• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.650-669
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• 2017

Coordinated multiple points transmission and reception (CoMP) technology is used to mitigate the inter-cell interference, and increase cell average user normalized throughput and cell edge user normalized throughput. There are two kinds of radio resource schedule strategies in LTE-A/5G CoMP system, and they are called centralized scheduling strategy and distributed scheduling strategy. The regional centralized scheduling cannot solve interference of inter-region, and the distributed scheduling leads to worse efficiency in the utilize of resources. In this paper, a novel distributed scheduling scheme named 9-Cell alternate authorization (9-CAA) is proposed. In our scheme, time-domain resources are divided orthogonally by coloring theory for inter-region cooperation in 9-Cell scenario [6]. Then, we provide a formula based on 0-1 integer programming to get chromatic number in 9-CAA. Moreover, a feasible optimal chromatic number search algorithm named CNS-9CAA is proposed. In addition, this scheme is expanded to 3-Cell scenario, and name it 3-Cell alternate authorization (3-CAA). At last, simulation results indicate that 9/3-CAA scheme exceed All CU CoMP, 9/3C CU CoMP and DLC resource scheduling scheme in cell average user normalized throughput. Especially, compared with the non-CoMP scheme as a benchmark, the 9-CAA and 3-CAA have improved the edge user normalized throughput by 17.2% and 13.0% respectively.

• Journal of KIISE:Software and Applications
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• v.33 no.2
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• pp.154-166
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• 2006

Product Line Engineering(PLE) is a software reuse paradigm that core assets are defined using common features in a domain and are instantiated in various applications. To apply the core asset effectively, variants which satisfy application requirements are extracted and the core asset should be also instantiated based on the variants. For the work, variability on architecture and components should be extracted exactly and an instantiation process and guidelines should be defined based on this variability In this paper, we define variability types depending on core assets elements and describe artifact templates related to tile variability. We also propose a systematic process which uses defined core assets including variability and verify practicability of the proposed process and variability expression through doing ease study. If utilizing with the proposed process in PLE, it can be feasible to model concrete core asset and variability and to utilize practical application engineering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9A
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• pp.719-726
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• 2009

CR systems performs spectrum sensing operation to detect the appearance of primary users. However, since it is not feasible to do spectrum sensing and data transmission simultaneously, they typically operate alternatively in a time domain. There have been an effort(8) to investigate the optimal spectrum sensing duration for maximum throughput for the scheme with cooperative spectrum sensing. This is based on an assumption that the communication channels between each secondary user and the fusion center are ideal and does not consider the effects of transmission error. Motivated by this, we here model the channels as binary symmetric channels and examined its effect on the maximum throughput and the associated optimal sensing duration. Analysis shows that the performance degradation due to the transmission error is smaller for the case of using the AND fusion rule than for the OR fusion rule.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.69-69
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• 2003

Human CD99 is a ubiquitous 32-kDa transmembrane protein encoded by the mic2 gene. The major cellular functions of CD99 protein are related to homotypic cell adhension, apoptosis, vesicular protein transport, and differentiation of thymocytes or T cells. Recently it has been reported that expression of a splice variant of CD99 transmembrane protein (Type I and Type II) increases invasive ability of human breast cancer cells. To understand structural basis for cellular functions of CD99 (Type I), we have initiated studies on hCD99$^{TMcytoI}$ and hCD99$^{cytoI}$ using circular dichroism (CD) and multi-dimensional NMR spectroscopy. CD spectrum of hCD99$^{TMcytoI}$ in the presence of 200mM DPC and CHAPS displayed an existence $\alpha$-helical conformation. The solution structure of hCD99$^{cytoI}$ determined by NMR is composed of one N-terminal $\alpha$-helix, $\alpha$A, two C-terminal short $\alpha$-helix segments, $\alpha$B and $\alpha$C. While $\alpha$A and $\alpha$B are connected by the long flexible loop, $\alpha$B and $\alpha$C connected by type III$\beta$-turn. Although it has been rarely figured out the correlation between structure and functional mechanism of hCD99$^{TMcytoI}$ and hCD99$^{cytoI}$, there is possibility of dimerization or oligomerization. In addition, the feasible mechanism of hCD99$^{cytoI}$ is that it could have intramolecular interaction between the N- and C- terminal domain through large flexible AB loop.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.117-127
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• 2015

