• Korean Journal of Ecology and Environment
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• v.54 no.1
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• pp.39-48
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• 2021

In order to control algal bloom, which causes environmental problems such as eutrophication in freshwater ecological environments, many attempts have recently been made using biological approaches. Among them is filtration using bivalve. Algae control with filter-feeding bivalves is emerging as an eco-friendly method. In this study, bivalves collected at Baekje weir in Geum River in Korea from Jun to Sep 2020 were tested to find out the possibility of algae control using filter-feeding bivalves through laboratory experiments. The Unio douglasiae, Anodonta woodiana, and Anodonta arcaeformis collected from Baekje weir were put into a water tank (2 L) containing Clorella vulgaris, and as a result, the average filtration rate was 95.9% per animal after 24 hrs. Calculating this with the Chl-a concentration converted to a calibration curve, it was found that the average of 154.84 ㎍ L^-1 of Chl-a was reduced. Based on this calculation, the possibility that one bivalve can eliminate Chl-a in one month is 0.0005%. It is expected that the effect is 20.14% when there are 40,000 animals. These results indirectly showed how effective bivalve's ability to control Chl-a in their habitat is. Although this study was limited to calculating the algae control ability of aquatic ecosystem based on the filtration rate of bivalve and the corresponding Chl-a reduction rate, it is thought that it will be used as basic data for integrated research from various factors and viewpoints (phytoplankton, aquatic plants, benthic organisms, and sediments) through additional research.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.120-130
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• 2021

This study was conducted for the purpose of developing an education program using smart apps that supports free play of children based on STEAM education and verifying its effectiveness. In order to achieve the purpose of the study, contents for using smart apps based on STEAM education for children's free play were derived through literature and data collection and field surveys in related fields, and a program was developed based on this. This program is a teaching strategy in which teachers and children interact at the start, middle, and end of free play using the 'Free Play' app installed on a smartphone. An experimental study was conducted to verify the effectiveness of the program using smart apps that support children's free play. As a result of the study, it was confirmed that the application of this program improves the self-regulation of children. This study is a teaching strategy to support both teachers and children during free play time, the core of early childhood education, and developed and applied the program with the idea of convergence of engineering and education, and hopes that it will be a starting point for revitalizing education using smart apps in the future education field.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.243-261
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• 2021

Social TV users and content are increasing day by day. The main purpose was to study the motivation for social television users, but I felt the need to analyze the potential psychological impact of users in various content. This study analyzed the impact on psychological well-being due to the interaction and viewing satisfaction by the object relations theory factors of social TV user in Korea. A survey was conducted on students of N university, ordinary university, and ordinary people who have experience using social TV to prove the observations or experiments of empirical facts in this study. Research result, First, Nonalienation have been have a positive effect on interaction and viewing satisfaction. Second, stable attachment have been have a positive effect on interaction. Third, social competence have been have a positive effect on interaction. Fourth, interaction have been have a positive effect on viewing satisfaction and psychological well-being. Fifth viewing satisfaction have been have a positive effect on Psychological well-being. Through this, This will contribute to the development of subdivided content and user-customized services for social television, and it is necessary to reconfigure and study various events that may occur between users in the future.

• Journal of Korean Elementary Science Education
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• v.40 no.2
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• pp.162-174
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• 2021

The purpose of this study was to investigate the types of questions raised by pre-service elementary teachers when planning a science class utilizing smart technology and the characteristics of their lesson plans. For this purpose, lesson plans and questions written by the 96 pre-service teachers were collected. The results of this study can be summarized as follows: (1) Pre-service teachers used simulation apps, information offering apps, clicker evaluation apps, astronomical observation apps. Simulation apps and clicker evaluation apps were used the most in the introduction stage of the class, simulation apps in the development stage, and clicker evaluation apps in the finishing stage. (2) In the lesson plans, the activities that elementary school students use smart technology showed more than those used by teachers, and its characteristics were more prominent in the development stage of the class. (3) As for the content type of smart technology, experience type was the highest, followed by tool type and resource type. In comparison, there were relatively few interaction support types and learning opportunity extensions. (4) There were many cases in which pre-service teachers replaced elementary school students with virtual experiences using experience type instead of providing opportunities to experiment or experience directly. (5) Pre-service teachers asked various questions while planning science class utilizing smart technology, and a total of 25 question types appeared in 7 categories.

• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.640-645
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• 2021

The deep learning based end-to-end TTS system consists of Text2Mel module that generates spectrogram from text, and vocoder module that synthesizes speech signals from spectrogram. Recently, by applying deep learning technology to the TTS system the intelligibility and naturalness of the synthesized speech is as improved as human vocalization. However, it has the disadvantage that the inference speed for synthesizing speech is very slow compared to the conventional method. The inference speed can be improved by applying the non-autoregressive method which can generate speech samples in parallel independent of previously generated samples. In this paper, we introduce FastSpeech, FastSpeech 2, and FastPitch as Text2Mel technology, and Parallel WaveGAN, Multi-band MelGAN, and WaveGlow as vocoder technology applying non-autoregressive method. And we implement them to verify whether it can be processed in real time. Experimental results show that by the obtained RTF all the presented methods are sufficiently capable of real-time processing. And it can be seen that the size of the learned model is about tens to hundreds of megabytes except WaveGlow, and it can be applied to the embedded environment where the memory is limited.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.1-12
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• 2021

This study focused on verifying the identification of freshwater fish species in Korea using Environmental DNA (eDNA) technique. The research of DNA is increasing in the field of ecology, since this is more sensitive of identify rather than traditional investigation method. Which is difficult to detect species hidden in water and be easily influenced by diverse factors (sites, bad weather, researchers and so on). We applied the pilot test in aquarium (Freshwater Fish Ecological Learning Center in Yangpyeong, Gyeonggi Do), where freshwater fish species are inhabits. We conducted to sampling and analyzing the sixteen water samples (50 species from 7 orders and 13 families) using MiFish primer set. The results showed that 45 species (90%) was investigated by eDNA. It highlight that eDNA with universal primer is possible to detect freshwater fish species of Korean. However, the errors on species identification seems to be caused by the primer that be not suited perfectly and the pollution such as aquarium, sampling collectors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.395-400
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• 2020

Pigs have been used widely in biomedical research owing to their physiologic and anatomic similarities to humans. Analysis of the hematologic and biochemical values in pigs is an important basis for biomedical research and veterinary clinical diagnosis, but research on transgenic pigs has been sparse. This study was conducted to obtain basic data on transgenic pigs and to describe and compare the reference values for hematologic and biochemical parameters in human tissue plasminogen activator (htPA) transgenic pigs vs normal pigs. Blood samples were obtained from 7 normal LY (Landrace-Yorkshire crossbred) pigs and 8 transgenic pigs and 16 hematologic and 15 serum biochemical parameters were tested. Among the hematologic parameters tested, significant differences were observed in the red blood cells (RBC), mean red blood cell hemoglobin (MCH), and lymphocytes (LYM), between the non-transgenic and transgenic pigs. Among the biochemical parameters tested, the blood urea nitrogen (BUN), total protein (TP), cholesterol (CHOL), alanine aminotransferase (ALT), creatinine (CREA), gamma glutamyl transpeptidase (GGT), globin (GOB), and amylase (AMYL) showed significant differences between the two groups. Thus, the values determined in this study can be used as basic reference values for transgenic pigs and will contribute to their use in biomedical research.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1349-1365
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• 2020

In recent years, in the fields of smart cities and digital twins, research on model generation is increasing due to the advantage of acquiring actual 3D coordinates by using point clouds. In addition, there is an increasing demand for a solid model that can easily modify the shape and texture of the building. In this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. Accordingly, in this paper, we propose a method to create a clustered solid building model based on point cloud data. The proposed method consists of five steps. In the first step, the ground points were removed through the planarity analysis of the point cloud. In the second step, building area was extracted from the ground removed point cloud. In the third step, detailed structural area of the buildings was extracted. In the fourth step, the shape of 3D building models with 3D coordinate information added to the extracted area was created. In the last step, a 3D building solid model was created by giving texture to the building model shape. In order to verify the proposed method, we experimented using point clouds extracted from unmanned aerial vehicle images using commercial software. As a result, 3D building shapes with a position error of about 1m compared to the point cloud was created for all buildings with a certain height or higher. In addition, it was confirmed that 3D models on which texturing was performed having a resolution of less than twice the resolution of the original image was generated.