• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.283-288
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• 2007

This paper presents an analytical prediction of Nonlinear characteristics of prestressed concrete bridges by strengthened of externally tendon considering the work sequence, using beam-column element based on flexibility method and tendon element. The beam-column element was developed with reinforced concrete material nonlinearities which are based on the smeared crack concept. The fiber hysteresis rule of beam-column element is derived from the uniaxial constitutive relations of concrete and reinforcing steel fibers. The tendon element represent the bonded tendon and unbonded tendon behaviors. Beam-column element and tendon element was be subroutine A computer program, named RCAHEST (Reinforced Concrete Analysis in Higher Evaluation System Technology), for the analysis of RC and PSC structures was used. The proposed numerical method for prestressed concrete structures by strengthened of externally tendon is verified by comparison with reliable experimental results.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.211-222
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• 1998

Parametric design is an important modeling paradigm in CAD/CAM applications, enabling efficient design modifications and variations. One of the major issues in parametric design is to develop a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this appear, we propose a new approach to geometric constraint solving that employs a graph-based method to solve the ruler-and-compass constructible configurations and a numerical method to solve the ruler-and-compass non-constructible configurations, in a way that combines the advantages of both methods. The geometric constraint solving process consists of two phases: 1) planning phase and 2) execution phase. In the planning phase, a sequence of construction steps is generated by clustering the constrained geometric entities and reducing the constraint graph in sequence. in the execution phase, each construction step is evaluated to determine the geometric entities, using both approaches. By combining the advantages of the graph-based constructive approach with the universality of the numerical approach, the proposed approach can maximize the efficiency, robustness, and extensibility of geometric constraint solver.

• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.67-71
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• 2003

This paper presents the use of an evert system to automate process planning of block assembly, a task that is usually completed manually. In order to determine the sequence of assembly operation, a search method guided by rules, such as merging of related operations, grouping of similar operations, and precedence rules based on know-hows and geometrical reasoning, is used. In this paper, the expert system developed is explained in detail regarding a global database, control strategies, and rule bases. For verification purposes, the evert system has been applied to simple examples. Since the rule bases are isolated from the inference engine in the developed system, it is easy to add more rules in the future.

• Archives of Pharmacal Research
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• v.8 no.2
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• pp.91-98
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• 1985

Dependence of the flow behavior of aqueous suspension of Young-Il bentonite on the concentration and the type of electrolytes was studied. Viscosity measurements were made was Rion Viscotester, using No. 3 rotor at 62.5 R. P. M. at 25.deg.C. As electrolyte concentration increased, the apparent viscosity was observed to increase. Changes in viscosity were in general agreement with predicted results based on the Hofmeister sequence and the Schulze-Hardy rule. The observed electrolyte effect on the apparent viscosity was discussed in terms of the Verwey-Overbeek theory.

• Journal of KIISE
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• v.44 no.8
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• pp.774-781
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• 2017

Mention detection systems use nouns or noun phrases as a head and construct a chunk of text that defines any meaning, including a modifier. The term "mention detection" relates to the extraction of mentions in a document. In the mentions, a coreference resolution pertains to finding out if various mentions have the same meaning to each other. A pointer network is a model based on a recurrent neural network (RNN) encoder-decoder, and outputs a list of elements that correspond to input sequence. In this paper, we propose the use of mention detection using pointer networks. Our proposed model can solve the problem of overlapped mention detection, an issue that could not be solved by sequence labeling when applying the pointer network to the mention detection. As a result of this experiment, performance of the proposed mention detection model showed an F1 of 80.07%, a 7.65%p higher than rule-based mention detection; a co-reference resolution performance using this mention detection model showed a CoNLL F1 of 52.67% (mention boundary), and a CoNLL F1 of 60.11% (head boundary) that is high, 7.68%p, or 1.5%p more than coreference resolution using rule-based mention detection.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.102-107
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• 2000

This study describes computer-aided design system for stepped asymmetric forgings. To establish the appropriate process sequence, an integrated approach based on a rule-base system was accomplished. This system has four modules, which are undercut prevention module, shape cognition module, 3D modelling module and corner/fillet correction module. These modules can be used independently or at all. The proposed shape cognition method could be widely used in forging design of asymmetric parts.

• Annual Conference of KIPS
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• 2020.11a
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• pp.967-970
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• 2020

In a previous work we have done, we presented a monitoring system to automatically detect some dogs' behaviors from videos. However, the input video data used by that system was pre-trimmed to ensure it contained a dog only. In a real-life situation, the monitoring system would continuously receive video data, including frames that are empty and ones that contain people. In this paper, we propose a YOLOv4-based system for automatic object detection and trimming of dog videos. Sequences of frames trimmed from the video data received from the camera are analyzed to detect dogs and people frame by frame using a YOLOv4 model, and then records of the occurrences of dogs and people are generated. The records of each sequence are then analyzed through a rule-based decision tree to classify the sequence, forward it if it contains a dog only or ignore it otherwise. The results of the experiments on long untrimmed videos show that our proposed method manages an excellent detection performance reaching 0.97 in average of precision, recall and f-1 score at a detection rate of approximately 30 fps, guaranteeing with that real-time processing.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.179-188
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• 2008

In this paper, knowledge based text to facial sequence image system for interaction of lecturer and learner in cyber universities is studied. The system is defined by the synthesis of facial sequence image which is synchronized the lip according to the text information based on grammatical characteristic of hangul. For the implementation of the system, the transformation method that the text information is transformed into the phoneme code, the deformation rules of mouse shape which can be changed according to the code of phonemes, and the synthesis method of facial sequence image by using deformation rules of mouse shape are proposed. In the proposed method, all syllables of hangul are represented 10 principal mouse shape and 78 compound mouse shape according to the pronunciation characteristics of the basic consonants and vowels, and the characteristics of the articulation rules, respectively. To synthesize the real time facial sequence image able to realize the PC, the 88 mouth shape stored data base are used without the synthesis of mouse shape in each frame. To verify the validity of the proposed method the various synthesis of facial sequence image transformed from the text information is accomplished, and the system that can be applied the PC is implemented using the proposed method.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.243-253
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• 2003

This paper presents a new geometric morphing algorithm for polygons based on a simple geometric structure called direction map, which is mainly composed of a circular list of direction vectors defined by two neighboring vertices of a polygon. To generate a sequence of intermediate morphing shapes, first we merge direction maps of given control shapes based on a certain ordering rule of direction vectors, and scale the length of each direction vectors using Bezier or blossom controls. We show that the proposed algorithm is an improvement of the previous methods based on Minkowski sum (or convolution) in th aspects of computational efficiency and geometric properties.

• Journal of KIISE
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• v.43 no.3
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• pp.370-379
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• 2016

Recently personal media were produced in a variety of ways as a lot of smart devices have been spread and services using these data have been desired. Therefore, research has been actively conducted for the media analysis and recognition technology and we can recognize the meaningful object from the media. The system using the media ontology has the disadvantage that can't classify the media appearing in the video because of the use of a video title, tags, and script information. In this paper, we propose a system to automatically classify video using the objects shown in the media data. To do this, we use a description logic-based reasoning and a rule-based inference for event processing which may vary in order. Description logic-based reasoning system proposed in this paper represents the relation of the objects in the media as activity ontology. We describe how to another rule-based reasoning system defines an event according to the order of the inference activity and order based reasoning system automatically classify the appropriate event to the category. To evaluate the efficiency of the proposed approach, we conducted an experiment using the media data classified as a valid category by the analysis of the Youtube video.