• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.36-44
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• 2010

When multi-user MIMO (Multiple-Input Multiple-Output) systems utilize a sum-rate maximization (SRM) scheduler, the throughput of the systems can be enhanced. However, fairness problems may arise because users located near cell edge or experiencing poor channel conditions are less likely to be selected by the SRM scheduler. In this paper, a weighted sum-rate maximization (WSRM) scheduler is used to enhance the fairness performance of the MIMO systems. Closed-form expressions for the optimal transmit power allocation of WSRM and corresponding weighted sum-rate (WSR) are derived in the 6-sector collaborative transmission system. Using the derived results, we propose an algorithm which searches the optimal power allocation for WSRM in the 3-sector collaborative transmission system. Based on the derived closed-form expressions and the proposed algorithm, we perform computer simulations to compare performance of the WSRM scheduler and the SRM scheduler with respect to the sum-rate and the log-sum-of-average rates. We further verify that the WSRM scheduler efficiently improves fairness performance by showing the enhanced performance of average transmission rates in low percentile region.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.3-11
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• 2014

Multiple antennas can provide huge capacity gains when the transmitter knows the channel state information (CSI). Precoding is a technique that exploits CSI at the transmitter side. In this paper, an adaptive precoding scheme is proposed, called a hybrid multiple-input multiple-output (MIMO) precoding (HMP). HMP is a combination of linear and nonlinear precoding. The number of transmit antennas less than or equal to four is as same as the conventional antenna selection scheme. Therefore, the HMP scheme uses more than four transmit antennas. The good channel means that the channels must be selected to maximize the channel capacity among the given channels, and the rest channels are called bad channel. In HMP scheme, we use the nonlinear precoding in the good channels and the linear precoding in the bad channels. The well-known Tomlinson-Harashima precoding (THP) is considered as nonlinear precoding. The system throughput and MSE (minimum square error) are shown for the performance of HMP scheme compared to the conventional schemes which are BD (block diagonalization), antenna selection and THP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1076-1084
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• 2012

In the CS/CB(Coordinated Scheduling/Beamforming) scheme, the cell edge user throughput is increased by selecting MIMO (Multiple Input Multiple Output) precoders which can minimize the interferences from adjacent base stations (BSs). However, in current LTE(Long Term Evolution) systems, the serving cell is selected in the initialization stage by using the synchronization signals and cell specific reference signals transmitted by adjacent BSs with a single antenna. The selected BS in the initialization stage may not be the best one since the MIMO precoding gain has not been considered in the cell selection stage. In this paper, a new cell selection technique is proposed for LTE systems with MIMO precoder by taking into account the effect of the precoder in the initialization stage. The proposed technique enables a user equipment (UE) in the cell boundary to select the serving BS by using the information (channel rank, effective channel capacity, and effective SINR(Signal to Interference plus Noise Ratio)) acquired from cell specific reference signals of candidate BSs. It is verified by computer simulation that the proposed technique can increase the channel capacity significantly in the multi-cell environments, compared with the conventional CS/CB scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.137-144
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• 2013

A delay-locked loop (DLL) that generates a 32-phase clock with the operating frequency of 125 MHz is introduced. The proposed DLL uses a delay line of $4{\times}8$ matrix architecture to improve a differential non-linearity (DNL) of the delay line. Furthermore, a integral non-linearity (INL) of the proposed DLL is improved by calibrating phases of clocks that is supplied to four points of an input stage of the $4{\times}8$ matrix delay line. The proposed DLL is fabricated by using $0.11-{\mu}m$ CMOS process with a 1.2 V supply. The measured operating frequency range of the implemented DLL is 40 MHz to 280 MHz. At the operating frequency of 125MHz, the measurement results shows that the DNL and INL are +0.14/-0.496 LSB and +0.46/-0.404 LSB, respectively. The measured peak-to-peak jitter of the output clock is 30 ps when the peak-to-peak jitter of the input clock is 12.9 ps. The area and power consumption of the implemented DLL are $480{\times}550{\mu}m^2$ and 9.6 mW, respectively.

• Journal of KIISE:Databases
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• v.37 no.1
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• pp.1-11
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• 2010

Recently, there has been a growing interest in the processing of continuous queries over multiple data streams. When the arrival rates of tuples exceed the memory capacity of the system, a load shedding technique is used to avoid the system becoming overloaded by dropping some subset of input tuples. In this paper, we propose an effective load shedding algorithm for multi-way windowed joins over multiple data streams. Most previous load shedding algorithms estimate the productivity of each tuple, i.e., the number of join output tuples produced by the tuple, based on its "join attribute value" and drop tuples with the lowest productivity. However, the productivity of a tuple cannot be accurately estimated from its join attribute value when the join attribute values are unique and do not repeat, or the distribution of the join attribute values changes over time. For these cases, we estimate the productivity of a tuple based on its "arrival order" on data streams, rather than its join attribute value. The proposed method can effectively estimate the productivity of a tuple even when the productivity of a tuple cannot be accurately estimated from its join attribute value. Through extensive experiments and analysis, we show that our proposed method outperforms the previous methods in terms of effectiveness and efficiency.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.53-63
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• 1999

For the close range digital photogrammetry, multi-step procedures should be embodied in an integrated system. However, it is hard to construct an Integrated system through conventional procedural processing. Using Object Oriented Programming(OOP), photogrammetric processings can be classified with corresponding subjects and it is easy to construct an integrated system lot digital photogrammetry as well as to add the newly developed classes. In this study, the equation of 3-dimensional mathematic model is developed to make an immediate calibration of the CCD camera, the focus distance of which varies according to the distance of the object. Classes for the input and output of images are also generated to carry out the close range digital photogrammetric procedures by OOP. Image matching, coordinate transformation, dirct linear transformation and bundle adjustment are performed by producing classes corresponding to each part of data processing. The bundle adjustment, which adds the principle coordinate and focal length term to the non-photogrammetric CCD camera, is found to increase usability of the CCD camera and the accuracy of object positioning. In conclusion, classes and their hierarchies in the digital photogrammetry are designed to manage multi-step procedures using OOP and close range digital photogrammetric process is implemented using CCD camera in an integrated System.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.51-61
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• 2002

