• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.231-243
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• 1997

In this paper we investigate weak convergence of the intergral processes whose index set is the non-compact infinite time interval. Our first goal is to develop the empirical central limit theorem as random elements of [0, .infty.) for an integral process which is constructed from iid variables. In developing the weak convergence as random elements of D[0, .infty.), we will use a result of Ossiander(4) whose proof heavily depends on the total boundedness of the index set. Our next goal is to establish the empirical central limit theorem for the Kaplan-Meier integral process as random elements of D[0, .infty.). In achieving the the goal, we will use the above iid result, a representation of State(6) on the Kaplan-Meier integral, and a lemma on the uniform order of convergence. The first result, in some sense, generalizes the result of empirical central limit therem of Pollard(5) where the process is regarded as random elements of D[-.infty., .infty.] and the sample paths of limiting Gaussian process may jump. The second result generalizes the first result to random censorship model. The later also generalizes one dimensional central limit theorem of Stute(6) to a process version. These results may be used in the nonparametric statistical inference.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.825-831
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• 2017

Radar clutter in real environment is in general heterogeneous and especially nonstationary if radar geometry is of non-sidelooking monostatic structure or bistatic structure. These clutter properties lead to the insufficient number of secondary data of IID(Independent identically distributed) property, conclusively deteriorate clutter suppression performance. In this paper, we propose a clutter suppression algorithm that estimates the clutter signal belonging to cull under test via calculation using only prior information, rather than using the secondary data. Through analyzing the angle-Doppler spectrum of the clutter signal, we show the estimation of the clutter signal using prior information only is possible and present the derivation of a clutter suppression algorithm through eigen-value analysis. Finally, we show the performance of the proposed algorithm by simulation.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.27-40
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• 2022

Medical AI, which has lately made significant advances, is playing a vital role, such as assisting clinicians with diagnosis and decision-making. The field of chest X-rays, in particular, is attracting a lot of attention since it is important for accessibility and identification of chest diseases, as well as the current COVID-19 pandemic. However, despite the vast amount of data, there remains a limit to developing an effective AI model due to a lack of labeled data. A research that used federated learning on chest X-ray data to lessen this difficulty has emerged, although it still has the following limitations. 1) It does not consider the problems that may occur in the Non-IID environment. 2) Even in the federated learning environment, there is still a shortage of labeled data of clients. We propose a method to solve the above problems by using the self-supervised learning model as a global model of federated learning. To that aim, we investigate a self-supervised learning methods suited for federated learning using chest X-ray data and demonstrate the benefits of adopting the self-supervised learning model for federated learning.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.119-130
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• 2003

SP data have been widely used in assessing new transport policies and transport related plans. However, one of criticisms of using SP is that respondents may show different reaction between hypothetical experiments and real life. In order to overcome the problem, combination of SP and RP data has been suggested and the combined methods have been being developed. The purpose of this paper is to suggest a new SP and RP combined method using error component method and to verify the method. The error component method decomposes IID extreme value error into non-IID error component(s) and an IID error component. The method estimates both of component parameters and utility parameters in order to obtain relative variance of SP data and RP data. The artificial SP and RP data was created by using simulation and used for the analysis, and the estimation results of the error component method were compared with those of existing SP and RP combined methods. The results show that regardless of data size, the parameters of the error component method models are similar to those assumed parameters much more than those of the existing SP and RP combined models, indicating usefulness of the error component method. Also the values of time for error component method are more similar to those assumed values than those of the existing combined models. Therefore, we can conclude that the error component method is useful in combining SP and RP data and more efficient than the existing methods.

• Archives of Pharmacal Research
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• v.28 no.4
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• pp.438-442
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• 2005

A series of 3-[1-(4-(2-methylpropyl) phenyl) ethyl]-1,2,4-triazole-5-thione (I) and its bicyclic condensed derivatives 6-benzylidenethiazolo[3,2-b]-1, 2,4-triazole-5(6H)-ones (IIa-IIf) were investigated for the prevention of ethanol-induced oxidative stress in liver and brain of mice. Administration of ethanol (0.1 mL/mice, p.o.) resulted in a drop of total thiol groups (T-SH) and non-protein thiol groups (NP-SH), and an increase in thiobarbituric acid reactive substances (TBARS) in both liver and brain tissue of mice (p<0.001). Among the compounds investigated (at a dose of 200 mg/kg, p.o.), I and IId ameliorated the peroxidative injury in these tissues effectively. Compounds IIa, IIc and IIe improved the peroxidative tissue injury only in brain. These findings suggest that certain condensed thiazolo-triazole compounds may contribute to the control of ethanol-induced oxidative stress in an organ selective manner.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.2
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• pp.415-421
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• 2009

TOA(time-of-arrival) and TDOA(time-difference-of-arrival) positioning techniques are commonly used in many radio-navigation systems. From the literature, it is known that the position estimate and error covariance matrix of TDOA obtained by GN(Gauss-Newton) method is exactly the same as that of TOA when the error source of the range measurement is only an IID white Gaussian noise. In case of geo-location and indoor positioning, however, multi-path or NLOS(non-line-of-sight) error is frequently appeared in range measurements. Though its occurrence is random, the multipath acts like a bias for a stationary user if it occurs. This paper presents the comparisons of error characteristics between TOA and TDOA positioning in presence of multi-path or NLOS error. It is analytically shown that the position estimate of TDOA is exactly the same as that of TOA even when bias errors are included in range measurements with different magnitudes. By computer simulation, position estimation error and error distribution are analyzed in presence of range bias errors.

