• 한국안전학회지
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• 제30권4호
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• pp.99-105
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• 2015

In this study, displacement estimation algorithm, which is not requiring an absolute reference point unlike the conventional displacement measurement method, is developed using the geophone. To estimate displacement of the bridge, measured velocity time signal is integrated in the frequency domain. And, the estimated displacement is compared with the measured result using a conventional method. Based on the dynamic field test results, it was found that the estimated displacement by the present algorithm is similar to that of a conventional method. The displacement estimation algorithm proposed in this paper can be effectively applied to measure the displacement of a structure, which is difficult to install a displacement transducer at the fixed point.

• 대한산업공학회지
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• 제33권2호
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• pp.183-190
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• 2007

We present a new decision tree classification algorithm using rough set theory that can induce classification rules, the construction of which is based on core attributes and relationship between objects. Although decision trees have been widely used in machine learning and artificial intelligence, little research has focused on improving classification quality. We propose a new decision tree construction algorithm that can be simplified and provides an improved classification quality. We also compare the new algorithm with the ID3 algorithm in terms of the number of rules.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.1022-1030
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• 2003

In this paper we propose a efficient offset curve construction algorithm for $C^0$-continuous Open and Closed 2D sequence curve with line segment in the plane. One of the most difficult problems of offset construction is the loop problem caused by the interference of offset curve segments. Prior work[1-10] eliminates the formation of local self-intersection loop before constructing a intermediate(or raw) offset curve, whereas the global self-intersection loop are detected and removed explicitly(such as a sweep algorithm[13]) after constructing a intermediate offset curve. we propose an algorithm which removes global as well as local intersection loop without making a intermediate offset curve by forward tracing of tangential circle. Offset of both open and closed poly-line segment sequence curve in the plane constructs using the proposed approach.

• 한국안전학회지
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• 제34권6호
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• pp.29-37
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• 2019

Since construction sites are exposed to outdoor environments, working conditions are significantly dangerous. Thus, wearing of the personal protective equipments such as safety helmet is very important for worker safety. However, construction workers are often wearing-off the helmet as inconvenient and uncomportable. As a result, a small mistake may lead to serious accident. For this, checking of wearing safety helmet is important task to safety managers in field. However, due to the limited time and manpower, the checking can not be executed for every individual worker spread over a large construction site. Therefore, if an automatic checking system is provided, field safety management should be performed more effectively and efficiently. In this study, applicability of deep learning based computer vision technology is investigated for automatic checking of wearing safety helmet in construction sites. Faster R-CNN deep learning algorithm for object detection and classification is employed to develop the automatic checking model. Digital camera images captured in real construction site are used to validate the proposed model. Based on the results, it is concluded that the proposed model may effectively be used for automatic checking of wearing safety helmet in construction site.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2157-2169
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• 2023

In order to handle the problem that puncture patterns will change the position distribution of original information bits and frozen bits in polar codes, which affects performance of puncture polar codes further, a minimum row weight and polar spectrum based puncture polar codes construction algorithm (called PA-MRWP) is proposed in this paper. The algorithm calculates row weight of generator matrix and sorts the row weight in ascending order first. Next, the positions with the minimum row weight are selected as initial puncture positions. If the rows with the same row weight cannot all be punctured, polar spectrum based auxiliary puncture scheme is used. In sub-channels with the same row weight, rows corresponding to the polarized sub-channels with higher reliability are selected as puncture positions to construct puncture vector, and the reliability is calculated based on polar spectrum. It is actually a two-step selection strategy, the proposed minimum row weight puncture (MRWP) algorithm is used for primary selection and polar spectrum based auxiliary puncture is used for adjustment. Simulation results show that, compared with worst quality puncture (WQP) algorithm, the proposed PA-MRWP algorithm and Gaussian approximation-aided minimum row weight puncture (GA-MRWP) algorithm provide gains of about 0.46 dB and 0.29 dB at bit error rate (BER) of 10^-4, respectively when code length N=400, code rate R=1/2. In addition, the proposed puncture algorithms improve the BER performance significantly with respect to quasi-uniform puncture (QUP) algorithm.

