• Restorative Dentistry and Endodontics
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• v.42 no.1
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• pp.60-64
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• 2017

Root canal anatomy is complex, and the recognition of anatomic variations could be a challenge for clinicians. This case report describes the importance of cone beam computed tomographyic (CBCT) imaging during endodontic treatment. A 23 year old woman was referred by her general dental practitioner with the chief complaint of spontaneous pain in her right posterior maxilla. From the clinical and radiographic findings, a diagnosis of symptomatic irreversible pulpitis was made and endodontic treatment was suggested to the patient. The patient underwent CBCT examination, and CBCT scan slices revealed seven canals: three mesiobuccal (MB1, MB2, and MB3), two distobuccal (DB1 and DB2), and two palatal (P1 and P2). Canals were successfully treated with reciprocating files and filled using single-cone filling technique. Precise knowledge of root canal morphology and its variation is important during root canal treatment. CBCT examination is an excellent tool for identifying and managing these complex root canal systems.

• Hwankyungkyoyuk
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• v.15 no.1
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• pp.31-50
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• 2002

The purpose of this study were the effects of principal related factors on the choice of the subject of environmental education in curriculum of middle and high school. We select 495 middle and high schools from 3 district of Chungbuk, Daejeon and Incheon. And, we send the questionnaires to the principals and withrowed answer questionnaire of 313(63.2%) from them. From the analysis of questionnaire, we obtained the reliability coefficient cronbach alpha value(0.8684). The results of this research as fallows : the principal factors that had chosen the subject of environmental education have significantly higher knowledge, recognition, attitude and practice than that not choiced on the subject of environmental education(p=0.000). The correlation between principal's attitude on the choice of the subject of environmental education and choice state of school was significantly higher than the other factors, and it's correlation coefficient was 0.328(p<0.01). Principal's attitude factor on the choice of the subject of environmental education have a great influence on his practice factor of them, and standard regression coefficient was 0.642(p<0.001). We found that principal's attitude factor on the choice of the subject of environmental education to have a great influence on the choice state of school in view of the results so far achieved.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.99-102
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• 2021

The article considers one of the areas of development of artificial intelligence where there is the development of computer intelligent systems capable of performing functions traditionally considered intelligent - language comprehension, inference, use of accumulated knowledge, learning, pattern recognition, as well as learn and explain their decisions. It is found that informational intellectual systems are promising in their development. The article is devoted to intelligent information systems and technologies in educational activities, ie issues of organization, design, development and application of systems designed for information processing, which are based on the use of artificial intelligence methods.

• Smart Structures and Systems
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• v.29 no.1
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• pp.105-116
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• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.613-618
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• 2023

In this paper, a monitoring program that can automatically determine whether a patient admitted to an isolation room acts out of a stable state through a screen photographed in real time is described. The motion recognition model of this program was built by learning through transfer learning. 900 images were used for the three movements, and this program was developed for the web to support all environments. The model was determined with high accuracy to determine the state of the subject hospitalized in the isolation room, and can be applied by applying it to the existing isolation room monitoring system.

• Journal of Korean society of Dental Hygiene
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• v.15 no.3
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• pp.477-486
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• 2015

Objectives: The purpose of the study is to investigate the influencing factors of subjective awareness of dental health status on the use of dental hygienic devices. Methods: A self-reported questionnaire was completed by 320 patients who visited dental clinics in Seoul and Gyeonggi-do from May to June 2014. Except incomplete answers, 284 copies were analyzed by SPSS WIN 18.0 program. The questionnaire was adapted from Park & Youn, and Chae. The questionnaire consisted of five questions of the general characteristics of the subjects, one question of subjective dental health status, eight questions of awareness of dental hygienic devices, and eight questions of use of dental hygienic devices. Results: Although the awareness of self dental health state was shown to statistically significantly affect the awareness of dental hygiene devices(p<0.001) which is the dependent variable, it was shown to not affect the use. Conclusions: Based on such results, to improve and maintain the dental health, an individual's subjective dental health state should be identified and provide accurate and objective information on the dental hygiene devices that are suitable to individual dental state, as well as make the patient's use of dental hygiene devices increase through continuous boosting of motivation.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.71-79
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• 1997

