i-manager Publications

i-manager's Journal on Future Engineering and Technology (JFET)

Current Issue Vol. 20 Issue 1

Biomaterial Strategies for Immune System Enhancement and Tissue Healing
Qualitative and Quantitative Performance Optimization of Simple Gas Turbine Power Plant using Three Different Types of Fuel
Efficient Shopping: RFID-Powered Cart with Automated Billing System
Medical Drone System for Automated External Defibrillator Shock Delivery for Cardiac Arrest Patients
A Critical Review on Biodiesel Production, Process Parameters, Properties, Comparison and Challenges
Review on Deep Learning Based Image Segmentation for Brain Tumor Detection

Most Cited

Volume 2 Issue 1 August - October 2006

Article

Segmentation Algorithm Using FCM: Application to MRI Brain Image

G. Wiselin Jiji* , L. Ganesan**

*Assist Professor ,Information Technology, Dr. Sivanthi Aditanar College Of Engineering, Tiruchendur

** HOD ,Computer science and engineering, A.C. College of Engg. and Technology, Karaikudi.

G. Wiselin Jiji and L. Ganesan (2006). Segmentation Algorithm Using FCM: Application to MRI Brain Image. i-manager’s Journal on Future Engineering and Technology, 2(1), 10-13. https://doi.org/10.26634/jfet.2.1.956

Abstract

Segmentation is the most common way to identify various constituents of an image. In medical image visualization and analysis, segmentation is an indispensable step in the processing of images. In this paper, we propose an unsupervised fuzzy based segmentation to derive the homogeneity measure for partitioning the regions of the image during the process of segmentation. The proposed approach proceeds in 2 stages. Initially, a Fuzzy C-Mean algorithm is used to provide a partition of the image. In the second Stage, a decision process by applying a global analysis followed by a fine segmentation which is only focused on ambiguous points. The feasibility and effectiveness of the proposed method is evaluated with the various types of MRI brain images to identify the components of brain, in turn, used to locate the brain tumour and its growth rate.

References

[1]. Timothy J.Ross ."Fuzzy Logic with Engineering applications" McGrawHill International Editions.

[2], Angiographic Images," IEEE Trans, on Med. Imaging, vol. 11, pp. 416-429,1992.

[3]. J. C. Bezdek and R F. Castelaz, "Prototype Classification and Feature Selection With Fuzzy Sets," IEEE Trans, on Systems, Man and Cybernetics, vol. SMC-7, pp. 87-92,1977.

[4], N. Boujemaa, G. Stamon, A. Gagalowicz, "Modelisation floue pour la segmentation d'images," 9,me CongrSs AFCET de Reconnaissance de Formes et Intelligence Artificielle, pp. 163-173, France, 1994.

[5], J.C.Bezdek.R.Ehrich and W.Full, 1984 FCM :the fuzzy C-Means Clustering Algorithm.

[6], M.S.Kamel and S.Z.Selim,1994, New algorithms for solving the fuzzy clustering problem.

[7], Freeman WJ (1992) Tutorial in neurobiology: From single neurons to brain chaos. International Journal of Bifurcation and Chaos 2:451 -482.

[8]. D. Metaxas and D. Terzopoulos, \Shape and nonrigid motion estimation trough Physicsbased synthesis," IEEE- PAMI15, pp. 580-591,1993.

[9]J.J-M. Morel and S. Solimini, Variational Methods in Image Segmentation, Birkhauser, Boston, 1994.

[10].D. Mumford and J. Shah, \Optimal approximations by piecewise smooth functions and variational problems," Comm. Pure and App. Math. 42,1989,

[11]. R. Nevatia, A color edge detector and its use in scene segmentation," IEEE Trans.Syst. Man, Cybern., 7, pp. 820-826,1977.

[12].J. Shah, Segmentation by nonlinear di_usion," Proc. IEEE-CVPR, 1991.

[13].J. Shah, Recovery of shapes by evolution of zero- crossings," Technical Report, Math. Dept. Northeastern Univ. Boston MA, 1995.

[14]. H.M. Soner, Motion of a set by the curvature of its boundary," J. of Di_. Equations 101, pp. 313-372,1993.

[15]. W. S. Stiles, A modied Helmholtz line element in brightness-colourspace," Proc. Phys. Soc. (London) 58, p. 41,1946.

[16].G. Berks, D.G. Keyserlingk, J. Jantzen, M. Dotoli, H. Axer, Fuzzy Clustering-A Versatile Mean to Explore Medical Database, ESIT2000, Aachen, Germany.

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Research Paper

Design and Realization of an Integrated Wireless Networking System

Daoud I. Zatari* , Abdul Rahim Tamimi**

*Electrical and Computer Engineering Department Palestine Polytechnic University ,Palestine.

