• Journal of Korean Home Economics Education Association
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• v.20 no.3
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• pp.179-200
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• 2008

This study is aimed at contributing to the future development of Home Economics Education Department by suggesting basic data of TQM(Total Qualify Management) for evaluating TQM of Home Economics Education Departmeut in education colleges. A survey was conducted involving all junior(3rd year) students of Home Economics Education Department in education colleges either by making a visit to 3 different schools or by sending it in the mail to 10 different schools. Responding answer-sheets, 302 copies(88.3%) out of 342 copies in total were returned. Finally, we used 285 copies(83.3%) as data for analysis. The results of this study are as follows: In terms of Professional Qualification of Home Economics Teachers, the students had passion for their Home Economics Education and also had a great pride and mission to be future Home Economics teachers. However, their ability proved to be poor and low in presenting a vision for Home Economics, in conducting extra-curricular activities, and the computer skills. In the case of college students, their satisfaction showed an average point 3.15 on a scale of 5. Those students who entered school voluntarily or those who hoped for re-entrance showed more satisfaction than those who entered school with good academic records or those who do not hope for re-entrance into school. In terms of professors' leadership, Students are perceived to choose 'Transactional Leadership' instead of 'Transformational Leadership'. Students', who have higher satisfaction and hopes for re-entrance, perception level about their professors' leadership style showed higher satisfaction than average. The students empowerment level showed average point 3.52, which is considered relatively high. Students at the college where professors majored in Home Economics Education are employed showed higher empowerment level than students at the college with professors who did not major in Home Economics Education. The result of evaluating general demand for renovating of Home Economics Education Dept. showed that: they perceived the "Teacher Education Course" of Home Economics Education Dept. as in need of cultivating practical skills in secondary school. They also said, "Teaching Method" is in great need of renovation. In the case of teaching method, they preferred laboratory work, and practical training. In earning credits, they emphasized the importance of faithfully completing the "Study of Content". For the Subject Matter Education, they required a training course to be set up in the secondary school. Finally they claimed that the teachers and students need to take the initiative in developing a Curriculum of Home Economics Education Dept. Based on the findings mentioned above, I would like to suggest further research on how to adopt and evaluate TQM in Home Economics Education, and faculty-centered evaluation methods. I also would like to suggest to vitalize quality research through the form of narrative research.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Physical Therapy Korea
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• v.23 no.2
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• pp.11-19
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• 2016

Background: In the stroke patients with the characteristics of hemiplegic gait, turning direction of the affected and unaffected side influences turning time. Therefore, it is important to investigate the walking response to turning directions in stroke patients. Objects: This study aimed to measure the walking time while turning direction in hemiplegic patients depending on balance ability measured by Berg Balance Scale. Methods: A group of forty-five subjects with stroke (Berg Balance Scale score${\geq}46$ were twenty-eight, Berg Balance Scale score${\leq}45$ were seventeen) were enrolled in this study. Subjects were asked to perform the Timed Up and Go test. Testing indications included two directions for turning in each subject. These indications were for turning toward the affected and unaffected side in stroke patients. The duration of total analysis duration, sit to stand phase, stand to sit phase, mid-turning phase, and end turning phase were recorded. The obtained data were analyzed by using paired t-test and Wilcoxon signed rank test in the group that are below and above 45 points of Berg Balance Scale score. The significance level was set at ${\alpha}=.05$. Results: There were significant increase time in the analysis duration and end turning phase duration while subjects were turned the unaffected side in stroke patients that presented a Berg Balance Scale score${\leq}45$ (p<.05). However, the comparison between the affected side and the unaffected side in the stroke patients with Berg Balance Scale score${\geq}46$, revealed no significant differences of the measured parameters. Conclusion: This finding should be suggested in the specific definition of turning direction for evaluation with Timed Up and Go test in the Berg Balance Scale score${\leq}45$, and other intervention for hemiplegic patients need to be suggested the direction of turning during walking training program.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.2
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• pp.31-43
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• 2000

This paper presents a novel algorithm lot extraction of the eye and mouth fields (facial features) from 2D gray level face images. First of all, it has been found that Eigenfeatures, derived from the eigenvalues and the eigenvectors of the binary edge data set constructed from the eye and mouth fields are very good features to locate these fields. The Eigenfeatures, extracted from the positive and negative training samples for the facial features, ate used to train a MultiLayer Perceptron(MLP) whose output indicates the degree to which a particular image window contains the eye or the mouth within itself. Second, to ensure robustness, the ensemble network consisting of multiple MLPs is used instead of a single MLP. The output of the ensemble network becomes the average of the multiple locations of the field each found by the constituent MLPs. Finally, in order to reduce the computation time, we extracted the coarse search region lot eyes and mouth by using prior information on face images. The advantages of the proposed approach includes that only a small number of frontal faces are sufficient to train the nets and furthermore, lends themselves to good generalization to non-frontal poses and even to other people's faces. It was also experimentally verified that the proposed algorithm is robust against slight variations of facial size and pose due to the generalization characteristics of neural networks.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.317-322
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• 2010

This paper proposes how to improve performance of the Korean document sentiment-classification system using semantic properties of the sentiment words. A sentiment word means a word with sentiment, and sentiment features are defined by a set of the sentiment words which are important lexical resource for the sentiment classification. Sentiment feature represents different sentiment intensity in general field and in specific domain. In general field, we can estimate the sentiment intensity using a snippet from a search engine, while in specific domain, training data can be used for this estimation. When the sentiment intensity of the sentiment features are estimated, it is called semantic orientation and is used to estimate the sentiment intensity of the sentences in the text documents. After estimating sentiment intensity of the sentences, we apply that to the weights of sentiment features. In this paper, we evaluate our system in three different cases such as general, domain-specific, and general/domain-specific semantic orientation using support vector machine. Our experimental results show the improved performance in all cases, and, especially in general/domain-specific semantic orientation, our proposed method performs 3.1% better than a baseline system indexed by only content words.

