• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.634-637
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• 2008

Performance-based Project Delivery System(PPDS) is one of Project Delivery System that when owner ask for performance than constructor feel free to choose materials, technology, an engineering method. PPDS rank higher position than Performance Warranty Contract and Technical Proposal Bid. This study aims to propose Improvement Idea for PPDS that based Housing Performance Grading Indication System. 'Request-performance Checklist' is used as communication means(between owner and constructor) and a kind of corroborative facts make the procedures achievement of project like contract easier.

• The Journal of Korean Association of Computer Education
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• v.21 no.6
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• pp.105-115
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• 2018

The descriptive-type question is appropriate for deep thinking ability evaluation, but it is not easy to grade. Since, even though same grading criterion, the graders produce different scores, we need the objective evaluation system. However, the system needs the Korean analysis. As the descriptive-type answering is described with the compound sentence, the system has to analyze the compound sentence. This paper develops the Korean syntactic-semantic analysis system for compound sentence and evaluates performance of the system. This system selects the modifiee of the word phrase using syntactic-semantic constraint and semantic dictionary. The 93% accurate rate shows that the system is effective. This system will be utilized in descriptive-type grading and Korean processing.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.498-506
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• 2010

To use domestic softwood for structural lumber, appropriate grading system for quality, production and distribution condition of domestic lumber should be prepared. Kim et al. developed an automatic image processing system for grading domestic structural lumber (2009a and b). This study was carried out to investigate optimal image merging conditions for improving performance of image input system which is the key technique of image processing system, developed in the previous paper. To merge digital images of Korean larch lumber, choosing the green channel information of obtained image data showed the most accurate merging performance. As a pre-treatment process, applying Y-derivative Sharr's kernel filter could improve the image merging accuracy, but the effect of camera calibration was imperceptible. The optimal size of template image was verified as 30 pixel widths and 150 pixel heights. When applying the above mentioned conditions, the error length of images was 3.1 mm and the processing time was 9.7 seconds in average.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.25-37
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• 2022

In this paper, a small-scale model testing system was developed using a series of small-scale model tests to analyze the mechanism of compaction pile formation and evaluate the quality of controlled grading aggregates proposed as an alternative material to the sand compaction pile (SCP) method and granular compaction pile (GCP). These are the most typical ground improvement methods in field practice, particularly for soft grounds. However, the SCP has faced difficulties due to the supply shortage of natural sand and the corresponding price surge of sand. The GCP is limited in marine soft grounds because of the failure occurring at the pile tip caused by excessive expansion of the deeper bulbs, leading to uneven bulb formation. The uniformity of compacted pile bulbs is critical to ensuring the bearing capacity and quality of the compaction pile. This study aims to evaluate the performance of the new material and controlled grading aggregates using small-scale model tests simulating field compaction process to investigate its potential application in comparison with SCP. The compaction piles are examined in four cases according to different materials used for compaction pile and clay strength. The compaction pile materials, which are made of sand and controlled grading aggregates, used in this study were compared to reveal the mechanism of the bulb creation. The experimental data confirm that the bulb formation quality of the traditional sand and the new material, controlled grading aggregates are comparable. The compaction pile made of controlled grading aggregates presents higher bearing capacity than that of marine sand.

• Korean Journal of Construction Engineering and Management
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• v.21 no.1
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• pp.78-86
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• 2020

Dozer is an expensive construction equipment and has a significant performance impact on earthwork performance. A machine guidance system has been applied to dozer equipment as a solution that can improve the performance. The system can provide earthwork-related information to equipment operators so that earthworks can be carried out with minimum support from surveyors. Construction Equipment Machine guidance has the function of supporting earthwork according to an earthwork plan by providing excavation-related information to machine operators. The objective of this study is to evaluate the performance improvement of a machine guidance system for an dozer earthwork operation, and to compare the machine guidance method with the traditional method. The performance has been evaluated in two folds: 1) productivity and 2) accuracy. The productivity shows the quantity of earthwork for a given unit time. The accuracy shows the deviation of grading level from the designed level on the construction drawing for earthwork. The machine guidance system has been applied to a testing bed in a construction site. Data comparison analysis showed that the earth earthwork had 46.59% improvement in productivity as well as 46.96% improvement in accuracy, and is expected to provide a tool for applying smart constrction to the earthwork operation.

