• Imaging Science in Dentistry
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• v.50 no.3
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• pp.227-236
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• 2020

Purpose: Image artifacts caused by patient motion cause problems in cone-beam computed tomography (CBCT) because they lead to distortion of the 3-dimensional reconstruction. This prospective study was performed to quantify patient movement during CBCT acquisition and its influence on image quality. Materials and Methods: In total, 412 patients receiving CBCT imaging were equipped with a wireless head sensor system that detected inertial, gyroscopic, and magnetometric movements with 6 dimensions of freedom. The type and amplitude of movements during CBCT acquisition were evaluated and image quality was rated in 7 different anatomical regions of interest. For continuous variables, significance was calculated using the Student t-test. A linear regression model was applied to identify associations of the type and extent of motion with image quality scores. Kappa statistics were used to assess intra- and inter-rater agreement. Chi-square testing was used to analyze the impact of age and sex on head movement. Results: All CBCT images were acquired in a 10-month period. In 24% of the investigations, movement was recorded (acceleration: >0.10 [m/s²]; angular velocity: >0.018 [°/s]). In all examined regions of interest, head motion during CBCT acquisition resulted in significant impairment of image quality (P<0.001). Movement in the horizontal and vertical axes was most relevant for image quality (R²>0.7). Conclusion: Relevant head motions during CBCT imaging were frequently detected, leading to image quality loss and potentially impairing diagnosis and therapy planning. The presented data illustrate the need for digital correction algorithms and hardware to minimize motion artefacts in CBCT imaging.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.43-50
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• 2014

In case of all patients who receive radiation therapy, a treatment plan is established and all steps of treatment are planned in the same geometrical condition. In case of head and neck cancer patients who undergo simulated treatment through computed tomography (CT), patients are fixed onto a table for planning, but laid on the top of the treatment table in the radiation therapy room. This study excogitated and fabricated an adjustable holder for head and neck cancer patients to fix patient's position and geometrical discrepancies when performing radiation therapy on head and neck cancer patients, and compared the error before and after adjusting the position of patients due to difference in weight to evaluate the correlation between patients' weight and range of error. Computed tomography system(High Advantage, GE, USA) is used for phantom to maintain the supine position to acquire the images of the therapy site for IMRT. IMRT 4MV X-rays was used by applying the LINAC(21EX, Varian, U.S.A). Treatment planning system (Pinnacle, ver. 9.1h, Philips, Madison, USA) was used. The setup accuracy was compared with each measurement was repeated five times for each weight (0, 15, and 30Kg) and CBCT was performed 30 times to find the mean and standard deviation of errors before and after the adjustment of each weight. SPSS ver.19.0(SPSS Inc., Chicago, IL,USA) statistics program was used to perform the Wilcoxon Rank test for significance evaluation and the Spearman analysis was used as the tool to analyze the significance evaluation of the correlation of weight. As a result of measuring the error values from CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.4{\pm}0.8mm$, $0.8{\pm}0.4mm$, 0 for 0Kg before the adjustment. In 15Kg CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.2{\pm}0.8mm$, $1.2{\pm}0.4mm$, $2.0{\pm}0.4mm$. After adjusting position was X,Y,Z axis was $0.2{\pm}0.4mm$, $0.4{\pm}0.5mm$, $0.4{\pm}0.5mm$. In 30Kg CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.8{\pm}0.4mm$, $2.4{\pm}0.5mm$, $4.4{\pm}0.8mm$. After adjusting position was X,Y,Z axis was $0.6{\pm}0.5mm$, $1.0{\pm}0mm$, $0.6{\pm}0.5mm$. When the holder for the head and neck cancer was used to adjust the ab.0ove error value, the error values from CBCT were $0.2{\pm}0.8mm$ for the X axis, $0.40{\pm}0.54mm$ for Y axis, and 0 for Z axis. As a result of statistically analyzing each value before and after the adjustment the value was significant with p<0.034 at the Z axis with 15Kg of weight and with p<0.038 and p<0.041 at the Y and Z axes respectively with 30Kg of weight. There was a significant difference with p<0.008 when the analysis was performed through Kruscal-Wallis in terms of the difference in the adjusted values of the three weight groups. As it could reduce the errors, patients' reproduction could be improved for more precise and accurate radiation therapy. Development of an adjustable device for head and neck cancer patients is significant because it improves the reproduction of existing equipment by reducing the errors in patients' position.

