• Progress in Medical Physics
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• v.21 no.1
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• pp.93-98
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• 2010

The aim of this work was to establish the methodology for event positioning by measuring depth of interaction (DOI) information and to evaluate the system sensitivity and spatial resolution of the new detector for I-125 and Tc-99m imaging. For this purpose, a Monte Carlo simulation tool, DETECT2000 and GATE were used to model the energy deposition and light distribution in the detector and to validate this approach. Our proposed detector module consists of a monolithic CsI(Tl) crystal with dimensions of $50.0{\times}50.0{\times}3.0\;mm^3$. The results of simulation demonstrated that the resolution is less than 1.5 mm for both I-125 and Tc-99m. The main advantage of the proposed detector module is that by using 3 mm thick CsI(Tl) with maximum-likelihood position-estimation (MLPE) method, high resolution I-125 imaging and high sensitivity Tc-99m imaging are possible. In this paper, we proved that our new detector to be a reliable design as a detector for a multi-energy SPECT.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.139-146
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• 2002

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless these algorithms can learn the optimal policy if the agent can visit every state-action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem, we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL) as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state space effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. In this paper we use the AMMQL algorithn as a learning method for dynamic positioning of the robot soccer agent, and implement a robot soccer agent system called Cogitoniks.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.683-689
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• 2017

We have carried out the development for hydraulic breaker which can be operated by optimal mode with ICT convergence technology. This developed system can predict the rock properties. Moreover, this system can maximize the energy efficient with intelligent control of hydraulic system. In order to provide the optimal impact force, this system can measure the descending depth of piston with the proximity sensor and discriminate the rock properties with the measuring data and control the piston stroke using solenoid valve eventually. In addition, we have developed the controller, display module and operating device for cascade (multi-level impact) system and applied the module which can communicate each system by wireless communications. In conclusion, the control system which can control the multi-level impact in accordance with strength of rocks has been developed and approved by several field tests.

• Korean Journal of Applied Biomechanics
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• v.19 no.1
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• pp.179-186
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• 2009

This works studied to compare gas analyzer with accelerometer and the estimation of energy expenditure based on different attaching position of tri-axial accelerometer such as waist and top of the foot Based on the fact that oxygen intake increases more radically linearly during walking more than 8.0km/hr. 9 male subjects performed walking and running on the treadmill with speed of $1.5{\sim}8.5km$/hr and $4.5{\sim}13.0km$/hr, respectively. Commercially available Nike + iPod Sports kit was used to compare energy expenditure with sensor module attached to their foot. Actual energy expenditure was determined by a continuous direct gas analyzer and two multiple regression equations of walking and running mode for different attaching position were developed. Results showed that estimation accuracy of energy expenditure using waist mounted accelerometer was higher than that of the top of the foot and Nike + iPod Sports kit. Results of energy expenditure based on waist and top of the foot showed that the crossover state of energy expenditure occurred at 7.5km/hr. But Nike + iPod Sports kit could not find intersection of energy expenditure in all nine subjects. Therefore the sensor module attached to the waist and separate multi regression equation by walking and running mode was the best to estimate more accurate prediction.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.3
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• pp.237-242
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• 2016

The major advantage of slip-ring technology in Spiral CT is that it facilitates continuous rotation of the x-ray tube, so that volume data can be acquired from a patient quickly. Not only for such a fast scan, but also for the dose reduction purpose, high signal-to-noise ratio and fast data acquisition system is required. In this study, we have built a multi-channel photodetector and multi-channel data acquisition system for CT application. The detector module consisted of CdWO4 crystal and Si photodiode in 16 channels. For the performance test of the preamplifier stage, both the transimpedance and switched integrator types are optimized for the photodetector modules. Switched integrator showed better noise performance in the limited bandwidth which is suitable for the current CT application. The control sequence for data acquisition and 20 bit ADC is designed with VHDL(Very High Speed Integrated Circuit Hardware Description Language) and implemented on FPGA(Field Programmable Gate Array) chip. Our Si photodiode detector module coupled to CdWO4 crystal showed comparable signal with other commercially available photodiode for CT. Switched integrator type showed higher SNR but narrower bandwidth compared to transimpedance preamplifier. Digital hardware is designed by FPGA, so that the control signal could be redesigned without hardware alteration.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.640-645
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• 2021

The deep learning based end-to-end TTS system consists of Text2Mel module that generates spectrogram from text, and vocoder module that synthesizes speech signals from spectrogram. Recently, by applying deep learning technology to the TTS system the intelligibility and naturalness of the synthesized speech is as improved as human vocalization. However, it has the disadvantage that the inference speed for synthesizing speech is very slow compared to the conventional method. The inference speed can be improved by applying the non-autoregressive method which can generate speech samples in parallel independent of previously generated samples. In this paper, we introduce FastSpeech, FastSpeech 2, and FastPitch as Text2Mel technology, and Parallel WaveGAN, Multi-band MelGAN, and WaveGlow as vocoder technology applying non-autoregressive method. And we implement them to verify whether it can be processed in real time. Experimental results show that by the obtained RTF all the presented methods are sufficiently capable of real-time processing. And it can be seen that the size of the learned model is about tens to hundreds of megabytes except WaveGlow, and it can be applied to the embedded environment where the memory is limited.

