• Journal of Platform Technology
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• v.10 no.4
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• pp.56-61
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• 2022

Various convergence technologies discovered through the 4th industrial revolution are permeating the industry. Drones are being used in industries such as construction, transportation, and national defense based on convergence technology. Quart-copter drone control is being used in a wide range of fields from the visual field of operation with the naked eye to the remote field of view using GCS. If we classify those who operate industrial drones, there are general pilots who directly use drones, instructors who train drone pilots, and mechanics who check the status of drones and use them for a long time. Depending on the shape of the screen of the drone GCS, a user's quick response or key data can be acquired. Accordingly, in this study, GUI characteristics were analyzed for the mission planner GCS and a screen composition method according to the user was proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.287-288
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• 2021

There is a growing interest in plant factories around the world, and in recent years, research on an automated management system that can grow crops even in an urban environment is in progress. The development of this management system is based on the development of ICT (Information Communications Technology) technology, and research is being conducted focusing on facilities, light sources, temperature, humidity and automation to increase the productivity of plants. Research on standardization is ongoing. In this paper, by constructing a test bed that can grow hydroponic ginseng in a container environment, we propose a model that can monitor and manage the environment for the growth process on mobile.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.870-877
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• 2020

A suction bucket foundation, especially useful at depths of more than 20m, is a method of construction. The method first places an empty upturned bucket at the target site. Then, the bucket is installed by sucking water or air into it to create negative pressure. For stability, it is crucial to secure the verticality of the bucket. However, inclination by the bucket may occur due to sea-bottom conditions. In general, a repeated intrusion-pulling method is used for securing verticality. However, it takes a long time to complete the job. In this paper, we propose a real-time suction bucket verticality monitoring system. Specifically, the system consists of a sensor unit that collects raw verticality data, a controller that processes the data and wirelessly transmits the information, and a display unit that shows verticality information of a circular steel pipe. The system is implemented using an inclination sensor and an embedded controller. Experimental results show that the proposed system can efficiently measure roll/pitch information with a 0.028% margin of error. Furthermore, we show that the system properly operates in a suction bucket-based model experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.401-408
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• 2017

Recently, the environment at littoral sea has been contaminated and damaged by submarine deposits, e.g. the fishing nets. To solve this problem, the government pushes the policies such as management plan of the fishing nets in whole life cycle of them. The representative causes are dumping and drifting away of the fishing nets, and shed new light on technological methods for tracking and management of the fishing nets. To prevent this drawbacks, this paper covers a development of tracking and management system for the fishing nets. To do this, we analyzed the existing products, and figured out performance improvement points. Also we proposed additional enhancement techniques which connects with a smartphone application and displays the positions and state information of the fishing nets, and so on. To adopt the proposed methods, we design and implement a tracking and management system based on ENC with the smartphone application, and verified the usefulness of the system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.59-71
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• 2019

In the rapidly changing industrial environment, the continuous increase in demand for entrepreneurship emphasizes the effective support of the government for the survival and growth of entrepreneurs and the necessity of establishing systematic initiative promotion policies. To this end, Of the total number of enterprises. The purpose of this study is to establish a new classification system for entrepreneurial industry that reflects the trend of entrepreneurship based on convergence technology that emerged during the 4th Industrial Revolution era in order to establish a systematic initiative upbringing policy. In this paper, we propose a new classification system for entrepreneurial ecosystem by using Delphi technique. As a result of the study, the categories of entrepreneurial industry are classified into technology entrepreneurship and general entrepreneurship. Technology entrepreneurship is divided into ICT services, ICT manufacturing, general manufacturing, cultural contents and biotechnology. The results of this study suggest a meaningful implication in the establishment of effective policies to support entrepreneurship in the future by establishing new standards of industry classification system of entrepreneurs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3183-3191
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• 2014

It is essential to effectively manage facilities because operating and maintenance cost for them accounts for more than 83% of lifecycle cost. This study developed BIM Object-based classification list to manage information required to operating and maintenance phase of them from design and construction phase. In order to develop this classification list, Construction Information Classification System, Design Criteria for Architectural Electrical Installations, commodity list classification of PPS(Public Procurement Service) were analyzed. and problems for consisting of object classification list were drawn. And each materials is classified that drawings discipline code (KSF 1540:2010 (Principle and criteria for CAD Drawing) was classified as level 1 to cover main areas and construction information classification system was classified as level 2 to cover elements also UNSPSC was classified as level 3 to cover objects for devices and equipments. this classification criteria was given code. This study is expected to be useful to exchange and share information in operating and maintenance phase by offering object point of view classification in design and construction phase. besides, it is looking forward to effective operating and maintenance of facilities by enabling management of devices and equipments by function, space, use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.805-807
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• 2016

By using ICT in the manufacturing industry with the advent of "Industry 4.0" of Germany, it has been promoted a lot of research to maximize the production capacity. Be particularly increased manufacturing complexity, increase the information delivered to the operator, augmented reality technologies in order to maximize production have been studied. In this paper, in order to solve the deficiencies problem that frequently occurs in the actual site, using the augmented reality technology, provides a system for providing personal training information to the worker. Proposed system, by fusing worker information and process another job, generates educational information of the individual, it is to provide information through the video of the tablet. When using such methods, it is expected that it is possible to improve the production quality of the manufacturing industry to overcome the deficiencies problem that frequently occurs through the continuing education of employees.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.165-170
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• 2022

By reducing time spent outside, a shopping system was developed for middle-aged and elderly people who mainly use neighborhood marts and neighborhood mart managers. The main functions of this app are direct shopping and online shopping, and it was developed using QR code using Zxing library on Android and Kakao Map using Kakao API. In addition, it provides information such as payment statistics and bulletin board posts that members need through recycler view and graphs in an easy-to-read manner. Through this system, members can efficiently manage by reducing fatigue when using the mart through direct purchase using QR code and delivery through map, and reducing manpower wastage as a mart manager. Also, as a mart manager, more consumers will be able to sell more items.

• Journal of IKEEE
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• v.26 no.1
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• pp.10-18
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• 2022

Accurate SOC estimation is an important indicator of battery operation strategies, and many studies have been conducted. The simulation method which was mainly used in previous studies, is difficult to conduct real-time SOC estimation like real BMS environment. Therefore, this paper aims to implement a real-time battery SOC estimation embedded system and analyze problems that can arise during the verification process. In environment consisting of two Raspberry Pi boards, SOC estimation with the EKF uses data measured by the Simscape battery model. Considering that the operating characteristics of the battery vary depend on the temperature, the results were analyzed at various ambient temperatures. It was confirmed that accurate SOC estimation was performed even when offset fault and packet loss occurred due to communication or sensing problems. This paper proposes a guide for embedded system strategies that enable real-time SOC estimation with errors within 5%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.