• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.361-375
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• 2013

While the mobile application market is growing fast, the revenues of the majority apps are declining. Moreover, paid mobile application prices and purchases have been slow because of intensifying competition. However, the conventional studies focused only on the acceptance factor of mobile applications, so they cannot explain the phenomenon such as acceptance resistance for paid mobile applications. Therefore, our study tries to analyze the factors for the acceptance resistance of users for paid mobile applications. The research model in this paper, which is based on S-O-R model, verified through surveys how social influence and app characteristics affect user perception and how user perception affects to app resistance. The results of our study showed that paid mobile applications happened to be destroyed in front of the chasm because of the perceived loss. Consequently, the results implicate that the developers should lower the initial price and actively react to the negative reviews in order to lower the perceived loss. Moreover, the results verified that a sense of self-efficacy can lower application acceptance resistance by including personal properties to our research model as control variables.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.59-67
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• 2018

There are not that many m-health related services limited to the elderly. Many of the elderly who are at risk of dementia are unfamiliar to smart devices, so it is required to design an user-customized App. Therefore, I design and embody a mobile voice alert integrated app, which enables voice input to increase the accessibility of the elderly, so as to prevent diseases caused by declined cognitive function such as dementia. I conducted interviews and questionnaire after having the students use the app in Lifelong Education Center in H region of Gyeongbuk, and the analysis result has showed the high satisfaction. It is expected that it will be able to play a key role for M-Health service for the elderly since it is possible to prevent dementia through the voice health care alert app. I would like to learn deep learning in the future to predict the life patterns and the possibility of dementia of the elderly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2946-2952
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• 2014

Among the Example based Super Resolution(SR) techniques, Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the Learning Sparse-Neighbor Image Representation baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we first use bicubic interpolation to synthesize its high resolution version. We extract the patches from this synthesized image and determine whether each patch corresponds to regions with high or low spatial frequencies. After the weight of each patch is obtained by our method, we used to learn separate SVR models. Finally, we update the pixel values using the previously learned SVRs. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.209-214
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• 2013

Improve the recognition performance of speech recognition systems as a method for recognizing human listening skills were incorporated into the system. In noisy environments by separating the speech signal and noise, select the desired speech signal. but In terms of practical performance of speech recognition systems are factors. According to recognized environmental changes due to noise speech detection is not accurate and learning model does not match. In this paper, to improve the speech recognition feature extraction using gamma tone and learning model using acoustic model was proposed. The proposed method the feature extraction using auditory scene analysis for human auditory perception was reflected In the process of learning models for recognition. For performance evaluation in noisy environments, -10dB, -5dB noise in the signal was performed to remove 3.12dB, 2.04dB SNR improvement in performance was confirmed.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.1
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• pp.57-66
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• 2014

This study has been conducted to identify the current status and practices of electrical stimulation for patients with dysphagia in Korea. Main goal of the study is to find evidences of developing and distributing a quality indicator and organized performance exam. This study analyzed 50 survey questionnaires given to clinical professionals in upper-scale general hospitals, university hospitals, nursing homes and professional rehabilitation hospitals. The survey sent out and collected by E-mails or interviews from August 21, 2013 to November 10, 2013. Most of the hospitals showed lack of using a quality indicator and organized performance exams in device maintenance, pre-operational tests and post-operational tests. It is strongly recommended to develop a standardized guideline of a higher quality indicator and organized performance exam in using neuromuscular electrical stimulator for patients who are suffering from dysphagia.

