• Journal of Environmental Science International
• /
• v.30 no.5
• /
• pp.399-406
• /
• 2021

The dissolution of ionized gas in dielectric barrier plasma, similar to the principle of ozone generation, is a major performance-affecting factor. In this study, the plasma gas dissolving performance of a gas mixing-circulation plasma process was evaluated using an experimental design methodology. The plasma reaction is a function of four parameters [electric current (X₁), gas flow rate (X₂), liquid flow rate (X₃) and reaction time (X₄)] modeled by the Box-Behnken design. RNO (N, N-Dimethyl-4-nitrosoaniline), an indictor of OH radical formation, was evaluated using a quadratic response surface model. The model prediction equation derived for RNO degradation was shown as a second-order polynomial. By pooling the terms with poor explanatory power as error terms and performing ANOVA, results showed high significance, with an adjusted R² value of 0.9386; this indicate that the model adequately satisfies the polynomial fit. For the RNO degradation, the measured value and the predicted values by the model equation agreed relatively well. The optimum current, gas flow rate, liquid flow rate and reaction time were obtained for the highest desirability for RNO degradation at 0.21 A, 2.65 L/min, 0.75 L/min and 6.5 min, respectively.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.7
• /
• pp.639-645
• /
• 2010

This paper presents the sensor fusion algorithm that recognizes a primary vehicle by fusing radar and monocular vision data. In general, most of commercial radars may lose tracking of the primary vehicle, i.e., the closest preceding vehicle in the same lane, when it stops or goes with other preceding vehicles in the adjacent lane with similar velocity and range. In order to improve the performance degradation of radar, vehicle detection information from vision sensor and path prediction predicted by ego vehicle sensors will be combined for target classification. Then, the target classification will work with probabilistic association filters to track a primary vehicle. Finally the performance of the proposed sensor fusion algorithm is validated using field test data on highway.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.8A
• /
• pp.745-751
• /
• 2006

The transmitter requires knowledge of the channel status information in order to adopt the adaptive modulation and coding scheme(AMC) for OFDM system. But in the outdoor environment which the users have high mobility, the channel status information from the users is outdated, so that it induces the degradation of system throughput and packet error rate(PER) performance. To solve this problem, researches about applying channel prediction technique to the AMC scheme have been proceeded. Most channel prediction techniques assume that there is no channel variation in the predefined time duration, e.g., a slot. As a result, those techniques cannot compensate the degradation of PER performance resulting from the rapid variation of channel during the slot duration. This paper introduces a novel channel prediction technique for OFDM/FDD system to support adaptive modulation and coding scheme over rapidly time-varying multipath fading channel. The proposed channel prediction technique considers the time-varying nature of channel during the slot duration. Simulation results show that the AMC scheme of OFDM/FDD system utilizing the proposed channel prediction technique can guarantee the target PER of 1% without any loss of system throughput compared with the case supported by the conventional channel prediction under ITU-R Veh A 30km/h.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.899-902
• /
• 2005

Pipeline hazard due to branch instructions is the major factor of the degradation on the performance of microprocessors. Branch target buffer predicts whether a branch will be taken or not and supplies the address of the next instruction on the basis of that prediction. If the branch target buffer predicts correctly, the instruction flow will not be stalled. This leads to the better performance of microprocessor. In this paper, the architecture of a tag memory that branch target buffer and TLB can share is presented. Because the two tag memories used for branch target buffer and TLB each is replaced by single shared tag memory, we can expect the smaller ship size and the faster prediction. This hared tag architecture is more advantageous for the microprocessors that uses more bits of address and exploits much more instruction level parallelism.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.170-173
• /
• 2009

In this paper, we propose a fast intra prediction mode selection method in Scalable Video Coding(SVC) which is an emerging video coding standard as an extension of H.264/Advanced Video Coding(H.264/AVC). The proposed method decides a candidate intra prediction mode based on the characteristic of macroblock smoothness. Statistical analysis is applied to computing that smoothness in spatial enhancement layer. We also propose an early termination scheme for Intra_BL mode decision where the RD cost value of Intra_BL is utilized. Compared with JSVM software, our scheme can reduce about 55% of the computation complexity of intra prediction on average, while the performance degradation is negligible; For low QP values, the average PSNR loss is very negligible, equivalently the bit rate increases by 0.01%. For high QP values, the average PSNR loss is less than 0.01dB, which equals to 0.25% increase in bitrate on average.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2000.04a
• /
• pp.18-18
• /
• 2000

