• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.147-153
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• 2011

In this paper, we present a new video management technique using forward timeline to efficiently store and delete the videos on a local server. The proposed method is based on capturing the changing preference of the videos according to recentness, frequency, and playback length of the requested videos. For this purpose, we utilize the forward timeline which represents the time area within a number of predefined intervals. The local server periodically measures time popularity and request segment of all videos. Based on the measured data, time popularity and request segment, the local server calculates the mean time popularity and mean request segment of a video using forward timeline. Using mean time popularity and mean request segment of video, we estimate the ranking and allocated storage space of a video. The ranking represents the priority of deletion when the storage area of local server is running out of space and the allocated storage space means the maximum size of storage space to be allocated to a video. In addition, we propose an efficient storage space partitioning technique in order to stably store videos and present a time based free-up storage space technique using the expected variation of video data in order for avoiding the overflow on a local server in advance. The simulation results show that the proposed method performs better than other methods in terms of hit rate and number of deletion. Therefore, our video management technique for local server provides the lowest user start-up latency and the highest bandwidth saving significantly.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.851-868
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• 2012

After the financial crisis in 2008, the financial market still seems to be unstable with expanding the insolvency of the financial companies' real estate project financing loan in the aftermath of the lasted real estate recession. Especially after the illegal actions of people's financial institutions disclosed, while increased the anxiety of economic subjects about financial markets and weighted in the confusion of financial markets, the potential risk for the overall national economy is increasing. Thus as economic recession prolongs, the people's financial institutions having a weak profit structure and financing ability commit illegal acts in a variety of ways in order to conceal insolvent assets. Especially it is hard to find the loans of shareholder and the same borrower sharing credit risk in advance because most of them usually use a third-party's name bank account. Therefore, in order to effectively detect the fraud under other's name, it is necessary to analyze by clustering the borrowers high-related to a particular borrower through an analysis of association between the whole borrowers. In this paper, we introduce Analysis Techniques for detecting financial loan frauds in advance through an analysis of association between the whole borrowers by extending SNA(social network analysis) which is being studied by focused on sociology recently to the forensic accounting field of the financial frauds. Also this technique introduced in this pager will be very useful to regulatory authorities or law enforcement agencies at the field inspection or investigation.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.649-654
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• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• Industry Promotion Research
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• v.5 no.2
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• pp.19-25
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• 2020

This study is a study on how to revitalize social and economic organizations in the Chungnam region. For this, the following major results were presented in literature studies based on prior studies. First, it is necessary to upgrade the social economic organization promotion system and system in Chungnam. Second, there is a need to advance the measures to revitalize various social and economic organizations in cities and counties by building an integrated support system for social and economic organizations. Third, it is necessary to expand the public purchase of products of social economic organizations. Fourth, it is necessary to strengthen the business competency of the social economy organization and promote education. Fifth, it is necessary to upgrade the network for social economic organizations and create differentiated businesses. On the other hand, the social economic organization in Chungnam region shown through this study is as follows. First, social and economic organizations should share their willingness to implement policies in the provincial and provincial areas of Chungnam Province and cities and counties in terms of solving and improving various problems in the region. Based on this, it is required to upgrade the social and economic organization area. Second, the Chungnam region needs a shift in awareness that it is a social and economic organization that is a key factor in overcoming changes in the demographic structure due to industrial weakness and aging. Third, a positive shift in awareness is required by shifting awareness and strengthening education on social and economic organizations. To this end, it is necessary to raise the awareness level of local residents through public education and joint public-private education.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.55-61
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• 2022

Currently police and fire departments use a Network/Wifi/GPS based emergency location positioning system established by mobile carriers to directly link with the device of the people who request the rescue to accurately position the expected location in the call area. However in the case of mountain rescue it is difficult to rescue the victim in golden time because the location of the search area cannot be limited when the victim is located in a radio shadow area of the mountain or the device power is off and this situation become worse if victim fail to report 911 by himself due to the injury. In this paper, we are expected to solve the previous problem by propose the mobile telecommunication forensic simulator consist of time series of cell information, human mobility model which include some general and specific features (age, gender, behavioral characteristics of victim, etc.) and intelligent infer system. The results of analysis appear in heatmap of polygons on the map based on the probability of the expected location information of the victim. With this technology we are expected to contribute to rapid and accurate lifesaving by reducing the search area of rescue team.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.197-204
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• 2015

Recent changes in health care environment including aging population and prevalence of chronic disease encourage the adoption of new innovative technological solutions including wearable vital sensors, wireless networks, and smart phone. In this paper, we present an effective at-home lifestyle monitoring system that can be used for self-management and health intervention of patient himself in the Management-by-Exception perspectives. We implemented the filtering and queuing algorithms as a preprocessor of monitoring system to enhance efficiency of proposed system, and the effective UX design for self-management of patients themselves. The 94,467 actual clinic data was used to test the efficiency of the proposed system. As as a result, 64.8% of the incoming vital data was identified to be filtered out.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.188-194
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• 2007

We propose a new ad hoc multicast routing protocol for based on the ontology scheme called inference network. Ontology knowledge-based is one of the structure of context-aware. We will have developed an algorithm that will design multi-hierarchy Layered networks to simulate a desired system.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4
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• pp.202-209
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• 2005

The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding owner's audio signal. Because this method uses an audio signal as a watermark to be embedded, it is very useful to claim the ownership aurally. And it has the advantage of restoring audio signal modified and especially removed by image removing attacks by applying our LBX(Linear Bit-expansion) interleaving. Three basic stages of our watermarking include: 1) Encode . analogue owner's audio signal by PCM and create new digital audio watermark, 2) Interleave an audio watermark by our LBX; and 3) Embed the interleaved audio watermark in the low frequency band on DTn (Discrete Haar Wavelet Transform) of image. The experimental results prove that this method is resistant to lossy JPEG compression as standard image compression and especially to cropping and rotation which remove a part of Image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.322-332
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• 2017

Wireless Body Area Networks is an environment that provides an appropriate service remotely by collecting user's biometric information. With the growing importance of sensor, WBAN also attracts extensive attention. Since WBAN is representatively used in the medical field, it can be directly related to the patient's life. Hence security is very important in WBAN. Mutual authentication between the client and the application provider is essential. And efficiency is also important because a used device is limited to computation cost. In this reason, ID-based anonymous authentication scheme in WBAN has been intensively studied. We show that the recent research result of Wu et al. which is about the ID-based anonymous authentication scheme is vulnerable to impersonation attack. And we propose a new ID-based anonymous authentication scheme that is secure against the attacks discovered in the existing schemes. Compared to the existing schemes, the computation cost of our scheme is improved by 30.6% and 7.3%.