• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.1009-1012
• /
• 1999

An analytical performance model that can predict the performance of a superscalar processor employing multiple branch prediction is introduced. The model is based on the conditional independence probability and the basic block size of instructions, with the degree of multiple branch prediction, the fetch rate, and the window size of a superscalar architecture. Trace driven simulation is performed for the subset of SPEC integer benchmarks, and the measured IPCs are compared with the results derived from the model. As the result, our analytic model could predict the performance of the superscalar processor using multiple branch prediction within 6.6 percent on the average.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.63-68
• /
• 2017

In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.47
• /
• pp.211-218
• /
• 1998

In start-up process control applications it may be necessary to limit the sample size to one measurement. A control chart for individual measurements is used whenever it is desirable to examine each individual value from the process immediately. A possible option would be to use an exponential weighted moving(EWM), using modifying statistics with individual measurement, chart for monitoring the process center, and using a moving range (MR) chart for monitoring process variability. In this paper it is shown that there is scheme in using the EWM procedure based on average run length. An expression for the ARL is given in terms of an integral equation, approximated using numerical quadrature. In this case, where it is reasonable to assume normality and negligible autocorrelation in the observations, provide graphs that simplify the design of EWM-MR chart and taking method of exponential smoothing constant(λ) and constant(K) are suggested. The charts suggested above evaluate using the conditional probability.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.2 no.3
• /
• pp.223-234
• /
• 1998

In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of structure system, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of PEM and AFOSM are applied to retaining wall.

• Current Optics and Photonics
• /
• v.1 no.5
• /
• pp.440-455
• /
• 2017

In this paper, we carry out a performance analysis of a two-user free-space optical (FSO) communication system with photodetector multiplexing, in which the two users are defined as the primary user (PU) and secondary user (SU). Unlike common single-user FSO systems, our photodetector multiplexing FSO system deploys a shared detector at the receiver and enables PU and SU to send their own data synchronously. We conduct the performance analysis of this FSO system for two cases: (1) in the absence of background radiation, and (2) in the presence of background radiation. Decision strategies for PU and SU are presented according to the two scenarios above. Exact and approximate conditional symbol-error probability (SEP) expressions for both PU and SU are derived, in an ideal channel with no fading. Average SEP expressions are also presented in the no-background-radiation scenario. Additionally, in some particular cases where the power ratio tends to 0.5 or 1, approximate SEP expressions are also obtained. Finally, numerical simulations are presented under different conditions, to support the performance analysis.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.933-937
• /
• 2010

This study aimed at the introduction of desktop method for assessment of environmental flows developed by IWMI(International Water Management Institute) recently and its application to Geum river basin. This scheme simulated the influence on aquatic ecosystem caused by watershed development and in turn the decrease of water quantity keeping the river's own flow regime. It was found to be as very effective method although it had simple structure. Flow duration curves for different environmental classes at Sutong and Gongjoo sites were estimated according to the natural conditional scenario of Geum river basin and the results were relatively compared well with the previous studies. The behaviors of monthly average runoff time series of both sites showed the level of A class. The results of this study would provide the fundamental data to establish the future plans of monitoring or management for aquatic ecosystem of Geum river basin.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.2 no.2
• /
• pp.151-161
• /
• 1998

In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of RC highway bridge, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of visual inspection and extensive field load tests are applied to the integrity assessment of a new RC highway bridge, namely, Jichok bridge.

• Bulletin of the Korean Chemical Society
• /
• v.14 no.4
• /
• pp.453-457
• /
• 1993

Cadmium(II) complexation by a well characterized soil fulvic acid (FA) from the Okchun Metamorphic Belt were studied at pH of 6.0 in 0.1 M $NaClO_4$ using the ultrafiltration technique. The conditional stability constants thus obtained were log K= 3.90${\pm}$0.15 and 3.99${\pm}$0.12 $L{\cdot}mol^{-1}$ at fulvic acid concentrations of 101 and 226 mg${\cdot}L^{-1}$ respectively. When free cadmium ion concentration was measured directly using an ion selective electrode, log K of 4.12${\pm}$0.03 $L{\cdot}mol^{-1}$ was obtained. These results show that fulvic acid forms predominately 1 : 1 complex with $Cd^{2+}$ ions. The maximum binding ability of this polyelectrolyte material was 0.886 mmol Cd/g FA. The average gram formula weight of fulvic acid was estimated to be 1130 daltons.

• Journal of Industrial Convergence
• /
• v.2 no.2
• /
• pp.127-147
• /
• 2004

This paper examines the time-series relations among expected return, risk, and book-to-market(B/M) at the portfolio level. The time-series analysis is a natural alternative to cross-sectional regressions. An alternative feature of the time-series regressions is that they focus on changes in expected returns, not on average returns. Using the time-series analysis, we can directly test whether the three-factor model explains time-varying expected returns better than the characteristic-based model. These results should help distinguish between the risk and mispricing stories. We find that B/M is strongly associated with changes in risk, as measured by the Fama and French(1993) three-factor model. After controlling for changes in risk, B/M contains little additional information about expected returns. The evidence suggests that the three-factor model explains time-varying expected returns better than the characteristic-based model.

• The Korean Journal of Applied Statistics
• /
• v.32 no.2
• /
• pp.173-185
• /
• 2019

Causal questions are prevalent in scientific research, for example, how effective a treatment was for preventing an infectious disease, how much a policy increased utility, or which advertisement would give the highest click rate for a given customer. Causal inference theory in statistics interprets those questions as inferring the effect of a given intervention (treatment or policy) in the data generating process. Causal inference has been used in medicine, public health, and economics; in addition, it has received recent attention as a tool for data-driven decision making processes. Many recent datasets are observational, rather than experimental, which makes the causal inference theory more complex. This review introduces key concepts and recent trends of statistical causal inference in observational studies. We first introduce the Neyman-Rubin's potential outcome framework to formularize from causal questions to average treatment effects as well as discuss popular methods to estimate treatment effects such as propensity score approaches and regression approaches. For recent trends, we briefly discuss (1) conditional (heterogeneous) treatment effects and machine learning-based approaches, (2) curse of dimensionality on the estimation of treatment effect and its remedies, and (3) Pearl's structural causal model to deal with more complex causal relationships and its connection to the Neyman-Rubin's potential outcome model.