• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.384-389
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• 2005

The objective on this project is to develop a cooperative Field Robot (FR), by using a customize Open Control Platform (OCP) as design and development process. An OCP is a CORBA-based solution for networked control system, which facilitates the transitioning of control designs to embedded targets. In order to achieve the cooperation surveillance system, two FRs are distributed by navigation messages (GPS and sensor data) using CORBA event-channel communication, while graphical information from IR night vision camera is distributed using CORBA Asynchronous Method Invocation (AMI). The QoS features of AMI in the network are to provide the additional delivery method for distributing an IR camera Images will be evaluate in this experiment. In this paper also presents an empirical performance evaluation from the variable chunk sizes were compared with the number of clients and message latency, some of the measurement data's are summarized in the following paragraph. In the AMI buffers size measurement, when the chuck sizes were change, the message latency is significantly change according to it frame size. The smaller frame size between 256 bytes to 512 bytes is more efficient fur the message size below 2Mbytes, but it average performance in the large of message size a bigger frame size is more efficient. For the several destination, the same experiment using 512 bytes to 2 Mbytes frame with 2 to 5 destinations are presented. For the message size bigger than 2Mbytes, the AMI are still able to meet requirement far more than 5 clients simultaneously.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.218-220
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• 2014

빅데이터가 새로운 가치창출과 문제해결의 핵심 엔진이 되는 데이터 중심 시대가 본격적으로 시작되고 있다. 본 연구는 빅데이터를 활용한 새로운 정보화 추진 방향과 대응 전략을 모색하는 것을 목표로 수행되었다. 이를 위해 사회 패러다임의 변화와 IT의 새로운 역할, 오픈 플랫폼화와 빅데이터, 빅데이터의 잠재력과 가능성 등을 연계해서 논의함으로써 빅데이터가 새로운 가치창출의 핵심 엔진임을 분석하였다. 그리고 이러한 분석 결과를 바탕으로 빅데이터 시대에 대응해서 국가 차원의 성공적인 미래를 만들어가기 위한 구체적인 전략 방향을 제시하였다. 구체적으로는 전략방향의 지향점, 초기 촉진책, 지속 가능 메커니즘이라는 3가지 전략적 질문에 대한 해답을 각각 도출하고자 하였다. 그 결과 빅데이터에 관한 국가 차원의 지향점으로서 '데이터 분석기반 창조 강국'을 국가 차원의 빅데이터 분석 활용의 촉진제로서 빅데이터를 활용한 스마트 정부 구현'을 지속 가능한 성공 메커니즘 창출의 대표적인 추진 전략으로서 '빅데이터 협력 거버넌스' 전략을 각각 식별하고 그 구체적인 방안을 제시하였다.

• 과학기술학연구
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• 제19권2호
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• pp.85-116
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• 2019

이 연구에서는 새롭게 등장하고 있는 전환적 혁신정책의 특성을 살펴보고 그것에 입각해서 한국 사회문제 해결형 R&D정책을 분석한다. 전환적 혁신정책은 사회적 도전과제 해결을 위해 사회 기술시스템 전환을 지향하는 정책이다. 이 연구에서는 전환적 혁신정책론의 틀에서 '제2차 과학기술기반 사회문제 해결 종합계획'을 분석했다. '종합계획'에서는 사회적 가치의 강조, 관련 주체들의 네트워크 형성, 사회적 성과 확산 등 과학기술혁신 활동의 새로운 방향성을 설정하고 관련 생태계를 형성하려는 노력을 하고 있다. 이렇게 '종합계획'에서는 과학기술혁신에서 사회 기술혁신까지 시야를 확대하고 있지만 사회 기술시스템 전체를 조망하면서 시스템 전환을 지향하는 관점은 약하다. 이 때문에 '종합계획'은 기존 시스템에 새로운 요소를 부가하는 시스템 개선을 이야기하고 있지 시스템 전환을 논의하고 있지는 않다. 전환적 혁신정책의 관점에서 사회문제 해결형 R&D정책을 발전시키기 위해서는 사회 기술시스템 전환에 대한 비전과 전망을 구성하는 것이 최우선적으로 요구된다.

