• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of fish pathology
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• v.6 no.2
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• pp.111-122
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• 1993

The mechanism by which $V_H$ region gene segments is selected in B lymphocyte is not known. Moreover, evidence for both random and nonrandom expression of $V_H$ genes in matured B cells has been presented previously. In this report, the technique of in situ hybridization allowed us to analyze expressed $V_H$ gene families in normal B lymphocyte at the single cell level. The analysis of normal B cells in this study eliminated any posssible bias resulting from transformation protocols used previously and minimized limitation associated with sampling size. Therefore, an accurate measure of the functional and expressed $V_H$ gene repertoire in B lymphocyte could be made. One of the most important controls for the optimization of in situ hybridization is to establish probe concentration and washing stringency due to the degree of nucleotide sequence similarlity between different families which in some cases can be as high as 70%. When the radioactive $C{\mu}$ and $V_{H}J558$ RNA probes are tested on LPS-stimulated adult spleen cells, $2{\sim}4{\times}106cpm$/slide shows low background and reasonable frequency of specific positive cells. For the washing condition. 40~50% formamide at $54^{\circ}C$ is found to be optimum for the $C{\mu}$. $V_{H}S107$ and $V_{H}J558$ probes. The analyzed results clearly demonstrate that the level of each different $V_H$ gene family expression is dependent upon the complexity or size of that family. These findings are also extended to the level of $V_H$ gene family expression in separated bone marrow B cells depend upon the various stage of differentiation and conclude no preferential utilization of specific $V_H$ gene family. Thus, the utilization of VH gene segments in B lymphocyte of adult BALB/c mice is random and is not regulated or changed during the differentiation of B cells.

• Journal of Korean Public Health Nursing
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• v.12 no.1
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• pp.132-146
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• 1998

This Study was attempted to provide the basic data necessary in the development and introduction of Home Health Nursing System by investigating the recognition and attitude level of Home Health Nursing System. The data were collected by means of questionaires presented to 74 patients who had been admitted in C general hospital in Chon Ju, from June 30, 1997. As the tool for this study, the questionares developed by Kim Yong. Soon, et al (1990) and Han Bok Hee(1993) were modified and supplemented for the aim of this study. The computer was used for data analysis. The items about the charateristics of the subjects and the attitude to the management plan of Home Health Nursing System were represented as the frequency and percentage. The standard deviation and calculation average were produced on the items related to definition, recognition, necessity, expected effect of the attitude of Home Health Nursing System and the items related to admission. The ANOVA test was .used according to the characteristics of variables to analyze the necessity and difference of Home Health Nursing System. The results of this study were as follows 1) The general characteristics of the subjects were as follows ; for sex, man, $58.1\%$ ; for age, 50-59 years, $29.7\%$ ; for the level of education, high school, $51.4\%$ ; $79.7\%$ of them were married; for the family forms, small family, $73.0\%$ ; and $68.9\%$ of them take the monthly income over 100 million won. 2) The characteristics related to admissions of the subjects were as follows ; for clinic, surgical department, $78.4\%$ ; addmission not more then 7days, $47.3\%$ ; for the operation-performance $71.6\%$ of them were experienced; for the admission route, via outpatients clinic, $54.1\%$ ; for waiting period to the admission day, 1-2 days, $71.6\%$. 3) The difficulties comming from the hospitalization were related mostly to the factor that they felt hospital life more inconvenient than home.(3.66) The reasons for the difficulties in the admission which was due to insufficient beds in the hospital was related to the concentration to the general hospital because of 'The Whole National Medical Insurance System'(4.05). 4) On the previous informations about the Home Health Nursing System, those who have heard of only the name were 42 $(56.8\%)$, and on the recognition of it, they thought that it is periodic treatment by the licenced nurses for the recovering pateints after early discharge(3.73). On the attitude about the necessity of Home Health Nursing System, they thought that it is necessary because of the increasing trend of a psychological disease by the change of environment and complexity of the social structure(4.24). On the expected effect of Home Health Nursing System, they answered that it is convinient for the family of the patient to take care of them(4.l8). 5) On the attitude to the management plan of the Home Health Nursing System, those who had intention to participate in the system in the case of systemic support were 42(56.8). In the visiting time, 'visit periodically' and 'visit when the patient needs' were $28(37.8\%)$ respectively. For the application of medical insurance, if possoble, they will use $(91.9\%)$; for the method of payment for the treatment, 'pay by the time required' was $23(31.1\%)$, for the subject of management, 'National public institute must operate' was $33(44.6\%)$. 6) The relationship between the general characteristics of the subjects and the necessity of Home Health Nursing System showed the notable difference in the age (F=3.508, P<0.05) and marrage state (F=5.402, P<.023).

