• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.23 no.1
• /
• pp.32-35
• /
• 1978

In order to screen cold tolerant soybean lines, germination at various temperature, and emergence and seedling height at 1$0^{\circ}C$ were investigated. Since the most conspicuous varietal difference of the germination speed was observed at 1$0^{\circ}C$, the germination test at 1$0^{\circ}C$ would be effective in screening cold tolerant lines.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.419-425
• /
• 2023

The research object of this paper is "Yi" and "Yi" in ancient calligraphy theory, as an aesthetic category with oriental characteristics, from Laozhuang philosophy of pre-Qin Dynasty to literature field of literature.The second chapter describes the emergence and development of the concept of "Yi", which has evolved into two concepts in ancient calligraphy and painting theory, namely, the concept of "Yi".In the third chapter, "Yi" is mainly used as an adjective to describe the speed, power and strength of writing, and in the fourth chapter, "Yi" is used to describe the writer's character.Based on the study of ancient sages' calligraphy, this paper attempts to explore the inner spirit of "Yi" and to systematically analyze and summarize the theory of calligraphy and painting.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.4
• /
• pp.119-129
• /
• 2009

In The increasing use of computers and high-speed Internet network has greatly influenced education, causing a veering away from the typical and traditional way of delivering instruction. Specifically, the various kinds of Web-based multimedia technology, the interactive activities on the Internet, and satellite broadcasting technology are accelerating the emergence of a virtual-lectures-based educational model, which transcends time and space. Such virtual lectures make it possible for the entire teaching-learning process to be done in a virtual learning environment, thus giving rise to problem regarding learning guidance, feedback, and appraisal. In this paper, we propose a system for attendance appraisal for learner participation degree based virtual lecture, an appraisal element in virtual learning environments. This appraisal model can set the elements of virtual learning environments in such a way as to reflect in the attendance appraisal of the opened virtual learning environment information regarding the learner's participation in class. In addition, this model motivates the learners to actively participate in the virtual learning environment and to support instructors by accomplishing the activities that are needed for attendance appraisal.

• Fashion & Textile Research Journal
• /
• v.25 no.6
• /
• pp.690-703
• /
• 2023

With the emergence of digitalization and environmental changes, such as those caused by COVID-19 and high-speed networks, online video platforms have changed how people communicate and created new marketing opportunities. The unique characteristics of mobile short-form videos are causing more people to consume and produce diverse content in the digital environment. The study focuses on two story types (product essential and relative information) to examine the effectiveness of short-form videos for fashion marketing. This study verified the influence of the common traits of short-form video content (informativeness, expertise, familiarity, and playfulness) on fun, e-WOM, and purchase intention and the mediation effect of fun using video samples categorized by story type. In this study, 300 Gen Z men and women responded to a survey after watching a 30-second short-form video sample. All the traits of short-form video content were found to have a positive effect on fun. Moreover, all the traits excluding playfulness had a positive effect on e-WOM and purchase intention as well. Fun had a positive effect on both e-WOM and purchase intention as well as a partial mediating effect. These findings are expected to provide insight and reference for planning short-form video marketing from the perspective of the fashion industry.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.6
• /
• pp.245-254
• /
• 2022

Proteins are the basic unit of all life activities, and understanding them is essential for studying life phenomena. Since the emergence of the machine learning methodology using artificial neural networks, many researchers have tried to predict the function of proteins using only protein sequences. Many combinations of deep learning models have been reported to academia, but the methods are different and there is no formal methodology, and they are tailored to different data, so there has never been a direct comparative analysis of which algorithms are more suitable for handling protein data. In this paper, the single model performance of each algorithm was compared and evaluated based on accuracy and speed by applying the same data to CNN, LSTM, and GRU models, which are the most frequently used representative algorithms in the convergence research field of predicting protein functions, and the final evaluation scale is presented as Micro Precision, Recall, and F1-score. The combined models CNN-LSTM and CNN-GRU models also were evaluated in the same way. Through this study, it was confirmed that the performance of LSTM as a single model is good in simple classification problems, overlapping CNN was suitable as a single model in complex classification problems, and the CNN-LSTM was relatively better as a combination model.

• International Journal of Computer Science & Network Security
• /
• v.23 no.10
• /
• pp.199-208
• /
• 2023

The emergence of COVID-19 virus has shaken almost every aspect of human life including but not limited to social, financial, and economic changes. One of the most significant impacts was obviously healthcare. Now though the pandemic has been over, its aftereffects are still there. Among them, a prominent one is people lifestyle. Work from home, enhanced screen time, limited mobility and walking habits, junk food, lack of sleep etc. are several factors that have still been affecting human health. Consequently, diseases like diabetes, high blood pressure, anxiety etc. have been emerging at a speed never witnessed before and it mainly includes the people at young age. The situation demands an early prediction, detection, and warning system to alert the people at risk. AI and Machine learning has been investigated tremendously for solving the problems in almost every aspect of human life, especially healthcare and results are promising. This study focuses on reviewing the machine learning based approaches conducted in detection and prediction of diabetes especially during and post pandemic era. That will help find a research gap and significance of the study especially for the researchers and scholars in the same field.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1081-1086
• /
• 2023