**Computer Center,Palestine Polytechnic University,Palestine.

Daoud I. Zatari and Abdul Rahim Tamimi (2006). Design and Realization of an Integrated Wireless Networking System. i-manager’s Journal on Future Engineering and Technology, 2(1), 65-70. https://doi.org/10.26634/jfet.2.1.980

Abstract

This paper describes the design, implementation and management of an integrated partial physical infrastructure of a wireless local and wide area (WLAN, WWAN) networking system. The system objectives are to serve and support the existing networking and data communications services of Palestine Polytechnic University PPU, and to facilitate connectivity of buildings within university campuses. The system consists of two main components: the first one represents a WLAN that is based on the communication protocol 802.11b, whiles the second represents the WWAN that connects two main buildings using two access points and radio frequency transmission technology. As a measure of performance, preliminary results showed that the system maintains an acceptable and secure data transfer rate between the sending and receiving sites. The speed of data while connection is maintained varies in the range of 2 to 10 Mbps and 10 to 50 Mbps for an indoor WLAN and an outdoor WWAN respectively. These findings are a good evidence of the efficiency of the integrated communication system with low operational cost and with feasible practical implementation.

References

[1], IEEE 802.11 Working Group, Wireless LAN medium access control (MAC) and physical layer (PHY) specifications, in: ANSI/IEEE Standard 802.11, August 1999.

[2], K. Sundaresan et al., "IEEE 802.11 over multi-hop wireless networks: problems and new perspectives". Ad Hoc Networks 2 (2004) 109132

[3]. H.-Y. Hsieh, R. Sivakumar, Performance comparison of cellular and multi-hop wireless networks: a quantitative study, in: Proceedings of ACM SIGMETRICS, Boston, MA June 2001.

[4].M. Frodigh, S. Parkvall.C. Roobol, R Johansson, R Larsson, Future-gene ration wireless networks, IEEE Personal Communications 8 (5) (2001) 1017.

[5].Konstantinos A. Banitsasl, Sapal Tachakra2, Robert S. H. Istepanianl, "Operational Parameters of a Medical Wireless LAN: Security, Range and Interference issues".

[6]. Cisco, "Wireless LAN Security", white paper, 2002

[7]. http://www.symbol.com/

[8].R. David Vernon, "Cornell Data Networking: Wired vs. Wireless ", http://www.cit.cornell.edu/oit/Arch- Init/wireless.html

[9]. Daoud I. Zatari and Hani Salah, "Measurement of Signal Propagation for the Design of a Wireless Local Area Network", Annales des telecommunications, 2006, submitted for publication.

[10].Pechac, (R), Klepal, (M.) Empirical Models for IndoorPropagation in CTU Prague Buildings.Radioengineering, April 2000, vol. 9, no. 1, p. 31 -36.

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Article

Non-Identical Parallel Machine Scheduling Using Simulated Annealing Technique

K. Raja* , C. Arumugam, V. Sella durai*, K.M. Senthil Kumar****

Senior lecturer ,Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore.

Selection Grade Lecturer,Mechanical Engineering Department of Coimbatore Institute of Technology, Coimbatore, India.

Professor ,Mechanical Engineering Department of Coimbatore Institute of Technology, Coimbatore, India.

****Lecturer , Mechanical Engineering Department of Coimbatore Institute of Technology, Coimbatore, India.

K. Raja, C. Arumugam, V. Selladurai and K.M. Senthil Kumar (2006). Non-Identical Parallel Machine Scheduling Using Simulated Annealing Technique. i-manager’s Journal on Future Engineering and Technology, 2(1), 14-19. https://doi.org/10.26634/jfet.2.1.958

Abstract

A generalized model for analyzing any manufacturing system is essential to improve its performance measures. Non - traditional optimization technique such as Simulated Annealing technique provides a complete solution methodology for solving the shop floor scheduling problems. The problem considered in this study consists of non-identical machines employed in parallel. Jobs ranging from 10 to 100 are to be processed on any one of the five non identical parallel machines. The objective is to reduce the completion time of the jobs. Simulated annealing methodology has been adopted to reach the optimal sequence. It has been found that the suggested optimization procedure arrives at the optimal solution at a reasonable time and is also found to outperform the existing heuristics.

References

[1]. Aarts, E. H. L., Van Laarhoven, R J. M., Lenstra, J. K., and Ulder, L. J., (1994), "A computational Study of Local Search Algorithms for Job Shop Scheduling", ORSA Journal on Computing, 5,118-125.

[2], Conway, R.W., Maxwell, W.L., and Miller, L.W., (1967), Theory of Scheduling, Addison-Wesley, Reading, MA.

