• Journal of Animal Science and Technology
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• v.62 no.6
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• pp.840-853
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• 2020

The present study was conducted to investigate the effect of a multi-protease on production indicators of broiler chickens fed a crude protein and amino acid deficient-diets for 35 days immediately after hatch. A total of 448 one-day-old Ross 308 male broiler chicks were allocated in a completely randomized design into one of eight dietary treatments (positive control [PC], negative control [NC: minus 0.5% from PC, and minus 2% of lysine, methionine, threonine and methionine plus cysteine], extreme negative control [ENC: minus 1% from PC, minus 4% of lysine, methionine, threonine and methionine plus cysteine], and plus multi-protease 150 or 300 g per ton [e. g., PC-150]; PC, PC-150, NC, NC-150, NC-300, ENC, ENC-150, ENC-300) to give eight replicates with seven birds in a battery cage. Body weight, average daily gain, average daily feed intake, feed conversion ratio, and mortality were measured every week. Carcass traits, proximate analysis of breast meat, and ileum digestibility were analyzed on day 21 and 35. Feeding a multi-protease (i.e., more than 150 g/ton) for 35 days immediately after hatching improved feed efficiency and ileum digestibility (i.e., dry matter, crude protein, and energy) compared to their counterparts (i.e., diets without multi-protease: PC, NC, and ENC). In conclusion, our results indicated that broiler chickens fed nutrients deficient-diet (i.e., crude protein and amino acids) supplemented a multi-protease had an ability to compensate and (or) improve their growth performance commensurate with increased ileal digestibility for 35 days immediately after hatch.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.301-308
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• 2018

Anthropogenic radioactive noble gases formed by nuclear fission are significant indicators used to monitor the nuclear activity of neighboring countries. In particular, radioactive xenon, owing to its abundant generation and short half-life, can be used to detect nuclear testing, and radioactive krypton has been used as a tracer to monitor the reprocessing of nuclear fuels. Released radioactive noble gases are in the atmosphere at infinitesimal amounts due to their dilution in the air and their short half-life decay. Therefore, to obtain reliable and significant data when performing measurement of noble gases in the atmosphere, the minimum detectable activity (MDA) for noble gases should be defined as low as possible. In this study, the MDA values for radioactive xenon and krypton were theoretically obtained based on the BfS-IAR system by collecting both noble gases simultaneously. In addition, various MDA methods, confidence level and analysis conditions were suggested to reduce and optimize MDA with an assessment of the factors affecting MDA. The current investigation indicated that maximizing the pretreatment efficiency and performance maintenance of the counter were the most important aspects for Xe. In the case of Kr, since sample activities are much higher than those of Xe, it is possible to change the target MDA or to simplification of the analysis system.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.2
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• pp.165-171
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• 2016

In this study, the characterization of projects and analysis of R&D products and commercialization performances were done to serve some implications on the policy decisions related to the commercialization of R&D in marine and fisheries sector. A total of 212 R&D projects with 144 ones for marine and 68 for fisheries performed for 5 years, from 2010 to 2014, were sorted and analyzed on the respect of government budget, main performing body, and research period. The R&D result and commercialization performance were substituted to quantitative indicators, such as the number of published papers, the number of patents, the amount of the technology royalty, the number of technology transfers, and the improvement of public service, which were subjects to be analysed. Based on the results, this study suggests the policy implications for the success of national R&D program; 1) diversifying the main performing body, 2) operating the system for sharing research infrastructures among researchers, 3) introducing the adaptable R&D program management, 4) expending the portion of grants without detailed requests for proposal, and 5) leaning the investigation of R&D budgets on projects focusing on the practicalization and commercialization.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• Tunnel and Underground Space
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• v.29 no.6
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• pp.379-393
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• 2019

