• Journal of Korean Medical Ki-Gong Academy
• /
• v.22 no.1
• /
• pp.28-71
• /
• 2023

Objective : From March 2018 to July 2022, H Korean Medicine Hospital conducted a guidance on Gigong training using the Moosim Gigong Doinbeop and Moosim Gigong Walking. This report intends to report the results and share the specific methods of a guidance on Gigong training used in the process of implementation, thereby helping the research of a guidance on Gigong training later. Methods : The methods and results of the implementation of Moosim Gigong Doinbeop and Moosim Gigong Walking implemented by H Korean Medicine Hospital were reported. For the movements of Doinbeop, the posture and movements, the precautions to be taken when guiding, the alternative movements, and the meaning of the movements were summarized. For Moosim Gigong Walking, the method of progress, the method of motion, precautions to be taken, and replaceable movements were summarized. The method of implementing the guidance on Gigong training for severely ill and elderly patients was introduced. The application cases that were applied to some diseases and effective were recorded. Results : At H Korean Medicine Hospital, Moosim Gigong Doinbeop and Moosim Gigong Walking were conducted in the form of an open lecture, and 4,682 patients attended the Doinbeop class and 3,373 patients attended the Walking class. There is no restriction on the type of disease of the participating patients. The attending physician recommends and the patient wishes, the patient participates in the course. Conclusions : Curing technology is a long-standing treatment method of Korean Medicine, but it has not yet been activated in the modern Korean Medicine system. Research on the guidance on Gigong training can be conducted to establish itself as a new treatment method for Korean Medicine.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2006.10a
• /
• pp.176-183
• /
• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.5A
• /
• pp.673-683
• /
• 2008

This study improved the existing method of using the longitudinal strain and concept of influence line to develop Bridge Weigh-in-Motion system without axle detector using the dynamic strain of the bridge girders and concrete slab. This paper first describes the considered algorithms of extracting passing vehicle information from the dynamic strain signal measured at the bridge slab, girders, and cross beams. Two different analysis methods of 1) influence line method, and 2) neural network method are considered, and parameter study of measurement locations is also performed. Then the procedures and the results of field tests are described. The field tests are performed to acquire training sets and test sets for neural networks, and also to verify and compare performances of the considered algorithms. Finally, comparison between the results of different algorithms and discussions are followed. For a PSC I-girder bridge, vehicle weight can be calculated within a reasonable error range using the dynamic strain gauge installed on the girders. The passing lane and passing speed of the vehicle can be accurately estimated using the strain signal from the concrete slab. The passing speed and peak duration were added to the input variables to reflect the influence of the dynamic interaction between the bridge and vehicles, and impact of the distance between axles, respectively; thus improving the accuracy of the weight calculation.

• Journal of Fisheries and Marine Sciences Education
• /
• v.28 no.1
• /
• pp.14-21
• /
• 2016

Research on ship motion and seasickness is recognized as the important research area to ensure the pleasant operative environment in addition to the research of operation safety of ship. In this paper, the motion performance in waves for the training ship Kaya of Pukyong National University is obtained by using the computer program based on Strip Method. To guarantee the pleasant seafaring in ocean, the vertical acceleration of ship motion is calculated according to the habitation division location in the ship. The results of calculation by changes of location of habitation division are compared with the guideline of MSI(Motion Sickness Incidence). The degree of motion sickness is shown and discussed through the comparison between calculated vertical acceleration spectrum and MSI guideline. To improve the safety of ship in motion and the pleasant seafaring in waves, the downtrend of seasickness ratio is needed by the decrease on vertical acceleration of the ship. Through the results in this paper, the relocation of both bridge and accommodation toward the aftship reduced the vertical acceleration and MSI.

• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.17-34
• /
• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.19 no.2 s.72
• /
• pp.125-138
• /
• 2006

The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.5
• /
• pp.50-57
• /
• 2016

The present study proposed three inspection reliability indices which compared inspection results evaluated at in-depth(routine) inspection and in-depth safety inspection; Nominal inspection reliability index, Real inspection reliability index, and DS nominal inspection reliability index. The methods to improve the inspection reliability were also proposed. Since bridge inspection process is critical to ensuring the safety of bridges and identifying repair and maintenance needs, the quality of the inspection data produced from the inspection process is very important. Consequently, the inspection reliability indices were suggested to evaluate quality of current inspection practices. Specifically, approximately 85% of inspection errors evaluated by the DS nominal inspection reliability index are within 1 rating grade(equal to or less than damage score ${\pm}0.1$). In order to improve the inspection reliability, transportation agency should implement QC(Quality Control) practices and develop professional expertises of inspectors by higher requirements for inspectors, on-off line inspection training and etc.

• Journal of the Korean GEO-environmental Society
• /
• v.19 no.11
• /
• pp.15-22
• /
• 2018

The main objective of this study was to analyse heavy metals in sediments obtained from Gwangan bridge and to evaluate pollution intensity of the sites. To evaluate pollution intensity of the sites, we used enrichment factor (EF), geoaccumulation index, potential ecological risk factor (PERF), and mean PEL quotient. Pollution intensities of these sites were evaluated by above methods, and we found most dangerous heavy metal and polluted sites. All sites showed non polluted or low risk for the heavy metals such as Cr, Cu, Ni, Pb, and Zn, but all sites were categorized as minor enrichment for Cd. G4 was evaluated as moderately polluted by Cd ($I_{geo}$) but other sites were unpolluted by heavy metals. In summary, Cd was found to be higher concentrations for all sites. For G4 and G5 sites, Pb and Zn in addition to Cd were higher than other sites.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.5
• /
• pp.315-321
• /
• 2023

Long-span bridges are flexible structures with low natural frequencies and damping ratios, making them susceptible to vibrational serviceability problems. However, the current design guideline of South Korea assumes a uniform threshold of wind speed or vibrational amplitude to assess the occurrence of harmful vibrations, potentially overlooking the complex vibrational patterns observed in long-span bridges. In this study, we propose a pointwise vortex-induced vibration (VIV) detection method using a deep-learning-based signalsegmentation model. Departing from conventional supervised methods of data acquisition and manual labeling, we synthesize training data by generating sinusoidal waves with an envelope to accurately represent VIV. A Fourier synchrosqueezed transform is leveraged to extract time-frequency features, which serve as input data for training a bidirectional long short-term memory model. The effectiveness of the model trained on synthetic VIV data is demonstrated through a comparison with its counterpart trained on manually labeled real datasets from an actual cable-supported bridge.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.57 no.3
• /
• pp.228-235
• /
• 2021

Marine accidents caused by ships are very diverse, such as collision, sinking, stranding, grounding and fire. In particular, persons on passenger ship are unspecified and not trained, so it makes evacuation harder. For this reason, an evacuation plan that considers diverse situation in ship is needed. Effective evacuation planning requires training in consideration of various evacuation situations. In this paper, we investigated the time elapsed on evacuation in various situations from "HANMIR," the fishery training ship of the Korean Institute of Maritime and Fisheries Technology, using a Ship Evacuation Analysis Program (SEA-Pro) which is introduced to the society. We assumed a situation that has not only inconveniences for real training but also the possibilities of happening. Not all trainees are resting in their cabin, so we assumed positions such as they are in the bridge or engine room and applied fire and flooding situations. We assumed that the time for alerting the situation would be short, so we applied only elapsed time of movement. Those analyses could be helpful in three ways. The first is predicting the consequence of possible accidents. There are some conditions that can be appliable to this model, such as the decreased area of sight in those situations. The second is concluding the optimal limit of carriage and placement of safety instruments on building a new ship. The third is to be a base data for ships to make a new effective evacuation plan based on these analyses.