• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.72-83
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• 2006

It is not a practical solution that the DDoS attacks or worm propagations are protected and responded within a domain itself because it clogs access of legitimate users to share communication lines beyond the boundary a domain. Especially, the DDoS attacks with spoofed source address or with bogus packets that the destination addresses are changed randomly but has the valid source address does not allow us to identify access of legitimate users. We propose a scheme of distributed network security management to protect access of legitimate users from the DDoS attacks exploiting randomly spoofed source IP addresses and sending the bogus packets. We assume that Internet is divided into multiple domains and there exists one or more domain security manager in each domain, which is responsible for identifying hosts within the domain. The domain security manager forwards information regarding identified suspicious attack flows to neighboring managers and then verifies the attack upon receiving return messages from the neighboring managers. Through the experiment on a test-bed, the proposed scheme was verified to be able to maintain high detection accuracy and to enhance the. normal packet survival rate.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.175-187
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• 2011

Since insects play important roles in existence of plants and other animals in the natural environment, they are considered as necessary biological resources from the perspectives of those biodiversity conservation and national utilization strategy. For the conservation and utilization of insect species, an observational learning environment is needed for non-experts such as citizens and students to take interest in insects in the natural ecosystem. The insect identification is a main factor for the observational learning. A current time-consuming search method by insect classification is inefficient because it needs much time for the non-experts who lack insect knowledge to identify insect species. To solve this problem, we proposed an smart phone-based insect identification inference system that helps the non-experts identify insect species from observational characteristics in the natural environment. This system is based on the similarity between the observational information by an observer and the biological insect characteristics. For this system, we classified the observational characteristics of insects into 27 elements according to order, family, and species, and proposed similarity indexes to search similar insects. In addition, we developed an insect identification inference prototype system to show this study's viability and performed comparison experimentation between our system and a general insect classification search method. As the results, we showed that our system is more effective in identifying insect species and it can be more efficient in search time.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.207-215
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• 2009

There has been a diversity of therapeutic interventions for patients with chronic low back pain. However most of them have been focused on only pain. But the patients usually have a kind of structurally abnormal have fixed in lumbar vertebrae, which can decrease range of joint movement and, what is worse, reduce immediate dynamic balancing ability(IDBA). The reduced IDBA can increase the risk of injury and decrease coping ability in dangerous situation. So we introduced Maitland's manual therapy in this study in order to recover the IDBA in patients with chronic low back pain. Sixty-four patients diagnosed with chronic low back pain were included for the study. Among them, thirty-two patients(experimental group) were managed by Maitland's manual therapy, another thirty-tow patients(control group) were treated by physical science methods(H/P, TENS, U/S). Each group made use of highly reliable(0.81$\sim$0.96) star excursion balance test(SEBT) to compare the possible changes of IDBAs in two groups after treatment. In experimental group, IDBA has increased in forward, rightward, leftward, and backward, but in control group, not changed. According to the results, we concluded that Maitland's manual therapy is effective for increasing IDBA by making joints more flexible in lumbar vertebrae.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.172-177
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• 2021

As part of the digital era, a digital twin that simulates the weak part of a product by performing a stress test that reduces the lifespan of some expensive equipment that cannot be done in reality by accurately moving the real world to virtual reality is being actively used in the manufacturing industry. Due to the development of IoT, the digital twin, which accurately collects data collected from the real world and makes it the same in the virtual space, is mutually beneficial through accurate prediction of urban life problems such as traffic, disaster, housing, quarantine, energy, environment, and aging. Based on its action, it is positioned as a necessary tool for smart city construction. Although digital twin is widely applied to the manufacturing field, this study proposes a smart city model suitable for the 4th industrial revolution era by using it to smart cities and increasing citizens' safety, welfare, and convenience through the proposed model. In addition, when a digital twin is applied to a smart city, it is expected that more accurate prediction and analysis will be possible by real-time synchronization between the real and virtual by maintaining realism and immediacy through real-time interaction.

