• Korean Journal of Optics and Photonics
• /
• v.31 no.2
• /
• pp.105-110
• /
• 2020

A compact beam combiner based on two-mode interference (TMI) in multimode waveguides is proposed, and its feasibility is shown through simulation with the three-dimensional beam propagation method. The input waveguides are separated by about 1 ㎛ at the interface with the multimode waveguide, so that the fabricated waveguide pattern is well repeated. The power transmission to the output port from the red, green, and blue input port is 93.5%, 94%, and 93%, respectively. When the wavelength deviation from a center wavelength is 10 nm, the power transmission is maintained to be greater than 90%. When the waveguide width error is 40 nm, the power transmission is maintained to be greater than 85% for all the three colors. The polarization dependence of the beam combiner is almost negligible, and its size is as tiny as 0.02 × 4 ㎟.

• Journal of ILASS-Korea
• /
• v.27 no.2
• /
• pp.57-65
• /
• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.11
• /
• pp.1619-1626
• /
• 2021

Unlike traditional delta-sigma analog-to-digital converters, incremental analog-to-digital converters enable 1:1 mapping of input and output through a reset operation, which can be used very easily for multiplexing. Incremental analog-to-digital converters also allow for simpler digital filter designs compared to traditional delta-sigma converters. Therefore, starting with analysis in the time domain of the delayed integrator and non-delayed integrator, which are the basic blocks of analog-to-digital converter design, the design equations of a second-order input feed-forward, extended counting, 2+1 MASH (Multi-stAge-noise-SHaping), 2+2 MASH incremental analog-to-digital converter are derived in this paper. This allows not only prediction of the performance of the incremental analog-to-digital converter before design, but also the design of a digital filter suitable for each analog-to-digital converter. In addition, extended counting and MASH design techniques were proposed to improve the accuracy of analog-to-digital converters.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.7
• /
• pp.36-44
• /
• 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
• /
• v.51 no.12
• /
• pp.3-11
• /
• 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
• /
• v.37A no.12
• /
• pp.1076-1084
• /
• 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
• /
• v.17 no.1
• /
• pp.137-144
• /
• 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
• /
• v.37 no.1
• /
• pp.1-11
• /
• 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
• /
• v.7 no.1 s.13
• /
• pp.53-63
• /
• 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
• /
• v.9B no.2
• /
• pp.139-146
• /
• 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.