• 정보처리학회논문지C
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• 제13C권4호
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• pp.397-404
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• 2006

소프트웨어 공격이 성공하기 위해서는 공격 코드가 프로그램의 주소 공간에 주입된 후 프로그램의 제어 흐름이 공격 코드 위치로 변경되어야 한다. 프로그램의 주소 공간 중 코드 영역은 실행 중에 변경이 불가능하므로 공격 코드가 주입될 수 있는 곳은 데이터 영역 밖에 없다. 따라서 데이터 영역으로 프로그램의 제어가 변경될 경우 주입된 공격 코드로 제어가 옮겨 가는 공격이 발생한 것으로 판단할 수 있다. 따라서 본 논문에서는 프로그램의 제어 흐름과 관련된 CALL, JMP, RET 명령어의 목적 주소를 검사하여 제어가 옮겨갈 목적 주소가 프로그램의 실행 코드가 저장된 텍스트 영역이 아닌 데이터 영역일 경우 소프트웨어 공격이 발생한 것으로 간주하는 소프트웨어 공격 탐지 기법을 제안하였다. 제안된 방법을 이용하면 함수의 복귀주소뿐만 아니라 함수포인터, longjmp() 버퍼 등 프로그램 제어 흐름과 관련된 모든 데이터가 변경되었는지 점검할 수 있었기 때문에 기존 기법들보다 더 많은 종류의 공격을 탐지할 수 있었다.

• 한국멀티미디어학회논문지
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• 제9권2호
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• pp.255-263
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• 2006

스팸 메일의 특성을 분석해 보면 스팸 메일 발송 프로그램이 메일 헤더에 기록된 주소와 송신자 및 수신자 메일 주소가 일치하지 않는 경우가 빈번하게 발견된다. 또한, 스팸 메일과 정상적인 메일을 비교-분석해 보면 제목만 살펴봐도 스팸 메일인지 여부를 쉽게 판별할 수가 있다. 본 논문에서는 이와 같은 스팸 메일의 특성을 이용하여 스팸 메일 필터링 시스템의 성능을 향상시키는 방안으로 메일 주소 유효성 검사 및 제목과 내용을 구분하여 각각 스팸 확률을 계산하는 기법을 제안하였다. 제안한 방법의 효용성을 검증하기 위하여 단순 베이스 기법에 대해 주소 유효성 검사 및 제목과 내용 등 각 요인의 중요도에 따른 스팸 메일 필터링의 성능 향상 정도를 측정하였다. 그 결과로, 제안한 방법을 적용했을 때 재현율이 11.6%, 정확률은 2.1%의 성능 향상 효과가 있음을 확인하였으며, 스팸 메일 필터링 시스템의 성능 향상에 많은 기여를 하는 것을 알 수 있었다.

• Coupled systems mechanics
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• 제4권1호
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• pp.37-65
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• 2015

Modeling and simulation of mechanical response of infrastructure object, solids and structures, relies on the use of computational models to foretell the state of a physical system under conditions for which such computational model has not been validated. Verification and Validation (V&V) procedures are the primary means of assessing accuracy, building confidence and credibility in modeling and computational simulations of behavior of those infrastructure objects. Validation is the process of determining a degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. It is mainly a physics issue and provides evidence that the correct model is solved (Oberkampf et al. 2002). Our primary interest is in modeling and simulating behavior of porous particulate media that is fully saturated with pore fluid, including cyclic mobility and liquefaction. Fully saturated soils undergoing dynamic shaking fall in this category. Verification modeling and simulation of fully saturated porous soils is addressed in more detail by (Tasiopoulou et al. 2014), and in this paper we address validation. A set of centrifuge experiments is used for this purpose. Discussion is provided assessing the effects of scaling laws on centrifuge experiments and their influence on the validation. Available validation test are reviewed in view of first and second order phenomena and their importance to validation. For example, dynamics behavior of the system, following the dynamic time, and dissipation of the pore fluid pressures, following diffusion time, are not happening in the same time scale and those discrepancies are discussed. Laboratory tests, performed on soil that is used in centrifuge experiments, were used to calibrate material models that are then used in a validation process. Number of physical and numerical examples are used for validation and to illustrate presented discussion. In particular, it is shown that for the most part, numerical prediction of behavior, using laboratory test data to calibrate soil material model, prior to centrifuge experiments, can be validated using scaled tests. There are, of course, discrepancies, sources of which are analyzed and discussed.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1075-1086
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• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• 한국정보기술학회 영문논문지
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• 제9권2호
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• pp.15-27
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• 2019

This paper deals with a web-based public address system for conveying information for different institutions. An architecture for a Short Messaging Service (SMS) based public address (PA) system that can be programmed by an authorized mobile phone or device is proposed. This PA system will facilitate information transfer from heads of offices, managers, directors, and deans of the institutions to its constituents or unit area as well as enable postings of information with proper authentication and validation remotely. The system supports high priority messaging, allowing the conveyance of critical and time sensitive information. The mobility management support for the PA system will be based on the Hierarchical Mobile Internet Protocol version 6 (HMIPv6), hence, allowing for a seamless connectivity to the system. The major advantage of this proposed PA system as compared with the traditional electronic displays and bulletin boards is seamless mobility wherein the display devices can be programmed remotely by heads of the institutions and business organization. It also allows faster communication and immediate actions concerning the different institutions, organizations, and businesses, thus, ensuring high productivity.

