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Journal articles on the topic 'Network-hardening'

Author: Grafiati

Published: 29 June 2021

Last updated: 17 February 2022

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1

Zhao, Chao, Huiqiang Wang, Junyu Lin, Hongwu Lv, and Yushu Zhang. "A Generation Method of Network Security Hardening Strategy Based on Attack Graphs." International Journal of Web Services Research 12, no. 1 (2015): 45–61. http://dx.doi.org/10.4018/ijwsr.2015010104.

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Analyzing attack graphs can provide network security hardening strategies for administrators. Concerning the problems of high time complexity and costly hardening strategies in previous methods, a method for generating low cost network security hardening strategies is proposed based on attack graphs. The authors' method assesses risks of attack paths according to path length and the common vulnerability scoring system, limits search scope with a threshold to reduce the time complexity, and lowers cost of hardening strategies by using a heuristic algorithm. The experimental results show that the authors' method has good scalability, and significantly reduces cost of network security hardening strategies with reasonable running time.

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2

Manzanares, Antonio Izquierdo. "Hardening Network Infrastructure: Not Suitable for Everyone." IEEE Distributed Systems Online 8, no. 10 (2007): 4. http://dx.doi.org/10.1109/mdso.2007.4384584.

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3

Wang, Lingyu, Steven Noel, and Sushil Jajodia. "Minimum-cost network hardening using attack graphs." Computer Communications 29, no. 18 (2006): 3812–24. http://dx.doi.org/10.1016/j.comcom.2006.06.018.

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4

Pan, Zhong Feng, Gui Cheng Wang, Chong Lue Hua, and Hong Jie Pei. "Research and Development of LM Neural Network Prediction System for Grind-Hardening." Key Engineering Materials 416 (September 2009): 248–52. http://dx.doi.org/10.4028/www.scientific.net/kem.416.248.

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An improved neural network based on L-M algorithm has been applied to the prediction of the grind-hardening parameters against to the slow convergence rate of conventional BP neural network. And the the neural network model for grind-hardening is established. The neural network prediction system for grind-hardening process has been developed based on L-M algorithm. The functions of system is analyzed, particularly and some pivotal technology to realize the system are put forward.

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5

Borbor, Daniel, Lingyu Wang, Sushil Jajodia, and Anoop Singhal. "Surviving unpatchable vulnerabilities through heterogeneous network hardening options." Journal of Computer Security 26, no. 6 (2018): 761–89. http://dx.doi.org/10.3233/jcs-171106.

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6

Myung, David, Wongun Koh, Jungmin Ko, et al. "Biomimetic strain hardening in interpenetrating polymer network hydrogels." Polymer 48, no. 18 (2007): 5376–87. http://dx.doi.org/10.1016/j.polymer.2007.06.070.

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7

Lambiase, F., A. M. Di Ilio, and A. Paoletti. "Prediction of Laser Hardening by Means of Neural Network." Procedia CIRP 12 (2013): 181–86. http://dx.doi.org/10.1016/j.procir.2013.09.032.

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8

Bouzid, Mehdi, and Emanuela Del Gado. "Network Topology in Soft Gels: Hardening and Softening Materials." Langmuir 34, no. 3 (2017): 773–81. http://dx.doi.org/10.1021/acs.langmuir.7b02944.

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9

Wu, Xiao Ling, and Fei Ren. "Research on the Prediction Model of Laser Surface Hardening Index on Cylinder Liner Based on RBF." Advanced Materials Research 148-149 (October 2010): 215–18. http://dx.doi.org/10.4028/www.scientific.net/amr.148-149.215.

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Based on the data obtained from the perpendicular experiment of laser surface hardening on HT150 cylinder liner of a certain motor engine, a Radial Basis Function (RBF) neural network prediction model of laser surface hardening index about HT150 cylinder liner is established by Matlab neural network toolbox in this paper. The parameters of input layer are affirmed by analyzing influential factors of the hardened index ,and the best form of the network is affirmed by selecting suitable spread in function-newrb( ),and as a result, the prediction accuracy and the adaptability of the network are improved. The result of testing the model indicates that the model based on RBF neural network has a good generalizing capability. Compared with traditional Back-Propagation Network (BP network), the result indicates that RBF has better accuracy and adaptability.

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Kemp, R., G. A. Cottrell, H. K. D. H. Bhadeshia, G. R. Odette, T. Yamamoto, and H. Kishimoto. "Neural-network analysis of irradiation hardening in low-activation steels." Journal of Nuclear Materials 348, no. 3 (2006): 311–28. http://dx.doi.org/10.1016/j.jnucmat.2005.09.022.

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11

Yang, Tung Sheng, and Huai Shiun Lu. "Predictions of Springback of Strain-Hardening Material in U-Shaped Bending Process." Key Engineering Materials 419-420 (October 2009): 481–84. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.481.

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This study applies the finite element method (FEM) in conjunction with an abductive network to predict springback of different strain-hardening material in U-shaped bending process.Springback is investigated for different material parameters, such as strength coefficient of material, strain-hardening exponent and Young’s modulus, by finite element analysis during U-shaped bending process. The abductive network is then applied to synthesize the data sets obtained from the numerical simulations. Prediction results of the springback of different strain-hardening material in U-shaped bending process are consistent with the results obtained from FEM simulation quite well. After employing the predictive model can provide valuable references in prediction of the springback of U-shaped bending process under a suitable range of material parameters.