[3], Eck, B.T., and M. Pinedo., (1993), "On the minimization of the make-span subject to flow time optimality''- Operations Research, 41,797-801.

[4], Hari Balasubramaniam., Lars Monch., John Fowler., Michele Pfund., (2004)," Heuristic Scheduling of Jobs on Parallel batch machines with incompatible job families and unequal ready times". International Journal of Production Research, 42(18): 1621.

[5]. Hutchison, J., (1990), "Current and Future Issues Concerning FMS Scheduling", OMEGA International Journal of Management Science, 19 (6), 529- 537.

[6], Ibarra. O. H., and C. E. Kim., (1977), "Heuristic algorithms for scheduling independent tasks on non¬identical processes". Journal of the Association for Computing Machinery, 24,280-289.

[7], Jain, A., and S. Meeran., (1998), "A state of the art review of job-shop scheduling Techniques", University of Dundee, Dundee, Scotland.

[8], Jose, A. Ventura., Deecheol Kim., (2003)," Parallel machine scheduling with earliness-tardiness penalties and additional resource constraints". Computers and Operations Research, 30( 13): 1945-1958.

[9], Jerald, J., Asokan, R, Prabaharan, G., Saravanan, R., (2005), "Scheduling optimization of flexible manufacturing systems using particle swarm optimization algorithm". International Journal of Advanced Manufacturing Technology, 25:964-971.

[10].J.Parthasarathy, S., C. Rajendran., (1998), "Scheduling to Minimize Mean Tardiness and Weighted Mean Tardiness in Flow shop and Flow line-based Manufacturing Cell", Computers and Industrial Engineering, 34 (2), 531 -546.

[11].J.Saravanan, R., Asokan, R, and Sachithanandam, M., (2001), "Comparative Analysis of Conventional and Non-Conventional Optimization Techniques for CNC Turning Process", International Journal of Advanced Manufacturing Technology, 17,471-476.

[12] .Saravanan, R., Asokan, R, and Vijayakumar, K., (2003), "Machining Parameters Optimization for Turning Cylindrical Stock into a Continuous Finished Profile Using Genetic Algorithm and Simulated Annealing", International Journal of Advanced Manufacturing Technology, 21,1-9.

[13] .Shmoys, D.B., and E. Tardos., (1993), "An approximation algorithm for the generalized assignment problem". Mathematical Programming, 62,461 - 474

[14] .Stuetzle, T., (1998),"An ant approach for the flow shop problem". Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT'98), Vol.3.Verlag Mainz, Aachen, Germany, pp, 1560-1564.

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Article

Comparative Performance Analysis of TCP Congestion Control Algorithms for the Efficiency Improvement of E-learning Applications

M. Chandrasekaran* , N. Kannan, Kalpana M*

Assistant Professor ,Electronics and communication Engineering department at Government College of Engineering, Salem.

Assistant Professor ,Computer Science and Engineering Department at Jayaram College of Engineering and Technology, Trichy

Assistant Professor , Electronics and Communication Engineering Department at Jayaram College of Engineering and Technology, Trichy.

Chandrasekaran M, N. Kannan and Kalpana M (2006). Comparative Performance Analysis of TCP Congestion Control Algorithms for the Efficiency Improvement of E-learning Applications. i-manager’s Journal on Future Engineering and Technology, 2(1), 20-23. https://doi.org/10.26634/jfet.2.1.961

Abstract

This paper mainly aims at suggesting methods to improve the efficiency of the e-learning applications by making use of the optimal TCP/IP Congestion control algorithm. This is done by first analyzing the various TCP Congestion control algorithms and comparing their performance. An investigation of some of the TCP/IP congestion control algorithms implemented in ns2 is done. Then the performance of these algorithms in a TCP/IP Network is studied. A Dumbbell topology with 9 source nodes each operates with a different congestion control algorithm is simulated using ns2. Using this topology, the performance of these algorithms is compared by evaluating their total throughput and bandwidth sharing of the bottleneck link. This comparison results into the suggestion of the algorithm TCP/Reno for improving the efficiency of the e-learning application, as it provides the maximum long term total throughput of all the algorithms.

References

[1 ]. Van Jacobson, "Congestion Avoidance and Control," ACM Computer Communication Review, vol.18, pp. 314-329, Aug. 1988. Proceedings of the Sigcomm '88 Symposium in Stanford, CA, August 1988.

[2], M. Allman and V. Paxson, TCP Congestion Control, Internet Engineering Task Force, April 1999, RFC 2581.

[3], Sally Floyd and Kevin Fall, "Promoting the use of end- to-end congestion control in the Internet," IEEE/ACM Transactions on Networking, vol. 7(4), pp. 458472, August 1999.

