• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.161-168
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• 2021

In this paper, it is a system that informs people who take medication periodically to facilitate the convenience of the elderly and the disabled. It is a system that measures the full weight of pills that need to be taken for a week using a weight sensor, and then determines whether or not the pills are taken by measuring the weight of the reduced pills again when the user takes them. For people with disabilities who are unable to move, it includes the function of automatically transporting medicine to the user-set location at the time of use using a line tracer based autonomous vehicle. It is also configured to inform users who have not taken the pill through an alarm that includes visual and auditory functions at a specific time to inform them of this. This work attempts to help users take their medication without forgetting by segmenting the task performance process of such a system through simulations.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.73-83
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• 2019

In this paper, we propose the augmented reality(AR) based driving navigation based on robust lane detection method to dynamic environment changes. The proposed technique uses the detected lane position as a marker which is a key element for enhancing driving information. We propose Symmetrical Local Threshold(SLT) algorithm which is able to robustly detect lane to dynamic illumination environment change such as shadows. In addition, by using Morphology operation and Connected Component Analysis(CCA) algorithm, it is possible to minimize noises in the image, and Region Of Interest(ROI) is defined through region division using a straight line passing through several vanishing points We also propose the augmented reality aided visualization method for Interchange(IC) and driving navigation using reference point detection based on the detected lane coordinates inside and outside the ROI. Validation experiments were carried out to assess the accuracy and robustness of the proposed system in vairous environment changes. The average accuracy of the proposed system in daytime, nighttime, rainy day, and cloudy day is 79.3% on 4600 images. The results of the proposed system for AR based IC and driving navigation were also presented. We are hopeful that the proposed research will open a new discussion on AR based driving navigation platforms, and thus, that such efforts will enrich the autonomous vehicle services in the near future.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.168-172
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• 2018

HACCP is scientific Sanitary control system to ensure food safety with autonomous, systematic and effective way by analysing hazard element that can be occurred in each steps until an end consumer takes food including raw material status, manufacturing, processing, storing, distributing, cooking and specifying the critical control point. In this paper, the temperature and humidity are measured during the transport of food, the stage of its distribution, to ensure systematic and effective management of HACCP, and we designed a monitoring terminal that uses this information to send it to servers periodically and a firmware that implements it. We have confirmed that the data transmitted by the terminal, including the information measured in sub-net, was well stored on the server and the response from the server is well received by the terminal. It is expected to be used for the management of food history, data tracking and statistical data in the future. This system is also considered to be an applicable system for group cafeteria such as schools or workplaces and logistics warehouses for raw materials or food storage and so on.

• Journal of Drive and Control
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• v.17 no.4
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• pp.23-30
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• 2020

Driving on irregular and inclined roads using agricultural machinery such as spraying machines or trucks in orchards causes farmer casualties associated with the overturning of agricultural machinery. In addition, the harm to agricultural workers caused by the excessive inhalation of the scattered pesticide frequently occurs during pest control processes. To address these problems, we introduced precision agricultural technology that could selectively spray pesticides only where the fruit is present by recognizing the presence or shape of the fruit in the orchard. In this paper, a 16-channel LIDAR (VLP-16) made of Velodyne was used to identify the shape of fruit trees. Solenoid valves were attached to the end parts of 12 nozzles of the orchard spraying machine for on/off control. The smart spraying machine implemented in this way was mounted on a vehicle capable of autonomous travel and performed selective control depending upon the shape of the fruit trees while traveling in the orchards. This is expected to significantly reduce the amounts of pesticides used in orchards and production costs.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.479-487
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• 2022

This paper presents the control and guidance algorithm of a KAU-SPUAV(Korea Aerospace University - Solar Powered Unmanned Aerial Vehicle) which is designed and developed in Korea Aerospace University. Aerodynamic coefficients are calculated using the vortex-lattice method and applied to the aircraft's six degrees of freedom equation. In addition, the thrust and torque coefficients of the propeller are calculated using the blade element theory. An altitude controller using thrust was used for longitudinal control of KAU-SPUAV to glide efficiently when it comes across the upwind. Also describes wind estimation technic for considering wind effect during flight. Finally, introduce some guidance laws for endurance, mission and coping with strong headwinds and autonomous landing.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.1
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• pp.1-8
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• 2022

To understand physical phenomena of ship maneuvering deeply, a numerical study based on computational fluid dynamics is required. A computational method that can simulate the interaction between the ship hull, propeller, and rudder will provide informative local flows during ship maneuvering tests. The analysis of local flows can be applied to improve a physical model of ship maneuvering that has been widely used in maneuvering simulations. In this study, the numerical program named as WAVIS that has been developed for ship resistance and propulsion problems is extended to simulate ship maneuvering by free-running tests. The six degree-of-freedom of ship motion is implemented based on Euler angles and the overset technique is applied to treat the moving grid of ship hull and rudder. The propulsion force due to a propeller is calculated by a panel method that is based on the lifting-surface theory. The newly extended code is applied to simulate turning and zig-zag tests of KCS and the comparison with the available experimental data has been made.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.301-313
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• 2021

The automotive industry is facing a paradigm shift, changing from owning to sharing and from manufacturing to service. However, it is hard to conclude that the economic value of smart mobility service is always positive to users. Cost related to owing or share a vehicle is very hard to estimate from the perspective of potential users as well as the benefit of the service. Focusing on the cost side of the story, this study develops a cost estimating model based on three main factors: electrification, advanced driving assistant systems (ADAS) function, and participation of ride-sharing service. As a result of the model analysis, low cost was estimated as a result when receiving cost benefits such as electrification and ride-sharing participation. Various factors were analyzed through sensitivity analysis also. These results can provide useful insights into the cost prediction and strategies for potential users and manufacturers on smart mobility service market.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.252-261
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• 2022

The present study concerns assessing the operability of a surface combatant, based on the Percent-Time-Operable (PTO). For validation of the seakeeping analysis in the regular waves, the model test is first conducted in a towing tank. The seakeeping analysis results in the regular waves are expanded to the irregular waves, considering the wave spectra around the Korean peninsula and in North Pacific. The seakeeping criteria of the surface combatant in transit, combat, replenishment operation, and survival condition are defined by the literature review. An annual operation scenario of the surface combatant in two operation areas, i.e., advance speed and wave direction, are combined with the seakeeping analysis results to assess PTO. The main constraints of operability of the surface combatant are identified as the pitch angle and vertical velocity at the helicopter deck.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.259-266
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• 2022

In this study, we developed a deep learning and vision sensor-based assembly performance evaluation method isfor prefabricated steel structures. The assembly parts were segmented using a modified version of the receptive field block convolution module inspired by the eccentric function of the human visual system. The quality of the assembly was evaluated by detecting the bolt holes in the segmented assembly part and calculating the bolt hole positions. To validate the performance of the evaluation, models of standard and defective assembly parts were produced using a 3D printer. The assembly part segmentation network was trained based on the 3D model images captured from a vision sensor. The sbolt hole positions in the segmented assembly image were calculated using image processing techniques, and the assembly performance evaluation using the k-nearest neighbor algorithm was verified. The experimental results show that the assembly parts were segmented with high precision, and the assembly performance based on the positions of the bolt holes in the detected assembly part was evaluated with a classification error of less than 5%.