• Journal of Biosystems Engineering
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• v.20 no.4
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• pp.376-382
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• 1995

This study was intended to develop more reliable fruit sorting algorithm regardless of the feeding positions of fruits by using the neural network in which various information could be included as input data. Specific objectives of this study were to select proper input units in the neural network by investigating the features of input image, to analyze the sorting accuracy of the algorithm depending on the feeding positions of Fuji apple and to evaluate the performance of the algorithm for practical usage. the average value in color grading accuracy was 90%. Based on the computing time required for color grading, the maximum sorting capacity was estimated to approximately 10, 800 apples per hours. Finally, it is concluded that the neuro-net based color sorting algorithm developed in this study has feasibility for practical usage.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.177-180
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• 2000

The objective of this study is to analyze the degree of surface-glossing of cement mortar with the grading of aggregate and contents of limestone powder. According to the experimental results, degree of surface-glossing of cement mortar using river sand is higher than that of crushed sand. As F.M of aggregates is less than 2.78, degree surface-flossing of cement mortar has better performance, Also, as the contents of limestone power increase, degree of surface-flossing is shown to be improved, And it shows that degree of surface-glossing decrease with elapse of age.

• Journal of Biosystems Engineering
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• v.22 no.2
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• pp.227-236
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• 1997

Manual grading and sorting of red-ginsengs are inherently unreliable due to its subjective nature. A computerized technique based on optical and geometrical characteristics was studied for the objective quality evalution. Spectral reflectance of three categories of red-ginsengs - "Chunsam", "Chisam", "Yangsam" - were measured and analyzed. Variation of reflectance among parts of a single ginseng was more significant than variation among the quality categories of ginsengs. A PC-based image processing algorithm was developed to extract geometrical features such as length and thickness of body, length and number of roots, position of head and branch point, etc. The algorithm consisted of image segmentation, calculation of Euclidean distance, skeletonization and feature extraction. Performance of the algorithm was evaluated using sample ginseng images and found to be mostly sussessful.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.253-259
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• 1996

The purpose of this study is to investigate the fundamental properties of polyurethan concrete. Polyurethane must be expanded by means of a blowing agent during polymerization. Chemical blowing is caused by the reaction water with isocyanate. Binder system for polyurethane concrete is based on polyol and isocyanate with catalyst, surfactant, and methyl chloride. Polyurethane concretes are prepared with various grading of aggregate, and tested for compressive, flexural strengths, flow test, foaming multiple proportion, working life, condition of surface, distirbution of aggregate. From the test results, the foaming of polyurethane concretes are affceted by amount and grading of aggregate. Workability increases with raising amount of methy chloride and working life reduced according to amount of catalyst. The mix proportion of B with methyl chloride of 1% and catalyst of 0.1g for polyurethane concrete is recommended in consideration of strengths, condition of surface and balance between cost and performance.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.769-782
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• 2022

A study on agricultural automation became more important. In Korea, sweet persimmon farmers spend a lot of time and effort on classifying profitable persimmons. In this paper, we propose and implement an efficient grading algorithm for persimmons before shipment. We gathered more than 1,750 images of persimmons, and the images were graded and labeled for classifications purpose. Our main algorithm is based on EfficientDet object detection model but we implemented more exquisite method for better classification performance. In order to improve the precision of classification, we adopted a machine learning algorithm, which was proposed by PyCaret machine learning workflow generation library. Finally we acquired an improved classification model with the accuracy score of 81%.