This study investigated the corporate growth with more emphasis on longitudinal characteristics, not the results of companies with relatively more emphasis on cross-sectional, in the 21st-century entrepreneurial context. As of the end of 2019, sampled 479 global unicorn companies, and 333 high-growth companies with revenue of more than $100 million among 5,000 private companies in the U.S. with a compound annual growth rate (CAGR) exceeding 15% for the past three years. They were examined with 3 perspectives in terms of corporate growth that 1) the growth of enterprise value, 2) the pace of growth, and 3) the effectiveness of growth. As a result of our study, the corporate growth of the perspective of creating enterprise value had a relatively higher relationship with the characteristics of industries and markets. The pace of growth was more fully explained by the characteristics of the industry and the market environment and the choice of strategies that make up a valid combination. In addition, growth in terms of the effectiveness of corporate performance was influenced by the choice of strategy, the characteristics of the industry and market environment, and its business age, the proxy variable of resource accumulation, comprehensively. This study through a sample based on companies with an enterprise value of more than $1 billion and annual revenue of more than $100 million can be a valid reference in terms of creating milestones and roadmaps for scale-up of early-stage startups, particularly in terms of practitioners' point of view. It also provides a critical reference for overcoming the limitations of mainstream theories of the 20th century and developing the theory of corporate growth that fits the 21st-century entrepreneurial context.
"Sangok", is a new japonica rice variety (Oryza sativa L.), which is a midium maturing ecotype developed by the rice breeding team of National Yeongnam Agricultural Experiment Station (NYAES) in 2003. This variety was derived from the cross of Milyang 101/YR8697Acp97 (in 1988/1989 winter) and selected by combination of the bulk and pedigree breeding. The pedigree of Sangokbyeo, designated as Milyang 182 in 2000, was YR12950-B-B-B-19-2-4-2-2. It has about 79cm stature in culm length and is medium maturing. This variety is resistant to bacterial blight (
A new rice cultivar, 'Joami', was developed by the rice breeding team of Sangju Substation, National Institute of Crop Science (NICS), Rural Development Administration. It was selected by a bulk and pedigree methods from a cross-combination among 'Sambaegbyeo', 'Yukara', and 'Tonggae112'. A promising line of YR20557-1-1-3-B-3 was designated as 'Sangju 36' in 2006. Local adaptability test of 'Sangju 36' was conducted at ten sites throughout the Korean peninsula during three years from 2006 to 2008. 'Sangju 36', thereafter, was registered as 'Joami' in 2008. The cultivar headed on July 30 in the test of local adaptability. Endosperm of 'Joami' is translucent with clear chalkiness and has 5.4% higher head rice ratio than that of 'Odaebyeo'. The yield potential of 'Joami' in milled rice is about 5.40 MT/ha under ordinary fertilizer level of local adaptability test, which was 6% higher than that of 'Odaebyeo'. In an alpine area of Korea, the rice variety needs a cold tolerance and a resistance to blast disease. 'Joami' showed a tolerance reaction at Chuncheon cold tolerance screening nursery and exhibited resistance reaction to blast disease in nation-wide disease screening nursery. Therefore, 'Joami' would be well adaptable to mid-mountainous area at central and southern part of Korean peninsula.
The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.
