• Journal of Korean Neurosurgical Society
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• v.38 no.4
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• pp.281-286
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• 2005

Objective : The authors report our experience of urokinase thrombolysis in treating patients harboring nonaneurysmal spontanesous intraventricular hemorrhage[IVH] and evaluated complications, safety and feasibility of this procedure retrospectively. Methods : Fifty-three patients with nonaneurysmal IVH>15mL without underlying structural etiology or coagulopathy were recruited. The patients with Glasgow Coma Scale[GCS]<5 were excluded. A catheter was directed into the IVH. Hematoma aspiration was followed by instillation of urokinase at the ear level of drainage bag under intracranial pressure monitoring system. This was repeated every 6hours until half of its initial volume. For analysis of prognostic factors, we classified the patients into two groups by Glasgow outcome scale[GOS]; good [$GOS\;{\ge}3$] and bad [GOS<3] prognosis group, and performed comparative analysis between two groups. Results : Mean age was 60.2years. The baseline hematoma size ranged 16 to 72mL. IVH volume reduction was done by an average of 74.2%. As complications, there were 3cases of rebleeding and 2cases of ventriculitis. No intracranial adverse effects were observed during thrombolytic theraphy. At 6months after the procedure, 29patients had achieved a good recovery, 15remained vegetative. 9patients died in hospital. The main good prognostic factors were young age, small IVH volume, and high GCS. Conclusion : The results of this study suggest that this relatively easy and safe method of treatment will improve the prognosis. However, further clinical studies also must assess optimal thrombolytic dosage, frequency, and timing of urokinase instillation for safety and effectiveness and must include controlled comparisons of mortality, disability outcome, quality of life, time until convalescence, and cost of care in treated and untreated patients.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.611-617
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• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.3
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• pp.11-19
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• 2009

Recently, concerns relating to the maintenance of large structures have been increased. In addition, the number of large structures that need to be evaluated for their structural safety due to natural disasters and structural deterioration has been rapidly increasing. It is common for the structural characteristics of an older large structure to differ from the characteristics in the initial design stage, and changes in dynamic characteristics may result from a reduction in stiffness due to cracks on the materials. The process of deterioration of such structures enables the detection of damaged locations, as well as a quantitative evaluation. One of the typical measuring instruments used for the monitoring of bridges and buildings is the dynamic measurement system. Conventional dynamic measurement systems require considerable cabling to facilitate a direct connection between sensor and DAQ logger. For this reason, a method of measuring structural responses from a remote distance without the mounted sensors is needed. In terms of non-contact methods that are applicable to dynamic response measurement, the methods using the doppler effect of a laser or a GPS are commonly used. However, such methods could not be generally applied to bridge structures because of their costs and inaccuracies. Alternatively, a method using a visual image can be economical as well as feasible for measuring vibration signals of inaccessible bridge structures and extracting their dynamic characteristics. Many studies have been conducted using camera visual signals instead of conventional mounted sensors. However, these studies have been focused on measuring displacement response by an image processing technique after recording a position of the target mounted on the structure, in which the number of measurement targets may be limited. Therefore, in this study, a model experiment was carried out to verify the measurement algorithm for measuring multi-point displacement responses by using a DIC (Digital Image Correlation) technique.

• Journal of Conservation Science
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• v.8 no.1 s.11
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• pp.40-50
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• 1999

A geotechnical research including observation of the movement of wall-structure, monitoring of groundwater, non-destructive geophysical investigation was conducted to workout a countermeasure to conserve the Muryong Royal Tomb which is the most extinguishable cultural property of the Baekje dynasty. Movement of the structure of Muryong Royal Tomb generally arises to the front chamber and its amplitude in a rainy season is twice of that in the dry season. It represents serious problem concerned about structural safety of the royal tomb in the rainy season. Movement of wall-structure is caused due to the rain infiltration through cracks in the quicklime layer within the soil mound on the top of the royal tomb and the change of the temperature inside of the tomb. Cracks found around the Muryong Royal Tomb are mostly spread in NW and SE of the tomb structure and it harmonizes with the direction of movement of wall-structure of the Muryong Royal Tomb. Counter-plans for safety and prevention of water-leakage that obstruct the movement of wall structures towards the direction of south are very important for the conservation of Muryong Royal Tomb. After getting rid of the cause of structural change by the restoration of the front chamber of the Muryong Royal Tomb, it needs to reinforce the quicklime layer for prevention of waterleak.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.451-458
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• 2023

As forest fires continue to increase in scale worldwide, the importance of forest roads in relation to forest fire prevention and suppression has become increasingly evident. To ensure effective functioning during a forest fire disaster, it is crucial to apply appropriate road planning and ensure roads' structural integrity. However, previous studies have predominantly focused on the impact of forest fires on firebreak efficacy and road placement, meaning that insufficient attention has been paid to ensuring the safety of these facilities. Therefore, this study sought to compare the strength of concrete facilities within areas damaged by forest fires over the past three years by using the rebound hammer test to identify signs of thermal degradation. The results revealed that concrete facilities damaged by forest fires exhibited significantly lower strength (15.6 MPa) when compared with undamaged facilities (18.0 MPa) (p<0.001), and this trend was consistent across all the target facilities. Consequently, it is recommended that safety assessment criteria for concrete forest road facilities be established to prevent secondary disasters following forest fire damage. Moreover, continuous monitoring and research involving indoor experiments are imperative in terms of enhancing the stability of forest road structures. It is expected that such research will lead to the development of more effective strategies for forest fire prevention and suppression.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.1-8
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• 2024