In this paper, a codeword-dependent distance normalization(CDDN) and an instar-formed fuzzy smoothing of output distribution are proposed for robust estimation of output probabilities in the FVQ(fuzzy vector quantization)-DHMM(discrete hidden Markov model). The FVQ-DHMM is a variant of DHMM in which the state output probability is estimated by the sum oft he product of the output probability and its weighting factor for each codeword on an input vector. As the performance of the FVQ-DHMM is influenced by weighting factor and output distribution from a state, it is required to get a method to get robust estimation of weighting factors and output distribution for each state. From experimental results, the proposed CDDN method has reduced 24% of error rate over the conventional FVQ-DHMM, and also reduced 79% of error rate when the smoothing of output distribution is also applied to the computation of an output probability. These results indicate that the use of CDDN and the fuzzy smoothing of output distribution to the FVQ-DHMM lead to improved recognition, and therefore it may be used as an alternative to the robust estimation of output probabilities for HMMs.

• Korean Security Journal
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• no.42
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• pp.251-276
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• 2015

The purpose of this article is to examine Israeli intelligence activity which had contributed to the building of Israel and of its national identity. In the late 19th, the Jews scattered around the world had shared the image of victims shaped in the history of the persecution. In this process, intelligence activity was a staple factor which established the state of Israel; political and religious community. Fighting against Arabs, Israel's intelligence agents had played key role in migrating Jews to Palestine and building their own state. In other words, Intelligence activity was the instrument of implementing political Zionism, Jewish nationalism. Even after independence in 1948, despite the opposition of Arab, Israeli intelligence agencies had persuaded the United States and the Soviet Union to recognize Israel as a member of the international society. Arab countries, nevertheless, had regarded Israel as 'a state to be disappeared', and its national identity was totally denied. However, Israel officially gained recognition for statehood through Arab-Israeli war and summit talks with Egypt. Israel finally restored the 'Promised Land' that is recorded in the Bible and established its identity of a winner. In conclusion, Israeli intelligence agency played a decisive role in founding the nation and even forming the consciousness of the people.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.7-12
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• 2022

The modern stage of society's development is characterized by the rapid penetration of information technologies into all spheres of life. Their use contributes to improving the quality of tourism services, as well as the competitiveness of tourism industry enterprises. The role of information technology in tourism is growing more and more every year, which determines the relevance of the study of modern trends in the use of information technology in the tourism sector. The purpose of the study is to determine the possibilities of using information technologies to improve the quality of services provided to the tourism industry under the COVID-19 restrictions. The article systematizes the main approaches to the "cluster" category and provides an original definition of the "regional tourist cluster" concept. Based on an expert survey, the main trends in the introduction of information technologies in the tourism industry under the COVID-19 restrictions have been identified, which include virtual reality and augmented reality, speech recognition technologies, photo, video, audio (contactless control technologies), mobile IT applications and Big Data technologies. It has been concluded that the vast majority of improvements in the organization of tourism services under restrictions will be based on the organization of virtual solutions and online activities. The types of tourism services will also change, and information technology will help their development and dissemination.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.895-904
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• 2011

In welding machine that executes existing spot welding, wrong operation of system has often occurs because of their mechanical motion that can be caused by a number of supply like the welding object. In exposed working environment for various situations such as worker or related equipment moving into any place that we are unable to exactly distinguish between good and not condition of nut. Also, in case of defective welding of nut, it needs various evaluation and analysis through image processing because the problem that worker should be inspected every single manually. Therefore in this paper, if the object was not stabilization state correctly, we have purpose to algorithm implementation that it is to reduce the analysis time and exact recognition as to improve system of image processing. As this like, as image analysis for assessment whether it is good or not condition of nut, in his paper, implemented algorithms were suggested and list by group and that it showed the effectiveness through more than one experiment. As the result, recognition rate of normality and error according to the estimation time have been shown as 40%~94.6% and 60%~5.4% from classification 1 of group 1 to classification 11 of group 5, and that estimation time of minimum, maximum, and average have been shown as 1.7sec.~0.08sec., 3.6sec.~1.2sec., and 2.5sec.~0.1sec.