• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.465-472
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• 2017

In the past, researchers mainly used the supervised learning technique of machine learning to analyze power data and investigated the identification of patterns through the data mining technique. Data analysis research, however, faces its limitations with the old data classification and analysis techniques today when the size of electric power data has increased with the possible real-time provision of data. This study thus set out to propose a clustering architecture to analyze large-sized electric power data. The clustering process proposed in the study supplements the K-means algorithm, an unsupervised learning technique, for its problems and is capable of automating the entire process from the collection of electric power data to their analysis. In the present study, power data were categorized and analyzed in total three levels, which include the row data level, clustering level, and user interface level. In addition, the investigator identified K, the ideal number of clusters, based on principal component analysis and normal distribution and proposed an altered K-means algorithm to reduce data that would be categorized as ideal points in order to increase the efficiency of clustering.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.197-204
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• 2010

An effective integration of web-based learning environment and mobile device technology is considered as a new challenge to the developers. The screen size, however, of the mobile device is too small, and its performance is too inferior. Due to the foregoing limit of mobile technology, displaying bulk data on the mobile screen, such as a cyber lecture accompanied with real-time image transmission on the web, raises a lot of problems. Users have difficulty in recognizing learning contents exactly by means of a mobile device, and continuous transmission of video stream with bulky information to the mobile device arouses a lot of load for the mobile system. Thus, an application which is developed to be applied in PC is improper to be used for the mobile device as it is, a player which is fitting for the mobile device should be developed. Accordingly, this paper suggests mobile presentation using transcoding techniques of the field concerned. To display continuous video frames of learning image, such as a cyber lecture or remote lecture, by means of a mobile device, the performance difference between high-resolution digital image and mobile device should be surmounted. As the transcoding techniques to settle the performance difference causes damage of image quality, high-quality image may be guaranteed by application of trial and error between transcoding and selected learning resources.

• Journal of KIISE:Information Networking
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• v.27 no.3
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• pp.348-359
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• 2000

Most of the important real time multimedia applications require multipoint transmissions. To support these applications in ATM based Intermet environments, it is important to provide efficient IP multicast transportations over ATM networks. IETF proposed MARS(Multicast Address Resolution Server) as the service architecture to transport connectionless IP multicast flows over connection oriented ATM VCs. MARS assumes UNI3.0/3.1 signalling. Since UNI3.0/3.1 does not provide any means for receivers to request a join for a multicast ATM VC, MARS provides overlay service to relay join request from IP multicast group members to the sources of the multicast group. Later on, ATM Forum standardized UNI4.0 signalling which is provisioned with a new signalling mechanism called LIJ(Leaf Initiated Join). LIJ enables receivers to directly signal the source of an ATM VC to join. In this paper, we propose a new service architecture providing IP multicast flow transportation over ATM networks deploying UNI4.0 signalling. The proposed architecture is named UNI4MARS. It comprises service components same as those of the MARS. The main functionality provided by the UNI4MARS is to provide source information to the receivers so that the receivers may exploit LIJ to join multicast ATM VCs dynamically. The implementation overhead of UNI4MARS and that of MARS are compared by a course of simulations. The simulation results show that the UNI4MARS supports the dynamic IP multicast group changes more efficiently with respect to processing, memory and bandwidth overhead.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.21-30
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• 2006

This study applies the cognitive apprenticeship theory a representative learning theory of constructivism. to design and create a web courseware for data device operator license. to enable research that begins with peripheral participation in Problem solving and ends with full participation and initiative, to act as a medium for assisting students in learning, to enable adaptation to actual situations through simulation studies, to allow aggressive interaction, and to help reinforce the level of data processing with regard to learning. The student was made to evaluate learning materials at real time for feedback on insufficient areas, to enable effective learning. The study was done by offering a web courseware without applying the cognitive apprenticeship theory and a web courseware with the cognitive apprenticeship theory, which was followed by an evaluation on study achievement level and learning behavior and then a survey was done after the evaluations. The results of this study were first, the learning group with web courseware applying cognitive apprenticeship theory showed more effect in improving learning achievement than the group with web courseware without the cognitive apprenticeship theory. Secondly, learning with web courseware applying cognitive apprenticeship theory was more effective for improving learning behavior.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1317-1328
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• 2021