• Korean Journal of Psychosomatic Medicine
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• v.26 no.1
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• pp.35-43
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• 2018

Objectives : Effects of multiple trauma are complex and extend beyond core PTSD symptoms. However, few psychological instruments for trauma assessment address this issue of symptom complexity. The Trauma Symptom Checklist-40 (TSC-40) is a self-report scale that assesses wide range of symptoms associated with childhood or adult traumatic experience. The purpose of the present study was to evaluate the validity of the Korean Version of the TSC-40 in a sample of psychiatric outpatients. Methods : Data of 367 treatment-seeking patients with DSM-IV diagnoses were obtained from an outpatient department of psychiatric unit at a university hospital. The diagnoses were anxiety disorder, posttraumatic stress disorder, depressive disorder, adjustment disorder and others. Included in the psychometric data were the TSC-40, the Life events checklist, the Impact of Event Scale-Revised, the Zung's Self-report Depression Scale, and the Zung's Self-report Anxiety Scale. Cronbach's ${\alpha}$ for internal consistency were calculated. Convergent and concurrent validity was approached with correlation between the TSC-40 and other scales (PTSD, anxiety and depression). Results : Exploratory factor analysis of the Korean Version of TSC-40 extracted seven-factor structure accounted for 59.55% of total variance that was contextually similar to a six-factor structure and five-factor structure of the original English version. The Korean Version of TSC-40 demonstrated a high level of internal consistency. (Cronbach's ${\alpha}=0.94$) and good concurrent and convergent validity with another PTSD scale and anxiety and depression scales. Conclusions : Excellent construct validity of The Korean Version of TSC-40 was proved in this study. And subtle difference in the factor structure may reflect the cultural issues and the sample characteristics such as heterogeneous clinical population (including non-trauma related disorders) and outpatient status. Overall, this study demonstrated that the Korean version of TSC-40 is psychometrically sound and can be used for Korean clinical population.

• Korean Journal of Ichthyology
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• v.17 no.3
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• pp.173-186
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• 2005

Genomic DNA was isolated from two geographic populations of largehead hairtail (Trichiurus lepturus) in Korea and the Atlantic Ocean. The eight arbitrarily selected primers were found to generate common, polymorphic, and specific fragments. The complexity of the banding patterns varied dramatically between primers from the two locations. The size of the DNA fragments also varied widely, from 150 bp (base pairs) to 3,000 bp. Here, 947 fragments were identified in the largehead hairtail population from Korea, and 642 in the largehead hairtail population from the Atlantic Ocean: 148 specific fragments (15.6%) in the Korean population, and 61 (9.5%) in the Atlantic population. In the Korean population, 638 common fragments with an average of 79.8 per primer were observed.; 429 common fragments, with an average of 53.6 per primer, were identified in the Atlantic population. The number of polymorphic fragments in the largehead hairtail population from Korea and the Atlantic Ocean was 76 and 27, respectively. Based on the average bandsharing values of all samples, the similarity matrix ranged from 0.784 to 0.922 in the Korean population, and from 0.833 to 0.990 in the Atlantic population. The bandsharing value of individuals within the Atlantic population was much higher than in the Korean population. The dendrogram obtained by the eight primers indicated two genetic clusters: cluster 1 (KOREAN 01~KOREAN 11), and cluster 2 (ATLANTIC 12~ATLANTIC 22). Individual KOREAN no. 10 from Korea was genetically most closely related to KOREAN no. 11 in the Korean population (genetic distance = 0.038). Ultimately, individual KOREAN no. 01 of the Korean population was most distantly related to ATLANTIC no. 16 of the Atlantic population (genetic distance = 0.708).

• Journal of The Korean Association For Science Education
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• v.31 no.2
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• pp.181-197
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• 2011

The purpose of this study was to look into students' understandings of environmental issues, especially issues on global warming in South Korea and Singapore. We surveyed students (n=2,389, from 6 to 10 years) from 12 schools in South Korea and 5 schools in Singapore on how useful students believe various actions might be in reducing global warming, and their willingness to undertake such actions. We employed questionnaires developed by Boyes, Skamp, & Stanisstreet (2009), which consists of 44 questions on 16 pro-environmental actions. We analyzed the degree of students' beliefs, willingness to act, and the relationship between the believed usefulness of action and willingness to act. Differences between the two countries were determined by Analysis of Covariance (ANCOVA) using the ordinal data and the potential effectiveness of education was explored by plotting the measures of the degree of willingness to act for a particular action against the value of the believed usefulness of action and fitting the regression line. The degree of willingness to act and their beliefs in the usefulness of action was different from question to question between the two countries, however, the overall relationship between willingness to take action and beliefs in the action has shown to be stronger among Singaporean students than those of South Korean students. Based on the findings, we attempted to discuss about how environmental education needs to take into account the complexity of beliefs, willingness to act, and action taking.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.100-106
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• 2008

