• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.131-138
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• 2023

This paper is related to performance improvement of Image-to-Image translation using Relativistic Average Patch GAN and Residual in Residual Dense Block. The purpose of this paper is to improve performance through technical improvements in three aspects to compensate for the shortcomings of the previous pix2pix, a type of Image-to-Image translation. First, unlike the previous pix2pix constructor, it enables deeper learning by using Residual in Residual Block in the part of encoding the input image. Second, since we use a loss function based on Relativistic Average Patch GAN to predict how real the original image is compared to the generated image, both of these images affect adversarial generative learning. Finally, the generator is pre-trained to prevent the discriminator from being learned prematurely. According to the proposed method, it was possible to generate images superior to the previous pix2pix by more than 13% on average at the aspect of FID.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.368-374
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• 2024

During an X-ray examination, the beam of radiation is dispersed in many directions. We believe that managing radiation dose is about providing transparency to users and patients in the accurate investigation and analysis of radiation dose. The purpose of measuring the radiation dose as a function of location is to ensure that medical personnel using the equipment or participating in the operating room are minimally harmed by the different radiation doses depending on their location. Four mobile diagnostic X-ray units were used to analyze the radiation dose depending on the spatial location. The image intensifier and the flat panel detector type that receives the image analyzed the dose by angle to measure the distribution of the exposure dose by location. The radiation equipment used was composed of four units, and measuring devices were installed according to the location. The X-ray (C-arm) was measured by varying the position from 0 to 360 degrees, and the highest dose was measured at the center position based on the abdominal position, and the highest dose was measured at the 90° position for the head position when using the image intensifier equipment. The operator or medical staff can see that the radiation dose varies depending on the position of the diagnostic radiation generator. In the image intensifier and flat panel detector type that accepts images, the dose by angle was analyzed for the distribution of exposed dose by position, and the measurement method should be changed according to the provision of dose information that is different from the dose output from the equipment according to the position.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.19-26
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• 2024

The phase-type, PH, distribution is defined as the time to absorption into a terminal state in a continuous-time Markov chain. As the PH distribution includes family of exponential distributions, it has been widely used in stochastic models. Since the PH distribution is represented and generated by an initial probability vector and a generator matrix which is called the Markovian representation, we need to find a vector and a matrix that are consistent with given set of moments if we want simulate a PH distribution. In this paper, we propose an approach to simulate a PH distribution based on distribution function which can be obtained directly from moments. For the simulation of PH distribution of order 2, closed-form formula and streamlined procedures are given based on the Jordan decomposition and the minimal Laplace transform which is computationally more efficient than the moment matching methods for the Markovian representation. Our approach can be used more effectively than the Markovian representation in generating higher order PH distribution in queueing network simulation.

• Journal of Biosystems Engineering
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• v.7 no.2
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• pp.18-29
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• 1983

A low cost and versatile data acquisition system for the field and laboratory use was developed by using a single board microcomputer. Data acquisition system based on a Z80 microprocessor was built, tested and modified to obtain the present functional system. The microcomputer developed consists of 6 kB ROM, 5 kB RAM, 6-seven segment LED display, 16-Hex. key and 8 command key board. And it interfaces with an 8 channel, 12 bits A/D converter, a microprinter, EPROM programmer for 2716, and RS232C interface to transfer data between the system and HP3000 mini-computer manufactured by Hewlett Packard Co., A software package was also developed, tested, and modified for the system. This package included drivers for the AID converter, LED display, key board, microprinter, EPROM programmer, and RS232c interface. All of these programs were written in 280 assembler language and converted to machine codes using a cross assembler by HP3000 computer to the system during modifying stage by data transferring unit of this system, then the machine language wrote to the EPROM by this EPROM programmer. The results are summarized as follows: 1. Measuring program developed was able to control the measuring intervals, No. of channels used, and No. of data, where the maximum measuring speed was 58.8 microsec. 2. Calibration of the system was performed with triangle wave generated by a function generator. The results of calibration agreed well to the test results. 3. The measured data was able to be written into EPROM, then the EPROM data was compared with original data. It took only 75 sec. for the developed program to write the data of 2 kB the EPROM. 4. For the slow speed measurements, microprinter instead of EPROM programmer proved to be useful. It took about 15 min. for microprinter to write the data of 2 kB. 5. Modified data transferring unit was very effective in communicating between the system and HP3000 computer. The required time for data transferring was only 1~2 min. 6. By using DC/DC converting devices such as 78-series, 79-series. and TL497 IC, this system was modified to convert the only one input power sources to the various powers. The available power sources of the system was DC 7~25 V and 1.8 A.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.45-49
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• 2019

