• Bulletin of the Korean Chemical Society
• /
• 제10권4호
• /
• pp.372-374
• /
• 1989

The new viscosity theory is applied to the abnormal behavior of the viscosity near the critical point. This theory suggests that the viscosity is equal to the product of the absolute pressure(kinetic pressure + internal pressure) and the collision time. We can find this abnormal behavior to be due to the large collision time near the critical point. The agreements between theoriticals and experimentals of the critical enhancement are satisfactory.

• 디지털산업정보학회논문지
• /
• 제8권1호
• /
• pp.125-137
• /
• 2012

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. For such reason, lots of intrusion detection system has been developed. Intrusion detection system has abilities to detect abnormal behavior and unknown intrusions also it can detect intrusions by using patterns studied from various penetration methods. Various algorithms are studying now such as the statistical method for detecting abnormal behavior, extracting abnormal behavior, and developing patterns that can be expected. Etc. This study using clustering of data mining and association rule analyzes detecting areas based on two models and helps design detection system which detecting abnormal behavior, unknown attack, misuse attack in a large network.

• 통상정보연구
• /
• 제9권3호
• /
• pp.305-320
• /
• 2007

With expanded use of B2B(between enterprises), B2G(between enterprises and government) and EDI(Electronic Data Interchange), and increased amount of available network information and information protection threat, as it was judged that security can not be perfectly assured only with security technology such as electronic signature/authorization and access control, Bayesian networks have been developed for protection of information. Therefore, this study speculates Bayesian networks system, centering on ERP(Enterprise Resource Planning). The Bayesian networks system is one of the methods to resolve uncertainty in electronic data interchange and is applied to overcome uncertainty of abnormal invasion detection in ERP. Bayesian networks are applied to construct profiling for system call and network data, and simulate against abnormal invasion detection. The host-based abnormal invasion detection system in electronic trade analyses system call, applies Bayesian probability values, and constructs normal behavior profile to detect abnormal behaviors. This study assumes before and after of delivery behavior of the electronic document through Bayesian probability value and expresses before and after of the delivery behavior or events based on Bayesian networks. Therefore, profiling process using Bayesian networks can be applied for abnormal invasion detection based on host and network. In respect to transmission and reception of electronic documents, we need further studies on standards that classify abnormal invasion of various patterns in ERP and evaluate them by Bayesian probability values, and on classification of B2B invasion pattern genealogy to effectively detect deformed abnormal invasion patterns.

• 한국세라믹학회지
• /
• 제32권5호
• /
• pp.587-593
• /
• 1995

Abnomal grain growth behavior of BaTiO3 ceramics was investigated with addition of seed grains. It was foudn that the nucleation rate of abnormal grain was constant and growth of abnormal grain was linearly increased with sitnering time, regardless of amount of seed grains. These facts were also confirmed by fitting of the volume fraction of abnormal grain vs. sintering time using Avrami type equation (n=4). It was suggested that seed grains did not change the nucleation rate or growth mechanism of abnormal grain but increase the number of abnormal grains at initial stage of sintering and then it led to fine microstructure of BaTiO3 ceramics.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2009년도 제38회 동계학술대회 초록집
• /
• pp.438-438
• /
• 2010

The abnormal behavior of the argon metastable density during the E-H mode transition in argon ICP discharge was investigated. Lots of investigations including global models expected that during and after the mode transition of ICP discharge, the density of metastable increases with applied rf power (i.e. electron density). However, recent direct measurement of metastable density revealed that the metastable density of argon decreases with the applied power during and after the mode transition. This result may not be explained by the previous global model which is based on the assumption of the Maxwellian electron energy distribution function (EEDF). In this paper, to explain this abnormal behavior with simple manners, a simple global model taking account of the effect of the non-Maxwellian EEDFs incorporating into a set of coupled rate equations is proposed. The result showed that the calculated metastable density taking account of non-Maxwellian EEDF and its evolution during the transition has an abnormal behavior with electron density and is in good agreement with the previous measurement results, indicating the close coupling of electron kinetics and the behavior of metastable density. The proposed simple model is expected to provide qualitative kinetic insight to understand the behavior of the metastable density in various plasma discharges which typically exhibit non-Maxwellian distribution.

• 한국통신학회논문지
• /
• 제39C권8호
• /
• pp.731-737
• /
• 2014

본 논문에서는 감시 카메라 환경에서 발생할 수 있는 군중의 비정상 행동 검출 방법을 제안한다. 군중들의 비정상 행동을 산발적으로 퍼지면서 뛰는 행동, 한쪽 방향으로 갑자기 뛰는 행동 두 가지로 정의하였다. 이를 검출하기 위하여 영상에서 움직임 벡터를 추출하여 군중의 비정상 행동 검출에 적합한 서술자 MHOF(Multi-scale Histogram of Optical Flow)와 DCHOF(Directional Change Histogram of Optical Flow)제안하였으며, 이를 이진 분류기인 SVM(Support Vector Machine)을 이용하여 검출하였다. 제안한 방법은 공개 데이터셋인 UMN 데이터와 PETS 2009 데이터를 이용하여 성능을 평가하였고 다른 방법론과의 비교를 통해 제안하는 알고리즘의 우수성을 입증하였다.