The purpose of this study was to confirm the exactitude of in vitro nuclear magnetic resonance spectroscopy(NMRS) and to complement the defect of in vivo NMRS. It has been difficult to understand the metabolism of a cerebellum using in vivo NMRS owing to the generated inhomogeneity of magnetic fields (B0 and B1 field) by the complexity of the cerebellum structure. Thus, this study tried to more exactly analyze the metabolism of a canine cerebellum using the cell extraction and high resolution NMRS. In order to conduct the absolute metabolic quantification in a canine cerebellum, the spectrum of our phantom included in various brain metabolites (i.e., NAA, Cr, Cho, Ins, Lac, GABA, Glu, Gln, Tau and Ala) was obtained. The canine cerebellum tissue was extracted using the methanol-chloroform water extraction (M/C extraction) and one group was filtered and the other group was not under extract processing. Finally, NMRS of a phantom solution and two extract solution (90% D2O) was progressed using a 500MHz (11.4 T) NMR machine. Filtering a solution of the tissue extract increased the signal to noise ratio (SNR). The metabolic concentrations of a canine cerebellum were more close to rat’s metabolic concentration than human’s metabolic concentration. The present study demonstrates the absolute quantification technique in vitro high resolution NMRS with tissue extraction as the method to accurately measure metabolite concentration.

• Journal of Animal Science and Technology
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• v.48 no.5
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• pp.637-650
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• 2006

Genomic DNA isolated from two crucian carp species obtained from Yesan (Carassius auratus) and Dangjin (Carassius cuvieri) in Korea were amplified at several times by polymerase chain reaction (PCR). The amplified products were separated by agarose gel electrophoresis (AGE) with oligonucleotides decamer primer and stained with ethidium bromide. The seven arbitrarily selected primers OPC-11, OPC-14, OPC-18, OPD- 02, OPD-11, OPD-15 and OPD-20 generated the shared loci by each species, the polymorphic and specific loci. The seven primers generated the total 458 loci that can be scored from the crucian carp obtained in C. auratus species. 358 fragments were generated from the species obtained in C. cuvieri species. The size of DNA fragments varies from 150 to 1,600bp. The complexity of the banding patterns varies dramatically between the primers and two locations. In this study, 458 loci were identified in the crucian carp species from Yesan and 358 in the crucian carp species from Dangjin: 84 polymorphic loci (18.3%) in the C. auratus species and 48 (13.4%) in the C. cuvieri species. 154 shared loci by each species, the average 22 per primer, were observed in the C. auratus species and 187 loci, the average 26.7 per primer, in the Dangjin species. Based on the average bandsharing (BS) values of all samples, the similarity matrix ranged from 0.434 to 0.868 in the C. auratus species and from 0.449 to 0.924 in the C. cuvieri species. The average BS value was 0.641±0.013 within the C. auratus species and 0.684±0.013 within the C. cuvieri species. The average BS value between two crucian carp species 0.484 ± 0.007, ranged from 0.307 to 0.682. The BS value between the individual No. 09 and No. 16 was 0.682, which was the highest between two crucian carp species. Compared separately, the BS value of individuals within the C. cuvieri species was higher than the C. auratus species. The dendrogram obtained by the seven primers, indicates three genetic clusters: cluster 1 (AURATUS No. 01, 02, 03, 04, 05, 06, 07, 08, 09, 10 and 11), cluster 2 (CUVIERI No. 12, 13, 14, 15, 16, 17, 18, 19, 20 and 21) and cluster 3 (CUVIERI no. 22). The shortest genetic distance displaying significant molecular difference was between the individual AURATUS No. 09 and AURATUS No. 08 from Yesan (genetic distance=0.064). The longest genetic distance displaying significant molecular differences was between the individual CUVIERI No. 17 and AURATUS No. 11 between two crucian carp species (0.477). RAPD-PCR analysis has revealed the significant genetic distance between two crucian carp species pairs.(Key words: Carassius auratus, Carassius cuvieri, Crucian Carp, DNA Polymorphism, Genetic Distance)

• Tuberculosis and Respiratory Diseases
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• v.56 no.4
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• pp.393-404
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• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.