• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.86-92
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• 2022

Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.149-171
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• 2020

The period at university is to make decision about getting an actual job. As our society develops rapidly and highly, jobs are diversified, subdivided, and specialized, and students' job preparation period is also getting longer and longer. This study analyzed the log data of college students to see how the various activities that college students experience inside and outside of school might have influences on employment. For this experiment, students' various activities were systematically classified, recorded as an activity data and were divided into six core competencies (Job reinforcement competency, Leadership & teamwork competency, Globalization competency, Organizational commitment competency, Job exploration competency, and Autonomous implementation competency). The effect of the six competency levels on the employment status (employed group, unemployed group) was analyzed. As a result of the analysis, it was confirmed that the difference in level between the employed group and the unemployed group was significant for all of the six competencies, so it was possible to infer that the activities at the school are significant for employment. Next, in order to analyze the impact of the six competencies on the qualitative performance of employment, we had ANOVA analysis after dividing the each competency level into 2 groups (low and high group), and creating 6 groups by the range of first annual salary. Students with high levels of globalization capability, job search capability, and autonomous implementation capability were also found to belong to a higher annual salary group. The theoretical contributions of this study are as follows. First, it connects the competencies that can be extracted from the school experience with the competencies in the Human Resource Management field and adds job search competencies and autonomous implementation competencies which are required for university students to have their own successful career & life. Second, we have conducted this analysis with the competency data measured form actual activity and result data collected from the interview and research. Third, it analyzed not only quantitative performance (employment rate) but also qualitative performance (annual salary level). The practical use of this study is as follows. First, it can be a guide when establishing career development plans for college students. It is necessary to prepare for a job that can express one's strengths based on an analysis of the world of work and job, rather than having a no-strategy, unbalanced, or accumulating excessive specifications competition. Second, the person in charge of experience design for college students, at an organizations such as schools, businesses, local governments, and governments, can refer to the six competencies suggested in this study to for the user-useful experiences design that may motivate more participation. By doing so, one event may bring mutual benefits for both event designers and students. Third, in the era of digital transformation, the government's policy manager who envisions the balanced development of the country can make a policy in the direction of achieving the curiosity and energy of college students together with the balanced development of the country. A lot of manpower is required to start up novel platform services that have not existed before or to digitize existing analog products, services and corporate culture. The activities of current digital-generation-college-students are not only catalysts in all industries, but also for very benefit and necessary for college students by themselves for their own successful career development.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.657-666
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• 2014

Coal gasification technology is considered as next generation clean coal technology even though it uses coal as fuel which releases huge amount of greenhouse gas because it has many advantages for carbon capture. Coal or pet-coke slurry gasification is very attractive technology at present and in the future because of its low construction cost and flexibility of slurry feeding system in spite of lower efficiency compared to dry feeding technology. In this study, we carried out gasification experiment using bituminous coal slurry sample by integrating coal slurry feeding facility and slurry burner into existing dry feeding compact gasifier. Especially, our experiment was conducted under fairly lower operation temperature than that of existing entrained-bed gasifier, resulting in partial slagging operation mode in which only part of ash was converted to slag and the rest of ash was released as fly ash. Carbon conversion rate was calculated from data analysis of collected slag and ash, and then cold gas efficiency, which is the most important indicator of gasifier performance, was estimated by carbon mass balance method. Fairly high performance considering pilot-scale experiment, 98.5% of carbon conversion and 60.4% of cold gas efficiency, was achieved. In addition, soundness of experimental result was verified from the comparison with chemical equilibrium composition and energy balance calculations.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.8
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• pp.449-455
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• 2017

Process input data including material and energy, process output data including product, co-product and its environmental emissions of the reference and target processes were collected and analyzed to evaluate the process performance. Environmentally problematic input/environmental emissions of the manufacturing processes were identified using these data. Significant process inputs contributing to each of the environmental emissions were identified using multiple regression analysis between the process inputs and environmental emissions. Optimum combination of the end-of-pipe technologies for treating the environmental emissions considering economic aspects was made using the linear programming technique. The cement manufacturing processes in Korea and the EU producing same type of cement were chosen for the case study. Environmentally problematic input/environmental emissions of the domestic cement manufacturing processes include coal, dust, and $SO_x$. Multiple regression analysis among the process inputs and environmental emissions revealed that $CO_2$ emission was influenced most by coal, followed by the input raw materials and gypsum. $SO_x$ emission was influenced by coal, and dust emission by gypsum followed by raw material. Optimization of the end-of-pipe technologies treating dust showed that a combination of 100% of the electro precipitator and 2.4% of the fiber filter gives the lowest cost. The $SO_x$ case showed that a combination of 100% of the dry addition process and 25.88% of the wet scrubber gives the lowest cost. Salient feature of this research is that it proposed a method for identifying environmentally problematic input/environmental emissions of the manufacturing processes, in particular, cement manufacturing process. Another feature is that it showed a method for selecting the optimum combination of the end-of-pipe treatment technologies.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.6
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• pp.286-304
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• 2017

