• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• The Korean Society of Law and Medicine
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• v.22 no.4
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• pp.3-35
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• 2021

Inmitten der Flut der privaten und öffentlichen Information gilt die riesige Informationsmenge als Schlüsselressource im Zeitalter der 4. industriellen Revolution, repräsentiert durch Big-Data. Das Interesse an diesen wächst weltweit. Es gibt eine aktive Diskussion darüber, wie man Daten sichert und akkumuliert und wie man die gesammelten Daten sicher und effektiv nutzt. Gesundheitsdaten werden vor allem als die wertvollste Ressource bewertet, für die Big-DataTechnologie eingesetzt wird. Um Gesundheitsdaten sinnvoll zu nutzen, müssen verteilte Gesundheitsdaten integriert und den Benutzern in einer Form zur Verfügung gestellt werden, die für Forschung oder Inspektion verwendet werden kann. In einer Situation, in der große Länder um den Aufbau bzw. die Führung der Datenwirtschaft konkurrieren, wurden im August 2020 auch in Südkorea die sog. „3-Daten-Gesetze" geändert, die das Datenschutzgesetz(DSG) enthälten. Das DSG führte das Konzept der pseudonymen Informationen ein und baute eine Rechtsgrundlage für deren Verwendung auf. Als Folgemaßnahme kündigte die, Kommission für den Schutz personenbezogener Daten(Personal Information Protection Commission: PIPC)' die „Richtlinien für die Bahandlung mit pseudonymen Informationen" und, Ministerium für Gesundheit und Wohlfahrt' die „Richtlinien für die Verwendung von Gesundheitsdaten" an. Gesundheitsdaten stehen direkt in Zusammenhang mit Leben und Körper des Menschen und damit enthalten viele sensible Daten. Es handelt sich also um ein System, das aus einer vorsichtigeren und konservativeren Sicht unter der Voraussetzung verwendet werden kann, personenbezogene Daten sicherer zu schützen. Um die Hauptinhalte der „Richtlinien für Verwendung von Gesundheitsdaten" zu analysieren, überprüften wir zunächst die Hauptinhalte des überarbeiteten DSG. Danach durch die Analyse der wesentlichen Inhalte der „Richtlinien für Verwendung von Gesundheitsdaten" wurden Probleme wie Konflikte mit anderen Gesetzen und Verbesserungsmaßnahmen überprüft.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.73-82
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• 2009

Due to the many advantages including low price, low power consumption, and miniaturization, the CMOS camera has been utilized in many applications, including mobile phones, the automotive industry, medical sciences and sensoring, robotic controls, and research in the security field. In particular, the 360 degree omni-directional camera when utilized in multi-camera applications has displayed issues of software nature, interface communication management, delays, and a complicated image display control. Other issues include energy management problems, and miniaturization of a multi-camera in the hardware field. Traditional CMOS camera systems are comprised of an embedded system that consists of a high-performance MCU enabling a camera to send and receive images and a multi-layer system similar to an individual control system that consists of the camera's high performance Micro Controller Unit. We proposed the SL-AVS (Small Size/Low power Around-View System) to be able to control a camera while collecting image data using a high speed synchronization technique on the foundation of a single layer low performance MCU. It is an initial model of the omni-directional camera that takes images from a 360 view drawing from several CMOS camera utilizing a 110 degree view. We then connected a single MCU with four low-power CMOS cameras and implemented controls that include synchronization, controlling, and transmit/receive functions of individual camera compared with the traditional system. The synchronization of the respective cameras were controlled and then memorized by handling each interrupt through the MCU. We were able to improve the efficiency of data transmission that minimizes re-synchronization amongst a target, the CMOS camera, and the MCU. Further, depending on the choice of users, respective or groups of images divided into 4 domains were then provided with a target. We finally analyzed and compared the performance of the developed camera system including the synchronization and time of data transfer and image data loss, etc.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.71-82
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• 2006