• Journal of Korean Neurosurgical Society
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• 제65권4호
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• pp.572-581
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• 2022

Objective : Compared to microscopes, exoscopes have advantages in field-depth, ergonomics, and educational value. Exoscopes are especially well-poised for adaptation into fluorescence-guided surgery (FGS) due to their excitation source, light path, and image processing capabilities. We evaluated the feasibility of near-infrared FGS using a 3-dimensional (3D), 4 K exoscope with near-infrared fluorescence imaging capability. We then compared it to the most sensitive, commercially-available near-infrared exoscope system (3D and 960 p). In-vitro and intraoperative comparisons were performed. Methods : Serial dilutions of indocyanine-green (1-2000 ㎍/mL) were imaged with the 3D, 4 K Olympus Orbeye (system 1) and the 3D, 960 p VisionSense Iridium (system 2). Near-infrared sensitivity was calculated using signal-to-background ratios (SBRs). In addition, three patients with brain tumors were administered indocyanine-green and imaged with system 1, with two also imaged with system 2 for comparison. Results : Systems 1 and 2 detected near-infrared fluorescence from indocyanine green concentrations of >250 ㎍/L and >31.3 ㎍/L, respectively. Intraoperatively, system 1 visualized strong near-infrared fluorescence from two, strongly gadolinium-enhancing meningiomas (SBR=2.4, 1.7). The high-resolution, bright images were sufficient for the surgeon to appreciate the underlying anatomy in the near-infrared mode. However, system 1 was not able to visualize fluorescence from a weakly-enhancing intraparenchymal metastasis. In contrast, system 2 successfully visualized both the meningioma and the metastasis but lacked high resolution stereopsis. Conclusion : Three-dimensional exoscope systems provide an alternative visualization platform for both standard microsurgery and near-infrared fluorescent guided surgery. However, when tumor fluorescence is weak (i.e., low fluorophore uptake, deep tumors), highly sensitive near-infrared visualization systems may be required.

• 예술경영연구
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• 제54호
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• pp.133-153
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• 2020

2019ICOM교토에서 새로운 박물관 정의의 채택 투표가 진행되었다. 문화적 담론으로의 새로운 박물관과 관련한 논의가 이루어지고 있었던 것에 힘입어 ICOM은 2015년 실무위원 구성을 중심으로 MDPP를 창설하고 새로운 박물관 정의를 제안했다. 본 연구는 박물관경영 차원에서 정의의 결정을 앞두고 논의 전개와 쟁점을 살펴보아 공론화하고자 하였다. 박물관 정의는 제트 샌달의 주도로 제안되었으며, 정의 채택에 대한 찬반 의견을 통해 각 국가들의 박물관 경영 전략이 의사결정에 전제되었음을 살펴보았다. 새로운 정의를 받아들일 충분한 논의와 준비의 필요 또한 확인하였다. 연구는 새로운 정의가 채택되면 대응차원에서 박물관이 직면하게 될 경영상 문제를 살펴보았다. 박물관 경영 비전과, 실행, 콘텐츠, 타겟 등의 경영 요소를 분류하고, 발생할 문제들을 예측하였다. 또한 뒤따를 제도적 법적 변화와, 예측을 통해 대비의 필요성을 제기하였다. 본 연구는 오늘날 박물관이 나아가고자 하는 방향성을 이해하고, 대응하기 위한 논의의 시발점으로 그 의미가 있다.

• International Journal of Contents
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• 제18권2호
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• pp.47-57
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• 2022

e-Learning content can be defined as digital content to achieve educational goals. Since it is an educational material that can be distributed in offline, online, and mobile environments, it is important to create content that meets the learner's education environment and educational goals. In particular, if the learner is a public official, the vision, philosophy, and characteristics of each local government must reflect. As non-face-to-face online education expands further due to the COVID-19 pandemic, local governments that have relied on onsite education in the past urgently require developing strong basic competency education and special task competency content that reflect regional characteristics. Such e-learning content, however, hardly exists and the ability to independently develop them is also insufficient. In this circumstance, this case study describes the process of self-production of e-learning content suitable for Busan's characteristics by the Human Resource Development (HRD) Institute of Busan City, a local government. The field of instructional design and instructional technology is always evolving and growing by blending technological innovation into instructional platform design and adapting to the changes in society. Busan HRD Institute (BHI), therefore, tried to implement blended learning by developing content that reflected the recent trend of micro-learning in e-learning through a detailed analysis. For this, an e-learning content developer with certain requirements was selected and contracted, and the process of developing content through a collaboration between the client and developer was described in this study according to the ADDIE model of Instructional Systems Development (ISD).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.89-89
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• 2022

