• Earthquakes and Structures
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• v.20 no.1
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• pp.87-96
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• 2021

Ground motions recorded in near-fault sites, where the rupture propagates toward the site, are significantly different from those observed in far-fault regions. In this research, finite element modeling is used to investigate the effect of pile cap stiffness on the seismic response of soil-pile-structure systems under near-fault ground motions. The Von Wolffersdorff hypoplastic model with the intergranular strain concept is applied for modeling of granular soil (sand) and the behavior of structure is considered to be non-linear. Eight fault-normal near-field ground motion records, recorded on rock, are applied to the model. The numerical method developed is verified by comparing the results with an experimental test (shaking table test) for a soil-pile-structure system. The results, obtained from finite element modeling under near-fault ground motions, show that when the value of cap stiffness increases, the drift ratio of the structure decreases, whereas the pile relative displacement increases. Also, the residual deformations in the piles are due to the non-linear behavior of soil around the piles.

• Advances in aircraft and spacecraft science
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• v.11 no.2
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• pp.195-213
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• 2024

This article deals with the changes in flow air properties across an oblique shock wave for a real gas. The flow through is investigated to find a general form for oblique shock waves. The main objective of this work will result in the development of a new numerical algorithm to determine the effect of the stagnation pressure on supersonic flow for thermally and calorically imperfect gases with a molecular dissociation threshold, thus giving a better affinity to the physical behavior of the waves. So, the effects of molecular size and intermolecular attraction forces are used to correct a state equation, emphasizing the determination of the impact of upstream stagnation parameters on oblique shock waves. As results, the specific heat pressure does not remain constant and varies with the temperature and density. At Mach numbers greater than 2.0, the temperature rise considerably, and the density rise is well above, that predicted assuming ideal gas behavior. It is shown that caloric imperfections in air have an appreciable effect on the parameters developed in the processes is considered. Computation of errors between the present model based on real gas theory and a perfect gas model shows that the influence of the thermal and caloric imperfections associated with a real gas is important and can rise up to 16%.

• Biomolecules & Therapeutics
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• v.24 no.5
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• pp.489-494
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• 2016

Neuropathic pain (NPP) is the main culprit among chronic pains affecting the normal life of patients. Procaine is a frequently-used local anesthesia with multiple efficacies in various diseases. However, its role in modulating NPP has not been reported yet. This study aims at uncovering the role of procaine in NPP. Rats were pretreated with procaine by intrathecal injection. Then NPP rat model was induced by sciatic nerve chronic compression injury (CCI) and behavior tests were performed to analyze the pain behaviors upon mechanical, thermal and cold stimulations. Spinal expression of Janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3) was detected by qRT-PCR and western blot. JAK2 was also overexpressed in procaine treated model rats for behavior tests. Results showed that procaine pretreatment improved the pain behaviors of model rats upon mechanical, thermal and cold stimulations, with the best effect occurring on the $15^{th}$ day post model construction (p<0.05). Procaine also inhibited JAK2 and STAT3 expression in both mRNA (p<0.05) and protein levels. Overexpression of JAK2 increased STAT3 level and reversed the improvement effects of procaine in pain behaviors (p<0.01). These findings indicate that procaine is capable of attenuating NPP, suggesting procaine is a potential therapeutic strategy for treating NPP. Its role may be associated with the inhibition on JAK2/STAT3 signaling.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.108-116
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• 2019

In this paper, we propose a method to apply artificial intelligence technology efficiently to integrated security control technology. In other words, by applying machine learning learning to artificial intelligence based on big data collected in integrated security control system, cyber attacks are detected and appropriately responded. As technology develops, many large capacity Is limited to analyzing individual logs. The analysis method should also be applied to the integrated security control more quickly because it needs to correlate the logs of various heterogeneous security devices rather than one log. We have newly proposed an integrated security service model based on artificial intelligence, which analyzes and responds to these behaviors gradually evolves and matures through effective learning methods. We sought a solution to the key problems expected in the proposed model. And we developed a learning method based on normal behavior based learning model to strengthen the response ability against unidentified abnormal behavior threat. In addition, future research directions for security management that can efficiently support analysis and correspondence of security personnel through proposed security service model are suggested.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4A
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• pp.267-279
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• 2009

A numerical model that can simulate the nonlinear behavior of ultra high strength fiber reinforced concrete (UHSFRC) structures subjected to monotonic loading is introduced. The material properties of UHSFRC, such as compressive and tensile strength or elastic modulus, are different from normal strength reinforced concrete. The uniaxial compressive stress-strain relationship of UHSFRC is designed on the basis of experimental result, and the equivalent uniaxial stress-strain relationship is introduced for proper estimation of UHSFRC structures. The steel is uniformly distributed over the concrete matrix with particular orientation angle. In advance, this paper introduces a numerical model that can simulate the tension-stiffening behavior of tension part of the axial member on the basis of the bond-slip relationship. The reaction of steel fiber is considered for the numerical model after cracks of the concrete matrix with steel fibers are formed. Finally, the introduced numerical model is validated by comparison with test results for idealized UHSFRC beams.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.857-866
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• 2003