One of the most popular pre-reinforcement methods of tunnel heading in cohesionless soils would be the fore-polling of grouted pipes, known as RPUM (reinforced protective umbrella method) or UAM (umbrella arch method). This technique allows safe excavation even in poor ground conditions by creating longitudinal arch parallel to the tunnel axis as the tunnel advances. Some previous studies on the reinforcing effects have been performed using numerical methods and/or laboratory-based small scale model tests. The complexity of boundary conditions imposes difficulties in representing the tunnelling procedure in laboratory tests and theoretical approaches. Full-scale study to identify reinforcing effects of the tunnel heading has rarely been carried out so far. In this study, a large scale model testing for a tunnel in granular soils was performed. Reinforcing patterns considered are four cases, Non-Reinforced, Crown-Reinforced, Crown & Face-Reinforced, and Face-Reinforced. The behavior of ground and pipes as reinforcing member were fully measured as the surcharge pressure applied. The influences of reinforcing pattern, pipe length, and face reinforcement were investigated in terms of stress and displacement. It is revealed that only the Face-Reinforced has decreased sufficiently both vertical settlement in tunnel heading and horizontal displacement on the face. Vertical stresses along the tunnel axis were concentrated in tunnel heading from the test results, so the heading should be reinforced before tunnel advancing. Most of maximum axial forces and bending moments for Crown-reinforced were measured at 0.75D from the face. Also it should be recommended that the minimum length of the pipe is more than l.0D for crown reinforcement.

• Korean Journal of Culture and Social Issue
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• v.12 no.1
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• pp.129-160
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• 2006

The purposes of this study were to find 1) the realities of social anxiety and perception of various kinds of social problems that exists in Korean society as well as the perception on the events that causes the social anxiety, 2) to see the difference of perceived level of social anxiety through variables of social demography and difference of perception on Korean society. The sample was distributed according to population size distinguishing the nation to 6 regions. The data of 1,375 adult respondents were analysed. The results are as follows. First of all, respondents mentioned that the most immediate problem to be solved in Korean society was financial anxiety, and the most desirable state of society was when the society is financially stabled. Single question was measured about social anxiety of Korean society and scored 6.84 from full marks of 10, showing difference in variables for instance sex, age, and subjective S.E.S. where women, aged under 20, and perceived low class group showed the highest rate of social anxiety. However, there weren't any difference found in social anxiety of the variables like presence of religion, educational background, residence, and monthly average household income. Also, there were differences in level of social anxiety according to the difference of perception of Korean society. Higher the perceived unpredictability, uncontrollability, and unmovability to the upper class, unfairness, and uncertainty, unreliability of the Korean society, higher the social anxiety. And the lower the perceived chance of success of reformation, higher the social anxiety. It was also found that the perceived social anxiety is influenced by social accidents and phenomenon as unemployment, economic depression, and the gap between rich and poor as well as the increase of crime through effluence of personal information. Finally the limitations and implications of this study were discussed.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.217-240
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• 2023

For a while, Functional cosmetics, Cosmeceutical cosmetics, and Derma cosmetics have gained trust and become popular due to the consumers' strong interest in ingredients & efficacy. It's remarkable that Clean or Vegan brands are growing fast because they are emphasizing on different values from the other cosmetic brands. It's needed to attempt to analyze the influence relationship between consumer lifestyle and social value in these changes, and to find out whether the consumption of vegan cosmetics is related to satisfying the need for self-expression in a social atmosphere where ESG is emphasized on. This study analyzed the effect of lifestyle types and self-expression needs on the purchase intention of vegan cosmetics by mediating social values for cosmetics consumers. Lifestyle types were classified into appearance-oriented, health-oriented, and fashion-oriented. For empirical analysis, 321 questionnaires collected from cosmetics consumers living across the country were used. SPSS v26.0 and PROCESS macro v4.2 were used to analyze based on a single mediating model as a single mediator. As a result of the analysis, first, lifestyle types and self-expression needs, excluding appearance-oriented types, were found to have a positive (+) effect on social values. Second, it was found that social value had a positive (+) significant effect on the purchase intention of vegan cosmetics. Third, appearance-oriented, health-oriented, trend-seeking lifestyle types and self-expression needs were all found to have a positive (+) effect on the purchase intention of vegan cosmetics. Fourth, social values were found to mediate lifestyle types, self-expression needs, and purchase intentions, except for appearance-oriented types. Appearance-oriented consumers do not directly affect social values but affect purchase intentions, suggesting that appearance-oriented consumers may not be significantly affected by product-related social values. In a comparison of the relative influence size using standardization coefficients, self-expression needs had the greatest impact on the purchase intention of vegan cosmetics when mediating social values, and health-oriented ones had the least impact. The academic implications of this study include contributing to consumer behavior research by providing insights, mediation mechanisms, and consideration of the niche consumer sector, and directing further research into the cosmetics industry beyond forming marketing strategies and sustainable business practices.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.119-133
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• 2024

