• Korean Journal of Poultry Science
• /
• v.49 no.2
• /
• pp.89-98
• /
• 2022

This study compared the production and physiological characteristics of male and female Korean native commercial chickens. We investigated the growth performance, vitality, and stress response of 479 male and 608 female chickens from 1 d to 12 weeks of age. The body weight, feed consumption and feed conversion ratio were measured as growth performance. The survival rate, amount of telomeric DNA, DNA damage rate, heterophil-lymphocyte ratio (H/L ratio), and heat shock protein (HSP)-70, HSP-90α, and HSP-90β gene expression levels were analyzed as indicators of vitality and stress response. Body weight was significantly higher in male chickens than in female chickens after 2 weeks of age (P<0.01). Feed intake was higher in male chickens than in female chickens, whereas the feed conversion ratio showed the opposite trend. The survival rate was significantly higher in female chickens than in male chickens (82.8% vs. 73.8%, P<0.05). Stress response analysis revealed no differences between male and female chickens in terms of telomeric DNA content, DNA damage rate, H/L ratio, and HSP gene expression levels. Taken together, it was concluded that there was a significant difference in the growth performance and survival rate between male and female Korean native commercial chickens, whereas there was no difference in the degree of stress response between them. Therefore, in terms of the productivity of Korean native commercial chickens, it is judged that separate-sex rearing is much more advantageous than mixed rearing, regardless of the physiological characteristics of males and females.

• Journal of Industrial Convergence
• /
• v.20 no.10
• /
• pp.87-94
• /
• 2022

This paper seeks to raise inflection points of battery manufacturing bases in Korea in the V4 region through the reorganization of new industrial technologies in accordance with ESG. As a result, the global supply chain market is cut off. The Russian-Ukraine war and the U.S.-China hegemony are competing in the economic crisis caused by COVID-19. It is showing diversification of new suppliers in an environment where mineral, grain procurement, gas, and even wheat imports from China and Russia are not possible. As a protective glocal, this area is used as a buffer zone(Pro-Russia, Hungary). to an isolated zone(anti-Russia, Poland) by war. In this paper, economic growth is expected to slow further due to the EU tapering period and high inflation in world countries. Due to these changes, the conversion of new tech industry and the contraction of Germany's structure due to energy supply may lose the driving force for economic growth over the past 20 years. This is caused by market disconnection(chasm) in the nominal indicators in this area. On the other hand, Korea should actively develop into the V4 area as an energy generation export (nuclear and electric hydrogen generation) area as a bypass development supply area due to the imbalance in the supply chain of rare earth materials that combines AI. By linking this industry, the energy platform can be scaled up and reliable supply technology (next generation BT, recycling technology) in diversification can be formed in countries around the world. This paper proves that in order to overcome the market chasm caused by the industries connection, new energy development and platform size can be achieved and reliable supply technology (next-generation battery and recycling technology, Low-cost LFP) can be diversified in each country.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1541-1555
• /
• 2022

Red tide has potential to harm marine ecology and aquaculture. Research on detecting red tide using various optical remote sensors has been conducted, but most of existing algorithms for detecting red tide has limitations, especially in shallow coastal waters with high levels of suspended sediment. For enhanced understanding of the optical behavior of red tide waters, analysis on remote sensing reflectance and water constituent is becoming increasingly important. This study analyzed the optical remote sensing data and water quality variables(Chl-a_(Spec), SPM, a_ph, a_d, Turbidity, Chl-a_(HPLC), Dominant species) of red tide waters. The data were collected from ship-based campaigns. In addition to the research on detecting red tide, the remote sensing reflectance and extinction coefficients for mesodinium and cochlodinium species were also analyzed. Through the analysis, it was possible to estimate the red tide chlorophyll concentration based on a specific wavelength of the remote sensing reflectance. The study found that chlorophyll concentration and phytoplankton absorption coefficient were highly correlated(R²=0.9), and that the RE_diff formula provided a more accurate estimate of red tide concentration than the B-G ratio.

• Journal of Internet of Things and Convergence
• /
• v.8 no.5
• /
• pp.85-91
• /
• 2022

In the IOT social environment, which emphasizes the convergence of science and technology and emotion, this study aims to explore the experience and meaning of the experience while participating in the design convergence class based on the operation of the Learning community of Chinese graduate students majoring in design. To this end, an implementation study was conducted by visualizing various research problems using a design-based inquiry method for 12 graduate students attending T University. The design-oriented convergence class was conducted in a small group with content that was deepened into a visual strategy by the expression technique given by the external environment and the learner's own inner motivation. In order to express the perspective and intention of the research problem in the research, the convergence design research expressed using various visual strategies such as metaphorical use and analysis of visual data in the research process and sensory approach to the research problem was presented in a form that expresses the creative thinking process. As a way of exploration, the teaching method of presenting results based on various experiences suggests changes in new teaching formats, practical knowledge sharing by instructors, and community participation by learning participants.

