• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.111-118
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• 2024

In general network-based intrusion detection system is designed to detect malicious behavior directed at a network or its resources. The key goal of this paper is to look at network data and identify whether it is normal traffic data or anomaly traffic data specifically for accounting information systems. In today's world, there are a variety of principles for detecting various forms of network-based intrusion. In this paper, we are using supervised machine learning techniques. Classification models are used to train and validate data. Using these algorithms we are training the system using a training dataset then we use this trained system to detect intrusion from the testing dataset. In our proposed method, we will detect whether the network data is normal or an anomaly. Using this method we can avoid unauthorized activity on the network and systems under that network. The Decision Tree and K-Nearest Neighbor are applied to the proposed model to classify abnormal to normal behaviors of network traffic data. In addition to that, Logistic Regression Classifier and Support Vector Classification algorithms are used in our model to support proposed concepts. Furthermore, a feature selection method is used to collect valuable information from the dataset to enhance the efficiency of the proposed approach. Random Forest machine learning algorithm is used, which assists the system to identify crucial aspects and focus on them rather than all the features them. The experimental findings revealed that the suggested method for network intrusion detection has a neglected false alarm rate, with the accuracy of the result expected to be between 95% and 100%. As a result of the high precision rate, this concept can be used to detect network data intrusion and prevent vulnerabilities on the network.

• Computers and Concrete
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• v.34 no.1
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• pp.93-122
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• 2024

One well-known reason for using Fiber Reinforced Polymer (FRP) composites is to improve concrete strength and strain capacity via external confinement. Hence, various studies have been undertaken to offer a good illustration of the response of FRP-wrapped concrete for practical design intents. However, in such studies, the strength and strain of the confined concrete were predicted using regression analysis based on a limited number of test data. This study presents an approach based on artificial neural networks (ANNs) to develop models to predict the strength and strain at maximum stress enhancement of circular concrete cross-sections confined with different FRP types (Carbone, Glass, Aramid). To achieve this goal, a large test database comprising 493 axial compression experiments on FRP-confined concrete samples was compiled based on an extensive review of the published literature and used to validate the predicted artificial intelligence techniques. The ANN approach is currently thought to be the preferred learning technique because of its strong prediction effectiveness, interpretability, adaptability, and generalization. The accuracy of the developed ANN model for predicting the behavior of FRP-confined concrete is commensurate with the experimental database compiled from published literature. Statistical measures values, which indicate a better fit, were observed in all of the ANN models. Therefore, compared to existing models, it should be highlighted that the newly developed models based on FRP type are remarkably accurate.

• Steel and Composite Structures
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• v.52 no.3
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• pp.327-341
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• 2024

This paper is the first in a series of articles dealing with the study and analysis of imperfections in thin-walled, cold-formed steel sections with modified cross-sectional shapes. A study was conducted, using 3D scanning techniques, to determine the most vulnerable geometric imperfections in the profiles. Based on a review of the literature, it has been determined that few researchers are studying thin-walled sections with modified cross-sectional shapes. Each additional bend in the section potentially generates geometric imperfections. Geometric imperfections significantly affect the resistance to loss of stability, which is crucial when analyzing thin-walled structures. In addition, the most critical locations along the length where these imperfections occur were determined. Based on the study, it was found that geometric imperfections cause a reduction in critical load. It should be noted that the tests performed are preliminary studies, based on which a program of further research will be developed. In addition, the article presents the current state of knowledge in the authors' field of interest. The future objective is to ascertain if these imperfections could potentially contribute positively to structural integrity. This enhanced understanding may pave the way for novel methodologies in structural engineering, wherein imperfections are viewed not solely as flaws but also as elements that could enhance the end product.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.6
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• pp.89-96
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• 2008

