• Title/Summary/Keyword: Network Presence

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Growing Hadiths Ontology

  • Alamri, Salah
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.317-322
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    • 2021
  • The modern technological era has brought about the Semantic Web. Ontologies are essential to achieve the vision of the Semantic Web. Ontologies enable machines to understand data. The Arabic Language currently does not have a significant presence on the Web. To achieve a comparable level of Arabic access to other important languages, further work is needed to build Arabic ontologies. A goal is to design and create a robust Arabic ontology that represents the concepts from a large and significant subset of Arabic. We use a source of Hadiths (prophet saying and deeds) from Riyadh As-Saliheen. Preliminary results are very promising.

MNE's Ability to Mitigate the FX Exposure: Subsidiary Network and Pass-through Ability

  • Cho, Hyejin
    • East Asian Journal of Business Economics (EAJBE)
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    • v.6 no.4
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    • pp.1-12
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    • 2018
  • Purpose - This paper tests the effect of the structure of manufacturing and marketing subsidiary network on FX exposure of Korean MNEs. Furthermore, the moderating effect of pass-through ability on the relationship between the subsidiary network and FX exposure is explored. Research design and methodology - This study utilizes a sample of 309 Korean MNEs constructed from database offered by KOTRA and KIS-VALUE. Results - As operational flexibility arising from having operations in multiple locations provides an option for firms to tackle FX exposure, greater breadth of manufacturing subsidiary network reduces FX exposure, and greater depth increases FX exposure. However, both the breadth and depth of marketing subsidiary network decrease FX exposure due to the firm's higher level of market presence and knowledge to devise an appropriate marketing strategy that can buffer adverse exchange rate movement. Such an effect is intensified when MNE's have FX exposure pass-through ability stemming from differentiated good. Conclusions - Empirical findings suggest that types and structure of Korean MNEs' foreign subsidiary network are closely related to the level of FX exposure they are experiencing. Also, they can utilize marketing subsidiary network more efficiently when having a higher R&D intensity.

A Study on Response Technique of Routing Attack under Wireless Ad Hoc Network. Environment (Wireless Ad Hoc Network환경에서의 라우팅 공격 대응 기법에 관한 연구)

  • Yang, Hwan Seok
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.1
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    • pp.105-112
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    • 2014
  • The utilization of Wireless Ad Hoc Network which can build easily network using wireless device in difficult situation to build network is very good. However, it has security threat element because it transfers data by only forwarding of wireless devices. The measures against this should be prepared because damage by especially routing attack can affect the entire network. It is hard to distinguish malicious node and normal node among nodes composing network and it is not easy also to detect routing attack and respond to this. In this paper, we propose new method which detect routing attack and can respond to this. The amount of traffic in all nodes is measured periodically to judge the presence or absence of attack node on the path set. The technique that hides inspection packet to suspected node and transmits is used in order to detect accurately attack node in the path occurred attack. The experiment is performed by comparing SRAODA and SEAODV technique to evaluate performance of the proposed technique and the excellent performance can be confirmed.

Effect of associating polymer on the dispersion stability and rheology of suspensions

  • Otsubo, Yasufumi;Horigome, Misao
    • Korea-Australia Rheology Journal
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    • v.15 no.1
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    • pp.27-33
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    • 2003
  • Associating polymers are hydrophilic long-chain molecules to which a small amount of hydrophobic groups (hydrophobes) is incorporated. In aqueous solution, the association interactions result in the formation of three-dimensional network through flowerlike micelles at high concentrations. In colloidal suspensions, the associating polymers act as flocculated by bridging mechanism. The rheological properties of suspensions flocculated by associating polymers end-capped with hydrophobes are studied in relation to the bridging conformation. At low polymer concentrations, the polymer chains effectively form bridges between particles by multichain association. The suspensions are highly flocculated and show typical viscoelastic responses. When the polymer concentration is increased above the absorbance at saturation, the excess polymer chains remaining in the solution phase build up three-dimensional network by associating interactions. Since the presence of particles does not significantly influence the network structures in the medium, the relative viscosity, which gives a measure of the degree of flocculation is decreased with increasing polymer concentration. The bridging conformation and flocculation level vary strongly depending on the polymer concentrations.

