• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.68-76
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• 2014

The accurate estimation of construction cost is important to a successful development in construction projects. In previous studies, the construction cost are estimated by statistical methods. Among the statistical methods, support vector regression (SVR) has attracted a lot of attentions because of the generalization ability in the field of cost estimation. However, despite the simplicity of the parameter to be adjusted, it is not easy to find optimal parameters. Therefore, to build an effective SVR model, SVR's parameters must be set properly without additional data handling loads. So this study proposes a novel approach, known as genetic algorithm (GA), which searches SVR's optimal parameters, then adopt the parameters to the SVR model for estimating cost in the early stage of apartment housing projects. The aim of this study is to propose a GA-SVR model and examine the feasibility in cost estimation by comparing with multiple regression analysis (MRA). The experimental results demonstrate the estimating performance based on the percentage of estimations within 25% and find it can effectively do the accurate estimation without through the trial and error process.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.133-144
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• 2006

In order to catch out such Bond Strength, the preceding researchers had ever examined the Bond Strength of FRP Plate through their experimentations by setting up of various fluent. However, since the experiment for research on such Bond Strength takes much of expenditure for equipment structure and time-consuming, also difficult to carry out, it is conducting limitedly. This Study purposes to develop the most suitable Artificial Neural Network Model by application of various Neural Network Model and Algorithm to the adhering experiment data of the preceding researchers. Output Layer of Artificial Neural Network Model, and Input Layer of Bond Strength were performed the learning by selection as the variable of the thickness, width, adhered length, the modulus of elasticity, tensile strength, and the compressive strength of concrete, tensile strength, width, respectively. The developed Artificial Neural Network Model has applied Back-Propagation, and its error was learnt to be converged within the range of 0.001. Besides, the process for generalization has dissolved the problem of Over-Fitting in the way of more generalized method by introduction of Bayesian Technique. The verification on the developed Model was executed by comparison with the resulted value of Bond Strength made by the other preceding researchers which was never been utilized to the learning as yet.

• The Journal of Art Theory & Practice
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• no.5
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• pp.7-24
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• 2007

The subject is connected with a structure named "The Symbolic" to Lacan, but he denied that the subject is explained simply as a fruit of language and "Other". From his point of view, passing through Subject, De-formation and Crack over it is designated as foundation of generation and creation rather than our destined defect. It should not be understood that subject of "The Real" is a concept of the subject free itself from restraint of "The Symbolic". However, this does not mean he asserts "Subject" is something incapable of being controlled by the unknown power. The problem is that this autonomous existence meets inside of it with something "more than one's own self" by "circulating around itself" like a permanent star. This is the indication of a "stranger in the middle of my privacy", or "extimit$\'{e}$", a coined-word by Lacan. Perhaps "Subject" is nothing more than the name of distance of object which is "too hot" to come close, and of this circulating movement. It's because of this object that the real subject stands against generalization and the subject can't be restored to any place in symbolic order-even though it is empty. The part which is told from Lacan's structural theory, that is to say, an importance to Lacan is that his Subject theory is not suggested or denied as a manual structure. On the contrary, it is a study of the relationship between the settled symbol that included in "real subject which is a unconscious one" and the symbolic subject hold- that is a metaphysical subject in general meaning. In Lacan's enlarged concept of subject beyond symbolic reality, it is noticeable that it gives justifiability to the union of a medium of different nature in artistic expression. We can recognize that the unconscious world is a living space which enables it to be a "condition of human being", not something dark under the surface of water through Magritte's(Rene Magritte, 1898~1967) surrealistic works. In other words, Magritte's art secures a core dimension of human nature through a mysterious gap of conscious and settled space. Magritte's drawings often evokes strange and unsettling feelings in people who view his paintings. This is because routine objects are found in "unsuitable" places from which we usually find them in our everyday lives. "Reality" in Magritte's paintings makes it aware that it is a strained field of concealment and disclosure basically between truths, and we can learn that his behavior to overturn to paint in-visible things is finally an effort to restore the "real subject" to the viewer's reality. In other words, such reversion arouses a nostalgic desire for the objects existing in their original appearance as they are - natural condition that our gaze had not been distorted yet by anamorphic stains. - and the state when we are conscious of them normally. Such desire offers an opportunity for us to get out of mental depression rather than operates to us as an abnormal crack. It's a successive process of effort to search for lost subject and Paradise Lost facing up to reality of subject human that is to be a subject of world and life are ousted from their place by structure and authority of culture.

• The Journal of Korean Philosophical History
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• no.35
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• pp.131-164
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• 2012

