• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.4
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• pp.371-378
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• 2015

Range extenders, which are power generation systems driven by small engines, extend the driving distance and time of electric vehicles (EVs) through continuous charging of batteries. The currently used range extenders with gasoline engines pose limitations with regard to the realization of high-power compact systems, owing to their complex structure and low energy density. In contrast, micro gas turbine (MGT) range extenders (MGT power packs) possess high power and low weight, and can therefore be significantly reduced in size despite increase in speed. In this study, an MGT power pack for the range extenders of EVs was developed using a turbo-prop micro turbine, an alternator for passenger vehicles and electric batteries. The operating characteristics of the MGT power pack were measured through a series of experiments conducted under electrical no-load and load conditions. Their power generation performance and efficiency were measured under various electrical loads and power transmission gear ratios. From the results, electrical load was found to have no influence on power generation performance. The maximum electrical power output was 0.8 kW at a core turbine speed of 150 krpm, and the application of 3:1 reduction gear to the turbine output shaft increased the power to 1.5 kW by 88%. This implies that the test results demonstrated stable power generation performance of the MGT power pack regardless of vehicle load changes, thus revealing its feasibility for use with the range extenders of EVs.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.94-102
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• 2020

Renewable energy (RE) is essential to comprise sustainable societies, especially, in rural villages of developing countries. Furthermore, application of off-grid RE systems to health care can improve the quality of life. In this research, a RE-based vaccination supply management system was constructed to enlarge the cold-chain in developing countries for the safe storage and delivery of vaccines. The system was comprised of the construction of RE plants and development of vaccine carriers. RE plants were constructed and connected to health posts in local villages. The cooling mechanism of vaccine carriers was improved and monitoring devices were installed. The effect of the system on vaccine cold-chain was evaluated from the field test and topographical analysis in the southern village of Nepal. RE plants were normally operated for the vaccine refrigerator in the health post. The modified vaccine carriers had a longer operation time and better temperature control via monitoring and RE-based recharging functionality. The topographical analysis estimated that the system can cover larger region. The system prototype showed great potential regarding the possibility of a sustainable and enlarged cold-chain. Thus, RE-based vaccine supply management is expected to facilitate vaccine availability while minimizing waste in the supply chain.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.653-666
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• 2020

Understanding the vegetation structure is important to manage forest resources for sustainable forest development. With the recent development of technology, it is possible to apply new technologies such as drones and deep learning to forests and use it to estimate the vegetation structure. In this study, the vegetation structure of Gongju, Samchuk, and Seoguipo area was identified by fusion of drone-optical images and LiDAR data using Artificial Neural Networks(ANNs) with the accuracy of 92.62% (Kappa value: 0.59), 91.57% (Kappa value: 0.53), and 86.00% (Kappa value: 0.63), respectively. The vegetation structure analysis technology using deep learning is expected to increase the performance of the model as the amount of information in the optical and LiDAR increases. In the future, if the model is developed with a high-complexity that can reflect various characteristics of vegetation and sufficient sampling, it would be a material that can be used as a reference data to Korea's policies and regulations by constructing a country-level vegetation structure map.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.503-514
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• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• KSBB Journal
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• v.21 no.3
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• pp.188-193
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• 2006

A new type of biofilter, a rotating drum biotrickling filter(RDBF), was developed and operated for the removal of styrene from industrial waste gas. The porous polyurethane foam sheet was used as a packing materials for the RDBF and a pure culture of Gram-positive bacterium Brevibacillus sp. SP1 was used as an inoculum. The reactor showed a short start-up period of 18 days, during which uniform biofilms were developed on the packing. During a steady operation at an incoming styrene concentration of $200ppm_v$ and a retention time of 0.5 min, a high and stable removal of styrene over 95% was observed. The maximum elimination capacity was estimated to be $125g/m^3{\cdot}hr$. The outstanding performance was attributed to an efficient gas-liquid mass transfer and the appropriate supply of nutrient solution to the biofilm microorganisms on the packing by the rotation of the drum.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.829-837
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• 2008

A cellular system with fixed relays is considered to be a technology that can support high data transmission service to wide areas. However, either inter-cell interference or inter-sector interference that can be produced by adding relays to the cellular system with fixed relays does not guarantee high link performance to deteriorate function, so that resource allocation for avoidance of interference is very much important. In the paper, the cellular system performance with repeater relay has been compared with the cellular system performance with relay, and cell coverage expansion at the use of relay repeater has been compared. To compare, this paper has suggested resource allocation method to avoid inter-cell interference and inter-sector interference at installation of fixed relay on the cellular system. The proposed method can allocate different frequency resources on adjacent base stations and relays to reduce interference and to expand high data transmission area, and all of frequency bands are used at each sector to elevate efficiency of the frequency when base stations and relays operate simultaneously.

• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.18-22
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• 2014

Satellite communications consist of communications between base stations of the ground and satellites. For efficient satellite communications, ground networks should be organically utilized. Grid networks are frequently used in and outside the country for wireless communications. The performance of wireless communications is determined by mobility, topography, and jamming signals. Therefore, continuous studies of grid networks are necessary for the utilization of next period satellite networks. Since military communications are used based on wireless systems, they can be considered as a sample of utilization of grid networks. Therefore, this paper presented the results of simulations conducted for the improvement of the performance of the grid networks used in military communications that employing the OSPF, a popular routing protocol for military applications. First we investigate the effects of changing the bit error rate (BER) and number of routers. Then we discuss the effects of maximum segment size (MSS) on network behavior and stability. In this way, we can determine the appropriate MSS for a grid network under various values of BER and number of routers. Such results can be also applied to commercial grid network evaluations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.106-118
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• 2019

In recent years, research and development on image object recognition using artificial intelligence have been actively carried out, and it is expected to be used for road maintenance. Among them, artificial intelligence models for object detection of road surface are continuously introduced. In order to develop such object recognition algorithms, a backbone network that extracts feature maps is essential. In this paper, we will discuss how to select the appropriate neural network. To accomplish it, we compared with 4 different deep neural networks using 6,000 road surface damage images. Based on three evaluation methods for analyzing characteristics of neural networks, we propose a method to determine optimal neural networks. In addition, we improved the performance through optimal tuning of hyper-parameters, and finally developed a light backbone network that can achieve 85.9% accuracy of road surface damage classification.

• Composites Research
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• v.33 no.6
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• pp.383-389
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• 2020

Thermoplastic composite is introduced to design an automotive door impact beam, and the manufacturing process is demonstrated. The safety regulation for vehicles has been steadily tightened, and weight-reduction has become a mandatory factor in the automotive industry. Hence, both high-performance and lightweight are demanded for automotive components. The aim of the present study is to develop an automotive door impact beam using fiber-reinforced thermoplastic composites to reduce the weight of the impact beam while increasing its mechanical performance. A new production method which combines continuous fiber-reinforced composite and LFT(Long Fiber-reinforced Thermoplastic) is implemented by using insert injection molding process. The mechanical performance of the composite impact beam was evaluated using 3-point bending tests. Thermoplastic composite will expand its application range to various automotive components due to its light-weight design capability and high productivity.