Volume-5 Issue-1

 Download Abstract Book

S. No

Volume-5 Issue-1, March 2016, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Sagar Vairagar, Shubhangi Vairagar, Shyam Sunder Gupta

Paper Title:

Efficient Peer to Peer Content Sharing using Wi-Fi

Abstract:      As mobile environment is becoming popular; it becomes very effective and quick way of sharing user contents between users. This content sharing using Peer to peer scheme is limited due to the lesser distance factor and continuous availability of communication medium. Whenever large file size transfer is required, it requires more time and limitation on radius. Additionally content sharing is in plain format without any security considerations. Peer-to-peer networks offer several advantages over traditional client-server networking models like lack of connectivity to reliable hosts or servers and the use of inexpensive communication channel. Peer-to-peer network model has becoming popular in the wired broadband environment but not yet been effectively adapted to the mobile network environment. Many researchers are currently proposing and developing new P2P schemes for mobile environments with different wireless communication protocols. They are significantly adapted into applications such as the sharing of large files like multimedia and DB files between mobile devices. The peer-to-peer model based on mobile environment having several challenges like the limited on device processing power, limited memory, wireless data bandwidth, and available battery energy. With the proposed a peer-to-peer protocol, these specific constraints are addressed. This system also investigates the feasibility of a practical implementation of a peer-to-peer file sharing model of android smart phones using Wi-Fi technology. This includes an analysis of impacted performance by various variables that can be dynamically controlled in the protocol. Proposed work is done on leading Android platforms and found various optimal strategies which include minimizing the upload and download ratio to conserve battery life effectively, using flexible file segments to increase throughput, and decrease memory overhead.

Bluetooth, Wi-Fi, Peer-to-peer communication, wireless communication..


1.       Piotr K. Tysowski, Pengxiang Zhao, KshirasagarNaik, “Peer to Peer Content Sharing on Ad Hoc Networks of Smartphones”,In proceeding of: Proceedings of the 7th International Wireless Communications and Mobile Computing Conference, IWCMC 2011, Istanbul.
2.       M. G. Williams, “Directions in Media Independent Handover”, IEICE Trans. Fundam. Electron. Commun. Comput. Sci., vol. E88-A, no. 7, pp. 1772–1776, 2005.

3.       R. Winter, T. Zahn, and J. Schiller, “Dynamo: A topology-aware p2p overlay network for dynamic, mobile ad-hoc environments”, Telecommunication Systems, vol. 27, no. 2, p. 321, 2004.

4.       Rowstron and P. Druschel, “Pastry: Scalable, decentralized object location, and routing for large-scale peer-to-peer systems”, Lecture Notes in Computer Science, vol. 2218, 2001.

5.       Datta, “Mobigrid: P2P overlay and MANET rendezvous — a data management perspective”, in CAiSE 2003 Doctoral Symposium”, 2003.

6.       K. Aberer, P. Cudr´e-Mauroux, A. Datta, Z. Despotovic, M. Hauswirth, M. Punceva, R. Schmidt, and J.Wu, “Advanced peer-to-peer networking: The p-grid system and
its applications”, PIK Journal – Praxis der Information sverarbeitung und Kommunikation, Special Issue on P2P Systems, 2003.

7.       Symbian OS, the mobile operating system. [Online]. Available: www.symbian.com

8.       R. Schollmeier, I. Gruber, and F. Niethammer, “Protocol for Peer-to-Peer  Networking in Mobile Environments,” in Computer Communications and   Networks, 2003. ICCCN 2003. Proceedings. The 12th International Conference on, 20-22 Oct. 2003, pp. 121–127.

9.       M. Matuszewski, N. Beijar, J. Lehtinen, and T. Hyyrylainen, “Mobile Peer-to-Peer content sharing application”, in Consumer Communications and Networking Conference, 2006. CCNC 2006. 2006 3rd IEEE, vol. 2, 8-10 Jan. 2006, pp. 1324–1325.

10.    T. Hakkarainen, V. Savikko, and A. Lattunen, “Generic engine for collaborative mobile applications,” in Proceedings of the IADIS International Conference WWW/Internet 2005 (ICWI2005), 2005, pp. 243 – 246.

