• Nuclear Engineering and Technology
• /
• 제36권1호
• /
• pp.12-23
• /
• 2004

In the present study a new measurement technique has been developed, which uses an ultrasonic transmission signal in order to identify the vertical two phase flow pattern. The ultrasonic measurement system developed in the present study not only provides the information required for the identification of vertical two phase flow patterns but also makes real time identification possible. Various vertical two phase flow patterns such as bubbly, slug, churn, annular flow etc. have been accurately identified with the present ultrasonic measurement system under atmospheric condition. In addition, the present test apparatus can practically simulate the ultrasonic propagation characteristics under high temperature and high pressure systems. Therefore, it is expected that the present ultrasonic flow pattern identification technique could be applicable to the vertical two phase flow systems under high temperature and high pressure conditions.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2001년도 하계종합학술대회 논문집(2)
• /
• pp.249-252
• /
• 2001

The paper describes the physical design flow of QPSK Demodulator in operating 60MHz. It includes problems and issues of each design flow, verification process for physical layout.

• 한국정보통신학회논문지
• /
• 제13권7호
• /
• pp.1411-1421
• /
• 2009

무선 인터넷이 기하급수적으로 증가함에 따라 최근 네트워킹과 멀티미디어 서비스에 대한 요구가 증대되어가고 있다. RTP는 인터넷 위에서 멀티미디어 통신을 지원하고 확장성과 유선환경에서의 적응력을 높였다. 그러나 RTP는 무선환경 안에서 양단간 QoS를 지원하지 못하는 제한을 갖는다. 본 논문은 실시간 멀티미디어 통신 아키텍쳐를 제안하고 하이브리드 흐름 제어를 설계하고 구현한다. 하이브리드 흐름 제어는 네트워크 상태나 사용자의 특성과 같은 메트릭을 이용한 개선된 AIMD를 기반으로 한다. 멀티캐스트 그룹 관리를 통해서 그룹 기반의 하이브리드 흐름제어를 한다. JMF를 이용하여 제안된 흐름 제어를 구현하여 성능을 분석하였다. 적용한 결과 제안된 흐름 제어가 AIMD보다 좋은 성능을 보여 준다.

• 정보처리학회논문지B
• /
• 제17B권4호
• /
• pp.303-308
• /
• 2010

본 논문에서는 기울기 벡터장과 조건부 엔트로피를 결합한 의료영상 정합 방법을 제안한다. 정합 방법은 조건부 확률의 엔트로피에 기반한 측도를 수행한다. 먼저 공간적 정보를 얻기 위해 윤곽선 정보의 방향을 제공하는 기울기 정보인 기울기 벡터장을 계산한다. 다음으로 주어진 두 영상에서 픽셀의 밝기정보와 에지정보를 결합하여 조인트 히스토그램을 계산하여 조건부 엔트로피를 구하고, 이것을 두 영상의 정합측도로 사용한다. 제안된 방법의 성능평가를 위해 자기공명 영상과 변환된 컴퓨터단층촬영 영상에 기존 방법인 상호정보기반의 측도, 조건부 엔트로피만을 사용한 측도와 비교 실험을 수행한다. 실험결과로부터 제안한 방법이 기존의 최적화 방법들 보다 더 빠르고 정확한 정합임을 알 수 있다.

• 한국병원경영학회지
• /
• 제11권3호
• /
• pp.19-41
• /
• 2006

The Objective of this study was to design the model which predict the future cash flow of hospitals and on the basis of designed model to support sound hospital management by the prediction of future cash flow. The five cash flow measurement variables discussed in financial accrual part were used as variables and these variables were defined as NI, NIDPR, CFO, CFAI, CC. To measure the cash flow B/S related variables, P/L related variables and financial ratio related variables were utilized in this study. To measure cash flow models were designed and to estimate the prediction ability of five cash flow models, the martingale model and the market model were utilized. To estimate relative prediction outcome of cash flow prediction model and simple market model, MAE and MER were used to compare and analyze relative prediction ability of the cash flow model and the market model and to prove superiority of the model of the cash flow prediction model, 32 Regional Public Hospital's cross-section data and 4 year time series data were combined and pooled cross-sectional time series regression model was used for GLS-analysis. To analyze this data, Firstly, each cash flow prediction model, martingale model and market model were made and MAE and MER were estimated. Secondly difference-test was conducted to find the difference between MAE and MER of cash flow prediction model. Thirdly after ranking by size the prediction of cash flow model, martingale model and market model, Friedman-test was evaluated to find prediction ability. The results of this study were as follows: when t-test was conducted to find prediction ability among each model, the error of prediction of cash flow model was smaller than that of martingale and market model, and the difference of prediction error cash flow was significant, so cash flow model was analyzed as excellent compare with other models. This research results can be considered conductive in that present the suitable prediction model of future cash flow to the hospital. This research can provide valuable information in policy-making of hospital's policy decision. This research provide effects as follows; (1) the research is useful to estimate the benefit of hospital, solvency and capital supply ability for substitution of fixed equipment. (2) the research is useful to estimate hospital's liqudity, solvency and financial ability. (3) the research is useful to estimate evaluation ability in hospital management. Furthermore, the research should be continued by sampling all hospitals and constructed advanced cash flow model in dimension, established type and continued by studying unified model which is related each cash flow model.