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12

Jun-chun, MA, WANG Yong-jun, SUN Ji-yin, and CHEN Shan. "A Minimum Cost of Network Hardening Model Based on Attack Graphs." Procedia Engineering 15 (2011): 3227–33. http://dx.doi.org/10.1016/j.proeng.2011.08.606.

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13

Kundu, Arkadeep, and Soumya K. Ghosh. "A multi-objective search strategy to select optimal network hardening measures." International Journal of Decision Support Systems 1, no. 1 (2015): 130. http://dx.doi.org/10.1504/ijdss.2015.067283.

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14

Theocaris, Pericles S., and P. D. Panagiotopoulos. "Generalised hardening plasticity approximated via anisotropic elasticity: A neural network approach." Computer Methods in Applied Mechanics and Engineering 125, no. 1-4 (1995): 123–39. http://dx.doi.org/10.1016/0045-7825(94)00769-j.

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15

Nimpaiboon, Adun, Sureerut Amnuaypornsri, and Jitladda T. Sakdapipanich. "OBSTRUCTION OF STORAGE HARDENING IN NR BY USING POLAR CHEMICALS." Rubber Chemistry and Technology 89, no. 2 (2016): 358–68. http://dx.doi.org/10.5254/rct.16.84825.

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ABSTRACT The effect of the polar chemicals phenol, diethylene glycol, and hydroxylamine hydrochloride on obstruction of storage hardening in NR was examined. A decrease in gel content and molecular weight of NR was observed after addition of diethylene glycol and hydroxylamine hydrochloride, whereas no significant change was observed after addition of phenol. The storage hardening behavior of NR containing these polar chemicals was investigated by accelerated storage with phosphorus pentoxide. The gel content, Mooney viscosity, and Wallace plasticity values of NR containing phenol increased obviously during accelerated storage hardening, whereas these values increased gradually in the presence of diethylene glycol and were constant in the presence of hydroxylamine hydrochloride. The efficiency of these polar chemicals for inhibiting storage hardening in NR follow the order hydroxylamine hydrochloride, diethylene glycol, and phenol, respectively. The mechanism of network formation during accelerated storage hardening was proposed to involve phospholipids at the chain ends of the NR molecule. Molecular structure analysis by Fourier transform infrared spectroscopy suggested that hydroxylamine inhibits storage hardening in NR by chemical interaction with phospholipid, apart from its polarity.

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16

Liu, Gu, Liu-ying Wang, Gui-ming Chen, and Shao-chun Hua. "Parameters Optimization of Plasma Hardening Process Using Genetic Algorithm and Neural Network." Journal of Iron and Steel Research International 18, no. 12 (2011): 57–64. http://dx.doi.org/10.1016/s1006-706x(12)60010-7.

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17

Li, Changhong, Chenbo Yin, and Xingtian Xu. "Hybrid optimization assisted deep convolutional neural network for hardening prediction in steel." Journal of King Saud University - Science 33, no. 6 (2021): 101453. http://dx.doi.org/10.1016/j.jksus.2021.101453.

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18

Weiss, Stephanie, Regina Seidl, Waltraud Kessler, Rudolf W. Kessler, Edith M. Zikulnig-Rusch, and Andreas Kandelbauer. "Unravelling the Phases of Melamine Formaldehyde Resin Cure by Infrared Spectroscopy (FTIR) and Multivariate Curve Resolution (MCR)." Polymers 12, no. 11 (2020): 2569. http://dx.doi.org/10.3390/polym12112569.

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Here, we study resin cure and network formation of solid melamine formaldehyde pre-polymer over a large temperature range via dynamic temperature curing profiles. Real-time infrared spectroscopy is used to analyze the chemical changes during network formation and network hardening. By applying chemometrics (multivariate curve resolution, MCR), the essential chemical functionalities that constitute the network at a given stage of curing are mathematically extracted and tracked over time. The three spectral components identified by MCR were methylol-rich, ether linkages-rich and methylene linkages-rich resin entities. Based on dynamic changes of their characteristic spectral patterns in dependence of temperature, curing is divided into five phases: (I) stationary phase with free methylols as main chemical feature, (II) formation of flexible network cross-linked by ether linkages, (III) formation of rigid, ether-cross-linked network, (IV) further hardening via transformation of methylols and ethers into methylene-cross-linkages, and (V) network consolidation via transformation of ether into methylene bridges. The presented spectroscopic/chemometric approach can be used as methodological basis for the functionality design of MF-based surface films at the stage of laminate pressing, i.e., for tailoring the technological property profile of cured MF films using a causal understanding of the underlying chemistry based on molecular markers and spectroscopic fingerprints.

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19

Waheed, Faisal, and Maaruf Ali. "Hardening CISCO Devices based on Cryptography and Security Protocols - Part II: Implementation and Evaluation." Annals of Emerging Technologies in Computing 2, no. 4 (2018): 11–27. http://dx.doi.org/10.33166/aetic.2018.04.002.

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This second part covers the implementation, testing, critical evaluation, conclusion and further study. It concentrates on the actual implementation details of hardening of network devices by referring to the hardware and software components, device operating system’s features, management controls, access-list restrictions, operational configurations and critically making sure that the data and credentials are not stored or transferred in ‘plaintext’ over the network by detailed testing and evaluation. It investigates the commands used to enable cryptography and network protocols based on encryption, in order to meet the need for essential security requirements. Substantial work is devoted to the command line details and testing of a router based on Cryptography and Security Protocols in the border router. A step-by-step hardening approach is detailed using the commands used to secure the proposed network framework’s border router. Encrypted services coupled with best practice configurations are explained and tested in an emulated environment. The use of protocol analysers, CISCO Configuration Professional’s Audit and penetration testing tools corroborated the success of the project.

