• Journal of Multimedia Information System
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• v.6 no.2
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• pp.49-60
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• 2019

Plants are very crucial for life on Earth. There is a wide variety of plant species available, and the number is increasing every year. Species knowledge is a necessity of various groups of society like foresters, farmers, environmentalists, educators for different work areas. This makes species identification an interdisciplinary interest. This, however, requires expert knowledge and becomes a tedious and challenging task for the non-experts who have very little or no knowledge of the typical botanical terms. However, the advancements in the fields of machine learning and computer vision can help make this task comparatively easier. There is still not a system so developed that can identify all the plant species, but some efforts have been made. In this study, we also have made such an attempt. Plant identification usually involves four steps, i.e. image acquisition, pre-processing, feature extraction, and classification. In this study, images from Swedish leaf dataset have been used, which contains 1,125 images of 15 different species. This is followed by pre-processing using Gaussian filtering mechanism and then texture and color features have been extracted. Finally, classification has been done using Multiclass-support vector machine, which achieved accuracy of nearly 93.26%, which we aim to enhance further.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.726-736
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• 2007

In this paper, real-time image scanning system using linescan cameras is designed. The system is specially designed to diagnose and analyse the conditions of tunnels such as crack widths through the captured images. The system consists of two major parts, the image acquisition system and the image merging system. To save scanned image data into storage media in real-time, the image acquisition system has been designed with two different control and management modules. The control modules are in charge of controlling the hardware device and the management modules handle system resources so that the scanned images are safely saved to the magnetic storage devices. The system can be mounted to various kinds of vehicles. After taking images, the image merging system generates extended images by combining saved images. Several tests are conducted in laboratory as well as in the field. In the laboratory simulation, both systems are tested several times and upgraded. In the field-testing, the image acquisition system is mounted to a specially designed vehicle and images of the interior surface of the tunnel are captured. The system is successfully tested in a real tunnel with a vehicle at the speed of 20 km/h. The captured images of the tunnel condition including cracks are vivid enough for an expert to diagnose the state of the tunnel using images instead of seeing through his/her eyes.

• Journal of the Korea Society of Computer and Information
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• v.6 no.1
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• pp.14-24
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• 2001

The huge and complicated plants such as nuclear power stations are likely to cause the operators to make mistakes due to a variety of inexplicable reasons and symptoms in case of emergency. Thats why the prevention system assisting the operators is being developed for. First of all. I suggest an improved fuzzy diagnosis. Secondly. I want to demonstrate that a classification system of nuclear plants accident investigating the causes of accidents foresees possible problems. and maintains the reliability of the diagnostic reports in spite of improper working in part. In the event of emergency in a nuclear plant, a lot of operational steps enable the operators to find out what caused the problems based on an emergent operating plan. Our system is able to classify their types within twenty to thirty seconds. As so, we expect the system to put don the accidents right after the rapid detection of the damage control-method concerned.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2B
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• pp.129-137
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• 2003

Multimedia streams, like MPEG continuously retrieve multimedia data because of their incessant playback. While these streams need an efficient support of kernel, the current buffer cache mechanism of Linux kernel such as Unix operating system was designed apt for small files, which is aperiodically requested as well as time uncritical. But, in case of continuous media, the CPU must enormously copy memory from kernel address space to user address space. This must lead to a large CPU overhead. This overhead both degrades system throughput and cannot guarantee QOS. In this paper, we have designed and implemented two memory copy reduction schemes in Linux kernel, direct I/O and one copy. The direct I/O skips the buffer cache layer of Linux kernel and results in dramatic reduction of CPU memory copy overhead. And, the one copy provides a fast disk-to-network data path without copying to user address space. The experimental results show considerable reduction of CPU overhead and throughput improvements.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1182-1189
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• 2011

We named the system Visual Path Map which visualizes the distribution of clusters according to characteristics and entire process about exercise prescription, and we purpose to visualize a process according to exercise prescription. Visual Path Map visualizes the distribution of clusters according to characteristics, current and object distribution, and changed distribution for prescription. So it visualizes paths from current distribution to object distribution according to prescription. We used SOM in order to express properties along subjects in Visual Path map, and visualized distribution of clusters about physical characteristics, body mass index, and age information of 1,500 ordinary people. Also we visualize practical exercise prescription according to real data of expert of exercise prescription.

