Journal of the Institute of Electronics Engineers of Korea SD
/
v.46
no.9
/
pp.58-67
/
2009
This paper presents a fully digital gain control system with a new high bandwidth and wide dynamic range power detector for DVB-S2 application. Because the peak-to-average power ratio (PAPR) of DVB-S2 system is so high and the settling time requirement is so stringent, the conventional closed-loop analog gain control scheme cannot be used. The digital gain control is necessary for the robust gain control and the direct digital interface with the baseband modem. Also, it has several advantages over the analog gain control in terms of the settling time and insensitivity to the process, voltage and temperature variation. In order to have a wide gain range with fine step resolution, a new AGC system is proposed. The system is composed of high-bandwidth digital VGAs, wide dynamic range power detectors with RMS detector, low power SAR type ADC, and a digital gain controller. To reduce the power consumption and chip area, only one SAR type ADC is used, and its input is time-interleaved based on four power detectors. Simulation and measurement results show that the new AGC system converges with gain error less than 0.25 dB to the desired level within $10{\mu}s$. It is implemented in a $0.18{\mu}m$ CMOS process. The measurement results of the proposed IF AGC system exhibit 80-dB gain range with 0.25-dB resolution, 8 nV/$\sqrt{Hz}$ input referred noise, and 5-dBm $IIP_3$ at 60-mW power consumption. The power detector shows the 35dB dynamic range for 100 MHz input.
Journal of the Institute of Electronics Engineers of Korea SD
/
v.43
no.3
s.345
/
pp.21-32
/
2006
A new SRAM circuit with row-by-row activation and low-swing write schemes is proposed to reduce switching power of active cells as well as leakage one of sleep cells in this paper. By driving source line of sleep cells by $V_{SSH}$ which is higher than $V_{SS}$, the leakage current can be reduced to 1/100 due to the cooperation of the reverse body-bias. Drain Induced Barrier Lowering (DIBL), and negative $V_{GS}$ effects. Moreover, the bit line leakage which may introduce a fault during the read operation can be eliminated in this new SRAM. Swing voltage on highly capacitive bit lines is reduced to $V_{DD}-to-V_{SSH}$ from the conventional $V_{DD}-to-V_{SS}$ during the write operation, greatly saving the bit line switching power. Combining the row-by-row activation scheme with the low-swing write does not require the additional area penalty. By the SPICE simulation with the Berkeley Predictive Technology Modes, 93% of leakage power and 43% of switching one are estimated to be saved in future leakage-dominant 70-un process. A test chip has been fabricated using $0.35-{\mu}m$ CMOS process to verify the effectiveness and feasibility of the new SRAM, where the switching power is measured to be 30% less than the conventional SRAM when the I/O bit width is only 8. The stored data is confirmed to be retained without loss until the retention voltage is reduced to 1.1V which is mainly due to the metal shield. The switching power will be expected to be more significant with increasing the I/O bit width.
$CO_2$ geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing $CO_2$ safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of $CO_2$ storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the $CO_2$ sequestration initiative. More detailed characterization of the geological storage and the simulation of $CO_2$ migration might be an essential for the CCS demonstration.
Journal of the Korean Association of Geographic Information Studies
/
v.18
no.3
/
pp.21-34
/
2015
In this study, a reference model is constructed that provides architects or designers with sufficient information on the intelligent service facility that is essential for U-City space configuration, and for the support of enhanced design, as well as for planning activities. At the core of the reference model is comprehensive information about the intelligent service facility that plans the content of services, and the latest related information that is regularly updated. A plan is presented to take advantage of the database of list information systems in the Public Procurement Service that handles intelligent service facilities. We suggest a number of improvements by analyzing the current status of, and issues with, the goods information in the Public Procurement Service, and by conducting a simulation for the proper placement of CCTV. As the design of U-City plan has evolved from IT technology-based to smart space-based, reviews of limitations such as the lack of standards, information about the installation, and the placement of the intelligent service facility that provides U-service have been carried out. Due to the absence of relevant legislation and guidelines, however, planning activities, such as the appropriate placement of the intelligent service facility are difficult when considering efficient service provision. In addition, with the lack of information about IT technology and intelligent service facilities that can be provided to U-City planners and designers, there are a number of difficulties when establishing an optimal plan with respect to service level and budget. To solve these problems, this study presents a plan in conjunction with the goods information from the Public Procurement Service. The Public Procurement Service has already built an industry-related database of around 260,000 cases, which has been continually updated. It can be a very useful source of information about the intelligent service facility, the ever-changing U-City industry's core, and the relevant technologies. However, since providing this information is insufficient in the application process and, due to the constraints in the information disclosure process, there have been some issues in its application. Therefore, this study, by presenting an improvement plan for the linkage and application of the goods information in the Public Procurement Service, has significance for the provision of the basic framework for future U-City enhancement plans, and multi-departments' common utilization of the goods information in the Public Procurement Service.
