• The Korean Journal of Nuclear Medicine Technology
• /
• v.24 no.1
• /
• pp.15-19
• /
• 2020

Purpose Generative Adversarial Network(GAN) is one of deep learning technologies. This is a way to create a real fake image after learning the real image. In this study, after acquiring artificial intelligence images through GAN, We were compared and evaluated with real scan time images. We want to see if these technologies are potentially useful. Materials and Methods 30 patients who underwent ¹⁸F-FDG Brain PET/CT scanning at Severance Hospital, were acquired in 15-minute List mode and reconstructed into 1,2,3,4,5 and 15minute images, respectively. 25 out of 30 patients were used as learning images for learning of GAN and 5 patients used as verification images for confirming the learning model. The program was implemented using the Python and Tensorflow frameworks. After learning using the Pix2Pix model of GAN technology, this learning model generated artificial intelligence images. The artificial intelligence image generated in this way were evaluated as Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR), and Structural Similarity Index(SSIM) with real scan time image. Results The trained model was evaluated with the verification image. As a result, The 15-minute image created by the 5-minute image rather than 1-minute after the start of the scan showed a smaller MSE, and the PSNR and SSIM increased. Conclusion Through this study, it was confirmed that AI imaging technology is applicable. In the future, if these artificial intelligence imaging technologies are applied to nuclear medicine imaging, it will be possible to acquire images even with a short scan time, which can be expected to reduce artifacts caused by patient movement and increase the efficiency of the scanning room.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.4
• /
• pp.283-289
• /
• 2018

Launch Acceptability Region(LAR) means an area for successfully hitting the target. And LAR should be calculated in real time on aircraft so that LAR can be seen by pilot. LAR can be changed by the launch condition of the bomb, the impact condition of the target, and the atmospheric condition at the time of flight of the bomb. In this paper, we propose the calculation method of LAR using Artificial Neural Network(ANN). The learning data was generated by changing each condition from existing LAR model, and LAR model was derived through ANN learning. We confirmed the accuracy of the new LAR model by comparing the difference between the result data of existing LAR model and the new LAR model. And we confirmed the possibility of real time calculation of the LAR model on the aircraft by comparing the calculation time.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.11
• /
• pp.1333-1343
• /
• 1999

경성 실시간 시스템의 태스크들은 논리적으로 올바른 결과를 산출해야 하지만 또한 각자의 시간 제한 조건을 만족하여야 한다. 간격제한 스케줄링은 시간 제한 조건이 시간 간격 제한으로 주어지는 실시간 태스크들을 스케줄하기 위하여 도입되었다. 간격제한 스케줄링에서의 각 태스크들은 시간 간격 제한 조건을 갖는데, 이것은 태스크의 두 연속적인 수행의 종료시간에 대해 제한을 가한다. 다시 말해, 간격제한 스케줄링에서의 각 태스크 수행은 그 태스크의 직전 수행 완료 시간으로부터 발생하는 데드라인을 갖는다. 간격제한 태스크 스케줄링에 관한 많은 연구는 단순화 방법에 기초하고 있다. 그러나, 우리는 이 논문에서 단순화 방법을 사용하지 않고, 정적 우선순위 및 정적 분리 제한 정책을 채용한 새로운 간격제한 태스크 스케줄링 방법을 제안한다. 제안된 정적 할당 방법은 스케줄링 분석 및 구현을 매우 간단히 할 수 있으며, 또한 스케줄러의 실행시간 오버헤드를 줄일 수 있다.Abstract Tasks in hard real-time systems must not only be logically correct but also meet their timing constraints. The distance-constrained scheduling has been introduced to schedule real-time tasks whose timing constraints are characterized by temporal distance constraints. Each task in the distance-constrained scheduling has a temporal distance constraint which imposes restriction on the finishing times of two consecutive executions of the task. Thus, each execution of a task in the distance-constrained scheduling has a deadline relative to the finishing time of the previous execution of the task.Much work on the distance-constrained task scheduling has been based on the reduction technique. In this paper, we propose a new scheme for the distance-constrained task scheduling which does not use the reduction technique but adopts static priority and static separation constraint assignment policy. We show that our static assignment approach can simplify the scheduling analysis and its implementation, and can also reduce the run-time overhead of the scheduler.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.27 no.1
• /
• pp.693-700
• /
• 2009

