• Journal of Sensor Science and Technology
• /
• v.30 no.3
• /
• pp.154-164
• /
• 2021

In this study, the IoT sensor technology required for improving the survival rate and high-density productivity of individual shrimp in smart shrimp farming (which involves the usage of recirculating aquaculture systems and biofloc technology) was analyzed. The principles and performances of domestic and overseas water quality monitoring IoT sensors were compared. Furthermore, the drawbacks of existing aquaculture monitoring technologies and the countermeasures for future aquaculture monitoring technologies were examined. In particular, for farming white-legged shrimp, an IoT sensor was employed to collect measurement indicators for managing the water quality environment in real-time, and the IoT sensor-based real-time monitoring technology was then analyzed for implementing the optimal farming environment. The results obtained from this study can potentially contribute to the realization of an autonomous farming platform that can improve the survival rate and productivity of shrimp, achieve feed reduction, improve the water quality environment, and save energy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.6
• /
• pp.496-502
• /
• 2020

The electronic attendance management system is being introduced and operated on a pilot basis by some universities and educational institutions. However, most of the related systems have installed and operated the existing barcode and magnetic card systems. Classroom attendance is managed by introducing RF cards, but it causes problems such as recognition distance (less than 5cm) and the need for a check process in which students have to read the card each time with a reader for attendance. Also, it is not possible to respond in real time to the situation of midterm (early leave, absence from the second lecture time, etc.) because it is used in the lecture time of one subject with the record checked once. In order to solve these problems, the various mobile attendance systems proposed to solve these problems are also unable to fundamentally solve problems such as interim attendance and proxy attendance because they check attendance using only the application of a smartphone. In this paper, we use geofencing technology, which is a positioning-based technology that detects the entry and exit of people, objects, etc. in areas separated by virtual boundaries. The proposed system solves the problem of intermediate attendance and alternate attendance by setting the student to automatically record the access record when entering and leaving the classroom set as a geofence with a smartphone. In addition, it also provides a function to prevent unintentional mistakes that occur through the smartphone by limiting some of the functions of the smartphone such as silence, vibration, and Internet use when entering the classroom.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.4
• /
• pp.133-142
• /
• 2021

With the recent advancements of deep learning, companies such as smart home, healthcare, and intelligent transportation systems are utilizing its functionality to provide high-quality services for vehicle detection, emergency situation detection, and controlling energy consumption. To provide reliable services in such sensitive systems, deep learning models are required to have high accuracy. In order to develop a deep learning model for analyzing previously mentioned services, developers should utilize the state of the art deep learning models that have already been verified for higher accuracy. The developers can verify the accuracy of the referenced model by validating the model on the dataset. For this validation, the developer needs structural information to document and apply deep learning models, including metadata such as learning dataset, network architecture, and development environments. In this paper, we propose a description language that represents the network architecture of the deep learning model along with its metadata that are necessary to develop a deep learning model. Through the proposed description language, developers can easily verify the accuracy of the referenced deep learning model. Our experiments demonstrate the application scenario of a deep learning description document that focuses on the license plate recognition for the detection of illegally parked vehicles.

• Journal of the Korea Convergence Society
• /
• v.13 no.3
• /
• pp.67-75
• /
• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.

• Journal of Christian Education in Korea
• /
• v.71
• /
• pp.241-276
• /
• 2022

Due to the 4th industrial revolution, which started with the Smart Revolution in the early 21st century, Hyper-Connectivity, Hyper-Convergence and Hyper-Intelligence of our society is accelerating. These changes induced formation of Metaverse as a fused new space that crosses the perimeter of the physical space and virtual(digital) spaces beyond time and place. The characteristics of Metaverse are continuously spread by engaging with the characteristics of the MZ generation, which collects both Millennial generation (M Generation) and Z Generation. With outburst of Covid-19 pandemic, a variety of attempts have been made to utilize Metaverse, even in church education when it was impossible to worship directly. In other words, the usefulness of the Metaverse was confirmed as a new community space of the education of the church. In addition, Metaverse may provide a substantial, experiential and evolving space for church education. However, in order for church education to further develop, the development in the method of education is also required to move beyond mere concept of space. In particular, when the learner-centered education method, one of the common characteristics of the Metaverse and MZ generation, it is thought that the church education in the Metaverse era will be able to go in a more evolving direction.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.571-585
• /
• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.537-542
• /
• 2021

