• Journal of the Korean Electrochemical Society
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• v.26 no.1
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• pp.1-10
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• 2023

The cathode, which is one of the four major components of a lithium secondary battery, is an important component responsible for the energy density of the battery. The mixing process of active material, conductive material, and polymer binder is very essential in the commonly used wet manufacturing process of the cathode. However, in the case of mixing conditions of the cathode, since there is no systematic method, in most cases, differences in performance occur depending on the manufacturer. Therefore, LiMn₂O₄ (LMO) cathodes were prepared using a commonly used THINKY mixer and homogenizer to optimize the mixing method in the cathode slurry preparation step, and their characteristics were compared. Each mixing condition was performed at 2000 RPM and 7 min, and to determine only the difference in the mixing method during the manufacture of the cathode other experiment conditions (mixing time, material input order, etc.) were kept constant. Among the manufactured THINKY mixer LMO (TLMO) and homogenizer LMO (HLMO), HLMO has more uniform particle dispersion than TLMO, and thus shows higher adhesive strength. Also, the result of the electrochemical evaluation reveals that HLMO cathode showed improved performance with a more stable life cycle compared to TLMO. The initial discharge capacity retention rate of HLMO at 69 cycles was 88%, which is about 4.4 times higher than that of TLMO, and in the case of rate capability, HLMO exhibited a better capacity retention even at high C-rates of 10, 15, and 20 C and the capacity recovery at 1 C was higher than that of TLMO. It's postulated that the use of a homogenizer improves the characteristics of the slurry containing the active material, the conductive material, and the polymer binder creating an electrically conductive network formed by uniformly dispersing the conductive material suppressing its strong electrostatic properties thus avoiding aggregation. As a result, surface contact between the active material and the conductive material increases, electrons move more smoothly, changes in lattice volume during charging and discharging are more reversible and contact resistance between the active material and the conductive material is suppressed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.117-129
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• 2023

Organizations must seek change in order to adapt to environmental changes and achieve better performance. However, despite this obvious statement, empirical analysis has been almost non-existent due to the difficulty of manipulating organizational performance or change. In this study, we overcame these limitations and analyzed the causes and effects of organizational change by assuming a professional sports team as a venture company, which is relatively easy to objectively measure and evaluate organizational change or performance. We systematically collected and preprocessed traditional and advanced metrics of National Basketball Association (NBA) statistics along with preprocessed trade data from eight years of regular seasons (2014~2015-2021~2022) to analyze our research model. Assessment of process macro model 7 derives the following empirical result. The results of the empirical analysis depict that NBA teams with low organizational performance in the previous season are more likely to make organizational changes through player trades to improve performance. Into the bargain player trades mediate the static relationship between the winning percentage in the previous season and the winning percentage in the current season. However, the indirect effect of a team's previous season's performance on player trades appears to vary depending on the current situations and context of each NBA team. Teams that made the playoffs in the previous season tend to make fewer trades than teams that did not and the previous season's performance is highly correlated with the current season's performance. On the other hand, teams that did not make the playoffs in the previous season tend to make a relatively larger amount of player trades in total, and the mediating effect of trades vanishes in this case. In other words, teams that did not make the playoffs in the previous season experience a larger change in performance due to trades than teams that made the playoffs, even if they achieved the same winning percentage. This empirical analysis of the inverse relationship between organizational change and the performance of professional sports teams has both theoretical and practical implications in the field of sports industry and management by analyzing the fundamentals of organizational change and the performance of professional sports teams.

• Journal of Technology Innovation
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• v.31 no.3
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• pp.39-73
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• 2023