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20

Библик, Ирина Валентиновна. "НЕЙРОСЕТЕВАЯ МОДЕЛЬ ДЛЯ ОЦЕНКИ ВЛИЯНИЯ КАЧЕСТВА ПОВЕРХНОСТНОГО СЛОЯ НА УСТАЛОСТНУЮ ПРОЧНОСТЬ ДЕТАЛЕЙ ГТД". Aerospace technic and technology, № 8 (31 серпня 2019): 85–89. http://dx.doi.org/10.32620/aktt.2019.8.13.

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An approach based on using the neural networks has been developed for predicting the fatigue strength of gas turbine engine (GTE) parts at the manufacturing stage. The neural network model implemented in the Delphi programming environment consists of an input layer containing four elements, one hidden layer with four neurons, and an output layer with one element. The output parameter of the neural network is fatigue strength, and the input parameters are determined by the technological process of manufacturing parts. These are the surface roughness, the degree, and depth of strain hardening and the residual compressive stresses in the surface layer. The sigmoid function is used as the activation function of the neural network. Back propagation error algorithm is developed to network’s training. The neural network is trained according to a previously prepared training and test data, including experimental and literary data. The fatigue strength values of GTE parts were determined for a constant base and test conditions. The mean squared errors calculated by the neural network for the training and test samples are 0.021 and 0.034, respectively. The input parameter ranges, on which the neural network model correctly performs prediction of fatigue strength, were determined. The relationships between the significance of each of the network input parameters for assessing the complex effect of surface layer parameters on fatigue strength are established. It is shown that residual compressive stresses and the degree of surface hardening have the greatest influence on the increase in the endurance limit of parts after processing. The possibility is considered and examples of the solution of the inverse problem are given, when by known values of the fatigue strength the values of the input parameters of the neural network, leading to the appearance of the available output, are searched. The developed approach may allow even at the stages of technological preparation of production to provide the required value of fatigue strength, to minimize the amount of testing and make the choice of optimal processing modes for GTE parts for the most effective hardening.

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21

Guan, Chun Ping, and Hong Ping Jin. "Determination of Residual Stress and Strain-Hardening Exponent Using Artificial Neural Networks." Advanced Materials Research 472-475 (February 2012): 332–35. http://dx.doi.org/10.4028/www.scientific.net/amr.472-475.332.

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Through dimensional analysis of indentation parameters in this study, we propose an artificial neural network (ANN) model to extract the residual stress and strain-hardening exponent based on spherical indentation. The relationships between indentation parameters and the residual stress and material properties are numerically calibrated through training and validation of the ANN model. They enable the direct mapping of the characteristics of the indentation parameters to the residual stress and the elastic-plastic material properties. The proposed ANN model can be used to quickly and effectively determine the residual stress and strain-hardening exponent.

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22

Yang, Tung Sheng, S. Q. Lee, J. Y. Li, and C. Y. Liu. "Prediction of Surface Parameters for Strain Hardening Material of Asperity Flattening in Metal Forming." Materials Science Forum 697-698 (September 2011): 470–73. http://dx.doi.org/10.4028/www.scientific.net/msf.697-698.470.

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This study applies the finite element method (FEM) in conjunction with an abductive network to predict the surface parameters for strain hardening material of asperity flattening in metal forming process. To verify the prediction of FEM simulation for surface parameters, the experimental data are compared with the results of current simulation. Contact area ratio, surface roughness, skewness and kurtosis are investigated for different process and material parameters, such as normal pressure, bulk strain rate, yielding stress, strength coefficient and strain hardening exponent of surface asperity flattening in metal forming, by finite element analysis. The abductive network is then utilized to synthesize the data sets obtained from numerical simulations, and the prediction model is established for predicting surface parameters. The predicted results of the surface parameters from the prediction model are in good agreement with the results obtained from the FEM simulation.

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23

Xu, Wei Feng, Jin He Liu, Dao Lun Chen, Guo Hong Luan, and Jun Shan Yao. "Tensile Properties and Strain Hardening Behavior of a Friction Stir Welded AA2219 Al Alloy." Advanced Materials Research 291-294 (July 2011): 833–40. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.833.

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Microstructures, tensile properties and work hardening behavior of friction stir welded (FSWed) AA2219-T62 aluminum alloy (in its one-third bottom slice of a 20 mm thick plate) were evaluated at different strain rates. While the yield strength was lower in the FSWed joint than in the base metal, the ultimate tensile strength of the FSWed joint approached that of the base metal. In particular the FSW resulted in a significant improvement in the ductility of the alloy due to the prevention of premature failure caused by intergranular cracking along the second-phase boundary related to the presence of the network-like grain boundary phase in the base metal. While stage III and IV hardening occurred after yielding in both base metal and FSWed samples, the FSW led to stronger hardening capacity and higher strain hardening exponent and rate due to the enhanced dislocation storage capacity associated with the microstructural change after FSW. The fracture surface of the FSWed joint was mainly characterized by dimples and tearing ridges along with micropores.

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24

OKIHARA, Koji, and Atsushi SAKUMA. "203 Representation of Hardening Coefficient by Neural Network learning Cyclic Stress-Strain Response." Proceedings of Conference of Chugoku-Shikoku Branch 2001.39 (2001): 45–46. http://dx.doi.org/10.1299/jsmecs.2001.39.45.

