• Journal of Information Technology Services
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• v.7 no.2
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• pp.1-12
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• 2008

The development of IT and explosively growing number of Internet users are rapidly spreading and developing e-commerce, while creating diverse on-line transaction methods such as a negotiation, a reverse auction, and a bid. Among these transaction methods, the transactions by means of a negotiation are being made for goods that have no posted price. In particular, the transactions by means of a negotiation are expected to be widely used in the B2B. In order to determine their transportation costs, shippers usually make negotiations with many transporters and logistics companies. And before long, these negotiations are expected to be made on an on-line automated negotiation system. Because of this, this study has tried to develop an automated negotiation methodology that is absolutely necessary for an on-line automated negotiation. This study has estimated and selected the evaluation functions for multi-lateral negotiators' proposals, thus developing an automated negotiation methodology. As a result of this study, a new direction for an automated negotiation has been suggested. Also we expect that this study will be widely used in the automated negotiation of diverse fields.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.334-349
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• 2022

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.295-304
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• 2011

For effective water quality management, it is necessary to secure reliable water quality information. There are many variables that need to be included in a comprehensive practical monitoring network : representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples, especially sampling location is considered to be the most important issues. Until now, monitoring network design for water quality management was set according to the qualitative judgments, which is a problem of representativeness. In this paper, we propose network design system for optimal water quality monitoring using the scientific statistical techniques. Network design system is made based on the SAS program of version 9.2 and configured with simple input system and user friendly outputs considering the convenience of users. It applies to Excel data format for ease to use and all data of sampling location is distinguished to sheet base. In this system, time plots, dendrogram, and scatter plots are shown as follows: Time plots of water quality variables are graphed for identifying variables to classify sampling locations significantly. Similarities of sampling locations are calculated using euclidean distances of principal component variables and dimension coordinate of multidimensional scaling method are calculated and dendrogram by clustering analysis is represented and used for users to choose an appropriate number of clusters. Scatter plots of principle component variables are shown for clustering information with sampling locations and representative location.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1768-1789
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• 2015

The maximal signal-to-interference-plus-noise ratio (Max-SINR) algorithm for interference alignment (IA) has received considerable attention for its high sum rate achievement in the multiple-input multiple-output (MIMO) interference channel. However, its complexity may increase dramatically when the number of users approaches the IA feasibility bound, and the number of iterations and computational time may become unacceptable. In this paper, we study the properties of the Max-SINR algorithm thoroughly by presenting theoretical insight into the algorithm and by providing the potential of reducing the overall computational cost. Furthermore, a novel IA algorithm based on the principle direction search is proposed, which can converge more rapidly than the conventional Max-SINR method. In the proposed algorithm, it searches along the principle direction, which is found to approximately point to the convergence values, and can approach the convergence solutions rapidly. In addition, the closed-form solution of the optimal step size can be formulated in the sense of minimal interference leakage. Simulation results demonstrate that the proposed algorithm outperforms the conventional minimal interference leakage and Max-SINR algorithms in terms of the convergence rate while guaranteeing the high throughput of IA networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1504-1526
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• 2018

For uplink multi-user massive MIMO systems, conventional minimum mean square error (MMSE) linear detection method achieves near-optimal performance when the number of antennas at base station is much larger than that of the single-antenna users. However, MMSE detection involves complicated matrix inversion, thus making it cumbersome to be implemented cost-effectively and rapidly. In this paper, we first summarize in detail the state-of-the-art simplified MMSE detection algorithms that circumvent the complicated matrix inversion and hence reduce the computation complexity from ${\mathcal{O}}(K^3)$ to ${\mathcal{O}}(K^2)$ or ${\mathcal{O}}(NK)$ with some certain performance sacrifice. Meanwhile, we divide the simplified algorithms into two categories, namely the matrix inversion approximation and the classical iterative linear equation solving methods, and make comparisons between them in terms of detection performance and computation complexity. In order to further optimize the detection performance of the existing detection algorithms, we propose more proper solutions to set the initial values and relaxation parameters, and present a new way of reconstructing the exact effective noise variance to accelerate the convergence speed. Analysis and simulation results verify that with the help of proper initial values and parameters, the simplified matrix inversion based detection algorithms can achieve detection performance quite close to that of the ideal matrix inversion based MMSE algorithm with only a small number of series expansions or iterations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.8-16
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• 2012