This paper is to make a generalization of Keyongyegimunrok(經義記聞錄) by Namdang Han Wonjin(1682~1751) whose historical positions of philosophy were contained, and to examine its established periods and the summaries of Ligi-Simseong Doseol(理氣心性圖說, illustrated Account of principle, Vital force, and Heart-mind) given in Appendix of Chap. 6. Total seventeen explanatory diagrams cover over the theory of principle and material force, theory of Heart-mind, theory of cultivation. These explanatory diagrams were produced systematically and easily to understand the pursuits of study, so-called Ho-hak(湖學), since Namdang becoming a member of the Yellow River(黃江) school. The philosophical argumentations of Namdang was usually succeeded by the orthodox stream of Ki-ho(畿湖) School transmitted from Ii, Song Si-yeol, Gwon Sang-ha. Ligi-wollyu-do(理氣源流圖), Ligi-dongjeong-do(理氣動靜圖), irwon-bunsu-do(一原分殊圖, 4 diagrams) are diagrams equivalent to Ki-ho School's ontology. As Ki-ho School's theory of Heart-mind, there are Seongjeong-hoenggan-do(性情橫看圖), Seongjeong-sugan-do(性情竪看圖), Seongjeong-chonghwoi-do(性情總會圖), Oseonghoju-do (五性互主圖), Oseongchubon-do(五性推本圖), Simseongmyohap-do (心性妙合圖), Simseongiji-do(心性二岐圖), Jungyongcheonmyeong-do(中庸天命圖), Insim dosim-do(人心道心圖), focusing on Simtongseongjeong-do(心統性情圖), and last diagram is Wihakjibang-do(爲學之方圖), which adapted from the diagram established by Ii and Song Si-yeol. The significance of Keyongyegimunrok(經義記聞錄) is comprehensive of the pursuits of the Yellow River school's studies, and provides evidence of a leading figure in Ho-hak.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.43-51
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• 2022

In this paper, we suggest the method to improve the existing method leaning context-free grammar(CFG) using tabular representation(TBL) as a chromosome of genetic algorithm in grammatical inference and show the more efficient experimental result. We have two improvements. The first is to improve the formula to reflect the learning evaluation of positive and negative examples at the same time for the fitness function. The second is to classify partitions corresponding to TBLs generated from positive learning examples according to the size of the learning string, proceed with the evolution process by class, and adjust the composition ratio according to the success rate to apply the learning method linked to survival in the next generation. These improvements provide better efficiency than the existing method by solving the complexity and difficulty in the crossover and generalization steps between several individuals according to the size of the learning examples. We experiment with the languages proposed in the existing method, and the results show a rather fast generation rate that takes fewer generations to complete learning with the same success rate than the existing method. In the future, this method can be tried for extended CYK, and furthermore, it suggests the possibility of being applied to more complex parsing tables.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.107-119
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• 2023

The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.3-12
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• 2023

The issue to be discussed is set as the relationship between urban fragmentation and urban heat phenomena. The fragmentation is recognized as a negative form that commonly occurs in the process of urbanization. The purpose of this study is to examine the relationship between urbanization entropy and heat phenomenon by looking at the five major cities in Korea. The employed methods are InVEST Urban Cooling Model and MSPA (Morphological Spatial Pattern Analysis) by using the meteological data for the July 2018. The major results are as follows; First, a low rank correlation(rho=-0.3) is found in the relation between entropy and Cooling Capacity Index (CCi). Second, a very high level of rank correlation is observed between entropy and Average Temperature(℃)(rho=0.9). The implications are that 1) a city with a large degree of sprawling development can have a negative effect on urban heat phenomena; 2) the composition of land use including dispersion and concentration in non-urbanized areas, which has the characteristics of open space, can affect the urban thermal environment. Due to the limited number of case studies, it is appropriate to understand that a possibility, not generalization, is observed between entropy and heat phenomena in urbanized areas.

• 한국체육학회지인문사회과학편
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• v.55 no.4
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• pp.85-107
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• 2016

By examining the constitutive characteristics of Yon-Ko-Jeon and analyzing the lived meanings and experiencing essence of students, this study details the students' awareness, responses, and strategies with regards to the phenomenon of women's alienation from Yon-Ko-Jeon. Students from the two colleges were divided into two groups- one which was aware of women's alienation from Yon-Ko-Jeon, and another group that was unaware of such a phenomenon. Students without awareness tended to perceive the alienation of women from Yon-Ko-Jeon as a natural phenomenon. On the other hand, the members who had awareness tended to see it as a phenomenon that was either justified, unequal, or in need of change. In the latter group, those who saw women's alienation as a justified phenomenon responded with tolerance and adopted a bystander strategy. Conversely, those who saw it as an unequal phenomenon responded with rejection and instead chose to adopt anti-/alternative Yon-Ko-Jeon strategies. The last group, which perceived women's alienation as a phenomenon in need of change, adopted correcting responses as well as intercollegiate solidarity and cooperation strategies. A generalization of the findings reveals that the students' experiencing essence of the phenomenon extends from critical thinking to awareness, response, and strategy in a step-by-step and sequential process. Through this study, it was found that the students' experiencing essence all follow a continuous thinking pattern, as illustrated in the diagram provided.

• Knowledge Management Research
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• v.24 no.2
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• pp.87-115
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• 2023

This study aims to examine the causal relationships between sales and employment for public technology-based startups. Although there is a limit to statistical generalization due to the poor understanding of the actual conditions of public technology start-up companies, these companies were analyzed by classifying them into high-growth companise, potential growth companies, and other companies. In order to understand the causal relationship, and to estimate the time required to be effective, panel vector autoregression was applied. As a result, the performance creation mechanism was identified as government supoort and private investment was mutually causal with employment, sales did not cause employment, and employment caused sales. In other words, it was found that employment plays an mediator role in public technology based startups' performance mechanism. In addition, private investment had the effect of improving employment and sales in the short time than governments support, and showed that firms with high employment can attract government support and private investment. This study are academically meaningful in that they empirically revealed the process of performance creation, whereas previous studies had only shown whether there was an effect on performance. It also has a policy contribution by suggesting the need for effective policy promotion by considering the 'employment' factor, such as human resource support, as more important.