A Study on Classifications and Trends with Convergence Form Characteristics of Architecture in Tall Buildings (초고층빌딩의 융합적 건축형태 분류와 경향에 관한 연구)
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- Korea Science and Art Forum
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- v.37 no.5
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- pp.119-133
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- 2019
This study is as skyscrapers are becoming increasingly taller, more constructors have decided the height alone cannot be a sufficient differentiator. As a result, atypical architecture is emerging as a new competitive factor. Also, it can be used for symbolizing the economic competitiveness of a country, city, or business through its form. Before the introduction of digital media, there was a discrepancy between the structure and form of a building and correcting this discrepancy required a separate structural medium. Since the late 1980s, however, digitally-based atypical form development began to be used experimentally, and, until the 2000s, it was used mostly for super-tall skyscrapers for offices or for industrial chimneys and communication towers. Since the 2000s, many global brand hotels and commercial and residential buildings have been built as super-tall skyscrapers, which shows the recent trend in architecture that is moving beyond the traditional limits. Complex atypical structure is formed and the formative characteristics of diagonal lines and curved surfaces, which are characteristics of atypical architecture, are created digitally. Therefore, it's goal is necessary to identify a new relationship between the structure and forms. According to the data of Council on Tall Buildings and Urban Habitat (CTBUH), 100-story and taller buildings were classified into typical, diagonal, curved, and segment types in order to define formative shapes of super-tall skyscrapers and provide a ground of the design process related to the initial formation of the concept. The purpose of this study was to identify the correlation between different forms for building atypical architectural shapes that are complex and diverse. The study results are presented as follows: Firstly, complex function follows convergence form characteristics. Secondly, fold has inside of architecture with repeat. Thirdly, as curve style which has pure twist, helix twist, and spiral twist. The findings in this study can be used as basic data for classifying and predicting trends of the future super-tall skyscrapers.
The purpose of this study was to investigate the effects of long-term aerobic dancing exercise on body composition, physical fitness and mental function in older women over 70 years old. All subjects were limited to older women aged 70 to under 85. The experimental group performed aerobic exercise of 2-3 times a week for 9.2 ± 4.6 yrs, and the control group did not perform any regular exercise and spent 3-4 times a week mainly in the relaxing facility for older. As a results in this study, the weight, muscle mass and body fat percentage of the aerobic group were not significantly different from those of the control group, but there were significantly positive effects of aerobic group in visceral fat mass, abdominal obesity rate(%), body water content and systolic blood pressure(p < .05). In terms of physical fitness, Sit & reach, one-legged stand (right) and TUG of the aerobic group were significantly higher than those of the control group(p < .05), but there were no significant differences between two groups in the shoulder flexibilities and grip strength. MMSE as a cognitive function was not significantly different between the two groups, but GDS was significantly lower in the aerobic group than in the control group(p < .05). According to the correlation analysis between all variables and MMSE and GDS, MMSE was significantly inversely correlated with height (r = -0.425)(p < .05), and no correlation was detected with other variables. However, GDS have signitively negative correlations with resting heart rate(r = -0.464), sit & reach(r = -0.525) left(r = -0.491) and right grip strengths(r = -0.635) as well as positive correlation systolic blood pressure(r = 0.482) and TUG (r = 0.479), respectively(p < .05). In conclusion, long-term aerobic exercise of elderly women over 70 older had positive effects on variables related to metabolic disease (visceral fat and resting heart rate), silver fitness variables related to falls, and depression level in the elderly.
From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.
