• The Korean Journal of Vision Science
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• v.20 no.4
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• pp.461-468
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• 2018

Purpose : Tourmaline, a natural ore material, was applied to the entire eyeglasses to observe changes in intraocular pressure (IOP), one of the factors related to human ocular metabolism. Methods : After making eyeglass frames by mixing TR-90, which is the main material of eyeglass frames and 7wt% of tourmaline, The changes of intraocular pressure before and after wearing of tourmaline spectacle frames were divided into low, middle and high groups according to the intraocular pressure in 90 normal subjects (46 men and 44 women) in their 20s. Results : Total intraocular pressure was a significantly decreased to -4.14% (p<0.000) in the right eye after wearing tourmaline frames, and significantly decreased to -6.39 % (p<0.000) and -4.64 % (p<0.017) in the High and Middle groups, respectively. Total intraocular pressure was a significantly decreased to -2.74 % (p<0.004) in the left eye, and -4.58 % (p<0.000) in the High group only showed statically significant value. Conclusion : In this study, the spectacle frame containing 7wt% tourmaline was used and it was confirmed that the intraocular pressure was significantly decreased after wearing the spectacle frame, and it became close to the average value of the normal intraocular pressure range. The results of this study showed that tourmaline, which has the effect of promoting the metabolism and blood circulation of the body, has an effect on the normalization of the intraocular pressure by attaching it to the spectacle frame.

• Journal of Korean Ophthalmic Optics Society
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• v.19 no.2
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• pp.207-216
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• 2014

Purpose: In this study, we analyzed visual acuity of children according to the rearing of the type of parents. Methods: We have done a comparative analysis about before and after of corrected visual acuity according to the wearing actual conditions with the Korean National Health and Nutrition Examination Survey 2010 document. Results: Visual acuity before correction of twoparent family's children was 0.91, single parent family's children was 0.83, grandparents family's children was 0.77 in low income and twoparent family's children was 0.80, single parent family's children was 0.77, grandparents family's children was 0.50 in lower middle income. Conclusions: In the rearing of low-income children, the lack of attention to visual acuity management according to the type of parents leads to a failing of visual acuity in myopia. The role of the parents is very important during this time period, so it is necessary to provide social interest giving decline prevention of vision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.476-482
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• 2017

This study examined the effects of the seat height of a chair on the muscle activity of the erector spinae and rectus abdominis. Thirty healthy subjects were asked to sit on chairs at three different seat heights. The muscle activities of both the erector spinae and rectus abdominis were measured by surface electromyography. The data were analyzed by repeated one way ANOVA and the muscle activity was compared according to the seat height. The alpha level was set to 0.05. The results showed that the muscle activities of the erector spinae were not significantly different among the three seat heights. The muscle activities of the rectus abdominis were significantly different among the three seat heights. Both the rectus abdominis muscle activities were significantly greater in the low seat height than the other seat heights. These results showed that the seat height of the chair affects the muscle activities of the rectus abdominis muscle, leading to musculoskeletal pain, such as low back pain. Therefore, the seat height of a chair with a correct sitting position is important for preventing musculoskeletal pain.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.187-198
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• 2017

In this study, we analyzed the accessibility of open platform Android mobile banking applications, based on Korean mobile application accessibility KS standard, Section 508 technical standard of Rehabilitation Act, and European BBC guidelines. Experimental result showed that there are no mobile banking applications of 8 commercial banks in Korea that satisfy all guidelines of three standards. Typical violations included missing alternative text, keyboard focus violations, control size and spacing non-compliance, and low contrast ratio. These violations are fatal in that they make the accessibility of the blind, the disabled and the low vision and the elderly impossible. The reason that mobile banking applications do not comply with accessibility is that mobile application developers and providers have low awareness of accessibility and do not know how to implement accessibility properly. Comparing Korea mobile application accessibility guidelines with the revised standard of the Section 508 of Rehabilitation Act and the BBC standard, many guidelines are missing. Also, evaluation criteria are ambiguous and abstract, making it difficult for developers to refer specifically. Therefore, improving mobile application accessibility requires developer and government efforts and complementation of standards.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• Korean Journal of Materials Research
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• v.32 no.8
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• pp.345-353
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• 2022

In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO₄ nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.

• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.11-19
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• 2024

Demand for small biomimetic robots that can carry out reconnaissance missions without being exposed to the enemy in underground spaces and narrow passages is increasing in order to increase the fighting power and survivability of soldiers in wartime situations. A small compound eye image sensor for environmental recognition has advantages such as small size, low aberration, wide angle of view, depth estimation, and HDR that can be used in various ways in the field of vision. However, due to the small lens size, the resolution is low, and the problem of resolution in the fused image obtained from the actual compound eye image occurs. This paper proposes a compound eye image quality enhancement algorithm based on Image Enhancement and ESRGAN to overcome the problem of low resolution. If the proposed algorithm is applied to compound eye image fusion images, image resolution and image quality can be improved, so it is expected that performance improvement results can be obtained in various studies using compound eye cameras.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.2
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• pp.103-110
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• 2005

Binocular vision had a short history in Korea. As there were many near works in these days, the needs about comparative study have been increased. There was related to both refractive error and binocular anomalies, but it is difficult to applying for binocular vision expected findings in itself due to the fact that Korean differ from foreigner. Objects were 100 adults in 18-36 years old ages, The test was Von Gaefe method and used aparatus was phoropter(Shinnippon VT10)and visual chart(Shinnippon CT30). According to interview results was that symptom in near works were headaches 28.0%, blinking 27.3%, red eye 25.1%, eyepain 15.6%, watering 15.3%, itch 12.2%, photophobia 8.5% and eye strain 7.4%. A people who have above ${\pm}0.50$ D refractive error in total objectives (100-male 45/female 55) were classified into ametropia. There was a results such as emmetropia (12.0%), ametropia(88.0%), exophoria(32.0%), esophoria(12.0%). Far negative relative convergence were that in case of high 43.0%, in case of low 7.0%. Far positive relative convergence were that in case of high 15.0%, in case of low 38.0%. Near phoria was exophoria(32.0%), esophoria(12.0%). Near negative relative convergence were that in case of high 23.0%, in case of low 38.0%. Far positive relative convergence were that in case of high 29.0%, in case of low 23.0%. Near negative relative accommodation were that in case of high 10.0%, in case of low 14,0%, Far positive relative convergence were that in case of high 69.0%, in case of low 12.0%. Results were different from expected findings, and especially positive relative accommodation was very high, However, We suggest that the expected findings in Korea for several subjects must study in binocular function.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1207-1212
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• 2013

The purpose of this study was to examine the effect of transcutaneous electrical nerve stimulation (TENS) according to frequency and intensity on postural sway distance and velocity. TENS was applied to posterior aspect of the dominant leg with postural sway during one leg stance. Twenty-four healthy participants were measured while standing on a force platform with 5 different stimulation dosages of no TENS, high frequency and high intensity, high frequency and low intensity, low frequency and high intensity, low frequency and low intensity applied in 30 seconds. The five different dosages were performed with vision in random order. The results indicated that TENS dosage in the high frequency and low intensity had a significant decrease in postural sway(p<.05). From these results, we concluded that TENS delivered a high frequency and low intensity enhanced the postural sway in healthy adults. We expect that the postural sway of patients with decreased balance will reduce by application of TENS.