• Smart Structures and Systems
• /
• v.26 no.4
• /
• pp.495-506
• /
• 2020

Monitoring of complex processes faces several challenges mainly due to the lack of relevant sensory information or insufficient elaborated decision-making strategies. These challenges motivate researchers to adopt complex data processing and analysis in order to improve the process representation. This paper presents the development and implementation of quality monitoring framework based on a model-driven approach using embedded artificial intelligence strategies. In this work, the strategies are applied to the supervision of a microfabrication process aiming at showing the great performance of the framework in a very complex system in the manufacturing sector. The procedure involves two methods for modelling a representative quality variable, such as surface roughness. Firstly, the hybrid incremental modelling strategy is applied. Secondly, a generalized fuzzy clustering c-means method is developed. Finally, a comparative study of the behavior of the two models for predicting a quality indicator, represented by surface roughness of manufactured components, is presented for specific manufacturing process. The manufactured part used in this study is a critical structural aerospace component. In addition, the validation and testing are performed at laboratory and industrial levels, demonstrating proper real-time operation for non-linear processes with relatively fast dynamics. The results of this study are very promising in terms of computational efficiency and transfer of knowledge to manufacturing industry.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.3989-4006
• /
• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.19 no.4
• /
• pp.94-101
• /
• 2015

Each of power systems of solar cell and fuel cell were configured and validated for long endurance UAV, as the preliminary research for the integration of power systems. Solar power system consisted of solar modules fabricated by solar cells of Sunpower's C60, commercial solar MPPT controller and Li-po battery, and then was validated. The re-start characteristics of hydrogen production from $NaBH_4$ hydrolysis was validated for operating the commercial fuel cell. The average voltage drop of Li-po battery in solar power system was -2.9 V/hour. The performance of re-start characteristics of $NaBH_4$ hydrolysis was stable in sequence mode of mission profile. Each of single systems were satisfied for the proposed mission profile.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.29 no.2
• /
• pp.137-152
• /
• 2009

Present experiment was conducted at the field of Gyeongnam Agricultural Research and Extension Services in Jinju city for two continuous cropping seasons to develop several adaptable and valuable year-round forage-producing system for elevating self-sufficiency and dollar-saving by reduced importing of crude forage. Twenty cropping systems were tested in experiment using whole crop barley (WCB), oat, rye, Italian ryegrass (IRG), and triticale in winter season and com, sorghum, sorghum ${\times}$ sudangrass hybrid, and oat in summer time. Sorghum ${\times}$ sudangrass hybrid showed highest fresh forage yield among experimented summer season crops, and followed com. Com produced the most dry matter yield, and followed sorghum${\times}$sudangrass hybrid, sorghum and oat in order. There was no significant effect of former winter crops on fresh and dry matter production succeeding summer time crops. Among winter season forage crops tested, oat showed the highest fresh and dry matter when clipped on mid-May, and followed triticale, IRG, rye and WCB. Winter-time cultivated crops showed no clear effect on the growth and forage (fresh and dry matter) producing ability of following summer crops. There was the most protein content in oat plant among summer season planted crops, and in sorghum for acid detergent fiber (ADF) and in sorghum ${\times}$ sudangrass hybrid for neutral detergent fiber (NDF), respectively. While, com showed highest value of relative feed value (RFV) and total digestive nutrients (TDN) among those crops. Among winter crops, the highest crude protein was in oat plant showing no significant differences of ADF and NDF, while, relatively higher value of RFV was recognized with rye and triticale. Also, triticale contained more TDN as compare to other forage crops. The cropping combinations such as com followed by (fb) rye and maize fb triticale were regarded as promising systems having higher dry matter producing ability among tested combinations. Considering TDN producing potential, the combinations with sorghum ${\times}$ sudangrass hybrid fb triticale andlor rye were would be suitable ones, coincidently. There was a tendency which elevating pH, electric conductivity (EC) and organic matter (OM) contents in soil after experiment comparing to before planting. More crude protein content in plant was shown at mid-May clipping as compared to the forage at April cut in all winter season grown crops. ADF and NDF contents were increased by delayed clipping showing decreased tendency of RFV and TDN in plant. In conclusion, many cropping systems would be available using above mentioned forage crops according to farmer's conditions and scale, etc.

• Journal of the Korea Computer Graphics Society
• /
• v.22 no.4
• /
• pp.21-30
• /
• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.4_1
• /
• pp.493-504
• /
• 2022

Recently, as interest in eco-friendliness grows, the supply of hybrid electric vehicles and pure electric vehicles (EVs) for improving fuel efficiency of automobiles is rapidly expanding. The average daily energy consumption of electric vehicles is less than 20 [%] of the total ESS capacity of the vehicle, and research on additional functions using the ESS of the vehicle is urgently needed to expand the supply of electric vehicles. V2H(Vehicle to Home), like V2G(Vehicle to Grid), includes the concept of cooperating with system stabilization using ESS of electric vehicles. In addition, it includes various operations that can realize home welfare, such as uninterrupted power supply in case of power outage at home, and power supply for home DC devices. Therefore, in order to expand the supply of eco-friendly electric vehicles, it is urgently required to develop a V2H system with various functions that can realize home welfare. In this paper, we propose a V2H system with a CLLC resonant converter and a non-isolated step-up converter that can solve different impedance and resonant frequencies depending on the power transfer direction. The proposed V2H system is 6 [kVA] applicable to 150-450 [V], the voltage range that can use the ESS voltage for electric vehicles, and is designed with a capacity that can handle instantaneous electricity use at home. In addition, in order to verify the feasibility, an experiment by Psim simulation and prototype production was performed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.334-334
• /
• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Journal of Life Science
• /
• v.29 no.7
• /
• pp.755-761
• /
• 2019