• 대한전자공학회논문지SP
• /
• 제48권1호
• /
• pp.111-121
• /
• 2011

지능형 비디오 분석시스템은 불특정 다수의 객체가 가지는 행동을 분석하고, 불의의 사고를 사전에 예측하여 관리자에게 경고를 전달하는 기술을 필요로 한다. 본 논문은 적응적으로 배경을 생성하여 월담, 실신, 버려진 물체, 배회와 같이 사전에 정의된 이상행위를 분석하는 기술을 제안한다. 제안된 비디오 분석 시스템은 배경 생성과 이상 행위 분석 모듈로 구성된다. 강건한 배경 생성을 위해서 영상 내의 움직임 변화를 검출하여 매 순간마다 움직임이 없는 영역을 지속적으로 갱신하고, 이를 기반으로 객체를 검출한다. 또한 객체 검출의 정확성을 높이기 위해 검출된 결과에서 잡음과 그림자 제거 단계를 추가하였다. 이상행위 분석 모듈에서는 검출된 객체로부터 무게 중심, 실루엣, 크기, 이동 궤적 정보를 추출한다. 이때 이상행위의 판단은 월담, 실신, 버려진 물체, 배회에 따라 시나리오 환경으로 구성하고 분석하였다. 실험 결과에서 제안된 시스템은 복잡한 배경 환경에서도 이동 객체 검출 및 이상행위 분석이 가능하였다.

• 정신신체의학
• /
• 제4권1호
• /
• pp.138-145
• /
• 1996

동일한 질병을 갖고 있거나, 같은 증상을 호소하는 환자의 경우라도 병과 관련된 행동은 사람마다 각기 다르다. 이러한 행동 양식을 잘 이해하는 것은 병의 진단과 치료 방법, 치료 순응도와 치료 효과를 결정하는 데에 중요한 요소가 된다. 비정상적인 질병 행동은 병자 역할이 핵심이 되며, 간혹 병을 부정하거나 무시하는 반대의 경우도 있다. 비정상적인 질병행동에 대한 평가는 기질적 원인이 밝혀지지 않는 여러 기능성 장애를 규명하는 한가지 방법으로 이용될 수 있으며, 인지 치료 내지는 재활, 직업 치료시에도 활용할 수 있는 중요한 개념으로 알려져 있다. 향후 한국인에게 맞는 치료법의 개발을 위해서는 각 질병에 따른 의학 역사적 관점, 사회 문화적 요소가 어우러진 통합적인 질병 행동 연구가 필요하리라 사료된다. 이는 의료 경제 측면에서도 필수적인 내용이 될 것이다.

• 한국세라믹학회지
• /
• 제32권1호
• /
• pp.51-56
• /
• 1995

Variation of sintered density of BaTiO3 powder calcined at 120$0^{\circ}C$ and 135$0^{\circ}C$ was investigated with respect to the grain growth behavior. It was found that BaTiO3 powder, which was calcined at 120$0^{\circ}C$, showed abnormal grain growth behavior during sintering process. At initial stage of sintering process, the densification rate of specimen was accelerated with rapid grain growth caused by the abnormal grain growth. But with the increase of sintering time, abnormally grown grain met each other and the density of specimen decreased drastically due to coalescence of pores located in triple junction. On the contrary, BaTiO3 powder calcined at 135$0^{\circ}C$ showed normal grain growth behavior and gradually densified with the increase of sintering time.

• International journal of advanced smart convergence
• /
• 제9권4호
• /
• pp.120-123
• /
• 2020

The surveillance system to prevent crime and accidents in advance has become a necessity, not an option in real life. Not only public institutions but also individuals are installing surveillance cameras to protect their property and privacy. However, since the installed surveillance camera cannot be monitored for 24 hours, the focus is on the technology that tracks the video after an accident occurs rather than prevention. In this paper, we propose a system model that monitors abnormal behaviors that may cause crimes through real-time video, and when a specific behavior occurs, the surveillance system automatically detects it and responds immediately through an alarm. We are a model that analyzes real-time images from surveillance cameras and uses I3D models from analysis servers to analyze abnormal behavior and deliver notifications to web servers and then to clients. If the system is implemented with the proposed model, immediate response can be expected when a crime occurs.