A series of experiments were conducted at Crop Experiment Station from 1968 to 1971 to obtain basic information on effects of selection on yield of wheat varieties. Heritability estimates, correlation and path coefficients computed for yield and yield related characters from fixed variety groups-Korean, U.S., and Japan; early and late-
The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
Background: The prevalence of tuberculosis in Korea decreased remarkably for the past 30 years, while the incidence of disease caused by mycobacteria other than tuberculosis is unknown. Korean Academy of Tuberculosis and Respiratory Diseases performed national survey to estimate the incidence of mycobacterial diseases other than tuberculosis in Korea. We analyzed the clinical data of confirmed cases for the practice of primary care physicians and pulmonary specialists. Methods: The period of study was from January 1981 to October 1994. We collected the data retrospectively by correspondence with physicians in the hospitals that referred the specimens to Korean Institute of Tuberculosis, The Korean National Tuberculosis Association for the detection of mycobacteria other than tuberculosis. In confirmed cases, we obtained the records for clinical, laboratory and radiological findings in detail using protocols. Results: 1) Mycobacterial diseases other than tuberculosis were confirmed that 1 case was in 1981, 2 cases in 1982, 4 cases in 1983, 2 cases in 1984, 5 cases in 1985, 1 case in 1986, 3 cases in 1987, 1 case in 1988, 6 cases in 1989, 9 cases in 1990, 14 cases in 1990, 10 cases in 1992, 4 cases in 1993, and 96 cases in 1994. Cases since 1990 were 133 cases(84.2%) of a total. 2) Fifty seven percent of patients were in the age group of over 60 years. The ratio of male to female patients was 2.6:1. 3) The distribution of hospitals in Korea showed that 61 cases(38.6%) were referred from Double Cross Clinic, 42 cases(26.6%) from health centers, 21 cases(13.3%) from tertiary referral hospitals, 15 cases(9.5%) from secondary referral hospitals, and 10 cases(6.3%) from primary care hospitals. The area distribution in Korea revealed that 98 cases(62%) were in Seoul, 17 cases(10.8%) in Gyeongsangbuk-do, 12 cases(7.6%) in Kyongki-do, 8 cases(5.1%) in Chungchongnam-do, each 5 cases(3.2%) in Gyeongsangnam-do and Chungchongbuk-do, 6 cases(3.8%) in other areas. 4) In the species of isolated mycobacteria other than tuberculosis, M. avium-intracellulare was found in 104 cases(65.2%), M. fortuitum in 20 cases(12.7%), M. chelonae in 15 cases(9.5%), M. gordonae in 7 cases(4.4%), M. terrae in 5 cases(3.2%), M. scrofulaceum in 3 cases(1.9%), M. kansasii and M. szulgai in each 2 cases(1.3%), and M. avium-intracellulare coexisting with M. terrae in 1 case(0.6%). 5) In pre-existing pulmonary diseases, pulmonary tuberculosis was 113 cases(71.5%), bronchiectasis 6 cases(3.8%), chronic bronchitis 10 cases(6.3%), and pulmonary fibrosis 6 cases(3.8%). The timing of diagnosis as having pulmonary tuberculosis was within 1 year in 7 cases(6.2%), 2~5 years ago in 32 cases(28.3%), 6~10 years ago in 29 cases(25.7%), 11~15 years ago in 16 cases(14.2%), 16~20 years ago in 15 cases (13.3%), and 20 years ago in 14 cases(12.4%). Duration of anti-tuberculous treatment was within 3 months in 6 cases(5.3%), 4~6 months in 17 cases(15%), 7~9 months in 16 cases(14.2%), 10~12 months in 11 cases(9.7%), 1~2 years in 21 cases(18.6%), and over 2 years in 8 cases(7.1%). The results of treatment were cure in 44 cases(27.9%) and failure in 25 cases(15.8%). 6) Associated extra-pulmonary diseases were chronic liver disease coexisting with chronic renal failure in 1 case(0.6%), diabetes mellitus in 9 cases(5.7%), cardiovascular diseases in 2 cases(1.3%), long-term therapy with steroid in 2 cases(1.3%) and chronic liver disease, chronic renal failure, colitis and pneumoconiosis in each 1 case(0.6%). 