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25

IGARASHI, Hideki, and Yoji SHIBUTANI. "405 Strain-hardening with Self-organization of Dislocation Network Patterned by Cellular Automata." Proceedings of Conference of Kansai Branch 2001.76 (2001): _4–9_—_4–10_. http://dx.doi.org/10.1299/jsmekansai.2001.76._4-9_.

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26

Waheed, Faisal, and Maaruf Ali. "Hardening CISCO Devices based on Cryptography and Security Protocols - Part One: Background Theory." Annals of Emerging Technologies in Computing 2, no. 3 (2018): 27–44. http://dx.doi.org/10.33166/aetic.2018.03.004.

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Network Security is a vital part of any corporate and enterprise network. Network attacks greatly compromise not only the sensitive data of the consumers but also cause outages to these networks. Thus inadequately protected networks need to be “hardened”. The hardening of network devices refers to the hardware and software components, device operating system’s features, management controls, access-list restrictions, operational configurations and above all making sure that the data and credentials are not stored or transferred in ‘plaintext’ over the network. This article investigates the use of cryptography and network protocols based on encryption, to meet the need for essential security requirements. Use of non-secure protocols, underrating and misconfigurations of management protection are reasons behind network devices not properly being hardened; hence leaving vulnerabilities for the intruders. The gap identified after conducting intense search and review of past work is used as the foundation to present solutions. When performing cryptography techniques by encrypting packets using tunnelling and security protocols, management level credentials are encrypted. These include password encryption and exceptional analysis of the emulated IOS (Internetwork Operating System). Necessary testing is carried out to evaluate an acceptable level of protection of these devices. In a virtual testing environment, security flaws are found mainly in the emulated IOS. The discoveries does not depend on the hardware or chassis of a networking device. Since routers primarily rely on its Operating System (OS), attackers focus on manipulating the command line configuration before initiating an attack. Substantial work is devoted to implementation and testing of a router based on Cryptography and Security Protocols in the border router. This is deployed at the core layer and acts as the first point of entry of any trusted and untrusted traffic. A step-by-step hardening approach is adopted to secure the proposed network framework’s border router. Encrypted services coupled with best practice configurations are implemented and tested in an emulated environment. The use of protocol analysers, CISCO Configuration Professional’s Audit and penetration testing tools corroborated the success of the project.

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27

Conrad, Nathaniel, Tynan Kennedy, Deborah K. Fygenson, and Omar A. Saleh. "Increasing valence pushes DNA nanostar networks to the isostatic point." Proceedings of the National Academy of Sciences 116, no. 15 (2019): 7238–43. http://dx.doi.org/10.1073/pnas.1819683116.

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The classic picture of soft material mechanics is that of rubber elasticity, in which material modulus is related to the entropic elasticity of flexible polymeric linkers. The rubber model, however, largely ignores the role of valence (i.e., the number of network chains emanating from a junction). Recent work predicts that valence, and particularly the Maxwell isostatic point, plays a key role in determining the mechanics of semiflexible polymer networks. Here, we report a series of experiments confirming the prominent role of valence in determining the mechanics of a model system. The system is based on DNA nanostars (DNAns): multiarmed, self-assembled nanostructures that form thermoreversible equilibrium gels through base pair-controlled cross-linking. We measure the linear and nonlinear elastic properties of these gels as a function of DNAns arm number, f, and concentration [DNAns]. We find that, as f increases from three to six, the gel’s high-frequency plateau modulus strongly increases, and its dependence on [DNAns] transitions from nonlinear to linear. Additionally, higher-valence gels exhibit less strain hardening, indicating that they have less configurational freedom. Minimal strain hardening and linear dependence of shear modulus on concentration at high f are consistent with predictions for isostatic systems. Evident strain hardening and nonlinear concentration dependence of shear modulus suggest that the low-f networks are subisostatic and have a transient, potentially fractal percolated structure. Overall, our observations indicate that network elasticity is sensitive both to entropic elasticity of network chains and to junction valence, with an apparent isostatic point 5<fc≤6 in agreement with the Maxwell prediction.

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28

Yang, Tung Sheng, and Tsung Hsien Yang. "Predictions of Maximum Forging Load and Effective Stress for Strain-Hardening Material of near Net-Shape Helical Gear Forging." Applied Mechanics and Materials 284-287 (January 2013): 894–97. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.894.

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In this paper, the use of the finite element method in conjunction with abductive network is presented to predict the maximum forging force and effective stress for strain-hardening material during near net-shape helical forging. The maximum forging load and effective stress are influenced by the material properties such as yielding stress, strength coefficient and strain hardening exponent. A finite element method is used to investigate the clamping-type forging of helical gear. In order to verify the prediction of FEM simulation for forging load, the experimental data are compared with the results of current simulation. A finite element analysis is also utilized to investigate the material properties on forging load and maximum effective stress. Additionally, the abductive network was applied to synthesize the data sets obtained from the numerical simulation. The prediction models are then established for the maximum forging load and maximum effective stress of near net-shape helical gear forging under a suitable range of material parameters.

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29

Zrník, Jozef, Sergey V. Dobatkin, and Ondrej Stejskal. "Deformation Behaviour and Ultrafine Grained Structure Development in Steels with Different Carbon Content Subjected to Severe Plastic Deformation." Key Engineering Materials 345-346 (August 2007): 45–48. http://dx.doi.org/10.4028/www.scientific.net/kem.345-346.45.