Purpose Lung Ventilation Scan(LVS) images directly inhaled radiation gas to evaluate lung ventilation ability. Therefore, it is influenced by various factors related to inhalation, including number of breaths, respiratory duration, respiration rate, and breathing method. In actual LVS examinations, it is difficult for objectify the patient's ability to inhale, and there is currently no known index related to inhalation. Therefore, this study confirms the correlation between counts per second(cps) in LVS and the results of pulmonary function test(PFT) and evaluate its usefulness as an objective indicator of inhalation. Materials and Methods From October 2010 to September 2018, 36 Chronic Obstructive Pulmonary Disease(COPD) patients who had both LVS and PFT were classified by severity(Mild, Moderate, Severe). LVS was performed by creating Technegas with Vita Medical's Technegas Generator and inhaling it to the patient. LVS images were acquired with Philips's Forte equipment., and PFT used Carefusion's Vmax Encore 22. The correlation between the cps measured by setting the region of interest(ROI) of both lungs on the LVS and the forced vital capacity(FVC), forced expiratory volume in one second($FEV_1$), $FEV_1/FVC$ of the results of PFT was compared and analyzed. Results We analyzed the correlation between cps of LVS using Technegas and the results of PFT by classifying COPD patients according to severity. Correlation coefficient between $FEV_1/FVC$ and cps was Severe -0.773, Moderate -0.750, and Mild -0.437. The Severe and Modulate result values were statistically significant(P<0.05) and Mild was not significant(P=0.155). On the other hand, the correlation coefficient between FVC and cps was statistically significant only in Mild and it was 0.882(P<0.05). Conclusion According to the study, we were able to analyze correlation between cps of LVS using Technegas and the results of PFT in COPD Patients. Using this result, when performing a LVS, the results of PFT can be used as an index of inhaling capacity. In addition, it is thought that it will be more effective for the operation of the exam rooms.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.243-250
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• 2014

In this paper, I devise a balance-swap optimization (BSO) algorithm to solve economic load dispatch with a quadratic fuel cost function. This algorithm firstly sets initial values to $P_i{\leftarrow}P_i^{max}$, (${\Sigma}P_i^{max}$ > $P_d$) and subsequently entails two major processes: a balance process whereby a generator's power i of $_{max}\{F(P_i)-F(P_i-{\alpha})\}$, ${\alpha}=_{min}(P_i-P_i^{min})$ is balanced by $P_i{\leftarrow}P_i-{\alpha}$ until ${\Sigma}P_i=P_d$; and a swap process whereby $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_i+{{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}$ = 1.0, 0.1, 0.1, 0.01, 0.001 is set at $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$. When applied to 15, 20, and 38-generators benchmark data, this simple algorithm has proven to consistently yield the best possible results. Moreover, this algorithm has dramatically reduced the costs for a centralized operation of 73-generators - a sum of the three benchmark cases - which could otherwise have been impossible for independent operations.

• Progress in Medical Physics
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• v.18 no.3
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• pp.144-148
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• 2007

Current digital radiography systems are rapidly glowing in clinical applications. The purpose of this study was to evaluate the characteristics of a mobile digital radiographic system. The performance of the mobile DR system was evaluated by measuring the modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). Measurements were made on a LISTEM Mobix-1000 generator and a Teleoptic PRA Alpha-R4000 detector. Imaging characteristics were measured for these two systems using the IEC-61267 defined RQA5 (kVp: 74, additional filtration: 21 mmAl) radiographic condition. The MTF at 10% was measured as 2.4 cycles/mm and the DQE(0) values for radiation exposure 0.19, 0.5, and 1.3 mR were measured as 54%, 55%, and 76%, respectively. The NPS curves gradually decreased at high spatial frequencies. This high DQE at low frequencies, may be useful for low frequency information. The results suggested that mobile DR system could be integrated with emergency ambulance system in teleradiologic imaging applications.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.409-414
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• 2007

The effect of multipath is especially serious in urban area and sea surface where buildings and water reflect GPS signal. Multipath brings about the performance degradation on many GPS application because the presence of multipath causes the diminution of pseudorange measurement accuracy in turn position accuracy. In this paper, a multipath mitigation named weighted correlation method is implemented on software GPS receiver, in which the asymmetric correlation function is compensated by modifying the late correlation value. Asymmetry compensation is obtained as weighted sum of two correlators which have different early-late chip spaces. This structure is adopted to lessen the computation load lower keeping up performance similar to that. The performance of implemented multipath mitigation technique is evaluated using GPS signal and multipath signal generated by GPS signal generator and software GPS receiver. The test results show that the weighted correlation method gives hefter performance than the standard correlator and the narrow correlator.