In this dissertation, We demonstrated the Travel Time forecasting model in the freeway of multi-section with regard of drives' attitude. Recently, the forecasted travel time that is furnished based on expected travel time data and advanced experiment isn't being able to reflect the time-lag phenomenon specially in case of long distance trip, so drivers don't believe any more forecasted travel time. And that's why the effects of ATIS(Advanced Traveler Information System) are reduced. Therefore, in this dissertation to forecast the travel time of the freeway of multi-section reflecting the time-lag phenomenon & the delay of tollgate, we used traffic volume data & TCS data that are collected by Korea Highway Cooperation. Also keep the data of mixed unusual to applicate real system. The applied model for forecasting is consisted of feed-forward structure which has three input units & two output units and the back-propagation is utilized as studying method. Furthermore, the optimal alternative was chosen through the twelve alternative ideas which is composed of the unit number of hidden-layer & repeating number which affect studying speed & forecasting capability. In order to compare the forecasting capability of developed ANN model. the algorithm which are currently used as an information source for freeway travel time. During the comparison with reference model, MSE, MARE, MAE & T-test were executed, as the result, the model which utilized the artificial neural network performed more superior forecasting capability among the comparison index. Moreover, the calculated through the particularity of data structure which was used in this experiment.

• Journal of Distribution Science
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• v.14 no.3
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• pp.73-83
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• 2016

Purpose - The parcel delivery service(courier) industry all over the world has been expanding its market so far, but its growth has been declining in recent years. In this situation, most parcel delivery companies are having trouble with managing themselves because of the pressure from the customer to increase service level and decrease the rate. The purpose of this study is to provide ways to improve competitive advantages of the parcel delivery service industry by evaluating the multi-period operating efficiency of Korea, Japan and global service providers. Research design, data, and methodology - The data for the period of 2011 to 2014 were collected from the annual reports published by parcel delivery companies. In this study, we analyze the marketability (revenue), profitability (operating profits), and management conditions (net profits) of parcel service companies by combining information on human resources (number of employees) and material resources (total assets and equity). Therefore, the number of employees, total assets, and equity are selected as input variables, and revenue, operating profits, and net profits as the output variables. In this study, DEA (Data Envelopment Analysis) is used to measure the comparative efficiency and MPI (Malmquist Productivity Index) is used to analyze the trend of change of the efficiency for a multi-year period. Results - The operational efficiency scores of medium-sized parcel delivery companies in Korea are higher than other larger competitors such as Korean, Japan and Global larger companies. As of 2014, Logen(1.878) was found to be the most efficient parcel delivery enterprise, followed by KGB (1.224), and Kyoungdong(1.002). Otherwise, Hanjin(0.235), CJ(0.262), Hyundai Logistics(0.657), DHL(0.611), UPS(0.766), FedEx(0.498), TNT(0.350), Yamato(0.762) and Sagawa(0.520), larger sized companies, were done inefficiently. The productivity of parcel delivery companies is influenced by endogenous factors as well as exogenous ones such as changes in business environment and technological advances. Conclusions - Korean medium-sized companies have relatively high efficiency scores in operation. That is why they still survive the competitive market in Korea where market restructuring on the industry has been expected to be conducted for many years. The reason why medium-sized couriers had higher efficient scores than larger couriers is that most of couriers spend more operating expenses versus unit price of delivery which is the amount of money that is needed in order to send a package by parcel service. So the delivery unit price must be taken into account by all the expenses associated with the cost of fuel, labor and maintenance expenses for facilities, etc. therefore, the unit price must be increased to strengthen business competitive power. In order for the industry to have more competitive advantage, the companies need to make profits by increasing demand volume and raising the delivery rate to provide high-quality delivery service to customers. And both endogenous and exogenous change must take precedence in order to strengthen their competitiveness.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.289-297
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• 2010

Common practice of Soil Water Assessment Tool (SWAT) model validation is to use a single variable (i.e., streamlfow) to calibrate SWAT model due to the paucity of actual hydrological measurement data in Korea. This approach, however, often causes errors in the simulated results because of numerous sources of uncertainty and complexity of SWAT model. We employed multi-variables (i.e., streamflow, evapotranspiration, and soil moisture), which were measured at mixed forest in Seolmacheon catchment ($8.54\;km^2$), in order to assess the performance and reduce the uncertainties of SWAT model output. Meteorological and surface topographical data of the catchment were obtained as basic input variables and SWAT model was calibrated using daily data of streamflow (Jan. - Dec.), evapotranspiration (Sep. - Dec.), and soil moisture (Jun. - Dec.) collected in 2007. The model performance was assessed by comparing its results with the observation (i.e., streamflow of 2003 to 2008 and evapotranspiration and soil moisture of 2008). When the multi-variable measurements were used to calibrate the SWAT model, the model results showed better agreement with the measurements compared to those using a single variable measurement by showing increases in coefficient of determination ($R^2$) from 0.72 to 0.76 for streamflow, from 0.49 to 0.59 for soil moisture, and from 0.52 to 0.59 for evapotranspiration. The findings highlight the importance of reliable and accurate collective observation data for improving performance of SWAT model and promote its facilitation for estimating more realistic hydrological cycles at catchment scale.