As a result of significant investments by the government in promoting public technology commercialization and fostering a venture startup ecosystem, there have been quantitative achievements, such as the registration of over 1,600 Innopolis Start-ups since 2006, generating a total revenue of 1.1 trillion won as of 2021. However, these achievements have been overshadowed by critical qualitative challenges, including a continuous decline in average revenue per Innopolis Start-up. This led to a focus on whether managers' technological and market orientations affect business performance. This study aims to provide insights into improving the qualitative growth of Innopolis Start-ups by analyzing the effects of technological and market orientations on business performance, as well as the moderating effects of adjusting marketing and research and development (R&D) costs on this relationship. Through prior research and empirical analysis, this study derives three main findings. First, technological excellence and innovation significantly influence the business performance of Innopolis Start-ups, while technological intensity does not. Second, customer orientation and competitive orientation significantly impact business performance, whereas entry barriers as a single factor do not. Third, adjusting marketing and R&D costs, as controlled variables obtained through general situations, has no direct impact on other variables. However, it interacts with entry barriers, influencing financial business performance, with R&D costs exhibiting a negative buffering effect and marketing costs showing a positive enhancing effect. This study confirms that both technological and market orientations directly influence the business performance of Innopolis Start-ups, thus being crucial factors affecting their growth. Moreover, it establishes that investments in marketing and R&D play significant roles in alleviating initial entry barriers and enhancing financial performance. Consequently, it underscores the importance of reinforcing technological and market orientations tailored to the characteristics of Innopolis Start-ups. Additionally, it proposes five theoretical contributions: strengthening institutional support systems for technology commercialization and innovation, improving qualitative evaluation criteria during the selection process of Innopolis Start-ups, conducting comprehensive analyses of technological and market aspects during startup selection, enhancing support for marketing education and consulting for smooth market entry, and supporting expenditure strategies and milestone setting tailored to the industrial characteristics of individual Innopolis Start-ups.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• THE JOURNAL OF KOREAN ORIENTAL ONCOLOGY
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• v.4 no.1
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• pp.37-53
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• 1998

The sprig of Jinryungtang Gagambang has been used for curing as a traditional medicine without any experimental evidence to support the rational basis for their clinical use. This experiment was carried out to evaluate the possible therapeutic or antitumoral effects of Jinryungtang Gagambang extract against cancer, and to study some mechanisms responsible for its effect. The cytotoxic and antitumor effects were evaluated on human cell liens (A549, hep3B, Caki-1, Sarcoma 180) after exposure to Jinryungtang Gagambang extract using in ILS, colony forming efficency and SRB assay which were regarded as a valuable method for cytotoxic and antitumor effects of unknown compound on tumor cell lines. The results obtained in this studies were as follows. 1. As a result of exposure to Jinryungtang Gagambang extract, the proliferation of A549, hep3B, Caki-1, good correlations were shown from the results of SRB assay and those of clogenetic assay. 2. The oral administration of Jinryungtang Gagambang extract showed significant effects of increase of MST(mean survival time) and ILS(increased life span) depending on the increasing concentration. 3. Against squamous cell carcinoma induced by MCA, Jinryungtang Gagambang decreased not only the frequency of tumor production but also the number and weight of tumors per tumor bearing mice(TBM). Jinryungtang Gagambang also significantly suppressed the development of 3LL cell-implanted tumors by frequency and their size, and some developed tumors were regressed by the continuous treatment of Jinryungtang Gagambang extract into TBM. 4. Jinryungtang Gagambang extract also increased NK cell activities. According to the above results, it could be suggested that Jinryungtang Gagambang extract has prominent antiutmor effect.