• Journal of Yeungnam Medical Science
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• v.36 no.3
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• pp.225-230
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• 2019

Background: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms. Methods: Coding activity consists of two stages. At first, the coders need to understand a presented medical term (informational activity). The second coding stage is about a navigating terminology browser to find a code that matches the concept (code-matching activity). Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) was used for the coding system. A new computer application to record the trajectory of the computer mouse and record the usage time was programmed. Using this application, we measured the time that was spent. A senior neurosurgeon who has studied SNOMED CT has analyzed the accuracy of the input coding. This method was tested by five neurosurgical residents (NSRs) and five medical record administrators (MRAs), and 20 neurosurgical terms were used. Results: The mean accuracy of the NSR group was 89.33%, and the mean accuracy of the MRA group was 80% (p=0.024). The mean duration for total coding of the NSR group was 158.47 seconds, and the mean duration for total coding of the MRA group was 271.75 seconds (p=0.003). Conclusion: We proposed a method to analyze the clinical coding process. Through this method, it was possible to accurately calculate the time required for the coding. In neurosurgical terms, NSRs had shorter time to complete the coding and higher accuracy than MRAs.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.2
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• pp.129-137
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• 2019

This study was conducted to investigate the effects of underwater noise caused by pile driving during marine construction on fish. In this study, the three gray rockfish were released about 1 km away from the construction site of wind power generation on July 18, 2018 and traced using two acoustic telemetry techniques. The behavior of the fish was analyzed by calculating the moving distance, swimming speed and direction of the gray rockfish. In the results of the acoustic tracking using the ship, the rockfish moved about 2.11 km for about two hours at a speed of $0.28{\pm}0.14m/s$ (0.94 TL/s). The bottom depth of the trajectory of the rockfish was $1.0{\pm}0.6m$ on average. There was a significant directionality in swimming direction of the gray rockfish, and there was no significant correlation between the swimming direction and tidal current direction. Moving distance during 5 minutes (5MD) during pile driving and finishing operations between rock surface and bedrock were 0.94-0.96 times (76.0-77.0 m) and 1.81-2.73 times (146.0-219.5 m), respectively, compared with no pile driving. This study is expected to be used as a basic data of fish behavior research on underwater noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.781-789
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• 2021

In this paper, we quantitatively analyzed the required UAV(Unmanned Aerial Vehicle) failure rate of small UAV (≤25kg) based on the harm to human caused by UAV crash to fly over the populated area. We compute the number of harm to human when UAV falls to the ground at certain descent point by using population density, car traffic, building to land ratio, number of floors of building data of urban area and UAV descent trajectory modeling. Based on this, the maximum allowable UAV failure rate is calculated to satisfy the Target Level of Safety(TLS) for each UAV descent point. Then we can generate the failure rate requirement in the form of map. Finally, we divide UAV failure rate into few categories and analyze the possible flight area for each failure rate categories. Considering the Youngwol area, it is analyzed that the UAV failure rate of at least 10^-4 (failure/flight hour) is required to access the residential area.

• Journal of Ocean Engineering and Technology
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• v.35 no.3
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• pp.173-182
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• 2021

The maneuvering performance of a ship on the actual sea is very different from that in calm water due to wave-induced motion. Enhancement of a ship's maneuverability in waves at the design stage is an important way to ensure that the ship navigates safely. This paper focuses on the maneuvering prediction of a Russian trawler in wind and irregular waves. First, a unified seakeeping and maneuvering analysis of a Russian trawler is proposed. The hydrodynamic forces acting on the hull in calm water were estimated using empirical formulas based on a database containing information on several fishing vessels. A simulation of the standard maneuvering of the Russian trawler was conducted in calm water, which was checked using the International Maritime Organization (IMO) standards for ship maneuvering. Second, a unified model of seakeeping and maneuvering that considers the effect of wind and waves is proposed. The wave forces were estimated by a three-dimensional (3D) panel program (ANSYS-AQWA) and used as a database when simulating the ship maneuvering in wind and irregular waves. The wind forces and moments acting on the Russian trawler are estimated using empirical formulas based on a database of wind-tunnel test results. Third, standard maneuvering of a Russian trawler was conducted in various directions under wind and irregular wave conditions. Finally, the influence of wind and wave directions on the drifting distance and drifting angle of the ship as it turns in a circle was found. North wind has a dominant influence on the turning trajectory of the trawler.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.424-430
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• 2021

Determining the cause of a traffic signal violation is difficult if the drivers' claims are contradictory. In this study, the process of identifying signal violations using a simulation was presented based on cases. First, statements from the driver or witness whose cause of the signal violation is unclear were excluded. Second, the final position, final location, damaged area, steering status, braking status, and road surface traces of the vehicle were collected. The impact point was investigated from the stop line. Third, simulation data were modified and entered until the collision situation of the accident vehicle and the final stop position were met. Fourth, if the simulation results were consistent with the crash situation, the facts were verified by cross-validation to conform to the driver's statement. The results of the simulation showed that the Lexus entered the left turn signal in the intersection at approximately 55 km/h. In comparison, the Sonata driver saw the vehicle straight ahead at the intersection, entered the 72 km/h intersection, and collided with the Lexus. Therefore, the Sonata was identified as a signal violation, and the claims of the Sonata driver, witnesses, and police were contradictory.