[4], Deepak Bansal and Hari Balakrishnan, "Binomial congestion control algorithms," in Proceedings of IEEE INFOCOM. April 2001.

[5]. Y. Richard Yang and Simon S. Lam, "General AIMD congestion control," in Proceedings of ICNP, November 2000.

[6], Lawrence S. Brakmo and Sean W. O'Malley, "TCP Vegas: New Techniques for Congestion Detection and Avoidance," in SIGCOMM '94 Conference on Communications Architectures and Protocols, (London, United Kingdom), pp. 24-35, Oct. 1994,

[7]. D. Bansal and H. Balakrishnan, "TCP-friendly Congestion Control for Real-time Streaming Applications," Tech. Rep. MIT-LCS-TR-806, MIT Laboratory for Computer Science, May 2000

[8]"ns-2 Network Simulator,"http://www.isi.edu/nsnam/ns/, 2000.

[9], S. Floyd and V. Jacobson, "Random Early Detection Gateways for Congestion Avoidance," IEEE/ACM Transactions on Networking, vol. 1, no. 4, Aug. 1993

[10]. Tejas Kokje Vijay Kakadia, ’ Analysis of Congestion Control Strategies For TCP Variants Using Droptail and RED Queuing Disciplines Department of Computer Science University of Southern California, Los Angeles

[11 ]. http://www.e-learningguru.com.

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Research Paper

Coated and Alloyed Effects of Ti, Zr and Hf on Reactive Wetting of Al2O3

H. Adanir O.T. Inal* , F.G. Yost**

*Materials and Metallurgical Engineering Dept.,New Mexico Tech ,Socorro,NM.

**Trapezium Technology ,Albuquerque NM.

H. Adanir O.T. Inal and F.G. Yost (2006). Coated and Alloyed Effects of Ti, Zr and Hf on Reactive Wetting of Al2O3. i-manager’s Journal on Future Engineering and Technology, 2(1), 24-29. https://doi.org/10.26634/jfet.2.1.964

Abstract

In this study, alloying and coating effects of active metals (Ti, Zr and Hf) alloyed with Sn were investigated on reactive wetting of Al2O3 at 1273K. To investigate the effect of alloying, Sn-6wt.%Ti, Sn-6wt.%Zr and Sn-6wt.% Hf alloys were prepared for sessile drop tests on polished Al2O3. Average contact angles measured were 68o, 60o and 68.5o, respectively. For the effect of coating, Al2O3 substrates were coated with TiO2, ZrO2 and HfO2, and sessile drop tests were done with pure Sn. Average contact angles measured were 36o, 28 o and 34.7o, respectively. In both cases, polished and coated (with TiO2, ZrO2 or HfO2) Al2O3 substrates, the measured contact angles were equal to or lower than 70o. Substrates were effectively wetted by Sn alloyed with active metals (Ti, Zr, Hf) as well as pure molten Sn. XRD, DTA, metallography techniques and SEM were used to characterize the braze alloys and cross sections of the wetted substrates. XRD results for wetted substrate cross-sections revealed the intermetallics TiAl3, ZrAl, and HfAl as reaction products. The most important result stemming from this work is that a reaction between active metal components and the substrate does not necessarily lead to lower contact angles.

References

[1].M.M. Schwartz, Ceramic Joining, ASM Inti. Metals Park, OH, 1990, pp. VII-140.

[2].M.M. Schwartz, Brazing, ASM International, Metals Park, OH, 1987, pp.315.

[3].I. Barin, Thermochemical Data of Pure Substance, Vol. 1, 2nd Edit., VCH, Duisburg, Germany, 1993, pp.l 7-190¬357-586-618.

[4].I. Barin, Thermochemical Data of Pure Substance, Vol. 2,2ndEdit.,VCH, Duisburg, Germany, 1993, pp.l 127-1681.

[5]. Y.M. Chiang, D. Birnie III, W.D. Kingery, Physical Ceramics, John Wiley & Sons, MIT Series in Materials Science and Engineering, 1997, pp. 361

[6]. D.V. Ragone, Thermodynamics of Materials, Vol, II, The MIT Series, John Wiley and Sons, Inc., 1995, pp. 8-98.

[7]. J. Emsley, The Elements, Oxford University Press, 1989, pp.80-198-214.

[8]. F.G. Yost and A.D. Romig, Electronic Packaging Materials Science III, Material Research Symposium Proceeding, 1988, pp. 385-390.

[9]. I. Aksay, C.E. Hoge and J.A. Pask, J. Phys.Chem., 1974,vol.78,pp.1178-1183.

[10].V. Laurent, D. Chatain and N. Eustathopoulos, Mat. Sci. Eng., 1991, vol. A135, pp.89-94.

