• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1669-1683
• /
• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.10
• /
• pp.55-61
• /
• 2009

This paper describes a point of production(POP) system which collects and manages real-time shop floor machining information in a wafer dicing process. The system are composed of POP terminal, line controller and network. In the configuration of the system, LAN and RS485 network are used for connection with the upper management system and down stratum respectively. As a bridge between POP terminal and server, a line controller is used. The real-time information which is the base of production management are collected from information resources such as machine, product and worker. The collected information are used for the calculation of optimal cutting condition. The collection of the information includes cutting speed, spout of pure water, accumulated count of cut in process for blade and wafer defect. In order to manage machining information in wafer dicing process, production planning information is delivered to the shop floor, and production result information is collected from the shop floor, delivered to the server and used for managing production plan. From the result of the system application, production progress status, work and non-working hour analysis for each machine, and wafer defect analysis are available, and they are used for quality and productivity improvements in wafer dicing process. A case study is implemented to evaluate the performance of the system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.100-103
• /
• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.693-700
• /
• 2024

As of the end of March 2022, the total area of domestic industrial complexes is 606 km2, which is only about 0.6% of the total land area. However, as of 2018, the annual energy consumption of domestic industrial complexes is 110,866.1 thousand TOE, accounting for 53.5% of the country's total energy consumption and 83.1% of the entire industrial sector energy consumption. In addition, industrial complexes have a significant impact on the environment, accounting for 45.1% of the country's total greenhouse gas emissions and 76.8% of industrial sector greenhouse gas emissions. Under this background, in this study, in order to contribute to the energy efficiency of industrial complexes, a prediction study on energy demand and supply for an industrial complex in Korea using machine learning was conducted. In addition, a simulator UI screen was designed to more efficiently convey information on energy demand/supply prediction results and energy consumption status. Among the machine learning algorithms, Multi-Layer Perceptron (MLP) was used, and Bayesian Optimization was applied as an optimization technique for the prediction model. The energy prediction model for the industrial complex built in this study showed a prediction accuracy of 87.90% for compressed air demand and 99.54% for the flow rate available for the public air compressor.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.5
• /
• pp.1-9
• /
• 2024

Recently, the TBM tunnel construction method has been in the spotlight as tunnel excavation under urban areas such as the Metropolitan Rapid Transit (GTX) has been actively carried out. Although the construction cost of the TBM tunnel is high, it is relatively free from noise and vibration compared to the NATM tunnel method, so it is well known to be a suitable construction method for application to the lower part of urban areas. In particular, when the stratum passes through the shallow section, it can have a great impact on existing upper structures and obstacles, so accurate numerical analysis considering various variables is required when designing the TBM tunnel. Unlike other tunnel construction methods, TBM tunnels build linings by assembling factory-made segments. Unlike NATM tunnels, segment lining has connections between segments, so how to the connection status between segments is reflected can have a significant impact on securing the reliability of analysis results. Therefore, in this paper, a segment joint model(Janssen Model) was applied to the lining for seismic analysis of the TBM tunnel, and the tunnel's behavioral characteristics were analyzed after numerical analysis using nonlinear models according to urban railway seismic design standards.

• The Journal of the Korea Contents Association
• /
• v.20 no.10
• /
• pp.688-701
• /
• 2020

In this study, a total of 68 domestic and international papers were selected from 1993 to August 2020 in order to examine the research trends related to artificial intelligence for the visually impaired. The papers were compared and analyzed by the number of papers published by year, research method, research topic, keyword analysis status, research type, and implementation method. As a result of the study, the number of papers during the study period seemed to increase steadily. But in the case of domestic research, It can be seen that it has become active since 2016. As for research methods, development research accounted for 89.7% of both domestic and foreign research. Keywords was in Visually Impaired, Deep Learning, and Assistive Device order in domestic research. And it was in Visually Impaired, Deep learning, Artificial intelligence order in foreign research. There was a difference in the frequency of words. Research type were Design, development and implementation both in domestic and foreign. Implementation method were in System 13.2%, Solution 7.4%, App. 4.4% order in domestic research, and it was in System 32.4%, App. 13.2%, Device 7.4% order in foreign research. As for the applied technology of the implementation method, were in YOLO 2.7%, TTS 2.1%, Tensorflow 2.1% order in domestic research, and it was used in CNN 8.0%, TTS 5.3%, MS-COCO 4.3% order in foreign research. The purpose of this study was to compare and analyze the trends of artificial intelligence-related research targeting the visually impaired, to immediately know the current status of domestic and foreign research, and to present the direction of artificial intelligence research for the visually impaired in the future.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.1
• /
• pp.41.1-41.1
• /
• 2018

