Vol. 06, No. 06 [June 2020]
- Citation
- Abstract
- Reference
- PDF Download
Paper Title | :: | Comparative Analysis of Mechanical Properties of plates cast through Investment Casting and Green Sand Casting Techniques |
Author Name | :: | Areo, S. O. || Khan, R.H. || Ndaliman, M.B. || Lawal, S.A. |
Country | :: | Nigeria |
Page Number | :: | 01-10 |
Plates of Aluminium Silicon Magnesium alloy (A356) with thicknesses of 8 mm, 10 mm and 12 mm were cast using the green sand casting and investment casting methods at pouring temperatures of 665oC, 690oC and 715oC. The castings were subjected to tensile strength test, impact test and hardness test and the results obtained were analysed using Minitab 17 software. From the results and comparative analysis, it was observed that the tensile strength was between 0.43 % and 1.1 %, the impact strength was between 1.90 % and 9.29 %, and the hardness was between 0.04 % and 0.30 %. The percentage differences in the mechanical properties of the green sand cast plates and the investment cast plates were minimal, hence the work concludes that investment castings or components can also conveniently serve under the same service condition with sand casting components without failure, and investment castings is a preferred choice when requirements like; casting of complex and intricate components, obtaining accurate dimensions and fine finishing are needed.
Keywords: Investment casting, Pattern, Plaster of Paris slurry, Sand casting, Silica sand.
Keywords: Investment casting, Pattern, Plaster of Paris slurry, Sand casting, Silica sand.
[1]. Khan R.H., (2005). Metal Casting Technology in Nigeria- Present Status and Future Prospects. F.U.T. Minna Inaugural Lecture series 8.,Minna, Kings Plaza.
[2]. Rao, T.V., (2003). Metal Casting: Principle and Practice. London, New Age International Press. ISBN 978-81-224-0843-0.
[3]. Library of Manufacturing (2015) The Process of Investment Casting. Retrieved from http://www.thelibraryofmanufacturing.com/investment_casting.html.
[4]. Senthil J. Prakash (2017). Pros and Cons of sand casting. Retrieved from http://www.engineeringproductdesign.com
[5]. Prasad, R.,(2012), Progress in Investment Castings. Science and Technology of Casting Processes, 25-47,Retrieved from: http://www.academia.edu/10488981/progress_in_investment_castings
[2]. Rao, T.V., (2003). Metal Casting: Principle and Practice. London, New Age International Press. ISBN 978-81-224-0843-0.
[3]. Library of Manufacturing (2015) The Process of Investment Casting. Retrieved from http://www.thelibraryofmanufacturing.com/investment_casting.html.
[4]. Senthil J. Prakash (2017). Pros and Cons of sand casting. Retrieved from http://www.engineeringproductdesign.com
[5]. Prasad, R.,(2012), Progress in Investment Castings. Science and Technology of Casting Processes, 25-47,Retrieved from: http://www.academia.edu/10488981/progress_in_investment_castings
- Citation
- Abstract
- Reference
- PDF Download
Paper Title | :: | An Analytical View of Interface on Security Logs Adapting Deep Learning Techniques |
Author Name | :: | Prateek Bajaj || Sumaiya PK |
Country | :: | India |
Page Number | :: | 11-15 |
Amongst all aspects of Security in Applications and Products, Security Log Analytics has taken a priority lower than many other aspects for a plethora of reasons. However, the power it holds over a responsive, as well as a proactive approach towards securing applications, and in lieu products is unmatched. Security Log Analysis does result in evidence of attacks. A lack of such, thus, results in several security threats going unnoticed. The issue, though, during log analysis with only human labor and intervention is a longer response time and a lot of manual effort. Thus, automating log-analysis is one way through which the technology of the future is helping out in making the products of today secure.
Deep learning algorithms, as popular as they are, have for some time now helped in multiple applications for making intelligent decisions with the help of huge amounts of data. This paper provides a look into a comprehensive deep-learning algorithm that would help in security log analysis for the generic use-cases, that can be tweaked according to the particular product’s log-data is elaborated.
Deep learning algorithms, as popular as they are, have for some time now helped in multiple applications for making intelligent decisions with the help of huge amounts of data. This paper provides a look into a comprehensive deep-learning algorithm that would help in security log analysis for the generic use-cases, that can be tweaked according to the particular product’s log-data is elaborated.
[1]. Anton Chuvakin. Scan34, http://old.honeynet.org/scans/scan34/. Last Accessed: 2018-11-03.
[2]. Tom M. Mitchell. Machine Learning. McGraw Hill, 1997.
[3]. Ren Pellissier. Business Research Made Easy. Juta Academic (September 5, 2008), ISBN-13: 978-0702177033.
[4]. K. Ryosuke O. Satoru and K. Kiyoshi. Minimizing false positives of a decision tree classifier for intrusion detection on the internet. Journal of Network and Systems Management, 16(4):399–419, 12 2008.
[5]. Tom Fawcett. An introduction to roc analysis. PatternRecognitionLetters,27(8):861 – 874, 2006. ROC Analysis in Pattern Recognition.
[2]. Tom M. Mitchell. Machine Learning. McGraw Hill, 1997.
[3]. Ren Pellissier. Business Research Made Easy. Juta Academic (September 5, 2008), ISBN-13: 978-0702177033.
[4]. K. Ryosuke O. Satoru and K. Kiyoshi. Minimizing false positives of a decision tree classifier for intrusion detection on the internet. Journal of Network and Systems Management, 16(4):399–419, 12 2008.
[5]. Tom Fawcett. An introduction to roc analysis. PatternRecognitionLetters,27(8):861 – 874, 2006. ROC Analysis in Pattern Recognition.
- Citation
- Abstract
- Reference
- PDF Download
Paper Title | :: | Geometry, Quantum Mechanics and low Energy Nuclear Transmutations |
Author Name | :: | Christos D. Papageorgiou |
Country | :: | Greece |
Page Number | :: | 16-21 |
Quantum mechanics Geometry generated potentials in Curved conducting wires strips or paths are
related with various peculiar phenomena as exploding wires and exploding Li-ion batteries. The proposed theory
can be used in exploration of low energy nuclear transmutation devices. The origin of the so called cold fusion
is possible to be connected with these phenomena.
Keywords: Schrödinger equation. Stark effect, exploding wires, , exploding batteries, low energy nuclear transmutations
Keywords: Schrödinger equation. Stark effect, exploding wires, , exploding batteries, low energy nuclear transmutations
[1]. https://en.wikipedia.org/wiki/Quantum-confined_Stark_effect
[2]. C. D. Papageorgiou, T. E .Raptis, Eur. Phys. J. Appl. Phys. 48 31002 (2009)
[3]. C. D. Papageorgiou, T. E .Raptis, Eur. Phys. J. Appl. Phys. 54 (01) (2011)
[4]. C. D. Papageorgiou, T. E. Raptis Open Access Library Journal, 2016, Volume 3, e3162
[5]. M. J. Taylor, J. Phys. D: Appl. Phys. 35 (2002) 700-709.
[2]. C. D. Papageorgiou, T. E .Raptis, Eur. Phys. J. Appl. Phys. 48 31002 (2009)
[3]. C. D. Papageorgiou, T. E .Raptis, Eur. Phys. J. Appl. Phys. 54 (01) (2011)
[4]. C. D. Papageorgiou, T. E. Raptis Open Access Library Journal, 2016, Volume 3, e3162
[5]. M. J. Taylor, J. Phys. D: Appl. Phys. 35 (2002) 700-709.