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This work investigates the effect of a frequency selective surface (FSS) composed of a regular array of square loop elements on the absorption properties of grounded ferrite composites. Polymer matrix composites of CoZnW hexaferrite powders having small magnetic loss were used as the substrate material. Computational tools were used to model the interaction between electromagnetic waves and materials and determine the reflection coefficient. Reflection loss and bandwidth were greatly improved by attaching an FSS with controlled electrical resistance (R) onto the grounded ferrite composites. For the FSS with R = 800 Ω, the minimum reflection loss decreased to −25 dB at 10 GHz and the bandwidth was broadened to 7.5-12.5 GHz with respect to −10 dB reflection loss.

The impact of the poloidally inhomogeneous particle source on the onset of Stringer spin-up (SSU) and geodesic acoustic mode (GAM) is investigated. Using a gyrofluid model with Hammet–Perkins closure, it was found that Landau damping stabilizes both waves and subsequently makes a threshold. To capture the full effects of Landau damping, a gyrokinetic model is adopted and results are compared with those from the gyrofluid model. Both models predicted the same value of the threshold for SSU, while for the case of GAM, the gyrofluid model overestimates the threshold value. Considering maximal throughput of the ITER pellet fueling system, the source intensity is calculated at a similar or slightly lower level compared to the source threshold for SSU. [ABSTRACT FROM AUTHOR]

A study is made of the effect of plasma elongation (κ) on parity of a global electromagnetic (EM) ion temperature gradient mode and intrinsic rotation generation. An odd parity component of the mode is generated by global EM effects and increases with β (=plasma thermal energy/magnetic energy), enhancing the symmetry breaking and subsequent Reynolds stress [Kaang et al., Phys. Plasmas 25, 012505 (2018)]. The plasma elongation is shown to diminish the parity change via the reduction in the effective ion temperature gradient by a factor α = 1 − E ′ , where E = r (κ − 1) / (κ + 1). A quasi-linear analysis indicates that plasma elongation can weaken the generation of intrinsic torque induced by the global EM effect as a result of the decline of the parity change. [ABSTRACT FROM AUTHOR]

We derive expressions for the gyro-averaging operator that is applicable to electrostatic fluctuations in a spatially inhomogeneous magnetic field. Both low and high wavenumber limits are considered. The gyro-averaging operator for the former case is represented by sums of Bessel functions with different orders. A simplified expression is provided as a Padé approximant in the low wavenumber limit. This form could be used in practical computations based on the gyrofluid formulation. In the high wavenumber limit, we find that the operator naturally involves fractional derivatives whose physical interpretations are yet to be explored. Discussions are made of a potential impact of this asymptotic expression in the high wavenumber limit. [ABSTRACT FROM AUTHOR]

Intussusception is a common surgical disorder in puppies. Double intussusception (DI) however, is an extremely rare form of this pathology. The authors report a case of a 3-month-old, Shih-Tzu puppy referred to Veterinary Medical Center of Chungbuk National University, Korea with symptoms of abdominal discomfort, intermittent vomiting and bloody diarrhea for 5 days. Ultrasonographic examination of the left mid-abdominal region revealed a mass with a ‘triple case’ sign completely different from the classic ‘target sign’. The surgical intervention confirmed it to be an ileocecal DI in ascending colon. The case emphasizes the rare ‘triple case’ sign as a descriptive finding on ultrasonography in DI presentations.

As the risk of disaster scenes increases, the number of cases of acquiring disaster scenes information using unmanned robots is increasing. Because unmanned robots can be remotely controlled, sensors such as LiDAR and optical cameras are installed so that investigators can safely observe disaster scenes and acquire information. In particular, the information that can be acquired is different depending on the sensor characteristics, and a sensor module suitable for the purpose is being developed. Accordingly, the National Disaster Management research Institute(NDMI) also developed a investigation robot capable of acquiring information on disaster sites independently. Based on 3D point cloud data, we developed a multi-sensor module and SLAM algorithm customized to the investigation robot to collect quantitative information on the damage situation. To test the performance of the independently developed multi-sensor module, SLAM mapping was performed in a disaster building reproduced like a disaster scene, and various SLAM algorithms and distance comparison were performed. As a result, PackSLAM developed in this study showed the lowest error. In the future, to increase applicability at disaster sites, more precise experiments will be conducted by conducted by establishing a rough terrain environment. [ABSTRACT FROM AUTHOR]

