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In radiotherapy, when photon energy exceeding 8 MV is utilized, photoneutrons can activate the components within the gantry of the linear accelerator (linac). At the end of the linac's lifecycle, radiation workers are tasked with its dismantling and disposal, potentially exposing them to unintentional radiation. This study aims to identify and measure the radioisotopes generated by this activation through spectroscopy, and to evaluate the effective dose rate. We selected nine medical linacs, considering various factors such as manufacturer (Siemens, Varian, and Elekta), model, energy, period of operation, and workload. We identified the radionuclides in the linac head by employing an in situ high-purity germanium (HPGe) detector. Spectroscopy and dose-rate measurements were conducted post-shutdown. We also measured the dose rates at the beam-exit window following irradiation with 10 MV and 15 MV photon beams. As a result of the spectroscopy, we identified approximately 20 nuclides including those with half-lives of 100 days or longer, such as 54Mn, 60Co, 65Zn, 122Sb, and 198Au. The dose rate measurements after 10 MV irradiation decreased to the background level in 10 min. By contrast, on 15 MV irradiation, the dose rate was 628 nSv/h after 10 min and decreased to 268 nSv/h after 1.5 hours. It was confirmed that the difference in the level of radiation and the type of nuclide depends on the period of use, energy, and workload. However, the type of nuclide does not differ significantly between the linacs. It is necessary to propose appropriate guidelines for the safety of workers, and disposal/move-install should be planned while taking into consideration the equipment's energy usage rate.

Although research into ultrahigh dose-rate (UHDR) radiation therapy is ongoing, there is a significant lack of experimental measurements for two-dimensional (2D) dose-rate distributions. Additionally, conventional pixel-type detectors result in significant beam loss. In this study, we developed a pixel array-type detector with adjustable gaps and a data acquisition system to evaluate its effectiveness in measuring UHDR proton beams in real time. We measured a UHDR beam at the Korea Institute of Radiological and Medical Sciences using an MC-50 cyclotron, which produced a 45-MeV energy beam with a current range of 10–70 nA, to confirm the UHDR beam conditions. To minimize beam loss during measurement, we adjusted the gap and high voltage on the detector and determined the collection efficiency of the developed detector through Monte Carlo simulation and experimental measurements of the 2D dose-rate distribution. We also verified the accuracy of the real-time position measurement using the developed detector with a 226.29-MeV PBS beam at the National Cancer Center of the Republic of Korea. Our results indicate that, for a current of 70 nA with an energy beam of 45 MeV generated using the MC-50 cyclotron, the dose rate exceeded 300 Gy/s at the center of the beam, indicating UHDR conditions. Simulation and experimental measurements show that fixing the gap at 2 mm and the high voltage at 1000 V resulted in a less than 1% loss of collection efficiency when measuring UHDR beams. Furthermore, we achieved real-time measurements of the beam position with an accuracy of within 2% at five reference points. In conclusion, our study developed a beam monitoring system that can measure UHDR proton beams and confirmed the accuracy of the beam position and profile through real-time data transmission.

For the medical linear accelerators (linac) that utilize more than 10 MV of photon energy, components inside the linac head become radioactivate during the 10–15-year operating cycle. Prior to disposal, radioactive waste must be evaluated for activity, and the same procedure should be followed for medical linacs. In the Republic of Korea, regulation and methodology for the radioactivity evaluation for the medical linac is not established yet. In this study, we employed gamma spectroscopy and a survey meter for evaluating the radioactivity of medical linac components. The components of the Siemens linac considered in this study were classified after decommissioning, and dose rates were measured to up to a 5 cm distance from the component surfaces by using a survey meter. Radionuclides from components were detected using an in situ HPGe detector. Based on the type of radionuclides and dose rate, we estimated the radioactivity of the components. We studied the feasibility of the methodology for disposing of radioactive components by using the in situ HPGe detector.

The advancement of the Internet and technology has made it possible to purchase and use different types of products and services online instead of offline. In particular, as the scale of online shopping malls is rapidly increasing, new functions have been tried and introduced to compensate for the limitation of not being able to directly wear clothes in an online mall. Among them, 3D virtual try-on is an innovative service and its technology is being advanced with continuous interest. Technological advances and interest in 3D virtual try-on have led to a variety of related studies. Most previous studies on virtual try-on have been conducted on the virtual fitting technology from the perspective of making clothes, or the effects and customer behavior from the customer perspective. However, there has been no research based on actual data of customers using 3D virtual try-on to show how virtual try-on affects sales. Therefore, this study understands the fundamental meaning of virtual `try-on' as a customer experience and examines the effects of 3D virtual try-on on online sales. We create a 3D body model complemented by adding more diverse body shapes and sizes, and investigate the effects of virtual try-on on online sales through actual data. In addition, qualitative data including interviews are used to complement and interpret the results. The results show that virtual try-on affects the sales results: the average sales per customer increased by 14,000 won (13USD). The most important finding is that the return rate decreased by 27% by filtering out incorrect sizes and fits. Virtual try-on may very well replace physical fitting rooms. This study presents an advanced technology of 3D virtual try-on and shows that virtual try-on is an effective tool to boost sales and decrease customer's returns in a case study of women's casual L brand.

