• Journal of the Korean Society for information Management
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• v.17 no.4
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• pp.187-206
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• 2000

This study is to analyrc the f~~nclional capdbiiities and interracc features or OPAC systems in twcnty-[ouracademc libraries in order to iuvesugale thc strongest pan and (he nveakesl or OPACs. For h e sludy, lllc checklistwas developed. TIE findmgs of thc sludy suegesl Lhat. among the leu RreE evaluated, '.Access Poinls." is lhe bcstdeveloped m a , whercas "Subject Scarc11 Aids" is the wekcst. Timefore, the OPAC system designers am1 librarianswill improvc the varlou sci~rch aids luncuonr and vocabulary browsiug function and will develop mil imlilen\ulcornerentvisual merracc ilnd hyper linkmg inechanism. hyper linkmg inechanism.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1765-1768
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• 2015

3D 디스플레이 기술이 발달함에 따라 3 차원 공간에서의 뇌-컴퓨터 인터랙션 기술에 대한 관심이 높아지고 있다. 3D 디스플레이 기술은 사용자에게 실재감과 몰입감을 부여하여 특정 태스크를 수행할 때 사용자 태스크 퍼포먼스를 향상시킬 수 있다. 이와 같은 3D 입체감이 주는 긍정적 효과에 대한 연구는 교육, 주의력 향상, 엔터테인먼트를 목적으로 하는 뇌-컴퓨터 인터랙션 분야에서도 활발히 이루어지고 있다. 뇌-컴퓨터 인터랙션을 구성하는 뇌파성분에는 시각, 청각, 촉각 유발지속전위, 사건유발전위, 사건관련 동기/비동기화 성분, 느린 피질전위 등이 있다. 이 중 시유발 지속전위를 이용한 뇌-컴퓨터 인터랙션 기술은 오브젝트 콘트롤을 위한 사전훈련이 거의 요구되지 않으며 높은 정보전달율을 가지는 것을 특정으로 하기 때문에 최근 널리 사용되고 있다. 그러나 저주파수 대역의 명멸자극이 유발하는 피로감으로 인해 사용시간이 제한적인 한계점이 있다. 따라서, 본고에서는 유발뇌파의 일종인 시유발지속전위를 이용한 뇌-컴퓨터 인터랙션 기술을 소개하고 3D 홀로그램 인터랙션 수행 시 피로감을 최소화할 수 있는 방안에 대해 논의 하고자 한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1167-1177
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• 2019

In this paper, the improved security operation model based on the vulnerability database is studied. The proposed model consists of information protection equipment, vulnerability database, and a dashboard that visualizes and provides the results of interworking with detected logs. The evaluation of the model is analyzed by setting up a simulated attack scenario in a virtual infrastructure. In contrast to the traditional method, it is possible to respond quickly to threats of attacks specific to the security vulnerabilities that the asset has, and to find redundancy between detection rules with a secure agent, thereby creating an optimal detection rule.

• Convergence Security Journal
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• v.22 no.3
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• pp.13-18
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• 2022

With the rapid development of IT technology, integration with existing industries has led to an increase in smart manufacturing that simplifies processes and increases productivity based on 4th industrial revolution technology. Security threats are also increasing and there are. In the case of supply chain attacks, it is difficult to detect them in advance and the scale of the damage is extremely large, so they have emerged as next-generation security threats, and research into detection technology is necessary. Therefore, in this paper, we collect, store, analyze, and visualize logs in multiple environments in real time using ELK Stack and Sysmon, which are open source-based analysis solutions, to derive information such as abnormal behavior related to supply chain attacks, and efficiently We try to provide an effective detection method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.333-336
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• 2022

With the development of IT technology, cybercrime is becoming sophisticated and intelligent. In particular, in the case of BackDoor, which is used in the APT attack (intelligent continuous attack), it is very important to detect malicious behavior and respond to infringement because it is often unaware that it has been damaged by an attacker. This paper aims to build an EDR platform that can monitor, analyze, and respond to malicious behavior in real time by collecting, storing, analyzing, and visualizing logs in an endpoint environment in real time using open source-based analysis solutions ELK Stack and Sysmon.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.181-191
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• 2005

