Gravitational waves are predicted by the Einstein's theory of General Relativity. The direct detection of gravitational waves is one of the most challenging tasks in modern science and engineering due to the 'weak' nature of gravity. Recent development of the laser interferometer technology, however, makes it possible to build a detector on Earth that is sensitive up to 100-1000 Mpc for strong sources. It implies an expected detection rate of neutron star mergers, which are one of the most important targets for ground-based detectors, ranges between a few to a few hundred per year. Therefore, we expect that the gravitational-wave observation will be routine within several years. Strongest gravitational-wave sources include tight binaries composed of compact objects, supernova explosions, gamma-ray bursts, mergers of supermassive black holes, etc. Together with the electromagnetic waves, the gravitational wave observation will allow us to explore the most exotic nature of astrophysical objects as well as the very early evolution of the universe. This review provides a comprehensive overview of the theory of gravitational waves, principles of detections, gravitational-wave detectors, astrophysical sources of gravitational waves, and future prospects.

불과 에너지의 순환에 대한 정확한 해석은 수문학, 기후학, 생태학적인 과정을 이해하는데 있어 매우 중요하다. 수문 순환 환경변화의 정확한 예측을 위해 사용되고 있는 모형들 중 Common Land Model(CLM}은 물과 에너지수지 방정식을 기반으로 한 최신 Soi1-Vegetation-Atmosphere Transfer(SVAT) 모형 중 하나로써, 비교적 간단한 매개변수를 이용하여 현실적이고 신뢰할 만한 결과를 산출해낼 수 있다. CLM 모형은 전 세계적으로 널리 이용되고 있으나, 국내에서는 정보의 부재와 입력자료의 미흡으로 인하여 실제적인 적용사례가 부촉한 실정이다. 본 연구에서는 CLM의 국내 적용성 검증을 위하여 해남 Korea Flux Network(KoFlux}의 자료와 Korea Land Data Assimilation System(KLDAS}의 자료를 이용하여 수문순환 환경인자들의 모형 결과를 산출하였다. 모형의 결과와 관측자료의 비교에서 KoFlux와 KLDAS의 두 입력 자료를 사용한 결과 모두 회귀분석에서의 결정계수 값이 0.73~1.00의 신뢰할 만한 수준으로 나타났다. 본 연구에서 CLM의 국내 적용 가능성을 확인하였고 지점자료가 존재하지 않는 지역에 대한 KLDAS의 이용가능성을 또한 확인하였다.

Accurate assessment of the water and energy cycles is essential to understand hydrologic, climatologic, and ecological processes. Common Land Model (CLM) is one of the well-developed Soil-Vegetation-Atmosphere Transfer (SVAT) models based on the water and energy balance equation for accurate prediction of hydro-environmental cycles. The CLM can estimate realistic and reliable results using relatively simple parameters. It has been widely used in the world, however in Korea practical applications of the CLM are rare due to lack of information and input data. In this study, the CLM with Korea Flux network (KoFlux) and Kore Land Data Assimilation System (KLDAS) data were individually validated for domestic applications. This study showed that all comparisons between observations and model results from KoFlux and KLDAS had reasonable correlation with determination coefficient of 0.73~1.00 via regression. The results confirmed the applicability of the CLM and the possibility of the KLDAS usage for the region where input data are not existed.

미국에서는 재난으로 인한 기반시설물의 피해를 줄이기 위해 국가기반시설 리질리언스 확보가 국가기반시설보호계
획에 활용되고 있다. 여기서 “리질리언스”는 재난으로 인한 시스템의 영향을 효율적으로 줄일 수 있는 기반시설 시
스템의 능력으로, 리질리언스 비용으로 정량화가 시도되었다. 리질리언스 비용은 시스템 영향과 복구노력을 합한 것
으로, 리질리언스 평가 사례는 리질리언스 평가시 복구노력을 고려할 필요가 있음을 보여주고 있다. 본 논문은 리질
리언스 비용을 설명하고, 연구 사례를 통해 리질리언스 비용의 평가 방법을 보여주고자 한다.

Critical infrastructure resilience has been integrated in critical infrastructure protection in US after Department of
Homeland Security recognized that protection, in isolation, is a brittle strategy. Here “resilience” is the system’s
ability to efficiently reduce both the magnitude and the duration of systemic impacts after hazards, and quantitatively
assessed as a resilience cost. The resilience cost is the sum of systemic impacts and recovery efforts, and
many case studies on resilience costs show that the recovery effort should be included in resilience assessment.
This paper explains how the resilience cost is defined and quantified with a case study.