• 한국건설관리학회논문집
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• 제11권4호
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• pp.68-79
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• 2010

도로면 크랙실링 공법은 예방적 차원에서 도로면에 발생된 크랙을 초기에 효과적으로 보수할 수 있는 공법으로 국내외에 서는 1990년대 초반부터 기존 도로면 크랙실링 작업의 생산성, 안전성 및 품질의 균일성 확보를 목적으로 크랙실링 자동화 장비의 개발을 위한 지속적인 연구개발 노력을 수행해 왔다. 도로면 크랙실링 자동화 장비를 개발함에 있어 특히 경로계획은 주어진 작업 영역 내에서 개발 장비로 하여금 실링될 크랙 네트워크를 시간 효과적으로 횡단할 수 있도록 하는 운항 정보를 제공하게 되므로 이는 개발 장비의 성능을 결정 짖는 매우 중요한 연구주제라 할 수 있다. 본 연구의 목적은 작업 영역 내 경로계획 데이터의 효과적인 모델링을 통해 크랙실링 자동화 장비의 최적 경로계획 알고리즘을 개발하는 것으로써, 경로 집합전체를 완전 탐색하는 2단계 트리 알고리즘과 크랙의 순열만을 탐색하는 1단계 트리 알고리즘을 개발하였으며, 알고리즘의 성능 측정 및 분석을 통해 최적 경로계획 알고리즘의 적용 범위와 그에 따른 성능 향상 정도를 평가하였다. 이 연구의 결과는 도로면 크랙실링 자동화 장비의 생산성 향상에 크게 기여할 수 있을 것으로 기대된다.

• 한국건축시공학회지
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• 제24권1호
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• pp.133-144
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• 2024

OpenCV 기반 길이측정 알고리즘은 길이측정 검측업무를 보조함과 동시에 객관적인 검측결과를 제시할 수 있을 것으로 판돤된다, 그러나, 건설현장 내에서 체커보드의 유형과 촬영조건이 해당 알고리즘의 정확도에 어떠한 영향을 미치는지에 대한 연구는 미흡한 실정이다. 이에 본 연구에서는 디지털 기술을 활용한 검측업무 수행에 적합한 체커보드와 촬영방법을 제시하고자 OpenCV 기반 길이측정 알고리즘 정확도 측정 실험을 수행하였다. 실험결과 OpenCV 기반 길이측정 알고리즘을 통한 검측업무 시 촬영거리 4m 이내, 촬영각도 90°의 조건 하, 체커보드 크기와 Square size를 각각 A4 이상, 50mm 이상으로 설정하는 것이 적절할 것으로 판단된다. 본 연구의 결과는 디지털 기술을 통한 길이측정 검측업무 수행 시 가이드라인으로 활용될 수 있을 것으로 사료된다.

• 드라이브 ㆍ 컨트롤
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• 제15권4호
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• pp.81-90
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• 2018

Indoor construction site such as building demolition sites, tunnel, vinyl house, and cattle shed are subject to various risk factors such as falling stones, soot and bad odors. However, most of the mini excavators have no cabin that can protect the driver from such risk factors. Therefore, researches on remote control technology of construction equipment are actively conducted as a method for protecting the driver from the risk factors occurring in the working environment. For effective remote control, it is necessary to be able to control the travelling and work using a portable small transmitter. However, due to the limitation of the size of the transmitter, complex operation control is required to control two or more actuators with a single joystick. Also, it is essential to check how remote control characteristics change in various environments such as distance, signal strength, obstacle. Therefore, in this study, an algorithm that can control two actuators simultaneously with a single joystick signal was developed, and a communication method suitable for indoor and outdoor mini construction equipment by analyzing experimentally how the remote control characteristics vary according to various work environments and telecommunication methods proposed.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.530-539
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• 2007

Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.