Background : Phospholipase C(PLC) plays an important role in cellular signal transduction and is thought to be critical in cellular growth, differentiation and transformation of certain malignancies. Two second messengers produced from the enzymatic action of PLC are diacylglycerol (DAG) and inositol 1, 4, 5-trisphosphate (IP3). These two second messengers are important in down stream signal activation of protein kinase C and intracellular calcium elevation. In addition, functional domains of the PLC isozymes, such as Src homology 2 (SH2) domain, Src homology 3 (SH3) domain, and pleckstrin homology (PH) domain play crucial roles in protein translocation, lipid membrane modificailon and intracellular memrane trafficking which occur during various mitogenic processes. We have previously reported the presence of PLC-
1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in
The immunosuppressive activity of newcastle disease virus(NDV) and some possible role of interferon(C-IF) in viral suppression of immune response were evaluated by SRBC-induced delayed-type hypersensitivity(DTH), rosette formation in spleen cells, number of lymphocytes in peripheral blood, hemagglutinin and hemolysin response to SRBC in ICR mice sensitized with SRBC. When NDV was inoculated before or after sensitization of mouse with SRBC, virus caused a marked inhibition of DTH, and its depressive effect was dependent on the time of virus inoculation in relation to SRBC sensitization or challenge. Rosette formation of spleen cells was significantly reduced by NDV infection. The degree of the depression of rosette formation was more prominent in mice inoculated before sensitization than after sensitization and could be related to the amount of serum interferon induced by the virus. Humoral response to SRBC of virus infected mouse was significantly depressed when NDV was inoculated 24 or 48 hours before sensitization. However, there was no difference in the response when the virus was inoculated 9 hour before and at the same time of sensitization or even after that. Lymphocytes in peripheral blood of mice were markedly diminished in numbers when NDV was inoculated 48 and 24 hour before sensitization with SRBC, but they were slightly augmented when the virus was inoculated 9 hour before and at the same time of sensitization. When UV-inactivated or heat-inactivated NDV was injected to the mouse at the same time of sensitization with SRBC, DTH and rosette formation of spleen cells were slightly depressed. DTH and rosette formation in mice treated with crude-IF were generally depressed as com pared with those of control mice. These studies suggest that the NDV causes a significant depression of cell-mediated immunity, whereas the humoral immune response is not inhibited markedly, and that the depression of immune response by NDV infection may be caused by interferon produced by NDV and direct viral activity.
The study was carried out to elucidate the effects of ovarian function on the thyroid gland, adrenal gland and uterus in female rats. One hundred and forty-four mature female rats were allotted into the three groups ; ovariectomized group, estradiol treated group and intact control group. The ovaries of 48 heads of rats were completely removed. Forty eight heads of rats were administered with
The present study prepared 72 test samples - 24 made of amalgam alloy, 24 of Verabond (Ni-Cr alloy) for crown and 24 of Talladium
The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.
indicates that our experimental manipulation of the moderate effect of the product type was successful. 3.3. Results As
indicates, there was a significant main effect on the only one dependent variable(attitude toward the shopping mall) by the information types. As predicted, VR has highest mean value compared to other information types. Thus, H1 was partially supported. However, main effect by the product types was not found. To evaluate H2 and H3, a two-way ANOVA was conducted. As
indicates, there exist the interaction effects on the three dependent variables(information usefulness, overall product quality and purchase intention) by the information types and the product types. As predicted, picture of the product with the real-person model has highest mean among the information types in the case of portable product. On the other hand, VR has highest mean among the information types in the case of installed product. Thus, H2 and H3 was supported. 4. Implications: The present study found the moderate effect by the product type of usage situation. Based on the findings the following managerial implications are asserted. First, it was found that information types are affect only the attitude toward the shopping mall. The meaning of this finding is that VR effects are not enough to understand the product itself. Therefore, we must consider when and how to use this VR tools. Second, it was found that there exist the interaction effects on the information usefulness, overall product quality and purchase intention. This finding suggests that consideration of usage situation helps consumer's understanding of product and promotes their purchase intention. In conclusion, not only product attributes but also product usage situations must be fully considered by the online retailers when they want to meet the needs of consumers.
Depression of Immune Response by Newcastle Disease Virus Infection
(Newcastle병(病) 바이러스감염(感染)에 의(依)한 면역반응억제(免疫反應抑制))
Effects of Ovarian Function on the Thyroid Gland, Adrenal Gland and Uterus in Female Rats
(흰쥐의 난소기능(卵巢機能)이 갑상선(甲狀腺), 부현(副賢) 및 자궁(子宮)에 미치는 영향(影響))
A Study on Corrosion according to Distance between Amalgam and Dissimilar Metals
(아말감과 이종(異種)금속의 거리에 따른 부식에 대한 고찰)
A Study on the Establishment of Comparison System between the Statement of Military Reports and Related Laws
(군(軍) 보고서 등장 문장과 관련 법령 간 비교 시스템 구축 방안 연구)
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