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.81-86
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• 2019

Deep learning is emerging as one of the best tool in processing data related to medical imaging. In our research work, we have proposed a deep learning based framework CNN (Convolutional Neural Network) for the classification of dysplastic tissue images. The CNN has classified the given images into 4 different classes namely normal tissue, mild dysplastic tissue, moderate dysplastic tissue and severe dysplastic tissue. The dataset under taken for the study consists of 672 tissue images of epithelial squamous layer of oral cavity captured out of the biopsy samples of 52 patients. After applying the data pre-processing and augmentation on the given dataset, 2688 images were created. Further, these 2688 images were classified into 4 categories with the help of expert Oral Pathologist. The classified data was supplied to the convolutional neural network for training and testing of the proposed framework. It has been observed that training data shows 91.65% accuracy whereas the testing data achieves 89.3% accuracy. The results produced by our proposed framework are also tested and validated by comparing the manual results produced by the medical experts working in this area.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.65-69
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• 2010

Moving Picture Expert Group(MPEG) is the organization foundedin 1998 to establish the standards for compressing and expressing the multimedia contents. The organization has established the technological standards such as MPEG-1, MPEG-2, MPEG-4 and MPEG-7. As the 3D video related standards, there is Multiview Profile which is included in the MPEG-2 video of 1996. However, as the MPEG-2 multiview profile is the standard for compressing the videos from two viewpoints on the object, it is not enough to meet the requirement of multiviewvideo technology. In addition, it does not have the technology on the viewpoint switching that it does not provide the services such as the user interaction. This paper proposes the structure in which the specific viewpoint can be described for video switching in addition to the current MPEG-4 system.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.91-107
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• 2003

In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform was implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based Inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which performed especially well in the areas of speed and stability.

• Journal of Intelligence and Information Systems
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• v.5 no.2
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• pp.29-42
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• 1999

현재 산업의 고도상장과 함께 주기적으로 고장을 진단하여야 하는 기기의 수와 종류도 급속도로 증가하고 있다. 이에 따라 여러 산업 분야에서 고장진단 시스템의 이용이 늘고 있는 추세이다. 이러한 고장진단 시스템은 경험적 고장진단 방식과 모델기반 고장 진단 방식으로 크게 나눌 수 있다. 경험적 고장진단 방식은 전문가가 경험한 사실의 범주에서는 신속하게 고장의 원인을 진단할 수 있지만 전문가가 경험하지 못했던 상황에 대해서는 융통성 있게 진단하지 못한다. 한편 기기의 물리적 기능적 지식을 기반으로 하는 모델기반 고장진단 방식을 변화하는 상황에 적절하게 대처하여 고장의 원인을 진단할 수 있다. 그러나 모델기반 고장진단 방식을 기기의 구조로부터 증상들을 추론하여 원인을 파악하므로 탐색 범위가 넓어 진단속도가 늦다는 단점이 있다. 본 연구에서는 이러한 경험적 고장진단 방식과 기기의 모델기반 고장진단 방식의 장점을 결합하여 신속하고 정확하게 고장진단을 할 수 있는 통합방식 고장진단 시스템을 제시한다. 통합방식 고장진단 시스템은 대상 기기의 진단 상태에 따라서 동적으로 적절한 진단 방식을 선택하기 위해서 블랙보드 추론기관을 이용한다. 또한 각 진단방식이 생성하는 가설 및 사실들을 효과적으로 통합하여 추론하기 위해서 제어지식을 정의하여 적용한다. 그리고 사용자와 진단 시스템간에 원활한 의사소통을 위해서 멀티미디어 기반 인터페이스를 채용하여 통합방식 진단 시스템을 구축한다.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.52-59
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• 2014

These days, smart card management system(SCMS) have been broadly used for security conformability, efficiency of issuance management, key management and expert management in the smart card market. SCMS is composed of card management, issuance management, key management, application management, and issuers management systems. SCMS enables card issuers from banks, credit card companies, and telecommunications companies to provide these cards to card users. And then SCMS enables card users to download new programs to chips for use of these cards successively and provide related smart card data in safety and efficiency. In this paper, we propose a framework for security assessment and an efficient method for security improvement through fault analysis which is more effective.