We introduce a current status and future plans of Korea Microlensing Telescope Network (KMTNet) microlensing experiments, which include an observational strategy, pipeline, event-finder, and collaborations with Spitzer. The KMTNet experiments were initiated in 2015. From 2016, KMTNet observes 27 fields including 6 main fields and 21 subfields. In 2017, we have finished the DIA photometry for all 2016 and 2017 data. Thus, it is possible to do a real-time DIA photometry from 2018. The DIA photometric data is used for finding events from the KMTNet event-finder. The KMTNet event-finder has been improved relative to the previous version, which already found 857 events in 4 main fields of 2015. We have applied the improved version to all 2016 data. As a result, we find that 2597 events are found, and out of them, 265 are found in KMTNet-K2C9 overlapping fields. For increasing the detection efficiency of event-finder, we are working on filtering false events out by machine-learning method. In 2018, we plan to measure event detection efficiency of KMTNet by injecting fake events into the pipeline near the image level. Thanks to high-cadence observations, KMTNet found fruitful interesting events including exoplanets and brown dwarfs, which were not found by other groups. Masses of such exoplanets and brown dwarfs are measured from collaborations with Spitzer and other groups. Especially, KMTNet has been closely cooperating with Spitzer from 2015. Thus, KMTNet observes Spitzer fields. As a result, we could measure the microlens parallaxes for many events. Also, the automated KMTNet PySIS pipeline was developed before the 2017 Spitzer season and it played a very important role in selecting the Spitzer target. For the 2018 Spitzer season, we will improve the PySIS pipeline to obtain better photometric results.

• Proceedings of the Korean Society of Organic Agriculture Conference
• /
• 2009.12a
• /
• pp.45-56
• /
• 2009

Current status on the occurrence and the management of the major disease, insect and mite pests were investigated in the organic or non-chemical pest control orchards from 2005 to 2009. Numbers of certified organic or non-chemical apple orchards were increased from 14 in 2005 to 78 in 2008. Severe damages on leaves and fruits occurred by the several diseases such as marssonina blotch, bitter rot, white rot, sooty blotch and flyspeck, and the several insect pests such as apple leaf-curling aphid, woolly apple aphid, oriental fruit moth and peach fruit moth on the almost certified organic or non-chemical pest control orchards. About 10 and 18 environmental-friendly materials were used to control diseases and insect or mite pests respectively. But, lime sulfur and bordeaux mixture to diseases and machine oil, plant oil mixed with egg yolk, and pheromone mating disruptions to insect pests were effective to control under the adequate conditions. At present, it is extremely difficult to produce organic apples in Korea. Growers must consider about and solve so many conditions on the cultivar, weather, local site, marketing and so on, before when they decide to change from conventional or IPM(Integrated Pest Management) to organic or non-chemical pest control orchards.

• Korean Journal of Organic Agriculture
• /
• v.18 no.2
• /
• pp.221-232
• /
• 2010

During 2005~2009, current status on the occurrence and the management of the major disease, insect and mite pests were investigated in the non-chemical or organic cultured apple orchards in Korea. Numbers of certified organic or non-chemical apple orchards increased from 14 in 2005 to 78 in 2008. Severe damages on leaves and fruits were caused by the several diseases such as marssonina blotch, bitter rot, white rot, sooty blotch and flyspeck, and the several insect pests such as apple leaf-curling aphid, woolly apple aphid, oriental fruit moth and peach fruit moth on the almost certified organic or non-chemical pest control orchards. About 10 and 18 environmental-friendly materials were used to control diseases and insect or mite pests, respectively. But, lime sulfur and bordeaux mixture to diseases and machine oil, plant oil mixed with egg yolk, and pheromone mating disruptions to insect pests were effective under the adequate conditions.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.18 no.1
• /
• pp.101-112
• /
• 2016

Monitoring and control of the greenhouse environment play a decisive role in greenhouse crop production processes. The network system for greenhouse control was developed by using recent technologies of networking and wireless communications. In this paper, a remote monitoring and control system for greenhouse using a smartphone and a computer with internet has been developed. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on sensors and equipments network. Graphical user interface for an integrated management system was designed with bases on the HMI and the experimental results showed that a sensor data and device status were collected by integrated management in real-time. Because the sensor data and device status can be displayed on a web page, transmitted using the server program to remote computer and mobile smartphone at the same time. The monitored-data can be downloaded, analyzed and saved from server program in real-time via mobile phone or internet at a remote place. Performance test results of the greenhouse control system has confirmed that all work successfully in accordance with the operating conditions. And data collections and display conditions, event actions, crops and equipments monitoring showed reliable results.