• Industry Promotion Research
• /
• v.4 no.1
• /
• pp.67-78
• /
• 2019

This study is to study Jung's analytical psychology and to study counseling process and counseling techniques based on the counseling theory derived from it. Jung divides the counseling process into four stages based on analytical psychology. The first stage is confession, and the prototype of analysis therapy is confession. The first step in the treatment process is to share secrets and reveal suppressed emotions. The second stage is elucidation, a process that clarifies by shedding light on the contents induced by the transfer. The third stage is the level of education. Explanation makes my counselors intelligent, but leaves them still in an incompetent state. At this stage, treatment goes beyond insight to train as a responsible client. The fourth stage is transformation. In the transformation phase with inner counselors, not only the debaters, but also the therapist is in the "in-analysis." Jung's counseling technique uses six things: dream analysis, use of symbols, word link test, symptom analysis, case history and MBTI. In conclusion, analytical psychology counseling has enabled, first, a more in-depth approach and understanding of the human mind, especially the unconscious world. Second, analytical psychology counseling has enabled us to recognize that all humans are human communities with a common mental structure through the concept of unconsciousness and archetypes. Third, analytical psychology counseling has allowed you to look at the meaning and purpose of life from a new perspective. Therefore, Jung emphasized that he should not be seen as having a pathological problem with patients, but as an omnipotent human being who wants to realize its fullness on his own.

• Journal of the Microelectronics and Packaging Society
• /
• v.27 no.4
• /
• pp.55-60
• /
• 2020

The PERC photovoltaic (PV) modules installed in PV power plant are still reports potential-induced degradation (PID) degradation due to high voltage potential differences. This is because Na+ ions in the cover glass of PV modules go through the encapsulant (EVA) and transferred to the surface of solar cells. As positive charges are accumulated at the ARC (SiOx/SiNx) interface where many defects are distributed, shunt-resistance (Rsh) is reduced. As a result, the leakage current is increased, and decrease in solar cell's power output. In this study, to prevent of this phenomenon, a Moth-eye nanostructure was deposited on the rear surface of an optical film using Nano-Imprint Lithography method, and a solar mini-module was constructed by inserting it between the cover glass and the EVA. To analyze the PID phenomenon, a cell-level PID acceleration test based on IEC 62804-1 standard was conducted. Also analyzed power output (Pmax), efficiency, and shunt resistance through Light I-V and Dark I-V. As a result, conventional solar cells were decreased by 6.3% from the initial efficiency of 19.76%, but the improved solar cells with the Moth-eye nanostructured optical film only decreased 0.6%, thereby preventing the PID phenomenon. As of Moth-eye nanostructured optical film, the transmittance was improved by 4%, and the solar module output was improved by 2.5%.

• Journal of Biomedical Engineering Research
• /
• v.42 no.3
• /
• pp.71-79
• /
• 2021

Currently, the naked eyes-based diagnosis of bone metastases on CT images relies on qualitative assessment. For this reason, there is a great need for a state-of-the-art approach that can assess and follow-up the bone metastases with quantitative biomarker. Radiomics can be used as a biomarker for objective lesion assessment by extracting quantitative numerical values from digital medical images. In this study, therefore, we evaluated the clinical applicability of non-invasive and objective bone metastases computer-aided diagnosis using radiomics-based biomarkers in CT. We employed a total of 21 approaches consist of three-classifiers and seven-feature selection methods to predict bone metastases and select biomarkers. We extracted three-dimensional features from the CT that three groups consisted of osteoblastic, osteolytic, and normal-healthy vertebral bodies. For evaluation, we compared the prediction results of the classifiers with the medical staff's diagnosis results. As a result of the three-class-classification performance evaluation, we demonstrated that the combination of the random forest classifier and the sequential backward selection feature selection approach reached AUC of 0.74 on average. Moreover, we confirmed that 90-percentile, kurtosis, and energy were the features that contributed high in the classification of bone metastases in this approach. We expect that selected quantitative features will be helpful as biomarkers in improving the patient's survival and quality of life.

• Journal of Broadcast Engineering
• /
• v.27 no.2
• /
• pp.228-239
• /
• 2022

In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

• Journal of Korea Water Resources Association
• /
• v.54 no.11
• /
• pp.955-968
• /
• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Journal of Industrial Convergence
• /
• v.20 no.5
• /
• pp.29-38
• /
• 2022

Because of the need of actual performance of education, this study aims to understand how the factors of educational content and organizational characteristics affect organizational commitment and work performance, which are organizational effects, through learning transfer. As a result, task value, job relevance, and organizational compensation had a significant effect on learning transfer, learning transfer had a significant effect on organizational commitment and work performance, and organizational commitment had a significant effect on work performance. In order to increase the learning transfer of education, when specifying the connection with the actual job and strengthening the compensation system of the members, the learning transfer can be increased and eventually connected to performance. Since limited variables are considered, a more representative sample or professional group should be extracted through future research. In future studies, it will be possible to closely grasp the relationship between learning transfer and organizational effectiveness by setting representative samples and specifying variables.