Three-dimensional printing technology has the advantage of facilitating the construction of complex three-dimensional shapes. For this reason, it is widely used in medical and radiological fields. However, few materials with high electron density similar to that of bone exist for fabricating a human phantom. In this study, commercially available filament materials were used with an FDM 3D printer to perform delivery quality assurance (DQA) and were evaluated for medical use. For the bone filament material, BaSO4 was synthesized in five ratios of 2%, 4%, 6%, 8%, and 10% with 40% PBAT and 50~58% PLA. The electron density for the 3D printing material fabricated was obtained using kV energy CT and compared with the electron density of human organs and bones. The radiation beam properties of the 3D printed structures were analyzed as films for treatment using a linear accelerator. As a result, by changing the infill density of the material, it was possible to produce a material similar to the density of human organs, and a homogeneous bone material with HU values ranging from 371 ± 9 to 1013 ± 28 was produced. The 3D printing material developed in this study is expected to be usefully applied to the development of a patient-specific phantom to evaluate the accuracy of radiotherapy.

Color-converted micro-LED displays consisting of mono-blue-colored micro LED arrays and color-conversion materials have been used to achieve full color while reliving the transfer and epitaxial growth of three different-colored micro LEDs. An efficient technique is suggested to deposit the color-conversion layers on the blue micro LEDs by using a mixture of photo-curable acrylic and nano-organic color-conversion materials through the conventional lithography technique. This study attempts to provide a solution to fabricate full-color micro-LED displays.

The automatic classification of cross-country (XC) skiing techniques using data from wearable sensors has the potential to provide insights for optimizing the performance of professional skiers. In this paper, we propose a unified deep learning model for classifying eight techniques used in classical and skating styles XC-skiing and optimize this model for the number of gyroscope sensors by analyzing the results for five different configurations of sensors. We collected data of four professional skiers on outdoor flat and natural courses. The model is first trained over the flat course data of two skiers and tested over the flat and natural course data of a third skier in a leave-one-out fashion, resulting in a mean accuracy of ~80% over three combinations. Secondly, the model is trained over the flat course data of three skiers and tested over flat course and natural course data of one new skier, resulting in a mean accuracy of 87.2% and 95.1% respectively, using the optimal sensor configuration (five gyroscope sensors: both hands, both feet, and the pelvis). High classification accuracy obtained using both approaches indicates that this deep learning model has the potential to be deployed for real-time classification of skiing techniques by professional skiers and coaches.

Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers' online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans' interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users.

The majority of the ground vehicles operating on the airside parts of commercial airports are currently powered by diesel engines. These include vehicles such as apron buses, fuel trucks, and aircraft tractors. Hence, these vehicles contribute to the overall CO 2 emissions of the aviation transport system and thus negatively influence its environmental footprint. To reduce this damaging environmental impact, these vehicles could potentially be electrified with on-board batteries as their energy sources. However, the conductive charging of such vehicles via stationary cable connections is rather time-consuming. A dynamic wireless charging system to supply public transportation passenger buses with electric energy while in motion has recently been installed on the Korea Advanced Institute of Science and Technology (KAIST) campus and in the Korean city of Gumi. In this paper, we study configuration problems related to the use of this technology to make airport operations more environmentally sustainable. We concentrate on the power supply for apron buses and analyze the location planning problems related to the distribution of the required power supply and the wireless charging units in the apron road system. To this end, we develop a formal optimization model and discuss the first numerical results.

This paper presents an initial investment cost analysis of public transportation systems operating with wireless charging electric vehicles (EVs). There are three different types of wireless charging systems, namely, stationary wireless charging (SWC), in which charging happens only when the vehicle is parked or idle, quasi-dynamic wireless charging (QWC), in which power is transferred when a vehicle is moving slowly or in stop-and-go mode, and dynamic wireless charging (DWC), in which power can be supplied even when the vehicle is in motion. This analysis compares the initial investment costs for these three types of charging systems for a wireless charging-based public transportation system. In particular, this analysis is focused on the energy logistics cost in transportation, which is defined as the cost of transferring and storing the energy needed to operate the transportation system. Performing this initial investment analysis is complicated, because it involves considerable tradeoffs between the costs of batteries in the EV fleet and different kinds of battery-charging infrastructure. Mathematical optimization models for each type of EV and infrastructure system are used to analyze the initial costs. The optimization methods evaluate the minimum initial investment needed to deploy the public transportation system for each type of EV charging solution. To deal with the variable cost estimates for batteries and infrastructure equipment in the current market, a cost-sensitivity analysis is performed. The goal of this analysis is to identify the market cost conditions that are most favorable for each type of wireless charging solution. Furthermore, the cost analysis quantitatively verifies the qualitative comparison of the three different wireless charging types conducted in the previous research.

