• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.93-98
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• 2023

In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.101-111
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• 2023

This study conducted systematic review and meta-analysis to analyze the effectiveness of a dual-task for cognitive function in patients with MCI in Korea. A search was conducted using eight databases, and the search terms were MCI, cognition, and dual task. This study includes RCT and nonRCT published from January 2013 to July 2023. A total of 682 studies were searched, and 8 studies that fulfilled the inclusion and exclusion criteria were finally analyzed. Methodological quality was assessed with the RoB, RoBANS. The meta-analysis used CMA 4.0 ver. As a result of the analysis, the overall effect size of the dual task was medium effect size. The effect size according to the outcome variables was large for orientation and executive function, and medium effect size for global cognitive function, visuospatial function, memory, and attention. As a result of analysis according to the intervention period, the effect was greater when applied for 4 to 8 weeks, and the effect size was larger when applied for 24 to 30 sessions. This study presented clinical evidence on the effectiveness and application method of a dual-task applied to improve cognitive function in patients with MCI.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.32-41
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• 2024

In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.215-224
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• 2024

The purpose of this study was to examine research trends related to neonatal simulation practice education of domestic nursing students. It was a descriptive research study. For literature collection, a total of 17 journals were selected as a result of a search using ('Newborn Simulation') AND ('Nursing Student' OR 'Nursing College Student' OR 'Student Nurse') in 6 domestic electronic databases. The research results showed that it started with 7 journals from 2011 to 2015 and decreased slightly to 5 journals from 2016 to 2020 and 5 journals from 2021 to 2023. The research design was mostly quantitative with a total of 16 journals(94%). Among them, there were 15 intervention journals(88%), 1 descriptive research journals(6%), and 1 mixed method journals(6%). The key topics in simulation practice were high-risk newborns with 9 journals(52%), respiratory distress syndrome in neonatal intensive care units appeared with 3 journals(18%), neonatal care with 3 journals(18%), normal newborn care with 1 journal(6%), and neonatal emergency airway care with 1 journals(6%). The main outcome variables were clinical performance, accounting for 5 journals(19.2%), followed by practice satisfaction 3 journals(11.5%). clinical competency and practice satisfaction were found to have significant positive effects. In conclusion, various research methods are required, such as expansion of nursing students' neonatal simulation practice education, repeated research, and qualitative research.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Tunnel and Underground Space
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• v.34 no.4
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• pp.312-329
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• 2024

In various underground research projects such as energy storage and development and radioactive waste disposal targeting deep underground, the characteristics of permeable rock fractures that serve as major pathway of groundwater flow in deep rock aquifer are considered as an important evaluation factor in the design, construction, and operation of research facilities. In Korea, there is little research and database on the location and hydraulic characteristics of permeable rock fractures and the pattern of groundwater flow patterns that may occur between fractures in deep rock boreholes. In this paper, the hydraulic characteristics of permeable rock fractures in deep rock aquifer were evaluated through the analysis of geothermal gradient and pumping test data. First, the deep geothermal distribution was identified through temperature logging, and the geothermal gradient was obtained through linear regression analysis using temperature data by depth. In addition, the hydraulic characteristics of the fractured rock were analyzed using outflow temperature obtained from pumping tests. Ultimately, the potential location and hydraulic characteristics of permeable rock fractures, as well as groundwater flow within the boreholes, were evaluated by integrating and analyzing the geophysical logging and hydraulic testing data. The process and results of the evaluation of deep permeable rock fractures proposed in this study are expected to serve as foundational data for the successful implementation of underground research projects targeting deep rock aquifers.

• Journal of Nutrition and Health
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• v.43 no.2
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• pp.197-206
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• 2010

Now a days, people eat outside of the home more and more frequently. Menu labeling can help people make more informed decisions about the foods they eat and help them maintain a healthy diet. This study was conducted to develop menu labeling system using Nutri-API (Nutrition Analysis Application Programming Interface). This system offers convenient user interface and menu labeling information with printout format. This system provide useful functions such as new food/menu nutrients information, retrieval food semantic service, menu plan with subgroup and nutrient analysis informations and print format. This system provide nutritive values with nutrient information and ratio of 3 major energy nutrients. MLS system can analyze nutrients for menu and each subgroup. And MLS system can display nutrient comparisons with DRIs and % Daily Nutrient Values. And also this system provide 6 different menu labeling formate with nutrient information. Therefore it can be used by not only usual people but also dietitians and restaurant managers who take charge of making a menu and experts in the field of food and nutrition. It is expected that Menu Labeling System (MLS) can be useful of menu planning and nutrition education, nutrition counseling and expert meal management.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.469-478
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• 2003

Internet information search engines using web robots visit servers conneted to the Internet periodically or non-periodically. They extract and classify data collected according to their own method and construct their database, which are the basis of web information search engines. There procedure are repeated very frequently on the Web. Many search engine sites operate this processing strategically to become popular interneet portal sites which provede users ways how to information on the web. Web search engine contacts to thousands of thousands web servers and maintains its existed databases and navigates to get data about newly connected web servers. But these jobs are decided and conducted by search engines. They run web robots to collect data from web servers without knowledge on the states of web servers. Each search engine issues lots of requests and receives responses from web servers. This is one cause to increase internet traffic on the web. If each web server notify web robots about summary on its public documents and then each web robot runs collecting operations using this summary to the corresponding documents on the web servers, the unnecessary internet traffic is eliminated and also the accuracy of data on search engines will become higher. And the processing overhead concerned with web related jobs on web servers and search engines will become lower. In this paper, a monitoring system on the web server is designed and implemented, which monitors states of documents on the web server and summarizes changes of modified documents and sends the summary information to web robots which want to get documents from the web server. And an efficient web robot on the web search engine is also designed and implemented, which uses the notified summary and gets corresponding documents from the web servers and extracts index and updates its databases.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.595-602
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• 2013

WiFi fingerprinting is well known as an effective localization technique used for indoor environments. However, this technique requires a large amount of pre-built fingerprint maps over the entire space. Moreover, due to environmental changes, these maps have to be newly built or updated periodically by experts. As a way to avoid this problem, crowd-sourced fingerprint mapping attracts many interests from researchers. This approach supports many volunteer users to share their WiFi fingerprints collected at a specific environment. Therefore, crowd-sourced fingerprinting can automatically update fingerprint maps up-to-date. In most previous systems, however, individual users were asked to enter their positions manually to build their local fingerprint maps. Moreover, the systems do not have any principled mechanism to keep fingerprint maps clean by detecting and filtering out erroneous fingerprints collected from multiple users. In this paper, we present the design of a crowd-sourced fingerprint mapping and localization(CMAL) system. The proposed system can not only automatically build and/or update WiFi fingerprint maps from fingerprint collections provided by multiple smartphone users, but also simultaneously track their positions using the up-to-date maps. The CMAL system consists of multiple clients to work on individual smartphones to collect fingerprints and a central server to maintain a database of fingerprint maps. Each client contains a particle filter-based WiFi SLAM engine, tracking the smartphone user's position and building each local fingerprint map. The server of our system adopts a Gaussian interpolation-based error filtering algorithm to maintain the integrity of fingerprint maps. Through various experiments, we show the high performance of our system.

• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.