• Journal of Distribution Research
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• v.16 no.3
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• pp.33-75
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• 2011

The ownership structure of a franchise system is determined by the franchisor's strategic choice. A close look at the extant theories and perspectives in economics and management such as resource scarcity theory, agency theory, transaction cost analysis, and mixed ownership theory reveals that firms choose their ownership structure for the sake of economic efficiency, profit potentials, the chance of survival, and other strategic concerns. The present study, on the basis of strategic choice perspective, reviews the divergent theories of a franchise system's ownership structure and its determinants, thus providing a theoretical framework for comparing the contradictory arguments along the several critical dimensions. We also developed and tested the conflicting hypotheses regarding key determinants of ownership structure including firm's age, size, transaction-specific investments, uncertainty, and risk-sharing propensity. Using a FDD (Franchise Disclosure Document) data set of 543 Korean franchisors, we found that the years in business, the total number of employees, days of training, the inverse of the years of franchising, and the requirement of royalty payment have positive relationships with the proportion of company-owned outlets to total number of outlets. On the other hand, the proportion of company-owned outlets was found to have negative relationships with the total number of outlets and the extent of geographic dispersion of outlets, but to have no significant relationships with the initial investment required and the inverse of contract length. Based on the findings, we provide several theoretical and managerial implications for studying ownership structure of franchise systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.895-901
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• 2007

Currently the advancement of the computer and the Internet sees the direction of studying freely to do, it does not receive not to be, the student the environment it will be able to study oneself it is doing the direct help of the teacher and to be possible. Plan and it embodied the high school information society which it follows in 7th curriculum and the WBI of computer subject from the dissertation which it sees. In order to improve the qualify of curriculum ultimately, it endeavored. Territory it analyzes a subject contents first, especially it surveys, foundation it hardens, the actual training semester and pure with studying of self-evaluation do to become accomplished, studying oneself to sleep the possibility of doing own lead studying which is the possibility of studying spontaneously and integrated textbook studying in same tine it does to be with they are composing of the education paradigm the flag for a problem solving ability and an originality accident. In this dissertation used the php, Apache web server and the DBMS used the MySQL. To program member joining, the information society and computer curriculum take a course and test, it questions and, it is composed to data mourge. After taking a course, simultaneously lecturing a paper and online instruction, set up a foundation and quering that gratify one's curiosity thus it will be able to digest a study in once.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.415-424
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• 2018

The purpose of this study was to examine the physical environmental readiness for smart learning and the actual utilization of smart devices by special education teachers, and to suggest ways to vitalize smart education. For this, a 14-item survey questionnaire was developed, which touched upon issues regarding the availability of wireless internet service and teachers' utilization of smart devices. An online survey was conducted among a randomly chosen sample of 991 special education teachers across the nation, including teachers who work at special schools for developmentally disabled students and in special classes at all three levels of regular schools.The collected data was analyzed with the method of a cross-time-frequency analysis using a SPSS 21.0 statistics program. The research findings indicated that both special schools and classes had a poor smart education environment and that special education teachers were having a harding time because of the lack of the infrastructure and additional expenses. In addition, special education teachers were found to use smart device mostly for the purpose of motivating students. These research findings propose that it is urgent to set up a proper smart education environment for special needs students and to provide a systematic training program for special education teachers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.347-350
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• 2018

In order for an IoT system to automatically make the house temperature pleasant for the user, the system needs to predict the optimal start-up time of air-conditioner or heater to get to the temperature that the user has set. Predicting the optimal start-up time is important because it prevents extra fee from the unnecessary operation of the air-conditioner and heater. This paper introduces an ANN(Artificial Neural Network) and an IoT system that predicts the cooling and heating time in households using air-conditioner and heater. Many variables such as house structure, house size, and external weather condition affect the cooling and heating. Out of the many variables, measurable variables such as house temperature, house humidity, outdoor temperature, outdoor humidity, wind speed, wind direction, and wind chill was used to create training data for constructing the model. After constructing the ANN model, an IoT system that uses the model was developed. The IoT system comprises of a main system powered by Raspberry Pi 3 and a mobile application powered by Android. The mobile's GPS sensor and an developed feature used to predict user's return.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2594-2603
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• 1997

A novel method of adaptive beam forming is presented in this paper. The proposed technique provides for a suboptimal beam pattern that increases the Signal to Noise/Interference Ratio (SNR/SIR), thus, eventually increases the capacity of the communication channel, under an assumption that the desired signal is dominant compared to each component of interferences at the receiver, which is precoditionally achieved in Code Division Multiple Access (CDMA) mobile communications by the chip correlator. The main advantages of the new technique are:(1)The procedure requires neither reference signals nor training period, (2)The signal interchoerency does not affect the performance or complexity of the entire procedure, (3)The number of antennas does not have to be greater than that of the signals of distinct arrival angles, (4)The entire procedure is iterative such that a new suboptimal beam pattern be generated upon the arrival of each new data of which the arrival angle keeps changing due tot he mobility of the signal source, (5)The total amount of computation is tremendously reduced compared to that of most conventional beam forming techniques such that the suboptimal beam pattern be produced at vevery snapshot on a real-time basis. The total computational load for generating a new set of weitht including the update of an N-by-N(N is the number of antenna elements) autocovariance matrix is $0(3N^2 + 12N)$. It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.