In this paper, we present an analysis to identify a sensor location for an inertial measurement unit (IMU) on the body of a skier and propose the best location to capture turn motions for training. We also validate the manner in which the data from the IMU sensor on the proposed location can characterize ski turns and performance with a series of statistical analyses, including a comparison with data collected from foot pressure sensors. The goal of the study is to logically identify the ideal location on the skier’s body to attach the IMU sensor and the best use of the data collected for the skier. The statistical analyses and the hierarchical clustering method indicate that the pelvis is the best location for attachment of an IMU, and numerical validation shows that the data collected from this location can effectively estimate the performance and characteristics of the skier. Moreover, placement of the sensor at this location does not distract the skier’s motion, and the sensor can be easily attached and detached. The findings of this study can be used for the development of a wearable device for the routine training of professional skiers.

A real-time streaming feedforward active-noise-cancellation (ANC) system for an in-ear headphone was demonstrated in a real application scenario, by implementing a 10-layer dilated convolutional-neural-network (CNN) on a field programmable gate array (FPGA). A 16 × 16 systolic array was used in the FPGA, to speed up the model computation. The system latency was 170.6 μs, at the system clock frequency of 120 MHz. The CNN model used 3232 parameters. Due to the large input receptive field, of 327 ms, this work achieved total power reduction, of 14.8 dB and 14.3 dB at the noise incident direction of 0∘ and 90∘, respectively, and the noise attenuation bandwidth was 2000 Hz at both angles; all results were superior to those of the conventional FxLMS algorithm.

Study DesignRetrospective study.PurposeTo determine the prevalence of high risk patient with osteopenia requiring pharmacologic treatment and investigate the difference of 10-year fracture probability whether bone mineral density (BMD) include or not in Korean FRAX model.Overview of LiteratureMany people with the fracture have osteopenia rather than osteoporosis, and BMD alone could be considered as a chance to prevent fracture.MethodsThree hundred sixty-nine patients who was diagnosed as osteopenia were divided into two groups according to age (group 1, under 65 years; group 2, over 65 years), and 10-year fracture probabilities were calculated by FRAX algorithm with and without femur neck T-score.ResultsThe high risk patients of the fracture who had above 3% of 10-year hip fracture probability were 15 cases in group 1 and 121 cases in group 2. In 193 patients of group 1, the mean 10-year fracture probability with BMD was significantly higher than the results without BMD (hip fracture: p=0.04, major osteoporotic fracture: p=0.01). Unlike the results of the group 1, the mean 10-year fracture probability without BMD was significantly higher than the results with BMD in 176 patients of group 2 (hip fracture: p=0.01, major osteoporotic fracture: p=0.01).ConclusionsTotal of 136 cases (36.8%) as a high risk of the fracture with osteopenia could be overlooked treatment eligibility in Korean. The Korean FRAX model without BMD could be effective in predicting fracture risk especially in the individuals who were over 65 years.

BackgroundPain on propofol injection is a well-known adverse effect. We evaluated the clinical factors that affect the pain on injection of propofol to develop a strategy to prevent or reduce pain.MethodsWe conducted a prospective, observational study of 207 adult patients (ASA I-II), and the patients were classified according to gender, age, the body mass index (BMI), the IV site and the side of the IV site. During the 10 seconds after propofol injection, pain intensity was measured on an 11-point numerical rating scale (0 = no pain and 10 = worst possible pain). Pain in excess of 3 on the numerical scale was regarded as moderate to severe pain.ResultsThe subgroups of gender (female: 55.6% vs. male: 25.0%; P < 0.01) and the IV site (dorsum of hand: 61.2% vs. wrist: 40.0% vs. antecubital fossa: 22.5%; P < 0.01) had significantly different frequencies for the incidence of pain on injection on the univariate and multivariate analyses. For the subgroup of females, the incidence of pain was statistically different according to the age group (20-40 yr: 71.0% vs. 41-60: 54.8% vs. 61-80: 38.5%; P = 0.014).ConclusionsOur results showed that the younger age patients, the patients with a peripheral IV site and female patients are more sensitive to pain on the injection of propofol.