• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.204-209
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• 2023

Dynamic Bandwidth Allocation (DBA) methods in telecommunication network & systems have emerged with mechanisms for sharing limited resources in a rapidly growing number of users in today's access networks. Since the DBA research trends are incredibly fast-changing literature where almost every day new areas and terms continue to emerge. Co - citation analysis offers a significant support to researchers to distinguish intellectual bases and potentially leading edges of a specific field. We present the visualization based analysis for DBA algorithms in telecommunication field using mainstream co-citation analysis tool-CiteSpace and web of science (WoS) analysis. Research records for the period of decade (2009-2018) for this analysis are sought from WoS. The visualization results identify the most influential DBA algorithms research studies, journals, major countries, institutions, and researchers, and indicate the intellectual bases and focus entirely on DBA algorithms in the literature, offering guidance to interested researchers on more study of DBA algorithms.

• 한국가시화정보학회지
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• 제22권2호
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• pp.27-34
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• 2024

In this study, we propose a novel approach for rapid and accurate pathogen detection by integrating Polydiacetylene (PDA) hydrogel sensors with advanced deep learning algorithms and visualization techniques. PDA hydrogel sensors exhibit a color transition in the presence of pathogens, enabling straightforward and quick pathogen detection. We developed a reliable pathogen detection system that combines deep neural network algorithms with color quantification technology for image-based analysis. This image-based system retains the ease of pathogen detection offered by PDA sensors while deriving quantified color standards to overcome the limitations of human visual assessment, enhancing reliability. This advancement contributes to public health and the development and application of pathogen detection technology.

• 한국정보통신학회논문지
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• 제26권4호
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• pp.624-632
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• 2022

인물관계망이나 네비게이션의 경로 탐색과 같은 관계망은 그래프 형태로 표현할 수 있다. 하지만 데이터 양이 많아지면서 한 화면에 표현할 때 원하는 데이터 탐색이 어려운 문제가 있다. 본 논문에서는 많은 노드를 갖는 인물관계망을 표현하기 위해 그래프를 사용해 인물의 검색, 인물 사이의 최단 경로 검색 및 탐색 결과에 대한 시각화 방법을 제시한다. 라우팅 테이블에서의 최단 경로와 달리 인물관계망에서의 최단 경로는, 분석하는 사용자의 의도나 관계의 중요도에 따라 변경 가능해야 한다. 이를 위해 인물관계망의 특성을 적용하기 위해 너비우선탐색 알고리즘을 변형하였다. 결과 검증을 위해, 한국고전번역원의 한국고전종합DB 인물관계정보에 있는 데이터를 활용하였다.

• 한국HCI학회논문지
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• 제5권2호
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• pp.7-14
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• 2010

센서 네트워크에 의해 수집되는 다양한 도시 데이터는 도시를 이해하고 분석하는데 있어서 필수적인 수단으로 자리매김하고 있다. 특히 Ubiquitous Sensor Network(USN) 기술들은 u-City 구현에 있어 중추신경망을 제공하였다. 이 연구는 도시 에너지의 사용량에 관한 정보를 USN을 이용하여 수집하고, 이를 도시공간정보와 연계된 직관적 가시화 환경을 통해 제공함으로써 u-City에서 에너지 공급계획을 수립, 모니터링하고, 궁극적으로 실사용자가 능동적으로 에너지를 절약할 수 있도록 도와주는 애플리케이션 구현을 목적으로 한다. 특히 3차원 지리정보환경의 층위에 다층적인 에너지 모니터링 정보를 동적으로 조합하면서 다양한 사용자의 관점에 대응하는 환경을 제시하였다. 또한 도시공간정보에 기반을 둔 논리적 LOD를 제공함으로써 효과적인 실시간 에너지 사용 모니터링 도구를 제공한다. 이를 위하여 관련 선행연구를 분석하여 어플리케이션 구현을 위한 시스템의 개념과 구성을 정의하고 데이터 구조 및 가시화방안을 구체화하였다. 본 논문에서는 특히 시스템 구현에 요구되는 공간정보, E-GIS 데이터, 에너지 사용량 센서 데이터를 효과적으로 조합하는 가시화 방법론, 직관적 표현방법, 데이터 구조 및 어플리케이션의 연구결과를 제시하고 Social Sensor Networking을 이용한 모니터링 확장 적용방안에 대해 연구한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.323-327
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• 2006