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The article focuses on the results from recent experimental of severe plastic deformation of low carbon (LC) steel and medium carbon (MC) steel performed at increased temperatures. The grain refinement of ferrite respectively ferrite-pearlite structure is described. While LC steel was deformed by ECAP die (ε = 3) with a channel angle φ = 90° the ECAP severe deformation of MC steel was conducted with die channel angle of 120° (ε = 2.6 - 4). The high straining in LC steel resulted in extensively elongated ferrite grains with dense dislocation network and randomly recovered and polygonized structure was observed. The small period of work hardening appeared at tensile deformation. On the other side, the warm ECAP deformation of MC steel in dependence of increased effective strain resulted in more progressive recovery process. In interior of the elongated ferrite grains the subgrain structure prevails with dislocation network. As straining increases the dynamic polygonization and recrystallization became active to form mixture of polygonized subgrain and submicrocrystalline structure. The straining and moderate ECAP temperature caused the cementite lamellae fragmentation and spheroidzation as number of passes increased. The tensile behaviour of the both steels was characterized by strength increase however the absence of strain hardening was found at low carbon steel. The favourable effect of ferrite-pearlite structure modification due straining was reason for extended work hardening period observed at MC steel.

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30

Clarijs, Coen C. W. J., and Leon E. Govaert. "Strain hardening in glassy polymers: Influence of network density on elastic and viscous contributions." Journal of Polymer Science Part B: Polymer Physics 57, no. 15 (2019): 1001–13. http://dx.doi.org/10.1002/polb.24856.

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31

Selvakumar, N., P. Radha, R. Narayanasamy, and P. Ganesan. "Neural network model for predicting strain hardening and densification constants of sintered aluminium preforms." Powder Metallurgy 47, no. 3 (2004): 261–66. http://dx.doi.org/10.1179/003258904225020800.

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32

Mohd Fuzi, Mohd Faris, Khairunnisa Abdullah, Iman Hazwam Abd Halim, and Rafiza Ruslan. "Network Automation using Ansible for EIGRP Network." Journal of Computing Research and Innovation 6, no. 4 (2021): 59–69. http://dx.doi.org/10.24191/jcrinn.v6i4.237.

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Network automation has evolved into a solution that emphasizes efficiency in all areas. Furthermore, communication and computer networks rely on a platform that provides the necessary technological infrastructure for packet transfer through the Internet using routing protocols. The Enhanced Interior Gateway Routing Protocol (EIGRP) is a hybrid routing protocol that combines the properties of both distance-vector and link-state routing methods. The traditional technique to configure EIGRP is inefficient and requires repeated processes compared to the network automation concept. Network automation helps to assist network administrators in automating and verifying the EIGRP configuration using scripting. This paper implemented network automation using Ansible to configure EIGRP routing and advanced configuration in the GNS3 environment. This study is focused on automated scripting to configure IP Addresses to the interfaces, EIGRP routing protocol, a default static route and advanced EIGRP configurations. Ansible ran the scripting on Network Automation Docker and pushed the configurations to the routers. The network automation docker communicated with other routers via SSH. In the testing phase, the running configuration between the traditional approach and automation scripting in the Ansible playbook was compared to verify EIGRP configurations' accuracy. The findings show that Ansible has successfully deployed the configuration to the routers with no errors. Ansible can help network administrators minimized human mistakes, reduce time-consuming and enable device visibility across the network environment. Implementing EIGRP authentication and hardening process can enhance the network security level for future study.

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33

Dazahra, M. N., F. Elmariami, A. Belfqih, and J. Boukherouaa. "A Defense-in-depth Cybersecurity for Smart Substations." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4423. http://dx.doi.org/10.11591/ijece.v8i6.pp4423-4431.

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The increase of cyber-attacks on industrial and power systems in the recent years make the cybersecurity of supervisory control and data acquisition and substation automation systemsa high important engineering issue. This paper proposes a defense in depth cybersecurity solution for smart substations in different layers of the substation automation system. In fact, it presents possible vulnerabilities in the substation automation system and propose a multiple layer solution based on best practice in cyber security such as the hardening ofdevices, whitelisting, network configuration, network segmentation, role-based account management and cyber security management and deployement.

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34

Revathi, S., N. Sivakumaran, D. Ramajayam, M. S. Saraswathi, S. Backiyarani, and S. Uma. "Growth estimation during hardening phase of tissue cultured banana plantlets using bootstrapped artificial neural network." Journal of Environmental Biology 40, no. 4 (2019): 719–24. http://dx.doi.org/10.22438/jeb/40/4/mrn-948.

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35

Theocaris, P. S., and P. D. Panagiotopoulos. "Hardening Plasticity Approximated via Anisotropic Elasticity. The Fokker-Planck Equation in a Neural Network Environment." ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 75, no. 11 (1995): 889–900. http://dx.doi.org/10.1002/zamm.19950751103.

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36

Ishihara, Shota, Yuta Hikima, and Masahiro Ohshima. "Preparation of open microcellular polylactic acid foams with a microfibrillar additive using coreback foam injection molding processes." Journal of Cellular Plastics 54, no. 4 (2018): 765–84. http://dx.doi.org/10.1177/0021955x18770441.

