• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.8-13
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• 2015

The experimental design methodology was applied in the drop tube furnace (DTF) to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of DTF. The dependent variables such as burnout ratios (BOR) of coal and $CO/CO_2$ ratios were mathematically described as a function of three independent variables (coal particle size, carrier gas flow rate, wall temperature) being modeled by the use of the central composite design (CCD), and evaluated using a second-order polynomial multiple regression model. The prediction of BOR showed a high coefficient of determination (R2) value, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the simulation data. However, $CO/CO_2$ ratio had a big difference between calculated values and predicted values using conventional RSM, which might be mainly due to the dependent variable increses or decrease very steeply, and hence the second order polynomial cannot follow the rates. To relax the increasing rate of dependent variable, $CO/CO_2$ ratio was taken as common logarithms and worked again with RSM. The application of logarithms in the transformation of dependent variables showed that the accuracy was highly enhanced and predicted the simulation data well.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.33-40
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• 2004

According as client/server is generalized by development of computer performance and information communication technology, Servers uses local cache for extensibility and early response time, and reduction of limited bandwidth. Consistency of cached data need between server and client this time and much technique are proposed according to this. This Paper improved update frequency cache consistency in old. Existent consistency techniques is disadvantage that response time is late because synchronous declaration or abort step increases because delaying write intention declaration. Techniques that is proposed in this paper did to perform referring update time about object that page request or when complete update operation happens to solve these problem. Therefore, have advantage that response is fast because could run write intention declaration or update by sel_mode electively asynchronously when update operation consists and abort step decreases and clearer selection.

• Earthquakes and Structures
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• v.15 no.4
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• pp.419-429
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• 2018

The seismic vulnerability analysis of multi-span bridges can be based on the response of the piers, provided that deck, bearings and foundations remain elastic. The lateral response of an RC bridge pier can be affected by different mechanisms (i.e., flexure, shear, lap-splice or buckling of the longitudinal reinforcement bars, second order effects). In the literature, simplified formulations are available for mechanisms different from the flexure. On the other hand, the flexural response is usually calculated with a numerically-based Moment-Curvature diagram of the base section and equivalent plastic hinge length. The goal of this paper is to propose a simplified analytical solution to obtain the Moment-Curvature relationship for hollow circular RC sections. This based on calibrated polynomials, fitted against a database comprising 720 numerical Moment-Curvature analyses. The section capacity curve is defined through the position of 6 characteristic points and they are based on four input parameters: void ratio of the hollow section, axial force ratio, longitudinal reinforcement ratio, transversal reinforcement ratio. A case study RC bridge pier is assessed with the proposed solution and the results are compared to a refined numerical FEM analysis, showing good match.

• Earthquakes and Structures
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• v.16 no.6
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• pp.705-714
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• 2019

Seismic assessment of underground structures is one of the challenging problems in engineering design. This is because there are usually many sources of uncertainties in rocks and probable earthquake characteristics. Therefore, for decreasing of the uncertainties, seismic response of underground structures should be evaluated by sufficient number of earthquake records which is scarcely possible in common seismic assessment of underground structures. In the present study, a practical risk-based approach was performed for seismic risk assessment of an unsupported tunnel. For this purpose, Incremental Dynamic Analysis (IDA) was used to evaluate the seismic response of a tunnel in south-west railway of Iran and different analyses were conducted using 15 real records of earthquakes which were chosen from the PEER ground motion database. All of the selected records were scaled to different intensity levels (PGA=0.1-1.7 g) and applied to the numerical models. Based on the numerical modeling results, seismic fragility curves of the tunnel under study were derived from the IDA curves. In the next, seismic risk curve of the tunnel were determined by convolving the hazard and fragility curves. On the basis of the tunnel fragility curves, an earthquake with PGA equal to 0.35 g may lead to severe damage or collapse of the tunnel with only 3% probability and the probability of moderate damage to the tunnel is 12%.

