• Journal of Information Processing Systems
• /
• 제14권3호
• /
• pp.569-589
• /
• 2018

Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.

• 한국산학기술학회논문지
• /
• 제15권5호
• /
• pp.3121-3131
• /
• 2014

메모리 관련 취약점은 컴퓨터 시스템 상에서의 가장 위협적인 공격이며 메모리 취약점을 이용한 실제 공격의 또한 증가하고 있다. 따라서 다양한 메모리 보호 메커니즘이 연구되고 운영체제 상에서 구현되었지만, 보호 시스템들을 우회하기 위한 새로운 공격 기법들이 함께 발전하고 있다. 특히, 메모리 관련 공격 기법 중 버퍼 오버플로우 공격은 코드 재사용 공격이라 불리는 Return-Oriented Programming(ROP), Jump-Oriented Programming(JOP)등으로 발전하여 운영체제가 포함하는 메모리 보호 메커니즘을 우회하고 있다. 본 논문에서는 코드 재사용 공격 기법의 특징을 분석하고, 분석된 결과를 이용하여 바이너리 수준에서의 코드 재사용 공격을 탐지할 수 있는 메커니즘을 제안하며, 실험을 통해 제안하는 메커니즘이 코드 재사용 공격을 효율적으로 탐지할 수 있음을 증명한다.

• Journal of Information Processing Systems
• /
• 제13권5호
• /
• pp.1372-1381
• /
• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Elastomers and Composites
• /
• 제39권4호
• /
• pp.318-323
• /
• 2004

Poly(ethylene-co-13.8 mol% octene) ($PEO_{13.8}$), Poly(ethylene-co-15.3 mol% octene) ($PEO_{15.3}$)과 분자크기와 분자구조가 각각 다른 탄화수소의 2성분계 혼합물에 대한 cloud-point, bubble-point 압력을 $150^{\circ}C$, 450 bar까지 측정하였다. (PEO+n-프로판), (PEO+n-부탄) 2성분계 혼합물에서 cloud-point 곡선이 측정되었고, (PEO+n-펜탄) 혼합물에서는 cloud-point와 bubble-point 곡선이 모두 측정되었다. (PEO+시클로펜탄), (PEO+시클로헥산), (PEO+시클로 헵탄), (PEO+시클로옥탄) 2성분계 혼합물에서는 bubble-point 곡선이 측정되었다. (PEO+탄화수소) 2성분계의 압력-조성 등온곡선과 온도-조성 등압곡선은 PEO의 농도가 약 5 wt%일 때 각각 최고점과 최저점을 가졌다. (PEO+탄화수소) 2성분계는 PEO 농도가 5 wt%에서 임계조성을 가진다. PEO는 n-알칸과 시클로알칸 용매에서 LCST 유형의 상거동을 보여주며, 탄화수소의 분자크기가 증가할수록 PEO의 녹는 압력은 감소하였고 용해도는 증가하였다.

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

• Journal of Preventive Medicine and Public Health
• /
• 제54권4호
• /
• pp.230-237
• /
• 2021

Objectives: This study explored changes in individuals' behavior in response to social distancing (SD) levels and the "no gatherings of more than 5 people" (NGM5) rule in Korea during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Using survey data from the COVID-19 Behavior Tracker, exploratory factor analysis extracted 3 preventive factors: maintenance of personal hygiene, avoiding going out, and avoiding meeting people. Each factor was used as a dependent variable. The chisquare test was used to compare differences in distributions between categorical variables, while binary logistic regression was performed to identify factors associated with high compliance with measures to prevent transmission. Results: In men, all 3 factors were significantly associated with lower compliance. Younger age groups were associated with lower compliance with maintenance of personal hygiene and avoiding meeting people. Employment status was significantly associated with avoiding going out and avoiding meeting people. Residence in the capital area was significantly associated with higher compliance with personal hygiene and avoiding venturing out. Increasing SD levels were associated with personal hygiene, avoiding going out, and avoiding meeting people. The NGM5 policy was not significantly associated with compliance. Conclusions: SD levels, gender, age, employment status, and region had explanatory power for compliance with non-pharmaceutical interventions (NPIs). Strengthening social campaigns to inspire voluntary compliance with NPIs, especially focused on men, younger people, full-time workers, and residents of the capital area is recommended. Simultaneously, efforts need to be made to segment SD measures into substrategies with detailed guidance at each level.