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Open microcellular polylactic acid foams with a fibrous polytetrafluoroethylene additive were prepared by a coreback foam injection molding technique. The effects of this fibrous additive on the foam cell structure were investigated. Fibrous polytetrafluoroethylene forms a network structure in polylactic acid in metering and mixing processes. The fibrous polytetrafluoroethylene network increased the viscoelasticity of polylactic acid and provided polylactic acid with a strain-hardening property. The network also provided heterogeneous bubble nucleation sites for physical foaming. However, because of the slow crystallization rate of polylactic acid, the fibrous polytetrafluoroethylene additive did not promote the nucleation of polylactic acid crystals under fast cooling conditions. During fast cooling, such as injection molding cooling conditions, the crystals induced by the fibrous polytetrafluoroethylene network could not behave as bubble nucleation sites. Thus, changes in rheological properties and the increased number of heterogeneous sites contributed to the decrease in cell size, the increase in the number density of cells and the increase in the open cell content. As the number density of cells increased, the cell walls with the fibrous polytetrafluoroethylene fibrous additive became so thin that they could be easily fibrillated by a stretching operation during the coreback operation, while their strain-hardening property prevented the walls from complete breakage. Synergistically conducting cell reduction and stretching (coreback) operations, high expansion ratio foams with high open cell content were prepared. When we adjusted the foaming temperature and holding time, five-fold expansion (i.e. 80% void ratio) foams with cell diameters less than 25 µm and open cell contents (OCC) higher than 80% were produced.

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G’Sell, Christian, and Abdelhamid Souahi. "Influence of Crosslinking on the Plastic Behavior of Amorphous Polymers at Large Strains." Journal of Engineering Materials and Technology 119, no. 3 (1997): 223–27. http://dx.doi.org/10.1115/1.2812248.

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The mechanical properties of three grades of PMMA, one linear and two crosslinked, are investigated in tension below and above the glass transition temperature. It is found that strain-hardening decreases gradually with temperature in the glassy state, but keeps a significant value in the rubbery state. The results are analyzed in terms of an entropy-based statistical model (van der Giessen and Wu, 1992) which describes the stress-strain response of a chain network. The junctions of the network are not only associated with the chemical crosslinks, but additionally with physical entanglements, which are more numerous in the glassy state.

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Boccaccio, Antonio, Maria Cristina Frassanito, Luciano Lamberti, et al. "Nanoscale characterization of the biomechanical hardening of bovine zona pellucida." Journal of The Royal Society Interface 9, no. 76 (2012): 2871–82. http://dx.doi.org/10.1098/rsif.2012.0269.

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The zona pellucida (ZP) is an extracellular membrane surrounding mammalian oocytes. The so-called zona hardening plays a key role in fertilization process, as it blocks polyspermy, which may also be caused by an increase in the mechanical stiffness of the ZP membrane. However, structural reorganization mechanisms leading to ZP's biomechanical hardening are not fully understood yet. Furthermore, a correct estimate of the elastic properties of the ZP is still lacking. Therefore, the aim of the present study was to investigate the biomechanical behaviour of ZP membranes extracted from mature and fertilized bovine oocytes to better understand the mechanisms involved in the structural reorganization of the ZP that may lead to the biomechanical hardening of the ZP. For that purpose, a hybrid procedure is developed by combining atomic force microscopy nanoindentation measurements, nonlinear finite element analysis and nonlinear optimization. The proposed approach allows us to determine the biomechanical properties of the ZP more realistically than the classical analysis based on Hertz's contact theory, as it accounts for the nonlinearity of finite indentation process, hyperelastic behaviour and material heterogeneity. Experimental results show the presence of significant biomechanical hardening induced by the fertilization process. By comparing various hyperelastic constitutive models, it is found that the Arruda–Boyce eight-chain model best describes the biomechanical response of the ZP. Fertilization leads to an increase in the degree of heterogeneity of membrane elastic properties. The Young modulus changes sharply within a superficial layer whose thickness is related to the characteristic distance between cross-links in the ZP filamentous network. These findings support the hypothesis that biomechanical hardening of bovine ZP is caused by an increase in the number of inter-filaments cross-links whose density should be higher in the ZP inner side.

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Yin, Longcheng, Tingjian Wang, Xinxin Ma, et al. "Pre-Coated Fe–Ni Film to Promote Low-Pressure Carburizing of 14Cr14Co13Mo4 Steel." Coatings 9, no. 5 (2019): 304. http://dx.doi.org/10.3390/coatings9050304.

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Case-hardening 14Cr14Co13Mo4 martensitic stainless steel needs to be carburized to improve surface performance. Low-pressure carburization has the benefit of having oxidation-free production and being ecofriendly. However, compared with the low-pressure carburization of the low-alloy steel, low-pressure carburization of the 14Cr14Co13Mo4 steel consumes more time and has a risk of network carbides. In order to promote carbon diffusion and avoid network carbide, Fe–Ni films with various thickness were electrodeposited on the 14Cr14Co13Mo4 steel prior to low-pressure carburization. The experimental results show that, under the same carburizing conditions, the surface carbon content decreases and the carburized layer increases with the increase of Fe–Ni film thickness. After the hardening heat treatment, the effective case depth (ECD) of the sample coated with 6.0 μm Fe–Ni film was increased by 29% compared to that of the uncoated sample. The morphology of carbides was a strip-shaped, discontinuous network distribution in the uncoated sample, while in the Fe–Ni coated samples, the carbides changed to a globular, uniformly dispersed distribution. The effect of Fe–Ni film on the low-pressure carburizing of steel is explained by the simulation of the carbon diffusion using DICTRA software. The Fe–Ni films reduce the steel surface carbon content in each boost stage of low-pressure carburizing and release carbon atoms in every diffusion stage. Through this adjustment mechanism, the steel surface carbon content can be reduced and carburized layer growth can be promoted.

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40

Zhang, Yao, Changjin Huang, Sangtae Kim, et al. "Multiple stiffening effects of nanoscale knobs on human red blood cells infected with Plasmodium falciparum malaria parasite." Proceedings of the National Academy of Sciences 112, no. 19 (2015): 6068–73. http://dx.doi.org/10.1073/pnas.1505584112.