11.    M. Bisignano, G. Di Modica, and O. Tomarchio, “JMobiPeer a middleware for mobile Peer-to-Peer computing in MANETs”, in Distributed Computing Systems Workshops, 2005. 25th IEEE International Conference on, 6-10 June 2005, pp. 785–791.
12.    G. Kortuem, J. Schneider, D. Preuitt, T. Thompson, S. Fickas, and Z. Segall, “When Peer-to-Peer comes face-to-face: collaborative Peer-to-Peer computing in mobile ad-hoc networks,” in Peer-to-Peer Computing, 2001. Proceedings. First International Conference on, 27-29 Aug. 2001, pp. 75–91.
13.    K. Kant, “An analytic model for peer to peer file sharing networks”, in IEEE International Conference on Communications, May 2003, pp. 1801 – 1805 vol. 3.

14.    Legout, G. Urvoy-Keller, and P. Michiardi, “Rarest First and Choke Algorithms Are Enough”, in IMC’06, Rio de Janeiro, Brazil, 2006.

15.    Yang, X. et al, “Service capacity of peer to peer networks”, in 23rd Joint Conference of IEEE Computer and Communications, 2004.

16.    Hu, T. H. et al, “Supporting mobile devices in Gnutella file sharing network with mobile agents”, in 8th IEEE Int. Symposium on Computers and Communication, Sep. 2003, pp. 1035 – 1040 vol. 2.

17.    Dhurandher, S. K. et al, “A swarm intelligence-based p2p file sharing protocol using bee algorithm”, in IEEE/ACS Int. Conf. on Computer Systems and Applications, 2009.

18.    Asadi, M. et al, “A scalable lookup service for p2p file sharing in manet,” in Proc. of the 2007 Int. Conference on Wireless Comm. and Mobile Computing. New York, NY, USA: ACM, 2007.

19.    Huang, C.-M. et al, “A file discovery control scheme for P2P file sharing applications in wireless mobile environments,” in Proc. of the 28th Australasian Conference on C.S., 2005.






Yogesh Ramdas Mahulkar, C. M. Sedani

Paper Title:

Performance of Heat Pipes under Different Inclinations and Working Fluids

Abstract:    For various applications of heat pipes are widely used according to heat conductivity capacity of working fluid. Based on the heat pipe capacity, heat pipes used in cooling electronic industry for controlling temperature of electronic parts. Some applications need to apply heat pipes at various inclinations for cooling purpose. So need to study heat pipes at various inclinations for best results in working condition. Here we study different heat pipes at various inclinations using different working fluids for heat pipe. Among various fluids, methanol as working fluid establishes best result at high and low inclination. The configuration of evaporator section heated with hot water provided inside evaporator jacket and condenser section cooled with liquid at atmospheric passed inside condenser jacket.

 heat pipe, working fluid, inclination, screen mesh, phosphorus bronze…


1.       Amir Faghri, Review and Advances in Heat Pipe Science and Technology, Journal of Heat Transfer, ASME DECEMBER 2012, Vol. 134 / 123001-1.
2.       M. N. Khan, Sandeep Pathak, Parametric study of the performance of heat pipe- a review, International Journal of Mechanical Engineering and Technology (IJMET), volume 4, Issue 1, January-February (2013), pp. 173-184.

3.       K. Mozumder1, A. F. Akon1, M. S. H. Chowdhury1 and S. C. Banik, PERFORMANCE OF HEAT PIPE FOR DIFFERENT WORKING FLUIDS AND FILL RATIOS, Journal of Mechanical Engineering, Vol. ME 41, No. 2, December 2010.

4.       Xue Zhihu, Qu Wei, Experimental study on effect of inclination angles to ammonia pulsating heat pipe, Chinese Journal of Aeronautics, (2014), 27(5): 1122–1127.

5.       Per Wallin, Heat Pipe, selection of working fluid, Project Report MVK160 Heat and Mass Transfer May 7, 2012, Lund, Sweden.

6.       Maziar Aghvami, Amir Faghri, Analysis of flat heat pipes with various heating and cooling configurations, Applied Thermal Engineering 31 (2011) 2645e2655.

7.       R. Senthilkumar, S. Vaidyanathan and B. Sivaraman, Performance investigation of heat pipe using aqueous solution of n-Pentanol with different inclinations, Journal of Mechanical Science and Technology 25 (4) (2011) 923~929 DOI 10.1007/s12206-011-0207-4.