• 융합보안논문지
• /
• 제18권1호
• /
• pp.13-18
• /
• 2018

암호시스템에서 효율성은 매우 중요한 요소 중의 하나이다. 천정희 외 3인은 이산대수 문제에 기반하는 암호 시스템에서 지수승 연산 속도를 높이기 위해 새로운 지수 형태를 제안하였다. 제안된 변형은 고정된 원소 ${\alpha}$와 작은 해밍 웨이트를 가지는 두 원소 $e_1$, $e_2$에 대해 $e_1+{\alpha}e_2$로 표현되며 스플릿 지수라 불린다. 그들은 $e_1$, $e_2$를 각각 $Z_p$의 부분집합이면서 언밸런스드 부분집합인 $S_1$, $S_2$에서 선택하였다. 본 논문에서는 $S_1$, $S_2$를 $Z_p$의 부분집합이면서 밸런스드 부분집합이 되도록 하여 효율성을 개선한다. 결과적으로, 이진 유한체에서의 지수승 연산 속도는 9.1%, 코블리츠 곡선에서의 스칼라 곱셈 연산 속도는 12.1% 빨라진다.

• 한국정보기술학회논문지
• /
• 제17권6호
• /
• pp.17-25
• /
• 2019

최근 자주 발생하는 싱크 홀(sinkhole)을 정확하게 발견하고 추적하는 것은 사람 및 재산 피해를 예방하기 위해서 매우 중요하다. 그 동안 싱크 홀을 검출하기 위한 방안들이 많이 제안되었지만 지하 깊은 곳에서 발생하는 싱크 홀에 대한 검출은 완전히 해결되지 않고 있다. 또한 실시간으로 싱크 홀을 감지하고 실시간으로 경고를 발생하는 시스템은 아직 안정화되지 않은 상태이다. 본 연구는 딥 러닝과 데이터 결합에 의해 싱크 홀을 실시간으로 검출하기 위한 연구이며, 제안하는 알고리즘은 크게 바이너리 분할(binrary segmentation), 싱크 홀분류(sinkhole classification) 및 싱크 홀 추적(sinkhole tracking)의 세 가지 주요 부분으로 구성된다. 실험 결과 싱크 홀이 실시간으로 데이터 세트에서 추적 될 수 있음을 보여주었다. 따라서 본 연구에서 제안된 시스템은 싱크 홀을 탐지하기 위해서 실제로 적용될 수 있음을 보여준다.

• Imaging Science in Dentistry
• /
• 제51권1호
• /
• pp.9-16
• /
• 2021

Purpose: The purpose of this study was to analyze the reliability of 7 panoramic radiographic signs for predicting proximity of the root apices of mandibular third molars to the mandibular canal using cone-beam computed tomography and to correlate these findings with the Pell and Gregory and the Winter classification systems. Materials and Methods: An observational, cross-sectional, descriptive study was conducted on 74 patients with bilateral impacted mandibular third molars. Four panoramic radiographic signs were observed in the tooth root (darkening, deflection, and narrowing of the root apices, and bifid apices), and another 3 in the mandibular canal (diversion, narrowing, and interruption of the mandibular canal). Cone-beam computed tomography images were analyzed to identify disruption and diversion of the mandibular canal and root deflection. Results: Binary logistic regression showed that only 4 of the 7 panoramic radiographic signs were able to predict proximity of the root apices of the mandibular third molars to the mandibular canal: darkening of the root, deflection of the root, narrowing of the root, and interruption of the mandibular canal(P<0.05). Conclusion: Darkening, deflection, and narrowing of the root, in tandem with the interruption of the mandibular canal on panoramic radiographs, indicate that cone-beam computed tomography should be performed when planning the extraction of impacted mandibular third molars. Proximity between mandibular third molars and the mandibular canal is correlated with the Winter classification.

• 한국정보통신학회논문지
• /
• 제26권5호
• /
• pp.641-648
• /
• 2022

본 논문은 3D 프린터 출력 방식 중 하나인, 전자빔용해법(EBM)의 공정 간에 발생하는 결함에 영향을 미치는 요인들을 데이터 분석을 통해 규명하는 연구이다. 선행 연구들을 기반으로 결함발생에 주요한 원인으로 지목되는 요소들을 참고하였으며, 공정 간 발생하는 로그파일 분석을 통해 결함 발생과 연관된 변수들을 추출하였다. 또한, 해당 데이터가 시계열 데이터라는 점에 착안하여 window의 개념을 도입하여, 현재 공정 층으로부터 총 3개 전 층까지의 데이터를 포함하여 분석에 사용 될 변수들을 구성하였다. 해당 연구의 종속변수는 결함발생유무이기에 이진분류를 통한 분석을 하였으며, 이때 결함 층의 비율이 낮다는(약 4%) 문제로 인해 SMOTE 기법을 적용하여 균형잡힌 훈련용 데이터를 만들었다. 분석을 위해 Gridsearch CV를 활용한 XGBoost를 사용하였고, 분류 성능은 혼동행렬을 기반으로 평가하였다. 마지막으로, SHAP값을 통한 변수 중요도 분석을 통해 연구의 결론을 내렸다.