• Journal of Digital Convergence
• /
• v.11 no.10
• /
• pp.341-350
• /
• 2013

Recently, in order to promote their marketing promotion, the entrepeneurs attach importance to many SNS(Social Network Service)and execute it. The representative elements of the SNS service are interactivity, information offering. This study analyzes empirical effects on the SNS Marketing Features in Domesic Enterprise The conclusion of this study shows that the Interactivity has a higher positive effects on Affective Commitment than those on information offering and Information offering has stronger positive effects on calculative commitment than interactivity. Also, these effects enlarge the high use frequency more than the low use frequency. This study also shows that the information offering affect the On-line Word-of-Mouth more positively than the Interactivity. And this study shows that SNS affects the positive effects on the relationship commitment rather than the On-line Word-of-Mouth. Based on the results, the practical implications are offered.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.187-192
• /
• 2023

In this study, trends in ICT education were investigated by analyzing the frequency of appearance of keywords related to machine learning and using conversion of iteration correction(CONCOR) techniques. A total of 304 papers from 2018 to the present published in registered sites were searched on Google Scalar using "ICT education" as the keyword, and 60 papers pertaining to ICT education were selected based on a systematic literature review. Subsequently, keywords were extracted based on the title and summary of the paper. For word frequency and indicator data, 49 keywords with high appearance frequency were extracted by analyzing frequency, via the term frequency-inverse document frequency technique in natural language processing, and words with simultaneous appearance frequency. The relationship degree was verified by analyzing the connection structure and centrality of the connection degree between words, and a cluster composed of words with similarity was derived via CONCOR analysis. First, "education," "research," "result," "utilization," and "analysis" were analyzed as main keywords. Second, by analyzing an N-GRAM network graph with "education" as the keyword, "curriculum" and "utilization" were shown to exhibit the highest correlation level. Third, by conducting a cluster analysis with "education" as the keyword, five groups were formed: "curriculum," "programming," "student," "improvement," and "information." These results indicate that practical research necessary for ICT education can be conducted by analyzing ICT education trends and identifying trends.

• Journal of The Korean Association For Science Education
• /
• v.10 no.2
• /
• pp.67-72
• /
• 1990

Correct comprehension of the scientific terms is the bottom of understanding the general concepts contained is them. Therefore a study is required to analyze whether the students correctly understand the scientific terms. The associative method was used to evaluate the comprehensibility of the terms. The scientific terms in this study are selected in the textbook of science in the junior high school were selected. The frequency of the same associative word responsed and the frequency of no response from the selected students for given scientific terms were measured for 9 different groups. The terms which are not used in the daily life, especially for the terms with chinese character or abstract terms turn out to be difficult for the students to understand. It is purposed that the instructor should remember the importance of understanding the scientific term and carefully explain them to the science class.

• Proceedings of the KIEE Conference
• /
• 2005.07e
• /
• pp.19-21
• /
• 2005

The purpose of power system design is, in a word, to provide a good quality of electric power. The design of reliable industrial and commercial power distribution system is important because of the high costs associated with power outage. Three major factors for realization of the purpose are: (1) To hold system frequency at or very close to a specified nominal value(e.g. 60Hz) by control of frequency-effective power. (2) To maintain the correct value of interchange power between power and local generators. (3) To hold system voltage at or very close to a specified nominal value by control of voltage-reactive power. Within the past decade, numbers of industrial and commercial facilities installed with local generation, large motors or both, are increasing. This means that system stability is of concern to a growing number of industrial plant electrical engineers and consultants.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.14 no.4
• /
• pp.89-95
• /
• 2005

This paper intends to identify experimentally the relationship between transverse vibration behavior of a spinning disk and high-frequency fluctuation in the driving torque. A testrig has been developed using a CD-ROM disk, a driving motor with torque-varying capability and a power transmission belt and a laser vibrometer was employed to measure the transverse vibration displacements of the disk for a certain range of the spinning speed. The results show that the spinning speed and the magnitude and frequency of the torque fluctuation affect the stability of the disk. In other word, the torque fluctuation causes the instability of the disk at several ranges of the spinning speed below the critical speed and its effects become larger as the disk spins faster or the magnitude of torque fluctuation becomes bigger. The experimental results are found to be in good agreement with analytical estimation.