Recent work has been shown that cognitive radio systems with multiple antenna at both transmitter and receiver are able to improve performance of secondary users. In such system, the main drawback is the increased complexity and raised cost as the number of antennas increase. It is desirable to apply antenna selection which select a subset of the available antennas so as to solve these problems. In this paper, we consider antenna selection method for cognitive radio systems in correlated channel from the IEEE 802.11n. For a multiple-input multiple-output(MIMO) system with more antennas at transmitter than the receiver, we select the same number of transmit antennas as that of receive antennas. The exhaustive search for optimal antenna becomes impractical. We present criterion for selecting subset in terms of projection of channel correlation vector to increase performance of secondary user with decreasing interference at primary user.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.633-643
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• 2003

UWB impulse radio signals have an very short duration, extremely wide bandwidth and share the same frequency spectrum with other existing systems. It was determined by the Federal Communications Commission (FCC) that UWB systems could cause interference with other systems, such as Global Positioning System (GPS) for example. Therefore, at present. the FCC has restricted the use of UWB systems to frequencies above 3.1㎓. In this paper, We evaluated performance of UWB system using proposed pulses in ［1］［2］ that are strictly limited in time to remove interference while, at the same time, contain their power distribution to a frequency band from 3.1㎓ to 10.6㎓. In particular, We evaluated the BER Performance in relation to system parameters such as pulse duration. $\delta$, the number of users. Nu. and the number of symbols, M. We found the optimal pulse duration $\delta$ through computer simulation using developed UWB pulses in ［1］［2］. It is shown that performance evaluation between the UWB communication system using these UWB pulses ［1］［2］and the Gaussian monocycle pulse in M-ary PPM and BPSK schemes. These results can be contributed to construct M-ary PPM UWB communication system in terms of multiuser parameters and pulse duration.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.2
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• pp.67-79
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• 1998

Most GIS applications are read-intensive on a large number of spatial objects and when the spatial objects are composite objects, the contained objects within the composite objects are also accessed. In GIS applications, creation, deletion, and update operations on spatial objects occur very rarely, but once they occur they deal with a large number of spatial objects. This paper proposes the concept of the multi-level pre-fetch query to retrieve a large number of spatial objects efficiently, and the functionality of the deferred-flush on the newly created persistent objects into the database with the optimal performance, and presents the design and implementation details of those ideas into an object-oriented DBMS BADA-III while considering these characteristics of GIS applications. The multi-level pre-fetch query retrieves the objects that satisfy the query and the objects that are contained within the objects up to the level specified by users, and registers the retrieved objects on the client cache. The deferred-flush flushes a large number of composite objects that are created by the application with a minimal overhead of the server and a minimal number of communications between the client and the server. These two functionality are suitable for the applications that search or create a large number of composite objects like GIS applications.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.81-91
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• 2019

Although the number of users of urban railways is greatly influenced by the land use plan around the railway station, Korea has been studying this problem in a small scale, so that the entrance width is uniformly calculated irrespective of the land use plan, And there is little deviation. Therefore, this study aims to establish a demand estimation model for the entrance and exit of urban railway stations. For this purpose, the demand, land use area, and socioeconomic indicators for each of the 20 urban railway stations were surveyed at 200m and 500m Regression model. The model is based on the assumption that the dependent variable (response variable) of the model is set to 1 day, peak 1 hour, peak time 5 minutes, Education, and park) and socioeconomic indicators (population, employer, employee, and student) as independent variables (explanatory variables). As a result, it was analyzed that the fit of the model is more statistically significant when the use area of the land use by 500 meters of the center radius of the city rail is used as an independent variable and the demand for the daily use of the railway station is used as a dependent variable. The purpose of this study is to estimate the optimal size of urban railway entrance in order to improve the mobility of the user and the transportation weak in urban railway station.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.107-114
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• 2008

In wireless access systems, there has been much interest in enhancing the performance of orthogonal frequency division multiplexing OFDM) in a frequency selective fading channel. If the channel is static and is perfectly known to both the transmitter and the receiver, the water-filling technique with adaptive modulation is known to be optimal. However, for OFDM systems, this requires intensive traffic overheads for reporting channel side information on all subcarriers to the transmitter In this paper, we propose an adaptive modulation and coding scheme for bit-interleaved coded OFDM (BIC-OFDM) for downlink packet transmissions with reduced feedback information. To minimize the feedback information, we employ a rate adaptation method based on the OFDM symbol rather than on each subcarrier. To illustrate the performance gap between the optimal water-filling and the proposed scheme, we will compare cutoff rates for both schemes. It is shown that the loss is less than 2dB while the proposed scheme significantly reduces the feedback payloads. Also, the OFDM system in multiuser environment with subcarrier grouping is considered. It is shown that by exploiting multiuser diversity the throughput of the proposed scheme approaches the channel outage capacity as the number of users and the number of subcarrier groups increase.