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During its asexual development within the red blood cell (RBC), Plasmodium falciparum (Pf), the most virulent human malaria parasite, exports proteins that modify the host RBC membrane. The attendant increase in cell stiffness and cytoadherence leads to sequestration of infected RBCs in microvasculature, which enables the parasite to evade the spleen, and leads to organ dysfunction in severe cases of malaria. Despite progress in understanding malaria pathogenesis, the molecular mechanisms responsible for the dramatic loss of deformability of Pf-infected RBCs have remained elusive. By recourse to a coarse-grained (CG) model that captures the molecular structures of Pf-infected RBC membrane, here we show that nanoscale surface protrusions, known as “knobs,” introduce multiple stiffening mechanisms through composite strengthening, strain hardening, and knob density-dependent vertical coupling. On one hand, the knobs act as structural strengtheners for the spectrin network; on the other, the presence of knobs results in strain inhomogeneity in the spectrin network with elevated shear strain in the knob-free regions, which, given its strain-hardening property, effectively stiffens the network. From the trophozoite to the schizont stage that ensues within 24–48 h of parasite invasion into the RBC, the rise in the knob density results in the increased number of vertical constraints between the spectrin network and the lipid bilayer, which further stiffens the membrane. The shear moduli of Pf-infected RBCs predicted by the CG model at different stages of parasite maturation are in agreement with experimental results. In addition to providing a fundamental understanding of the stiffening mechanisms of Pf-infected RBCs, our simulation results suggest potential targets for antimalarial therapies.

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Shimizu, Yoshihiko, Keita Sakakibara, and Yoshinobu Tsujii. "Strain Hardening of Highly Stretchable Elastomeric Composites Reinforced with Well-Defined Nanofiber Network of Bacterial Cellulose." Journal of Fiber Science and Technology 74, no. 1 (2018): 17–23. http://dx.doi.org/10.2115/fiberst.2018-0003.

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42

Wu, P. D., and E. Van Der Giessen. "On improved network models for rubber elasticity and their applications to orientation hardening in glassy polymers." Journal of the Mechanics and Physics of Solids 41, no. 3 (1993): 427–56. http://dx.doi.org/10.1016/0022-5096(93)90043-f.

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Zhang, Huifeng, Lu Zhang, Xu Chen, et al. "The Role of Non-Rubber Components on Molecular Network of Natural Rubber during Accelerated Storage." Polymers 12, no. 12 (2020): 2880. http://dx.doi.org/10.3390/polym12122880.

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Though the non-rubber components have long been recognized to be a vital factor affecting the network of natural rubber (NR), the authentic role of non-rubber components on the network during accelerated storage has not been fully illuminated. This work attempts to clarify the impact of non-rubber components on the network for NR during accelerated storage. A natural network model for NR was proposed based on the gel content, crosslinking density, and the non-rubber components distribution for NR before and after centrifugation. Furthermore, the effect of non-rubber components on the network was investigated during accelerated storage. The results show that terminal crosslinking induced by non-rubber components and entanglements are primary factors affecting the network formation during accelerated storage. By applying the tube model to analyze the stress-strain curves of NR, we found that the contribution of the entanglements to the network formation is larger than that of terminal crosslinking during accelerated storage. The work highlights the role of non-rubber components on the network during accelerated storage, which is essential for understanding the storage hardening mechanism of NR.

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Celina, M., A. C. Graham, K. T. Gillen, R. A. Assink, and L. M. Minier. "Thermal Degradation Studies of a Polyurethane Propellant Binder." Rubber Chemistry and Technology 73, no. 4 (2000): 678–93. http://dx.doi.org/10.5254/1.3547613.

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Abstract The thermal oxidative aging of a crosslinked hydroxy-terminated polybutadiene (HTPB)/isophorone diisocyanate (IPDI) based polyurethane rubber, used as a polymeric binder in solid propellant grain, was investigated at temperatures from 25 to 125 °C. The changes in tensile elongation, polymer network properties and chain dynamics, mechanical hardening and density were determined with a range of techniques including modulus profiling, solvent swelling, NMR relaxation and O2 permeability measurements. We critically evaluated the Arrhenius methodology that is commonly used with a linear extrapolation of high temperature aging data using extensive data superposition and highly sensitive oxygen consumption experiments. The effects of other constituents in the propellant formulation on aging were also investigated. We conclude that crosslinking is the dominant process at higher temperatures and that the degradation involves only limited hardening in the bulk of the material. Significant curvature in the Arrhenius diagram of the oxidation rates was observed. This is similar to results for other rubber materials.

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Yang, Tung Sheng, Sheng Yi Chang, and Jian Chang Chou. "Predictions of Scratch Characters for Engineering Material by Using FEM and Abductive Network." Applied Mechanics and Materials 232 (November 2012): 659–64. http://dx.doi.org/10.4028/www.scientific.net/amm.232.659.

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Scratch test is mainly used to study mechanical properties of materials near their surface. This study applies the finite element method (FEM) in conjunction with an abductive network to predict the scratch character such as rear contact angle, shape ratio and hardness for strain hardening bulk material of scratch process. To verify the prediction of FEM simulation of scratch process, the experimental data are compared with the results of current simulation. A finite element analysis is also utilized to investigate the material properties on side view contour, rear contact angle, hardness and shape ratio. Additionally, the abductive network was applied to synthesize the data sets obtained from the numerical simulation. The prediction models are then established for the rear contact angle, hardness and shape ratio of nanoscratch process under a suitable range of material parameters.

