• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.194-202
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• 1998

This paper describes a hardware implementation method of a Petri Net-based controller. A flexible and systematic implementation method, based on look-up tables, is suggested, which enables to build high speed Petri net-based controllers. The suggested method overcomes the inherent speed limit that arises from the microprocessors by using of matrix-based look-up tables. Based on the matrix framework, this paper suggests various specific data path structures as well as a basic data path structure, accompanied by evolution algorithms, for sub-class Petri nets. A new sub-class Petri net, named Biarced Petri Net, resolves memory explosion problem that usually comes with matrix-based look-up tables. The suggested matrix-based method based on the Biarced Petri net has as good efficiency and expendability as the list-based methods. This paper shows the usefulness of the suggested method, evaluating the size of the look-up tables and introducing an architecture of the signal processing unit of a programmable controller. The suggested implementation method is supported by an automatic design support program.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.451-452
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• 2023

최근 CNN 이 다양한 산업에 확산되고 있으며, IoT 기기 및 엣지 컴퓨팅에 적합한 경량 모델에 대한 연구가 급증하고 있다. 본 논문에서는 CNN 모델의 파라미터 비트 연산을 위한 자동화 프레임워크를 제안하고, 파라미터 비트와 모델 정확도 사이의 관계를 실험 및 연구한다. 제안된 프레임워크는 하위 n- bit 를 0 으로 설정하여 정보 손실 발생시킴으로써 ImageNet 데이터셋으로 사전 학습된 CNN 모델의 파라미터와 정확도의 강인성을 비트 단위로 체계적으로 실험할 수 있다. 우리는 비트 연산을 수행한 파라미터로 InceptionV3, InceptionResnetV2, ResNet50, Xception, DenseNet121, MobileNetV1, MobileNetV2 모델의 정확도를 평가한다. 실험 결과는 성능이 낮은 모델일수록 파라미터와 정확도 간의 강인성이 높아 성능이 좋은 모델보다 정확도를 유지하는 비트 수가 적다는 것을 보여준다.

• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.326-334
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• 2024

Extra-oral imaging techniques such as Panoramic X-rays (PXs) and Cone Beam Computed Tomography (CBCT) are the most preferred imaging modalities in dental clinics owing to its patient convenience during imaging as well as their ability to visualize entire teeth information. PXs are preferred for routine clinical treatments and CBCTs for complex surgeries and implant treatments. However, PXs are limited by the lack of third dimensional spatial information whereas CBCTs inflict high radiation exposure to patient. When a PX is already available, it is beneficial to reconstruct the 3D oral structure from the PX to avoid further expenses and radiation dose. In this paper, we propose 3DentAI - an U-Net based deep learning framework for 3D reconstruction of oral structure from a PX image. Our framework consists of three module - a reconstruction module based on attention U-Net for estimating depth from a PX image, a realignment module for aligning the predicted flattened volume to the shape of jaw using a predefined focal trough and ray data, and lastly a refinement module based on 3D U-Net for interpolating the missing information to obtain a smooth representation of oral cavity. Synthetic PXs obtained from CBCT by ray tracing and rendering were used to train the networks without the need of paired PX and CBCT datasets. Our method, trained and tested on a diverse datasets of 600 patients, achieved superior performance to GAN-based models even with low computational complexity.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.11a
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• pp.157-162
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• 2002

A distributed simulation with HLA/RTI provides stable and satisfactory results. In this study, a distributed simulation of Petri net models under the HLA/RTI framework is considered. Throughout our experiences, it is recognized that the proper use of interface specification and time management services are important in order to achieve successful implementation of RTI. The interfacing tokens that are delivered to other models are distinguished as information entity and physical entity. Both entities are modeled as Interaction Class in order to send and receive messages. In synchronizing local simulation clocks, a conservative method with NERA service is considered. A eel manufacturing system is modeled and implemented with RTI to illustrate the distributed simulation of Petri net models.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.59-59
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• 2000