• Journal of the Mineralogical Society of Korea
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• v.30 no.2
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• pp.45-57
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• 2017

Two single crystals of fully dehydrated $Cd^{2+}$-exchanged zeolites Y were prepared by the exchange of ${\mid}Na_{75}{\mid}[Si_{117}Al_{75}O_{384}]-FAU$ ($Na_{75}-Y$, Si/Al = 1.56) with aqueous $0.05M\;Cd(NO_3)_2$ (pH = 3.65) at 294 K, followed by vacuum dehydration at 723 K (crystal 1) and a second crystal, similarly prepared, was exposed to zeolitically dried benzene for 72 hours at 294 K and evacuated (crystal 2). Their structures were determined crystallographically using synchrotron X-rays and were refined to the final error indices using $F_o$>$4{\sigma}(F_o)$ of $R_1/wR_2=0.040/0.121$ and 0.052/0.168, respectively. In crystal $1({\mid}Cd_{36}H_3{\mid}[Si_{117}Al_{75}O_{384}]-FAU)$, $Cd^{2+}$ ions primarily occupy sites I and II, with additional $Cd^{2+}$ ions at sites I', II', and a second site II. In crystal $2({\mid}Cd_{35}(C_6H_6)_{24}H_5{\mid}[Si_{117}Al_{75}O_{384}]-FAU)$, $Cd^{2+}$ ions occupy five crystallographic sites. The 24 benzene molecules are found at two distinct positions within the supercages. The 17 benzene molecules are found on the 3-fold axes in the supercages where each interacts facially with one of site IIa $Cd^{2+}$ ions. The remaining 7 benzene molecules lie on the planes of the 12-rings where each is stabilized by multiple weak electrostatic and van der Waals interactions with framework oxygens.

• Korean Journal of Crystallography
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• v.7 no.1
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• pp.8-19
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• 1996

Cholestryl Methyl and Propyl Carbonate(CH3OCOOC27H45, C3H7OCOOC27H45) are monoclinic, space group P21, with a=17.014(1), b=7.682(1), c=10.612(1)Å, β=103.05(1)°, Z=2, V=1351.16Å3, Dc=1.09 g/cm3 for methyl carbonate, and with a=13.683(1), b=11.864(2), c=18.904(2)Å, β=106.30(1)°, Z=4, V=2945.4Å3, Dc=1.06 g/cm3, Dm=1.06 g/cm3 for propyl carbonate. The intensity data were collected on an Enraf-Nonius CAD-4 diffractometer with a graphite monochromated Cu-Kα radiation. The structure was solved by direct methods and refined by full matrix least-squares methods. The final R factor was 0.051 for 2323 observed reflections for methyl carbonate and 0.074 for 3323 observed reflections for propyl carbonate. Compared with other cholesteryl derivatives, the cholesteryl ring and tail region of the molecules are normal. The molecules are stacked in clearly separated layers. At center of the layer, there are cholesteryl-C(17) side chain interactions. The interface region between layers is occupied by the loosely packed methyl carbonate chains. The structure of cholesteryl propyl carbonates have two propyl carbonates have two molecules(A, B) that are not related by crystal symmetry and have their tetracyclic system almost parallel to each other. Cholesteryl-cholesteryl interactions between symmetry related A-molecules, and cholesteryl-C(17) side chain interactions between symmetry related B-molecules occur at the center of the layers and these molecules stack along 2₁ screw axes. There are also C(17)chain-carbonate chain and C(17)chain-C(17)chain interactions in the interface region between layers. There is efficient packing between cholesteryl ring systems in propyl carbonates. Temperature ranges of cholesteric mesophases of cholesteryl alkyl cargonates are narrow for methyl, pentyl and hexyl carbonates, and rather broader for ethyl and propyl carbonates. Cholesteryl-isotropic transitions change very little with chain length.