Journal of Korean Society of Coastal and Ocean Engineers
/
v.31
no.1
/
pp.28-39
/
2019
In the design process of counter measures against the beach erosion, information like the main sediment transport mode and yearly net amount of longshore and cross shore transport is of great engineering value. In this rationale, we numerically analyzed the yearly sediment budget of the Mang-Bang beach which is suffering from erosion problem. For the case of cross sediment transport, Bailard's model (1981) having its roots on the Bagnold's energy model (1963) is utilized. In doing so, longshore sediment transport rate is estimated based on the assumption that longshore transport rate is determined by the available wave energy influx toward the beach. Velocity moments required for the application of Bailard's model (1981) is deduced from numerical simulation of the nonlinear shoaling process over the Mang-Bang beach of the 71 wave conditions carefully chosen from the wave records. As a wave driver, we used the consistent frequency Boussinesq Eq. by Frelich and Guza (1984). Numerical results show that contrary to the Bailard's study (1981), Irribaren NO. has non negligible influence on the velocity moments. We also proceeds to numerically simulate the yearly sediment budget of Mang-Bang beach. Numerical results show that for ${\beta}=41.6^{\circ}$, the mean orientation of Mang-Bang beach, north-westwardly moving longshore sediment is prevailing over the south-eastwardly moving sediment, the yearly amount of which is simulated to reach its maxima at $125,000m^3/m$. And the null pint where north-westwardly moving longshore sediment is balanced by the south-eastwardly moving longshore sediment is located at ${\beta}=47^{\circ}$. For the case of cross shore sediment, the sediment is gradually moving toward the shore from the April to mid October, whereas these trends are reversed by sporadically occurring energetic wind waves at the end of October and March. We also complete the littoral drift rose of the Mang-Bang beach, which shows that even though the shore line is temporarily retreated, and as a result, the orientation of Mang-Bang beach is larger than the orientation of null pont, south-eastwardly moving longshore sediment is prevailing. In a case that the orientation of Mang-Bang beach is smaller than the orientation of null pont, north-westwardly moving longshore sediment is prevailing. And these trend imply that the Mang-Bang beach is stable one, which has the self restoring capability once exposed to erosion.
Journal of Korean Society of Coastal and Ocean Engineers
/
v.30
no.6
/
pp.306-318
/
2018
In order to evaluate the seismic capacity of massive vertical type breakwaters which have intensively been deployed along the coast of South Korea over the last two decades, we carry out the preliminary numerical simulation against the PoHang, GyeongJu, Hachinohe 1, Hachinohe 2, Ofunato, and artificial seismic waves based on the measured time series of ground acceleration. Numerical result shows that significant sliding can be resulted in once non-negligible portion of seismic energy is shifted toward the longer period during its propagation process toward the ground surface in a form of shear wave. It is well known that during these propagation process, shear waves due to the seismic activity would be amplified, and non-negligible portion of seismic energy be shifted toward the longer period. Among these, the shift of seismic energy toward the longer period is induced by the viscosity and internal friction intrinsic in the soil. On the other hand, the amplification of shear waves can be attributed to the fact that the shear modulus is getting smaller toward the ground surface following the descending effective stress toward the ground surface. And the weakened intensity of soil as the number of attacking shear waves are accumulated can also contribute these phenomenon (Das, 1993). In this rationale, we constitute the numerical model using the model by Hardin and Drnevich (1972) for the weakened shear modulus as shear waves go on, and shear wave equation, in the numerical integration of which $Newmark-{\beta}$ method and Modified Newton-Raphson method are evoked to take nonlinear stress-strain relationship into account. It is shown that the numerical model proposed in this study could duplicate the well known features of seismic shear waves such as that a great deal of probability mass is shifted toward the larger amplitude and longer period when shear waves propagate toward the ground surface.
Journal of Korea Society of Industrial Information Systems
/
v.28
no.6
/
pp.53-62
/
2023
This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.
One of the most important decisions for managers in the online banner advertising industry, is to choose the best banner alternative for exposure to customers. Since it is difficult to know the click probability of each banner alternative in advance, managers must experiment with multiple alternatives, estimate the click probability of each alternative based on customer clicks, and find the optimal alternative. In this reinforcement learning process, the main decision problem is to find the optimal balance between the level of exploitation strategy that utilizes the accumulated estimated click probability information and exploration strategy that tries new alternatives to find potentially better options. In this study we analyze the impact of word-of-mouth effects and the number of alternatives on the optimal exploration-exploitation strategies. More specifically, we focus on the word-of-mouth effect, where the click-through rate of the banner increases as customers promote the related product to those around them after clicking the exposed banner, and add it to the overall reinforcement learning process. We analyze our problem by employing the Multi-Armed Bandit model, and the analysis results show that the larger the word-of-mouth effect and the fewer the number of banner alternatives, the higher the optimal exploration level of advertising reinforcement learning. We find that as the probability of customers clicking on the banner increases due to the word-of-mouth effect, the value of the previously accumulated estimated click-through rate knowledge decreases, and therefore the value of exploring new alternatives increases. Additionally, when the number of advertising alternatives is small, a larger increase in the optimal exploration level was observed as the magnitude of the word-of-mouth effect increased. This study provides meaningful academic and managerial implications at a time when online word-of-mouth and its impact on society and business is becoming more important.
Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.
Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.
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