8.       MOHAMED S. EL-GENK and LIANMIN HUANG, An experimental investigation of the transient response of a water heat pipe, Int J. Heat Mass Transfer. Vol.3 6, No. 15.&q 3823-3830,1993.






Yogesh Ramdas Mahulkar, C. M. Sedani

Paper Title:

Study of Parameters Affecting the Thermal Performance of Heat Pipe

Abstract:     The heat pipes are widely uses in many applications specially for cooling of electronic part industry and heat transfer industry. The need to study the capacity of heat pipe which changes according to applications and for better identification of the heat pipe for special application. Here we study the unlike heat pipes using dissimilar diameter, wire mesh layer and adiabatic section for diverse application of heat pipe. The heat pipe identified for use in special application with respect to its capability and limitation of heat pipe. Some heat pipe results in use for high capacity, low and high inclination, also according to limitations of heat pipe such as capillary limit, entrainment limit. The result detect the double wrapped screen wire mesh affords better result for each pipe diameter and adiabatic section. Also some modify in size of heat pipe diameter and adiabatic section have better than other heat pipe as changes observed in capillary limit and entrainment limit.

 heat pipe, capillary limit, entrainment limit, wrapped screen mesh, adiabatic section


1.     R.Manimaran, K.Palaniradja, N.Alagumurthi, J.Hussain, FACTORS AFFECTING THE THERMAL PERFORMANCE OF HEAT PIPE –A REVIEW, Journal of Engineering Research and Studies E-ISSN0976-7916.
2.     Leonard L. Vasiliev, Review Heat pipes in modern heat exchangers, Applied Thermal Engineering 25 (2005) 1–19.

3.     Per Wallin, Heat Pipe, selection of working fluid, Project Report MVK160 Heat and Mass Transfer May 7, 2012, Lund, Sweden.

4.     GEORGE FRANCHI and XIAO HUANG, Development of composite wicks for heat pipe performance enhancement, Heat transfer engineering, 29(10): 873-884, 2008.

5.     D. Somasundaram, A. Mani, M. Kamaraj, Numerical analysis of thermal performance of flat heat pipe, International Refrigeration and Air Conditioning Conference at Purdue, July 16-19, 2012.

6.     Zesheng LU, Binghui MA, Equivalent thermal conductivity of heat pipes, Front. Mech. Eng. China 2008, 3(4): 462–466.

7.     Enertron engineer, Heat Pipe Selection, Revision 12/04/2001.

8.     Mohamed H.A. Elnaggar, M.Z. Abdullah, M. Abdul Mujeebu, Experimental analysis and FEM simulation of finned U-shape multi heat pipe for desktop PC cooling, Energy Conversion and Management 52 (2011) 2937–2944.






Karen Niña P. Escosura, Ma. Margarita V. Ortega, Marlen Joyce H. Tuazon, Rovilyn L. Carta, Roselito E. Tolentino

Paper Title:

Real-Time Detection of Single-Text Character Using the Integration of Extremal Region Filtering and Connected Component Filtering

Abstract:    Nowadays, among all the contents in images, text information is the most significant value, may it be in a documented text or in a real-world scene. Text detection and recognition in an image is an important task in image analysis. Due to different properties, text detection is a challenging part in an image where textual content are very important. The previous study by Neumann and Matas limits the text detection and recognition in at least three characters. To extend the detection and recognition, especially of single text characters, the proposed solution is to integrate the two methods, Extremal Region Filtering and Connected Component Filtering with Tesseract OCR Engine. Single–text character candidates are filtered by the Connected Component Filtering, wherein the regions extracted and region features from the two stages of Extremal Region Filtering are considered. With structural analysis, connected components with equal value and similar stroke width and stroke orientation are considered single–text character candidates. Character candidates are recognized by the Tesseract OCR engine.

 connected component, extremal region, single-text, Tesseract


1.       Neumann, L. and Matas, J. (2012). Real-Time Scene Text Localization and Recognition. USA: 25th IEEE Conference on Computer Vision and Pattern Recognition.
2.       Smith, R. (2007). An Overview of the Tesseract OCR Engine. IEEE

3.       Tian, Y. and C. Yi (2011). Text String Detection from Natural Scenes by Structure-based Partition and Grouping. IEEE,.

