• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.30-41
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• 1993

Developed in this paper is a feature based modeling system for the design of welded plat construction(WPC) which is composed of flat or bended plates represented as reference plane with a constant thickness. First, the necessity and the characteristics of the modeing system for WPC as compared with the assembly of mechanical parts are investigated. Secondly, feature library for the assembly of WPC is shown which contains several types of features like joint feature, groove feature, material feature, and precision feature. Thirdly, the assembly procedures are presented which mainly consist of both the assembly transformation and the correct assembly checking. Fourthly, weld lines of the assembled WPC are defined so that those can be used in the process planning or the manufacturing stage. Finally, a prototype by a geometric modeling software Pro/Engineer, a graphic software GL(Graphic Library), and C language on a CAD workstation IRIS.

• Korean Journal of English Language and Linguistics
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• v.2 no.2
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• pp.207-226
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• 2002

In this paper we provide an alternative explanation for there construction, by assuming that the expletive there (EXPL) has independently uninterpretable Case feature as well as u[person], not as being pied-pipied with $\varphi$-feature. If EXPL has only u[person], we could analyse incorrectly some there constructions, including an embedded infinitive clause: by Chomsky (1998, 1999) in the construction, EXPL is ‘frozen’ and cannot participate in the computation of higher. As a result, we could predict incorrectly that the derivation is crashed. But if EXPL has two uninterpretable features, u[person] and u[Case], we could predict correctly that the derivation is converged: the u[person] of EXPL is deleted under Matching/Agree with $T_{def}$; still, the undeleted u[Case] of EXPL is activating; so EXPL can be raised to [SPEC, T] to satisfy the EPP-feature of matrix T.

• Korean Journal of Construction Engineering and Management
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• v.22 no.2
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• pp.63-71
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• 2021

This paper looks into how to enhance construction project management, focusing on the change order, which is often considered one of the major causes for construction delays, disputes, and claims in the middle east construction. First, this paper categorizes the major causes of change orders. It suggests a detailed classification standard for affecting factors resulting from change orders based on a case study result of an on-going construction project in the Middle East. In particular, this paper presents a method to apply a machine learning-based feature selection to quantify the importance of change order triggers and affecting factors. As a result, the case study identifies six major change order triggers and eight affecting factors. Also, a meaningful relationship between change order triggers and affecting factors by each category is presented. This paper will contribute to setting a clear guideline for change order management for the international plant construction field while helping prevent construction delays and cost run-ups by reducing the time required for change order resolution between project owners and contractors.

• ETRI Journal
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• v.41 no.2
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• pp.235-241
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• 2019

In this paper, we propose a rank-weighted reconstruction feature to improve the robustness of a feed-forward deep neural network (FFDNN)-based acoustic model. In the FFDNN-based acoustic model, an input feature is constructed by vectorizing a submatrix that is created by slicing the feature vectors of frames within a context window. In this type of feature construction, the appropriate context window size is important because it determines the amount of trivial or discriminative information, such as redundancy, or temporal context of the input features. However, we ascertained whether a single parameter is sufficiently able to control the quantity of information. Therefore, we investigated the input feature construction from the perspectives of rank and nullity, and proposed a rank-weighted reconstruction feature herein, that allows for the retention of speech information components and the reduction in trivial components. The proposed method was evaluated in the TIMIT phone recognition and Wall Street Journal (WSJ) domains. The proposed method reduced the phone error rate of the TIMIT domain from 18.4% to 18.0%, and the word error rate of the WSJ domain from 4.70% to 4.43%.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.317-326
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• 2022

With the development of various technologies in the area of artificial intelligence, a number of studies to application of artificial intelligence technology in the construction field are underway. Diverse technologies have been applied to the task of predicting construction costs, and construction cost prediction technologies applying artificial intelligence technologies have recently been developed. However, it is difficult to secure the vast amount of construction cost data required for machine learning, which has not yet been practically used. In this study, to predict the construction cost, the latest artificial neural network(ANN) method is used to propose a method to improve the construction cost prediction performance. In particular, to improve predictive performance, a log conversion method of target variables and a feature scaling method to eliminate the difference in the relative influence of each column data are applied, and their performance in predicting construction cost is compared and analyzed.

