뇌졸중으로 유발된 전체성 실어증 환자에 대한 두침치료 치험 2례

강아름,우지명,이미림,김수빈,조기호,문상관,정우상,Kang, Ah-reum,Woo, Ji-myung,Lee, Mi-rim,Kim, Su-bin,Cho, Ki-ho,Moon, Sang-kwan,Jung, Woo-sang 대한한방내과학회 2016 大韓韓方內科學會誌 Vol.37 No.2

Objectives: This study presents two cases of patients with post-stroke global aphasia who were treated with scalp acupuncture with electrical stimulation.Method: The two patients were treated by scalp acupuncture with electrical stimulation six times a week. The degree of aphasia was measured via the Korean version of the western aphasia battery (K-WAB).Results: After treatment, aphasia was improved in both cases (autism-spectrum quotient [AQ] scores increased from 13.7 to 37.1 and from 4.1 to 18.4 in the two patients).Conclusion: Based on the results of these two cases, scalp acupuncture could be effective in treating post-stroke global aphasia.

고해상도 SAR 영상을 이용한 도심지 건물 재구성

강아름 ( Ah Reum Kang ),이승국 ( Seung Kuk Lee ),김상완 ( Sang Wan Kim ) 대한원격탐사학회 2013 大韓遠隔探査學會誌 Vol.29 No.4

공간해상도 약 1 m의 고해상도 X-band SAR 위성이 이용되면서 SAR를 이용한 도심지 모니터링, 표적탐지, 건물 재구성에 관한 연구가 진행되고 있다. 본 연구에서는 고해상도 TerraSAR-X SAR 영상을 이용한 도심지 건물 재구성을 수행하였다. 도심지 건물 재구성을 위하여 1:25,000 수치지형도로부터 건물의 외곽선을 추출하였으며, 추출한 건물의 외곽선을 기반으로 SAR 영상에서 모서리반사 위치를 찾았다. KS 테스트(Kolmogorov-Smirnov Test)에 기반하여 고해상도 SAR 진폭영상의 건물 모서리반사 위치로부터 레이오버 길이를 측정하여 건물의 초기 높이를 설정하였다. 진폭영상을 이용하여 추출한 건물의 초기 높이 기준 -10 m에서 +10 m로 건물의 높이를 변화시키며 도심지에 적합한 간섭위상 시뮬레이션을 수행하여 TerraSAR-X 간섭위상과의 위상 일치성 계산을 하였다. 위상 일치의 경향성 분석을 통해 건물의 높이를 설정해 줌으로써 고해상도 SAR 영상을 이용한 도심지 건물 재구성 연구를 진행하였다. 대전지역의 아파트 단지에 적용한 결과, 진폭영상과 간섭위상을 이용하여 추정된 건물 높이는 LiDAR로부터 추출된 높이를 기준으로 약 1~2 m 정도의 RMSE (Root Mean Square Error)를 보였다. 개발된 알고리즘은 향후 TerraSARX와 TanDEM-X 간섭쌍 자료에 적용할 경우, 보다 도심지 모니터링에 효과적으로 이용될 수 있을 것이다. The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeatpass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.

문서 구조 및 스트림 오브젝트 분석을 통한 문서형 악성코드 탐지

강아름(Ah Reum Kang),정영섭(Young-Seob Jeong),김세령(Se Lyeong Kim),김종현(Jonghyun Kim),우지영(Jiyoung Woo),최선오(Sunoh Choi) 한국컴퓨터정보학회 2018 韓國컴퓨터情報學會論文誌 Vol.23 No.11

In recent years, there has been an increasing number of ways to distribute document-based malicious code using vulnerabilities in document files. Because document type malware is not an executable file itself, it is easy to bypass existing security programs, so research on a model to detect it is necessary. In this study, we extract main features from the document structure and the JavaScript contained in the stream object In addition, when JavaScript is inserted, keywords with high occurrence frequency in malicious code such as function name, reserved word and the readable string in the script are extracted. Then, we generate a machine learning model that can distinguish between normal and malicious. In order to make it difficult to bypass, we try to achieve good performance in a black box type algorithm. For an experiment, a large amount of documents compared to previous studies is analyzed. Experimental results show 98.9% detection rate from three different type algorithms. SVM, which is a black box type algorithm and makes obfuscation difficult, shows much higher performance than in previous studies.