Static Switch Controller Based on Artificial Neural Network in Micro-Grid Systems

  • Saeedimoghadam, Mojtaba;Moazzami, Majid;Nabavi, Seyed. M.H.;Dehghani, Majid
    • Journal of Electrical Engineering and Technology
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    • v.9 no.6
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    • pp.1822-1831
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    • 2014
  • Micro-grid is connected to the main power grid through a static switch. One of the critical issues in micro-grids is protection which must disconnect the micro-grid from the network in short-circuit contingencies. Protective methods of micro-grid mainly follow the model of distribution system protection. This protection scheme suffers from improper operation due to the presence of single-phase loads, imbalance of three-phase loads and occurrence of power swings in micro-grid. In this paper, a new method which prevents from improper performance of static micro-grid protection is proposed. This method works based on artificial neural network (ANN) and able to differentiate short circuit from power swings by measuring impedance and the rate of impedance variations in PCC bus. This new technique provides a protective system with higher reliability.

Optical Flow Estimation Using the Hierarchical Hopfield Neural Networks (계층적 Hopfield 신경 회로망을 이용한 Optical Flow 추정)

  • 김문갑;진성일
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.3
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    • pp.48-56
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    • 1995
  • This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.

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Consensus of Linear Multi-Agent Systems with an Arbitrary Network Delay (임의의 네트워크 지연을 갖는 선형 다개체시스템의 일치)

  • Lee, Sungryul
    • Journal of IKEEE
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    • v.18 no.4
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    • pp.517-522
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    • 2014
  • This paper investigates the consensus problem for linear multi-agent systems with an arbitrary network delay. The sufficient conditions for a state consensus of linear multi-agent systems are provided by using linear matrix inequalities. Moreover, it is shown that under the proposed protocol, the consensus can be achieved even in the presence of an arbitrarily large network delay. Finally, an illustrative example is given in order to show the effectiveness of our design method.

Numerical study on the effect of crack network representation on water content in cracked soil

  • Krisnanto, Sugeng;Rahardjo, Harianto;Leong, Eng Choon
    • Geomechanics and Engineering
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    • v.21 no.6
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    • pp.537-549
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    • 2020
  • The presence of cracks changes the water content pattern during seepage through a cracked soil as compared to that of intact soil. In addition, several different crack networks may form in one soil type. These two factors result in a variation of water contents in the soil matrix part of a cracked soil during seepage. This paper presents an investigation of the effect of crack network representation on the water content of the soil matrix part of cracked soil using numerical models. A new method for the numerical generation of crack networks incorporating connections among crack endpoints was developed as part of the investigation. Numerical analysis results indicated that the difference in the point water content was large, whereas the difference in the average water content was relatively small, indicating the uniqueness of the crack network representation on the average water content of the soil matrix part of cracked soil.

Shear lag prediction in symmetrical laminated composite box beams using artificial neural network

  • Chandak, Rajeev;Upadhyay, Akhil;Bhargava, Pradeep
    • Structural Engineering and Mechanics
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    • v.29 no.1
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    • pp.77-89
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    • 2008
  • Presence of high degree of orthotropy enhances shear lag phenomenon in laminated composite box-beams and it persists till failure. In this paper three key parameters governing shear lag behavior of laminated composite box beams are identified and defined by simple expressions. Uniqueness of the identified key parameters is proved with the help of finite element method (FEM) based studies. In addition to this, for the sake of generalization of prediction of shear lag effect in symmetrical laminated composite box beams a feed forward back propagation neural network (BPNN) model is developed. The network is trained and tested using the data base generated by extensive FEM studies carried out for various b/D, b/tF, tF/tW and laminate configurations. An optimum network architecture has been established which can effectively learn the pattern. Computational efficiency of the developed ANN makes it suitable for use in optimum design of laminated composite box-beams.

Neural Network Application to the Bad Data Detection Using Autoregressive filter in Power System (AR 필터에 의한 전력계통의 불량데이타검출에서 신경회로망의 응용)

  • Lee, H.S.;Yang, S.O.;Park, J.H.
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.131-133
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    • 1993
  • In the power system state estimation, the J(x)-index test and normalized residuals $r_N$ have been used to detect the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network model using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional methods and simulation results show the good performance in the bad data identification based on the neural network under sample power system.

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