• Journal of Digital Convergence
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• v.18 no.2
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• pp.151-162
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• 2020

In this paper, a research model was designed to investigate the factors affecting the purpose intentions to the online paid knowledge contents in China. The research model includes the contents characteristics, recognition of copyright, recognition of paid, the theory of planned behavior factors. In this research, the data was collected by online survey, and in final analysis, 457 users' questionnaires were used. The empirical paper proves research hypothesis by using SPSS 25.0 and AMOS 23.0. The results of the study are as follows: the contents characteristics partially give positive effects to attitude. In addition, recognition of paid and planning behavior theory factors have positive effects to purpose intentions. This paper provides a useful scheme to promotion the purpose of purchase for paid online knowledge contents.

• Korean Journal of Agricultural Science
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• v.30 no.1
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• pp.102-113
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• 2003

Various government-based consulting techniques are being adapted to increase competitive power and to achieve management innovation of Korean farms. These business consulting services are offered by free or paid consulting. This study focuses on what socio-economic characteristics are affecting farmers' intension of adapting consulting services, based on 169 surveyed data from Chunchungnam-do. Logit Model is used to identify the relationship between the probability of consulting intent and factors representing farm characteristics. The model was applied on each of free and paid consulting. According to the results, degree of consulting recognition, age, education, raised crop are significant factors affecting farmers' intension of adapting consulting service in the case of free consulting at 10% of significance level. In the case of paid consulting, level of farming, age, income, insufficiency of farming, and education were identified as significant factors. In terms of elasticity of each variable, most variables for free consulting service are inelastic to consulting intent, whereas age, level of farming, and education are elastic for paid consulting service. Overall results implies that more public relations are required to activate free consulting services for the farms with moderate level of farming. In the case of paid consulting, it is effective to adapt consulting services for younger farms with higher level of farming and education.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.99-102
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• 2005

Research efforts have been made for out-of-vocabulary word rejection to improve the confidence of speech recognition systems. However, little attention has been paid to non-recognition sentence rejection. According to the appearance of pronunciation correction systems using speech recognition technology, it is needed to reject non-recognition sentences to provide users with more accurate and robust results. In this paper, we introduce standard phoneme based sentence rejection system with no need of special filler models. Instead we used word spotting ratio to determine whether input sentences would be accepted or rejected. Experimental results show that we can achieve comparable performance using only standard phoneme based recognition network in terms of the average of FRR and FAR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.451-457
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• 2020

Format recognition and OCR techniques are widely used as methods for detecting and protecting personal information from electronic documents. However, due to the poor recognition rate of the OCR engine, personal information cannot be detected or false positives commonly occur. It also takes a long time to analyze a large amount of electronic documents. In this paper, we propose a method to improve the speed of image analysis of electronic documents, character recognition rate of the OCR engine, and detection rate of personal information by improving the existing method. The analysis speed was increased using the format recognition method while the analysis speed and character recognition rate of the OCR engine was improved by image correction. An algorithm for analyzing personal information from images was proposed to increase the reconnaissance rate of personal information. Through the experiments, 1755 image format recognition samples were analyzed in an average time of 0.24 seconds, which was 0.5 seconds higher than the conventional PAID system format recognition method, and the image recognition rate was 99%. The proposed method in this paper can be used in various fields such as public, telecommunications, finance, tourism, and security as a system to protect personal information in electronic documents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2824-2838
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• 2013

There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

• Speech Sciences
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• v.7 no.3
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• pp.69-85
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• 2000

Recently, Computer Assisted Language Learning (CALL) received widely held attention from diverse audiences. However, to the author's knowledge, relatively little attention was paid to the educational implications of voice recognition (VR) softwares in language teaching in general, and teaching and learning pronunciation in particular. This study explores, and extends the applicability of VR softwares toward second language research areas addressing how VR softwares might facilitate interview data entering processes. To aid the readers' understanding in this field, the background of classroom interaction research, and the rationale of why interview data, therefore the role of VR softwares, becomes critical in this realm of inquiry will be discussed. VR softwares' development and a brief report on the features of up-to-date VR softwares will be sketched. Finally, suggestions for future studies investigating the impact of VR softwares on second language learning, teaching, and research will be offered.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.439-443
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• 2007

Nowadays, activity recognition becomes a hot topic in context-aware computing. In activity recognition, machine learning techniques have been widely applied to learn the activity models from labeled activity samples. Most of the existing work uses only one learning method for activity learning and is focused on how to effectively utilize the labeled samples by refining the learning method. However, not much attention has been paid to the use of multiple classifiers for boosting the learning performance. In this paper, we use two methods to generate multiple classifiers. In the first method, the basic learning algorithms for each classifier are the same, while the training data is different (ASTD). In the second method, the basic learning algorithms for each classifier are different, while the training data is the same (ADTS). Experimental results indicate that ADTS can effectively improve activity recognition performance, while ASTD cannot achieve any improvement of the performance. We believe that the classifiers in ADTS are more diverse than those in ASTD.

• MALSORI
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• no.59
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• pp.27-51
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• 2006

For speech recognition systems, rejection function as well as decoding function is necessary to improve the reliability. There have been many research efforts on out-of-vocabulary word rejection, however, little attention has been paid on non-target sentence rejection. Recently pronunciation approaches using speech recognition increase the need for non-target sentence rejection to provide more accurate and robust results. In this paper, we proposed filler model method and word/phoneme detection ratio method to implement non-target sentence rejection system. We made performance evaluation of filler model along to word-level, phoneme-level, and sentence-level filler models respectively. We also perform the similar experiment using word-level and phoneme-level word/phoneme detection ratio method. For the performance evaluation, the minimized average of FAR and FRR is used for comparing the effectiveness of each method along with the number of words of given sentences. From the experimental results, we got to know that word-level method outperforms the other methods, and word-level filler mode shows slightly better results than that of word detection ratio method.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.3
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• pp.219-237
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• 2021

Visual information is widely used to deliver health information more effectively on social media, but there is lack of research on how effectively visual information delivers health information on social media. This study reports Facebook users' reading patterns and cognitive tests (recall and recognition tests) results using health-related Facebook posts. For this study, 21 college students participated in online questionnaire, eye tracking experiment, and recall and recognition tests. First, users paid their attention to the area that contains information (i.e., users focused on the main text rather than photos that do not contain information). Second, in the case of Facebook posts containing infographics, users paid their attention on the infographics, but the recall and recognition test results of the posts with infographics were lower than the posts containing photos. Particularly, when the infographics are in a complex collage format, recall and recognition tests result lower scores. Third, regarding the length of the text, the Facebook posts with short text resulted in higher recall and recognition test scores than the posts with medium or long texts. This study suggested to Facebook health information providers and distributors how to design Facebook posts for delivering health information more effectively.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.271-274
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• 1998

Ultrasonic sensors are becoming indispensable components in every sector of automation equipments due to many advantages. But the main purposes of the noncontact sensing device are rather narrowly confined within object detection and distance measurement. To widen the realm of the applications to object recognition, ultrasonic sensors need to improve the recognition resolution to a certain amount. To resolve the problem of spatial resolution restriction, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensor has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. For an object recognition using ultrasonic sensors, measurements of distance, shift, oblique angle in certain ranges should be obtained. But a little attention has been paid to the measurement of angles. In this paper we propose a practical method for an object angular value detection in addition to distance measurement in ultrasonic sensor array system with little additional hardware burden. Using the established measurement look-up table for the variations of distance, shift, angle and transmitter voltages for each sensor characteristics, a set of different return echo signals for adjacent receivers are processed to provide enhanced angular value reading for an object.