• Korean System Dynamics Review
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• v.14 no.4
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• pp.113-141
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• 2013

The main purpose of this research is to introduce PsyCap(Positive Psychological Capital) and new leadership helping ordinary people to create positive thinking and leading to social integration in South Korea. Additionally, by looking at conventional leadership theories and by applying the PsyCap to leadership based on causal loop analysis, this study is to seek new approach which political leader is able to communicate with the people and can help the people to build positive mine. Throughout this study, there are several important implications how political leader can lead to social integration and stable political development in South Korea. In particular, when political leader encourage the people to have confidence to take on and put in the necessary effort to succeed at challenging tasks, when political leader make the people a positive attribution (optimism) about succeeding now and in the future, when political leader help the people to persevere toward goals and redirection paths to goals (hope) in order to succeed, and when political leader make the people beset by problems and adversity environment to overcome these concerns, it can be expected political leader to build social integration and the people to create positive thinking which has been emphasized by political leader in South Korea. Finally, 21st century has required new political leadership that the people are able to make positive psychological capital composed by optimism, hope, confidence, and resilience.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.1
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• pp.1-6
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• 2015

The purpose of this study is to suggest the effective operation method by developing prediction model for the gas production rate, an indicator of the effectiveness of anaerobic digestion tank, using data mining. At the result, gas production estimate model is developed by using ANN within 10% error. It is expected to help operation of anaerobic digestion by suggesting selected parameter. Meanwhile case based reasoning is applied to develop dewatering cake management technology. Case based reasoning uses the most similar examples of past when a new problem occurs, therefore in this study, management measures are developed that proposes dewatering cake minimization with the minimum change by applying the case based reasoning to sludge disposal process.

• KSBB Journal
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• v.11 no.6
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• pp.696-703
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• 1996

The bacterium Serratia marcescens QM Bl466 produces selectively large amount of chitinolytic enzymes(about 1mg/L medium). Enzymatic hydrolysis of chitin to N-acelyl-${\beta}$-D-glucosamine(NAG) is performed by a system consisting of two hydrolases : chitinase and chilobiase. Objectives of this study included optimization of a microbial host by using chitin particles for chitinase/chitobiase production and secretion and also development of batch fermentation system for high cell density cultivalion of S. marcescens QM B1466. Also, the influence of chitin source and carboxymethyl(CM) chitin on chitinase/chitobiase production and NAG production was investigated. When carboxymethyl chitin was substituted for colloidal and practical grade chitin, the chitinase activity was increased about 7∼10U/mL. In this case, the ratio of chitinase/chitobiase was 30.03U/3.44U(9:1). The highest amounts of NAG(3.0g/L) was obtained.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.219-228
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• 2019

Thanks to the development of information technology and the vitalization of smart services, the Internet of Things (IoT) technology, in which various smart devices are connected to the network, has been continuously developed. In the legacy IoT architecture, data processing has been centralized based on cloud computing, but there are concerns about a single point of failure, end-to-end transmission delay, and security. To solve these problems, it is necessary to apply decentralized blockchain technology to the IoT. However, it is hard for the IoT devices with limited computing power to mine blocks, which consumes a great amount of computing resources. To overcome this difficulty, this paper proposes an IoT architecture based on the edge computing technology that can apply blockchain technology to IoT devices, which lack computing resources. This paper also presents an operaional procedure of blockchain in the edge computing-based IoT architecture.

• Journal of the Korean Magnetics Society
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• v.27 no.2
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• pp.63-69
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• 2017

Naval ships are particularly required to maintain acoustic and magnetic silence due to their operational characteristics. Among them, underwater magnetic field signals derived by ships are likely to be detected by threats such as surveillance systems and mine systems at close distance. In order to increase the survivability of the vessels, various techniques for reducing the magnetic field signal are being studied and it is necessary to consider not only the magnitude of the magnetic field signal but also the gradient of it. In this paper, we use the commercial electromagnetic finite element analysis tool to predict the induced magnetic field signal of ship's scaled model, and arrange the degaussing coil. And the optimum degaussing current of the coil was derived by applying the particle swarm optimization algorithm considering the gradient constraint. The validity of the optimal degaussing technique is verified analytically by comparing the magnetic field signals after the degaussing with or without gradient constraint.

• Mineral and Industry
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• v.25
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• pp.1-10
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• 2012

In this present work, the froth flotation of lithium ore from Boam mine located in Wooljin, Kyungbuk has been carried out to produce high-grade lithium concentrate. The sample ore-Lepidolite mainly contained silicate mineral (quartz, muscovite) and calcite. In consequences of the experiment, it has been possible to obtain relatively high-grade lithium while using anionic acid (oleic acid) to remove calcite before the froth flotation for lithium concentrate. Among the amines collectors (Armac-T, Armac-C, Armafloat-18, Armafloat-1597), Armac-T has been relatively effective than another ones. Under the optimum condition (collector : Armac-T 100g/t, frother : AF65 50g/t, depressants : $Na_2SiO_3$ 600g/t and Lactic acid 100g/t, pulp density : 20%, pH 5.5, number of cleaning : 2), it has been obtained relatively high-grade lithium concentrate ($Li_2O$) with recovery of 80.3% and with grade of 4.33%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.50-56
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• 2020

With the rapid development of deep neural network theory and application research, the effect of face detection has been improved. However, due to the complexity of deep neural network calculation and the high complexity of the detection environment, how to detect face quickly and accurately becomes the main problem. This paper is based on the relatively simple model of the MTCNN model, using FDDB (Face Detection Dataset and Benchmark Homepage), LFW (Field Label Face) and FaceScrub public datasets as training samples. At the same time of sorting out and introducing MTCNN(Multi-Task Cascaded Convolutional Neural Network) model, it explores how to improve training speed and Increase performance at the same time. In this paper, the dynamic image pyramid technology is used to replace the traditional image pyramid technology to segment samples, and OHEM (the online hard example mine) function in MTCNN model is deleted in training, so as to improve the training speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.25-36
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• 2010

Tertiary unconsolidated mudstones spread throughout the eastern coast area. The demand for high quality filling materials in these areas is increasing due to harbors and large-scale residential land development. Rock produced in-situ or near site has been used as road subbase construction or reclamation materials for economical reason, but it is hard to decide appropriateness of quality specification because of its characteristics. The test results showed that unconsolidated rocks are diversely considered according to a different method of the applied geotechnical investigation. Therefore, the site of tertiary unconsolidated mudstones, the classification of rock and evaluation of rock properties that must be evaluated by objective criteria and apply a different set of criteria are needed. In addition, the environmental impact must be considered due to acid mine drainage.