Canopy turbulence plays an important role in mass and energy exchanges at the canopy-atmosphere interface. Despite extensive studies on canopy turbulence over a flat terrain, less attention has been given to canopy turbulence in a complex terrain. The purpose of this study is to scrutinize characteristics of canopy turbulence in roughness sublayer over a hilly forest terrain. We investigated basic turbulence statistics, conditionally sampled statistics, and turbulence spectrum in terms of different atmospheric stabilities, wind direction and vertical structures of momentum fluxes. Similarly to canopy turbulence over a homogeneous terrain, turbulence statistics showed coherent structure. Both quadrant and spectrum analysis corroborated the role of intermittent and energetic eddies with length scale of the order of canopy height, regardless of wind direction except for shift of peak in vertical wind spectrum to relatively high frequency in the down-valley wind. However, the magnitude of the momentum correlation coefficient in a neutral condition was smaller than typical value over a flat terrain. Further scrutiny manifested that, in the up-valley flow, temperature skewness was larger and the contribution of ejection to both momentum and heat fluxes was larger compared to the downvalley flow, indicating that thermal instability and weaker wind shear in up-valley flow asymmetrically affect turbulent transport within the canopy.

The core of neutron-star matter is supposed to be at a much higher density than the normal nuclear-matter density, for which various possibilities have been suggested, such as, for example, meson or hyperon condensation and/or deconfined quark or color-superconducting matter. In this work, we explore the implication on hadron physics of a dense compact object that has three “phases”: nuclear matter at the outer layer, kaon condensed nuclear matter in the middle, and strange quark matter at the core. Using a drastically simplified but not unreasonable model, we develop the scenario where the different phases are smoothly connected with the kaon condensed matter playing a role of a “doorway” to a quark core, the equation of state of which with parameters restricted within the range allowed by nature could be made compatible with the mass vs radius constraint given by the 1.97-solar-mass object PSR J1614-2230 recently observed.

The goal of magnetic resonance electrical impedance tomography (MREIT) is to produce a tomographic image of a conductivity distribution inside an electrically conducting object. Injecting current into the object, we measure a z-component B_z of an induced magnetic flux density using an MRI scanner. Based on the relation between the conductivity and measured B_z data, we may reconstruct cross-sectional images of the conductivity distribution. In a two-dimensional imaging slice, we can see that conductivity changes along equipotential lines are determined by the measured B_z data. Since the equipotential lines themselves depend nonlinearly on the unknown conductivity distribution, it is not possible to recover the conductivity distribution directly from measured B_z data. Conductivity image reconstruction algorithms such as the harmonic B_z algorithm utilize an iterative procedure to update conductivity values and in each iteration we need to solve an elliptic boundary value problem with a presumed conductivity distribution. This iteration is often troublesome in practice due to excessive amounts of noise in some local regions where weak MR signals are produced. This motivated us to develop a non-iterative reconstruction algorithm which does not depend on a global structure of the conductivity distribution. In this paper, we propose a new MREIT conductivity image reconstruction algorithm, called the non-iterative harmonic B_z algorithm, which provides a conductivity image directly from measured B_z data. From numerical simulations, we found that the new method produces absolute images of a conductivity distribution with a high accuracy by maximizing the use of reliable B_z data. It effectively reduces adverse effects of excessive noise in some local regions of weak MR signals by restricting the influences within them.

In magnetic resonance electrical impedance tomography, among several conductivity image reconstruction algorithms, the harmonic B_z algorithm has been successfully applied to B_z data from phantoms and animals. The algorithm is, however, sensitive to measurement noise in B_z data. Especially, in in vivo animal and human experiments where injection current amplitudes are limited within a few milliampere at most, measured B_z data tend to have a low SNR. In addition, magnetic resonance (MR) signal void in outer layers of bones and gas-filled organs, for example, produces salt-pepper noise in the MR phase and, consequently, B_z images. The B_z images typically present areas of sloped transitions, which can be assimilated to ramps. Conductivity contrasts change ramp slopes in B_z images and it is critical to preserve positions of those ramps to correctly recover edges in conductivity images. In this paper, we propose a ramp-preserving denoising method utilizing a structure tensor. Using an eigenvalue analysis, we identified local regions of salt-pepper noise. Outside the identified local regions, we applied an anisotropic smoothing to reduce noise while preserving their ramp structures. Inside the local regions of salt-pepper noise, we used an isotropic smoothing. After validating the proposed denoising method through numerical simulations, we applied it to in vivo animal imaging experiments. Both numerical simulation and experimental results show significant improvements in the quality of reconstructed conductivity images.