• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.1-8
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• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.98-104
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• 2004

When a straight-in landing from an instrument approach using ILS or VOR/DME is not possible or desirable because of topographical reason or bad weather, a circling approach maneuver is initiated by the pilot to align the aircraft with a runway for landing. Visual contact with the runway is necessary while conducting a circle to land maneuver. This research is to develop a new warning system based on a convention marker system which alerts pilots to watch out for exceeding the circling approach area. The airborne system also uses the same receiver unit without any new installations. The objective of this research is to design and develop a Yagi antenna in a special form. The research includes computer simulations to determine the size of antenna radiation pattern and to compute an expected flight path in case of alarm to validate effectiveness of the system.

• International journal of thyroidology
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• v.11 no.2
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• pp.130-136
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• 2018

Background and Objectives: Intraoperative neural monitoring (IONM) of recurrent laryngeal nerve (RLN) in thyroid surgery has been employed worldwide to identify and preserve the nerve as an adjunct to visual identification. The aims of this study was to evaluate the efficacy of IONM and difficulties in the learning curve. Materials and Methods: We studied 63 patients who underwent thyroidectomy with IONM during last 2 years. The standard IONM procedure was performed using NIM 3.0 or C2 Nerve Monitoring System. Patients were divided into two chronological groups based on the success rate of IONM (33 cases in the early period and 30 cases in the late period), and the outcomes were compared between the two groups. Results: Of 63 patients, 32 underwent total thyroidectomy and 31 thyroid lobectomy. Failure of IONM occurred in 9 cases: 8 cases in the early period and 1 case in the late period. Loss of signal occurred in 8 nerves of 82 nerves at risk. The positive predictive value increased from 16.7% in the early period to 50% in the late period. The mean amplitude of the late period was higher than that of the early period (p<0.001). Conclusion: IONM in thyroid surgery is effective to preserve the RLN and to predict postoperative nerve function. However, failure of IONM and high false positive rate can occur in the learning curve, and the learning curve was about 30 cases based on the results of this study.

• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1393-1398
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• 2018

In conventional single-photon emission computed tomography (SPECT), only the photoelectric events in the detectors are used for image reconstruction. However, if the $^{131}I$ isotope, which emits high-energy radiations (364, 637, and 723 keV), is used in nuclear medicine, both photoelectric and Compton scattering events can be used for image reconstruction. The purpose of our work is to perform simulations for Compton SPECT by using the Geant4 application for tomographic emission (GATE). The performance of Compton SPECT is evaluated and compared with that of conventional SPECT. The Compton SPECT unit has an area of $12cm{\times}12cm$ with four gantry heads. Each head is composed of a 2-cm tungsten collimator and a $40{\times}40$ array of CdZnTe (CZT) crystals with a $3{\times}3mm^2$ area and a 6-mm thickness. Compton SPECT can use not only the photoelectric effect but also the Compton scattering effect for image reconstruction. The correct sequential order of the interactions used for image reconstruction is determined using the angular resolution measurement (ARM) method and the energies deposited in each detector. In all the results of simulations using spherical volume sources of various diameters, the reconstructed images of Compton SPECT show higher signal-to-noise ratios (SNRs) without degradation of the image resolution when compared to those of conventional SPECT because the effective count for image reconstruction is higher. For a Derenzo-like phantom, the reconstructed images for different modalities are compared by visual inspection and by using their projected histograms in the X-direction of the reconstructed images.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.513-522
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• 2022

The purpose of this study is to evaluate the accessibility of the Cakewalk TTS-1 for the screen reader users. An evaluation was performed by testing the accessibility of a editing virtual instrument that is a part of MIDI production based on the NCS(National Competency Standards) by using the TTS-1 and the Sense Reader. The results of this study are as follows. The TTS-1 itself can't provide enough accessibility for the screen users to do an above task. But the screen reader users can perform the above tasks if they use extended access functions like Sense Reader's Mouse Pointer function, Position Memory function and MIDI Control Signal function. Even if they use the extended access function, there are functions that is difficult to access. To solve this problem, several suggestions are proposed.

• Journal of radiological science and technology
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• v.44 no.6
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.

• Physical Therapy Korea
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• v.30 no.3
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• pp.221-229
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• 2023

Background: In modern society, the use of computers accounts for a large proportion of our daily lives. Although substantial research is being actively conducted on musculoskeletal diseases resulting from computer use, there has been a recent surge in interest in improving the working environment for prevention. Objects: This study aimed to examine the effects of posture correction feedback (PCF) on changes in neck posture and muscle activation during computer typing. Methods: The participants performed a computer typing task in two sessions, each lasting 16 minutes. The participant's dominant side was photographed and analyzed using ImageJ software to verify neck posture. Surface electromyography (EMG) was used to confirm the participant's cervical erector spinae (CES) and upper trapezius muscle activities. The EMG signal was analyzed using the percentage of reference voluntary contraction and amplitude probability distribution function (APDF). In the second session, visual and auditory feedback for posture correction was provided if the neck was flexed by more than 15° in the initial position during computer typing. A 20-minute rest period was provided between the two sessions. Results: The neck angle (p = 0.014), CES muscle activity (p = 0.008), and APDF (p = 0.015) showed significant differences depending on the presence of the PCF. Furthermore, significant differences were observed regarding the CES muscle activity (p = 0.001) and APDF (p = 0.002) over time. Conclusion: Our study showed that the feedback system can correct poor posture and reduces unnecessary muscle activation during computer work. The improved neck posture and reduced CES muscle activity observed in this study suggest that neck pain can be prevented. Based on these results, we suggest that the PCF system can be used to prevent neck pain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2627-2642
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• 2023

Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.

• The Journal of the Acoustical Society of Korea
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• v.29 no.8
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• pp.504-508
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• 2010

In conventional diagnostic ultrasound strain imaging, when displaying strain image on a monitor, human visual characteristics are utilized such that hard regions are displayed as dark and soft regions are displayed as bright. Thus, hard regions representing tumor or cancer are displayed as dark, decreasing the contrast inside the lesion. Because the lesion area is stiff and thus displayed as dark, a method of inverting the image brightness and thereby increasing the contrast in the lesion for better diagnostic purposes is proposed wherein a postcompression signal is extended in the time domain by a factor corresponding to the reciprocal of the amount of the applied compression using a technique termed globally uniform stretching. Experiments were carried out to verify the proposed method on an ultrasound elasticity phantom with radio-frequency data acquired from a diagnostic ultrasound clinical scanner. It is found that the new method improves the contrast-to-noise ratio by a factor of up to about 1.8 compared to a conventional strain imaging method that employs a reversed gray color map without globally uniform stretching.