• Korean Journal of Clinical Pharmacy
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• v.26 no.2
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• pp.150-162
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• 2016

Objective: First-in-human dose estimation is an essential approach for successful clinical trials for drug development. In this study, we systematically compared first-in-human dose and human pharmacokinetic parameter estimation approaches. Methods: First-in-human dose estimation approaches divided into similar drug comparison approaches, regulatory guidance based approaches, and pharmacokinetic based approaches. Human clearance, volume of distribution and bioavailability were classified for human pharmacokinetic parameter estimation approaches. Results: Similar drug comparison approaches is simple and appropriate me-too drug. Regulatory guidance based approaches is recommended from US Food and Drug Administration (FDA) and European Medicines Agency (EMA) regarding no-observed-adverse-effect level (NOAEL) or minimum anticipated biological effect level (MABEL). Pharmacokinetic based approaches are 8 approaches for human clearance estimation, 5 approaches for human volume of distribution, and 4 approaches for human bioavailability. Conclusion: This study introduced and compared all methods for first-in-human dose estimation. It would be useful practically to estimate first-in-human dose for drug development.

• The Research Journal of the Costume Culture
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• v.6 no.4
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• pp.120-135
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• 1998

The purpose of this study were to develop the taxonomy of apparel buying decision approaches and to identify the relationships between the apparel buying decision approaches and the situational characteristics. Data were collected via a questionnaire developed on the previous studies and the focus interview from 425 female college students living at Pusan, and analyzed by Factor Analysis, Cluster Analysis, Analysis of Variance, and Discriminant Analysis. Results indicated that apparel buying decision approaches consisted of eight dimensions and situational characteristics of affecting a particular apparel buying decision approaches were composed of three or five factors. The four types of apparel buying decision approaches were derived by Cluster Analysis and ANOVA: Recreational Shoppers, Brand Conscious Shoppers, Quality Conscious Shoppers, and Apathetic Shoppers. The findings revealed some patterns that were similar to previous studies and was useful to marketing managers who can view their customer segments in terms of the types in the taxonomy. Further, it provided a tool by which sales representatives can develop adaptive selling approaches based on a small set of buying situation and corresponding apparel buying decision approaches.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.17-46
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• 2010

This paper studies six different AHP (Analytic Hierarchy Process) approaches and suggests that the features of the approaches are classified by application circumstances in order to contribute to the applicability and quality usage of the AHP. Our study investigates the hierarchical principles and characteristics of the AHP, and historical debates on the AHP evaluation in which the six approaches have been involved. One of six approaches is an ANP (Analytic Network Process) application that is directly connected to AHP usage. The application differences among the six approaches are validated with a plain example. Then, the four circumstances of AHP applications are classified by two dimensions: the first dimension is whether or not the importance (weights) of criteria is independent of restrictively setting alternatives, and the second dimension is whether or not preference (priorities) of alternatives is independent of adding alternative(s) to or removing alternative(s) from the considering set of alternatives. Then featuring way of weighting criteria is classified. We suggest the distinguishing manners and describe the implications of the AHP application. Finally, we discuss rank reversal and multiplicative AHP.

• Human Ecology Research
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• v.51 no.6
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• pp.649-663
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• 2013

As cultural diversity has gained a great deal of attention and the social fabric of Korean society is redefined, the number of studies on multi-cultural family homes has been growing in the area of human ecology, but relevant research is rarely found on the subject of housing. While the emphasis of housing research is on multidisciplinary approaches and empirical research is highly valued, a theoretical and methodological platform for discussing the new rising agenda of multi-cultural family homes is lacking. The purpose of this study was to explore approaches to and to discuss the issues in research for multi-cultural family homes in terms of housing theories and multidisciplinary approaches. To understand the housing related needs of multi-cultural families, this study highlights social constructionism, the ecological perspective, and feminist epistemology. These three multidisciplinary approaches were useful for generating an ontological analysis of multi-cultural family homes. Further, this study highlights two housing related theories, the microsociological and housing pathways approaches, for dealing with multi-cultural family homes. In conclusion, the five approaches were useful for exploring issues in housing research on multi-cultural family homes with appropriate research methods like hermeneutics, quantitative, and qualitative methods, and field research. Insights into using perspectives and holistic approaches might be useful for solving the problems of multi-cultural family homes in Korea.