The rapid growth and increasing complexity of modern networks have highlighted the limitations of traditional network architectures. The emergence of SDN (Software-Defined Network) in response to these challenges has changed the existing network environment. The SDN separates the control unit and the data unit, and adjusts the network operation using a centralized controller. However, this structure has also recently caused a huge amount of traffic due to the rapid spread of numerous Internet of Things (IoT) devices, which has not only slowed the transmission speed of the network but also made it difficult to ensure quality of service (QoS). Therefore, this paper proposes a method of load distribution by switching the IP and any server (processor) from the existing data processing scheduling technique, RR (Round-Robin), to mapping when a large amount of data flows in from a specific IP, that is, server overload and data loss.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.3
• /
• pp.583-588
• /
• 2024

With the emergence of Brain-Computer Interface (BCI) technology, analyzing mirror neurons has become more feasible. However, evaluating the accuracy of BCI systems that rely on human thoughts poses challenges due to their qualitative nature. To harness the potential of BCI, we propose a new approach to measure accuracy based on the characteristics of mirror neurons in the human brain that are influenced by speech speed, depending on the ultimate goal of movement. In Chapter 2 of this paper, we introduce mirror neurons and provide an explanation of human posture estimation for mirror neurons. In Chapter 3, we present a powerful pose estimation method suitable for real-time dynamic environments using the technique of human posture estimation. Furthermore, we propose a method to analyze the accuracy of BCI using this robotic environment.

• Korean Journal of Medicinal Crop Science
• /
• v.1 no.1
• /
• pp.3-9
• /
• 1993

This experiment was conducted to study germination characteristics and the decrease cause of germination percent in Angelica gigas Nakai seed. The emergence percent of winter sowing was higher than that of spring sowing as 66.6% and 41.1%, respectively, and the first emergence date was also earlier in winter sowing. The seed germination speed, percent and coefficent showed the highest value at $20^{\circ}C$ of incubation temperature, but lower value at $10^{\circ}C\;and\;30^{\circ}C$. The water uptake speed was increased along with increasing water temperature. The weight of imbibed seed at germination was 3.4times higher based on the weight of intact dry seed and 2.3times on removal of seed coat. In terms of length of seed was large, the germination percent was higher. The germination percent of brown colored seeds showed higher value than that of green colored seeds. The prolonged storage period decreased germination percent. When A.gigas seeds stored at room temperatue for 2years, the seeds were lost their viability. The biological inhibition effect of methanol, water and ether extract on the germination and growth of A.gigas and lettuce seed showed the highest value in the methanol extract, followed by water extract and the least in ether extract.

• Journal of Distribution Science
• /
• v.12 no.11
• /
• pp.85-100
• /
• 2014

Purpose - Recently, the prevalence of high-speed mobile communication technology (4G) and mobile devices (smart phones, tablet PC, etc.) is leading innovative changes across all fields in society as well as business environments. Furthermore, a diversified mobile application service has spread rapidly through mobile devices such as smart phones and tablet PCs. Accordingly, the traditional E-government services paradigm has rapidly changed into mobile intelligence. To identify the influencing factors on the using intention of G4C smart app services, based on previous studies, the variables that influence using G4C smart app services are defined; these are user cognitive factors (perceived usefulness, perceived easiness), user characteristics factors (user innovativeness, self-efficiency, social influence), service quality factors (convenience, interactivity, accessibility), and system quality factors (instant connectivity, safety). Research design, data, and methodology - This is designed not only to collect data with a questionnaire survey (9/22/13~10/23/13) but also to test hypotheses with SEM by SPSS 21.0 and AMOS 21.0 in both Korea and China. All items are used with Likert 5 scales. A total of 643 questionnaires (Korea 318, China 325) are used. Results - The perceived usefulness and perceived easiness in user cognitive factors have positive influence on using intention. The user innovativeness, self-efficiency, and social factors in user characteristics factors have positive influences on using intention. The convenience, interactivity, and accessibility in service quality factors have positive influences on both reliability and using intention. Safety in system quality has positive influence on both reliability and using intention. Reliability has positive influence on using intention. The control variables (Korea and China) affect its control hypothesis. Strategies and implications are suggested to assist the public using the intention of smartphone's e-government services based on the results of the empirical analysis. The mobile application service can be considered a new emergence of the paradigm just like the government's on-line portal websites appeared in the past. Under this prevailing situation of mobile smart devices, to promote the success of e-government mobile APP services, accurate analysis and understanding of users should precede anything, to provide services to grasp and satisfy users' desire properly. Conclusions - This study proposes implications to help E-governmental officers and companies make strategies. First, this is expected to give some information on the understanding and knowledge regarding the process of G4C smart APP service based on the empirical study. Second, this helps to make future policies and ways about E-government G4C smart APP service. Third, it is proved that super speed mobile communication technology and devices including phones will be crucial to change the structure of E-government services in 2-3 years. Fourth, it is necessary to increase the trust and using intention of users. Fifth, considering what type of environment users are placed in, to present proper public information matching their inclination, is important. Finally, various ways of experiencing service to explore potential users and ceaseless public relations are required.