• Journal of Pharmacopuncture
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• v.11 no.4
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• pp.59-64
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• 2008

Objectives The aim of study was to evaluate the effect of Herbal medicine on post stroke cognitive deficit. Methods All groups were treated with acupunture treatment, moxa treatment, herbal medicines, physical and occupational therapy for 4 weeks, additionally cardiotonic pills(CP) were taken in the cardiotonic pills group. The effect of treatment was assessed using Verval fluency, MMSE-KC, Word List Immediate Recall test. Statistical significance was achived if the probability was less than 5%(p,0.05). Results Verval fluency, MMSE-KC, Word List Immediate Recall test scores increased in both group. MMSE-KC, Word List Immediate Recall test scores were significantly increased in the CP group. Verval fluency, MMSE-KC, Word List Immediate Recall test scores were significantly increased in the control group. In the Verval fluency, MMSE-KC, Word List Immediate Recall test of the CP group more increased compared to the control group. There were no significant differences between two groups. In the CP group, the scores of the infarction group more increased compared to the hemorrhage group. Conclusions According to the these results, herbal medicines are effective to improve post stroke cognitive-deficit. Futher studies are needed to know cardiotonic pills in the ischemic stroke.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1017-1022
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• 2018

In this paper, a single house fire alarm device, which can solve the problem of fire perception at midnight time and the attenuation of alarm signal due to the wall between rooms based on the wireless communication, was developed. The radio controlled fire alarm device was designed to allow fire to be recognized quickly and accurately by monitoring the temperature and $CO_2$ concentration based on the temperature sensor and gas sensor, by detecting the fire in the house and by transmitting the fire alarm to the individual wireless alarms of other rooms using the wireless transmission/reception module. Using the Arduino as a main control device, three independent fire alarm device prototypes were made, and their usefulness was verified by the correct operations in temperature and gas tests.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1139-1145
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• 2014

User recognition technology, which identifies or verifies a certain individual is absolutely essential under robotic environments for intelligent services. The conventional face recognition algorithm using single distance face image as training images has a problem that face recognition rate decreases as distance increases. The face recognition algorithm using face images by actual distance as training images shows good performance but this has a problem that it requires user cooperation. This paper proposes the LDA-based long distance face recognition method which uses multiple distance face images from a zoom camera for training face images. The proposed face recognition technique generated better performance by average 7.8% than the technique using the existing single distance face image as training. Compared with the technique that used face images by distance as training, the performance fell average 8.0%. However, the proposed method has a strength that it spends less time and requires less cooperation to users when taking face images.

• Journal of KIISE
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• v.43 no.1
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• pp.27-33
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• 2016

Virtualization has become one of the most helpful techniques in computing systems, and today it is prevalent in several computing environments including desktops, data-centers, and enterprises. However, since I/O layers are implemented to be oblivious to the I/O behaviors on virtual machines (VM), there still exists an I/O scalability issue in virtualized systems. In particular, when a multi-queue solid state drive (SSD) is used as a secondary storage, each system reveals a semantic gap that degrades the overall performance of the VM. This is due to two key problems, accelerated lock contentions and the I/O parallelism issue. In this paper, we propose a novel approach, including the design of virtual CPU (vCPU)-dedicated queues and I/O threads, which efficiently distributes the lock contentions and addresses the parallelism issue of Virtio-blk-data-plane in virtualized environments. Our approach is based on the above principle, which allocates a dedicated queue and an I/O thread for each vCPU to reduce the semantic gap. Our experimental results with various I/O traces clearly show that our design improves the I/O operations per second (IOPS) in virtualized environments by up to 155% over existing QEMU-based systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6066-6075
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• 2014

The aim of this study was to analyze the productivity changes in government-funded research institutes for Economics & Humanities and Social Sciences. From Malmquist total factor productivity index analysis, the average productivity decreased 6.5% between 2006 and 2010. Further analysis showed that technical efficiency increased 4.7% annually while the technology change rate decreased 10.8% on average. Under pressure for innovation from the outside, research institutes responded to managerial efficiency improvement, which lead to increases in technical efficiency. On the other hand, for productivity improvement of government funded research institutes, they must pursue technological advances by securing an outstanding research workforce, expanding the R&D budget, and changing the R&D method. Each institute must perceive the cause of an individual institute's productivity change, and establish strategies for increasing productivity.