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Research Paper

Modeling of holographic Imaging using modified Covariance Method

Mujahid Fahmy Al-azzo*

Department of communication and Electronic Engineering Faculty of Engineering, Philadelphia University- Jordan.,Amman

Mujahid Fahmy Al-azzo (2006). Modeling of holographic Imaging using modified Covariance Method. i-manager’s Journal on Future Engineering and Technology, 2(1), 30-35. https://doi.org/10.26634/jfet.2.1.965

Abstract

A high resolution modified covariance method is applied to modeling an ultrasonic holographic imaging of concealed objects. In-line holography is used to increase the signal to noise ratio. Different concealing materials are used. The results are compared with the traditional, Fourier transform, method. The performance is investigated for different values of signal to noise ratio.

References

[l].S.L. Marple 'Digital Spectral Analysis with applications", Englewood Cliffs,NJ: Prentice Hall,1987.

[2]. S. Cavalcanti, L. Chiari, S. Severi, G.Avanzolini, G. Enzmann, C. Lamberti "Parametric analysis of heart rate variability during hemodialysis". International Journal of Bio-Medical Computing, vol.42, no.3,Aug. 1996.p.215- 224.

[3]. A. viznho, L.R.Wyatt "Evaluation of the use of the modified-covariance method in HF radar ocean measurement", IEEE Journal of Ocean Engineering, vol.26, no.4, p832-840, Oct. 2001.

[4]. Proc. IEEE, Special Issue on "Acoustic imaging", vol.67, no.4, p.452-675 Apr. 1979.

[5].V. A. Deason, K.L. Telschow, S.M. Watson "Imaging of acoustic waves in sand", Proc. of SPIE, vol.5191, p 1-7, Nov. 2003.

[6].Sidhu,.S.Paul, Ultrasound of abdominal transplantation, Stuttgart:thieme 2002.

[7].J.W. Goodman, "Introduction to Fourier Optics" Third Edition, Roberts &Company Publisher, 2004.

[8]. Grilli, S., Ferraro, P, De Nicola, S. Finizio, A., Pierattini, G., Meucci, R., "Whole optical wavefields reconstruction by Digital holography". Optics Express 9 (6),p 294-302,2001.

[9]. A.Greve, D.Morris "Repetitive radio Reflector surface deformation" IEEE Trans, Antennas & Propagation, vol,53, no.6, p 2123-2126, June 2005.

[10] . G.F.Garlick, J.O.Shelby "Detector inultrasonic holography" J.Acoustic Soc.Am., vol. 114, no.6, p 2995 March 2004

[11]. E.Julliard, S.Pauzin, F.Simon, D.Biron"Acoustic sources' localization in presenceofreverberation" J.Acoustic Soc.Am., vol. 118, no.3, p 1886 Sept. 2005.

[12], D. Carl, B. Kemper, and G. VonBally, "Parameter- optimized digital holographic microscope for high- resolution living cell analysis". Applied Optics 43 (36), 2004, p 6536-6544.

[13].P.Roux, Diedercasserau, A. Roux, "A high resolution algorithm for wave number estimation using holographic array processing", J.Acoustic Soc.Am., vol. 115, no.3, March 2004.

[14]. A.R Anderson, "Microwave holography",IEE Proc., vol, 129, part H, Aug. 1982,

[15].U.Schnars "Digital holography:digital holograms recording,numerical reconstruction and related techniques" Werner Jueptner 2004.

[16]. G.Saxby "Practical holography" Third Edition, Taylor & Francis, 2003.

[17]. K. H. Sayidmarie, A. R Anderson, J.C. Bennet, "Digital in-line holographic techniques for long wavelength imaging", Proc. IEE, vol. 129, part h, No.4, Aug. 1982. p 211-220.

[18].S. M. Kay "Modern spectral estimation", Prentice Hall, New Jersey, 1988.

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Research Paper

Comparison of Pi and Fuzzy Logic Control for Harmonic Reduction in Power Electronic Converters

E. Chandra Sekaran* , P. Anbalagan**

*senior grade lecturer, Department of EEE,Coimbatore Institute of Technology.

**Professor and Head of the Department, Department of EEE ,Coimbatore Institute of Technology

E. Chandra Sekaran and P. Anbalagan (2006). Comparison of Pi and Fuzzy Logic Control for Harmonic Reduction in Power Electronic Converters. i-manager’s Journal on Future Engineering and Technology, 2(1), 36-41. https://doi.org/10.26634/jfet.2.1.969

Abstract

The deterioration of currents and voltages in electrical networks is due to the presence of non-linear loads (rectifiers, variable speed transmissions, lighting etc) absorbing non sinusoidal currents. These harmonic current circulate in the electrical network, disturb the correct operation of the components and can even generate their destruction. So the reduction of harmonic component becomes essential. In this paper, harmonic reduction using PI and fuzzy logic control has been proposed for a AC-DC converter. The proposed control logic is simulated using MATLAB/SIMULINK and the results are compared.