The purpose of this study is to investigate the flexural strengthening effectiveness for the beams reinforced with NSM CFRP strips. To accomplish this objective, concrete T beams were made and tested. From this study, it is found that the flexural stiffness and strength of the beams reinforced with NSM strips were significantly improved compared to the beams without CFRP strip. The maximum increase of flexural strength was 247%. Failure of the beam reinforced with NSM was initiated by a part of separation of NSM strips along the longitudinal direction, and the second failure of strips was investigated. After the first rupture of the NSM strips, the load dropped suddenly and the second rupture was succeeded. This result shows that a perfect composite reaction with NSM strips and concrete is possible in the beam reinforced with NSM CFRP strips the NSM strips and Near surface mounted(NSM) is one of the most recent and promising strengthening techniques for reinforced concrete structures.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.365-374
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• 2011

Recently, malicious video classification and filtering techniques are of practical interest as ones can easily access to malicious multimedia contents through the Internet, IPTV, online social network, and etc. Considerable research efforts have been made to developing malicious video classification and filtering systems. However, the malicious video classification and filtering is not still being from mature in terms of reliable classification/filtering performance. In particular, the most of conventional approaches have been limited to using only the spatial features (such as a ratio of skin regions and bag of visual words) for the purpose of malicious image classification. Hence, previous approaches have been restricted to achieving acceptable classification and filtering performance. In order to overcome the aforementioned limitation, we propose new malicious video classification framework that takes advantage of using both the spatial and temporal features that are readily extracted from a sequence of video frames. In particular, we develop the effective temporal features based on the motion periodicity feature and temporal correlation. In addition, to exploit the best data fusion approach aiming to combine the spatial and temporal features, the representative data fusion approaches are applied to the proposed framework. To demonstrate the effectiveness of our method, we collect 200 sexual intercourse videos and 200 non-sexual intercourse videos. Experimental results show that the proposed method increases 3.75% (from 92.25% to 96%) for classification of sexual intercourse video in terms of accuracy. Further, based on our experimental results, feature-level fusion approach (for fusing spatial and temporal features) is found to achieve the best classification accuracy.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.515-523
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• 2020

This study aims to improve the flow and noise performances of an axial-flow fan for cooling the machine room in a refrigerator by using airfoil-cascade analysis and surface ridge shape. First, the experimental evaluations using a fan performance tester and an anechoic chamber are performed to analyze the flow and noise performances of the existing fan system. Then, the corresponding flow and noise performances are numerically assessed using the Computational Fluid Dynamics (CFD) techniques and the Ffowcs-Williams and Hawkings (FW-H) equation, and the validity of numerical results are confirmed through their comparisons with the experimental results. The analysis for the flow of a cascade of airfoils constructed from the existing fan blades is performed, and the pitch angles for the maximum lift-to-drag ratio are determined. The improved flow performance of the new fan applied with the optimum pitch angles is confirmed. Then, the fan blades with surface ridges on their pressure sides are devised, and the reduction of aerodynamic noise of the ridged fan is numerically confirmed. Finally, the prototype of the final fan model is manufactured, and improvements in the flow and noise performances of the prototype are experimentally confirmed.

• Structural Engineering and Mechanics
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• v.63 no.3
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• pp.361-370
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• 2017

Through the use of finite element analysis and acoustic emission techniques we have evaluated the interfacial failure of a carbon fiber reinforced polymer (CFRP) repair patch on a notched aluminum substrate. The repair of cracks is a very common and widely used practice in the aeronautics field to extend the life of cracked sheet metal panels. The process consists of adhesively bonding a patch that encompasses the notched site to provide additional strength, thereby increasing life and avoiding costly replacements. The mechanical strength of the bonded joint relies mainly on the bonding of the adhesive to the plate and patch stiffness. Stress concentrations at crack tips promote disbonding of the composite patch from the substrate, consequently reducing the bonded area, which makes this a critical aspect of repair effectiveness. In this paper we examine patch disbonding by calculating the influence of notch tip stress on disbond area and verify computational results with acoustic emission (AE) measurements obtained from specimens subjected to uniaxial tension. The FE results showed that disbonding first occurs between the patch and the substrate close to free edge of the patch followed by failure around the tip of the notch, both highest stress regions. Experimental results revealed that cement adhesion at the aluminum interface was the limiting factor in patch performance. The patch did not appear to strengthen the aluminum substrate when measured by stress-strain due to early stage disbonding. Analysis of the AE signals provided insight to the disbond locations and progression at the metal-adhesive interface. Crack growth from the notch in the aluminum was not observed until the stress reached a critical level, an instant before final fracture, which was unaffected by the patch due to early stage disbonding. The FE model was further utilized to study the effects of patch fiber orientation and increased adhesive strength. The model revealed that the effectiveness of patch repairs is strongly dependent upon the combined interactions of adhesive bond strength and fiber orientation.

