• Nuclear Medicine and Molecular Imaging
• /
• v.43 no.5
• /
• pp.443-450
• /
• 2009

Purpose: Conventional image reconstruction uses simplified physical models of projection. However, real physics, for example 3D reconstruction, takes too long time to process all the data in clinic and is unable in a common reconstruction machine because of the large memory for complex physical models. We suggest the realistic distributed memory model of fast-reconstruction using parallel processing on personal computers to enable large-scale technologies. Materials and Methods: The preliminary tests for the possibility on virtual manchines and various performance test on commercial super computer, Tachyon were performed. Expectation maximization algorithm with common 2D projection and realistic 3D line of response were tested. Since the process time was getting slower (max 6 times) after a certain iteration, optimization for compiler was performed to maximize the efficiency of parallelization. Results: Parallel processing of a program on multiple computers was available on Linux with MPICH and NFS. We verified that differences between parallel processed image and single processed image at the same iterations were under the significant digits of floating point number, about 6 bit. Double processors showed good efficiency (1.96 times) of parallel computing. Delay phenomenon was solved by vectorization method using SSE. Conclusion: Through the study, realistic parallel computing system in clinic was established to be able to reconstruct by plenty of memory using the realistic physical models which was impossible to simplify.

• KIPS Transactions on Computer and Communication Systems
• /
• v.10 no.7
• /
• pp.191-198
• /
• 2021

Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.

• Journal of the Korean Institute of Gas
• /
• v.24 no.6
• /
• pp.18-27
• /
• 2020

This study presents flow assurance analysis in subsea pipeline considering system availability of topside in LNG-FPSO. A hydrate management strategy was established, which consisted of PVCap experiments, system availability analysis of LNG-FPSO topside, hydrate risk analysis in the pipeline, and calculation of PVCap injection concentration. The experimental data required for the determination of PVCap injection concentration were obtained by measuring the hydrate induction time of PVCap at the subcooling temperatures of 6.1, 9.2, and 12.1℃. The availability of LNG-FPSO topside system for 20 years was 89.3%, and the longest downtime of 50 hours occurred 2.9 times per year. The subsea pipeline model for multiphase flow simulation was created using field geometry data. As a result of risk analysis of hydrate plugging using subsea pipeline model, hydrate was formed at the end of flowline in 23.2 hours under the condition of 50 hours shutdown. The injection concentration of PVCap was determined based on the PVCap experiment results. The hydrate plugging in subsea pipeline of LNG-FPSO can be completely prevented by injecting PVCap 0.25 wt% 2.9 times per year.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.4
• /
• pp.171-181
• /
• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• The Journal of Korean society of community based occupational therapy
• /
• v.6 no.1
• /
• pp.41-48
• /
• 2016

Objective : We tried to know the improvement and neurological effect of diabetes when the complex exercise training was applied on diabetes that delayed the recovery of the ischemic brain injury. Methods : We performed this study in a animal lab which located in Gyengsangbukdo. We used 10 diabetes rats with ischemic brain injury, which is induced by STZ. We applied the complex exercise training on the rats for 4 weeks. We executed the maze test to confirm the recovery of the brain function and checked the blood sugar to know the improvement. Results : As a result of applying the complex exercise on diabetes rats with ischemic brain injury, there was a significant reduce of error and escape time in 3 weeks and 1 weeks, respectively. There was no difference of the blood sugar in control but there was a significant improvement in experiment group after applying the exercise training in 4 weeks. Conclusion : The senile disease like stroke and diabetes was increased currently. It is important for rehabilitation to improve the quality of life during the remainder of their life. In the study, we've known the improvement of diabetes and the recovery of the brain function when the complex exercise training was applied the rats with both diabetes and the ischemic brain injury.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.8
• /
• pp.2484-2496
• /
• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.40 no.8
• /
• pp.619-630
• /
• 2003

