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Cho, Mee-Hyun,Boo, Kyung-On,Lee, Johan,Cho, Chunho,Lim, Gyu-Ho American Geophysical Union 2014 Journal of geophysical research. Atmospheres Vol.119 No.8
In this study, we investigated the impacts of land use alterations from harvesting practices on the regional surface climate over the North China Plain. The surface climate responses after harvest in June in regions where double-cropping is practiced were evaluated using observations and model simulations with the global climate model HadGEM2-Atmosphere. Responses were modeled under both present and possible future climate conditions. In the model, double-cropping was represented using the monthly varying fraction of vegetation. This contributed to an improvement in the model simulation over East Asia. Modeling results showed that the land surface was warmer and drier after harvest, and these simulation results were consistent with observations. The bare soil surface after harvest in June had biophysical impacts on the surface climate that were mediated by decreasing evapotranspiration and latent heat flux effects, which increased surface air temperatures and decreased surface humidity. An increase in shortwave radiation also contributed to the rise in temperatures. Under two Representative Concentration Pathways (RCP) scenarios for possible future climate conditions, land conversion induced additional warming in addition to greenhouse gases induced global warming. The RCP 8.5 and RCP 2.6 scenarios demonstrated a warming of 1.0 degrees C and 1.4 degrees C due to harvesting practices in June, respectively. The response magnitude was affected by the climate conditions in each RCP. Our results suggest that potential impacts of harvest on the local climate need to be considered in future projections of CO2-induced warming on a regional scale. Key Points <list id='jgrd51004-list-0001' list-type='bulleted'> <list-item id='jgrd51004-li-0001'>Harvest impacts on surface climate over the North China Plainare investigated <list-item id='jgrd51004-li-0002'>Harvesting could make the land surface warmer and drier <list-item id='jgrd51004-li-0003'>Sensitivity to climate from future projections of agricultural-induced land cover change 20 were evaluated
화자식별 기반의 AI 음성인식 서비스에 대한 사이버 위협 분석
홍천호 ( Chunho Hong ),조영호 ( Youngho Cho ) 한국인터넷정보학회 2021 인터넷정보학회논문지 Vol.22 No.6
음성인식(ASR: Automatic Speech Recognition)은 사람의 말소리를 음성 신호로 분석하고, 문자열로 자동 변화하여 이해하는 기술이다. 초기 음성인식 기술은 하나의 단어를 인식하는 것을 시작으로 두 개 이상의 단어로 구성된 문장을 인식하는 수준까지 진화하였다. 실시간 음성 대화에 있어 높은 인식률은 자연스러운 정보전달의 편리성을 극대화하여 그 적용 범위를 확장하고 있다. 반면에, 음성인식 기술의 활발한 적용에 따라 관련된 사이버 공격과 위협에 대한 우려 역시 증가하고 있다. 기존 연구를 살펴보면, 자동화자 식별(ASV: Automatic Speaker Verification) 기법의 고안과 정확성 향상 등 기술 발전 자체에 관한 연구는 활발히 이루어지고 있으나, 실생활에 적용되고 있는 음성인식 서비스의 자동화자 식별 기술에 대한 사이버 공격 및 위협에 관한 분석연구는 다양하고 깊이 있게 수행되지 않고 있다. 본 연구에서는 자동화자 식별 기술을 갖춘 AI 음성인식 서비스를 대상으로 음성 주파수와 음성속도를 조작하여 음성인증을 우회하는 사이버 공격 모델을 제안하고, 상용 스마트폰의 자동화자 식별 체계를 대상으로 실제 실험을 통해 사이버 위협을 분석한다. 이를 통해 관련 사이버 위협의 심각성을 알리고 효과적인 대응 방안에 관한 연구 관심을 높이고자 한다. Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.
Impact of Large-Scale Advection on Regional Heat Flux Estimation over Patchy Agricultural Land
Jinkyu Hong,Chunho Cho,Tae-Young Lee,Monique Leclerc 한국기상학회 2009 Asia-Pacific Journal of Atmospheric Sciences Vol.45 No.2
This paper attempted to constrain regional heat fluxes simulated by an atmospheric mesoscale model using the convective boundary layer (CBL) budget method and flux tower data over a mosaic of farmland. In tower footprint scales, the mesoscale model reproduced heat fluxes comparable to the tower measurement. In regional scales, the modeled heat fluxes were consistent with those from the CBL budget method only when the advection inside the CBLwas considered. Our analysis showed that the advection in the CBL, in conjunction with sealand breeze and heat transport from the inland, played a critical role in estimating regional scale fluxes since the net change of temperature in the CBL was balanced with entrainment in the CBL budget method. However, inconsistent magnitudes and pattern of advection between the model and the CBL budget method hindered us from inferring reliable regional heat fluxes around the site.