This paper depicts a case study of the BIM (Building Information Modeling)-enabled evaluation of design alternatives for an actual remodeling project in Yeongwol, Korea. The increase of urban population and income followed by the growth of economy has derived massive supply of grand scale housing project in Korea since 1970s. Consequently, building remodeling became one of the feasible resolutions for renovating such old housings in these days. This paper aims to introduce a technical approach to such remodeling projects based on BIM-enabled applications focusing on quantitative analysis of design alternatives. Among the technical issues of such building remodeling projects, this paper focuses on the BIM-enabled area analysis and comparison between design alternatives to support decision-making even in early phase of remodeling design process. BIM and its variety of applications have broadly influenced the domain of AEC-FM (Architecture, Engineering, Construction, and Facility Management) within the lifecycle of buildings. As one of the applications facilitated by BIM, the automated area calculation and scenario-based comparison between alternatives can play an important role in the early phase of remodeling project. We modeled three design alternatives (buildings) and three housing modules (units) based on the actual case in Yeongwol city, Korea using a BIM design authoring tool. Nine combinatorial BIM models were demonstrated for the BIM-enabled review process described in this paper. To determine the most optimal design scenario among nine alternatives, this paper demonstrates a result of the conducted spatial program review. The main subject includes specific spatial program issues on; 1) the number of unit spaces; and 2) area of individual/grouped and private/shared spaces.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.741-752
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• 2016

Numerous studies have shown that normal inverse Gaussian (NIG) distribution adequately fits the empirical return distribution of financial securities. The estimation of parameters can also be done relatively easily, which makes the NIG distribution more useful in financial markets. The maximum likelihood estimation and the method of moments estimation are easy to implement; however, we may encounter a problem in practice when a relationship among the moments is violated. In this paper, we investigate this problem in the parameter estimation and try to find a simple solution through simulations. We examine the effect of our adjusted estimation method with real data: daily log returns of KOSPI, S&P500, FTSE and HANG SENG. We also checked the performance of our method by computing the value at risk of daily log return data. The results show that our method improves the stability of parameter estimation, while it retains a comparable performance in goodness-of-fit.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.159-185
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• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.184-184
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• 2012

Recently, InGaN/GaN multi-quantum well grown on GaN pyramid structures have attracted much attention due to their hybrid characteristics of quantum well, quantum wire, and quantum dot. This gives us broad band emission which will be useful for phosphor-free white light emitting diode. On the other hand, by using quantum dot emission on top of the pyramid, site selective single photon source could be realized. However, these structures still have several limitations for the single photon source. For instance, the quantum efficiency of quantum dot emission should be improved further. As detection systems have limited numerical aperture, collection efficiency is also important issue. It has been known that micro-cavities can be utilized to modify the radiative decay rate and to control the radiation pattern of quantum dot. Researchers have also been interested in nano-cavities using localized surface plasmon. Although the plasmonic cavities have small quality factor due to high loss of metal, it could have small mode volume because plasmonic wavelength is much smaller than the wavelength in the dielectric cavities. In this work, we used localized surface plasmon to improve efficiency of InGaN qunatum dot as a single photon emitter. We could easily get the localized surface plasmon mode after deposit the metal thin film because lnGaN/GaN multi quantum well has the pyramidal geometry. With numerical simulation (i.e., Finite Difference Time Domain method), we observed highly enhanced decay rate and modified radiation pattern. To confirm these localized surface plasmon effect experimentally, we deposited metal thin films on InGaN/GaN pyramid structures using e-beam deposition. Then, photoluminescence and time-resolved photoluminescence were carried out to measure the improvement of radiative decay rate (Purcell factor). By carrying out cathodoluminescence (CL) experiments, spatial-resolved CL images could also be obtained. As we mentioned before, collection efficiency is also important issue to make an efficient single photon emitter. To confirm the radiation pattern of quantum dot, Fourier optics system was used to capture the angular property of emission. We believe that highly focused localized surface plasmon around site-selective InGaN quantum dot could be a feasible single photon emitter.

• The Journal of the Acoustical Society of Korea
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• v.21 no.6
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• pp.552-558
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• 2002

Recently, based on the human speech recognition (HSR) model of Fletcher, the multi-band speech recognition has been intensively studied by many researchers. As a new automatic speech recognition (ASR) technique, the multi-band speech recognition splits the frequency domain into several sub-bands and recognizes each sub-band independently. The likelihood scores of sub-bands are weighted according to reliabilities of sub-bands and re-combined to make a final decision. This approach is known to be robust under noisy environments. When the noise is stationary a sub-band SNR can be estimated using the noise information in non-speech interval. However, if the noise is non-stationary it is not feasible to obtain the sub-band SNR. This paper proposes the inverse sub-band distance (ISD) weighting, where a distance of each sub-band is calculated by a stochastic matching of input feature vectors and hidden Markov models. The inverse distance is used as a sub-band weight. Experiments on 1500∼1800㎐ band-limited white noise and classical guitar sound revealed that the proposed method could represent the sub-band reliability effectively and improve the performance under both stationary and non-stationary band-limited noise environments.