• Annual Conference of KIPS
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• 2001.04b
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• pp.1089-1092
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• 2001

IDS 에서 가장 중요한 것은 침입을 논리적으로 모델링하고, 이것을 센싱 할 수 있는 Filter 의 개발이며 Filter 에서 발생한 이벤트들에서 특정 공격 행위를 인식할 수 있는 신호인 Signature 의 정의를 통해 이벤트 스트림에서 Signature 를 자동으로 인식할 수 있는 방법에 대한 연구가 가장 핵심적이라고 할 수 있다. 본 논문은 이러한 filter 와 Signature 에서 사용할 수 있도록 특징들이 정의 되어있는 양식으로 원시 데이터로부터 profile 을 생성 filter 와 signature 에서 탐지할 수 있는 모듈을 적용할 수 있도록 네트웍과 host input stream 등의 raw audit data 에서 특징을 추출 Feature Construction 작성에 대한 연구이다.

• Language and Information
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• v.7 no.2
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• pp.163-178
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• 2003

Korean displays an interesting construction (so-called possessor agreement construction), where a possessor nominal and its possessum nominal are marked with the same case as shown in the example Mary-ka John-ul tali-lul cha-ss-ta ‘Mary kicked John's leg’ More interestingly, not all possessors in possessive construction are marked the same case with its possessum as shorn in the ungrammatical sentence ＊Mary-ka John-ul cha-lul cha-ss-ta ‘Mary kicked John's car’. Hence, a simple but non-trivial question arises: In what situation are both possessors and possessums marked with the same case\ulcorner In this paper, we advance three claims: (i) Possessor agreement appears in the situation where entailment is satisfied as follows: If Mary kicked John's leg, it entails that Mary kicked John, (ii) entailment in possessor agreement results from theta-feature sharing; specifically, the whole DP and the possessor DP share the same theta role, and (iii) Possessor nominals are marked with accusative (or nominative) case when they are assigned internal theta role from the predicate directly.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.680-681
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• 2015

This study develops an algorithm that automatically performs reverse engineering on three-dimensional (3D) sweeping shapes using a user's pre-defined feature templates and 3D point cloud data (PCD) of sweeping shapes. Existing methods extract 3D sweeping shapes by extracting points on a PCD cross section together with the center point in order to perform curve fitting and connect the center points. However, a drawback of existing methods is the difficulty of creating a 3D sweeping shape in which the user's preferred feature center points and parameters are applied. This study extracts shape features from cross-sectional points extracted automatically from the PCD and compared with pre-defined feature templates for similarities, thereby acquiring the most similar template cross-section. Fitting the most similar template cross-section to sweeping shape modeling makes the reverse engineering process automatic.

• Journal of the Korea Institute of Building Construction
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• v.21 no.2
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• pp.165-174
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• 2021

The construction industry causes the most accidents and fatalities among all industries. Although many efforts have been made to reduce safety accidents in construction, the study on the lost workdays that return to work place is insufficient. Therefore, this study proposes a model that classifies the lost workdays lost into moderate and severity, and derives the importance of variable and analyzes important factors through the trained random forest model. We analyze the learning process of the random forest which is a black box model, and extracted important variables that impact on the severity of the lost workdays through the extracted feature importance. The factors existing inside were analyzed through the extracted variables. The purpose of this study is to analyze the accident case data at the construction site through a random forest model and to review variables that have a high impact on the lost workdays. In the future, this sutdy can apply to improve construction safety management and reduce the accident of industrial accidents.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.834-842
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• 2015

We propose a method to construct composite feature vector based on discriminant analysis for face recognition. For this, we first extract the holistic- and local-features from whole face images and local images, which consist of the discriminant pixels, by using a discriminant feature extraction method. In order to utilize both advantages of holistic- and local-features, we evaluate the amount of the discriminative information in each feature and then construct a composite feature vector with only the features that contain a large amount of discriminative information. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed composite feature vector has improvement of face recognition performance.