• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• 한국통신학회논문지
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• 제25권6A호
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• pp.910-917
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• 2000

Because the random early detection(RED) algorithm deals all flows with the same best-effort traffic characteristic, it can not correctly control the output link bandwidth for the flows with different traffic characteristics. To remedy this problem, several per-flow algorithms have been proposed. In this paper, we propose a new per-flow type Fair Droptail algorithm which can fairly allocate bandwidth among flows over a shared output link. By evenly allocating buffers per flow, the Fair Droptail can restrict a flow not to use more bandwidth than others. In addition, it can be simply implemented even if it employs the per-flow state mechanism, because the Fair Droptail only keeps each information of flow in active state.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.354-357
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• 2020

DDoS(Distributed Denial of Service) 공격은 현재의 인터넷 환경뿐만 아니라 NDN에서도 정상적인 서비스를 저해시키는 주요 문제이며 이에 관련된 다양한 연구들이 진행되고 있다. 본 논문에서는 DDoS 공격이 가해질 때 NDN 라우터의 PIT(Pending Interest Table) 가용성 저해로 인해 발생하는 문제 해결에 중점을 둔다. 이를 위한 방안으로 RED(Random Early Detection) 알고리즘을 기반으로 하는 기법을 적용하고, 시뮬레이션을 통한 측정 결과를 보여준다.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.123-130
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• 2022

During the past decades, detection of gear defects remains as a major problem, especially when the gears are subject to non-stationary phenomena. The idea of this paper is to mixture a multilevel wavelet transform with a fast EMD decomposition in order to early detect gear defects. The sensitivity of a kurtosis is used as an indicator of gears defect burn. When the gear is damaged, the appearance of a crack on the gear tooth disrupts the signal. This is due to the presence of periodic pulses. Nevertheless, the existence of background noise induced by the random excitation can have an impact on the values of these temporal indicators. The denoising of these signals by multilevel wavelet transform improves the sensitivity of these indicators and increases the reliability of the investigation. Finally, a defect diagnosis result can be obtained after the fast transformation of the EMD. The proposed approach consists in applying a multi-resolution wavelet analysis with variable decomposition levels related to the severity of gear faults, then a fast EMD is used to early detect faults. The proposed mixed methods are evaluated on vibratory signals from the test bench, CETIM. The obtained results have shown the occurrence of a teeth defect on gear on the 5th and 8th day. This result agrees with the report of the appraisal made on this gear system.

• 한국산업정보학회논문지
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• 제28권5호
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• pp.109-126
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• 2023

대형 산림화재를 예방하기 위해 산림화재의 조기발견은 매우 중요하다. 조기발견을 위한 하나의 방안으로 산림화재 발생 예측이 고려되고 있으며 다양한 관련 연구가 진행되었다. 그러나 대다수의 선행연구가 산림화재의 주요 발화 원인 중의 하나인 인적요인을 고려하지 않고 기상요인과 지리적 요인만을 주로 다루고 있다. 따라서 본 연구는 기상 및 지리적 요인뿐만 아니라 인적요인을 고려한 산림화재 예측모형을 개발하기 위해 2003년부터 2020년까지의 강원도 산림화재 데이터를 활용하여 로지스틱 회귀모형과 다양한 머신러닝 기법 기반의 예측모형을 개발하고 성능을 비교분석하였다. 성능분석 결과, 머신러닝 기법인 랜덤 포레스트(AUC=0.920)와 XG Boost 모형(AUC=0.925)이 가장 우수한 성능을 나타냈다. 운영시사점을 도출하기 위해 순열특성중요도 분석을 활용하여 요인들의 상대적 중요도를 분석하였으며, 기상요인이 인적요인보다 높은 영향도를 나타냈지만 다양한 인적요인도 유효한 것으로 확인되었다.

• 한국전문물리치료학회지
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• 제7권3호
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• pp.1-18
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• 2000

The present study was performed to investigate the prevalence rate of idiopathic scoliosis and to determine the effect of exercise training on scoliotic angle in elementary school children. In this study, two out of five elementary schools in Seosan city were chosen by random sampling. Seven hundred sixty four students (from four grade to the sixth grade student) were selected in two schools. Screening tests were conducted to find idiopathic scoliosis. Among the 764 individuals, 139 subjects who showed positive sign in physical examination took whole spine radiography. Thirty six subjects who had a curve of 10 or greater and consented to participate in the exercise program were selected for the exercise program. The exercise program was performed four times a week for 5 months. The results of this study were as follows: 1) One hundred thirty nine subjects showed positive sign in the scoliosis screening test. 2) The overall prevalence of curve of $10^{\circ}or$ greater in X-ray finding was 8.15%. The prevalencies of curve of $10^{\circ}or$ greater in male and female were 7.1% and 9.2%, respectively. 3) Scoliosis curves were observed at thoracic area (48.4%), at thoracolumbar area (27.4%) and at lumbar area(24.4%). 4) Right side curve was 59.7%, and left side curve was 40.3%. 5) After the 5 month exercise program for scoliosis, the Cobb's angle was significantly decreased. 6) There was no significant difference of Cobb's angle change respect to sex, grades, and scoliosis curve site. Results shown here indicates that an early detection and early exercise for scoliosis can result in decreased the Cobb's angle in elementary school children.