4.       Eikvil, L. (1993). OCR Optical Character Recognition.

5.       Matas, J., Chum, O., Urban, M. and Pajdla T. (2004). Robust Wide Baseline Stereo from Maximally Stable Extremal Regions.

6.       Halgaonkar, P.S. (2011). Connected Component Analysis and Change Detection for Images. India: International Journal of Computer Trends and Technology.

7.       Mithe, R., Indalkar, S. and Divekar, N. (2013). Optical Character Recognition. International Journal of Recent Technology and Engineering.

8.       Neumann, L. and Matas, J. (2011). Text Localization in Real-world Images using Efficiently Pruned Exhaustive Search. Czech Republic: Czech Technical University.

9.       Saabni, R. andZwilling, M. (2012). Text Detection and Recognition in Real World Images. International Conference on Frontiers in Handwriting Recognition






Siti Norasmah Surip, Siti Ayuni Hamka

Paper Title:

Hybrid-Biodegradable Film Made From Polylactic Acid

Abstract:    In this experimental study, the biodegradability of PLA/EFB film with two different mixings; with and without lemongrass fibers (LG) were investigated by the landfill degradation. PLA/EFB film without the presence of lemongrass fibers showed the most significance of weight loss compared to the samples with the presence of lemongrass fibers. The highest weight loss percentage recorded in PLA:EFB:LG was in ratio 3 which is 8.42%. Meanwhile, in PLA:EFB, the highest weight loss percentage was recorded in ratio 3 (32.05%) and the lowest was in ratio 4 (19.22%). Ratio 1 acted as the comparison parameter in both composites mixing. Four different ratio of PLA/EFB showed significance improvement in Young’s modulus with ratio 4 had the highest reading (1492.2 MPa) and ratio 2 with the lowest reading (1021.1 MPa). In MOR, ratio 2 exhibited the highest reading (30.14 MPa) while ratio 4 with the lowest reading (9.49 MPa).

  Bio-composites, Lemon grass, Anti-microbial, Empty fruit bunches, Poly lactic acid.


1.       Guo W., Bao F., Wang Z. Biodegradability of Wood Fibers/poly(lactic acid) Composites. Journal of Composite Materials 2012; 47(28): 3573-3580.
2.       Kim H.S., Kim H.J., Lee J.W., et al. Biodegradability of Bio-flour Filled Biodegradable Poly(butylene succinate) Biocomposites in Natural and Compost Soil. Polymer Degradation and  Stability2006; 91: 1117-1127.

3.       Ochi S. Mechanical Properties of Kenaf Fibers and Kenaf/PLA Composites. Mechanics of Materials 2008; 40: 446-452.

4.       Oksman K., Skirfvars M., Selin J.F. Natural Fibers as Reinforcement in Polylactic Acid (PLA) Composites. Composites Science and Technology 2003; 63: 1317-1324.

5.       Tserki V., Matzinos P. and Parayiotou C. EWffect of Compatibilization on the Performance of Biodegradable Composites Using Cotton Fiber Waste As Filler. Journal of Applied Science 2003; 88: 1825-1835.

6.       Valdes A., Mellinas A. C., Ramos M, Garrigos M.C., Jimenez A. Natural Additives and Agricultural Wastes in Biopolymer Formulations for Food Packaging. Frontiers in Chemistry 2014; 2: 1-10.






A. Akilan, M. Boojith, R. G. Sree Krishna, V. Vijayanand

Paper Title:

Productivity Improvement by Lean Techniques in a Small Scale Industry

Abstract:    In our project, “Productivity Improvement by Lean Techniques,” undertaken in Unirols Airtex (P) Ltd, Coimbatore, the core objective is to improve the production capacity of the industry. In order to meet the demand one of the lean manufacturing tools 5S (Sort, Set in order, Shine, Standardize and Sustain) has been implemented successfully to ensure that the workspace is tidy, ergonomically efficient and capable of repeatable, quality output to achieve better efficiency. In addition to this technique, we also analyzed and optimized the layout of the industry using the software VIP-PLANOPT 2006 resulting in the improvement of overall productivity which helps the industry in meeting the demand.

 Lean tools, 5S, layout optimization, productivity.