• Clean Technology
• /
• v.28 no.2
• /
• pp.174-181
• /
• 2022

Biomass is a sustainable alternative resource for production of liquid fuels and organic compounds that are currently produced from fossil fuels including petroleum, natural gas, and coal. Because the use of fossil fuels can increase the production of greenhouse gases, the use of carbon-neutral biomass can contribute to the reduction of global warming. Although biological and chemical processes have been proposed to produce petroleum-replacing chemicals and fuels from biomass feedstocks, it is difficult to replace completely fossil fuels because of the high oxygen content of biomass. Production of petroleum-like fuels and chemicals from biomass requires the removal of oxygen atoms or conversion of the oxygen functionalities present in biomass derivatives, which can be achieved by catalytic hydrodeoxygenation. Hydrodeoxygenation has been used to convert raw biomass-derived materials, such as biomass pyrolysis oils and lignocellulose-derived chemicals and lipids, into deoxygenated fuels and chemicals. Multifunctional catalysts composed of noble metals and transition metals supported on high surface area metal oxides and carbons, usually selected as supports of heterogeneous catalysts, have been used as efficient hydrodeoxygenation catalysts. In this review, the catalysts proposed in the literature are surveyed and hydrodeoxygenation reaction systems using these catalysts are discussed. Based on the hydrodeoxygenation methods reported in the literature, an insight for feasible hydrodeoxygenation process development is also presented.

• Clean Technology
• /
• v.29 no.3
• /
• pp.163-171
• /
• 2023

Hydrogen has been gaining a lot of attention as a possible clean energy source that can aid in reaching carbon neutrality. Currently, hydrogen production has relied on the steam reforming of fossil fuels. However, due to the carbon dioxide emissions caused by this process, hydrogen production based on the steam reforming of bio-oil derived from biomass has been proposed as an alternative approach. In order to use this alternative approach efficiently, one of the key issues that must be overcome is that the complexity of bio-oil, which has a large molecular weight and diverse functional groups of hydrocarbons, promotes the catalytic deactivation of nickel-based catalysts. In this review, research efforts to improve nickel-based catalysts for the steam reforming of bio-oil have been discussed in terms of the active phase, support, and promoters. The active phases are involved in activating C-C and C-H bonds of high-molecular-weight hydrocarbons, and noble and transition metals can be utilized. In terms of the support and promoters, the catalytic deactivation of Ni-based catalysts can be inhibited by utilizing reactive lattice oxygen for support or by suppressing the acidity. The development of active and stable Ni-based reforming catalysts plays a critical role in clean hydrogen production based on bio-oils.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.7
• /
• pp.361-370
• /
• 2016

Effective acquisition technology is an important factor determining the competitiveness of companies(Roxas et al., 2011). Since the importance of technology transfer has been increased, there has been a growing interest in company, government, university and research institutes (Bozeman et al., 2015). Despite the national efforts for activating technology transfer, a lot of technology is still in universities and R&D center(Ockwell et al., 2009). The barriers of technology transfer are a main reason to inhibit the technology transfer. In order to be lower technology transfer barriers, it is necessary to derive the technology transfer broker based on social network analysis. However, most studies related to technology transfer broker had been focused on empirical study(Bozeman et al., 2015). Therefore, it is needed to suggest the method to grasp the opportunity that can lead to technology innovation based on analyzing and visualizing the network of technology transfer. The method in this study provides the company with the connectable path, technology transfer broker and strategy to classify the technology actor within the network. Finally, the method is applied to Global MVP for verifying the feasibility of method.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.5D
• /
• pp.635-644
• /
• 2009

Image processing technique in the outdoor environment is very sensitive, and it tends to lose a lot of accuracy when it rapidly changes by outdoor environment. Therefore, in order to calculate accurate traffic information using the traffic monitoring system, we must resolve removing shadow in transition time, Distortion by the vehicle headlights at night, noise of rain, snow, and fog, and occlusion. In the research, we developed a system to calibrate the amount of traffic, speed, and time occupancy by using image processing technique in a variety of outdoor environments change. This system were tested under outdoor environments at the Gonjiam test site, which is managed by Korea Institute of Construction Technology (www.kict.re.kr) for testing performance. We evaluated the performance of traffic information, volume counts, speed, and occupancy time, with 4 lanes (2 lanes are upstream and the rests are downstream) from the 16th to 18th December, 2008. The evaluation method performed as based on the standard data is a radar detection compared to calculated data using image processing technique. The System evaluation results showed that the amount of traffic, speed, and time occupancy in period (day, night, sunrise, sunset) are approximately 92-97% accuracy when these data compared to the standard data.