• Physical Therapy Rehabilitation Science
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• v.11 no.2
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• pp.235-244
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• 2022

Objective: The aim of this study was to investigate of the foot plantar pressure and usability after gait training using the ExoAtlet wearable exoskeleton robot in an incomplete spinal cord injury (SCI) patient. Design: A case study Methods: Six participants with an asymmetry in motor and sensory function completed the gait training using ExoAtlet wearable exoskeleton robot for 15 sessions, five per weeks, 3weeks. They were divided into two groups (low and high strength group) and group differences were evaluated about session at stating of gait, gait distance at final session and foot plantar pressures and useability after training. Results: Low strength group was faster than high strength group on adaptation of robot gait. And high strength group increased faster than low strength group on the gait distance during training. In standing and gait, weaker leg was higher than stronger leg on mean foot plantar pressure in low strength group. And stronger leg was higher than weaker leg on foot plantar pressure in high strength group. The length of the anterior-posterior trajectory of the center of pressure during gait was similar in low strength group, but different in high strength group. useability was positive about ExoAtlet wearable exoskeleton gait after training. Conclusions: ExoAtlet wearable exoskeleton robot gait training was positive about improving gait in all participants regardless of differences in severity of symptoms and gait abnormalities.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.303-311
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• 2021

In this study, data from the 11th year of the Korean Welfare Panel Study (2016), the 12th year (2017), the 13th year (2018), and the 14th year (2019) were used to verify whether drinking problems in adults had an end-to-end effect on depression. The analysis showed that, first, the initial value of depression has a static (+) relationship with the initial value of problem drinking, and a significant relationship with the rate of change in problem drinking. Second, the supply and demand households showed a static relationship with the initial value of depression, the initial value of problem drinking. Third, in the case of people with disabilities, the relationship between the initial value of depression, the initial value of problem drinking, and the amulet (-). Therefore, it was suggested that the development of drinking problem prevention programs and education should be actively carried out in school education before adulthood.

• Journal of Ecology and Environment
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• v.46 no.4
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• pp.282-291
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• 2022

Background: The Arctic permafrost stores enormous amount of carbon (C), about one third of global C stocks. However, drastically increasing temperature in the Arctic makes the stable frozen C stock vulnerable to microbial decomposition. The released carbon dioxide from permafrost can cause accelerating C feedback to the atmosphere. Soil organic matter (SOM) composition would be the basic information to project the trajectory of C under rapidly changing climate. However, not many studies on SOM characterization have been done compared to quantification of SOM stocks. Thus, the purpose of our study is to determine soil properties and molecular compositions of SOM in four different Arctic regions. We collected soils in different soil layers from 1) Cambridge Bay, Canada, 2) Council, Alaska, USA, 3) Svalbard, Norway, and 4) Zackenberg, Greenland. The basic soil properties were measured, and the molecular composition of SOM was analyzed through pyrolysis-gas chromatography/mass spectrometry (py-GC/MS). Results: The Oi layer of soil in Council, Alaska showed the lowest soil pH and the highest electrical conductivity (EC) and SOM content. All soils in each site showed increasing pH and decreasing SOC and EC values with soil depth. Since the Council site was moist acidic tundra compared to other three dry tundra sites, soil properties were distinct from the others: high SOM and EC, and low pH. Through the py-GC/MS analysis, a total of 117 pyrolysis products were detected from 32 soil samples of four different Arctic soils. The first two-axis of the PCA explained 38% of sample variation. While short- and mid-hydrocarbons were associated with mineral layers, lignins and polysaccharides were linked to organic layers of Alaska and Cambridge Bay soil. Conclusions: We conclude that the py-GC/MS results separated soil samples mainly based on the origin of SOM (plants- or microbially-derived). This molecular characteristics of SOM can play a role of controlling SOM degradation to warming. Thus, it should be further investigated how the SOM molecular characteristics have impacts on SOM dynamics through additional laboratory incubation studies and microbial decomposition measurements in the field.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.