• Phonetics and Speech Sciences
• /
• v.12 no.1
• /
• pp.33-42
• /
• 2020

This study identified the substitution of /u/ for /o/ (e.g., pyəllo [pyəllu]) in Korean based on the speech corpus as a function of grammar items. Korean /o/ and /u/ share the vowel feature [+rounded], but are distinguished in terms of tongue height. However, researchers have reported that the merger of Korean /o/ and /u/ is in progress, making them indistinguishable. Thus, in this study, the frequency of the phonetic manifestation /u/ of the underlying form of /o/ for each grammar item was calculated in The Korean Corpus of Spontaneous Speech (Seoul Corpus 2015) which is a large corpus from a total of 40 speakers from Seoul or Gyeonggi-do. It was then confirmed that linking endings, particles, and adverbs ending with /o/ in the word-final position were substituted for /u/ approximately 50% of the stimuli, whereas, in nominal items, they were replaced at a frequency of less than 5%. The high rates of substitution were the special particle "-do[du]" (59.6%) and the linking ending "-go[gu]" (43.5%) among high-frequency items. Observing Korean pronunciation in real life provides deep insight into its theoretical implications in terms of speech recognition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.508-512
• /
• 2003

In 2000, the economy of Asia made a V-character type recovery from the currency and financial crisis in 1997. The increase in exports is assumed to be one of the causes. To negotiate with foreign countries, English must be indispensable in many cases. In this study, we investigated how English education is performed in East Asian countries while focusing on English textbooks. We metrically analyzed some textbooks used junior high schools and high school in Japan and Korea, and elementary schools in China and Singapore to compare them with U.S.A and U.K textbook. We investigated some characteristics of character-and word-appearance of English textbook using an exponential function. Moreover we derived the degree of difficulty far each material through the variety of words and their frequency on the basis of the required English vocabulary in Japanese junior high schools. As a result we could show at which level of U.S.A. or U.K the English textbooks used in East Asian countries are.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.97-117
• /
• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.2E
• /
• pp.31-37
• /
• 1998

This paper proposes a feature extraction method using wavelet transform for speech recognition. Speech recognition system generally carries out the recognition task based on speech features which are usually obtained via time-frequency representations such as Short-Time Fourier Transform (STFT) and Linear Predictive Coding(LPC). In some respects these methods may not be suitable for representing highly complex speech characteristics. They map the speech features with same may not frequency resolutions at all frequencies. Wavelet transform overcomes some of these limitations. Wavelet transform captures signal with fine time resolutions at high frequencies and fine frequency resolutions at low frequencies, which may present a significant advantage when analyzing highly localized speech events. Based on this motivation, this paper investigates the effectiveness of wavelet transform for feature extraction of wavelet transform for feature extraction focused on enhancing speech recognition. The proposed method is implemented using Sampled Continuous Wavelet Transform (SCWT) and its performance is tested on a speaker-independent isolated word recognizer that discerns 50 Korean words. In particular, the effect of mother wavelet employed and number of voices per octave on the performance of proposed method is investigated. Also the influence on the size of mother wavelet on the performance of proposed method is discussed. Throughout the experiments, the performance of proposed method is discussed. Throughout the experiments, the performance of proposed method is compared with the most prevalent conventional method, MFCC (Mel0frequency Cepstral Coefficient). The experiments show that the recognition performance of the proposed method is better than that of MFCC. But the improvement is marginal while, due to the dimensionality increase, the computational loads of proposed method is substantially greater than that of MFCC.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.5 no.1
• /
• pp.41-46
• /
• 2011

A sensorineural hearing loss(SNHL) occurs when the cochlea in the inner has functional problem. The region in the cochlea with no(or very few) functioning inner hair cells or neurons called 'dead regions'. Amplification using hearing aid over a frequency range corresponding to a dead region may not a beneficial. In this paper, we compared speech recognition with different location of dead region and gain and searched effective gain for hearing aid with dead region. In order to experiment, eight people who has normal hearing ware tested, and we used white noise and babble noise(SNR=0 dB). we divided by three conditions, low, mid and high frequency dead region. In addition, the gains in dead region ware 14.5 dB, 11.5dB and 6 dB gain. There ware different results by location of dead region. The result of WRS and preference in mid-frequency dead region and high-frequency dead region ware higher than them in low-frequency dead region. When we compared as gains, the score of WRS with lower gain was higher than 14.5 dB gain, and the preference was lower as higher gain.