In recent years, the place occupied by the various manifestations of cyber-crime in companies has been considerable. Indeed, due to the rapid evolution of telecommunications technologies, companies, regardless of thei...In recent years, the place occupied by the various manifestations of cyber-crime in companies has been considerable. Indeed, due to the rapid evolution of telecommunications technologies, companies, regardless of their size or sector of activity, are now the target of advanced persistent threats. The Work 2035 study also revealed that cyber crimes (such as critical infrastructure hacks) and massive data breaches are major sources of concern. Thus, it is important for organizations to guarantee a minimum level of security to avoid potential attacks that can cause paralysis of systems, loss of sensitive data, exposure to blackmail, damage to reputation or even a commercial harm. To do this, among other means, hardening is used, the main objective of which is to reduce the attack surface within a company. The execution of the hardening configurations as well as the verification of these are carried out on the servers and network equipment with the aim of reducing the number of openings present by keeping only those which are necessary for proper operation. However, nowadays, in many companies, these tasks are done manually. As a result, the execution and verification of hardening configurations are very often subject to potential errors but also highly consuming human and financial resources. The problem is that it is essential for operators to maintain an optimal level of security while minimizing costs, hence the interest in automating hardening processes and verifying the hardening of servers and network equipment. It is in this logic that we propose within the framework of this work the reinforcement of the security of the information systems (IS) by the automation of the mechanisms of hardening. In our work, we have, on the one hand, set up a hardening procedure in accordance with international security standards for servers, routers and switches and, on the other hand, designed and produced a functional application which makes it possible to: 1) Realise the configuration of the hardening;2) Verify them;3) Correct the non conformities;4) Write and send by mail a verification report for the configurations;5) And finally update the procedures of hardening. Our web application thus created allows in less than fifteen (15) minutes actions that previously took at least five (5) hours of time. This allows supervised network operators to save time and money, but also to improve their security standards in line with international standards.展开更多
Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on...Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To exploit the benefits presented by the laser hardening process, it is necessary to develop an integrated strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive modelling approach for predicting the hardened surface physical and geometrical attributes. The laser surface transformation hardening of cylindrical AISI 4340 steel workpieces is modeled using the conventional regression equation method as well as artificial neural network method. The process parameters included in the study are laser power, beam scanning speed, and the workpiece rotational speed. The upper and the lower limits for each parameter are chosen considering the start of the transformation hardening and the maximum hardened zone without surface melting. The resulting models are able to predict the depths representing the maximum hardness zone, the hardness drop zone, and the overheated zone without martensite transformation. Because of its ability to model highly nonlinear problems, the ANN based model presents the best modelling results and can predict the hardness profile with good accuracy.展开更多
The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or ...The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or the chemical composition by its hardenability. The prediction result is more precise than that obtained from the traditional method based on the simple mathematical regression model.展开更多
Most conventional ceramic based aluminum metal matrix composites(MMCs) are either heavy,costly or combination of both. In order to reduce cost and weight,while at the same time maintaining quality,cow horn particles(C...Most conventional ceramic based aluminum metal matrix composites(MMCs) are either heavy,costly or combination of both. In order to reduce cost and weight,while at the same time maintaining quality,cow horn particles(CHp) was used with aluminum alloy A356 to produce MMC for brake drum application and other engineering uses. The aim of this research is to model the age hardening process of the produced composite using response surface methodology(RSM) and artificial neural network(ANN),and to use the developed ANN as fitness function for a simulated annealing optimization algorithm(SA-NN system) for optimization of age hardening process parameters. The results show that ANN modeled the age hardening data excellently and better than RSM with a correlation coefficient of experimental response with ANN predictions being 0.9921 as against 0.9583 for the RSM. The SA-NN system optimized process parameters were in very close agreement with the experimental values with the maximum relative error of 1.2%,minimum of 0.35% and average of 0.71%.展开更多
Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model ...Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model to perform non-destructive quality estimation is an essential part of the assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network (ANN) based model for quality estimation and prediction in LSTHP using a commercial 3 kW Nd:Yag laser. The proposed approach examines laser hardening parameters and conditions known to have an influence on performance characteristics of hardened surface such as hardened bead width (HBW) and hardened depth (HD) and builds a quality prediction model step by step. The modeling procedure begins by examining, through a structured experimental investigations and exhaustive 3D finite element method simulation efforts, the relationships between laser hardening parameters and characteristics of hardened surface and their sensitivity to the process conditions. Using these results and various statistical tools, different quality prediction models are developed and evaluated. The results demonstrate that the ANN based assessment and prediction proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of hardened surface characteristics under variable hardening parameters and conditions.展开更多
Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using gene...Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using genetic algorithm-back propagation neural network（GA-BP） was developed based on the experimental results.The non-linear relationship between properties of hardening layers and process parameters was established.The results show that the GA-BP predicting model is reliable since prediction results are in rather good agreement with measured results.The optimal properties of the hardened layer were deduced from GA.And through multi optimizations,the optimum comprehensive performances of the hardened layer were as follows：plasma arc current is 90 A,hardening speed is 2.2 m/min,plasma gas flow rate is 6.0 L/min and hardening distance is 4.3 mm.It concludes that GA-BP mode developed in this study provides a promising method for plasma hardening parameters prediction and optimization.展开更多