For the economical construction of a tunnel by TBM, the selection of TBM optimized with the various project conditions is important, and also necessary to predict the performances of selected TBM in advance. This study was conducted to comprehensively evaluate the performance of the EPB shield TBM screw conveyor by the discrete element method. The sticky particles were used for the excavated material models, and screw conveyor with 11 different inclined angles were simulated to evaluate the performance depending on the different inclined angles. The four different rotational speed conditions of the screw were used, and torque, required power, extra energy for muck discharge, and the muck discharge rate were selected as four performance indicators. As a result, the optimized inclined angle was selected, and selected angle accords with the fact that EPB shield TBM screw conveyor is generally installed and adjusted at the inclined angle between 20.0° and 30.0° in the field.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.481-492
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• 2004

We report the successful fabrication and I-V curve superconductivity test results of the Nb/Al-based superconducting tunnel junctions. STJs with side-lengths of 20, 40, 60 and $80{\mu}m$ were fabricated by deposition of polycrystalline Nb/Al/AlOx/Al/Nb 5-layer thin films incorporated on a 3-inch Si wafer. STJ was designed by $Tanner^{TM}$ L-Edit 8.3 program, and fabricated in SQUID fabrication facility, KRISS. S-layer STJ thin-films were fabricated using UV photolithography, DC magnetron sputtering, Reactive ion etching, and CVD(Chemical Vapor Deposition) techniques. Superconducting state test for STJ was succeeded in 4K with liquid helium cooling system. Their performance indicators such ie energy gap, normal resistance, normal resistivity, dynamic resistance, dynamic resistivity, and quality factor were measured from I-V curve. Fabricated Nb/Al STJ shows $11\%$ higher FWHM energy resolution than genuine Nb STJ.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.137-144
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• 2015

Development of the yarn sorting equipment (khonhook) by slide way due to the principle of engineering that cause of workers on the long of motion time. The data was collected from the weaving group Ban Nongkok village, Nakornratchasima Province, THAILAND. According to the study, the step of yarn sorting (konhook) was one of the steps that affect long of motion time. The problem was the inadequate capacity equipment. The objective of research was to study and develop the yarn sorting equipment (konhook). The fabric used in the study was 64 meters in length and 1 meter in width. Researchers studied the processes the yarn sorting (konhook) which it consists of seven sub steps, 1) the thread tube setting, 2) yarn bunching, 3) tying a knot at the end of yarn, 4) looping the yarn into a pillar, 5) sorting the yarn (konhook), 6) crossing pillars and 7) taking out the yarn. Researchers focused on studying yarn sorting process (konhook) by designing and creating a device for yarn sorting (konhook) for reducing yarn sorting (konhook) time by the original method performance indicators. The results found that the developed yarn sorting equipment (konhook) ) by slide way could reduce working time from 7.24 minutes to 6.08 minutes of the original equipment yarn sorting (konhook). This means it could make the process 16.02 % faster. This also helps reducing the distance of workers' movement from 2,234 meters to 8 meters. This is 99.64 % shorter.

• Journal of Radiation Protection and Research
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• v.48 no.3
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• pp.144-152
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• 2023

Background: Color texture analysis was applied as a tool for quantitative evaluation of radiation-induced skin injuries. Materials and Methods: We prospectively selected 20 breast cancer patients who underwent whole-breast radiotherapy after breast-conserving surgery. Color images of skin surfaces for irradiated breasts were obtained by using a mobile skin analyzer. The first skin measurement was performed before the first fraction of radiotherapy, and the subsequent measurement was conducted approximately 10 days after the completion of the entire series of radiotherapy sessions. For comparison, color images of the skin surface for the unirradiated breasts were measured similarly. For each color image, six co-occurrence matrices (red-green [RG], red-blue [RB], and green-blue [GB] from color channels, red [R], green [G], blue [B] from gray channels) can be generated. Four textural features (contrast, correlation, energy, and homogeneity) were calculated for each co-occurrence matrix. Finally, several statistical analyses were used to investigate the performance of the color textural parameters to objectively evaluate the radiation-induced skin damage. Results and Discussion: For the R channel from the gray channel, the differences in the values between the irradiated and unirradiated skin were larger than those of the G and B channels. In addition, for the RG and RB channels, where R was considered in the color channel, the differences were larger than those in the GB channel. When comparing the relative values between gray and color channels, the 'contrast' values for the RG and RB channels were approximately two times greater than those for the R channel for irradiated skin. In contrast, there were no noticeable differences for unirradiated skin. Conclusion: The utilization of color texture analysis has shown promising results in evaluating the severity of skin damage caused by radiation. All textural parameters of the RG and RB co-occurrence matrices could be potential indicators of the extent of skin damage caused by radiation.