This study developed an algorithm for real-time signal control based on the detection system that can collect sectional travel time. The signal control variable is maximum queue length per cycle and this variable has a sectional meaning. When a individual vehicle pass through the detector, we can gather the vehicle ID and the detected time. Therefor we can compute the travel time of an individual vehicle between consecutive detectors. This travel time informations were bisected including the delay and not. We can compute queue withdrawing time using this bisection and the max queue length is computed using the deterministic delay model. The objective function of the real-time signal control aims equalization of queue length for all direction. The distribution of the cycle is made by queue length ratios.

• Phonetics and Speech Sciences
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• v.11 no.3
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• pp.39-47
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• 2019

We propose a method to improve the performance of spontaneous speech recognizers by extending their phone set using speech data. In the proposed method, we first extract variable-length phoneme-level segments from broadcast speech signals, and convert them to fixed-length latent vectors using an long short-term memory (LSTM) classifier. We then cluster acoustically similar latent vectors and build a new phone set by choosing the number of clusters with the lowest Davies-Bouldin index. We also update the lexicon of the speech recognizer by choosing the pronunciation sequence of each word with the highest conditional probability. In order to analyze the acoustic characteristics of the new phone set, we visualize its spectral patterns and segment duration. Through speech recognition experiments using a larger training data set than our own previous work, we confirm that the new phone set yields better performance than the conventional phoneme-based and grapheme-based units in both spontaneous speech recognition and read speech recognition.

• Journal of Practical Agriculture & Fisheries Research
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• v.21 no.2
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• pp.103-114
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• 2019

In this study we examined the preferences of college life factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the results of text mining were visualized as word cloud. And those results were used for statistical analysis of the students' willingness to farm after graduation. The items of the favorable survey consisted of 10 items in 5 areas including university image, self-capacity, dormitory, education system, and future vision. After classifying the emotions of positive and negative in the collected questionnaire, a dictionary of positive and negative was created to evaluate the preference. The items of 'college image' at the time of university support, 'self after 10 years' after graduation, 'self-capacity' and 'present KNCAF' showed high positive emotion. On the other hand, positive emotion was low in the items of 'college dormitory', 'educational course', 'long-term field practice' and 'future of Korean agriculture'. In the cross-analysis of the difference in the will to farming according to gender, farming base, and entrance motivation, the will to farm according to gender and entrance motivation showed statistically significant results, but it was not significant in farming base. Also in binary logistic regression analysis on the will to farming, the statistically significant variable was found to be 'motivation for admission'

• Journal of the Korean Society of Earth Science Education
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• v.14 no.1
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• pp.33-47
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• 2021

This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.

• Journal of the Korean Chemical Society
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• v.54 no.1
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• pp.150-157
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• 2010

In this study, we investigated the differences of mapping understanding and the types of mapping errors by the levels of students' cognitive/affective variables and the relationships between mapping understanding and these variables in learning 'concentration and reaction rate' with analogy. After administering the tests regarding logical thinking ability, visual imagery ability, analogical reasoning ability, self efficacy, and need for cognition as pretests, students learned with analogy. Then, students' familiarity and mapping understanding were examined. Analyses of the results revealed that the scores of the mapping understanding for the students with higher levels of all cognitive/affective variables except visual imagery ability and familiarity were significantly higher than those for the students with lower levels. The differences in the types of the mapping errors such as overmapping, failure to map, impossible mapping, artificial mapping, mismapping, rash mapping, and retention of a base feature were also found by the levels of students' cognitive and affective variables. The scores of students' mapping understanding were positively correlated with those of all cognitive and affective variables. The results of multiple regression analysis indicated that students' science achievement, logical thinking ability, and familiarity were significant predictors of mapping understanding. Educational implications of these findings are discussed.