• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.1-7
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• 2004

The development of direct receiver techniques is expected to be a solution for future wideband or multi-band wireless systems based on software defined radio. In this Paper, we study the regeneration of I and Q signals for the SDR based direct conversion receiver, so that we can handle a wide bandwidth and maintain maximal flexibility in system utilization. After modeling the basic system considering the real wireless communication environment, and studying the impact of imperfect phase imbalance on the performance of a direct conversion receiver, we propose a suboptimal I and Q signal regeneration algorithm for the system. The proposed algerian regenerates I and Q signals using a real time early-late compensator which effectively estimates phase imbalances and gives feedback in a directreceiver. The proposed algorithm is shown to mitigate the impact of AWGN and improves performance especially at low SNR channel condition. According to the computer simulation, the BER performance of the proposed system is at least about 4 dB better than conventional systems under $45{\~}55$ degrees random phase errors.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.885-893
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• 2006

The Bayesian network(BN) has emerged in recent years as a powerful technique for handling uncertainty iii complex domains. Parameter learning of BN to find the most proper network from given data set has been investigated to decrease the time and effort for designing BN. Off-line learning needs much time and effort to gather the enough data and since there are uncertainties in real world, it is hard to get the complete data. In this paper, we propose an online learning method of Bayesian network parameters from incomplete data. It provides higher flexibility through learning from incomplete data and higher adaptability on environments through online learning. The results of comparison with Voting EM algorithm proposed by Cohen at el. confirm that the proposed method has the same performance in complete data set and higher performance in incomplete data set, comparing with Voting EM algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.149-154
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• 2017

The MCT-Adaboost algorithm chooses an optimal set of features in each rounds. On each round, it chooses the best feature by calculate minimizing error rate using feature index and MCT kernel distribution. The involved process of weak classification executed by a hard decision. This decision occurs some problems when it chooses ambiguous kernel feature. In this paper, we propose the modified MCT-Adaboost classification using soft decision. The typical MCT-Adaboost assigns a same initial weights to each datum. This is because, they assume that all information of database is blind. We assign different initial weights with our propose new algorithm using some statistical properties of involved features. In experimental results, we confirm that our method shows better performance than the traditional one.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.467-476
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• 1997

This paper presents a designing of a digital hearing aid processor (DHAP) chip being operated by a dedicated DSP core. The DHAP for hearing aid devices must be feasible within a size and power consumption required. Furthermore, it should be able to compensate for wide range of hearing losses and allow sufficient flexibility for the algorithm development. In this paper, a programmable 16-bit fixed-point DSP core is employed thor the designing of the DHAP. The designed DHAP performs a nonlinear loudness correction of 8 frequency bands based on audiometric measurements of impaired subjects. By employing a programmable DSP, the DHAP provides all the flexibility needed to implement audiological algorithms. In addition, the chip has low-power feature and $5, 500\times5000$$\mu$$m^2$ dimensions that fit for wearable hearing aids.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.55-61
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• 2011

The small-sized wind turbine generating system with the output power less than 10kW, which can be installed in some areas of hills, parks, and cities due to its flexibility, is one of the progressive research and development fields in renewable energy. It is important for the small wind turbine generators to have low cost, high reliability as well as high efficiency. To meet these requirements, development of various maximum-power-point-tracking (MPPT) control schemes should be required. Generally, the output of the controller can be connected to a 48V battery to supply power to a DC load. In this work, the design and implementation of an FPGA-based MPPT controller for small-sized wind turbine generating system is presented. For the verification of the practical performance of various MPPT algorithms, CRIO controller from NI has been used.

• Convergence Security Journal
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• v.11 no.1
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• pp.11-18
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• 2011

Wireless mesh network technology with transmission speeds similar to wired and wireless technology means to build, compared with wired networks, building a more efficient network to provide convenience and flexibility. The wireless mesh network router nodes in the energy impact of the mobility is less constrained and has fewer features entail. However, the characteristics of various kinds due to network configuration settings and the choice of multiple paths that can occur when the system overhead and there are many details that must be considered. Therefore, according to the characteristics of these network routing technology that is reflected in the design and optimization of the network is worth noting. In this paper, a multi-path setting can be raised in order to respond effectively to the problem of the router node data loss and bandwidth according to traffic conditions and links to elements of the hop count evaluation by using a genetic algorithm as a workaround for dynamic routing the routing metric for wireless mesh network scheme is proposed.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.358-363
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• 2007

Reinforcing steel work plays an important role in terms of its structural performance or weight of construction cost for reinforced concrete structures. Precise estimation of re-bar quantity gives a basis for managing the reinforcing steel work effectively. However, the estimation process is still performed ineffectively based upon the expert's experience or manpower in spite of the advanced technology or improvement efforts. Therefore, the purpose of this research is to develop a prototype system for taking-off the quantity of reinforcing steel bars quickly and accurately in an order consistent with the specific members identified on the drawings. An estimate algorithm considering the connection, settlement and coating thickness of re-bars was suggested regarding to their replacement conditions which places more emphasis on constructibility. Also, this system produces the shop drawings automatically with the calculation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1170-1178
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• 2010

Recently as the number of users and application traffic is increasing on high speed network, the importance of application traffic classification is growing more and more for efficient network resource management. Although a number of methods and algorithms for traffic classification have been introduced, they have some limitations in terms of accuracy and completeness. In this paper we propose an application traffic classification based multi-level architecture which integrates several signature-based methods and behavior algorithm, and analyzes traffic using correlation among traffic flows. By strengthening the strength and making up for the weakness of individual methods we could construct a flexible and robust multi-level classification system. Also, by experiments with our campus network traffic we proved the performance and validity of the proposed mechanism.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.945-956
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• 2021

In this study, we considered the algorithm of Legendre and Legendre (2012), which derives canonical correspondence analysis from weighted principal component analysis. And, it was proved that the canonical correspondence analysis based on the weighted principal component analysis is exactly the same as Ter Braak's (1986) canonical correspondence analysis based on the Gaussian response model. Ter Braak (1986)'s canonical correspondence analysis derived from a Gaussian response curve that can explain the abundance of species in ecology well uses the basic assumption of the species packing model and then conducts generalized linear model and canonical correlation analysis. It is derived by way of binding. However, the algorithm of Legendre and Legendre (2012) is calculated in a method quite similar to Benzecri's correspondence analysis without such assumptions. Therefore, if canonical correspondence analysis based on weighted principal component analysis is used, it is possible to have some flexibility in using the results. In conclusion, this study shows that the two methods starting from different models have the same site scores, species scores, and species-environment correlations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1202-1208
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• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.