In this paper, we present a framework for modeling and control of multiple mobile robots which cowork within a bounded workspace and limited resources. To achieve this goal, we adopt a formalism of discrete event system and supervisory control theory based on Petri nets. We can divide our whole story into two parts: first, we search the shortest path using the distance vector algorithm, and then we construct the control scheme from which a number of mobile robots can work within a bounded workspace without any collision. The use of Petri net modeling allows us In synthesize a controller which achieves a control specification for the desired closed-loop behavior efficiently. Finally, the usefulness of the proposed Petri net formalism is illustrated by a simulation study.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.43-49
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• 2020

In this paper, we propose a stage-wise knowledge transfer method that uses block-wise retraining to transfer the useful knowledge of a pre-trained residual network (ResNet) in a teacher-student framework (TSF). First, multiple hint information transfer and block-wise supervised retraining of the information was alternatively performed between teacher and student ResNet models. Next, Softened output information-based knowledge transfer was additionally considered in the TSF. The results experimentally showed that the proposed method using multiple hint-based bottom-up knowledge transfer coupled with incremental block-wise retraining provided the improved student ResNet with higher accuracy than existing KD and hint-based knowledge transfer methods considered in this study.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.324-330
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• 2021

Agriculture is one of the essential needs of human life on planet Earth. It is the source of food and earnings for many individuals around the world. The economy of many countries is associated with the agriculture sector. Lots of diseases exist that attack various fruits and crops. Apple Tree Leaves also suffer different types of pathological conditions that affect their production. These pathological conditions include apple scab, cedar apple rust, or multiple diseases, etc. In this paper, an automatic detection framework based on deep learning is investigated for apple leaves disease classification. Different pre-trained models, VGG16, ResNetV2, InceptionV3, and MobileNetV2, are considered for transfer learning. A combination of parameters like learning rate, batch size, and optimizer is analyzed, and the best combination of ResNetV2 with Adam optimizer provided the best classification accuracy of 94%.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1385-1388
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• 2007

현재 학교에서 이루어지고 있는 수업의 문제점 중의 하나는 교수자가 학습자의 이해 및 요구사항을 정확히 파악하지 못한 채 일반적인 강의형식으로 수업이 진행된다는 것이다. 학습자들은 면대면에서 오는 두려움으로 인하여 적극적으로 수업에 참여하지 못하고 이로 인하여 교수자는 학습자들의 이해와 생각을 파악하지 못한 채 단순 지식전달 형태의 수업이 진행되며, 이로 인하여 학습자는 학습목표 달성에 어려움을 겪는 악순환이 발생되고 있는 것이다. 이에 본 연구에서는 단순하면서도 효과적으로 학생들의 수업참여를 유도할 수 있도록 하고 교수자가 학습자의 생각과 의견을 한눈에 파악할 수 있는 기능을 기본으로 하는 수업 보조도구를 설계 및 구현하였다. 양질의 솔루션을 제공하고 추후 확장성 및 시스템의 활성화를 고려하여.Net Framework2.0 기반으로 개발 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.368-373
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• 2005

This paper presents a new framework for the traffic flow control based on integrated model descriptions as the Hybrid Dynamical System (HDS).

• Journal of the Korean Society of Systems Engineering
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• v.13 no.2
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• pp.65-74
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• 2017

Supercritical carbon dioxide power system is the next generation electricity technology expected to be highly developed. The power system can improve net efficiency, simplify cycle configuration, and downsize equipment compared to conventional steam power system. In order to dominate the new market in advance, it is required to found Front End Engineering Design (FEED) Framework of the system. Therefore, this study developed the FEED framework including design processes for the supercritical carbon dioxide power system, information elements for each process, and relationships for each element. The developed FEED framework is expected to be able to secure systematic technological capabilities by establishing a common understanding and perspective among multi-field engineers participating in the design.