References

[1].Jain.S.K.Agrawal .P,and Gupta.H.O,"Simulation and experimental investigation on shunt active power filter for harmonics and reactive power compensation" IETE Technical Review, Vol. 20, No, 6, November/December 2003, pp. 481-492.

[2].B.Wayne bequette, "Process control modeling, design and simulation", Prentice hall of India, 2003, pp 196-198.

[3].S.KJain, RAgarwal and H.O.Gupta, "Fuzzy logic controlled shunt active power filter for power quality improvement", IEE Proc-Electr. 149, No.5, September 2002, pp31 7-328.

[4].Mack Grady.W, Santoso.S, "Understanding Power System Harmonics" IEEE Power Engineering Review, September 2001, pp. 1 -6.

[5].Chang.G.W, "Harmonics theory" IEEE Power Engineering Review, January 1998, pp.8-16.

[6].Chang.G.W, "Harmonics theory" IEEE Power Engineering Review, January 1998, pp.8-16.

[7].Mack Grady.W, Santoso.S, "Understanding Power System Harmonics" IEEE Power Engineering Review, September 2001, pp. 1 -6.

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Research Paper

Solidification Simulations Coupled With Neural Networks for Prediction of Secondary Dendrite Arm Spacings in Sand Castings

D. Hanumantha Rao* , G.R.N. Tagore, G. Ranga Janardhana*

Associate professor of Mechanical Engineering, Deccan college of Engineering and technology, Hyderabad.

Professor & Head, Dept. of Meeh. Engg. at National Institute of Technology, WARANGAL

Professor of Mechanical Engineering, Jawaharlal Nehru Technological University, Hyderabad.

D. Hanumantha Rao, G.R.N. Tagore and G.Ranga Janardhana (2006). Solidification Simulations Coupled With Neural Networks for Prediction of Secondary Dendrite Arm Spacings in Sand Castings. i-manager’s Journal on Future Engineering and Technology, 2(1), 42-49. https://doi.org/10.26634/jfet.2.1.970

Abstract

Systematic knowledge accumulation regarding casting process is essential in order to obtain optimal process conditions. A number of factors define the metallurgical structure in castings of which primary importance is secondary dendrite arm spacing. Controlling the rate of solidification can control dendrite structure. The objective of the present paper is to study the influence of casting process parameters like pouring temperature, insulation on riser, chill thickness and chill contact area on the microstructure parameter secondary dendrite arm spacing. A component of material aluminum alloy A356 is used in the present study. Neural networks are widely used in solving complicated mathematical problems whose analytical description is very difficult and computationally demanding. Design of experiments are used for experimental simulations using finite difference method. The developed neural network models are trained using the response obtained from solidification simulation. The predicted secondary dendrite arm spacing values from neural network are found to be in reasonable agreement with the simulation results and the effect of varied input values on output response is also obtained through sensitivity analysis.

References

[1]. F.Mampaey 'Practical Examples Using the Finite Volume method for Simulating the Casting Process' AFS Transactions 01-075.

[2]. K.S.Lee, J.C.lin " Design of the runner and gating system paprameters for a multi-cavity injection muold using FEM and neural network" Inti. Journal Adv. Manuf. Tech. (2005).

[3]. M.Joseph Davidson et all " A neural network and reposne surface methodology based surface roughness prediction model for EDM"- Journal of Manufacturing technology today, July 2005.

[4]. Mahesh B. Parappagoudar et all 'Green Sand Mould System Modelling Through Design of Experiments' Indian Foundry Journal April 2005

[5]. Jukka Heikkonen and Jouko Lampinen, "Building Industrial Applications with Neural Networks" - Helsinki University of Technology, Laboratory of Computational Engineering Finland.

[6]. Eichlseder W.: 'Influence of Dendrite-Arm-Spacing on Fatigue Life1,4th FEMFAT User Meeting, 7th-9th May 2003, Steyr/Austria

[7]. XU Qingyan, LIU Baicheng 'Numerical Modeling of Dendrite Growth in Al Alloys'- Tsinghu science and technology-Vol. 9, Number5, Oct 2005.

[8].Merton C.Flemings' Solidification Processing'

[9]. John Campbell 'Castings'. Butterworth-Heinemann ltd

[10].Dale H.Besterfield et all 'Total Quality Management' Pearson Education

[11]. Jiju Antony 'Design of experiments for Engineers and Scientists' Butterworth Heinemann.