• Progress in Medical Physics
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• v.9 no.2
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• pp.65-71
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• 1998

The aims are to evaluate the effects of an 1.0 cm acrylic plate and SSD on the dose profile and depth dose distribution of 9 MeV electron beam and to analyse adequacy for using an acrylic plate to reduce energy of electron beams. An acrylic plate of 1.0 cm thickness was used to reduce energy of 9 MeV electron beam to 7 MeV. The plate was put on an electron applicator at 65.4 cm distance from x-ray target. The size of the applicator was 10${\times}$l0cm at 100 cm SSD. For 100cm, l05cm and 110cm SSD, depth dose on beam axis and dose profiles at d$\_$max/ on two principal axes were measured using a 3D water phantom. From depth dose distributions, d$\_$max/, d$\_$85/, d$\_$50/ and R$\_$p/, surface dose, and mean energy and peak energy at surface were compared. From dose profiles flatness, penumbra width and actual field size were compared. For comparison, 9 MeV electron beams were measured. Surface dose of 7 MeV electron beams was changed from 85.5% to 82.2% increasing SSD from 100 cm to 110 cm, and except for dose buildup region, depth dose distributions were independent of SSD. Flatness of 7 MeV ranged from 4.7% to 10.4% increasing SSD, comparing 1.4% to 3.5% for 9 MeV. Penumbra width of 7 MeV ranged from 1.52 cm to 3.03 cm, comparing 1.14 cm to 1.63 cm for 9 MeV. Actual field size increased from 10.75 cm to 12.85 cm with SSD, comparing 10.32 cm to 11.46 cm for 9 MeV. Virtual SSD's of 7 and 9 MeV were respectively 49.8 cm and 88.5cm. In using energy reducer in electron therapy, depth dose distribution were independent of SSD except for buildup region as well as open field. In case of using energy reducer, increasing SSD made flatness to deteriorate more severely, penumbra width more wide, field size to increase more rapidly and virtual SSD more short comparing with original electron beam. In conclusion, it is desirable to use no energy reducer for electron beam, especially for long SSD.

• Journal of Korean Society of Forest Science
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• v.108 no.2
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• pp.147-167
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• 2019

This study was conducted to analyze forest vegetation structure in the Marugeum (Ridge) area of Gitdaebaegibong to Jukryeong, Baekdudaegan. Data were collected in 298 quadrates through a Braun-Blanquet vegetation survey from April, 2018 to October, 2018. Forest vegetation was classified into 13 vegetation units. A Quercus mongolica community was divided into Morus bombycis, Filipendula glaberrima, Fraxinus sieboldiana, Prunus maackii unit and Q. mongolica typical unit. The M. bombycis unit was further classified into a Deutzia glabrata group and M. bombycis typical group. The F. glaberrima unit was subdivided into a Veratrum oxysepalum group, Arundinella hirta group, and F. glaberrima typical group. The F. sieboldiana unit was divided into a Pinus densiflora group, Larix kaempferi group, and F. sieboliana typical group. The relationship between vegetation units and environmental factors was studied through coincidence analysis and CCA. The F. glaberrima unit (VU 6~8) was distributed by elevation above 1,200 m and other vegetation units were distributed below 1,200 m. Results of the CCA analysis showed that the F. glaberrima unit distribution is positively correlated with elevation. As a result of species diversity, the F. glaberrima unit was higher than other vegetation units. A similarity index analysis revealed that the F. sieboldiana unit (VU 9~11) was relatively homogeneous, and the M. bombycis unit (VU 1~5) and A. girta group (VU 7) were relatively heterogeneous. A detrended correspondence analysis determined that the distance between the statistical axes of the M. bombycis and F. glaberrima units was the greatest, which is consistent with the analysis of the similarity index. As a result of interspecific correlation of major woody plants, hydrophilic species were positively correlated, and a negative correlation was found between Q. mongolica and intolerant species such as P. densiflora and L. kaempferi.

• 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.