The field of Management of Technology(MOT) emerged in response to the need for research management within U.S. public research institutions during the 1960s. Since its inception, it has proliferated significantly, being practiced in more than 809 institutions globally and over 19 institutions in Korea, encompassing both research and educational endeavors. Particularly noteworthy is the substantial investment of government resources, primarily channeled through the Ministry of Industry since 2007, which has expeditiously established a comprehensive framework for cultivating graduate-level MOT expertise, marked by both quantitative and qualitative advancements. The educational curriculum in the realm of Korean MOT deviates from foreign counterparts through distinctive pathways, exemplified by its emphasis on industry practice-oriented educational programs, standardization and isomorphism across different schools, as well as its interconnectedness with proximate academic disciplines. This research systematically undertakes an analysis of the curriculum in Korean MOT graduate schools, thereby ascertaining its intrinsic identity and distinct attributes. In this endeavor, a comprehensive examination of eleven principal MOT textbooks(three in Korean and eight in English) is conducted to delineate the primary content of the curriculum across seven thematic domains. Moreover, the study deliberates on its differentiation from neighboring academic disciplines and the definitional attributes of MOT. Subsequently, this analysis also encompasses nine Korean MOT graduate programs, projecting the seven thematic domains onto their respective curricula. The findings illuminate that within the context of Korean graduate programs, a substantial proportion of the curriculum, amounting to 62.5%, is dedicated to facets encompassing the operational aspects of technology management within corporate contexts, technology management specific to varying industries and technologies, and collaborative endeavors between academia and industry in the form of projects and seminars. Evidently, the Korean approach to technology management education is notably geared towards the cultivation of adept practitioners capable of executing technology management functions at a mid-tier managerial level, aligned with the exigencies of regional industries. Grounded in the analysis of technology management curricula, this study extrapolates implications for the future trajectory of MOT education in Korea, encompassing a consideration of the stages of industrial development. It underscores the necessity to augment the educational curricula pertaining conceptual foundation of technology and innovation, strategic perspectives of technology and innovation, and the socio-economic context of technology management.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.605-622
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• 2007

Elemental, Rock-Eval pyrolysis and isotopic analysis of the core sediments from the northwestern and eastern Ulleung Basin of the East were carried out to identify their geochemical characteristics, spatial and vertical variation and origin of organic matter in Upper Quaternary sediments from the northwestern and eastern Ulleung Basin of the East Sea. TOC, m and TS did not show spatial variation between the sampling locations whereas they showed systematic vertical variation associated with MIS stages related to the sea-level change of the East Sea. It is suggested that these past changes of sea-level influenced the sedimentary depositional environments and/or diagenesis which resulted the patterns observed in this study. Based on the results of TOC/N, TS/TOC, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ analysis, organic matters in the study area appears to be predominantly originated from the marine algae rather than land plant and deposited under normal marine oxic condition during MIS I and MIS III period, and under euxinic/anoxic condition during MIS II period. TOC/N, ${\delta}^{13}C_{org}\;and\;{\delta}^{15}N_{org}$ have a relatively constant value irrespective of MIS stages, implying that the organic matter source does not change by the sea-level fluctuations. However, the results of Rock-Eval pyrolysis indicates that the organic matter is in immature stage and originated from land-plant (Type III), locating in the immature stage land plant (Type III). Similar differences were reported from other areas such as the Atlantic Ocean, Iberia Abyssal Plain, Mediterranean Sea, suggesting that Rock-Eval method does not exactly reflect the characteristic of immature organic matters. Accordingly, the application of Rock-Eval pyrolysis for delineating the source of immature organic matters should be approached with caution and all other geochemical proxies should be considered altogether at the same time.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.

• Radiation Oncology Journal
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• v.18 no.2
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• pp.157-166
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• 2000

