• Korean Journal of Construction Engineering and Management
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• v.24 no.4
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• pp.60-73
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• 2023

The need for adopting automation technologies to improve inefficiencies in interior finishing modeling work is increasing during the Building Information Modeling (BIM) design stage. As a result, the use of visual programming languages (VPL) for practical applications is growing. However, undefined or incorrect space designations in BIM models can hinder the development of automated finishing modeling processes, resulting in erroneous corrections and rework. To address this challenge, this study first developed a rule-based automated interior finishing detailing module for floors, walls, and ceilings. In addition, an automated space integrity checking module with 86.69% ACC using the Multi-Layer Perceptron (MLP) model was developed. These modules were integrated into a design automation module for interior finishing, which was then verified for practical utility. The results showed that the automation module reduced the time required for modeling and integrity checking by 97.6% compared to manual work, confirming its utility in assisting BIM model development for interior finishing works.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.989-999
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• 2023

The aim of this paper is to study the projective curvature tensor field of the Curvature tensor Rⁱ_jkh on a recurrent non Riemannian space admitting recurrent affine motion, which is also decomposable in the form Rⁱ_jkh=Xⁱ Y_jkh, where Xⁱ and Y_jkh are non-null vector and tensor respectively. In this paper we decompose Special Pseudo Projective Curvature Tensor Field. In the sequal of decomposition we established several properties of such decomposed tensor fields. We have considered the curvature tensor field Rⁱ_jkh in a Finsler space equipped with non symmetric connection and we study the decomposition of such field. In a special Pseudo recurrent Finsler Space, if the arbitrary tensor field 𝜓ⁱ_j is assumed to be a covariant constant then, in view of the decomposition rule, 𝜙_kh behaves as a recurrent tensor field. In the last, we have considered the decomposition of curvature tensor fields in Kaehlerian recurrent spaces and have obtained several related theorems.

• Journal of the Korean Society of Safety
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• v.9 no.1
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• pp.134-139
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• 1994

In order to assess the level of atmospheric pollution and to contribute the hearth improvement of residents in Taejon city, the authors were measured the concentration of air pollutants(CO, SO$_2$, NO$_2$, TSP, Pb, Cd, Cr) at three places of the control road in Taejon. The investigative research performed bimonthly from May 1993 to September 1993, and the places were the underground shopping stores of Taejon station, Dongyang department store and provincial goverment areas. The results of statistical analysis are as followings. \circled1CO :0.569~0.966ppm \circled2SO$_2$：0.084~0.170ppm \circled3NO$_2$:0.0045~0.022ppm \circled4TSP：249~299$\mu\textrm{g}$/㎥. \circled5Pb :0.366~1.157$\mu\textrm{g}$/㎥. \circled6Cd：0.016~0.025$\mu\textrm{g}$/㎥. \circled7 Cr : 0.198 ~0.290$\mu\textrm{g}$/㎥. The mean concentration of SO$_2$in Dongyang department store area was 0.17ppm, and it exceeded the ambient air quality standard by 0.02ppm. The concentration of TSP was higher than a standing rule of public hygiene, and it was very near to a standing rule of environmental preservation. The standing rule of indoor air pollution in underground shopping store have two different laws, the public hygiene and the environmental preservation. Therefore, it was difficult to judge what to do in such circumstance. In regarding to the laws, an environmental standard for air pollution in the underground space must unify into the standard of public hygiene.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.6-11
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• 2003

Recently, the modular network was proposed in a way to keep the size of the neural network small. The modular network solves the problem by splitting it into sub-problems. In this aspect, fuzzy systems act in a similar way. However, in a fuzzy system, there must be an expert rule which separates the input space. To overcome this, fuzzy-neural network has been used. However, the number of fuzzy rules grows exponentially as the number of input variables grow. In this paper, we would like to solve the size problem of neural networks using modular network with the hierarchic structure. In the hierarchic structure, the output of precedent module affects only the THEN part of the rule. Finally, the rules become shorter being compared to the rule of fuzzy-neural system. Also, the relations between input and output could be understood more easily in the Proposed modular network and that makes design easier.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.63-71
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• 2011