온라인 게임 봇 탐지를 위한 사용자 행위 분석

강아름(Ah Reum Kang),우지영(Jiyoung Woo),박주용(Juyong Park),김휘강(Huy Kang Kim) 한국정보보호학회 2012 정보보호학회논문지 Vol.22 No.2

온라인 게임의 다양한 보안 위협 가운데, 온라인 게임 봇의 사용이 게임 서비스에 가장 심각한 문제를 야기하고 있다. 본 논문에서는 온라인 게임 봇 탐지를 위한 소셜 액티비티 분석 프레임워크를 제안한다. 이 프레임워크를 이용하여 게이머의 소셜 액티비티를 가장 많이 포함하고 있는 파티 플레이(party play) 로그를 분석하는 데에 적용하였다. 게임 봇은 일반 사용자들과 다르게, 사이버 자산을 빠르게 얻는데 특화되어 있기 때문에 소셜 액티비티를 분석할 경우 정상적인 사용자들과 행동 패턴에 차이가 있다. 이 특징을 이용하여 게임 봇 이용자와 일반 이용자들을 구분해 낼 수 있도록, 사용자 행위를 분석하고 온라인 게임 봇 탐지를 위한 임계값을 정의하였다. 탐지 규칙을 포함하는 지식 기반 시스템을 구축한 뒤 이를 국내 최대, 세계 6위 규모의 게임에 적용하였다. 본 논문의 프레임워크를 활용하여 분류를 한 결과 95.92%의 높은 정확도를 보였다. Among the various security threats in online games, the use of game bots is the most serious problem. In this paper, we propose a framework for user behavior analysis for bot detection in online games. Specifically, we focus on party play that reflects the social activities of gamers: In a Massively Multi-user Online Role Playing Game (MMORPG), party play log includes a distinguished information that can classify game users under normal-user and abnormal-user. That is because the bot users" main activities target on the acquisition of cyber assets. Through a statistical analysis of user behaviors in game activity logs, we establish the threshold levels of the activities that allow us to identify game bots. Also, we build a knowledge base of detection rules based on this statistical analysis. We apply these rule reasoner to the sixth most popular online game in the world. As a result, we can detect game bot users with a high accuracy rate of 95.92%.

메타버스에서의 보안 위협

강아름(Kang Ah Reum),이병엽(Lee Byoung Yup) 한국콘텐츠학회 2022 한국콘텐츠학회 종합학술대회 논문집 Vol.2022 No.7

팔미지황탕가미 및 침, 뜸 치료를 이용한 당뇨병성 신경병증 치험 1례

우지명,강아름,이미림,김수빈,정우상,문상관,조기호,Woo, Ji-myung,Kang, Ah-reum,Lee, Mi-rim,Kim, Su-bin,Jung, Woo-sang,Moon, Sang-kwan,Cho, Ki-ho 대한한방내과학회 2016 大韓韓方內科學會誌 Vol.37 No.2

Objective: Diabetic neuropathy is a common complication of diabetes mellitus. Patients with this disease suffer from various peripheral sensory symptoms that are not easily alleviated. We report on a case of a patient with diabetic neuropathy whose symptoms were alleviated after traditional Korean medical treatment.Methods: A patient with hand and foot numbness and coldness diagnosed with diabetic neuropathy was treated with Palmijihwang-tang (Bai Wei Di Huang Wa, 八味地黃湯) three times a day. The progress was evaluated with the numerical rating scale (NRS), neuropathy disability score (NDS), and neuropathy symptom score (NSS).Results: The improvement of symptoms appeared to be faster and more effective than that of conventional treatment. The improvement was observed from the second day of the treatment.Conclusions: This case study shows that Palmijihwang-tang may be an effective treatment for diabetic neuropathy.

