• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.1
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• pp.46-54
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• 2012

One major safety issue of surface operations is the occurrence of runway incursions. Runway incursions are the consequence of multiple operational and/or environmental factors. Human error is known to contribute to almost every runway incursion. One major contributing factor for runway incursion is crew's lack of situational awareness during airport surface operations, induced by weather considerations, by complex airport factors or by crew technique itself; it is also caused by ATC issues. Various airport factors may affect pilot situational awareness, distract the crew, or lead to crew confusion. The recommendations to avoid runway incursions are manifold; Proper Crew's CRM/TEM skills, adequate communication technique, proper knowledge of airport surface markings, lights and signs and preparation of preparation of expected taxi out/in routing. Also runway incursion risk assessment on specific airport before flight may lead to aware of risk level and contribute to prevent runway incursion.

• Journal of Ocean Engineering and Technology
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• v.37 no.1
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• pp.38-48
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• 2023

To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.69-80
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• 2024

Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.629-636
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• 2013

Nowadays, many interface devices or training systems have been developed with recent developments in IT technology but only a few training systems for developmentally disabled people have been introduced. In this paper, we present a real-time, interactional and situational training system based on augmented reality in order to improve cognitive capability and adaptive ability in the daily life of developmentally disabled people. Our system is specifically based on serving food in restaurants. This augmented reality based system provides them to experience various different situations safely and take the training session as much as they want under any circumstances. When they use our system, they are able to look around with Head Mounted Display(HMD) and take training sessions easily based on various situational scenarios. After experimenting on our system for 3 months, we found they had no aversion about wearing HMD and learned quicker as they practiced over and over and improved their cognitive capability and adaptive ability. We also got a positive feedback that it had an excellent educational value from teachers in special-education-school.

• Journal of Agricultural Extension & Community Development
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• v.8 no.2
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• pp.235-244
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• 2001

The objectives of this study were to inquire the theories associated with YLD (Youth Leadership Development), and to draw implications for improving youth leadership abilities, The results of the inquiry revealed the theories associated with YLD as follows; 1. All youth have leadership potential and abilities, but there were few programs to improve it. 2. Activity-Observation-Reflection model of Hughes, Ginnett & Curphy(1993) and Awareness-Interaction-Mastery model of Linden & Fertman(1998) were the best effective YLD models. 3. Situational contingency approach was very appropriate theory associated with YLD. 4. The learning of leadership skills had occurred within an educational context known as experiential learning, so it was the best method of YLD.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.216-224
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• 2023

Guide robots that provide services in public places have recently emerged as a non-face-to-face solution with the spread of COVID-19 and are growing. However, most guide robots provide only the same level of intelligence and the same interaction in different and changing environments. Therefore, its usefulness is limited and customers' interest is quickly lost. To solve this problem, it is necessary to develop social intelligence that can improve the robot's environment and situational awareness performance, and to continuously maintain customer interest by providing personalized and situational services. In this study, we developed guide robot services based on social HRI components that provides multi-modal context-aware. We evaluated service usefulness by measuring user satisfaction and frequency of use of the service through the survey. We analyzed the service quality attributes to identify the differentiating factors of guide robot based on social HRI components.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.23-32
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• 2021

The high-level Space Situational Awareness (SSA) objective is to provide to the users dependable, accurate and timely information in order to support risk management on orbit and during re-entry and support safe and secure operation of space assets and related services. Therefore the risk assessment for the re-entry of space objects should be managed nationally. In this research, the Software for Re-Entry Prediction of space objects (SREP) was developed for national SSA system. In particular, the rate of change of the drag coefficient is estimated through a newly proposed Drag Scale Factor Estimation (DSFE), and is used for high-precision orbit propagator (HPOP) up to an altitude of 100 km to predict the re-entry time and position of the space object. The effectiveness of this re-entry prediction is shown through the re-entry time window and ground track of space objects falling in real events, Grace-1, Grace-2, Tiangong-1, and Chang Zheng-5B Rocket body. As a result, through analysis 12 hours before the final re-entry time, it is shown that the re-entry time window and crash time can be accurately predicted with an error of less than 20 minutes.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.87-101
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• 2022

Cyber-attacks occur in the blink of an eye in cyberspace, and the damage is increasing all over the world. Therefore, it is necessary to develop a cyber common operational picture that can grasp the various assets belonging to the 3rd layer of cyberspace from various perspectives. By applying the method for grasping battlefield information used by the military, it is possible to achieve optimal cyberspace situational awareness. Therefore, in this study, the visualization screens necessary for the cyber common operational picture are identified and the criteria (response speed, user interface, object symbol, object size) are investigated. After that, the framework is designed by applying the identified and investigated items, and the visualization screens are implemented accordingly. Finally, among the criteria investigated by the visualization screen, an experiment is conducted on the response speed that cannot be recognized by a photograph. As a result, all the implemented visualization screens met the standard for response speed. Such research helps commanders and security officers to build a cyber common operational picture to prepare for cyber-attacks.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.123-139
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• 2011

Context-awareness as a key technology of ubiquitous computing needs a context model that understands and processes situational information coming from diverse sensors and devices, and can be applied diversely in various domains. Semantic web based ontologies use structured standard format and express meaning of information, so it is possible to recognize effectively context-awareness situations, allowing the system to share information and understand situation by inference. In this paper, we propose a layered ontology model to support generality and scaleability of the context-awareness system, and applied the model to u-Convention domain. In addition, we propose a effective reasoning method to handle compound situation by combining OWL-DL and SWRL rules.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.281-288
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• 2022

According to statistics conducted by the Korea Coast Guard, the number of accidents on small boats under 5 tons is increasing every year. This is because only a small number of people are on board. The previously developed maritime distress and safety systems are not well distributed because passengers must be equipped with additional remote equipment. The purpose of this study is to develop a distress awareness system that recognizes man over-board situations in real time. This study aims to present the part of the passenger tracking system among the small ship's distress awareness situational system that can generate passenger's location information in real time using deep learning based object detection and tracking technologies. The system consisted of the following steps. 1) the passenger location information is generated in the form of Bounding box using its detection model (YOLOv3). 2) Based on the Bounding box data, Deep SORT predicts the Bounding box's position in the next frame of the image with Kalman filter. 3) When the actual Bounding Box is created within the range predicted by Kalman-filter, Deep SORT repeats the process of recognizing it as the same object. 4) If the Bounding box deviates the ship's area or an error occurs in the number of tracking occupant, the system is decided the distress situation and issues an alert. This study is expected to complement the problems of existing technologies and ensure the safety of individuals aboard small boats.