• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.939-947
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• 2010

The LDPC(Low-Density Parity-Check) code, which is one of the channel encoding methods in IEEE 802.11n wireless LAN standard, has superior error-correcting capabilities. Since the hardware complexity of LDPC decoder is high, it is very important to take into account the trade-offs between hardware complexity and decoding performance. In this paper, the effects of LLR(Log-Likelihood Ratio) approximation on the performance of MSA(Min-Sum Algorithm)-based LDPC decoder are analyzed, and some optimal design conditions are derived. The parity check matrix with block length of 1,944 bits and code rate of 1/2 in IEEE 802.11n WLAN standard is used. In the case of $BER=10^{-3}$, the $E_b/N_o$ difference between LLR bit-widths (6,4) and (7,5) is 0.62 dB, and $E_b/N_o$ difference for iteration cycles 6 and 7 is 0.3 dB. The simulation results show that optimal BER performance can be achieved by LLR bit-width of (7,5) and iteration cycle of 7.

• Journal of IKEEE
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• v.22 no.1
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• pp.180-184
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• 2018

Gallium oxide ($Ga_2O_3$) and silicon carbide (SiC) are the material with the wide band gap ($Ga_2O_3-4.8{\sim}4.9eV$, SiC-3.3 eV). These electronic properties allow high blocking voltage. In this work, we investigated the characteristic of $Ga_2O_3$ and 4H-SiC vertical depletion-mode metal-oxide-semiconductor field-effect transistors. We demonstrated that the blocking voltage and on-resistance of vertical DMOSFET is dependent with structure. The structure of $Ga_2O_3$ and 4H-SiC vertical DMOSFET was designed by using a 2-dimensional device simulation (ATLAS, Silvaco Inc.). As a result, 4H-SiC and $Ga_2O_3$ vertical DMOSFET have similar blocking voltage ($Ga_2O_3-1380V$, SiC-1420 V) and then when gate voltage is low, $Ga_2O_3-DMOSFET$ has lower on-resistance than 4H-SiC-DMOSFET, however, when gate voltage is high, 4H-SiC-DMOSFET has lower on-resistance than $Ga_2O_3-DMOSFET$. Therefore, we concluded that the material of power device should be considered by the gate voltage.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.271-300
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• 2004

We investigate the two recent simulations of the proto-type domestic carbon emission trading system in Korea and draw some policy implications. The first simulation includes the 5 electric power companies based on baseline and credit. But the second one is with the 7 energy-intensive companies based on cap and trade. The voluntary approaches in this paper revealed the instability of market equilibrium, i.e., price volatility or distortion, excess supply or demand. These phenomena stems from excess incentives to the players, asymmetric information, players' irresponsible strategic behaviors, and non acquaintance of trading system. This paper suggests the basic design for domestic carbon trading system in future and a stepwise introduction strategy for it including the incentive auction scheme, the total quantity of incentive needed, and how to finance it. Meantime, the further simulations on the various sectors based on voluntary participation must be essential for learning experiences and better policy design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.5-24
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• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• Earthquakes and Structures
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• v.10 no.5
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• pp.1067-1087
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• 2016

In this paper, a decoupled proportional-integral-derivative (PID) control approach for seismic control of smart structures is presented. First, the state space equation of a structure is transformed into modal coordinates and parameters of the modal PID control are separately designed in a reduced modal space. Then, the feedback gain matrix of the controller is obtained based on the contribution of modal responses to the structural responses. The performance of the controller is investigated to adjust control force of piezoelectric friction dampers (PFDs) in a benchmark base isolated building. In order to tune the modal feedback gain of the controller, a suitable trade-off among the conflicting objectives, i.e., the reduction of maximum modal base displacement and the maximum modal floor acceleration of the smart base isolated structure, as well as the maximum modal control force, is created using a multi-objective cuckoo search (MOCS) algorithm. In terms of reduction of maximum base displacement and story acceleration, numerical simulations show that the proposed method performs better than other reported controllers in the literature. Moreover, simulation results show that the PFDs are able to efficiently dissipate the input excitation energy and reduce the damage energy of the structure. Overall, the proposed control strategy provides a simple strategy to tune the control forces and reduces the number of sensors of the control system to the number of controlled stories.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.240-249
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• 2011