• Korean Journal of Computational Design and Engineering
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• v.21 no.4
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• pp.453-461
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• 2016

The trend of using Grasshopper with Rhino3D actively in architectural design process is recently spreading around the world. Well-known architects and designers such as Zaha Hadid, Patrik Schmacher is famous for using Grasshopper as their main design tool. As a tool for so-called 'Parametric Design', Grasshopper is receiving much attention all over the world. Grasshopper as a visual programming language has an advantage that designers and non-professionals of computer can easily learn it and use it to their works. However, those designers tend to make inefficient approaches with Grasshopper compared to computer programming professionals. Meanwhile, the difference between other programming languages and Grasshopper leads to the need of different approaches from other programming languages. This study aims to propose desired approaches of Grasshopper programming or scripting to be able to break through the inefficient approaches that designer is likely to make, by examining the characteristics of Grasshopper and exploring the appropriate programming approaches for Grasshopper.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• Genomics & Informatics
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• v.19 no.2
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• pp.13.1-13.8
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• 2021

Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.28-37
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• 2006

Recently, transport layer mobility supporting approaches based on SCTP, which is a new standard transport layer protocol, are proposed. In this paper, the handover performance and overheads of these transport layer mobility supporting approaches are compared to those of the traditional network layer mobility supporting approaches. Through the simulation results, it is shown that the handover performance of the transport layer mobility supporting approaches is better or at least similar to that of the plain MIPv6, which is the representative network layer mobility supporting approach. With respect to the amount of control packet, the transport layer approaches impose less overhead than any of the network layer approaches.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.881-888
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• 1997

The existing method s for curvature estimation have a common problem in determining a unique smoothong factor. we previously proposed two approaches to overcome that problem: a constrained regularization approach and a mean field annealing approach. We consistently detected corners from the perprocessed smooth boundary obtained by either the constrained eglarization approach or the mean field annealing approach. Moreover, we defined corner sharpness to increase the robustness of both approaches. We evaluate the performance of those methods proposed in this paper. In addition, we show some matching results using a two-dimensional Hopfield neural network in the presence of occlusion as a demonstration of the power of our proposed methods.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.2
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• pp.228-236
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• 2004

Two varieties of alfalfa (Medicago sativa L cv. Pioneer and Beaver) and timothy (Phleum pratense L cv. Climax and Joliette), grown at different locations in Saskatchewan (Canada), were cut at three stages [1=one week before commercial cut (early bud for alfalfa; joint for timothy); 2=at commercial cut (late bud for alfalfa; pre-bloom head for timothy); 3=one week after commercial cut (early bloom for alfalfa; full head for timothy)]. The energy values of forages were determined using three approaches, including chemical (NRC 2001 formula) and biological approaches (standard in vitro and in situ assay). The objectives of this study were to determine the effects of forage variety and stage of maturity on energy values under the climate conditions of western Canada, and to investigate relationship between chemical (NRC 2001 formula) approach and biological approaches (in vitro and in situ assay) on prediction of energy values. The results showed that, in general, forage species (alfalfa vs. timothy) and cutting stage had profound impacts, but the varieties within each species (Pioneer vs. Beaver in alfalfa; Climax vs. Joliette in timothy) had minimal effects on energy values. As forage maturity increased, the energy contents behaved in a quadratic fashion, increasing at stage 2 and then significantly decreasing at stage 3. However, the prediction methods-chemical approach (NRC 2001 formula) and biological approaches (in vitro and in situ assay) had great influences on energy values. The highest predicted energy values were found by using the in situ approach, the lowest prediction value by using the NRC 2001 formula, and the intermediate values by the in vitro approach. The in situ results may be most accurate because it is closest to simulate animal condition. The energy values measured by biological approaches are not predictable by the chemical approach in this study, indicating that a refinement is needed in accurately predicting energy values.