[12]. J.S.R.Jung, C.T.sun, E.Mizutnai "Neuro-Fuzzy and soft computing" Prentice hall of India.

[13]. User manuals of Virtual Casting.

[14], User manuals of Neuro Solutions.

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Research Paper

Implementation and Calibration of Real Time Posture Tracking Of Human Limb Segment Motions

N. Suthanthira Vanitha* , V. Palanisamy, M. Mani*

Research Scholar,(Anna University)Govt.College of Engg ., Salem.

Principal ,Govt .College of tech ,Coimbatore.

Lecturer,K.S.R.College of Tech,Tiruchengode

N. Suthanthira Vanitha, V. Palanisamy and M. Mani (2006). Implementation and Calibration of Real Time Posture Tracking Of Human Limb Segment Motions. i-manager’s Journal on Future Engineering and Technology, 2(1), 50-56. https://doi.org/10.26634/jfet.2.1.974

Abstract

This paper mainly deals with the software implementation of the quaternion filter algorithms and calibration algorithms for the sensors. Rigid body orientation may be determined without the aid of a generated source using a nine-axis Magnetic field, Angular Rate, and Gravity sensor containing three orthogonally mounted rate sensors, linear accelerometers and magnetometers. It describes a system designed to determine the posture of an articulated body in real-time. In the system the orientation of each segment relative to an Earth-fixed reference frame is individually determined through the use of an attached source less sensor. The orientations are used to set the posture of an articulated body model. Details of the fabrication of a prototype MARG sensor and a human body model designed to accept Earth-fixed reference orientation data are also described. Experimental results demonstrate the effectiveness of the tracking system and verify the correctness of the underlying theory.

References

[1]. Bray, J. & Sturman, C., Bluetooth: Connect without Cables, Prentice Hall, Inc., 2000.

[2]. Brown, R. & Hwang, R, Introduction to Random Signals and Applied Kalman Filtering, Second Edition, John Wiley and Sons, Inc., New York, NY., 1992.

[3]. Caruso, M., Set/Reset Pulse Circuits for Magnetic Sensors, Honeywell, Inc., 1995.

[4]. Cormen, T., Leiserson, C., & Rivest, R. Introduction to Algorithms McGraw-Hill, New York, 1994.

[5]. Crossbow Inc., Crossbow CXL04M3 Data Sheet., 1998.

[6]. Durlach, N. & Mayor, A. (Eds.), and National Research Council, Virtual Reality Scientific and Technological Challenges, National Academy Press, Washington, D.C., pp. 188 -204,306-317,1995.

[7]. Funda, J., Taylor, R., & Paul, R., "On Homogeneous Transforms, Quaternion, and Computational Efficiency," IEEE Transactions on Robotics and Automation, Vol. 6, No. 3, pp. 382-388,1990.

[8]. Honeywell Inc., Honeywell Three-Axis Hybrid, HMC2003,1998,

[9]. McGhee, R., "Some Parameter-Optimization Techniques," Digital Computer User's Handbook, McGraw-Hill, pp. 234-253,1967.

[10]. McKinney, D., McKinney Technology, 9 Glen Avenue, Prunedale, CA, 93907, doug@mt.to.

[11]. Watt, A. and M. Watt, 1992. Advanced Animation and Rendering Techniques, Theoryand Practice. NY.

[12]. Bachmann, E. R., Duman, I., Usta, U. Y., McGhee, R.B., Yun, X. R, Zyda, M. J., "Orientation Tracki For Humans and Robots Using Inertial sensors,"Proc of 1999 Symposium on Computational.

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Research Paper

Experimental Study on Axial Behaviour of R.C Columns Subjected To Steel Corrosion under Loading

M. Usha Rani* , K. Subramanian**

*Faculty of Civil Engineering at VL.B. Janakiammal College of Engineering and i Technology, Coimbatore

**Professor and Head of Civil Engineering Department, Coimbatore Institute of Technology,Coimbatore.

M. Usha Rani and K. Subramanian (2006). Experimental Study on Axial Behaviour of R.C Columns Subjected To Steel Corrosion under Loading. i-manager’s Journal on Future Engineering and Technology, 2(1), 57-64. https://doi.org/10.26634/jfet.2.1.975

Abstract

This paper examines and analyzes the test results produced from a comprehensive test program designed to study the axial behaviour of reinforced concrete columns subjected to steel corrosion under service loads. Several small size concrete columns with various reinforcement configurations were subjected to accelerated corrosion condition in the laboratory. After a target level of corrosion the column specimens were tested to study the failure mode, load-strain behaviour, crack load and ultimate load. The corrosion level was measured based on the loss in weight of the reinforcement1. Uncorroded columns were used as control samples and tested in parallel with the corroded samples.