This study analyzes the early satellite mission marine fog detection results from Geostationary Ocean Color Imager-II (GOCI-II). We investigate optical characteristics of the GOCI-II spectral bands for marine fog between October 2020 and March 2021 during the overlapping mission period of Geostationary Ocean Color Imager (GOCI) and GOCI-II. For Rayleigh-corrected reflection (R_rc) at 412 nm band available for the input of the GOCI-II marine fog algorithm, the inter-comparison between GOCI and GOCI-II data showed a small Root Mean Square Error (RMSE) value (0.01) with a high correlation coefficient (0.988). Another input variable, Normalized Localization Standard (NLSD), also shows a reasonable correlation (0.798) between the GOCI and GOCI-II data with a small RMSE value (0.007). We also found distinctive optical characteristics between marine fog and clouds by the GOCI-II observations, showing the narrower distribution of all bands' R_rc values centered at high values for cloud compared to marine fog. The GOCI-II marine fog detection distribution for actual cases is similar to the GOCI but more detailed due to the improved spatial resolution from 500 m to 250 m. The validation with the automated synoptic observing system (ASOS) visibility data confirms the initial reliability of the GOCI-II marine fog detection. Also, it is expected to improve the performance of the GOCI-II marine fog detection algorithm by adding sufficient samples to verify stable performance, improving the post-processing process by replacing real-time available cloud input data and reducing false alarm by adding aerosol information.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.12
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• pp.301-312
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• 2018

In industrial wireless sensor networks, the continuous object detection such as fire or toxic gas detection is one of major applications. A continuous object occurs at a specific point and then diffuses over a wide area. Therefore, many studies have focused on accurately detecting a continuous object and delivering data to a static sink with an energy-efficient way. Recently, some applications such as fire suppression require mobile sinks to provide real-time response. However, the sink mobility support in continuous object detection brings challenging issues. The existing approaches supporting sink mobility are designed for individual object detection, so they establish one-to-one communication between a source and a mobile sink for location update. But these approaches are not appropriate for a continuous object detection since a mobile sink should establish one-to-many communication with all sources. The one-to-many communication increases energy consumption and thus shortens the network lifetime. In this paper, we propose the origin-centric communication scheme to support sink mobility in a continuous object detection. Simulation results verify that the proposed scheme surpasses all the other work in terms of energy consumption.

• Economic and Environmental Geology
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• v.52 no.4
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• pp.313-322
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• 2019

SAR (Synthetic Aperture Radar) remote sensing data is a very useful tool for near-real-time identification of landslide affected areas that can occur over a large area due to heavy rains or typhoons. This study aims to develop an effective algorithm for automatically delineating landslide areas from the polarimetric SAR data acquired after the landslide event. To detect landslides from SAR observations, reduction of the speckle effects in the estimation of polarimetric SAR parameters and the orthorectification of geometric distortions on sloping terrain are essential processing steps. Based on the experimental analysis, it was found that the IDAN filter can provide a better estimation of the polarimetric parameters. In addition, it was appropriate to apply orthorectification process after estimating polarimetric parameters in the slant range domain. Furthermore, it was found that the polarimetric entropy is the most appropriate parameters among various polarimetric parameters. Based on those analyses, we proposed an automatic landslide detection algorithm using the histogram thresholding of the polarimetric parameters with the aid of terrain slope information. The landslide detection algorithm was applied to the ALOS-2 PALSAR-2 data which observed landslide areas in Japan triggered by Typhoon in September 2011. Experimental results showed that the landslide areas were successfully identified by using the proposed algorithm with a detection rate of about 82% and a false alarm rate of about 3%.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Journal of Korean Society of Archives and Records Management
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• v.19 no.3
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• pp.223-245
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• 2019

As the foundation for the Fourth Industrial Revolution, blockchain is becoming an essential core infrastructure and technology that creates new growth engines in various industries and is rapidly spreading to the environment of businesses and institutions worldwide. In this study, the characteristics and trends of blockchain technology were investigated and arranged, its application to the records management section of public institutions was required, and the procedures and methods of construction in the records management field of public institutions were studied in literature. Finally, blockchain technology was applied to the records management to propose an archive chain model and describe possible expectations. When the transactions that record the records management process of electronic documents are loaded into the blockchain, all the step information can be checked at once in the activity of processing the records management standard tasks that were fragmentarily nonlinked. If a blockchain function is installed in the electronic records management system, the person who produces the document by acquiring and registering the document enters the metadata and information, as well as stores and classifies all contents. This would simplify the process of reporting the production status and provide real-time information through the original text information disclosure service. Archivechain is a model that applies a cloud infrastructure as a backend as a service (BaaS) by applying a hyperledger platform based on the assumption that an electronic document production system and a records management system are integrated. Creating a smart, electronic system of the records management is the solution to bringing scattered information together by placing all life cycles of public records management in a blockchain.