• Earthquakes and Structures
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• v.16 no.4
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• pp.487-499
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• 2019

Energy-based seismic design of structures has gradually become prominent in today's structural engineering investigations because of being more rational and reliable when it is compared to traditional force-based and displacement-based methods. Energy-based approaches have widely taken place in many previous studies and investigations and undoubtedly, they are going to play more important role in future seismic design codes, too. This paper aims to compute the maximum earthquake energy input to elastic single-degree-of-freedom (SDOF) systems for selected real ground motion records. A data set containing 100 real ground motion records which have the same site soil profiles has been selected from Pacific Earthquake Research (PEER) database. Response time history (RTH) analyses have been conducted for elastic SDOF systems having a constant damping ratio and natural periods of 0.1 s to 3.0 s. Totally 3000 RTH analyses have been performed and the maximum mass normalized earthquake input energy values for all records have been computed. Previous researchers' approaches have been compared to the results of RTH analyses and an approach which considers the pseudo-spectral velocity with Arias Intensity has been proposed. Graphs of the maximum earthquake input energy versus the maximum pseudo-spectral velocity have been obtained. The results show that there is a good agreement between the maximum input energy demands of RTH analysis and the other approaches and the maximum earthquake input energy is a relatively stable response parameter to be used for further seismic design and evaluations.

• Journal of Microbiology and Biotechnology
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• v.32 no.11
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• pp.1406-1415
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• 2022

The formation of macrophage foam cells stimulated by oxidized low-density lipoprotein (ox-LDL) is deemed an important cause of atherosclerosis. Transcription factor Yin Yang 1 (YY1), which is a universally expressed multifunctional protein, is closely related to cell metabolism disorders such as lipid metabolism, sugar metabolism, and bile acid metabolism. However, whether YY1 is involved in macrophage inflammation and lipid accumulation still remains unknown. After mouse macrophage cell line RAW264.7 cells were induced by ox-LDL, YY1 and proprotein convertase subtilisin/kexin type 9 (PCSK9) expressions were found to be increased while low-density lipoprotein receptor (LDLR) expression was lowly expressed. Subsequently, through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), Western blot analysis, Oil Red O staining and cholesterol quantification, it turned out that silencing of YY1 attenuated the inflammatory response and lipid accumulation in RAW264.7 cells caused by ox-LDL. Moreover, results from the JASPAR database, chromatin immunoprecipitation (ChIP) assay, luciferase reporter assay and Western blot analysis suggested that YY1 activated PCSK9 by binding to PCSK9 promoter and modulated the expression of LDLR in the downstream of PCSK9. In addition, the results of functional experiments demonstrated that the inhibitory effects of YY1 interference on ox-LDL-mediated macrophage inflammation and lipid accumulation were reversed by PCSK9 overexpression. To sum up, YY1 depletion inhibited its activation of PCSK9, thereby reducing cellular inflammatory response, cholesterol homeostasis imbalance, and lipid accumulation caused by ox-LDL.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.83-90
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• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.128-134
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• 2016

IoT devices including smart devices are connected with internet, thus they have security threats everytime. Particularly, IoT devices are composed of low performance MCU and small-capacity memory because they are miniaturized, so they are likely to be exposed to various security threats like DoS attacks. In addition, in case of IoT devices installed for a remote place, it's not easy for users to control continuously them and to install immediately security patch for them. For most of IoT devices connected directly with internet under user's intention, devices exposed to outside by setting IoT gateway, and devices exposed to outside by the DMZ function or Port Forwarding function of router, specific protocol for IoT services was used and the devices show a response when services about related protocol are required from outside. From internet search engine for IoT devices, IP addresses are inspected on the basis of protocol mainly used for IoT devices and then IP addresses showing a response are maintained as database, so that users can utilize related information. Specially, IoT devices using HTTP and HTTPS protocol, which are used at usual web server, are easily searched at usual search engines like Google as well as search engine for the sole IoT devices. Ill-intentioned attackers get the IP addresses of vulnerable devices from search engine and try to attack the devices. The purpose of this study is to find the problems arisen when HTTP, HTTPS, CoAP, SOAP, and RestFUL protocols used for IoT devices are detected by search engine and are maintained as database, and to seek the solution for the problems. In particular, when the user ID and password of IoT devices set by manufacturing factory are still same or the already known vulnerabilities of IoT devices are not patched, the dangerousness of the IoT devices and its related solution were found in this study.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2000-2007
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• 1999

Recently, DDS (Distributed Database System) has been often implemented on VAN (Value Added Network) as we know the amazing expansion of information network. DDS can yield significant cost and response time advantages over centrailzed systems for geographically distributed organizations. However, inappropriate design can result in high cost and poor response time. In a DDS design, the main problem is 1) how to select proper computer, and 2) how to allocate data fragment into proper nodes. This paper addresses DDS design problem of selecting the proper class of computers and the allocating data files on VAN. Also, the formulated model includes tow objectives, the operating and investment cost. GA (Genetic Algorithm) is developed to solve this mathematical formulation. A numerical experiment shows that the proposed method arrives at a good solution.