CNN 기반 MS Office 악성 문서 탐지

박현수,강아름,Park, Hyun-su,Kang, Ah Reum 한국정보보호학회 2022 정보보호학회논문지 Vol.32 No.2

Document-type malicious codes are being actively distributed using attachments on websites or e-mails. Document-type malicious code is relatively easy to bypass security programs because the executable file is not executed directly. Therefore, document-type malicious code should be detected and prevented in advance. To detect document-type malicious code, we identified the document structure and selected keywords suspected of being malicious. We then created a dataset by converting the stream data in the document to ASCII code values. We specified the location of malicious keywords in the document stream data, and classified the stream as malicious by recognizing the adjacent information of the malicious keywords. As a result of detecting malicious codes by applying the CNN model, we derived accuracies of 0.97 and 0.92 in stream units and file units, respectively.

기상정보를 활용한 머신러닝 기반의 전력수요 예측 모델

차현종(Hyun-Jong Cha),강아름(Ah Reum Kang) 한국콘텐츠학회 2023 한국콘텐츠학회논문지 Vol.23 No.2

공조 시스템은 일상생활에서 중요한 역할을 하며, 전력수요에도 큰 영향을 준다. 기상 상황에 따라 전력수요의 차이가 크다. 기상 상황에 따른 정확한 전력수요의 예측은 미래의 스마트 그리드 시스템의 구축과 신뢰도, 효율성을 향상시킨다. 따라서 전력수요를 예측하기 위해 여러 가지 머신러닝 분석 기법이 활발히 연구되고 있다. 본 연구에서는 기상정보를 기반으로 하는 전력을 예측하는 기법을 제안한다. 특히 기상청에서 제공되는 과거의 기상정보와 실제 공조 시스템에서 사용된 전력 값을 이용하여 머신러닝 모델을 훈련하여 미래의 전력 수요 값을 예측한다. 또한, 전력예측에 있어서 어떠한 기상 변수가 중요한지 분석하였다. 실험결과 89% 이상의 정확도를 나타내었으며 휴일 유무와 풍속, 기압, 기온, 습도 등이 전력수요에 중요한 요소임을 확인하였다. Electricity demand varies greatly depending on weather conditions. In this study, a power forecasting technique based on weather information is proposed. In particular, a machine learning model is trained using the past weather information provided by the Korea Meteorological Administration and the power value used in the actual air conditioning system to predict the future power demand value. In addition, we analyzed which meteorological variables are important in power prediction.

Opcode와 IAT를 활용한 PE 파일 악성코드 탐지

이정훈(JeongHun Lee),강아름(Ah Reum Kang) 한국컴퓨터정보학회 2023 한국컴퓨터정보학회 학술발표논문집 Vol.31 No.1

급성기 뇌경색 환자의 화열증상 변화와 기능회복도간의 상관관계에 대한 연구

현상호,민경동,예영철,강아름,이은찬,문상관,조기호,정우상,박성욱,고창남,Hyun, Sang-Ho,Min, Kyung-Dong,Yei, Young-Chul,Kang, Ah-Reum,Lee, Eun-Chan,Moon, Sang-Kwan,Cho, Ki-Ho,Jung, Woo-Sang,Park, Sung-Wook,Ko, Chang-Nam 대한한방내과학회 2013 大韓韓方內科學會誌 Vol.34 No.4

Objectives : The aim of this study was to examine if there is a significant correlation between the changes of Fire- and Heat- related symptoms and motor function recovery in acute cerebral infarction patients. Methods : We studied inpatients within a month after the onset of cerebral infarction who were admitted at Kyunghee University Medical Center from May 2011 to January 2013. We executed correlation analysis between Fire-heat pattern score and motricity index score at visit 1 and visit 2, and checked if there was a significant correlation between the changes of Fire-heat pattern score and changes of motricity index score. Also, we compared the changes of both scores in patients taking Fire-heat and non Fire-heat pattern prescriptions. Results : There was a significant correlation between the Fire-heat pattern score and Motricity index score at visit 1 and visit 2, and changes of Fire-heat pattern score showed significant correlation with changes of motricity index score. Patients taking Fire-heat pattern prescriptions showed significant change in Fire-heat pattern score after herb-medication treatment while patients taking non-Fire-heat prescriptions showed insignificant change in Fire-heat pattern score. Conclusions : This study provides evidence that taking a Fire-heat pattern prescription could be considered as a first line herb-medication treatment in acute cerebral infarction patients.