Kojic acid (KA) is produced by Aspergillus oryzae-sort of like mushrooms, which is commonly called as koji in Japan. KA is used as a chelation agent and a preservative preventing oxidative browning of fruits. KA also shows antibacterial and antifungal properties. Because KA stops the production of melanin by inhibiting tyrosinase in the biosynthetic pathway from tyrosine to melanin in skin, it has been applied as a skin lightening ingredient in cosmetics. Since some animal studies have shown that high amounts of KA had side effects such as in liver, kidney, reproductive, cardiovascular, gastrointestinal, respiratory, brain, and nervous system, more efficient KA derivatives are needed to be developed in order to safely apply as a skin lightening ingredient. A series of KA derivatives via conjugated with triazole by click reaction were synthesized and their in vitro tyrosinase inhibitory activities were evaluated. Most of all KA derivatives have shown in moderate tyrosinase inhibitory activities. In case of KA-hybrid compound, 1~3 have shown tyrosinase inhibitory activities about 50~10,000 times more effective tyrosinase inhibitor compared to KA itself. Specifically, the $IC_{50}$ value of KA-hybrid compound, 2 was $0.0044{\pm}0.74{\mu}M$ against tyrosinase. It is about 10,000 times more effective tyrosinase inhibitor compared to KA itself ($IC_{50}=45.2{\pm}4.6{\mu}M$).

• Korean Journal of Organic Agriculture
• /
• v.19 no.3
• /
• pp.373-384
• /
• 2011

This experiment was conducted to investigate the selection of regional double cropping system for production of organic forage in middle part of Korea and investigated their productivity, feed values and stock carrying capacity. The test results proved the Sorghum${\times}$Sudangrass hybrid was 10.9 $ton{\cdot}ha^{-1}$, the one of Rye + Red clover and Rye + Hairy vetch were the highest one as 3.3 $ton{\cdot}ha^{-1}$ and the relative yield about a Rye is higher in the dry matter yield in the field soil. And as for the relative forage values (RFV), Corn is the most excellent ones as 96.6 but there were no the significant difference between the Sorghum${\times}$Sudangrass hybrid of 84.4 and it. The total digestible nutrient (TDN) content in Rye + Hairy vetch is higher than others as 59.7%. As for the relative feed value, Rye + Red clover is the highest one as 83.8 but there was no significant differences between them. As for the ability to raise livestock in the field soil, the average values of $K_{CP}$ and $K_{TDN}$ are shown as 4.27 head/ha/yr in Sorghum${\times}$Sudangrass hybrid. As for the same crops, the average values of $K_{CP}$ and $K_{TDN}$ showed the highest ones as 1.74 head/ha/yr, in Rye + Red clover but there were no the significant differences. As for the dry matter yield of the rice field soil, organic rice straw was 3.3 $ton{\cdot}ha^{-1}$ and Rye + Red clover significantly showed the highest values as 4.1 $ton{\cdot}ha^{-1}$. In the rice filed soil, the crude protein content of organic rice straw was 3.1% and the TDN content of organic rice straw was 55%. The TDN content in Rye + Red clover was higher than others as 59.7%. As for the relative forage values, Rye + Red clover showed the highest one as 83.8 but there were no significant differences between them. As for the ability to raise livestock in the rice field, the average values of $K_{CP}$ and $K_{TDN}$ in the organic rice straw was 1.04 head/ha/yr and the average values of $K_{CP}$ and $K_{TDN}$ in Rye + Red clover is the highest one as 1.84 head/ha/yr, but there were no significant differences in all of them.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.32 no.3
• /
• pp.309-316
• /
• 2012

This study was performed to investigate the effects of forage cropping system and cattle slurry on productivity of whole crop rice, whole crop barley and Sorghum-Sudangrass hybrid and environmental pollution in paddy land. Forage cropping system used in this study was consisted of double-cropping whole crop barley followed by whole crop rice applied with cattle slurry (DWBRC) and double-cropping whole crop barley followed by Sorghum-Sudangrass hybrid applied with cattle slurry (DSSBC). The field experiments were conducted on the clay loam at Backsanmyun, Kimje, Chunlabukdo province in Korea for three years (May 2006 to Apr. 2009). This study was arranged in completely randomized design with three replicates. The field had been sown with whole crop rice 'Nampyung', Sorghum-Sudangrass hybrid 'Sordan79' and whole crop barley 'Younyang'. The yields of whole crop barley in DWBRC and DSSBC were 7,515 kg/ha and 8,515 kg/ha, respectively. The yields of whole crop barley in DSSBC significantly increased as compared with that of DWBRC (p<0.05). The contents of crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), total digestible nutrient (TDN) of whole crop barley in DWBRC were not difference as compared with those of DSSBC. The pH, and contents of total nitrogen and organic matter in soil samples collected at the end of the experiment increased as compared with those at the beginning of the experiment (p<0.05). However, The content of phosphate in DWBRC was no difference as compared with DSSBC. In addition, after the end of experiment, the concentrations of exchangeable cations (Ca, Na, Mg and K) in soil samples collected at the end of the experiment were remarkably higher than those at the beginning of the experiment (p<0.05). The concentrations of $NH_4$-N, $NO_3$-N, $PO_4$-P, Cl, Ca, K, Mg and Na in leaching water were hardly influenced by the cropping system and application of cattle slurry.