• The KIPS Transactions:PartA
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• v.10A no.3
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• pp.181-188
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• 2003

We propose a heuristic on-line scheduling algorithm for the IRIS (Increasing Reward with Increasing Service) tasks, which has low computation complexity and produces total reward approximated to that of previous on-line optimal algorithms. The previous on-line optimal algorithms for IRIS tasks perform scheduling on all tasks in a system to maximize total reward. Therefore, the complexities of these algorithms are too high to apply them to practical systems handling many tasks. The proposed algorithm doesn´t perform scheduling on all tasks in a system, but on (constant) W´s tasks selected by a predefined task selection policy. The proposed algorithm is based on task selection policies that define how to select tasks to be scheduled. We suggest two simple and intuitive selection policies and a generalized selection policy that integrates previous two selection policies. By narrowing down scheduling scope to only W´s selected tasks, the computation complexity of proposed algorithm can be reduced to O(Wn). However, simulation results for various cases show that it is closed to O(W) on the average.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.215-218
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• 2009

In this paper, we analyze the performance of interpolation in demosaicing techniques for single sensor digital camera. We choose BI(bilinear interpolation), ACPI(adaptive color plane interpolation), ECI(effective color interpolation), Ideal ACPI, and EECI(Enhanced effective color interpolation) in the literature of demosacing techniques since they provide low-complexity and substantial image quality. We survey the algorithms and simulate them. To evaluate the methods in terms of objective image quality and complexity, 24 Kodak images will be used in this experiment. Experimental results show that the ECI method is better than others in terms of image quality versus complexity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.7-14
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• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.654-659
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• 2010

In this paper, we propose a new frequency allocation method for improvement of edge and low 5% user throughputs. Although many kinds of inter cell interference mitigation methods have been proposed, those have still high complexity of implementation. The proposed algorithm has lower complexity and higher edge user throughput than conventional algorithms since the same frequency allocation method is applied in all cell. Finally, we analyze and compare the edge and low 5% user throughputs using a system level simulation (SLS).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.322-328
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• 2009

This paper proposes new simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes. The proposed SSP algorithm can replace multiplications and divisions with additions and subtractions without extra computations. In addition, the proposed SSP algorithm can simplify both the In[tanh(x)] and tanh-1 [exp(x)] by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SSP algorithm can improve about $0.3\;{\sim}\;0.8\;dB$ of BER performance compared with the existing modified sum-product algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.683-690
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• 2008

By using inherent stopping criteria of LDPC codes, the average number of iterations can be substantially reduced at high signal to noise ratio (SNR). However, we encounter a problem when hybrid automatic repeat request (H-ARQ) systems are applied. Frequent failures of decoding at low SNR region imply that the decoder leaches the maximum number of iterations frequently and thus the decoding complexity increases. In this paper, we propose a combination of stopping criteria using the syndrome weight of tentative codeword. By numerical analysis, it is shown that the decoding complexity of given H-ARQ system is reduced by 70-80% with the proposed algorithms.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.106-113
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• 1997

While driving, the low frequency interior noise below 200Hz causes the main component that irritates the auditory acoustic sense. But these passive control methods bring out increment in cost and weight of the vehicle and result in low efficiency. Recently, various ANC(Active Noise Control) methos to suppress the low frequency noise began to launch into application. In this study, we implemented the active noise control system for passenger vehicle to cancel the engine booming noise using DSP-based control unit, 4 micorphones, and 2 speakers. We used MEFX-LMS (Multiple Error Filtered X-Least Mean Square) algorithm since it can be easily implemented in real time. Also, MEFX-RLS algorithm was taken to enhance the suppression of the harmonic components of the engine booming noise inspite of its computational complexity. The performance of two adaptive algorithms were analyzed with experimental resutls.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.772-776
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• 2004

This paper proposes an interference avoidance approach for Constraint-Based Routing (CBR) algorithm in the Multi-Protocol Label Switching (MPLS) network. The MPLS network itself has a capability of integrating among any layer-3 protocols and any layer-2 protocols of the OSI model. It is based on the label switching technology, which is fast and flexible switching technique using pre-defined Label Switching Paths (LSPs). The MPLS network is a solution for the Traffic Engineering(TE), Quality of Service (QoS), Virtual Private Network (VPN), and Constraint-Based Routing (CBR) issues. According to the MPLS CBR, routing performance requirements are capability for on-line routing, high network throughput, high network utilization, high network scalability, fast rerouting performance, low percentage of call-setup request blocking, and low calculation complexity. There are many previously proposed algorithms such as minimum hop (MH) algorithm, widest shortest path (WSP) algorithm, and minimum interference routing algorithm (MIRA). The MIRA algorithm is currently seemed to be the best solution for the MPLS routing problem in case of selecting a path with minimum interference level. It achieves lower call-setup request blocking, lower interference level, higher network utilization and higher network throughput. However, it suffers from routing calculation complexity which makes it difficult to real task implementation. In this paper, there are three objectives for routing algorithm design, which are minimizing interference levels with other source-destination node pairs, minimizing resource usage by selecting a minimum hop path first, and reducing calculation complexity. The proposed CBR algorithm is based on power factor calculation of total amount of possible path per link and the residual bandwidth in the network. A path with high power factor should be considered as minimum interference path and should be selected for path setup. With the proposed algorithm, all of the three objectives are attained and the approach of selection of a high power factor path could minimize interference level among all source-destination node pairs. The approach of selection of a shortest path from many equal power factor paths approach could minimize the usage of network resource. Then the network has higher resource reservation for future call-setup request. Moreover, the calculation of possible path per link (or interference level indicator) is run only whenever the network topology has been changed. Hence, this approach could reduce routing calculation complexity. The simulation results show that the proposed algorithm has good performance over high network utilization, low call-setup blocking percentage and low routing computation complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2A
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• pp.179-187
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• 2007

As wireless networks evolve to orthogonal frequency division multiple access(OFDMA) systems, inter-cell interference control becomes a critical issue in radio resource management. The allocation of the same channels in neighbor cells cause inter-cell interference, so the channel allocation needs to be taken carefully to lower the inter-cell interference. In distributed channel allocation, each cell independently tries to allocate channels that suffer low interference level. In this paper, under the assumption of static users, we introduce the concept of interference range and use it in designing our two algorithms; basic and combined. The basic algorithm performs interference range detection and determines whether to use the considered channel, while the combined algorithm checks the channel quality in addition to detecting the interference range. The two algorithms dynamically perform channel allocation with low complexity and show good throughput and fairness performance.