文摘In recent years, the place occupied by the various manifestations of cyber-crime in companies has been considerable. Indeed, due to the rapid evolution of telecommunications technologies, companies, regardless of their size or sector of activity, are now the target of advanced persistent threats. The Work 2035 study also revealed that cyber crimes (such as critical infrastructure hacks) and massive data breaches are major sources of concern. Thus, it is important for organizations to guarantee a minimum level of security to avoid potential attacks that can cause paralysis of systems, loss of sensitive data, exposure to blackmail, damage to reputation or even a commercial harm. To do this, among other means, hardening is used, the main objective of which is to reduce the attack surface within a company. The execution of the hardening configurations as well as the verification of these are carried out on the servers and network equipment with the aim of reducing the number of openings present by keeping only those which are necessary for proper operation. However, nowadays, in many companies, these tasks are done manually. As a result, the execution and verification of hardening configurations are very often subject to potential errors but also highly consuming human and financial resources. The problem is that it is essential for operators to maintain an optimal level of security while minimizing costs, hence the interest in automating hardening processes and verifying the hardening of servers and network equipment. It is in this logic that we propose within the framework of this work the reinforcement of the security of the information systems (IS) by the automation of the mechanisms of hardening. In our work, we have, on the one hand, set up a hardening procedure in accordance with international security standards for servers, routers and switches and, on the other hand, designed and produced a functional application which makes it possible to: 1) Realise the configuration of the hardening;2) Verify them;3) Correct the non conformities;4) Write and send by mail a verification report for the configurations;5) And finally update the procedures of hardening. Our web application thus created allows in less than fifteen (15) minutes actions that previously took at least five (5) hours of time. This allows supervised network operators to save time and money, but also to improve their security standards in line with international standards.
文摘Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To exploit the benefits presented by the laser hardening process, it is necessary to develop an integrated strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive modelling approach for predicting the hardened surface physical and geometrical attributes. The laser surface transformation hardening of cylindrical AISI 4340 steel workpieces is modeled using the conventional regression equation method as well as artificial neural network method. The process parameters included in the study are laser power, beam scanning speed, and the workpiece rotational speed. The upper and the lower limits for each parameter are chosen considering the start of the transformation hardening and the maximum hardened zone without surface melting. The resulting models are able to predict the depths representing the maximum hardness zone, the hardness drop zone, and the overheated zone without martensite transformation. Because of its ability to model highly nonlinear problems, the ANN based model presents the best modelling results and can predict the hardness profile with good accuracy.
文摘The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or the chemical composition by its hardenability. The prediction result is more precise than that obtained from the traditional method based on the simple mathematical regression model.
文摘Most conventional ceramic based aluminum metal matrix composites(MMCs) are either heavy,costly or combination of both. In order to reduce cost and weight,while at the same time maintaining quality,cow horn particles(CHp) was used with aluminum alloy A356 to produce MMC for brake drum application and other engineering uses. The aim of this research is to model the age hardening process of the produced composite using response surface methodology(RSM) and artificial neural network(ANN),and to use the developed ANN as fitness function for a simulated annealing optimization algorithm(SA-NN system) for optimization of age hardening process parameters. The results show that ANN modeled the age hardening data excellently and better than RSM with a correlation coefficient of experimental response with ANN predictions being 0.9921 as against 0.9583 for the RSM. The SA-NN system optimized process parameters were in very close agreement with the experimental values with the maximum relative error of 1.2%,minimum of 0.35% and average of 0.71%.
文摘Quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser surface transformation hardening process (LSTHP). Accurate and efficient model to perform non-destructive quality estimation is an essential part of the assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network (ANN) based model for quality estimation and prediction in LSTHP using a commercial 3 kW Nd:Yag laser. The proposed approach examines laser hardening parameters and conditions known to have an influence on performance characteristics of hardened surface such as hardened bead width (HBW) and hardened depth (HD) and builds a quality prediction model step by step. The modeling procedure begins by examining, through a structured experimental investigations and exhaustive 3D finite element method simulation efforts, the relationships between laser hardening parameters and characteristics of hardened surface and their sensitivity to the process conditions. Using these results and various statistical tools, different quality prediction models are developed and evaluated. The results demonstrate that the ANN based assessment and prediction proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of hardened surface characteristics under variable hardening parameters and conditions.
文摘Plasma surface hardening process was performed to improve the performance of the AISI 1045 carbon steel.Experiments were carried out to characterize the hardening qualities.A predicting and optimizing model using genetic algorithm-back propagation neural network（GA-BP） was developed based on the experimental results.The non-linear relationship between properties of hardening layers and process parameters was established.The results show that the GA-BP predicting model is reliable since prediction results are in rather good agreement with measured results.The optimal properties of the hardened layer were deduced from GA.And through multi optimizations,the optimum comprehensive performances of the hardened layer were as follows：plasma arc current is 90 A,hardening speed is 2.2 m/min,plasma gas flow rate is 6.0 L/min and hardening distance is 4.3 mm.It concludes that GA-BP mode developed in this study provides a promising method for plasma hardening parameters prediction and optimization.
