• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.174-183
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• 2022

The abstract should summarize the contents of the paper and written below the author information. Use the word "Abstract" as the title, in 12-point Times New Roman, boldface type, italicized, centered relative to the column, initially capitalized, fixed-spacing at 13 pt., 12 pt. spacing before the text and 6 pt. after. The abstract content is to be in 11-point, italicized, single spaced type. Leave one blank line after the abstract, and then begin the keywords. All manuscripts must be in English. When it comes to the issue of "virtual and real" in traditional Chinese painting, the first impression is to describe the problems of painting strokes and ink, layout of pictures, etc., but it runs through the initial conception of the work, creation in the middle and aesthetic appreciation of the work. It exists in the whole process of artistic creation and appreciation. In essence, it is a problem of aesthetic thinking and philosophical thinking. Because the traditional Chinese painting theory is influenced by Taoism, when the concept of "virtual and real" is implemented in the specific picture of Chinese painting, it is contained in the specific shape of "physics", that is, the painting theory research of "blank space" in the picture. Based on the traditional Taoist philosophy of China, this paper takes the "virtual and real" view in Lao Zhuang's thought as the research object, deeply analyzes and compares its relationship with the "virtual and real" in Chinese landscape painting, and finds out their artistic spirit, essential characteristics and how to present them. This paper mainly discusses the internal relationship between Taoist philosophy and "virtual and real" in Chinese landscape painting from the following aspects. The introduction expounds the origin, purpose, significance, innovation and research methods of the topic. This paper analyzes the philosophical thoughts about landscape in the philosophical thoughts represented by Lao Tzu and Zhuangzi. The development of Chinese traditional aesthetics theory is closely related to Taoist philosophy, which has laid the foundation and pointed out the direction for the development of Chinese painting theory since ancient times. It also discusses the influence of the Taoist philosophy of "the combination of the virtual and real" on the emergence and development of the artistic conception of landscape painting. Firstly, through the analysis of the artistic conception of landscape painting and its constituent factors, it is pointed out that the artistic conception is affected by the personality and the painting artistic conception. Secondly, through the Taoist thought of "the combination of the virtual and real" in landscape painting, so as to reflect that it is the source of the artistic conception of Chinese landscape painting. It is the unique spiritual concept of "Yin and Yang" and "virtual and real" that creates the unique "blank space" aesthetic realm of Chinese painting in the composition of the picture. Finally, it focuses on the "nothingness" in Taoist philosophy and the "blank space" in Chinese landscape painting. The connotation of the "blank space" in Chinese painting exceeds its own expressive significance, which makes the picture form the aesthetic principle of emotional blending, virtual and real combination and dynamic and static integration. Through the "blank space", it deepens the artistic characteristics of the picture and sublimates the expression of "form" in Chinese painting.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• Journal of Veterinary Science
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• v.21 no.4
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• pp.65.1-65.13
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• 2020

Background: Aleutian mink disease virus (AMDV) causes major economic losses in fur-bearing animal production. The control of most AMDV outbreaks is complex due to the difficulties of establishing the source of infection based only on the available on-farm epidemiological data. In this sense, phylogenetic analysis of the strains present in a farm may help elucidate the origin of the infection and improve the control and biosecurity measures. Objectives: This study had the following aims: characterize the AMDV strains from most outbreaks produced at Spanish farms between 2012-2019 at the molecular level, and assess the utility of the combined use of molecular and epidemiological data to track the possible routes of infection. Methods: Thirty-seven strains from 17 farms were partially sequenced for the NS1 and VP2 genes and analyzed phylogenetically with other strains described worldwide. Results: Spanish AMDV strains are clustered in four major clades that generally show a good geographical correlation, confirming that most had been established in Spain a long time ago. The combined study of phylogenetic results and epidemiological information of each farm suggests that most of the AMDV outbreaks since 2012 had been produced by within-farm reservoirs, while a few of them may have been due to the introduction of the virus through international trade. Conclusions: The combination of phylogenetic inference, together with epidemiological data, helps assess the possible origin of AMDV infections in mink farms and improving the control and prevention of this disease.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.275-284
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• 2023

Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.77-92
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• 2022

Recently, digital transformation in the financial industry has been accelerated, and it has become an important task to improve the level of utilization of Internet banking by elderly consumers, who are vulnerable to Internet use. Accordingly, this study analyzed 3,101 respondents in their 60s or older from the 11th year of the Media Panel Survey to identify demographic, experiential, and psychological factors that affect the self-efficacy of elderly consumers' usage of Internet banking. The main research findings are as follows. First, gender, education, occupation, and income were identified as demographic variables. Second, the Internet shopping experience was identified as an experiential factor. Also, concerns about information security, digital literacy, and high will for problem-solving were identified as psychological factors. Third, as a result of the moderating effect analysis on whether the experiential and psychological factors have different influences according to the group divided into the 60s and 70s, the effect on self-efficacy in the usage of the Internet was classified by age. The results of this study will be able to enrich the discussions related to the intention to utilize technology among elderly consumers by empirically revealing that there are characteristics that cause differences in financial behavior even within one group called the elderly.

• Pediatric Infection and Vaccine
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• v.30 no.2
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• pp.62-72
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• 2023

Purpose: A change is expected in the pattern of respiratory viruses including human coronavirus (HCoV) after the coronavirus disease 2019 (COVID-19) outbreak. Accordingly, identifying the distribution of respiratory viruses before the COVID-19 outbreak is necessary. Methods: We retrospectively analyzed the results of samples of nasal swabs collected from children under aged ≤18 years who were hospitalized at Myongji Hospital, Gyeonggi-do due to acute respiratory infections from 2017 to 2019. Viruses were detected by real-time reverse transcription polymerase chain reaction (RT-PCR). Results: Out of 3,557 total patients, 3,686 viruses were detected with RT-PCR including coinfections. Of the 3,557 patients, 2,797 (78.6%) were confirmed as PCR-positive. Adenovirus and human rhinovirus (hRV) were detected throughout the year, and human enterovirus was most detected during summer. Respiratory syncytial virus, influenza virus, and HCoV were prevalent in winter. In patients with croup, parainfluenza virus was most frequently detected, followed by hRV and HCoV. The PCR positive rate in summer and winter differed significantly. Conclusions: Respiratory virus patterns in northwestern Gyeonggi-do were not much different from previously reported data. The data reported herein regarding respiratory virus epidemiological information before the COVID-19 outbreak can be used for use in comparative studies of respiratory virus patterns after the COVID-19 outbreak.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.85-91
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• 2021

School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, and identify peer relationships. The frequency of conversations between students in the class was quantified using a rating scale questionnaire, and this data was grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.351-361
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• 2023

The purpose of this paper is to help those who research and develop solar cells in university laboratories and industrial sites understand the most basic and important quantum efficiency measurement and analysis method in analyzing solar cell performance. Starting with the definition of quantum efficiency, we calculate the theoretical current density according to the band gap of the solar cell material from the solar spectrum, along with a detailed introduction to the measurement and analysis methods, and measure and analyze the theoretical current density and quantum efficiency. We discuss in depth how to analyze the performance of solar cells through Quantum efficiency measurement and analysis of solar cells is a very useful method that can give intuition to solar cell performance analysis as it can analyze solar cells according to depth (front emitter, bulk, rear surface). Students and researchers who study solar cells with a deep understanding of theoretical current density and quantum efficiency measurement analysis are expected to use it as a basis for analyzing solar cell performance.