• The Korean Journal of Archival Studies
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• no.19
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• pp.57-102
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• 2009

Recently, distribution of record via web and coefficient of utilization are increase. so, Archival information service using website becomes essential part of record center. The main point of archival information service by website is making record information retrieval easy. It has need of matching user's request and representation of record resources correctly to making archival information retrieval easy. Archivist and record manager have used various information representation tools from taxonomy to recent thesaurus, still, the accuracy of information retrieval has not solved. This study constructed record retrieval system based on Topic Map by modeling record resources which focusing on description metadata of the records to improve this problem. The target user of the system is general web users and its range is limited to the president related sources in the National Archives Portal Service. The procedure is as follows; 1) Design an ontology model for archival information service based on topic map which focusing on description metadata of the records. 2) Buildpractical record retrieval system with topic map that received information source list, which extracted from the National Archives Portal Service, by editor. 3) Check and assess features of record retrieval system based on topic map through user interface. Through the practice, relevance navigation to other record sources by semantic inference of description metadata is confirmed. And also, records could be built up as knowledge with result of scattered archival sources.

• Journal of vocational education research
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• v.37 no.6
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• pp.63-83
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• 2018

The purpose of this study is to identify the main factors helping university students sucessfully adapt to campus life and achieve academic accomplishment through a critical period in personal development. For this purpose, the analysis verifying influence of self leadership as an individual trait variable and social support as a socio environmental trait variable on academic achievement of university students and the mediating effect of school adjustment among them was conducted. Total 271 responses collected by implementing a questionnaire survey in "S", a four-year private university located in Seoul, were used for the analysis. The validity of the measurement was verified through confirmatory factor analysis and the relationship among the variables was examined through structural model equation, bootstrap and sobel test. The major finding of this study are as follows. First, this study confirmed the causal relationship of self leadership and social support impacting on academic achievement of university students. This result suggests that an integrated approach taking into account both individual and socio environmental factors is necessary to support academic achievement of university students. Second, it was proved that self leadership and social support indirectly influences academic achievement through school adjustment. This demonstrates that school adjustment is an important predictor of academic achievement as well as plays a major role in mediating among self leadership, social support and academic achievement. In conclusion, the results of this study conveys its significance in suggesting the necessity to provide insititutional support on individual trait and socio environmental factor enabling university students sucessfully to adapt to campus life and achieve academic achievement.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.495-509
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• 2020

This study is a theoretical research to explore ways to effectively learn AI in the age of intelligent information driven by artificial intelligence (hereinafter referred to as AI). The emphasis is on presenting a teaching method to make AI education accessible not only to students majoring in mathematics, statistics, or computer science, but also to other majors such as humanities and social sciences and the general public. Given the need for 'Explainable AI(XAI: eXplainable AI)' and 'the importance of storytelling for a sensible and intelligent machine(AI)' by Patrick Winston at the MIT AI Institute [33], we can find the significance of research on AI storytelling learning model. To this end, we discuss the possibility through a pilot study targeting general students of an university in Daegu. First, we introduce the AI storytelling(AI+ST) learning method[30], and review the educational goals, the system of contents, the learning methodology and the use of new AI tools in the method. Then, the results of the learners are compared and analyzed, focusing on research questions: 1) Can the AI+ST learning method complement algorithm-driven or developer-centered learning methods? 2) Whether the AI+ST learning method is effective for students and thus help them to develop their AI comprehension, interest and application skills.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.589-600
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• 2022

In order to verify the reliability of Dry Test Bench (DTB) used for testing the output energy from ballistic extracorporeal shock wave therapeutic devices, the measurements with DTB were compared with the acoustic energy measured with a Laser Doppler Vibrometer (LDV) for a commercial ballistic ESWT device. It was shown that the mechanical energy detected with DTB had variability maintained within 5 % at the same output power setting and also had a linear correlation (adj. R² = 0.991) with the acoustic energy measured with the LDV for the entire output power settings. Using the correlation between the two methods and the correlation on the acoustic energy measured in between air and water with the LDV, the DTB measurement can be used to estimate the energy flux density in water with an average error of 7.85 % for the entire output power settings of the ballistic shock wave generator considered in the experiment. DTB provides information limited to the output mechanical energy and therefore it is not suitable for testing the various acoustic output parameters required in IEC61846 and IEC63045. However, DTB that is simple in measurement principles and easy to use is expected for manufacturers and clinical users to monitor the performance of ballistic Extracorporeal Shock Wave Therapy (ESWT) devices.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.