In the high lift devices specifications for surface smoothness requirements, as manufacturing tolerances, arise out of aerodynamic consideration to minimize drag. True optimization of tolerances is a multi-disciplinary problem involving fluid mechanics, device performance, manufacturing philosophy and life cycle costing. One of the reasons for degradation of wetted surface is discrete roughness as a consequence of manufacturing defects, collectively termed as one of the excrescences effect. Usually, excrescence drag arising out of discrete roughness is of considerable lower order of magnitude as compared to the total drag of the flight bodies. Nor was there adequate predicting tool to account for the extent of drag degradation. Estimation of excrescence drag remained as a state-of-the art based on experimental results.

• Smart Structures and Systems
• /
• v.22 no.2
• /
• pp.167-174
• /
• 2018

Digital input and output modules are widely used to connect digital sensors and actuators to automation systems. Digital I/O modules provide flexible connectivity extension to numerous sensors and actuators and protect systems from high voltages and currents by isolation. Components in digital I/O modules are inevitably affected by operating and environmental conditions, such as high voltage, high current, high temperature, and temperature cycling. Because digital I/O modules transfer signals or isolate the systems from unexpected voltage and current transients, their failures may result in signal transmission failures and damages to sensitive circuitry leading to system malfunction and system shutdown. In this study, the lifetime of optocouplers, one of the critical components in digital I/O modules, was predicted using Bayesian tracking approaches. Accelerated degradation tests were conducted for collecting the critical performance parameter of optocouplers, current transfer ratio (CTR), during their lifetime. Bayesian tracking approaches, including extended Kalman filter and particle filter, were applied to predict the failure. The performance of each prognostic algorithm was then compared using accuracy and robustness-based performance metrics.

• Transactions on Electrical and Electronic Materials
• /
• v.13 no.5
• /
• pp.256-261
• /
• 2012

Recently, many photovoltaic systems (PV systems) including solar parks and PV farms have been built to prepare for the post fossil fuel era. To investigate the degradation process of the PV systems and thus, efficiently operate PV systems, there is a need to visually monitor PV systems in the range of infrared ray through the Internet. For efficient visual monitoring, this paper explores a multithreaded implementation of a recently developed HEVC standard whose compression efficiency is almost two times higher than H.264. For an efficient parallel implementation under a meshbased 64 multicore system, this work takes into account various design choices which can solve potential problems of a two-dimensional interconnects-based 64 multicore system. These problems may have not occurred in a small-scale multicore system based on a simple bus network. Through extensive evaluation, this paper shows that, for an efficient multithreaded implementation of HEVC intra prediction in a mesh-based multicore system, much effort needs to be made to optimize communications among processing cores. Thus, this work provides three design choices regarding communications, i.e., main thread core location, cache home policy, and maximum coding unit size. These design choices are shown to improve the overall parallel performance of the HEVC intra prediction algorithm by up to 42%, achieving a 7 times higher speed-up.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.4
• /
• pp.412-417
• /
• 2005

The Internet has been widely applied to the remote control system. The network-based control system, however, has a random time delay and an inherent weak point of the network, when the data ate transmitted. The network delay may result in performance degradation or even system instability in teleoperation. In this paper a prediction model of network delay using TSK (Takagi-Sugeno-Kang) fuzzy model is presented. An adaptive scheme is developed to update the prediction model according to the current network status. The prediction model is applied to the control of an Internet-based mobile robot to show its usefulness. In the computer simulation the TSK Prediction model of network delay is proven superior to the conventional algorithms.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.4E
• /
• pp.11-16
• /
• 1998

For large vocabulary speech recognition using HMMs, context-dependent subword units have been often employed. However, when context-dependent phone models are used, they result in a system which has too may parameters to train. The problem of too many parameters and too little training data is absolutely crucial in the design of a statistical speech recognizer. Furthermore, when building large vocabulary speech recognition systems, unseen triphone problem is unavoidable. In this paper, we propose the modified phonetic decision tree algorithm for the automatic prediction of unseen triphones which has advantages solving these problems through following two experiments in Japanese contexts. The baseline experimental results show that the modified tree based clustering algorithm is effective for clustering and reducing the number of states without any degradation in performance. The task experimental results show that our proposed algorithm also has the advantage of providing a automatic prediction of unseen triphones.