• Journal of Pharmaceutical Investigation
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• v.30 no.3
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• pp.191-199
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• 2000

Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.2
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• pp.86-100
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• 2015

Cloud computing is a computing term that evolved in the late 2000s, based on utility and consumption of computer resources. Google say that "Cloud computing involves deploying groups of remote servers and software networks that allow different kinds of data sources be uploaded for real time processing to generate computing results without the need to store processed data on the cloud. Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a utility (like the electricity grid) over a network. At the foundation of cloud computing is the broader concept of converged infrastructure and shared services. Cloud computing, or in simpler shorthand just "the cloud", also focuses on maximizing the effectiveness of the shared resources." The cloud service is a smart and/or intelligent service to save private files in any device, anytime, anywhere. Dropbox, OAuth, PAClous are required that the accumulated user's data are archives with cloud service. Currently we suggest an implementation technique to process many tasks to the cloud server with a thread pooling. Thread pooling is one of efficient implementating technique for client and service environment. In this paper, to present the implementation technique we suggest three diagrams in the consideration of software engineering.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.475-486
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• 2015

Mining the microarray data accumulated in the public data repositories can save experimental cost and time and provide valuable biomedical information. Big data analysis pooling multiple data sets increases statistical power, improves the reliability of the results, and reduces the specific bias of the individual study. However, integrating several data sets from different studies is needed to deal with many problems. In this study, I limited the focus to the cross platform classification that the platform of a testing sample is different from the platform of a training set, and suggested a simple classification method based on rank. This method is compared with the diagonal linear discriminant analysis, k nearest neighbor method and support vector machine using the cross platform real example data sets of two cancers.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.245-254
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• 2016

Many surveys provide categorical data and there may be one or more missing categories. We describe a nonignorable nonresponse model for the analysis of two-way contingency tables from small areas. There are both item and unit nonresponse. One approach to analyze these data is to construct several tables corresponding to missing categories. We describe a hierarchical Bayesian model to analyze two-way categorical data from different areas. This allows a "borrowing of strength" of the data from larger areas to improve the reliability in the estimates of the model parameters corresponding to the small areas. Also we use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data on thirteen states to obtain the finite population proportions.

• Journal of Technology Innovation
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• v.9 no.2
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• pp.56-76
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• 2001

The main purpose of this study is to analyse the digital divide and th determinants of ICT diffusion rate in Korean industries. We estimate the ICT diffusion function using the pooling data for this analysis. The results are as follows. First, the ICT capital accumulated in machinery & equipment, electrical machinery and construction industry is estimated to be 83% of total In capital stock in the 90s. Second, using the panel analysis, we find positive correlation among ICT diffusion, network effect and accumulation of human capital, which is more prominent in the service sector. Third, the estimation results show that the additional 1% increase of human capital accumulation will allow to increase the 0.69% of ICT capital intensity in Korean industries.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.97-116
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• 1999

The growing demand for the real time traffic information is bringing about the category and number of traffic collection mechanism in the era of ITS. There are, however, two problems in making data into information using various traffic data. First, the information making process of making data into the representative information, for each traffic collection mechanism, for the specified analysis periods is required. Second, the integration process of fusing each representative information into "the information" for each link out of each source is also required. That is, both data reduction and/or data to information process and information fusion are required. This article is focusing on the development of information fusing algorithm based on voting technique, fuzzy regression, and, Bayesian pooling technique for estimating the dynamic link travel time of networks. The proposed algorithm has been validated using the field experiment data out of GPS probes and detectors over the roadways and the estimated link travel time from the algorithm is proved to be more useful than the mere arithmetic mean from each traffic source.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.89-112
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• 2015

Recently, the business environment of healthcare has changed rapidly due to the entering the mobile era, the intensifying global competition, and the explosion of healthcare needs. Despite of necessity in expanding new IT-based medical services and investing IT resources to respond environmental changes, the small and medium sized hospitals could not realize these requirements due to the limited management resources. CHISSMH is designed and presented in this research to provide high valued clouding medical services with reasonable price. CHISMH is designed and presented in this research to provide high valued medical services with reasonable price through cloud computing. CHISME is designed to maximize resource pooling and sharing through the visualization. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, provide high level services with reasonable pay-per-use price. By doing so, Cloud Service provider could minimize maintenance cost of cloud data center, and could provide high level services with reasonable pay-per-use price. CHISME is expected to be base framework of cloud HIS services and be diffusion factor of cloud HIS services Operational experience in CHISSMH with 15 hospitals is analyzed and presented as well.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2407-2412
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• 2013

Background and Objectives: Data on associations between soy food intake after cancer diagnosis with breast cancer survival are conflicting, so we conducted this meta-analysis for more accurate evaluation. Methods: Comprehensive searches were conducted to find cohort studies of the relationship between soy food intake after cancer diagnosis and breast cancer survival. Data were analyzed with comprehensive meta-analysis software. Results: Five cohort studies (11,206 patients) were included. Pooling all comparisons, soy food intake after diagnosis was associated with reduced mortality (HR 0.85, 95%CI 0.77 0.93) and recurrence (HR 0.79, 95%CI 0.72 0.87). Pooling the comparisons of highest vs. lowest dose, soy food intake after diagnosis was again associated with reduced mortality (HR 0.84, 95%CI 0.71 0.99) and recurrence (HR 0.74, 95%CI 0.64 0.85). Subgroup analysis of ER status showed that soy food intake was associated with reduced mortality in both ER negative (highest vs. lowest: HR 0.75, 95%CI 0.64 0.88) and ER positive patients (highest vs. lowest: HR 0.72, 95%CI 0.61 0.84), and both premenopausal (highest vs. lowest: HR 0.78, 95%CI 0.69 0.88) and postmenopausal patients (highest vs. lowest: HR 0.81, 95%CI 0.73 0.91). In additioin, soy food intake was associated with reduced recurrence in ER negative (highest vs. lowest: HR 0.64, 95%CI 0.44 0.94) and ER+/PR+ (highest vs. lowest: HR 0.65, 95%CI 0.49 0.86), and postmenopausal patients (highest vs. lowest: HR 0.67, 95%CI 0.56 0.80). Conclusion: Our meta-analysis showed that soy food intake might be associated with better survival, especially for ER negative, ER+/PR+, and postmenopausal patients.

• Management & Information Systems Review
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• v.33 no.4
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• pp.63-75
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• 2014

The paper investigates empirically the determinants of standardization activity at the industry level, focusing on market structure. The enactments or amendments of collective standards is used as the proxy variable for standardization activity. The independent variables, in addition to market structure, are technological opportunity, factor intensity, export ratio, and industry characteristics(assembly). We estimated the logistic regression model(so-called Logit), using the pooling data for 9 Korean industries, including foods, textiles, chemicals, nonmetallic minerals, metals, electronics and electrics, machinery, automobiles, and shipbuilding, over 2006-2009. The empirical finding shows that market structure has no any effects on the enactments or amendments of collective standards in Korea. This might infer that oligopolistic firms devote themselves to de facto standards determined by market rather than de jure standards such as collective standards and Korean Standards(KS). Besides market structure variable, whereas technological opportunity and assembly characteristics are likely to relate positively with the enactments or amendments of collective standards, capital intensity and export ratio have no any relationship with industrial standardization, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.