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Video Retrieval System supporting Adaptive Streaming Service (적응형 스트리밍 서비스를 지원하는 비디오 검색 시스템)

  • 이윤채;전형수;장옥배
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.1
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    • pp.1-12
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    • 2003
  • Recently, many researches into distributed processing on Internet, and multimedia data processing have been performed. Rapid and convenient multimedia services supplied with high quality and high speed are to be needed. In this paper, we design and implement clip-based video retrieval system on the Web enviroment in real-time. Our system consists of the content-based indexing system supporting convenient services for video content providers, and the Web-based retrieval system in order to make it easy and various information retrieval for users in the Web. Three important methods are used in the content-based indexing system, key frame extracting method by dividing video data, clip file creation method by clustering related information, and video database construction method by using clip unit. In Web-based retrieval system, retrieval method ny using a key word, two dimension browsing method of key frame, and real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time retrieval for video clips on Web environment and provides the multimedia service in stability. The proposed methods show a usefulness of video content providing, and provide an easy method for serching intented video content.

A research on the emotion classification and precision improvement of EEG(Electroencephalogram) data using machine learning algorithm (기계학습 알고리즘에 기반한 뇌파 데이터의 감정분류 및 정확도 향상에 관한 연구)

  • Lee, Hyunju;Shin, Dongil;Shin, Dongkyoo
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.27-36
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    • 2019
  • In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

A Study on the System for AI Service Production (인공지능 서비스 운영을 위한 시스템 측면에서의 연구)

  • Hong, Yong-Geun
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.10
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    • pp.323-332
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    • 2022
  • As various services using AI technology are being developed, much attention is being paid to AI service production. Recently, AI technology is acknowledged as one of ICT services, a lot of research is being conducted for general-purpose AI service production. In this paper, I describe the research results in terms of systems for AI service production, focusing on the distribution and production of machine learning models, which are the final steps of general machine learning development procedures. Three different Ubuntu systems were built, and experiments were conducted on the system, using data from 2017 validation COCO dataset in combination of different AI models (RFCN, SSD-Mobilenet) and different communication methods (gRPC, REST) to request and perform AI services through Tensorflow serving. Through various experiments, it was found that the type of AI model has a greater influence on AI service inference time than AI machine communication method, and in the case of object detection AI service, the number and complexity of objects in the image are more affected than the file size of the image to be detected. In addition, it was confirmed that if the AI service is performed remotely rather than locally, even if it is a machine with good performance, it takes more time to infer the AI service than if it is performed locally. Through the results of this study, it is expected that system design suitable for service goals, AI model development, and efficient AI service production will be possible.

Visualization and Localization of Fusion Image Using VRML for Three-dimensional Modeling of Epileptic Seizure Focus (VRML을 이용한 융합 영상에서 간질환자 발작 진원지의 3차원적 가시화와 위치 측정 구현)

  • 이상호;김동현;유선국;정해조;윤미진;손혜경;강원석;이종두;김희중
    • Progress in Medical Physics
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    • v.14 no.1
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    • pp.34-42
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    • 2003
  • In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

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Usability Testing of Open Source Software for Digital Archiving (디지털 아카이브 구축을 위한 공개 소프트웨어 사용성 평가)

  • Jeon, Kyungsun;Chang, Yunkeum
    • Journal of the Korean Society for Library and Information Science
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    • v.52 no.3
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    • pp.247-271
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    • 2018
  • This research aims to explore the possibility of open source software for creating digital archives of small organizations or ordinary people that run short of budget and professional workforce and may easily create digital archives without the help of a professional. To do so, this study suggested three open source software, AtoM, ArchivesSpace, and Omeka, for such use, and conducted usability tests with system designers and users who had no experience with open source software. The results of the usability testing was that AtoM, which was developed to support the records management system and user services of small organizations, proved satisfactory to both system designers and users. ArchivesSpace had too many required fields with it to create archives. Omeka greatly satisfied the system designers because it is possible to create archives with simple inputs on the item level. However, Omeka, which focuses on exhibition functions while neglecting search functions, registered low satisfaction among the users. Based on the results of the usability testing, this study suggested selection criteria of open source software for small organizations or ordinary individuals, namely, purposes, license, characteristics, service creation environment, advantages and disadvantages, functions, metadata, file type, and interoperability.