We present a method of runtime configuration scheduling in reconfigurable SoC design. As a model of computation, we use a popular formal model of computation, hierarchical FSM (HFSM) with synchronous dataflow (SDF) model, in short, HFSM-SDF model. In reconfigurable SoC design with HFSM-SDF model, the problem of configuration scheduling becomes challenging due to the dynamic behavior of the system such as concurrent execution of state transitions (by AND relation), complex control flow (HFSM), and complex schedules of SDF actor firing. This makes it hard to hide configuration latency efficiently with compile-time static configuration scheduling. To resolve the problem, it is necessary to know the exact order of required configurations during runtime and to perform runtime configuration scheduling. To obtain the exact order of configurations, we exploit the inherent property of HFSM-SDF that the execution order of SDF actors can be determined before executing the state transition of top FSM. After obtaining the order information and storing it in the ready configuration queue (ready CQ), we execute the state transition. During the execution, whenever there is FPGA resource available, a new configuration is selected from the ready CQ and fetched by the runtime configuration scheduler. We applied the method to an MPEG4 decoder and IS95 design and obtained up to 21.8% improvement in system runtime with a negligible overhead of memory usage.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.1
• /
• pp.61-69
• /
• 2020

This study examined the braking characteristics of a heavy haul freight train with P4a distribution valves applied to domestic high-speed freight trains. A freight train was composed of 50 cars, which is twice the normal operation. A braking test was performed to confirm the characteristics of the braking of a heavy haul. The brake cylinder pressures were measured for emergency and service braking on the 1st, 10th, 20th, 30th, and 50th cars. Because the brake signal is transmitted to the pressure through the braking tube connected to the end of the train, the rear vehicle is braking later than the vehicle ahead. Therefore, it is necessary to predict the brake pressures in all cars in a train to supplement the results of the limited tests and calculate the braking distance. The pressure in each car was determined using empirical models of linear interpolation, stepwise, and exponential models, which provided reliable information. The predictive results of the empirical models were compared with the measured results, and the exponential model was predicted relatively accurately. These results are expected to contribute to the safe operation of heavy haul freight trains and can be used to predict the braking distance and calculate the level of impact between vehicles during braking.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.21 no.2
• /
• pp.227-242
• /
• 2019

This paper presents a method to predict ground types ahead of a tunnel face utilizing operational data of the earth pressure-balanced (EPB) shield tunnel boring machine (TBM) when running through soil ground. The time series analysis model which was applicable to predict the mixed ground composed of soils and rocks was modified to be applicable to soil tunnels. Using the modified model, the feasibility on the choice of the soil conditioning materials dependent upon soil types was studied. To do this, a self-organizing map (SOM) clustering was performed. Firstly, it was confirmed that the ground types should be classified based on the percentage of 35% passing through the #200 sieve. Then, the possibility of predicting the ground types by employing the modified model, in which the TBM operational data were analyzed, was studied. The efficacy of the modified model is demonstrated by its 98% accuracy in predicting ground types ten rings ahead of the tunnel face. Especially, the average prediction accuracy was approximately 93% in areas where ground type variations occur.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.4
• /
• pp.9-21
• /
• 2008

In this paper, we propose a GNSS-based RF receiver, A high precision localization architecture, and a high sensitivity localization architecture in order to solve the satellite navigation system's problem mentioned above. The GNSS-based RF receiver model should have the structure to simultaneously receive both the conventional GPS and navigation information data of future-usable Galileo. As a result, it is constructed as the multi-band which can receive at the same time Ll band (1575.42MHz) of GPS and El band (1575.42MHz), E5A band (1207.1MHz), and E4B band (1176.45MHz) of Galileo This high precision localization architecture proposes a delay lock loop with the structure of Early_early code, Early_late code, Prompt code, Late_early code, and Late_late code other than Early code, Prompt code, and Late code which a previous delay lock loop structure has. As we suggest the delay lock loop structure of 1/4chips spacing, we successfully deal with the synchronization problem with the C/A code derived from inaccuracy of the signal received from the satellite navigation system. The synchronization problem with the C/A code causes an acquisition delay time problem of the vehicle navigation system and leads to performance reduction of the receiver. In addition, as this high sensitivity localization architecture is designed as an asymmetry structure using 20 correlators, maximizes reception amplification factor, and minimizes noise, it improves a reception rate. Satellite navigation system repeatedly transmits the same C/A code 20 times. Consequently, we propose a structure which can use all of the same C/A code. Since this has an adaptive structure and can limit(offer) the number of the correlator according to the nearby environment, it can reduce unnecessary delay time of the system. With the use of this structure, we can lower the acquisition delay time and guarantee the continuity of tracking.