Disasters that occur in recent years are linked to various factors and occur in a chain, and the scale is also increasing. In order to solve the more complex and serious disaster problem, it is necessary to expand the affect scope of the disaster and to acquire and manage information by integrating and operating various sensors. With the introduction of UAVs for disaster work, various studies such as investigation of the affected area, rescue of survivors, and establishment of emergency communication networks are being conducted. This is useful for strengthening the field of disaster management because it is very effective in terms of time and human resources. In addition, it is possible to acquire high-resolution images, and by using the 3D point cloud data and ortho-mosaic imagery generation, it is possible to produce a disaster scene close to the real world. Therefore, if UAV information can be linked to disaster types and characteristics prior to supporting disaster damage investigation, it is possible to establish a response method according to the disaster damage situation and help decision-making. In order to examine the applicability of UAV technology for actual disaster sites, this study conducted data collection and analysis of damaged areas targeting sites damaged by heavy rain and chemical accidents. In the heavy rain damage site, flooding damage occurred in the ginseng cultivation patches due to river overflow caused by the torrential rain, and the damaged area and lots were investigated. The site of the chemical accident was damaged by hydrochloric acid gas leaking into the atmosphere, and the surrounding forest, crops, and residential facilities were identified and the affected area was calculated. As a result of investigating the damage from heavy rain and chemical accidents using UAV, it was possible to quickly collect data on a wide disaster site. In addition, it was easy to calculate the damaged area based on ortho-imagery, and the limitations of spatial analysis were reduced, so that it could be used more specifically and efficiently to the disaster site. [ABSTRACT FROM AUTHOR]

This study aims to testify the applicability of UAV photogrammetry and artificial intelligence (AI) for the management of natural disaster. Recently artificial intelligence is considered as an emerging tool for recognizing disaster events from aerial imagery of drones. In this paper, we present firstly the approach related to use of AI techniques for disaster detecting and identification. Secondly, we suggest small easy-to-use UAV-based investigation procedure for natural disaster damaged area in the phase of disaster recovery in Korea. Finally, we evaluate the mapping accuracy and work efficiency of drone mapping for disaster investigation application through comparing with traditional investigation work process which was dependent on labor-intensive field survey. The resolution ortho-image map of within less 5cm of GSD generated by aerial photos acquired from UAVs at the altitude of 100m–250m enabled us to check damage information such as facilities destroy or the trace of soil erosion around the river flooded and reservoir collapsed area. The photogrammetry-based drone mapping technology for the disaster damage investigation is expected to be an alternative approach to support or replace the labor-intensive disaster site survey that needs to investigate the disaster site quickly and timely. [ABSTRACT FROM AUTHOR]

Disasters are not easy to predict because they occur suddenly, and the scale of disasters is increasing compared to the past. Since a new type of disaster field always appears, when a disaster occurs, responders who are put into the site recognize the same risk as secondary damage and are put into the field. In this regard, the robot performs missions such as search and rescue in the initial response process at the disaster field. It is a technology with high potential to reduce damage to people and property. Most of the robots are equipped with site accessibility and monitoring through cameras and remote control, but considering the specificity of the disaster field, it is not easy to fully monitor the site with a camera sensor as the possibility of poor visibility is very high. LiDAR uses a laser to recognize the distance to a nearby object in a relatively wide range and acquires three-dimensional information, so its accuracy and precision are higher than other sensors.In this study, one multi-sensor module was manufactured by combining LiDAR and IMU sensor with a computing board for real-time monitoring so that it could be used in the field of robots. In addition, we studied how to stably mount this multi-sensor module to a robot so that it can maintain optimal accuracy at disaster field, and it is intended to be utilized as a prior research for field operation of robots equipped with sensors in the future. [ABSTRACT FROM AUTHOR]