137
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• 2009

Web Game provides computer games through a web browser, and have several benefits. First, we can access the game through web browser easily if we are connected to the internet environment. Second, usually we don't need much space of a game data for downloading it into a local disk. Nowadays, an industry area of Web Game has a chance to grow through advancements of mobile computing technologies and an age of Web 2.0. This study proposes a Web Game system that users can apply to manipulate the game with multimodal interfaces and mobile devices for intuitive interactions. In this study, multi modal interfaces are used to efficient control the game, and both ordinary computers and mobile devices are applied to the game scenarios. The proposed system is evaluated in both performance and user acceptability in comparison with previous approaches. The proposed system reduces total clear time and numbers of errors of the experiment in a mobile device. It can also provide good satisfactions of users.

• The Korean Journal of Pain
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• v.34 no.2
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• pp.193-200
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• 2021

Background: Local anesthetic infiltration at the site of a surgical wound is commonly used to control postoperative pain. In this study, we examined the effectiveness of continuous local infiltration at an abdominal surgical site in patients undergoing anterior lumbar interbody fusion (ALIF) surgery. Methods: Sixty-one patients who underwent ALIF surgery were enrolled. For thirtyone of them, a continuous local anesthetics infiltration system was used at the abdominal site. We collected data regarding the patients' sleep quality; satisfaction with pain control after surgery; abilities to perform physical tasks and the additional application of opioids in the postoperative 48 hours. Results: The On-Q system group showed reduced visual analogue scale scores for pain at the surgical site during rest and movement at 0, 12, 24, and 48 hours; and more was satisfied with pain control management at the first postoperative day (7.0 ± 1.2 vs. 6.0 ± 1.4; P = 0.003) and week (8.1 ± 1.6 vs. 7.0 ± 1.8; P = 0.010) than the control group. The number of additional patient-controlled analgesia (PCA) bolus and pethidine injections was lower in the On-Q group (PCA: 3.67 ± 1.35 vs. 4.60 ± 1.88; P = 0.049 and pethidine: 2.09 ± 1.07 vs. 2.73 ± 1.38; P = 0.032). Patients who used the On-Q system performed more diverse activity and achieved earlier ambulation than those in the control group. Conclusions: Continuous wound infiltration with ropivacaine using an On-Q system may be effective for controlling postoperative pain after ALIF surgery.