• 인터넷정보학회논문지
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• 제22권1호
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• pp.31-39
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• 2021

TV홈쇼핑을 통한 상품 구매 과정에서, 전화망을 통한 배송지 정보의 확보는 필수적인 과정이며 동시에, 서비스 운영 효율을 높이기 위한 주요한 자동화 적용 대상 과정이다. 본 연구는 음성으로 기록된 배송지 정보를 자동으로 인식 및 검증하려는 방법을 제안한다. 본 제안 방법은 음성 기반의 주소 정보를 처리하는 데 필요한 다음의 세 가지 기능을 포함한다. 첫 번째 기능은 한글 발화문으로 부터 원래 주소의 표기 형태로 올바르게 변환하는 것이고, 두 번째 기능은 음성 녹취 과정에서 주소의 구성 요소별 순서 변화 혹은 동일 구성 요소의 중복 발화 같은 주소 잡음을 처리하는 것이며, 마지막 기능은 띄어쓰기 처리를 통한 최종 주소의 가독성을 보장할 수 있는 기능이다. 제안된 방법을 구현하기 위해 우정사업본부 주소 DB와 행정안전부의 주소 DB를 사용하였으며, 통화에서 획득한 주소 발화로부터 도로명 주소를 도출하고, 도출된 주소의 유효성을 검증하였다. 또한 제안 방법의 구현 결과물은 STT를 통한 발화 인식 결과뿐만 아니라, 키보드를 이용한 표준 입출력으로도 입력 채널을 확장하여, 주소 검증이 필요한 비음성 기반의 서비스에서도 활용될 수 있도록 하였다. 제안 방법은 주소 구성 요소의 위치 변화 잡음에 강건하게 동작했지만, 요소 생략의 경우 오작동 경향이 존재했다. 이는 생략된 요소에 의해 하위 요소의 지역을 명시하지 못하는 경우 처리하지 못한 모호함 때문이었다.

• 한국컴퓨터정보학회논문지
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• 제20권6호
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• pp.151-159
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• 2015

In traditional programing education, computers were used as the main tool. Consequently, it was problematic to provide education in an environment without computers or for learners without computer skills. To address this problem, this study developed and validated an unplugged robot education system capable of computerless programming education. The key feature of the proposed system is that programing can be done only by connecting programming blocks in symbols of a flow chart with built-in commands. Validation of the system was performed by a specialist group. Validity was very high with values of content validity ratio (CVR) over 0.7 in all evaluation criteria except "Ease of error debugging" and "Linkages to educational curriculum," whose CVR values were each 0.6. Future directions include improvement in the two areas that scored lower than the others did by, respectively, system improvement to support debugging in error conditions that may occur during the programming process, and development of user guide to support linkages to educational curriculum.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.461-471
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• 2017

In this paper we propose a feature selection method identifying important features in the semivarying coefficient model. One important issue in semivarying coefficient model is how to estimate the parametric and nonparametric components. Another issue is how to identify important features in the varying and the constant effects. We propose a feature selection method able to address this issue using generalized cross validation functions of the varying coefficient least squares support vector regression (LS-SVR) and the linear LS-SVR. Numerical studies indicate that the proposed method is quite effective in identifying important features in the varying and the constant effects in the semivarying coefficient model.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1358-1367
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• 2017

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector responses (using the adjoint transport solution) with measured responses. DIMP performs well with forward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search volume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

• Korean Journal of Radiology
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• 제22권3호
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• pp.442-453
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• 2021

Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical validation, device approval, and insurance coverage decisions of AI algorithms for medical diagnosis and prediction. Discrimination accuracy of AI algorithms is often evaluated with the Dice similarity coefficient, sensitivity, specificity, and traditional or free-response receiver operating characteristic curves. Calibration accuracy should also be assessed, especially for algorithms that provide probabilities to users. As current AI algorithms have limited generalizability to real-world practice, clinical validation of AI should put it to proper external testing and assisting roles. External testing could adopt diagnostic case-control or diagnostic cohort designs. A diagnostic case-control study evaluates the technical validity/accuracy of AI while the latter tests the clinical validity/accuracy of AI in samples representing target patients in real-world clinical scenarios. Ultimate clinical validation of AI requires evaluations of its impact on patient outcomes, referred to as clinical utility, and for which randomized clinical trials are ideal. Device approval of AI is typically granted with proof of technical validity/accuracy and thus does not intend to directly indicate if AI is beneficial for patient care or if it improves patient outcomes. Neither can it categorically address the issue of limited generalizability of AI. After achieving device approval, it is up to medical professionals to determine if the approved AI algorithms are beneficial for real-world patient care. Insurance coverage decisions generally require a demonstration of clinical utility that the use of AI has improved patient outcomes.