The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.11-17
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• 2007

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it cannot explain how the classification result is obtained. In order to overcome this problem, we propose an incremental teaming algorithm based on RPA (Recursive Partition Averaging) to extract IF-THEN rules that describe regularities inherent in training patterns. But rules generated by RPA eventually show an overfitting phenomenon, because they depend too strongly on the details of given training patterns. Also RPA produces more number of rules than necessary, due to over-partitioning of the pattern space. Consequently, we present the IREA (Incremental Rule Extraction Algorithm) that overcomes overfitting problem by removing useless conditions from rules and reduces the number of rules at the same time. We verify the performance of proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.7-13
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• 2002

Almost applications using fuzzy theory are based on the fuzzy inference. However fuzzy inference needs much time in calculation process for the fuzzy system with many input variables or many fuzzy labels defined on each variable. Inference time is dependent on the number of arithmetic Product in computation Process. Especially, the inference time is a primary constraint to fuzzy control applications using microprocessor or PC-based controller. In this paper, a simple fast fuzzy inference algorithm(FFIA), without loss of information, was proposed to reduce the inference time based on the fuzzy system with triangular membership functions in antecedent part of fuzzy rule. The proposed algorithm was induced by using partition of input state space and simple geometrical analysis. By using this scheme, we can take the same effect of the fuzzy rule reduction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.485-493
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• 2019

The purpose of this study is to gain basic information to manage the free choice activities of kindergarten by investigating the teachers' perception of restriction rules. The subjects of the study were 200 kindergarten teachers who worked in J province. The instrument used for this study was a questionnaire that focused on teachers' perception about the restriction rules for the free choice activities. The results of this study were as follows. First, the teachers considered restriction rules in the art center as the most important factor. Second, the teachers recognized that limiting the number of players in a same center is the most important thing among the three restriction rules. Third, the teachers' perception regarding the necessity of restriction rules is as follows. The rule of restricting the number of players is needed to prevent too many players focusing in a certain center. The rule of restricting play time is necessary to encourage children to play in various centers, and the rule of restricting play space is crucial to solidify the educational purpose that every interest center has. The meaning and the necessity of the restriction rules on children's free choice activities were further discussed as connected with children's right to play.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.6
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• pp.946-953
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• 2022

Using the management strategy evaluation methods and data on the Korea chub mackerel Scomber japonicus where the state-space logistic production model is used as the operation and the estimation model respectivley, we examined the effects of both Dorn's rule, α and the buffer value for ABC (allowable biological catch), which are used by the Korea fishery managers for decision rules. We set scenarios that have different pairs of buffer and α values, which include those currently used in the management in Korea. Under each sceanario, we projected the fish population biomass until year 2050, during which ABC is determined in each year with the decision rule. We used three kinds of performance measures: (i) whether the biomass in 2050 is overfished; (ii) the average of annual yields over the simulation period; and (iii) the variability of annual yields over the period. We found that the current practice (buffer=0.9, and α = 0.05) resulted in the best performance in terms of avoiding the "overfished" status. However, the current practice failed to reach the maximum average of the annual yields and led to larger uncertainty in the annual yields.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.139-147
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• 2010

A novel turbo coded modulation scheme, called turbo-APPM, for deep space optical communications is constructed. The constructed turbo-APPM is a serial concatenations of turbo codes, an accumulator and a pulse position modulation (PPM), where turbo codes act as an outer code while the accumulator and the PPM act together as an inner code. The generator polynomial and the puncturing rule for generating turbo codes are chosen to show the low bit error rate. At the receiver, the joint decoding is performed by exchanging soft information iteratively between the inner decoder and the outer decoder. In the outer decoder, a local iterative decoding for turbo codes is conducted before transferring soft information to the inner decoder. Poisson distribution is used to model the deep space optical channel. It is shown by simulations that the constructed turbo-APPM provides coding gains over all previously proposed schemes such as LDPC-APPM, RS-PPM and SCPPM.