• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.163-171
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• 2024

In the existing air traffic management (ATM) system, various types of safety alert features are provided based on trajectory data to ensure the safety of aircraft operations, along with aircraft position and detailed flight information. The urban air traffic management (UATM) system for urban air mobility (UAM) should also provide safety alert features to ensure the safety of UAM operations. Considering the operational environment of UAM, it is necessary that the safety alert features provided at least match or exceed those available in the existing ATM system. This study aims to present the safety alert features of the new UATM system that differ from those provided by the existing ATM system before introduction and commercialization of UAM. The study was conducted focusing on the safety alert features that should be provided in the event of a deviation from the UAM's path, and the establishment of the safety alert features was carried out in two parts: approach path monitor (APM), which is applied during the approach phase, and route adherence monitoring (RAM), which is applied during the cruise phase.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.804-814
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• 2023

Various buildings are scattered below and around the flight path of UAM (Urban Air Mobility), which flies within a densely populated urban area. And the vertiport used by UAM for takeoff and landing is located on a flat area within the city center or on top of a building. As such, UAM operates in densely populated urban areas, and vertiports for takeoff and landing are installed in densely populated areas, requiring a very high level of safety. In particular, for safe landing of UAM, it is necessary to monitor the approach status of UAM approaching the vertiport from the final approach course and provide approach information. Accordingly, to monitor the UAM vertiport final approach path, research was conducted on technology that utilizes optical equipment that can be installed in a narrow site and has the advantage of reducing the burden of electromagnetic waves.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.975-983
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• 2022

This paper presents an innovative way of integrating scheduling and project controls with the environmental impact of a construction project to track, monitor, and manage environmental emissions at the activity level. As a starting point, scheduling and project controls help monitor the status of a project to provide an assessment of the duration and sequence of activities. Additionally, project schedules can also reflect resource allocation and costs associated with various phases of a construction project. Owners, contractors and construction managers closely monitor tasks or activities on the critical path(s) and/or longest path(s) calculated through network based scheduling techniques. However, existing industry practices do not take into account environmental impact associated with each activity during the life cycle of a project. Although the environmental impact of a project may be tracked in various ways, that tracking is not tied to the project schedule and, as such, generally is not updated when schedules are revised. In this research, a Cradle to Gate approach is used to estimate environmental emissions associated with each activity of a sample project schedule. The research group has also investigated the potential determination of scenarios of lowest environmental emissions, just as project managers currently determine scenarios with lowest cost or time. This methodology can be scaled up for future work to develop a library of unit emissions associated with commonly used construction materials and equipment. This will be helpful for project owners, contractors, and construction managers to monitor, manage, and reduce the carbon footprint associated with various projects.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.345-348
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• 1994

A real-time collision avoidance algorithm for an AMR (Autonomous Mobile Robot) using the Distance Transform and Vector Field Histogram is studied. This approach enables AMR to find a collision-free path with the unknown obstacles. All system parameters including positions of the obstacles can be accepted using a mouse icon and all the obtained trajectories can be displayed on a computer monitor in graphics.

• Smart Structures and Systems
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• v.20 no.2
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• pp.175-180
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• 2017

The load-carrying capacity and structural behavior of concrete-filled steel tube (CFST) structures is highly influenced by the grouting compactness in the steel tube. Due to the invisibility of the grout in the steel tube, monitoring of the grouting progress in such a structure is still a challenge. This paper develops an active sensing approach with combined piezoceramic-based smart aggregates (SA) and piezoceramic patches to monitor the grouting compactness of CFST bridge structure. A small-scale steel specimen was designed and fabricated to simulate CFST bridge structure in this research. Before casting, four SAs and two piezoceramic patches were installed in the pre-determined locations of the specimen. In the active sensing approach, selected SAs were utilized as actuators to generate designed stress waves, which were detected by other SAs or piezoceramic patch sensors. Since concrete functions as a wave conduit, the stress wave response can be only detected when the wave path between the actuator and the sensor is filled with concrete. For the sake of monitoring the grouting progress, the steel tube specimen was grouted in four stages, and each stage held three days for cement drying. Experimental results show that the received sensor signals in time domain clearly indicate the change of the signal amplitude before and after the wave path is filled with concrete. Further, a wavelet packet-based energy index matrix (WPEIM) was developed to compute signal energy of the received signals. The computed signal energies of the sensors shown in the WPEIM demonstrate the feasibility of the proposed method in the monitoring of the grouting progress.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.181-186
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• 2016

Recently, the surveillance system research has focused because Unmanned Aerial Vehicle(UAV) has the ability to monitor wide area. When the wide area are monitored, controlling UAVs repeatedly by pilots invokes the cost problem to operate UAVs. If monitoring path can be defined in advance, the cost problem can be solved by controlling UAVs autonomously based on the monitoring path. The traditional approach generates multiple motor primitives based on flied GPS locations. However, the monitoring points by UAVs are not considered by the generated motor primitives, the surveillance by UAVs is not performed properly. This paper proposes a motor primitive structure for surveillance UAVs to be flied autonomously. Motor primitives are generated automatically by setting surveillance points to denote surveillance targets accurately.

• The Journal of Korean Medicine
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• v.44 no.1
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• pp.38-55
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• 2023

Objectives: The purpose of this study was to provide direction for future research in the field of Korean medicine by analyzing microbiome based technologies emerging as a new diagnostic and treatment paradigm. Methods: To achieve the purpose of the study intellectual property data was used. After establishing citation network from registered microbiome-related US patents, citation network was analyzed by knowledge persistence-based main path approach to understanding technological trajectories. Furthermore, community detection algorithms were used to quantitatively identifying specific technological domain in a particular time period. Results: Results shows that early technologies in livestock industry contribute most to the recent patents. Knowledge in the patents flow through the path of food and beverage technological domain, and finally are inherited to the recent development of diagnosis, treatment and prevention technic. Conclusions: This study indicate that developing diagnostic tools which can link the composition of microbiome to specific diseases should be given high priority. Researches should lead to novel therapeutic strategies. Specifically, improving reliability of pattern identification and finding effective therapeutic compositions based on principles of Korean medicine is necessary.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.615-622
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• 2016

Automotive control software can be a source of critical safety issues when developers do not comply system constraints. However, a violation is difficult to identify in complicated source code if not supported by an automated verification tool. This paper introduces two possible approaches that check whether an automotive control software complies API call constraints to compare their performance and effectiveness. One method statically analyzes the source code and explores all possible execution paths, and the other utilizes a model checker to monitor constraint violations for a given set of constraint automata. We have implemented both approaches and performed a series of experiments showing that the approach with model-checking finds constraint violations more accurately and scales better.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.