The expansion joint is installed to offset the expansion of the superstructure and must ensure sufficient gap during its service life. In detailed guideline of safety inspection and precise safety diagnosis for bridge, damage due to lack or excessive gap is specified, but there are insufficient standards for determining the abnormal behavior of superstructures. In this study, a data-based maintenance was proposed by continuously monitoring the expansion-gap data of the same expansion joint. A total of 2,756 data were collected from 689 expansion joint, taking into account the effects of season. We have developed a method to evaluate changes in the expansion joint-gap that can analyze the thermal movement through four or more data at the same location, and classified the factors that affect the superstructure behavior and analyze the influence of each factor through deep learning and explainable artificial intelligence(AI). Abnormal behavior of the superstructure was classified into narrowing and functional failure through the expansion joint-gap evaluation graph. The influence factor analysis using deep learning and explainable AI is considered to be reliable because the results can be explained by the existing expansion gap calculation formula and bridge design.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.104-114
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• 2000

This study was carried out to estimate current status of dust concentrations in the factories producing non-metallic products in Korea. Data were gathered from the environmental monitoring reports by 40 workplace environmental monitoring institutes and the questionnaire designed for the study by the authors. A total of 1838 dust samples from 368 plants were obtained from the reports and were analyzed with no data modifications. But data on asbestos, rock wool, and welding fumes were excluded in this evaluation. The factories were classified into eight groups according to the standard industrial classification scheme in Korea. The results of this study were as follows; 1. The factories included were glass, non-refractory ceramic, refractory ceramic ware, structural non-refractory clay and ceramic, cement and lime, articles of concretes, and stone. Mean(geometric mean) concentrations of total dust samples ranged from $1.75(0.84)mg/m^3$ to $5.87(2.84)mg/m^3$. Statistically significantly higher dust concentrations were found in the cement and lime industries compared with other industries. 2. The non-compliance rates were 15.2% in glass and 20.6% in other non-metallic mineral products industries. Although all institutions surveyed utilized the identical sampling and classification scheme for dusts as specified in the current occupational exposure limits, wide discrepancies were found in collecting samples and classifying dusts. Further problems were discovered in classifying dusts. A dust sample collected could be classified into any of the three groups regardless of silica content. The results of this study showed that dust concentrations in the non-metallic products industries varied widely. Also discovered was classification errors of dust types among workplace monitoring institutes. These errors could adversely affect the results of exposure assessments and the true nature of dust hazards. Further, no institutions performed respirable dust sampling and analysis of crystalline silica. In order to correct these malpractices, current standards of occupational exposure limits should be revised and tight supervision by the Ministry of Labour be suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.403-411
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• 2016

Recently, the number of occurrences of inundation and the severity of flood damage has increased rapidly as the frequency of localized heavy rainfall and the ratio of impervious area increased in urban areas. Most local governments focus on employing structural measures (e.g., the construction of detention reservoirs/pump stations, rehabilitation of drainage and sewer pipes) to prevent urban inundation. On the other hand, the effectiveness of implementing such structural measures is being dimished because there are already many inundation prevention facilities. The limitation of structural measures can be overcoming by employing non-structure measures, such as flood alerts and the operation of drainage facilities. This study suggests the pump operation rule (i.e., suggesting pump stop level) for a new detention reservoir operating method, which triggers the operation of a pump based on the water level at the monitoring node in urban drainage system. In the new reservoir operation, a total of 48 rainfall events are generated by the Huff distribution for determining the proper pump stop level. First, the generated rainfall events are distributed as frequencies, quartiles, and durations. The averaged system resilience value was determined to range from 1.2 m to 1.5 m is based on the rainfall-runoff simulation with rainfall generated by the Huff distribution. In this range, 1.2 m was identified considering the safety factor of 1.25 by the Standard on sewer facilities in 2011.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.172-181
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• 2023

In this study, real-time damage evaluation of cable-stayed bridges was conducted for cable damage. ICP type acceleration sensors were used for real-time damage assessment of cable-stayed bridges, and Kinetic Energy Optimization Techniques (KEOT) were used to select the optimal conditions for the location and quantity of the sensors. When a structure vibrates by an external force, KEOT measures the value of the maximum deformation energy to determine the optimal measurement position and the quantity of sensors. The damage conditions in this study were limited to cable breakage, and cable damage was caused by dividing the cable-stayed bridge into four sections. Through FE structural analysis, a virtual model similar to the actual model was created in the real-time damage evaluation method of cable. After applying random oscillation waves to the generated virtual model and model structure, cable damage to the model structure was caused. The two data were compared by defining the response output from the virtual model as a corruption-free response and the response measured from the real model as a corruption-free data. The degree of damage was evaluated by applying the data of the damaged cable-stayed bridge to the Improved Mahalanobis Distance (IMD) theory from the data of the intact cable-stayed bridge. As a result of evaluating damage with IMD theory, it was identified as a useful damage evaluation technology that can properly find damage by section in real time and apply it to real-time monitoring.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.