For real-time precise GPS data processing such as a long baseline network RTK (Real-Time Kinematic) survey, PPP (Precise Point Positioning) and monitoring of ionospheric/tropospheric delays, it is necessary to guarantee accuracy comparable to IGS (International GNSS Service) precise orbit with no latency. As a preliminary study for determining near real-time satellite orbits, the general procedures of satellite orbit determination, especially the dynamic approach, were studied. In addition, the transformation between terrestrial and inertial reference frames was tested to integrate acceleration. The IAU 1976/1980 precession/nutation model showed a consistency of 0.05 mas with IAU 2000A model. Since the IAU 2000A model has a large number of nutation components, it took more time to compute the transformation matrix. The classical method with IAU 2000A model was two times faster than the NRO (non-rotating origin) approach, while there is no practical difference between two transformation matrices.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.8
• /
• pp.1366-1372
• /
• 2006

After the import liberalization of agricultural products, The Imported agricultural products rapidly increased market share of domestic agricultural products. But Imported agricultural products include various agricultural chemicals and food additives. In order to improve competitiveness in domestic markets of farmhouses and to secure food safety, the farmers needs to introduce Systematic support and various system. In this paper, established system that use Monitoring technology, to inform production information and management information about agricultural products to consumer by real time. Therefore unused analog camera such as CCTV(Closed-Circuit Television) for real time Monitoring. This system Used web camera that offer picture quality that is good than CCTV at place that consists network without distinction in the place. An advantage of real time Monitoring system designed multi-vision interface showing multi images on single screen and, for the purpose of the improvement in efficiency, the functions of saving images and of scheduling the time to save the images.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.337-344
• /
• 2004

Most of the virtual space constructed sufficiently realistic need a lot of memory space to navigate smoothly. And this kind of virtual space also requires real-time responsibility for the navigation as well as realism. In the off-line virtual system, real-time responsibility can be resolved by using large scale if secondary memory. In the web-based online virtual system, on the other hand, real-time responsibility is highly related to the latency time of network data communication. This induces the necessity of the algorithm for fast data loading. In this paper, we propose and verify the validity of the two methodology for cell leading algorithm. According to the results of computer simulation, the algorithm using hexagonal type cell promotes the real-time responsibility over 30％ than that of the rectangular type.

• Journal of Korean Society for Quality Management
• /
• v.47 no.3
• /
• pp.497-508
• /
• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.

• International Journal of Advanced Culture Technology
• /
• v.8 no.3
• /
• pp.223-230
• /
• 2020

Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.6
• /
• pp.614-620
• /
• 2006

Today the automobile has been changed from a mechanical system to an electronic control system fly the development of the electronic technology. In the automobile body, most of these electronic control devices are networked and managed fully by the CAN protocol. But, when a network system is overloaded, unexpected transmission delay for relative low priority objects occurs due to the static priority definition of the CAN protocol. To resolve this problem, this paper proposes a dynamic precedence queue mechanism that creates a queue for the low priority object and its relevant objects to be transmitted, which becomes urgent in an overloaded network system to keep the maximum allowable time delay. For the generated queue, the highest priority is assigned to transmit the queued objects within the shortest time. The mechanism is implemented in the logical link layer of CAN, which does not require any modification of the old CAN hardware. Effectiveness of the proposed mechanism is verified by the real experiments with an automobile network system.

• ETRI Journal
• /
• v.32 no.2
• /
• pp.241-247
• /
• 2010

We propose and experimentally demonstrate a service-aware optical transport system. The proposed service-aware optical transport system makes a flow based on service type and priority of traffic. The generated flow is mapped to a corresponding sub-${\lambda}$ for transport over an optical network. Using sub-${\lambda}$ provided by the centralized control plane, we could effectively provide quality-of-service guaranteed Ethernet service and best-effort service simultaneously in a single link. The committed information rate (CIR) traffic and best-effort traffic are assigned to different sub-${\lambda}s$. The bandwidth of the CIR traffic is guaranteed without being affected by violation traffic because the bandwidth is managed per each sub-${\lambda}$. The failure detection time and restoration time from a link failure is measured to be about 60 ${\mu}s$ and 22 ms, respectively, in the ring network. The measured restoration time is much smaller than the 50 ms industry requirement for real-time services. The fast restoration time allows the proposed service-aware optical transport system to offer high availability and reliability which is a requirement for transport networks.