• World Technopolis Review
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• v.8 no.2
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• pp.74-81
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• 2019

Cities will soon host two third of the population worldwide, and already today 80% of the world energy is used in the 20 largest cities. Urban areas create 80% of the greenhouse gas emission, so we should take care that urban areas are smart and sustainable as implementations have especially here the greatest impact. Smart Cities (SC) or Smart Sustainable Cities (SSC) are the actual concepts that describe methodologies how cities can handle the high density of citizens, efficiency of energy use, better quality of life indicators, high attractiveness for foreign investments, high attractiveness for people from abroad and many other critical improvements in a shifting environment. But if we talk about Entrepreneurship Ecosystem and Innovation, we do not see a lot of literature covering this topic within those SC/SSC concepts. It seems that 'Smart' implies that all is embedded, or isn't it properly covered as brick stone of SC/SSC concepts, as they are handled in another 'responsibility silo', meaning that the policy implementation of a Science and Technology Park (STP) is handled in another governing body than SC/SSC developments. If this is true, we will obviously miss a lot of synergy effects and economies of scale effects. Effects that we could have in case we stop the siloed approaches of STPs by following a more holistic concept of a Smart Sustainable City, covering also a continuous flow of innovation into the city, without necessarily always depend on large corporate SSC solutions. We try to argue that every SSC should integrate SP/STP concepts or better their features and services into their methodology. The very limited interconnectivity between these concepts within the governance models limits opportunities and performance in both systems. Redesigning the architecture of the governance models and accepting that we have to design a system-of-systems would support the possible technology flow for smart city technologies, it could support testbed functionalities and the public-private partnership approach with embedded business models. The challenge is of course in complex governance and integration, as we often face siloed approaches. But real SSC are smart as they are connecting all those unconnected siloes of stakeholders and technologies that are not yet interoperable. We should not necessarily follow anymore old greenfield approaches neither in SSCs nor in SP and STP concepts from the '80s that don't fit anymore, being replaced by holistic sustainability concepts that we have to implement in any new or revised SSC concepts. There are new demands for each SP/STP being in or close to an SC/SCC as they have a continuous demand for feeding the technology base and the application layer and should also act as testbeds. In our understanding, a big part of STP inputs and outputs are still needed, but in a revised and extended format. We know that most of the SC/STP studies claim the impact is still far from understood and often debated, therefore we must transform the concepts where SC/STPs are not own 'cities', but where they act as technology source and testbed for industry and new SSC business models, being part of the SC/STP concept and governance from the beginning.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.723-734
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• 2021

Wind energy is one of the rapidly developing renewable energies which is being developed and invested in response to climate change. As renewable energy policies and power plant installations are promoted, the supply of wind power in Korea is gradually expanding and attempts to accurately predict demand are expanding. In this paper, the ARIMA and ARIMAX models which are Time series techniques and the SVR, Random Forest and XGBoost models which are machine learning models were compared and analyzed to predict wind power generation in the Jeonnam and Gyeongbuk regions. Mean absolute error (MAE) and mean absolute percentage error (MAPE) were used as indicators to compare the predicted results of the model. After subtracting the hourly raw data from January 1, 2018 to October 24, 2020, the model was trained to predict wind power generation for 168 hours from October 25, 2020 to October 31, 2020. As a result of comparing the predictive power of the models, the Random Forest and XGBoost models showed the best performance in the order of Jeonnam and Gyeongbuk. In future research, we will try not only machine learning models but also forecasting wind power generation based on data mining techniques that have been actively researched recently.