• Bulletin of the Korean Chemical Society
• /
• v.31 no.10
• /
• pp.2761-2770
• /
• 2010

In this study, we have developed QSAR models for a series of 38 piperidine-4-carboxamide CCR5 antagonists using CoMFA, CoMSIA and HQSAR methods. Developed models showed good statistics in terms of $q^2$ and $r^2$ values. Best predictions obtained with standard CoMFA model ($r^2$ = 0.888, $q^2$ = 0.651) and combined CoMSIA model ($r^2$ = 0.892, $q^2$ = 0.665) with electrostatics and H-bond acceptor parameter. The validity of developed models was assessed by test set of 9 compounds, which showed good predictive correlation coefficient for CoMFA (0.804) and CoMSIA (0.844). Bootstrapped analysis showed statistically significant and robust CoMFA (0.968) and CoMSIA (0.936) models. Best HQSAR model was obtained with a $q^2$ of 0.662 and $r^2$ of 0.936 using atom, connection, hydrogen, donor and acceptor as parameters and fragment size (7-10) with optimum number of 6 components. Predictive power of developed HQSAR model was proved by test set and it was found to be 0.728.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1491-1498
• /
• 2014

The major criticism of optimal experimental design is that it depends heavily on the model and its accompanying assumption that often leads the number of support points equal to the number of parameters in the model. Often in the past, a polynomial model of higher degree is assumed to handle the experimental design for the polynomial regression of lower degree. In this paper we searched the possible set of designs which are robust to the departure of the assumed model. The designs are categorized with respect to D-efficiency. The approach by O'Brien (1995) was discussed in univariate polynomial regression model setting.

• The Korean Journal of Applied Statistics
• /
• v.6 no.2
• /
• pp.371-381
• /
• 1993

When the multicollinearity presents in the standard linear regression model, ridge regression might be used to mitigate the effects of collinearity. As the prediction-oriented criterion, the integrated mean sqare error criterion $J_w(k)$ was introduced by Lim, Choi & Park(1980). By noting the equivalent relationship between the $C_k$ criterion and $J_w(k)$ with a special choice of weight function $W(x)$, we propose a more reasonable selection rule of k w.r.t. the $C_k$ criterion than that given in Myers(1986). Next, to find the $\beta(k)$ which behaves reasonably well w.r.t. competing criteria, we adopt the minimax principle in the sense of maximizing the worst relative efficiency of k among competing criteria.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.9
• /
• pp.1060-1069
• /
• 2019

Pedestrian-based camera self-calibration methods are suitable for video surveillance systems since they do not require complex calibration devices or procedures. However, using arbitrary pedestrians as calibration targets may result in poor calibration accuracy due to the unknown height of each pedestrian. To solve this problem in the real surveillance environments, this paper proposes a novel Bayesian approach. By assuming known statistics on the height of pedestrians, we construct a probabilistic model that takes into account uncertainties in both the foot/head locations and the pedestrian heights, using foot-head homology. Since solving the model directly is infeasible, we use variational Bayesian inference, an approximate inference algorithm. Accordingly, this makes it possible to estimate the height of pedestrians and to obtain accurate camera parameters simultaneously. Experimental results show that the proposed algorithm is robust to noise and provides accurate confidence in the calibration.

• Journal of Positioning, Navigation, and Timing
• /
• v.8 no.2
• /
• pp.79-85
• /
• 2019

The mission tasks of polar exploration utilizing unmanned systems such as glacier monitoring, ecosystem research, and inland exploration have been expanded. To facilitate unmanned exploration mission tasks, precise and robust navigation systems are required. However, limitations on the utilization of satellite navigation system are present due to satellite orbital characteristics at the polar region located in a high latitude. The orbital inclination of global positioning system (GPS), which was developed to be utilized in mid-latitude sites, was designed at $55^{\circ}$. This means that as the user is located in higher latitudes, the satellite visibility and vertical precision become worse. In addition, the use of satellite-based wide-area augmentation system (SBAS) is also limited in higher latitude regions than the maximum latitude of signal reception by stationary satellites, which is $70^{\circ}$. This study proposes a local-area augmentation system that additionally utilizes Global Navigation Satellite System (GLONASS) considering satellite navigation system environment in Polar Regions. The orbital inclination of GLONASS is $64.8^{\circ}$, which is suitable in order to ensure satellite visibility in high-latitude regions. In contrast, GLONASS has different system operation elements such as configuration elements of navigation message and update cycle and has a statistically different signal error level around 4 m, which is larger than that of GPS. Thus, such system characteristics must be taken into consideration to ensure data integrity and monitor GLONASS signal fault. This study took GLONASS system characteristics and performance into consideration to improve previously developed fault detection algorithm in the local-area augmentation system based on GPS. In addition, real GNSS observation data were acquired from the receivers installed at the Antarctic King Sejong Station to analyze positioning accuracy and calculate test statistics of the fault monitors. Finally, this study analyzed the satellite visibility of GPS/GLONASS-based local-area augmentation system in Polar Regions and conducted performance evaluations through simulations.