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46

Melikhova, Oksana, Jakub Čížek, Petr Hruška, et al. "Influence of Deformation on Precipitation Kinetics in Mg-Tb Alloy." Defect and Diffusion Forum 322 (March 2012): 151–62. http://dx.doi.org/10.4028/www.scientific.net/ddf.322.151.

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Precipitation effects in age-hardenable Mg-13wt.%Tb alloy were investigated in this work. The solution treated alloy was subjected to isochronal annealing and decomposition of the supersaturated solid solution was investigated by positron annihilation spectroscopy combined with transmission electron microscopy, electrical resistometry, differential scanning calorimetry and microhardness measurements. Peak hardening was observed at 200°C due to precipitation of finely dispersed particles of β phase with the D019structure. Vacancy-like defects associated with β phase particles were detected by positron annihilation. At higher temperatures precipitation of β and subsequently β phase takes place. Formation of these phases lead to some additional hardening and introduces open volume defects at precipitate/matrix interfaces. To elucidate the effect of plastic deformation on the precipitation sequence we studied also a Mg-13wt.%Tb alloy with ultra fine grained structure prepared by high pressure torsion. In the ultra fine grained alloy precipitation of the β phase occurs at lower temperature compared to the coarse grained material and the peak hardening is shifted to a lower temperature as well. This effect can be explained by enhanced diffusivity of Mg and Tb atoms due to a dense network of grain boundaries and high density of dislocations introduced by severe plastic deformation. Moreover, dislocations and grain boundaries serve also as nucleation sites for precipitates. Hence, precipitation effects are accelerated in the alloy subjected to severe plastic deformation.

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Cochrane, H., and C. S. Lin. "The Influence of Fumed Silica Properties on the Processing, Curing, and Reinforcement Properties of Silicone Rubber." Rubber Chemistry and Technology 66, no. 1 (1993): 48–60. http://dx.doi.org/10.5254/1.3538299.

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Abstract The present study uses a commercial heat cured silicone rubber formula (including a process aid) and mixing techniques to investigate the effect of varying fumed silica properties—including load, surface area, silica structure level, and surface pretreatment levels—on the rubber processing, curing, and cured physical properties. Based on the results, a simple silica network reinforcement model was developed to explain the changes in processing, curing, and vulcanizate properties of the silicone elastomers. The network is held together by silica-silica interactions and silica-polymer-silica bridge bonds between the silica aggregates. Increasing the silica loading, surface area, and structure level increases the number of interactions and hence the network strength. The pretreatment of the silica surface with organosilane molecules reduces the strength of silica-silica and silica-polymer interactions, therefore, weakening the silica network. Furthermore, the good interrelations between the initial plasticity, crepe hardening, curing, modulus yield, and durometer values strongly supports the concept of the presence of a silica network within the compounds under the low strain conditions of the tests.

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Razavi, Sayyed Ali, Fakhreddin Ashrafizadeh, and Saghar Fooladi. "Prediction of age hardening parameters for 17-4PH stainless steel by artificial neural network and genetic algorithm." Materials Science and Engineering: A 675 (October 2016): 147–52. http://dx.doi.org/10.1016/j.msea.2016.08.049.

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Bartolacci, Michael R., and Stanko Dimitrov. "Promoting Resiliency in Emergency Communication Networks." International Journal of Information Systems for Crisis Response and Management 9, no. 1 (2017): 1–10. http://dx.doi.org/10.4018/ijiscram.2017010101.

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Police, fire, and emergency personnel rely on wireless networks to serve the public. Whether it is during a natural disaster, or just an ordinary calendar day, wireless nodes of varying types form the infrastructure that local, regional, and even national scale agencies use to communicate while keeping the population served safe and secure. In this article, Michael R. Bartolacci and Stanko Dimitrov present a network interdiction modeling approach that can be utilized for analyzing vulnerabilities in public service wireless networks; subject to hacking, terrorism, or destruction from natural disasters. They develop a case study for wireless networks utilized by the sheriff's department of Miami-Dade County in Florida in the United States. Finally, the authors' modeling approach—given theoretical budgets for the “hardening” of wireless network nodes and for would-be destroyers of such nodes—highlights parts of the network where further investment may prevent damage and loss of capacity.

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Prasad, Mahesh R. G., Anupam Neogi, Napat Vajragupta, Rebecca Janisch, and Alexander Hartmaier. "Influence of Temperature on Void Collapse in Single Crystal Nickel under Hydrostatic Compression." Materials 14, no. 9 (2021): 2369. http://dx.doi.org/10.3390/ma14092369.

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Employing atomistic simulations, we investigated the void collapse mechanisms in single crystal Ni during hydrostatic compression and explored how the atomistic mechanisms of void collapse are influenced by temperature. Our results suggest that the emission and associated mutual interactions of dislocation loops around the void is the primary mechanism of void collapse, irrespective of the temperature. The rate of void collapse is almost insensitive to the temperature, and the process is not thermally activated until a high temperature (∼1200–1500 K) is reached. Our simulations reveal that, at elevated temperatures, dislocation motion is assisted by vacancy diffusion and consequently the void is observed to collapse continuously without showing appreciable strain hardening around it. In contrast, at low and ambient temperatures (1 and 300 K), void collapse is delayed after an initial stage of closure due to significant strain hardening around the void. Furthermore, we observe that the dislocation network produced during void collapse remains the sample even after complete void collapse, as was observed in a recent experiment of nickel-base superalloy after hot isostatic pressing.

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