Cooperative diversity protocols have attracted a great deal of attention since they are thought to be capable of providing diversity multiplexing tradeoff among single antenna wireless devices. In the high signal-to-noise ratio (SNR) region, cooperation is rarely required; hence, the spectral efficiency of the cooperative protocol can be improved by applying a proper cooperation selection technique. In this paper, we present a simple "cooperation selection" technique based on instantaneous channel measurement to improve the spectral efficiency of cooperative protocols. We show that the same instantaneous channel measurement can also be used for relay selection. In this paper two protocols are proposed-proactive and reactive; the selection of one of these protocols depends on whether the decision of cooperation selection is made before or after the transmission of the source. These protocols can successfully select cooperation along with the best relay from a set of available M relays. If the instantaneous source-to-destination channel is strong enough to support the system requirements, then the source simply transmits to the destination as a noncooperative direct transmission; otherwise, a cooperative transmission with the help of the selected best relay is chosen by the system. Analysis and simulation results show that these protocols can achieve higher order diversity with improved spectral efficiency, i.e., a higher diversity-multiplexing tradeoff in a slow-fading environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3293-3311
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• 2015

Cloud services are required to be composed as a single service to fulfill the workflow applications. Service composition in Cloud raises new challenges caused by the diversity of users with different QoS requirements and vague preferences, as well as the development of cloud computing having geographically distributed characteristics. So the selection of the best service composition is a complex problem and it faces trade-off among various QoS criteria. In this paper, we propose a Cloud service composition approach based on evolutionary algorithms, i.e., NSGA-II and MOPSO. We utilize the combination of multi-objective evolutionary approaches and Decision-Making method (AHP) to solve Cloud service composition optimization problem. The weights generated from AHP are applied to the Crowding Distance calculations of the above two evolutionary algorithms. Our algorithm beats single-objective algorithms on the optimization ability. And compared with general multi-objective algorithms, it is able to precisely capture the users' preferences. The results of the simulation also show that our approach can achieve a better scalability.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• International Commerce and Information Review
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• v.16 no.1
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• pp.91-116
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• 2014

This study reviews the methodology for utilizing information technology by which even non-professionalists in FTAs and commodity classification area can perform the determination of commodity classification, with ease and by themselves, by means of easy utilization of the information on commodity classification and FTAs, of importing and exporting goods. This article examines the technological elements and logics, etc. which simulate the commodity classification for utilizing FTAs. To achieve this, the author has developed the technology to support the determination of commodity classification numbers by accumulating the database of examples for classification after analyzing the classification factors by each commodity item. Utilizing this Commodity Classification Determination Supporting System, users can enjoy effects of education as well as consulting. In this regards, the advantages of this system can be enumerated as followings : Firstly, self-checking on commodity classification can be performed. Secondly, time and cost for classification can be saved. Thirdly, comprehensive competitiveness will be enhanced by allowing traders to achieve the benefit of FTA preferential tariff, for they will be able to issue the Certificate of Origins on a more accurate and precise basis of commodity classification.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.45-59
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• 2015

As many companies have been interested in big data, they have invested a lot of resources to get more customer data. Some companies try to trade the data illegally. In order to collect more customer data, companies provide various incentive programs to customers. However, their results are normally much less than their expectations. This study focuses on exploring the relative importance of the factors which influence customer attitudes to providing his/her personal information. This study conducts a conjoint analysis to assess trade-offs among the five influential factors-monetary reward, concern for data collection, concern for secondary use, concern for unauthorized use, and concern for errors. This study finds that the customer attitude to providing personal information is most influenced by the concern for secondary use. Furthermore, it shows that there are some differences between the light internet user group and the heavy internet user group in the relative importances of these factors. The monetary rewards appeal to the heavy internet users, rather than the light internet users.