• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.39-47
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• 2008

With dramatic development of IT technology and start of DMB service, installing the DMB equipment in a vehicle for watching TV programs and literal or pictorial traffic information are increasing. Watching the DMB during driving the vehicle could cause visual and cognitive distraction to drivers as much as eating food, operating radio and using mobile phone. However, there is not much empirical research for this topic and no research examined the effect of watching the DMB on driving behaviors in Korea. So, the present study examined the effect of watching the DMB on the driving behaviors with car simulator experiment. Within subject design was used in the study. That is, all subjects drove the vehicle both in the watching DMB condition and the non-watching DMB condition. The results indicated that subjects in the watching DMB condition took longer time to arrive at the destination and operated accelerator and brake pedal rapidly than subjects in the non-watching DMB condition. That is, their overall driving stability was lower than non-watching subjects'. Additionally, we examined the difference among the DMB control conditions (i.e., keypad condition, touch-pad condition and remote controller condition) in the driving behaviors. Finally, we discussed the limitations and the implications of the present study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2507-2517
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• 2015

In this research, we aim to analyze the trend of Huawei's PCT patent applications. As a result of analyzing Huawei's PCT patents by dividing temporal spans into three periods - the early 2000s, the late 2000s, and the early 2010s -, the following characteristics have been observed. First, the number of PCT patent applications has conspicuously increased from the early 2000s to the late 2000s and this trend has continued during the early 2010s. Second, in terms of a core technological field, whereas Huawei focused on the development of technologies in the 'H04L: transmission of digital information' sector during the early/late 2000s, it changed this field to the 'H04W: wireless communication networks' sector during the early 2010s. Lastly, in the case of the patent maps, it was found that while general communications technologies, as expressed with such keywords as 'user' and 'network,' were actively developed during the early/late 2000s, mobile phone-related technologies grasped this leading position, as shown with the keywords including 'user equipment,' 'base station,' and 'MME,' during the early 2010s. It was also noticeable that Huawei filed LTE-related patent applications more actively than Apple and Samsung Electronics, which implies that it will presumably pioneer the global market more aggressively than its competitors in the future.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.53-55
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• 2004

In emergency cases, such as the severe trauma involving the fracture of skull, spine, or cervical bone, from auto accident or a fall, and/or pneumothorax which can not be diagnosed exactly by the eye examination, it is necessary the radiological examination during transferring to the hospital for emergency care. The aim of this study was to design and evaluate the prototype of mobile medical image communication system based on CDMA 1X EVDO. The system consists of a laptop computer used as a transmit DICOM client, linked with cellular phone which support to the CDMA 1X EVDO communication service, and a receiving DICOM server installed in the hospital. The DR images were stored with DICOM format in the storage of transmit client. Those images were compressed into JPEG2000 format and transmitted from transmit client to the receiving server. All of those images were progressively transmitted to the receiving server and displayed on the server monitor. To evaluate the image quality, PSNR of compressed image was measured. Also, several field tests had been performed using commercial CDMA2000 1X-EVDO reverse link with the TCP/IP data segments. The test had been taken under several velocity of vehicle in seoul areas.

• Asia pacific journal of information systems
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• v.24 no.3
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• pp.299-323
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• 2014

The reason location based service is drawing attention recently is because smart phones are being supplied increasingly. Smart phone, basically equipped with GPS that can identify location information, has the advantage that it can provide contents and services suitable for the user by identifying user location accurately. Offering such diverse advantages, location based services are increasingly used. In addition, for use of location based services, release of user's personal information and location data is essentially required. Regarding personal information and location data, in addition to IT companies, general companies also are conducting various profitable businesses and sales activities based on personal information, and in particular, personal location data, comprehending high value of use among personal information, are drawing high attentions. Increase in demand of personal information is raising the risk of personal information infringement, and infringements of personal location data also are increasing in frequency and degree. Therefore, infringements of personal information should be minimized through user's action and efforts to reinforce security along with Act on the Protection of Personal Information and Act on the Protection of Location Information. This study aimed to improve the importance of personal information privacy by empirically analyzing the effect of perceived values on the intention to strengthen location information security and continuously use location information for users who received location-based services (LBS) in mobile environments with the privacy calculation model of benefits and risks as a theoretical background. This study regarded situation-based provision, the benefit which users perceived while using location-based services, and the risk related to personal location information, a risk which occurs while using services, as independent variables and investigated the perceived values of the two variables. It also examined whether there were efforts to reduce risks related to personal location information according to the values of location- based services, which consumers perceived through the intention to strengthen security. Furthermore, it presented a study model which intended to investigate the effect of perceived values and intention of strengthening security on the continuous use of location-based services. A survey was conducted for three hundred ten users who had received location-based services via their smartphones to verify study hypotheses. Three hundred four questionnaires except problematic ones were collected. The hypotheses were verified, using a statistical method and a logical basis was presented. An empirical analysis was made on the data collected through the survey with SPSS 12.0 and SmartPLS 2.0 to verify respondents' demographic characteristics, an exploratory factor analysis and the appropriateness of the study model. As a result, it was shown that the users who had received location-based services were significantly influenced by the perceived value of their benefits, but risk related to location information did not have an effect on consumers' perceived values. Even though users perceived the risk related to personal location information while using services, it was viewed that users' perceived value had nothing to do with the use of location-based services. However, it was shown that users significantly responded to the intention of strengthening security in relation to location information risks and tended to use services continuously, strengthening positive efforts for security when their perceived values were high.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.