Purpose : This investigation was peformed in order to improve the health care of radiation workers, to predict a risk, to minimize the radiation exposure hazard to them and for them to realize radiation exposure danger when they work in radiation area in hospital. Methods and Materials : The documentations checked regularly for personal radiation exposure in four university hospitals in Pusan city in Korea between January 1, 1993 and December 31, 1997 were analyzed. There were 458 persons in this documented but 111 persons who worked less then one year were excluded and only 347 persons were included in this study. Results : The average of yearly radiation exposure of 347 persons was 1.52$\pm$1.35 mSv. Though it was less than 50mSv, the limitaion of radiation in law but 125 (36%) people received higher radiation exposure than non-radiation workers. Radiation workers under 30 year old have received radiation exposure of mean 1.87$\pm$1.01 mSv/year, mean 1.22$\pm$0.69 mSv between 31 and 40 year old and mean 0.97$\pm$0.43 mSv/year over 41year old (p<0.001). Men received mean 1.67$\pm$1.54 mSv/year were higher than women who received mean 1.13$\pm$0.61 mSv/year (p<0.01). Radiation exposure in the department of nuclear modicine department in spite of low energy sources is higher than other departments that use radiations in hospital (p<0.05). And the workers who received mean 3.59$\pm$1.81 msv/year in parts of management of radiation sources and injection of sources to patient receive high radiation exposure in nuclear medicine department (p<0.01). In department of diagnostic radiology high radiation exposure is in barium enema rooms where workers received mean 3.74$\pm$1.74 mSv/year and other parts where they all use fluoroscopy such as angiography room of mean 1.17$\pm$0.35 mSv/year and upper gastrointestinal room of mean 1.74$\pm$1.34 mSv/year represented higher radiation exposure than average radiation exposure in diagnostic radiology (p<0.01). Doctors and radiation technologists received higher radiation exposure of each mean 1.75$\pm$1.17 mSv/year and mean 1.50$\pm$1.39 mSv/year than other people who work in radiation area in hospital (p<0.05). Especially young doctors and technologists have the high opportunity to receive higher radiation exposure. Conclusions : The training and education of radiation workers for radiation exposure risks are important and it is necessary to rotate worker in short period in high risk area. The hospital management has to concern health of radiation workers more and to put an effort to reduce radiation exposure as low as possible in radiation areas in hospital.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.272-279
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• 2012

In order to effectively treat livestock wastewater in constructed wetlands by natural purification method, removal velocities of pollutants under different injection methods in constructed wetlands were investigated. The removal velocities of chemical oxygen demand (COD), suspended solid (SS), T-N and T-P by continuous injection method were slightly rapid than those by intermittent injection method in full-scale livestock wastewater treatment plant. The removal velocity (K; $day^{-1}$) of COD by continuous injection method was $0.38\;d^{-1}$ for $1^{st}$ bed, $0.13\;d^{-1}$ for $2^{nd}$ bed, $0.17\;d^{-1}$ for $3^{rd}$ bed, $0.05\;d^{-1}$ for $4^{th}$ bed and $0.17\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of COD in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.210\;d^{-1}$, $0.086\;d^{-1}$, $0.222\;d^{-1}$, $0.053\;d^{-1}$ and $0.137\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of SS by continuous injection method was $0.750\;d^{-1}$ for $1^{st}$ bed, $0.108\;d^{-1}$ for $2^{nd}$ bed, $0.120\;d^{-1}$ for $3^{rd}$ bed, $0.086\;d^{-1}$ for $4^{th}$ bed and $0.292\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of SS in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.485\;d^{-1}$, $0.056\;d^{-1}$, $0.174\;d^{-1}$, $0.081\;d^{-1}$ and $0.227\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of T-N by continuous injection method was $0.361\;d^{-1}$ for $1^{st}$ bed, $0.121\;d^{-1}$ for $2^{nd}$ bed, $109\;d^{-1}$ for $3^{rd}$ bed, $0.047\;d^{-1}$ for $4^{th}$ bed and $0.155\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of T-N in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.235\;d^{-1}$, $0.071\;d^{-1}$, $0.171\;d^{-1}$, $0.058\;d^{-1}$ and $0.126\;d^{-1}$, respectively. The removal velocity (K; $day^{-1}$) of T-P by continuous injection method was $0.803\;d^{-1}$ for $1^{st}$ bed, $0.084\;d^{-1}$ for $2^{nd}$ bed, $0.076\;d^{-1}$ for $3^{rd}$ bed, $0.118\;d^{-1}$ for $4^{th}$ bed and $0.301\;d^{-1}$ for $5^{th}$ bed. The removal velocities (K; $day^{-1}$) of T-P in $1^{st}$, $2^{nd}$, $3^{rd}$, $4^{th}$ and $5^{th}$ beds by intermittent injection method were $0.572\;d^{-1}$, $0.049\;d^{-1}$, $0.090\;d^{-1}$, $0.112\;d^{-1}$ and $0.222\;d^{-1}$, respectively.