1.       “An Application of Production Excellence through Value Flow” –vol.1 and issue 6 June 2014 by Ravindra Ojha, Sanjay Katyal , Sanjay Sethi published in Industrial Engineering Journal. ISSN: 0970-2555.
2.       “Design improvement in facility layout through Non-Traditional Algorithms” – vol,1 and issue number 8 August 2014 by Vadivel S.M and Amirthagadeswaran K.S published in Industrial Engineering Journal. ISSN: 0970-2555.

3.       “Efficiency Improvement of a Plant Layout” – Vol.3, issue 4, April 2014 by Vivekanand.S et al., published in International Journal of Innovative Research in Science,Engineering and Technology. ISSN: 2319-8753.

4.       “A Survey on Lean manufacturing implementation in Malaysian Automotive Industry” – Vol.1, No.4, October 2010. ISSN: 2010-0248.

5.       “Implementation of 5s Methodology in the Small Scale Industry: A Case Study” by R.S.Agrahari et al., published in International Journal of Science and Technology research volume 4 Issue 04,April 2015. ISSN: 2277-8616.

6.       “Investigation of Lean Tools to Enhance Productivity in Manufacturing Sector” – vol.3 (3), July, 2013 by Ritesh R. Bhat, Raviraj R. Shetty published in International Journal of Advances in Engineering Sciences.ISSN: 2231-2013.

7.       “Productivity Improvement through Lean Deployment & Work Study Methods” – vol.3 and issue 2 Feb-2014 by Prathamesh P. Kulkarni, Sagar S. Kshire, Kailas V. Chandratre published in International Journal of Research in Engineering and Technology. ISSN: 2321-7308.

8.       “Productivity Improvement of an Industry by Implementing Lean Manufacturing Principles” – vol.3, Special Issue 3, March 2014 2014 by S. Krishna Kumari, A.N.Balaji, R.Sundar published in International Conference on Innovations in Engineering and Technology. ISSN: 2347-6710.

9.       “5S for operators – 5 pillars of the visual workplace” by the Productivity Press Development Team, Productivity Press, New York (USA).






Juan Ochoa Aldeán, José Cuenca Granda, Byron Solórzano Castillo, Julio Romero Sigcho

Paper Title:

Implementation of A Long Distance Radio Link using Low-Costhardware

Abstract:     The long distance links with low-cost hardware have been used to interconnect rural populations in places where incumbents fail, and it is a global initiative for developing countries. This initiative has been promoted by various agenciesas: TIER, ICTP, ESLARED Foundation. This article describes the implementation of a radio link between the Villonaco Hill and the National University of Loja, using the experience gained by various agencies in the development of WiFi-based Long Distancetechniques. WiLD network with links as long as 50-100 km have the potencial to provide connectivity at substantially lower costs than traditional approaches. However, real-world deployments of such networks yield very poor end-to-end performance. First, the current 802.11 MAC protocol has fundamental shortcomings when used over long distances. Second, WiLD networks can exhibit high and variable loss characteristics, thereby severely limiting end-to-end throughput. In the implementation was used thewell-known Linksys WRT54G routers, where the factory firmware was replacedfor DD-WRT firmware. We also present the feasibility of the radio link through Radio Mobile Software, and the results using the PING command.

 WiLD, IEEE 802.11, DD-WRT, Radio Mobile.


1.        R. Patra, S. Nedevschi, S. Surana, A. Sheth, L. Subramnian, E. Brewer, WiLDNet: Design and Implementation of High Performance WiFi Based Long Distance
Networks, USENIX NSDI, April 2007.

2.        B. Sklar, Digital Communications Fundamentals and Aplication, 2nd ed., Prentice-Hall, Upper Saddle River, NJ, 2001.

3.        J. S. Seybold, Introduction to RF Propagation, Wiley, 2005.
4.        http://www.cplus.org/rmw/rme.html.

5.        http://www.dd-wrt.com

6.        https://es.wikipedia.org/wiki/WRT54G




Volume-5 Issue-2

 Download Abstract Book

S. No

Volume-5 Issue-2, May 2016, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Laxmi Shankar Awasthi

Paper Title:

Case Study: Business Analytical Problems

Abstract:  Now days with ever increasing size of the data and ever increasing method of the data collection, the amount of data is growing exponentially. With the downpour of such a huge amount of data from various sources, the use of automated systems and computer platforms is inevitable. The Humans are living in an information age, where the capabilities of the manual data manipulations have long been surpassed. Business Analytics aims to address such issues which are directly related to the interests of the Business. There are different types of problems, and for which there exist different solutions to tackle the specific problems.. This paper will help  to understand the existing problem by Case Study.