• Journal of Korean Society for Quality Management
• /
• v.50 no.3
• /
• pp.473-490
• /
• 2022

Purpose: The purpose of this study is to propose a new useful suggestion to monitor the stability of process by developing a stability ratio or index related to investigating how well the process is controlled or operated to the specified target. Methods: The proposed method to monitor the stability of process is building up a new measure index which is making up for the weakness of the existing index in terms of short or long term period of production. This new index is a combined one considering both stability and capability of process to the specification limits. We suppose that both process mean and process variation(or deviation) are changing on time period. Results: The results of this study are as follows: regarding the stability of process as well as capability of process, it was shown that two indices, called SI(stability index) and PI(performance index), can be expressed in two-dimensional X-Y graph simultaneously. This graph is categorized as 4 separated partitions, which are characterized by its numerical value intervals of SI and PI which are evaluated by test statistics. Conclusion: The new revised index is more robust than the existing one in investigating the stability of process in terms of short and long period of production, even in case both process mean and variation are changing.

• Advances in nano research
• /
• v.15 no.5
• /
• pp.401-410
• /
• 2023

Vibration investigation of fluid-filled three layered cylindrical shells is studied here. A cylindrical shell is immersed in a fluid which is a non-viscous one. Shell motion equations are framed first order shell theory due to Love. These equations are partial differential equations which are usually solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the wave propagation approach procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. Hankel's functions of second kind designate the fluid influence. Mathematically the integral form of the Lagrange energy functional is converted into a set of three partial differential equations. It is also exhibited that the effect of frequencies is investigated by varying the different layers with constituent material. The coupled frequencies changes with these layers according to the material formation of fluid-filled FG-CSs. Throughout the computation, it is observed that the frequency behavior for the boundary conditions follow as; clamped-clamped (C-C), simply supported-simply supported (SS-SS) frequency curves are higher than that of clamped-simply (C-S) curves. Expressions for modal displacement functions, the three unknown functions are supposed in such way that the axial, circumferential and time variables are separated by the product method. Computer software MATLAB codes are used to solve the frequency equation for extracting vibrations of fluid-filled.

• Communications for Statistical Applications and Methods
• /
• v.31 no.1
• /
• pp.1-35
• /
• 2024

The assumption of homoscedasticity is one of the most crucial assumptions for many parametric tests used in the biological sciences. The aim of this paper is to compare the empirical probability of type I error and the power of ten parametric and two non-parametric tests for homoscedasticity with simulations under different types of distributions, number of groups, number of samples per group, variance ratio and significance levels, as well as through empirical data from an agricultural experiment. According to the findings of the simulation study, when there is no violation of the assumption of normality and the groups have equal variances and equal number of samples, the Bhandary-Dai, Cochran's C, Hartley's Fmax, Levene (trimmed mean) and Bartlett tests are considered robust. The Levene (absolute and square deviations) tests show a high probability of type I error in a small number of samples, which increases as the number of groups rises. When data groups display a nonnormal distribution, researchers should utilize the Levene (trimmed mean), O'Brien and Brown-Forsythe tests. On the other hand, if the assumption of normality is not violated but diagnostic plots indicate unequal variances between groups, researchers are advised to use the Bartlett, Z-variance, Bhandary-Dai and Levene (trimmed mean) tests. Assessing the tests being considered, the test that stands out as the most well-rounded choice is the Levene's test (trimmed mean), which provides satisfactory type I error control and relatively high power. According to the findings of the study and for the scenarios considered, the two non-parametric tests are not recommended. In conclusion, it is suggested to initially check for normality and consider the number of samples per group before choosing the most appropriate test for homoscedasticity.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.2
• /
• pp.96-100
• /
• 2006

Kim et al. Proposed Normalized Confidence Measure (NCM) [1-2] and it was successfully used for rejecting mis-recognized words in isolated word recognition. However their experiments were performed on the fixed word speech recognition. In this Paper we apply NCM to the domain of vocabulary independent speech recognition (VISP) and shows the rejection Performance of NCM in VISP. Specialty we Propose vector quantization (VQ) based method for overcoming the problem of unseen triphones. It is because NCM uses the statistics of triphone confidence in the case of triphone-based normalization. According to speech recognition experiments Phone-based normalization method shows better results than RLJC[3] and also triphone-based normalization approach. This results are different with those of Kim et al [1-2]. Concludingly the Phone-based normalization shows robust Performance in VISP domain.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.1
• /
• pp.182-196
• /
• 2024

This study introduces driving pattern analysis and change detection methods using smartphone sensors, based on contrastive learning. These methods characterize driving patterns without labeled data, allowing accurate classification with minimal labeling. In addition, they are robust to domain changes, such as different vehicle types. The study also examined the applicability of these methods to smartphones by comparing them with six lightweight deep-learning models. This comparison supported the development of smartphone-based driving pattern analysis and assistance systems, utilizing smartphone sensors and contrastive learning to enhance driving safety and efficiency while reducing the need for extensive labeled data. This research offers a promising avenue for addressing contemporary transportation challenges and advancing intelligent transportation systems.