• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.169-176
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• 2018

CS Unplugged education at the base of computer science is emphasized as an instrument for teaching the basic principles of elementary SW education, but these materials for elementary education are very lacking. So We'll present the data error detection and correction materials for elementary school classes. Based on previous studies related to this topic, we developed learning materials for elementary higher grade students using Hamming code. We introduces the card magic in the introduction part. 'error detection and correction' learning materials based on the principle of Hamming code, were composed as activity-based education. The results of the questionnaire survey showed that it had a positive effect on improving learners' understanding of computer science.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.1-6
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• 2007

In order to operate a secure network, it is very important for the network to raise positive detection as well as lower negative detection for reducing the damage from network intrusion. By using SVM on the intrusion detection field, we expect to improve real-time detection of intrusion data. However, due to classification based on calculating values after having expressed input data in vector space by SVM, continuous data type can not be used as any input data. Therefore, we present the hybrid model between SVM and decision tree method to make up for the weak point. Accordingly, we see that intrusion detection rate, F-P error rate, F-N error rate are improved as 5.6%, 0.16%, 0.82%, respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.51-56
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• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.413-423
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• 2022

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.1 s.106
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• pp.27-33
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• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.243-248
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• 2007

This study proposed a procedure to improve the error defection of attached cadastral maps using digital map data. In addition, this study also provided the direction for the accuracy improvement of attached cadastral maps by comparing analysis methods. - such as centroid, Lee Sallee shape index, and area index. The analysis is performed as follows. First, by using centroid measurement, the center point of cadastral maps and attached cadastral maps are compared. Secondly by using Lee Sallee shape measurement, the location accuracy of range area is investigated. Thirdly, by using area measurement, the range area within allowable error scope is verified. Based on analysis, the discrepancy between cadastral maps and the attacked cadastral maps are detected as follows; 98.2% from Lee Sallee shape index, 41.8% from centroid, 15.4% from area index in the whole error.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.228-233
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• 2000

It is common to apply the technology of FPGA (Fie이 Programmable Gate Array) which is one of the design methods for ASIC(Application Specific IC)to the active components used in the data processing at the digital system of satellite aircraft missile etc for compact lightness and integration of Printed Circuit Board (PCB) In carrying out the digital data processing the FPGAs are designed for the various functions of the Process Control Interrupt Control Clock Generation Error Detection and Correction (EDAC) as the individual module. In this paper an FPGA chip for Single Error Correction and Double Error Detection (SEC-DED) for EDAC is designed and simulated by using a VLSI design software LODECAP.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.17-22
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• 2018

In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.677-685
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• 2008

This paper proposes algorithm for the obstacle detection and classification using a single laser scanner. In a measurement data from a laser scanner, there exist points with large differential value called singular points, which can be used to obtain the boundary of an obstacle such that obstacle information can be analyzed. On the other hand, measurement data include a lot of measurement error, which makes it difficult to analyze the accurate obstacle information. To solve this problem, the least square estimation algorithm is used to obtain the accurate information using a single laser scanner, by compensation for the measurement error. This algorithm can be used for the effective obstacle avoidance of mobile robots, and the experimental results are included to demonstrate the effectiveness of the propose algorithm.

• ETRI Journal
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• v.45 no.6
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.