7) The clinical presentations of mycobacterial diseases other than tuberculosis were 86 cases (54.4%) of chronic pulmonary infections, 1 case(0.6%) of cervical or other site lymphadenitis, 3 cases(1.9%) of endobronchial tuberculosis, and 1 case(0.6%) of intestinal tuberculosis. 8) The symptoms of patients were cough(62%), sputum(61.4%), dyspnea(30.4%), hemoptysis or blood-tinged sputum(20.9%), weight loss(13.3%), fever(6.3%), and others(4.4%). 9) Smear negative with culture negative cases were 24 cases(15.2%) in first examination, 27 cases(17.1%) in second one, 22 cases(13.9%) in third one, and 17 cases(10.8%) in fourth one. Smear negative with culture positive cases were 59 cases(37.3%) in first examination, 36 cases (22.8%) in second one, 24 cases(15.2%) in third one, and 23 cases(14.6%) in fourth one. Smear positive with culture negative cases were 1 case(0.6%) in first examination, 4 cases(2.5%) in second one, 1 case (0.6%) in third one, and 2 cases(1.3%) in fourth one. Smear positive with culture positive cases were 48 cases(30.4%) in first examination, 34 cases(21.5%) in second one, 34 cases(21.5%) in third one, and 22 cases(13.9%) in fourth one. 10) The specimens isolated mycobacteria other than tuberculosis were sputum in 143 cases (90.5%), sputum and bronchial washing in 4 cases(2.5%), bronchial washing in 1 case(0.6%). 11) Drug resistance against all species of mycobacteria other than tuberculosis were that INH was 62%, EMB 55.7%, RMP 52.5%, PZA 34.8%, OFX 29.1%, SM 36.7%, KM 27.2%, TUM 24.1%, CS 23.4%, TH 34.2%, and PAS 44.9%. Drug resistance against M. avium-intracellulare were that INH was 62.5%, EMB 59.6%, RMP 51.9%, PZA 29.8%, OFX 33.7%, SM 30.8%, KM 20.2%, TUM 17.3%, CS 14.4%, TH 31.7%, and PAS 38.5%. Drug resistance against M. chelonae were that INH was 66.7%, EMB 66.7%, RMP 66.7%, PZA 40%, OFX 26.7%, SM 66.7%, KM 53.3%, TUM 53.3%, CS 60%, TH 53.3%, and PAS 66.7%. Drug resistance against M. fortuitum were that INH was 65%, EMB 55%, RMP 65%, PZA 50%, OFX 25%, SM 55%, KM 45%, TUM 55%, CS 65%, TH 45%, and PAS 60%. 12) The activities of disease on chest roentgenogram showed that no active disease was 7 cases(4.4%), mild 20 cases(12.7%), moderate 67 cases(42.4%), and severe 47 cases(29.8%). Cavities were found in 43 cases(27.2%) and pleurisy in 18 cases(11.4%). 13) Treatment of mycobacterial diseases other than tuberculosis was done in 129 cases(81.7%). In cases treated with the first line anti-tuberculous drugs, combination chemotherapy including INH and RMP was done in 86 cases(66.7%), INH or RMP in 30 cases(23.3%), and not including INH and RMP in 9 cases(7%). In 65 cases treated with the second line anti-tuberculous drugs, combination chemotherapy including below 2 drugs were in 2 cases(3.1%), 3 drugs in 15 cases(23.1%), 4 drugs in 20 cases(30.8%), 5 drugs in 9 cases(13.8%), and over 6 drugs in 19 cases (29.2%). The results of treatment were improvement in 36 cases(27.9%), no interval changes in 65 cases(50.4%), aggravation in 4 cases(3.1%), and death in 4 cases(3.1%). In improved 36 cases, 34 cases(94.4%) attained negative conversion of mycobacteria other than tuberculosis on cultures. The timing in attaining negative conversion on cultures was within 1 month in 2 cases(1.3%), within 3 months in 11 cases(7%), within 6 months in 14 eases(8.9%), within 1 year in 2 cases(1.3%) and over 1 year in 1 case(0.6%). Conclusion: Clinical, laboratory and radiological findings of mycobacterial diseases other than tuberculosis were summarized. This collected datas will assist in the more detection of mycobacterial diseases other than tuberculosis in Korea in near future.