• The Korean Society of Law and Medicine
• /
• v.23 no.2
• /
• pp.119-139
• /
• 2022

Brain stimulation technology that administers electrical and magnetic stimulation to a brain has shown a significant level of possibility for treating a wide range of various neurological and psychiatric disorders. Depending on its nature, the technology is defined either as invasive or non-invasive, and deep brain stimulation (DBS) is one of the most well-known invasive brain stimulation technologies. Currently categorized as grade 4 medical device in accordance with Guideline On Medical Devices And Their Grades, a Notification of Ministry of Food and Drug Safety (MFDS), the DBS has been used as a stable treatment for several diseases. At the same time, the DBS technology has recently achieved substantial advancement, encouraging active discussions for its use from various perspectives. On the contrary, debates over legal regulation related to the use of DBS has relatively been smaller in numbers. In this context, this article aims to 1) introduce the DBS technology and its safety in setting out the tone; 2) touch upon major legal issues that would potentially rise from its use for four different purposes of treatment, clinical study, areas of non-standard treatment where no other methods are available, and enhancement; and finally 3) highlight disputes concerning common emerging issues observed in the aforementioned four purposes from the viewpoint of legal responsibility and liability of using the DBS, which are benefit-risk assessment, physicians' duty of information, patients' capacity to consent, control for device, and insurance coverage.

• Smart Media Journal
• /
• v.11 no.3
• /
• pp.9-17
• /
• 2022

Algorithmic trading, which uses algorithms to trade financial products, has a problem in that the results are not stable due to many factors in the market. To alleviate this problem, ensemble techniques that combine trading algorithms have been proposed. However, there are several problems with this ensemble method. First, the trading algorithm may not be selected so as to satisfy the minimum performance requirement (more than random) of the algorithm included in the ensemble, which is a necessary requirement of the ensemble. Second, there is no guarantee that an ensemble model that performed well in the past will perform well in the future. In order to solve these problems, a method for selecting trading algorithms included in the ensemble model is proposed as follows. Based on past data, we measure the contribution of the trading algorithms included in the ensemble models with high performance. However, for contributions based only on this historical data, since there are not enough past data and the uncertainty of the past data is not reflected, the contribution distribution is approximated using the Dirichlet distribution, and the contribution values are sampled from the contribution distribution to reflect the uncertainty. Based on the contribution distribution of the trading algorithm obtained from the past data, the Transformer is trained to predict the future contribution. Trading algorithms with high predicted future contribution are selected and included in the ensemble model. Through experiments, it was proved that the proposed ensemble method showed superior performance compared to the existing ensemble methods.

• The Journal of the Korea Contents Association
• /
• v.22 no.3
• /
• pp.547-559
• /
• 2022

This study is a qualitative study to explore caring of a mentally disabled family using mental rehabilitation facilities. As a result of the analysis, the life of a mentally disabled family appeared in 6 topics and 12 sub-themes. Life before the outbreak was warm and comfortable like an electric stove, and a frustrating and difficult life like a parrot in a cage due to family conflicts. The feeling of looking at the child who is starting to develop symptoms is fear and hopelessness that is hard to see ahead, and a sense of guilt for a child trapped in a disease before blooming his life. Forced hospitalization, and my feelings were torn apart, and my thoughts were confused by opaque recovery and worries about future life. The experience I felt as the disease lasted for a long time and hospitalized and discharged repeatedly feared that the mental illness of the family would be known to the people around me, and found that they struggled to cope with repeated recurrence and worsening symptoms. While using mental rehabilitation facilities, the changed life was comforted in a comfortable shelter, and turned out that there was hope for the future and that there was room to smile. The life expected in the future and the theme of hope turned out to be grateful for small changes and determined to be a warm fence for recovery.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.42 no.1
• /
• pp.117-126
• /
• 2022

Currently, the number of bridge structures in Korea is continuously increasing and enlarged, and the number of old bridges that have been in service for more than 30 years is also steadily increasing. Bridge aging is being treated as a serious social problem not only in Korea but also around the world, and the existing manpower-centered inspection method is revealing its limitations. Recently, various bridge damage detection studies using deep learning-based image processing algorithms have been conducted, but due to the limitations of the bridge damage data set, most of the bridge damage detection studies are mainly limited to one type of crack, which is also based on a close set classification model. As a detection method, when applied to an actual bridge image, a serious misrecognition problem may occur due to input images of an unknown class such as a background or other objects. In this study, five types of bridge damage including crack were defined and a data set was built, trained as a deep learning model, and an open set recognition-based bridge multiple damage recognition model applied with OpenMax algorithm was constructed. And after performing classification and recognition performance evaluation on the open set including untrained images, the results were analyzed.

• Journal of the Microelectronics and Packaging Society
• /
• v.28 no.4
• /
• pp.91-96
• /
• 2021

The enhancement of thermoelectric figure of merit was achieved by the simple processes of sieving and high energy ball milling, respectively, which are enable to reduce the grain size of n-type Bi₂Te₃ thermoelectric materials. By optimizing the grain size, the electrical conductivities and thermal conductivities were controlled. In this study, spark plasma sintering was employed for hindering the grain growth during the sintering process. The thermoelectric figure of merit was measured to be 0.78 in the samples with 30 min high energy ball milling process. Notably, this value was 40 % higher than that of pristine Bi₂Te₃ sample. This result shows the properties of thermoelectric materials can be readily controlled by optimization of grain size via simple ball milling process.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.4
• /
• pp.179-184
• /
• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.