• 한국항공운항학회지
• /
• 제30권3호
• /
• pp.38-53
• /
• 2022

Recently, the acquisition and production of information using digital tools and the creation of new knowledge are emphasized as important educational elements. Therefore, in this study, the effect of learning achievement according to the digital literacy level of college students was analyzed. For the analysis, a questionnaire is conducted with college students majoring in aviation services attending universities in Seoul Capital Area and Chungcheong area. To verify the hypothesis of the study, demographic characteristics are identified based on the questionnaire, reliability and validity of measurement items are verified, and structural equation model analysis is performed to verify the hypothesis. The analysis results are as follows. First, among the sub-factors of digital literacy competency of college students majoring in aviation service, 'technology use' is found to have a positive effect on 'cognitive flow' and 'emotional flow' of learning flow except 'behavioral flow'. Second, among the sub-factors of digital literacy competency, 'self-learning' is found to have a positive effect on 'cognitive flow', 'emotional flow', and 'behavioral flow' in learning flow. Third, the sub-factors of learning flow, 'cognitive flow', 'emotional flow', and 'behavioral flow' have a positive effect on 'learning satisfaction'. Fourth, 'learning satisfaction' is found to have a positive effect on 'learning outcomes'. Based on the research results, practical support measures and strategies for educational success are presented.

• 한국컴퓨터정보학회논문지
• /
• 제23권11호
• /
• pp.229-238
• /
• 2018

The purpose of this study is to investigate the mediating effect of learners' learning flow in the effect of presence on academic achievement in web-based e-learning. For this purpose, this study analyzed the influencing relationship between the each factor based on the structural model with the learning flow as a mediator variable. Based on existing theoretical studies, learning satisfaction and academic achievement, which represent learning outcomes, are set as dependent variables, and teaching presence, cognitive presence, and social presence are set as independent variables. Data collected from a total of 256 e-learning learners were used in the analysis of this study. According to the results of the analysis, teaching presence, cognitive presence, and social presence were found to have a significant effect on academic achievement when a learning flow is a mediator variable. Concretely, teaching presence, cognitive presence, and social presence have a positive effect on the learning flow, while learning flow has a positive effect on learning satisfaction. On the other hand, learning flow has a negative effect on academic achievement. As a result of verifying the mediating effect of learning flow on the relationship between presence, learning satisfaction, and academic achievement, there was meditating effect in the aggregate. This study implies that in order to increase the level of learning satisfaction and academic achievement, it is necessary to make the teaching-learning design in the provision of contents and materials for e-learning so that the learner can feel the presence. The results of this study can be used as a basic data for seeking support and promotion strategies for enhancement of future learning flow and presence.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권10호
• /
• pp.3858-3874
• /
• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권1호
• /
• pp.264-284
• /
• 2021

As the next-generation network architecture, software-defined networking (SDN) has great potential. But how to forward data packets safely is a big challenge today. In SDN, packets are transferred according to flow rules which are made and delivered by the controller. Once flow rules are modified, the packets might be redirected or dropped. According to related research, we believe that the key to forward data flows safely is keeping the consistency of flow rules. However, existing solutions place little emphasis on the safety of flow rules. After summarizing the shortcomings of the existing solutions, we propose FRChain to ensure the security of SDN data forwarding. FRChain is a novel scheme that uses blockchain to secure flow rules in SDN and to detect compromised nodes in the network when the proportion of malicious nodes is less than one-third. The scheme places the flow strategies into blockchain in form of transactions. Once an unmatched flow rule is detected, the system will issue the problem by initiating a vote and possible attacks will be deduced based on the results. To simulate the scheme, we utilize BigchainDB, which has good performance in data processing, to handle transactions. The experimental results show that the scheme is feasible, and the additional overhead for network performance and system performance is less than similar solutions. Overall, FRChain can detect suspicious behaviors and deduce malicious nodes to keep the consistency of flow rules in SDN.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권6호
• /
• pp.2781-2800
• /
• 2016

Emerging attacks aim to access proprietary assets and steal data for business or political motives, such as Operation Aurora and Operation Shady RAT. Skilled Intruders would likely remove their traces on targeted hosts, but their network movements, which are continuously recorded by network devices, cannot be easily eliminated by themselves. However, without complete knowledge about both inbound/outbound and internal traffic, it is difficult for security team to unveil hidden traces of intruders. In this paper, we propose an autonomous anomaly detection system based on behavior profiling and relation mining. The single-hop access profiling model employ a novel linear grouping algorithm PSOLGA to create behavior profiles for each individual server application discovered automatically in historical flow analysis. Besides that, the double-hop access relation model utilizes in-memory graph to mine time-sequenced access relations between different server applications. Using the behavior profiles and relation rules, this approach is able to detect possible anomalies and violations in real-time detection. Finally, the experimental results demonstrate that the designed models are promising in terms of accuracy and computational efficiency.