 Business Analytics, Machine Learning, Artificial Intelligence, Data Mining.


1.       Research In Organizational Behavior an annual series of analytical essays and critical reviews. Volume 26.
2.       Diversified business communications selects group 1 for enterprise data quality.

3.       Consumer Rights Electric, Natural Gas and Telephone(http://www.psc.state.ga.us/pscinfo/brochures/consumer_rights_brochure.pdf)






Swapnil J. Patil, V. R. Gambhire

Paper Title:

Design & Modeling of Infinite variable Transmission System Based on Constantaniesco Torque Convertor

Abstract: Infinitely variable transmission eliminates clutch and gear box for automobile and gives the required torque conversions automatically. In this paper infinitely variable transmission systems have designed and modelled based on Constantaniesco torque convertor for light to medium duty vehicles. IVT includes various parts as input and output shafts, yoke, connecting link and masses. It is necessary while designing IVT to calculate the governing parameters of the model. The study also includes the comparisons of theoretical parameters with experimental parameters as speed, torque, efficiency, power etc. on performance curves. So first of all theoretical design and calculations are carried out. Then after development of experimental set up readings are taken and calculations are carried out, from which performance parameters are plotted.

 Infinite variable transmission system, torque conversion, experimental set up, performance parameters.


1.    Timothy Cyders, Robert L. Williams II, “Analysis of a new form intrinsically automatic continuously variable transmission”, Proceedings of the ASME 2010 international design engineering technical conferences and computers and information in engineering conference IDTEC/CIE ,August 15-18,(2010).
2.    Ryan R.Daling “An investigation of positive engagement, continuously variable transmissions”, Thesis submitted to Brigham Young University, (2008).
3.    Ion ION, “George Constantinescu torque convertor analysis by simulink”, SIMON 2007 and homogial session of the commissions of acoustics, Bucharest, 29-31 may, (2007).
4.    G. Carbone, M. Napolitano, E. Sedoni, “Design optimization of input and output coupled power split infinitely variable transmissions”, ASME journal of mechanical
design, vol. 131,(2009) .

5.    A text book “Ian Constantinesco: Geroge Constantinesco his Torque Convertor and other Inventions” (chapter 5) (1925).

6.    William T. Beale: US Patent # 7,011,322 B2: “Automatic Transmission with Steeples, Continuously Variable Speed and Torque Ratio” (2006).

7.    John G. Bolger: US Patent # 4,907,474: “Mechanical Torque Convertor” (1990).

8.    George Constantinesco: US Patent # 1,613,344: “Power Transmission” (1927).






P. Paul Clee, S.V.L. Narasimham

Paper Title:

Analyzing the Power System in the Presence of FACTS Controllers: Effect of Control Parameters

Abstract:  Now a day technological development in power electronics based controllers formerly known as Flexible AC Transmission Controllers (FACTS), the power system can operate with high security. These controllers help to enhance the transmission line loadings in terms of its thermal ratings. The line loadings and bus voltage profiles can be controlled using these FACTS controllers. To analyze the effect of the FACTS devices, these controllers should be incorporated in a given system and the load flow analysis is performed using Newton Raphson (NR) method. In this paper, very popularly used FACTS controllers known for Static VAr Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) are considered. The effect of these devices on system bus voltages, line power flows and system power losses is analyzed on standard test system such as HALE network and IEE-30 bus test systems are considered.

 Power flow analysis, SVC, TCSC, NR-load flow, Optimal location.

1.       S. N. Singh and A. K. David, “Optimal location of FACTS devices for congestion management,” Elect. Power Syst. Res., vol. 58, no. 2, pp.71–79, 2001.
2.       Y. Lu and A. Abur, “Static security enhancement via optimal utilizationof thyristor-controlled series capacitor,” IEEE Trans. Power Syst., vol.17, no. 2, pp. 324–329, May 2002.

3.       J. G. Singh, S. N. Singh, and S. C. Srivastava, “An approach for optimal placement of static VAr compensators based on reactive power spotprice,” IEEE Trans.
Power Syst., vol. 22, no. 4, pp. 2021–2029, Nov.2007.