• Korean Journal of Veterinary Research
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• v.42 no.2
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• pp.209-217
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• 2002

This study was performed to produce monoclonal antibodies (mAb) specifically reacting with chicken leukocyte surface antigens. Popliteal lymph node cells of BALB/c mice previously immunized through foot-pad with peripheral blood mononuclear cells (PBMC) of chickens separated by Ficoll-Histopaque method. They were fused with P3X63Ag14 mouse myeloma cells. A total of 34 hybridomas secreted antibodies specifically binding to the PBMC. According to the reactivity patterns with PBMC, the mAbs were divided into 4 groups. Group 1 mAbs (IIB3, IIB10, IIE10) specifically reacted with non-adherent lymphocytes but not with adherent cells which were mainly composed of thrombocytes and monocytes in PBMC culture. These mAbs were reactive with 25-59% of thymus cells and 42-64% of spleen cells of chickens. They did not show any significant reactivity with cells in the bursa of Fabricius, T-cell (MDCC-MSB1) and B-cell (LSCC-1104B1) lines. These results indicate that Group I mAbs specifically reacted with T-lymphocyte subpopulation. Monoclonal antibodies in Group II (IC6, IG2-2 and IID9) showed specific reactivity with monocytes but not with thrombocytes or non-adherent cells in PBMC culture. These mAbs, though not reacted with the chicken macrophage cell line, HD11, also bound to macrophages of the spleen and lung in immunohistochemical staining. Five mAbs in Group III showed characteristics of binding to lymphocytes and monocytes, but not to thrombocytes. Twenty-three mAbs in Group IV showed specific reactivity to lymphocytes, monocytes, and thrombocytes. Two mAbs (IC3 and IE9) in Group IV reacted with most of PBMC.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.846-860
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• 2011

The binaural auditory system of human has ability to differentiate the direction and the distance of the sound sources by using the information which are inter-aural intensity difference(IID), inter-aural time difference(ITD) and/or the spectral shape difference(SSD). These information is generated from the acoustical transfer of a sound source to pinna, the outer ears. We can create a virtual sound system using the information which is called Head related transfer function(HRTF). However the performance of 3D sound is not always satisfactory because of non-individual characteristics of the HRTF. In this paper, we propose the algorithm that uses human's auditory characteristics for accurate perception. To achieve this, excitation energy of HRTF, global masking threshold and loudness are applied to the proposed algorithm. Informal listening test shows that the proposed method improves the sound localization characteristics much better than conventional methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Parasites, Hosts and Diseases
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• v.53 no.4
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• pp.395-402
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• 2015

Non-human primates (NHPs) are confirmed as reservoirs of Cryptosporidium spp., Giardia intestinalis, and Enterocytozoon bieneusi. In this study, 197 fresh fecal samples from 8 NHP species in Qinling Mountains, northwestern China, were collected and examined using multilocus sequence typing (MLST) method. The results showed that 35 (17.8%) samples were positive for tested parasites, including Cryptosporidium spp. (3.0%), G. intestinalis (2.0%), and E. bieneusi (12.7%). Cryptosporidium spp. were detected in 6 fecal samples of Macaca mulatta, and were identified as C. parvum (n=1) and C. andersoni (n=5). Subtyping analysis showed Cryptosporidium spp. belonged to the C. andersoni MLST subtype (A4, A4, A4, and A1) and C. parvum 60 kDa glycoprotein (gp60) subtype IId A15G2R1. G. intestinalis assemblage E was detected in 3 M. mulatta and 1 Saimiri sciureus. Intra-variations were observed at the triose phosphate isomerase (tpi), beta giardin (bg), and glutamate dehydrogenase (gdh) loci, with 3, 1, and 2 new subtypes found in respective locus. E. bieneusi was found in Cercopithecus neglectus (25.0%), Papio hamadrayas (16.7%), M. mulatta (16.3%), S. sciureus (10%), and Rhinopithecus roxellana (9.5%), with 5 ribosomal internal transcribed spacer (ITS) genotypes: 2 known genotypes (D and BEB6) and 3 novel genotypes (MH, XH, and BSH). These findings indicated the presence of zoonotic potential of Cryptosporidium spp. and E. bieneusi in NHPs in Qinling Mountains. This is the first report of C. andersoni in NHPs. The present study provided basic information for control of cryptosporidiosis, giardiasis, and microsporidiosis in human and animals in this area.