For detecting an intrusion based on the anomaly of a user's activities, previous works are concentrated on statistical techniques in order to analyze an audit data set. However. since they mainly analyze the average behavior of a user's activities, some anomalies can be detected inaccurately. In this paper, a new clustering algorithm for modeling the normal pattern of a user's activities is proposed. Since clustering can identify an arbitrary number of dense ranges in an analysis domain, it can eliminate the inaccuracy caused by statistical analysis. Also, clustering can be used to model common knowledge occurring frequently in a set of transactions. Consequently, the common activities of a user can be found more accurately. The common knowledge is represented by the occurrence frequency of similar data objects by the unit of a transaction as veil as the common repetitive ratio of similar data objects in each transaction. Furthermore, the proposed method also addresses how to maintain identified common knowledge as a concise profile. As a result, the profile can be used to detect any anomalous behavior In an online transaction.

• Composites Research
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• v.36 no.2
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• pp.117-125
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• 2023

This paper proposes a new finite element formulation based on enhanced first-order shear deformation theory including the transverse normal strain effect via the mixed formulation (EFSDTM-TN) for the effective thermo-mechanical analysis of laminated composite structures. The main objective of the EFSDTM-TN is to provide an accurate and efficient solution in describing the thermo-mechanical behavior of laminated composite structures by systematically establishing the relationship between two independent fields (displacement and transverse stress fields) via the mixed formulation. Another key feature is to consider the thermal strain effect without additional unknown variables by introducing a refined transverse displacement field. In the finite element formulation, an eight-node isoparametric plate element is newly developed to implement the advantage of the EFSDTM-TN. Numerical solutions for the thermo-mechanical behavior of laminated composite structures are compared with those available in the open literature to demonstrate the numerical performance of the proposed finite element model.

• Steel and Composite Structures
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• v.50 no.1
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• pp.1-13
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• 2024

The objective of this research is to study experimentally and numerically the behavior of steel beam columns with openings. Although the presence of openings in the beam columns is inevitable, finding ways to maintain strength is crucial. The studied parameters are opening shape, the ratio between opening height to specimen height, the percentage of opening location from support to beam column length, and web slenderness. Experimental tests are conducted including twelve specimens to study the effect of these parameters and record failure load, load deflection curve, and stress strain curve. Two failure modes are observed: local and flexural buckling. Interaction curves plotted from finite element model analysis are also used to expand the parametric study. Changing the location of the opening can decrease failure load by up to 7% and 60% in both normal and moment ratios respectively. Increasing the opening dimension can lead to a drop in the axial ratio by up to 29% and in the moment ratio by up to 74%. The weakest beam column behavior is noticed in specimens with rectangular openings which results from uneven and concentrated stresses around the opening. The main results of this research illustrate that the best location for opening is at 40% - 50% from beam column support. Also, it is advisable to use circular openings instead of rectangular openings in specimens having slender webs because moment ratios are raised by 85% accompanied by a rise in normal ratios by 9%.

• Steel and Composite Structures
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• v.14 no.3
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• pp.267-282
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• 2013

This paper presents the behavior and design of axially loaded normal and steel fiber reinforced concrete in-filled steel tube (SFRCFT) columns, to examine the contribution of steel fibers on the compressive strength of the composite columns. Non-linear finite element analysis model (FEA) using ANSYS software has been developed and used in the analysis. The confinement effect provided by the steel tube is considered in the analysis. Comparisons of the analytical model results, along with other available experimental outputs from literature have been done to verify the structural model. The compressive strength and stiffness of SFRC composite columns were discussed, and the interpretation of the FEA model results has indicated that, the use of SFRC as infill material has a considerable effect on the strength and stiffness of the composite column. The analytical model results were compared with the existing design methods of composite columns - (EC4, AISC/LRFD and the Egyptian code of Practice for Steel Construction, ECPSC/LRFD). The comparison indicated that, the results of the FEA model were evaluated to an acceptable limit of accuracy. The code design equations were modified to introduce the steel fiber effect and compared with the results of the FEA model for verification.

• Journal of KIISE:Software and Applications
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• v.37 no.7
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• pp.568-572
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• 2010

Self-healing is one of the techniques that assure dependability of mission-critical system. Self-healing consists of fault detection and fault recovery and fault detection is important first step that enables fault recovery but it causes overhead. We can detect fault based on model, the detection tasks that notify system's behavior and compare normal behavior model and system's behavior are heavy jobs. In this paper, we propose architecture-based multi-level self-adaptive monitoring method that complements model-based fault detection. The priority of fault detection per component is different in the software architecture. Because the seriousness and the frequency of fault per component are different. If the monitor is adapted to intensive to the component that has high priority of monitoring and loose to the component that has low priority of monitoring, the overhead can be decreased and the efficiency can be maintained. Because the environmental changes of software and the architectural changes bring the changes at the priority of fault detection, the monitor learns the changes of fault frequency and that is adapted to intensive to the component that has high priority of fault detection.