4.       N. Acharya and N. Mithulananthan, “Locating series FACTS devices for congestion management in deregulated electricity markets,” Elect.Power Syst. Res., vol. 77, no. 3-4, pp. 352–360, 2007.

5.       M. Gitizadeh and M. Kalantar, “A novel approach for optimum allo-cation of FACTS devices using multi-objective function,” Energy Con-vers. Manage vol. 50, no. 3, pp. 682–690, 2009.

6.       R. Benabid, M. Boudour, and M. A. Abido, “Optimal location and setting of SVC and TCSC devices using non-dominated sorting par-ticle swarm optimization,” Elect. Power Syst. Res., vol. 79, no. 12, pp.1668–1677, 2009.
7.       N. Yorino, E. E. El-Araby, H. Sasaki, and S. Harada, “A new formu-lation for FACTS allocation for security enhancement against voltagecollapse,” IEEE Trans. Power Syst., vol. 18, no. 1, pp. 3–10, Feb. 2003.
8.       R. Minguez, F. Milano, R. Zarate-Minano, and A. J. Conejo, “Optimalnetwork placement of SVC devices,” IEEE Trans. Power Syst., vol. 22,no. 4, pp. 1851–1860, Nov. 2007.

9.       M. Eghbal, N. Yorino, E. E. El-Araby, and Y. Zoka, “Multi load levelreactive power planning considering slow and fast VAR devices bymeans of particle swarm optimization,” IET Trans. Gen., Transm., Dis-trib., vol. 2, no. 5, pp. 743–751, 2008.

10.    R. Zárate-Miñano, A. J. Conejo, and F. Milano, “OPF-Based securityredispatching including FACTS devices,” IET Trans. Gen., Transm.,Distrib., vol. 2, no. 6, pp. 821–833, 2008.

11.    A.E.  Guile and W.D.  Paterson, „Electrical power systems, Vol.  2‟,

12.    (Pergamon Press, 2nd edition, 1977).

13.    W.D.  Stevenson Jr., „Elements of power system analysis‟, (McGraw-Hill, 4thedition, 1982).

14.    W.  F.  Tinney, C.  E.  Hart,  “Power  Flow  Solution  by  Newton’s  Method,  “IEEE  Transactions  on  Power  Apparatus  and  systems  ,  Vol.  PAS-86, pp. 1449-1460, November 1967.

15.    W.  F.  Tinney, C.  E.  Hart, “Power Flow Solution by Newton’s Method, “IEEE TRANS.  POWER APPARATUS AND SYSTEMS, Vol.  PAS-86, pp. 1449-1460, November 1967.

16.    Carpentier “Optimal Power Flows”, Electrical Power and Energy Systems, Vol.1, April 1979, pp 959-972.

17.    D.I.Sun, B.Ashley, B.Brewer, A.Hughes and W.F.Tinney, “Optimal Power  Flow by Newton Approach”,  IEEE Transactions on Power Apparatus and systems, vol.103, No.10, 1984, pp2864-2880.

18.    W. R. Klingman and D. M. Himmelblau, “Nonlinear programming with the aid of a multiple-gradient summation technique,” J. ACM, vol. 11, pp. 400-415, October 1964

19.    H.  Dommel, “Digital methods for power system analysis” (in German), Arch.  Elektrotech., vol.  48, pp.  41-68, February 1963 and pp.  118-132, April 1963.

20.    D.  Das, H.S.Nagi and D.P.  Kothari  ,  “Novel  Method  for  solving  radial distribution networks,”  Proceedings IEE Part C (GTD), vol.141, no. 4, pp.291 – 298, 1991

21.    T.K.A.  Rahman  and  G.B. Jasmon,  “A  new  technique  for  voltage  stability analysis  in  a  power  system  and  improved  load flow  algorithm  for distribution
network,”  Energy  Management  and  Power  Delivery Proceedings of EMPD ’95; vol.2, pp.714 – 719, 1995.