• Composites Research
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• v.34 no.4
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• pp.241-248
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• 2021

As the electric vehicle market grows, there is an issue of light weight vehicles to increase battery efficiency. Therefore, it is going to replace the battery module cover that protects the battery module of electric vehicles with high strength/high heat-resistant polymer composite material which has lighter weight from existing aluminum materials. It also aims to respond to the early electric vehicle market where technology changes quickly by combining 3D printing technology that is advantageous for small production of multiple varieties without restrictions on complex shapes. Based on the composite material mechanics, the critical length of glass fibers in short glass fiber (GF)/polycarbonate (PC) composite materials manufactured through extruder was derived as 453.87 ㎛, and the side feeding method was adopted to improve the residual fiber length from 365.87 ㎛ and to increase a dispersibility. Thus, the optimal properties of tensile strength 135 MPa and Young's modulus 7.8 MPa were implemented as GF/PC composite materials containing 30 wt% of GF. In addition, the filament extrusion conditions (temperature, extrusion speed) were optimized to meet the commercial filament specification of 1.75 mm thickness and 0.05 mm standard deviation. Through manufactured filaments, 3D printing process conditions (temperature, printing speed) were optimized by multi-optimization that minimize porosity, maximize tensile strength, and printing speed to increase the productivity. Through this procedure, tensile strength and elastic modulus were improved 11%, 56% respectively. Also, by post-processing, tensile strength and Young's modulus were improved 5%, 18% respectively. Lastly, using the FEA (finite element analysis) technique, the structure of the battery module cover was optimized to meet the mechanical shock test criteria of the electric vehicle battery module cover (ISO-12405), and it is satisfied the battery cover mechanical shock test while achieving 37% lighter weight compared to aluminum battery module cover. Based on this research, it is expected that 3D printing technology of polymer composite materials can be used in various fields in the future.

• Journal of Energy Engineering
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• v.21 no.1
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• pp.26-32
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• 2012

This study has been performed Thermal Shock test for analyze the cause of Power drop in PV(Photovoltaic) Module. Thermal Shock test condition was performed with temperature range from $-40^{\circ}C{\sim}85^{\circ}C$. One cycle time is 30min. which are consist of low and high temperature 15min. each other. The test was performed with total 500cycles. EL, I-V were conducted every 100cycle up to 500cycles. Mono Cell resulted in 8% Power drop rates in Bare Cell and 9% in Solar Cell. In the case of Multi Cell resulted in 6% Power drop rates in Bare Cell and 13% in Solar Cell. After Thermal Shock test, Solar Cell's Power drop resulted from surface damages, but in the case of Bare Cell's Power drop had no surface damages. Therefore, Bare Cell's Power drop was confirmed as according to leakage current increase by analysis of Fill Factor after Thermal Shock test. Also, Solar Cell's Power drop rates are higher than that of Bare Cell because of surface damages and consuming electric power increase. From now on, it should be considered that analyzed the reasons of Fill Factor decrease and irregular Power drop in PV module and Cell level using cross section, various conditions and test methods.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.41-53
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• 2015

In meteorological field, many researchers have tried to develop micro scale weather analysis modules for providing real-time weather information service in the metropolitan area. This effort enables us to cope with various economic and social harms coming from serious change in the micro meteorology of a metropolitan area due to rapid urbanization such as quantitative expansions in its urban activity, growth of population, and building concentration. The accuracy of the micro scale weather analysis modules (MSWAM) directly related to usefulness and quality of the real-time weather information service in the metropolitan area. This paper design a evaluation system along with verification tools that sufficiently accommodate spatio-temporal characteristics of the outputs of the MSWAM. For this we proposes a test for the equality of mean vectors of the output series of the MSWAM and corresponding observed time series by using a spectral analysis technique. As a byproduct, a time series cluster analysis method, using a function of the test statistic as the distance measure, is developed. A real data application is given to demonstrate the utility of the method.

• Journal of radiological science and technology
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• v.33 no.1
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• pp.51-59
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• 2010

We developed an analysis software that automatically detects incoming isotopes for multi-purpose gamma-ray detectors. The software is divided into three major parts; Network Interface Module (NIM), Spectrum Analysis Module (SAM), and Graphic User Interface Module (GUIM). The main part is SAM that extracts peak information of energy spectrum from the collected data through network and identifies the isotopes by comparing the peaks with pre-calibrated libraries. The proposed peak detection algorithm was utilized to construct libraries of standard isotopes with two peaks and to identify the unknown isotope with the constructed libraries. We tested the software by using GammaPro1410 detector developed by NuCare Medical Systems. The results showed that NIM performed 200K counts per seconds and the most isotopes tested were correctly recognized within 1% error range when only a single unknown isotope was used for detection test. The software is expected to be used for radiation monitoring in various applications such as hospitals, power plants, and research facilities etc.