• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• 부동산연구
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• 제28권3호
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• pp.21-35
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• 2018

최근 주택담보대출 이행이력에 대한 연구는 중도상환 위험과 분리하여 채무불이행 위험의 작용을 연구할 필요성에 대하여 주의를 환기한다. 본 연구는 미국 연방주택모기지회사(Freddie Mac)의 유동화된 주택담보 대출 자료를 이용하여 차입자의 채무불이행 의사결정을 다룬다. 자료는 2011년 1월에서 2013년 9월이다. 추정 모델은 Cox의 비례적 위험 모델이다. 본 연구는 두 개의 연체 모형을 내포한 채무불이행 모델을 제안한다. 하나는 연체와 이행 더미변수이고, 다른 모형은 연체확률 모델이다. 본 연구는 Vuong (1989) 논문의 예에 따라, 설명력 테스트를 수행하였다. 테스트는 내포모델과 중첩모델로 나누어 두 차례 시행하였다. 본 연구는 연체확률 모델이 통계적으로 유의하게 연체와 이행 더미변수보다 우월함을 증명하였다. 또한 Shumway (2001) 논문에서 제시된 방법론에 따라 예측력 테스트를 수행한바, 연체확률 모델이 연체와 이행 더미변수 모델보다 우월함을 보였다.

• 정보보호학회논문지
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• 제21권2호
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• pp.119-129
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• 2011

본 논문은 인터넷 서버의 정상적인 TCP 연결을 방해하는 형태의 DDoS(Distributed Denial of Service) 공격으로부터 서버를 보호하고 원활한 서비스를 제공하기 위한 DDoS 공격 차단 방법에 관한 것이다. 즉, 유효한 TCP 연결만을 전달해주는 기능을 가진 네트워크 인터페이스 카드에서의 고속 TCP 연동 로직(NIC_Cookie)에 대하여 기술한다. NIC_Cookie의 장점은 플러딩 공격 상태에서도 실시간으로 공격 패킷을 차단하고 정상적인 패킷만이 메인 CPU로 전달될 수 있도록 하기 때문에, 서버의 CPU 성능과 외부 네트워크의 구성 등에 영향을 받지 않는다는 것이다. 또한, 패킷 단위로 공격 TCP 세션에 대하여 실시간 차단 대응을 하기 때문에 정상적인 연결 시도에 대하여 잘못된 대응을 할 가능성이 없다. 이와 더불어, NCI_Cookie 로직 추가로 발생하는 지연시간은 패킷 길이와 상관없이 $7{\times}10^{-6}$초 이하의 성능을 보장하며, 본 논문에서는 구현된 NIC_Cookie가 일반적인 플러딩 공격을 실시간으로 방어하면서 그 성능을 보장함을 확인하였다.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• Wind and Structures
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• 제35권4호
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• pp.269-285
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• 2022

The pressure-mitigating effects of a high-speed train passing through a tunnel with a partially reduced cross-section are investigated via the numerical approach. A compressible, three-dimensional RNG k-ε turbulence model and a hybrid mesh strategy are adopted to reproduce that event, which is validated by the moving model test. Three step-like tunnel forms and two additional transitions at the tunnel junction are proposed and their aerodynamic performance is compared and scrutinized with a constant cross-sectional tunnel as the benchmark. The results show that the tunnel step is unrelated to the pressure mitigation effects since the case of a double-step tunnel has no advantage in comparison to a single-step tunnel, but the excavated volume is an essential matter. The pressure peaks are reduced at different levels along with the increase of the excavated earth volume and the peaks are either fitted with power or logarithmic function relationships. In addition, the Arc and Oblique-transitions have very limited gaps, and their pressure curves are identical to each other, whereas the Rec-transition leads to relatively lower pressure peaks in C_Pmax, C_Pmin, and ΔC_P, with 5.2%, 4.0%, and 4.1% relieved compared with Oblique-transition. This study could provide guidance for the design of the novel railway tunnel.

• 한국컴퓨터정보학회논문지
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• 제14권3호
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• pp.139-147
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• 2009

메모리 기반 추론 기법은 단순히 학습패턴이나 대표패턴의 형태로 메모리에 저장하며 테스트 패턴과의 거리 계산을 통하여 분류한다. 이 기법의 가장 큰 문제점은 학습 패턴 전체를 메모리에 저장하거나 학습 패턴들을 대표 패턴으로 대체하는 방법을 사용함으로 다른 기계학습 방법에 비하여 많은 메모리 공간을 필요로 하며, 저장되는 학습패턴이 증가할수록 분류에 필요한 시간도 많이 소요된다는 단점을 갖는다. 본 논문은 효율적인 메모리 사용과 분류 성능의 향상을 위한 EAS 기법을 제안하였다. 즉, 학습패턴에 대해 분할공간을 생성한 후 생성된 각 분할공간을 MDL기법과 PM기법으로 평가하였다. 그리고 평가 결과 가장 우수한 분할공간만을 취하여 대표패턴으로 삼고 나머지는 다시 분할하여 평가를 반복하는 기법이다. UCI Machine Learning Repository에서 벤치마크 데이터를 발췌한 실험 자료를 사용하여 제안한 기법의 성능과 메모리 사용량에 있어 우수함을 입증하였다.