Parallel Processing of k-Means Clustering Algorithm for Unsupervised Classification of Large Satellite Images: A Hybrid Method Using Multicores and a PC-Cluster (대용량 위성영상의 무감독 분류를 위한 k-Means Clustering 알고리즘의 병렬처리: 다중코어와 PC-Cluster를 이용한 Hybrid 방식)

  • Han, Soohee;Song, Jeong Heon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.6
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    • pp.445-452
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    • 2019
  • In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

A Study on Improving the Billing System of the Wireless Internet Service (무선인터넷 서비스의 과금체계 개선에 관한 연구)

  • Min Gyeongju;Hong Jaehwan;Nam Sangsig;Kim Jeongho
    • The KIPS Transactions:PartC
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    • v.12C no.4 s.100
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    • pp.597-602
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    • 2005
  • In this study, file size for measurement and the service system's billing data were submitted to a comparative analysis by performing a verification test on the billing system of three major mobile communication services providers, based on the wireless Internet service packet. As shown in the result of the verification test, there were some differences in the billing data due to transmission overhead, according to the network quality that is affected by the wireless environment of mobile operators. Consequently, the packet analysis system was proposed as a means of applying consistent packet billing to all service providers being compared. If the packet analysis system is added to supplement the current billing system various user requirements can be met. Billing by Packet among mobile operators and differentiated billing based on the content value are available, since the packet data can be extracted through protocol analysis by service, and it can be classified by content tape through traffic data analysis. Furthermore, customer's needs can be satisfied who request more information on the detailed usage, and more flexible and diverse billing policies can be supported like application of charging conditions to the non-charging packet handling. All these services are expected to contribute to the popularization of the wireless Internet service, since user complaints about the service charge could be reduced.

A Study on the Effects of BIM Adoption and Methods of Implementationin Landscape Architecture through an Analysis of Overseas Cases (해외사례 분석을 통한 조경분야에서의 BIM 도입효과 및 실행방법에 관한 연구)

  • Kim, Bok-Young;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.45 no.1
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    • pp.52-62
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    • 2017
  • Overseas landscape practices have already benefited from the awareness of BIM while landscape-related organizations are encouraging its use and the number of landscape projects using BIM is increasing. However, since BIM has not yet been introduced in the domestic field, this study investigated and analyzed overseas landscape projects and discussed the positive effects and implementation of BIM. For this purpose, landscape projects were selected to show three effects of BIM: improvement of design work efficiency, building of a platform for cooperation, and performance of topography design. These three projects were analyzed across four aspects of implementation methods: landscape information, 3D modeling, interoperability, and visualization uses of BIM. First, in terms of landscape information, a variety of building information was constructed in the form of 3D libraries or 2D CAD format from detailed landscape elements to infrastructure. Second, for 3D modeling, a landscape space including simple terrain and trees was modeled with Revit while elaborate and complex terrain was modeled with Maya, a professional 3D modeling tool. One integrated model was produced by periodically exchanging, reviewing, and finally combining each model from interdisciplinary fields. Third, interoperability of data from different fields was achieved through the unification of file formats, conversion of differing formats, or compliance with information standards. Lastly, visualized 3D models helped coordination among project partners, approval of design, and promotion through public media. Reviewing of the case studies shows that BIM functions as a process to improve work efficiency and interdisciplinary collaboration, rather than simply as a design tool. It has also verified that landscape architects could play an important role in integrated projects using BIM. Just as the introduction of BIM into the architecture, engineering and construction industries saw great benefits and opportunities, BIM should also be introduced to landscape architecture.