References

[1 ].LamyaAmleh and Saeed Mirza, Corrosion influence on bond between steel and concrete. Title No. 96-S46, ACI Structural Journal/ May-June 1999, pp 415-423.

[2].John F. Bonacci and Mohamed Maalej, Externally Bonded Fibre-Reinforced Polymer for Rehabilitation of Corrosion Damaged Concrete Beams, Title No. 97-S71, ACI Structural Journal/ September-October 2000, pp 703-711.

[3].Daksh Baweja, Harold Roper, and Vute sirivivatnanon, Chloride-induced Steel corrosion in concrete: part 1- Corrosion Rates, Corrosion Activity, and Attack Areas, Title No. 95-M19, ACI Materials Journal I May-June 1998, pp 207-214.

[4].Pantazopoulou S.J, Bonacci. J.F, .Sheikh.S, Members, ASCE, Thomas M.D.A., and Hearn.,N "Repair of Corrosion- Damaged Columns with FRP Wraps" Journal of Composites for Construction, February 2001, pp3-l 1.

[5].Ballim. Y, Reid. J.C and Kemp. A.R, Deflection of RC beams under simultaneous load and steel corrosion. Magazine of concrete research ,2001,53,No.3, Junel 71 - 181.

[6].yuBun Auyeung, Balaguru, and Lan Chung" Bond Behavior of corroded Reinforcement Bars, title no. 97- M28.ACI materials Journal March/April 2000 pp214 220.

i-manager's Journal on Future Engineering and Technology (JFET)

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*Materials and Metallurgical Engineering Dept.,New Mexico Tech ,Socorro,NM. **Trapezium Technology ,Albuquerque NM.

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Department of communication and Electronic Engineering Faculty of Engineering, Philadelphia University- Jordan.,Amman

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D. Hanumantha Rao* , G.R.N. Tagore**, G. Ranga Janardhana***

*Associate professor of Mechanical Engineering, Deccan college of Engineering and technology, Hyderabad. **Professor & Head, Dept. of Meeh. Engg. at National Institute of Technology, WARANGAL ***Professor of Mechanical Engineering, Jawaharlal Nehru Technological University, Hyderabad.

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N. Suthanthira Vanitha* , V. Palanisamy**, M. Mani***

*Research Scholar,(Anna University)Govt.College of Engg ., Salem. **Principal ,Govt .College of tech ,Coimbatore. ***Lecturer,K.S.R.College of Tech,Tiruchengode

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M. Usha Rani* , K. Subramanian**

*Faculty of Civil Engineering at VL.B. Janakiammal College of Engineering and i Technology, Coimbatore **Professor and Head of Civil Engineering Department, Coimbatore Institute of Technology,Coimbatore.

M. Usha Rani and K. Subramanian (2006). Experimental Study on Axial Behaviour of R.C Columns Subjected To Steel Corrosion under Loading. i-manager’s Journal on Future Engineering and Technology, 2(1), 57-64. https://doi.org/10.26634/jfet.2.1.975

Abstract

References

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Pdf

*Assist Professor ,Information Technology, Dr. Sivanthi Aditanar College Of Engineering, Tiruchendur

** HOD ,Computer science and engineering, A.C. College of Engg. and Technology, Karaikudi.

*Electrical and Computer Engineering Department Palestine Polytechnic University ,Palestine.

**Computer Center,Palestine Polytechnic University,Palestine.

K. Raja* , C. Arumugam, V. Sella durai*, K.M. Senthil Kumar****

M. Chandrasekaran* , N. Kannan, Kalpana M*

*Materials and Metallurgical Engineering Dept.,New Mexico Tech ,Socorro,NM.

**Trapezium Technology ,Albuquerque NM.

*senior grade lecturer, Department of EEE,Coimbatore Institute of Technology.

**Professor and Head of the Department, Department of EEE ,Coimbatore Institute of Technology

D. Hanumantha Rao* , G.R.N. Tagore, G. Ranga Janardhana*

Associate professor of Mechanical Engineering, Deccan college of Engineering and technology, Hyderabad.

Professor & Head, Dept. of Meeh. Engg. at National Institute of Technology, WARANGAL

Professor of Mechanical Engineering, Jawaharlal Nehru Technological University, Hyderabad.

N. Suthanthira Vanitha* , V. Palanisamy, M. Mani*

Research Scholar,(Anna University)Govt.College of Engg ., Salem.

Principal ,Govt .College of tech ,Coimbatore.

Lecturer,K.S.R.College of Tech,Tiruchengode

*Faculty of Civil Engineering at VL.B. Janakiammal College of Engineering and i Technology, Coimbatore

**Professor and Head of Civil Engineering Department, Coimbatore Institute of Technology,Coimbatore.