• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.119-127
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• 2006

Granulated Blast Furnace Slag (GBFS) is produced in the manufacture process of pig-iron and shows a similar particle formation to that of natural sea sand and also shows light weight, high shear strength, well permeability, and especially has a latent hydraulic property by which GBFS is solidified with time. Therefore, when GBFS is used as a backfill material of quay or retaining walls, the increase of shear strength induced by the hardening is presumed to reduce the earth pressure and consequently the construction cost of harbor structures decreases. In this study, using the model sand box (50 cm$\times$50 cm$\times$100 cm), the model wall tests were carried out on GBFS and Toyoura standard sand, in which the resultant earth pressure, a wall friction and the earth pressure distribution at the movable wall surface were measured. In the tests, the relative density was set as Dr=25, 55 and 70% and the wall was rotated at the bottom to the active earth pressure side and followed by the passive side. The maximum horizontal displacement at the top of the wall was set as ${\pm}2mm$. By these model test results, it is clarified that the resultant earth pressure obtained by using GBFS is smaller than that of Toyoura sand, especially in the active-earth pressure.

• Korean Journal of Microbiology
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• v.37 no.3
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• pp.228-233
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• 2001

The acid tolerance response (ATR) of log-phase Salmouella enterica seroyar Typhimurium is induced by acid adaptation below pH4.5 and will protect cells against more severe acid. Two distinctive ATR systems in thisorganism are a log-phase and stationary-phase ATR in which acid adaptations trigger the synthesis of acid shockproteins (ASPs). We found that log-phase ATR system was strongly affected by environmental factor, low tem-perature, $25^{\circ}C$. Exposure to low temperature and mild acid has been shown to increase acid survival dra-matically, and this survival rate was showed higher than $37^{\circ}C$. Especially unadapted cells at $25^{\circ}C$ presented tenthousand folds survival increasing when compared with cells at $37^{\circ}C$. The degree of acid tolerance of rpoSwhich is blown to be required for acid tolerance more increase than $37^{\circ}C$. Even though AIR pattern of rpoSbetween unadapted and adapted was showed similar at pH 3.1, rpoS-dependent ATR system also has beendetected in low temperature because rpoSAp prevents sustained acid survival at $25^{\circ}C$. Therefore the resultssuggest low temperature ATR system requires rpoS-dependent and -independent both. To investigate the basisfor low temperature related ATR system, gene that was participated for low temperature acid tolerance (lat) wasscreened in virulent S. enterica serovar Typhimurium UKl Using the technique of P22- MudJ (Km, lacZ)-directed lacZ operon fusion, LF452 latA‥‥MudJ was isolated. The latA‥‥MudJ of S. enterica Typhimurium pre-vented low temperature acid tolerance response. Therefore latA is considered one of the important genes for acidadaptation.

• Journal of the Korean Society of Radiology
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• v.7 no.6
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• pp.403-408
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• 2013

This study made a tentative estimation of the shielding rate of barium compound by thickness through monte carlo simulation to apply medical radiation shielding products that can replace existing lead. Barium sulfate($BaSO_4$) was used for the shielding material, and thickness of the shielding material specimen was simulated from 0.1 mm to 5 mm by applying $15{\times}15cm^2$ of specimen area, $4.5g/cm^3$ of density of barium sulfate, and $11.34g/cm^3$ density of lead. Entered source was simulated with 10kVp Step in consecutive X-ray energy spectrum(40 kVp ~ 120 kVp). Absorption probability in 40 kVp ~ 60 kVp showed same shielding rate with lead in 3 mm ~ 5 mm of thickness, but it was identified that under 2 mm, the shielding rate was a bit lower than the existing lead shielding material. Also, the shielding rate in 70 kVp ~ 120 kVp energy band showed similar performance as the existing lead shielding material, but it was tentatively estimated as fairly low shielding rate below 0.5 mm. This study estimated the shielding rate of barium compound as the thickness function of x-ray energy band for medical radiation through monte carlo simulation, and made comparative analysis with existing lead. Also, this study intended to verify application validity of the x-ray shielding material for medical radiation of pure barium sulfate. As a result, it was estimated that the shielding effect was 95% higher than the existing lead 1.5 mm in at least 2 mm thickness of barium compound in medical radiation energy band 70 kVp ~ 120 kVp, and this result is considered valid to be provided as a base data in weight lightening production of radiation shielding product for medical radiation.

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.440-447
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• 2020

The demand for large-scale horticultural complexes utilizing reclaimed lands is increasing, and one of the pending issues for the construction of large-scale facilities is to establish foundation design criteria. In this paper, we tried to review previous studies on the method of reinforcing the foundation of soft ground. Target construction methods are spiral piles, wood piles, crushed stone piles and PF (point foundation) method. In order to evaluate the performance according to the basic construction method, pull-out resistance, bearing capacity, and settlement amount were measured. At the same diameter, pull-out resistance increased with increasing penetration depth. Simplified comparison is difficult due to the difference in reinforcement method, diameter, and penetration depth, but it showed high bearing capacity in the order of crushed stone pile, PF method, and wood pile foundation. In the case of wood piles, the increase in uplift resistance was different depending on the slenderness ratio. Wood, crushed stone pile and PF construction methods, which are foundation reinforcement works with a bearing capacity of 105 kN/㎡ to 826 kN/㎡, are considered sufficient methods to be applied to the greenhouse foundation. There was a limitation in grasping the consistent trend of each foundation reinforcement method through existing studies. If these data are supplemented through additional empirical tests, it is judged that a basic design guideline that can satisfy the structure and economic efficiency of the greenhouse can be presented.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.249-263
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• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.