• Proceedings of the Korea Multimedia Society Conference
• /
• 2004.05a
• /
• pp.774-777
• /
• 2004

RAIM techniques based on TLS have rarely born addressed because TLS requires a great number of computations. In this paper, the special form of the observation matrix H, that is, one column is exactly known, is exploited so as to develop a new TLS-based sequential algorithm to identify an errant satellite. The algorithm makes us enjoy the advantages of TLS with less computational burden. The proposed algorithm is verified through a numerical simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.4
• /
• pp.321-326
• /
• 2009

The mobile air cleaner analyzes a distribution of polluted air to purify the air fast, calculates an optimal position and moves the position so that it can remove indoor dust more quickly. At this time, the self-localization is necessary to make the mobile air cleaner move accurately to the calculated position. This paper proposed a self-localization algorithm having high accuracy without complicated calculation and implemented it by combining a ultrasonic sensor and video processing technologies, so that it is suitable for a mobile air cleaner, and as a test result, the mean error of $\pm1cm$ appeared between the actually measured position and the calculated position.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.41 no.2
• /
• pp.17-25
• /
• 2004

In this Paper, new data matrix structure and respective processing algorithm for digital holographic storage are Proposed. Data matrix consists of user data and reference grid which is used to compensate geometrical errors such as magnification, shift and rotation of stored information. Processing algorithm identifies the location of reference grid and extracts user data. As a result of experiment, raw BER in case of shit, rotation and magnification are 3.09${\times}$10$^{-18}$ , 6.14${\times}$10$^{-12}$ , 1.2${\times}$10$^{-7}$ , respectively.

• ETRI Journal
• /
• v.28 no.3
• /
• pp.320-328
• /
• 2006

Using biometrics to verify a person's identity has several advantages over the present practice of personal identification numbers (PINs) and passwords. To gain maximum security in a verification system using biometrics, the computation of the verification as well as the storing of the biometric pattern has to take place in a smart card. However, there is an open issue of integrating biometrics into a smart card because of its limited resources (processing power and memory space). In this paper, we propose a speaker verification algorithm using a support vector machine (SVM) with a very few features, and implemented it on a 32-bit smart card. The proposed algorithm can reduce the required memory space by a factor of more than 100 and can be executed in real-time. Also, we propose a hardware design for the algorithm on a field-programmable gate array (FPGA)-based platform. Based on the experimental results, our SVM solution can provide superior performance over typical speaker verification solutions. Furthermore, our FPGA-based solution can achieve a speed-up of 50 times over a software-based solution.

• Journal of Sensor Science and Technology
• /
• v.25 no.6
• /
• pp.431-434
• /
• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• Atmosphere
• /
• v.30 no.4
• /
• pp.335-346
• /
• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• Proceedings of the KIEE Conference
• /
• 1998.11b
• /
• pp.648-650
• /
• 1998

This paper proposes a constructive algorithm for generating the Takagi-Sugeno type fuzzy model through the sequential learning from training data set. The proposed algorithm has a two-stage learning scheme that performs both structure and parameter learning simultaneously. The structure learning constructs fuzzy model using two growth criteria to assign new fuzzy rules for given observation data. The parameter learning adjusts the parameters of existing fuzzy rules using the LMS rule. To evaluate the performance of the proposed fuzzy modeling approach, well-known benchmark is used in simulation and compares it with other modeling approaches.

• Korean Chemical Engineering Research
• /
• v.47 no.5
• /
• pp.565-571
• /
• 2009

This study was conducted to evaluate hydrocarbon and water dew points of natural gas. For this purpose, algorithm of suppressing divergence was devised to evaluate hydrocarbon dew point up to near critical point and algorithm for finding water dew points lower than that of hydrocarbon, which cannot be calculated by commercial dew point program, was developed. The evaluated values were compared to commercial program and ISO reference values, and the results showed that deviations were zero.

• ETRI Journal
• /
• v.44 no.6
• /
• pp.1020-1033
• /
• 2022

In this paper, we propose novel disaggregated memory module (dMM) architecture and memory access control schemes to solve the collision and contention problems of memory disaggregation, reducing the average memory access time to less than 1 ㎲. In the schemes, the distributed scheduler in each dMM determines the order of memory read/write access based on delay-sensitive priority requests in the disaggregated memory access frame (dMAF). We used the memory-intensive first (MIF) algorithm and priority-based MIF (p-MIF) algorithm that prioritize delay-sensitive and/or memory-intensive (MI) traffic over CPU-intensive (CI) traffic. We evaluated the performance of the proposed schemes through simulation using OPNET and hardware implementation. Our results showed that when the offered load was below 0.7 and the payload of dMAF was 256 bytes, the average round trip time (RTT) was the lowest, ~0.676 ㎲. The dMM scheduling algorithms, MIF and p-MIF, achieved delay less than 1 ㎲ for all MI traffic with less than 10% of transmission overhead.

• Journal of Biosystems Engineering
• /
• v.38 no.1
• /
• pp.18-24
• /
• 2013

Purpose: This study was conducted to develop an optimal combine scheduling program using Max-Coverage algorithm which derives the maximum efficiency for a specific location in harvest seasons. Methods: The combine scheduling program was operated with information about combine specification and farmland. Four operating types (Max-Coverage algorithm type, Boustrophedon path type, max quality value type, and max area type) were selected to compare quality and working capacity. Result: The working time of Max-Coverage algorithm type was shorter than others, and the total quality value of Max-Coverage algorithm and max quality value type were higher than others. Conclusion: The developed combine scheduling program using Max-Coverage algorithm will provide optimal operation and maximum quality in a limited area and time.