During the past decades in South Korea, there have been several projects to reduce water demand and save water for paddy irrigation system by automation. This is called as intensive water management system by telemetering of paddy ponding depth and canal water level and telecontrol of water supply facilities. This study suggests a method of constructing topology-based irrigation network system using GIS tools. For the network modeling, a typical agricultural watershed included reservoirs, irrigation and drainage canals, pumping stations was selected. ArcHydro tools composed of edge, junction, waterbody and watershed were used to construct hydro-network. ArcHydro Model was then designed and the network was successfully built using the HydroID. Visualization using ArcHydro tools could display table property of each object. ArcHydro Model was linked to Agricultural Water Demamd and Supply Estimation System (AWDS) which developed by Korea Rural Community and Agriculture Corporation (KRC) to extract information of the study area. And menu of supply facilities information, demand analysis and supply analysis constructed for information acquisition and visualization of acquired informations.

• 한국가시화정보학회지
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• 제20권2호
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• pp.78-85
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• 2022

In these days, the rapid development in prediction technology using artificial intelligent is being applied in a variety of engineering fields. Especially, dimensionality reduction technologies such as autoencoder and convolutional neural network have enabled the classification and regression of high-dimensional data. In particular, pixel level prediction technology enables semantic segmentation (fine-grained classification), or physical value prediction for each pixel such as depth or surface normal estimation. In this study, the pressure distribution of the ship's surface was estimated at the pixel level based on the artificial neural network. First, a potential flow analysis was performed on the hull form data generated by transforming the baseline hull form data to construct 429 datasets for learning. Thereafter, a neural network with a U-shape structure was configured to learn the pressure value at the node position of the pretreated hull form. As a result, for the hull form included in training set, it was confirmed that the neural network can make a good prediction for pressure distribution. But in case of container ship, which is not included and have different characteristics, the network couldn't give a reasonable result.

• 한국가시화정보학회지
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• 제21권1호
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 2부
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• pp.424-431
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• 2007

본 연구는 관계망 시각화에 이용되는 데이터의 특성을 분석하고 그에 맞는 시각화 요소를 추출하여 시각화하는 것에 관한 연구이다. 사회 관계망 시각화는 점과 선을 기초 요소로 하여 점은 사회적 요소(actor), 선은 관계(relation)를 의미한다, 점과 선은 시각화에 사용되는 데이터의 특성에 따라 다양한 형태를 갖게 된다. 이 논문에서는 관계망 시각화에 사용되는 데이터의 특성을 데이터의 형태, 관계, 상태에 따라 분류하고, 각각의 특성에 맞는 관계망 시각화의 형태를 추출하고, 그에 따른 시각화 요소를 추출하였다. 이를 바탕으로 모바일 커뮤니케이션을 통해 형성되는 인맥 네트워크를 시각화함으로써, 인맥 네트워크 구성원 간의 친밀도를 효과적으로 파악할 수 있는 방법에 대해 제시하였다. 또한, 시각화의 결과를 이용하여 휴대전화로 인맥 네트워크를 유지, 관리하기 위한 서비스를 제안하였다. 이러한 연구는 데이터의 특성에 맞는 시각화의 요소를 추출하고, 데이터의 형태, 관계, 상태를 직관적으로 제공함으로써 사용자로 하여금 자신의 인맥 네트워크 구성원들의 친밀도와 관계 형태, 상태를 파악하여 자신의 인맥을 유지, 관리하고 보수할 수 있도록 한다.

• Industrial Engineering and Management Systems
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• 제10권4호
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• pp.238-246
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• 2011

Given a directed graph, we can determine how the user's preference moves from one product item to another. In this graph called "preference transition network", each node represents the product item while its edge pointing to the other nodes represents the transition of user's preference. However, with the large number of items make the network become more complex, unclear and difficult to be interpreted. In order to address this problem, this paper proposes a visualization technique in preference transition analysis based on recency and frequency. By adapting these two elements, the semantic meaning of each item and its transition can be clearly identified by its different types of node size, color and edge style. The experiment in a sales data has shown the results of the proposed approach.

• 한국가시화정보학회지
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• 제19권1호
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• pp.57-61
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• 2021

In order to determine erythrocyte sedimentation rate (ESR) indicating acute phase inflammation, a Westergren method has been widely used because it is cheap and easy to be implemented. However, the Westergren method requires quite a long time for 1 hour. In this study, a gated recurrent unit (GRU) neural network was used to reduce measurement time of ESR evaluation. The sedimentation sequences of the erythrocytes were acquired by the camera and data processed through image processing were used as an input data into the neural network models. The performance of a proposed models was evaluated based on mean absolute error. The results show that GRU model provides best accurate prediction than others within 30 minutes.