This paper improves the possibility of recognizing fast-moving objects through the YOLO (You Only Look Once) deep learning recognition model in an application environment for object recognition in images. The purpose was to study the method of collecting semantic data through processing. In the recognition model, the moving object recognition error was identified as unrecognized because of the difference between the frame rate of the camera and the moving speed of the object and a misrecognition due to the existence of a similar object in an environment adjacent to the object. To minimize the recognition errors by compensating for errors, such as unrecognized and misrecognized objects through the proposed data collection method, and applying vision processing technology for the causes of errors that may occur in images acquired for sports (tennis games) that can represent real similar environments. The effectiveness of effective secondary data collection was improved by research on methods and processing structures. Therefore, by applying the data collection method proposed in this study, ordinary people can collect and manage data to improve their health and athletic performance in the sports and health industry through the simple shooting of a smart-phone camera.

• Korean small business review
• /
• v.42 no.1
• /
• pp.43-56
• /
• 2020

The technology conflict between the U.S. and China is deepening recently. The U.S.-China battle began as a national security issue but is comprehending as a U.S.'s check for China's rapid technological advancement. China is rapidly growing in several indexes including R&D expenditure, patent application, and publications, and is challenging the U.S. in 5G and Artificial Intelligence. In 2018, Huawei became the largest 5G network/equipment provider and second largest smart phone manufacturer in the world. Now, Huawei is outperforming at AI chipset manufacturing, Bigdata analysis and cloud, positioning to become a critical player in the 4th industrial revolution. The purpose of this research is to analyze the effect of recent Huawei issues to Korean SMEs focusing on the relation between Huawei and Korean companies; the cooperation status from the Global Value Chain (GVC) perpsective, and Korean government's policies related to Huawei's information security issues will be the three main frames for the analysis. Then, this research proposes policy implications such as increasing Korea's competitiveness in manufacturing and information security.

• Journal of the Korea Convergence Society
• /
• v.13 no.2
• /
• pp.151-166
• /
• 2022

Museum is the carrier and symbol of history and cultural accumulation, and the museum cultural relics are clues with the spirit of history. Moreover, the museum cultural and creative products are portable history. Museum has changed form the traditional "object-basic" model to the modern "people-basic" model, which pays more attention to its living inheritance. Therefor, the museum cultural and creative products is also the way of expression of its living inheritance. This paper analyzes the opportunities and difficulties of cultural and creative products of Chinese museums by means of network survey, field survey and expert interview. In order to improve the design method of cultural and creative products. By exploring the cultural connotation, broadening the functional factors, innovating the design factors and creating the empathy factor between products and people to explore and the verify. Trying to make up the imperfect design methods of cultural and creative products in small and medium-sized museums which leads to the lack of function, innovation and communication of cultural and creative products. We try to attract more people's attention, spread traditional culture and realize the resonance between people and objects.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.7
• /
• pp.1231-1237
• /
• 2022

In the present study, the optimization of the main particulars of a ship using AI-based design search techniques was investigated. For the design search techniques, the SHERPA algorithm by HEEDS was applied, and CFD analysis using STAR-CCM+ was applied for the calculation of resistance performance. Main particulars were automatically transformed by modifying the main particulars of the ship at the stage of preprocessing using JAVA script and Python. Small catamaran was chosen for the present study, and the main dimensions of the length, breadth, draft of demi-hull, and distance between demi-hulls were considered as design variables. Total resistance was considered as an objective function, and the range of displaced volume considering the arrangement of the outfitting system was chosen as the constraint. As a result, the changes in the individual design variables were within ±5%, and the total resistance of the optimized hull form was decreased by 11% compared with that of the existing hull form. Throughout the present study, the resistance performance of small catamaran could be improved by the optimization of the main dimensions without direct modification of the hull shape. In addition, the application of optimization using design search techniques is expected for the improvement in the resistance performance of a ship.