• Journal of Science and Technology Studies
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• v.10 no.2
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• pp.107-141
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• 2010

Visualization techniques are transformed into reliable representations through socio-technological processes which include the agreement on the instrument and the embodiment of practices in relevant scientific communities. Visual representations thus produced are justified by realistic and epistemic virtues in science. This paper analyzes different visual images presented in the scientific papers of two research groups who argue different theories about the mechanism of face perception. These two scientific groups use the same fMRI technology; yet, different experimental paradigms and visual stimuli change their hypotheses into distinct testable theories, which in turn lead to different evidences to support their own theories. Visual evidences are intermediate representations which lie between fMRI brain images and scientific theories, and theoretical models obtain the scientific value based on the consistency in the chain of visual representations. This study shows that representations in science tend to be good representations within the context of scientific communities. It will provide a chance to think of the value and limit of the scientific knowledge

• Journal of the Mineralogical Society of Korea
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• v.28 no.2
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• pp.127-133
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• 2015

Li-bearing muscovite is commonly found along with trioctahedral lepidolite in granitic pegmatites. Structurally, $Li^+$ ions can replace $K^+$ ions in the interlayer (Int) of muscovite or incorporate into vacancies of the dioctahedral sheet (Sub). However, detailed mechanism of the lithium incorporation into muscovite is challenging to investigate using experimental techniques alone. In the current study, density functional theory (DFT) has been applied to examine the crystal structure and energy variation when $Li^+$ resides in the interlayer or the octahedral sheet. Depending on the position of $Li^+$ (i.e., Int vs. Sub), DFT showed significant differences in the mica's structures such as lattice parameters, sheet thickness, interlayer separation, and OH angles with respect to the ab plane. DFT further showed that, in pure muscovite, $Li^+$ has a lower energy when it is located in Int than Sub. By contrast, in the case of $Fe^{2+}$ substitution into the octahedral sheet, $Li^+$ has a lower energy in Sub than in Int. These results imply that $Li^+$ incorporates into the Al octahedral sheets only when the octahedral sheets possess structural charges, suggesting cation substitution in the octahedral sheets plays an important role in the Li incorporation mechanism into muscovite. They can also explain the experimental observation about the positive relationship between $Fe^{2+}$ and $Li^+$ amounts in Li-bearing muscovite.

• Magazine of the Korea Concrete Institute
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• v.6 no.2
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• pp.97-107
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• 1994

The objective of this study is to develop polymer-impregnated concrete(PIC), which is a newly developed composite material made by impregnating polymer impregnanls into hardened normal concrete, and to develop analytical techniques for its proper applications. Crystalline methyl methacrylate(MMA) is chosen as a monomer of polymer impregnants. The corrlpositions of polymer impregnants and producing processes are developed by analyzing the effects of penetration, polymerization, thermal safety, and strengthening characteristics. On t he basis of experimental results of this study, various strength characteristics and stress strain constitutive relations are formulated in terms of the compressive strength of normal concrete and the polymer loadings, which can be applied for analysis and design of PIC members. In order to provide a model for fracture analysis of flexural members, fracture toughness, fracture energy, critical crack width, and tension softening relations near crack tip are also formulated in terms of member depth, initial notch depth, and the flexural strength of normal concrete. The structural analysis procedure and the finite element computer program developed in the study are applicable to evaluate elastic behavior, ultimate strength, and tension softening behavior of MMA type PIC structural members subject to various loading conditions. The accuracy and effectiveness of the developed computer program is examined by comparing the anal ytical results with the experimental results. Therefore, it is concluded that the developed structural analysis procedure and the finite element computer program are applicable to analysis and design of in-situ and precast PIC structural members.