• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.173-183
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• 2009

We present a real-time monitoring system for detecting anomalous network events using the entropy. The entropy accounts for the effects of disorder in the system. When an abnormal factor arises to agitate the current system the entropy must show an abrupt change. In this paper we deliberately model the Internet to measure the entropy. Packets flowing between these two networks may incur to sustain the current value. In the proposed system we keep track of the value of entropy in time to pinpoint the sudden changes in the value. The time-series data of entropy are transformed into the two-dimensional domains to help visually inspect the activities on the network. We examine the system using network traffic traces containing notorious worms and DoS attacks on the testbed. Furthermore, we compare our proposed system of time series forecasting method, such as EWMA, holt-winters, and PCA in terms of sensitive. The result suggests that our approach be able to detect anomalies with the fairly high accuracy. Our contributions are two folds: (1) highly sensitive detection of anomalies and (2) visualization of network activities to alert anomalies.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.4
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• pp.312-333
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• 2005

SIP(Session Initiation Protocol) has been proposed for session control protocol of Internet multimedia communication system like VoIP(Voice over IP). SIP has complicated session control steps to support various kinds of audio and video formats and to assure service quality of real time data communication. Up until now, existing protocol analyzers can not provide such detailed information of SIP based communication system. In this paper, therefore, we propose a new protocol analyzer as a tool that can analyze and diagnose SIP based multimedia communication system throughout the session initiation, data exchange and session change steps. The propose traffic analyzer, which is called STAT(SIP based Traffic Analysis Tool), Is implemented on Winder's environment so that it is generally usable and extensible. Since STAT analyze low level packets captured via Ethernet broadcasting property, it is able to provide session status and real time traffic monitoring information without any affection to the communication system. The STAT which is implemented in this paper. therefore, is expected to be a useful tool for developing and managing of a SIP based multimedia communication system.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.831-835
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• 2009

Volunteer computing is a computing paradigm in which the operations of a large-scale application are processed using idle resources of Internet-connected computers. The redundant-work distribution techniques used in the volunteer computing environment cause some problems like delay of the work completion time or inefficiency of the work execution due to continuous requests of the work redistribution because the techniques do not consider the characteristics of works and dynamic resources. To cope with such problems this paper suggests a P2P based regional matchmaking technique which can redistribute works in consideration of the characteristics of the works and the participant resources. The techniques consist of the profiles for works/resources, the module for monitoring the available resources spaces, the protocols for the matching request/reply, the module for match-ratio calculation, and so on.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1755-1763
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• 2007

Specially, location information can say that is important information in this ubiquitous environment and solutions of new GIS system to utilize this are required. Examine method to improve web geography information service system because this paper uses XML and presented specific implementation result. Through internet. it planed various geography information that offer in form of service that do not receive restriction of heterogeneous system environment. Also, did thing that is easy when request service about geography information that user need and deliver fast by purpose. Supplement and to improve open-ended and XML of form normalized use and developed existent web geography information service. So that can use map service in web browser without setup of application program that buy expensive GIS software or offer in each company design and implement.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.47-53
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• 2019

Safety accidents at industrial sites can occur anytime, anywhere. Recently, research on the industrial safety management system based on the IoT has been actively conducted. However, most of the studies are studies of actions after safety accidents or simply monitoring. In this paper, the safety equipment was introduced before safety accidents occurred, and the subjects could be managed not only by workers but also by visitors. Also, it implements a system to prevent the accident by detecting the user's motion and situation periodically before a safety accident occurs. The implemented system is a system that attaches the device for safety management to the hard hat and can identify the safety situation by using the Bluetooth beacon device attached to the user's smartphone and the industrial site.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.203-211
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• 2006

Today, Internet covers a world wide range and most appliances of our life are linked to network from enterprise server to household electric appliance. Therefore, the importances of administrable framework that can grasp network state by real-time is increasing day by day. Our objective in this paper is to describe a network weather report framework that monitors network traffic and performance state to report a network situation including traffic status in real-time. We also describe a mobile agent architecture that collects state information in each network segment. The framework could inform a network manager of the network situation. Through the framework. network manager accumulates network data and increases network operating efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.86-97
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• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.

• The Korea Journal of Herbology
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• v.36 no.5
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• pp.1-14
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• 2021

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the "Naver DataLab (http://datalab.naver.com)" service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : 'Cheonsangap (천산갑, 穿山甲, Manitis Squama)' was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.18-29
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• 2019

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant's long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.253-262
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• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.