Soybean (Glycine max (L.) Merr.) is a representative food resource. To preserve the integrity of soybean, it is necessary to protect soybean yield and seed quality from threats of various pests and diseases. Riptortus pedestris is a well-known insect pest that causes the greatest loss of soybean yield in South Korea. This pest not only directly reduces yields but also causes disorders and diseases in plant growth. Unfortunately, no resistant soybean resources have been reported. Therefore, it is necessary to identify the distribution and movement of Riptortus pedestris at an early stage to reduce the damage caused by insect pests. Conventionally, the human eye has performed the diagnosis of agronomic traits related to pest outbreaks. However, due to human vision's subjectivity and impermanence, it is time-consuming, requires the assistance of specialists, and is labor-intensive. Therefore, the responses and behavior patterns of Riptortus pedestris to the scent of mixture R were visualized with a 3D model through the perspective of artificial intelligence. The movement patterns of Riptortus pedestris was analyzed by using time-series image data. In addition, classification was performed through visual analysis based on a deep learning model. In the object tracking, implemented using the YOLO series model, the path of the movement of pests shows a negative reaction to a mixture Rina video scene. As a result of 3D modeling using the x, y, and z-axis of the tracked objects, 80% of the subjects showed behavioral patterns consistent with the treatment of mixture R. In addition, these studies are being conducted in the soybean field and it will be possible to preserve the yield of soybeans through the application of a pest control platform to the early stage of soybeans.

• 한국컴퓨터정보학회논문지
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• 제28권12호
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• pp.67-77
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• 2023

본 연구는 스마트팜 환경에서 진행된 혁신적인 연구로, 딥러닝을 기반으로 한 질병 및 해충 탐지 모델을 개발하고, 이를 지능형 사물인터넷(IoT) 플랫폼에 적용하여 디지털 농업 환경 구현의 새로운 가능성을 탐색하였다. 연구의 핵심은 Pseudo-Labeling, RegNet, EfficientNet 등 최신 ImageNet 모델과 전처리 방식을 통합하여, 복잡한 농업 환경에서 다양한 질병과 해충을 높은 정확도로 탐지하는 것이었다. 이를 위해 앙상블 학습 기법을 적용하여 모델의 정확도와 안정성을 극대화했으며, 평균 정밀도(mAP), 정밀도, 재현율, 정확도, 박스 손실 등의 다양한 성능 지표를 통해 모델을 평가하였다. 또한, SHAP 프레임워크를 활용하여 모델의 예측 기준에 대한 깊은 이해를 도모하였고, 이를 통해 모델의 결정 과정을 보다 투명하게 만들었다. 이러한 분석은 모델이 어떻게 다양한 변수들을 고려하여 질병 및 해충을 탐지하는지에 대한 중요한 통찰력을 제공하였다.

• 로봇학회논문지
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• 제19권3호
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• pp.293-310
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• 2024

In this paper, we propose an agent model for Language-Driven Zero-Shot Object Navigation (L-ZSON) tasks, which takes in a freeform language description of an unseen target object and navigates to find out the target object in an inexperienced environment. In general, an L-ZSON agent should able to visually ground the target object by understanding the freeform language description of it and recognizing the corresponding visual object in camera images. Moreover, the L-ZSON agent should be also able to build a rich spatial context map over the unknown environment and decide efficient exploration actions based on the map until the target object is present in the field of view. To address these challenging issues, we proposes AML (Agent Model for L-ZSON), a novel L-ZSON agent model to make effective use of AI foundation models such as Large Language Model (LLM) and Vision-Language model (VLM). In order to tackle the visual grounding issue of the target object description, our agent model employs GLEE, a VLM pretrained for locating and identifying arbitrary objects in images and videos in the open world scenario. To meet the exploration policy issue, the proposed agent model leverages the commonsense knowledge of LLM to make sequential navigational decisions. By conducting various quantitative and qualitative experiments with RoboTHOR, the 3D simulation platform and PASTURE, the L-ZSON benchmark dataset, we show the superior performance of the proposed agent model.