• Restorative Dentistry and Endodontics
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• 제45권4호
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• pp.45.1-45.8
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• 2020

Objective: The aim of this study was to introduce a gelatin/bovine serum albumin (BSA) tissue standard, which provides dissolution properties identical to those of biological tissues. Further, the study evaluated whether the utilization of endodontic activating devices led to enhanced phantom dissolution rates. Materials and Methods: Bovine pulp tissue was obtained to determine a benchmark of tissue dissolution. The surface area and mass of samples were held constant while the ratio of gelatin and BSA were varied, ranging from 7.5% to 10% gelatin and 5% BSA. Each sample was placed in an individual test tube that was filled with an appropriate sodium hypochlorite solution for 1, 3, and 5 minutes, and then removed from the solution, blotted dry, and weighed again. The remaining tissue was calculated as the percent of initial tissue to determine the tissue dissolution rate. A radiopaque agent (sodium diatrizoate) and a fluorescent dye (methylene blue) were added to the phantom to allow easy quantification of phantom dissolution in a canal block model when activated using ultrasonic (EndoUltra) or sonic (EndoActivator) energy. Results: The 9% gelatin + 5% BSA phantom showed statistically equivalent dissolution to bovine pulp tissue at all time intervals. Furthermore, the EndoUltra yielded significantly more phantom dissolution in the canal block than the EndoActivator or syringe irrigation. Conclusions: Our phantom is comparable to biological tissue in terms of tissue dissolution and could be utilized for in vitro tests due to its injectability and detectability.

• Nuclear Engineering and Technology
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• 제56권4호
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• pp.1310-1319
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• 2024

The reactor cavity cooling system (RCCS) is a passive reactor safety system commonly present in the designs of High-Temperature Gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel by means of natural convection and radiation. It is one of the factors responsible for ensuring that the reactor does not melt down under any plausible accident scenario. For the simulation of accident scenarios, which are transient phenomena unfolding over a span of up to several days, intermediate fidelity methods and system codes must be employed to limit the models' execution time. These models can quantify radiation heat transfer well, but heat transfer caused by natural convection must be quantified with the use of correlations for the heat transfer coefficient. It is difficult to obtain reliable correlations for HTGR RCCS heat transfer coefficients experimentally due to such a system's size. They could, however, be obtained from high-fidelity steady-state simulations of RCCSs. The Rayleigh number in RCCSs is too high for using a Direct Numerical Simulation (DNS) technique; thus, a Reynolds-Averaged Navier-Stokes (RANS) approach must be employed. There are many RANS models, each performing best under different geometry and fluid flow conditions. To find the most suitable one for simulating an RCCS, the RANS models need to be validated. This work benchmarks various RANS models against three experiments performed on the HTTR RCCS Mockup by the Japanese Atomic Energy Agency (JAEA) in 1993. This facility is a 1/6 scale model of a vessel cooling system (VCS) for the High Temperature Engineering Test Reactor (HTTR), which is operated by JAEA. Multiple RANS models were evaluated on a simplified 2d-axisymmetric geometry. They were found to reproduce the experimental temperature profiles with errors of up to 22% for the lowest temperature benchmark and 15% for the higher temperature benchmarks. The results highlight that the pragmatic turbulence models need to be validated for high Rayleigh natural convection-driven flows and improved accordingly, more publicly available experimental data of RCCS resembling experiments is needed and indicate that a 2d-axisymmetric geometry approximation is likely insufficient to capture all the relevant phenomena in RCCS simulations.

• 한국정보과학회논문지:시스템및이론
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• 제26권9호
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• pp.1177-1184
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• 1999

본 논문에서는 스캔플립프롭 선택 시간이 짧고 높은 고장 검출률(fault coverage)을 얻을 수 있는 새로운 부분스캔 설계 기술을 제안한다. 순차회로에서 테스트패턴 생성을 용이하게 하기 위하여 완전스캔 및 부분스캔 설계 기술이 널리 이용되고 있다. 스캔 설계로 인한 추가영역을 최소화 하고 최대의 고장 검출률을 목표로 하는 부분스캔 기술은 크게 구조분석과 테스트 가능도(testability)에 의한 설계 기술로 나누어 볼 수 있다. 구조분석에 의한 부분스캔은 짧은 시간에 스캔플립프롭을 선택할 수 있지만 고장 검출률은 낮다. 반면 테스트 가능도에 의한 부분스캔은 구조분석에 의한 부분스캔보다 스캔플립프롭의 선택 시간이 많이 걸리는 단점이 있지만 높은 고장 검출률을 나타낸다. 본 논문에서는 구조분석에 의한 부분스캔과 테스트 가능도에 의한 부분스캔 설계 기술의 장단점을 비교.분석하여 통합함으로써 스캔플립프롭 선택 시간을 단축하고 고장 검출률을 높일 수 있는 새로운 부분스캔 설계 기술을 제안한다. 실험결과 대부분의 ISCAS89 벤치마크 회로에서 스캔플립프롭 선택 시간은 현격히 감소하였고 비교적 높은 고장 검출률을 나타내었다.Abstract This paper provides a new partial scan design technique which not only reduces the time for selecting scan flip-flops but also improves fault coverage. To simplify the problem of the test pattern generation in the sequential circuits, full scan and partial scan design techniques have been widely adopted. The partial scan techniques which aim at minimizing the area overhead while maximizing the fault coverage, can be classified into the techniques based on structural analysis and testabilities. In case of the partial scan by structural analysis, it does not take much time to select scan flip-flops, but fault coverage is low. On the other hand, although the partial scan by testabilities generally results in high fault coverage, it requires more time to select scan flip-flops than the former method. In this paper, we analyzed and unified the strengths of the techniques by structural analysis and by testabilities. The new partial scan design technique not only reduces the time for selecting scan flip-flops but also improves fault coverage. Test results demonstrate the remarkable reduction of the time to select the scan flip-flops and high fault coverage in most ISCAS89 benchmark circuits.

• 유통과학연구
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• 제11권10호
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• pp.55-62
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• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.