• Journal of Information Processing Systems
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• 제5권1호
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2429-2432
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• 2013

Background and Objectives: Yanting in Sichuan Province is one of the highest risk areas of esophageal cancer (EC) in the world. We here summarize the epidemiology of EC in Yanting using data from the national screening programme during 2006-2011. Methods: Random cluster sampling was used to select a proportion of natural villages from six towns in Yanting, and residents aged 40-69 years old were invited for screening. Participants were screened using endoscopy with iodine staining and then confirmed by histological examinations. Results: The overall detection rates of low-grade hyperplasia (LH), moderate hyperplasia (MH), high-grade hyperplasia (HH), carcinoma in situ (CIS), intramucosal carcinoma (IC) and invasive carcinoma (INC) were 5.33%, 1.28%, 0.68%, 0.15%, 0.06% and 0.29%, respectively. The detection rates of LH, MH, HH and INC increased with age, reaching the peak among those aged 60-65 years, and the prevalences of LH and MH were higher among men than among women. In addition, the detection rates of hyperplasia were much higher in mountainous than in hilly areas. Conclusions: Among the high risk population, there are a great number of people with early-stage EC or precancerous conditions who do not have presenting symptoms. In particular, the elderly, men, or those living in mountainous areas are the most vulnerable population. It is therefore important to reinforce health education and screening services among such high risk populations.

• 마케팅과학연구
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• 제16권1호
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• pp.13-26
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• 2006

본 연구에서는 안정적 NBD모형에 개별구매자들의 평균적 구매율 변화로 발생되는 임의의 불안정성이 개입하였는지를 체계적으로 검정하기 위한 방법을 개발하였다. 이를 위해 본 연구에서는 안정적 NBD모형에서 개별구매자들의 갖는 평균적 구매율이 임의의 불안정성의 영향으로 구조적 변화를 일으키는지에 대한 통계적 가설로부터 우도비를 도출하였다. 또한, 본 연구에서는 반복구매가 이루어지는 패널자료를 대상으로 개발된 ㅂ아법의 실증적 적합성을 살펴보았다. 본 연구의 결과는 NBD모형이 지니는 안정성의 가정을 극복할 수 있는 수단을 제공한다는 점, 마케팅환경의 변화를 조기에 감지함으로써 관련 환경변화에 신속히 대처할 수 있는 마케팅전략의 운용을 가능케 할 것이란 점, 특정 마케팅믹스전략의 효과측정에도 활용될 수 있다는 점 등을 기대할 수 있다.

• 인터넷정보학회논문지
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• 제23권3호
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• pp.35-45
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• 2022

현대에도 일부 소외된 지역에서는 의료 인력의 부족으로 인해 위·중증 환자에 대한 치료가 지연되는 경우가 많다. 의료 데이터에 대한 분석을 자동화하여 의료 서비스의 접근성 문제 및 의료 인력 부족을 해소하고자 하는 연구가 계속되고 있다. 컴퓨터 비전 기반의 진료 자동화는 훈련 목적에 대한 데이터 수집 및 라벨링 작업에서 많은 비용이 요구된다. 이러한 점은 희귀질환이나 시각적으로 뚜렷하게 정의하기 어려운 병리적 특징 및 기전을 구분하는 작업에서 두드러진다. 이상 탐지는 비지도 학습 전략을 채택함으로써 데이터 수집 비용을 크게 절감할 수 있는 방법으로 주목된다. 본 논문에서는 기존의 이상 탐지 기법들을 기반으로, 흉부 X-RAY 영상에 대해 이상 탐지를 수행하는 방법을 다음과 같이 제안한다. (1) 최적 해상도로 샘플링된 의료 영상의 색상 범위를 정규화한다. (2) 무병변 영상으로부터 패치 단위로 구분된 중간 수준 특징 집합을 추출하여 그 중 높은 표현력을 가진 일부 특징 벡터들을 선정한다. (3) 최근접 이웃 탐색 알고리즘을 기반으로 미리 선정된 무병변(정상) 특징 벡터들과의 차이를 측정한다. 본 논문에서는 PA 방식으로 촬영된 흉부 X-RAY 영상들에 대한 제안 시스템의 이상 탐지 성능을 세부 조건에 따라 상세히 측정하여 제시한다. PadChest 데이터세트로부터 추출한 서브세트에 대해 0.705 분류 AUROC를 보임으로써 의료 영상에 대한 이상 탐지 적용의 효과를 입증하였다. 제안 시스템은 의료 기관의 임상 진단 워크플로우를 개선하는 데에 유용하게 사용될 수 있으며, 의료 서비스 접근성이 낮은 지역에서의 조기 진단을 효율적으로 지원할 수 있다.