In this study, we proposed a new-type of circular perforated caisson breakwater consisting of a bundle of latticed blocks that can be applied to a small port such as a fishing port, and numerically investigated the hydraulic characteristics of the breakwater. The numerical method used in this study is OLAFOAM which newly added wave generation module, porous media analysis module and reflected wave control module based on OpenFOAM that is open source CFD software published under the GPL license. To investigate the applicability of OLAFOAM, the variations of wave pressure acting on the three-dimensional slit caisson were compared to the previous experimental results under the regular wave conditions, and then the performance for irregular waves was examined from the reproducibility of the target irregular waves and frequency spectrum analysis. As a result, a series of numerical simulations for the new-type of circular perforated caisson breakwaters, which is similar to slit caisson breakwater, was carried out under the irregular wave actions. The hydraulic characteristics of the breakwater such as wave overtopping, reflection, and wave pressure distribution were carefully investigated respect to the significant wave height and period, the wave chamber width, and the interconnectivity between them. The numerical results revealed that the wave pressure acting on the new-type of circular perforated caisson breakwaters was considerably smaller than the result of the impermeable vertical wall computed by the Goda equation. Also, the reflection of the new-type caisson breakwater was similar to the variation range of the reflection coefficient of the existing slit caisson breakwater.

• Korean Chemical Engineering Research
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• v.52 no.6
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• pp.720-726
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• 2014

PEM fuel cell vehicles have been getting much attraction due to a sort of highly clean and effective transportation. The onboard fuel processor, however, is inevitably required to supply the hydrogen by conversion from some fuels since there are not enough available hydrogen stations nearby. A lot of studies have been focused on analyses of ATR reactor under the assumption of thermo-neutral condition and those of the optimized process for the minimization of energy consumption using thermal efficiency as an objective function, which doesn't guarantee the maximum hydrogen production. In this study, the analysis of optimization for 100 kW PEMFC onboard fuel processor was conducted targeting various fuels such as gasoline, LPG, diesel using newly defined hydrogen efficiency and keeping simply synthesized heat exchanger network regardless of external utilities leading to compactness and integration. Optimal result of gasoline case shows 9.43% reduction compared to previous study, which shows the newly defined objective function leads to better performance than thermal efficiency in terms of hydrogen production. The sensitivity analysis was also done for hydrogen efficiency, heat recovery of each heat exchanger, and the cost of each fuel. Finally, LPG was estimated as the most economical fuel in Korean market.

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.255-268
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• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.507-519
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• 2017

The applications of NDVI (Normalized Difference Vegetation Index) as a vegetation index has been widely used to understand vegetation biomass and physiological activities. However, NDVI is not suitable way for monitoring vegetation stress because it is less sensitive to change in physiological state than biomass. PRI (Photochemical Reflectance Index) is well developed to present physiological activities of vegetation, particularly high-light-stress condition, and it has been adopted in several satellites to be launched in the future. Thus, the understanding of PRI performance and the development of analysis method will be necessary. This study aims to interpret the characteristics of light-stress-sensitive PRI in shadow areas and to evaluate the PRI calculated by other wavelengths (i.e., 488.9 nm, 553.6 nm, 646.9 nm, and 668.4 nm) instead of 570 nm that used in original PRI. Using airborne-based hyperspectral image, we found that PRI values were increased in shadow detection due to the reduction of high light induced physiological stress. However, the qualities of both PRI and NDVI data were dramatically decreased when the shadow index (SI) exceeded the threshold (SI<25). In addition, the PRI calculated using by 553.6 nm had best correlation with original PRI. This relationship was improved by multiple regression analysis including reflectances of RED and NIR. These results will be helpful to the understanding of physiological meaning on the application of PRI.

• Korean Journal of Applied Biomechanics
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• v.12 no.2
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• pp.361-380
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• 2002

The purposes of this study were to a analysis of friction relation between tennis outsole and tennis playing surfaces. Tennis footwear is an important component of tennis game equipment. It can support or damage players performance and comfort. Most importantly athletic shoes protect the foot preventing abrasions and injuries. Footwear stability in court sports like tennis is incredibly important since it is estimated that as many as 45% of all lower extremity injuries occur in the foot and ankle. The friction force is the force exerted by a surface as an object moves across it or makes an effort to move across it. The friction force opposes the motion of the object. Friction results when two surfaces are pressed together closely, causing attractive intermolecular forces between the molecules of the two different surfaces. The outsole provides traction and reduces wear on the midsole. Today's outsoles address sport specific movements (running versus pivoting) and playing surface types. Different areas of the outsole are designed for the distinct frictional needs of specific movements. Traction created by the friction between the outsole and the surface allows the shoe to grip the surface. As surfaces, conditions and player motion change, traction may need to vary. An athletic shoe needs to grip well when running but not when pivoting. Laboratory tests have demonstrated force reductions compared to impact on concrete. There is a correlation between pain, injury and surface hardness. These are a variety of traction patterns on the soles of athletic shoes. Traction like any other shoe characteristic must be commensurate and balanced with the sport. The equal and opposite force does not necessarily travel back up your leg. The surface itself absorbs a portion of the force converting it to other forms of energy. Subsequently, tennis court surfaces are rated not only for pace but also for the percentage of force reduction.