Sabri M. Ben Mansour, Jawhar Ghommam, Saber M. Naceur

Paper Title:

Design and Visio Control for Navigation and Obstacles Detection Based on Color and Texture Attributes of Two-Wheeled Mobile Robot

Abstract: This paper addresses Visio and path following control problem of a nonholonomic Two-Wheeled Inverted Pendulum Mobile Robot. We propose control architecture based on two control layers. A speed inner loop control scheme is first designed based on state feedback technique to ensure stability of the inverted structure of the robot. A second outer loop control scheme is proposed to help the robot navigate along a desired path formed by a set of way points. It is designed inspiring the model predictive control technique. The elements of the predictive control, which are the cost function, controls and constraints, must be defined and specified: the use of different trajectories group in the control can adapt the behavior of the robot to different displacement phases. The obstacle detection architecture based on the attributes of color and texture has been developed to be implemented on an Raspberry PI and is designed as a generic high-speed image processing device. The optimization criteria are based on a maximization of performance in terms of image processing per second and a minimization of consumed resources. Our obstacles detection algorithm consists of three main steps: the color transformation, the calculation of the color and texture attributes and their classification.

 Mobile robot, navigation, stability, Predictive control, Obstacles detections, Image processing


1.        Grasser F, D’arrigo A, Colombi S and Rufer A. Joe: A  Mobile Inverted Pendulum:IEEE Transaction on Industrial Electronics;2002.
2.        Ooi R C. Balancing a Two-Wheeled Autonomous Robot: Final Year Thesis: The University of Western Australia School of Mechanical Engineering, Faculty of Engineering and Mathematical Sciences University of Western Australia, Australia;2003.

3.        Ho K C R. Balancing Wheeled Robot: Research Project, University of Southern Queensland, Australia; 2005.

4.        Grepl R. Balancing Wheeled Robot: Effective Modelling, Sensory Processing And Simplified Control: Engineering Mechanics, 16 (2), pp.141–154;2009.

5.        Takita Y, Date H and Shimazu H. Competition of Two-wheel Inverted Pendulum Type Robot Vehicle on MCR Course: The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems,5578-5584; 2009.

6.        Chee Y O and Abidin M S Z. Design and Development of Two Wheeled Autonomous Balancing Robot; Student Conference on Research and Development; 2006.

7.        Nawawi S W, Ahmad M and Osman J H S. Real-Time Control of a Two-Wheeled Inverted Pendulum Mobile Robot: World Academy of Science, Engineering and Technology,214-220; 2008.

8.        Tsai C, Chan C and Fan Y H. Planned Navigation of a Self-balancing Autonomous Service Robot: IEEE International Conference on Advanced Robotics and Its Social Impacts, vol 6764; 2008.

9.        Latombe J.C Kluwer,Robot Motion Planning: Academic Publishers, Boston;1991.

10.     Choset. Sensor Based Motion Planning the Hierarchical Generalized Voronoi Graph” Phd thesis,  California Institure of Technology;1996.

11.     Chazzzelle and Guibas.Visibiliy and ontersection problems in plane geometry” , Discrete and  Computational Geometry;2000

12.     Shin and McKay. A dynamic programming approach to trajectory planning of the robotic manipulators”, IEEE Transactions on Automatic Control;1996.

13.     Hart, A Formal Basis for the Heuristic Determination of Minimum Cost Paths” , IEEE Transactions on Systems Science and Cybernetics;1986.

14.     Stentz and Anthony, Optimal and Efficient Path Planning for Partially-Known Environments, Proceedings of the International Conference on Robotics and Automation;1994.

15.     Defoort, Motion planning for cooperative unicycle-type mobile robots with limited sensing ranges, A distributed receding horizon approach , Robotics and Autonomous Systems;2009.

16.     ŠKRJANC, Igor, BLAŽIČ, Sašo, Predictive functional control based on fuzzy model : design and  stability study”, Journal of intelligent & robotic systems, ISSN 0921-0296, 2005, vol. 43, pp. 283-299 ;2005.

17.     KLANČAR, Gregor, ŠKRJANC, Igor, A case study of the collision-avoidance problem based on Bernstein-Bézier path tracking for multiple robots with known constraints”. Journal of intelligent &  robotic systems, ISSN 0921-0296, Nov. 2010, vol. 60, no. 2, pp. 317-337, ilustr., doi: 10.1007/s10846-010-9417-8;2010.

18.     Micaelli A. Trajectory tracking for unicycle-type and two-steering-wheels mobile robots: Sophia-Anitpolis, France: Institut National de Recherche en Automatique er en Automatique; 1993.

19.     Hu J S, Tsai M C, Hu F R and Hori Y. Robust Control For Coaxıal Two-Wheeled Electrıc Vehıcle: Journal of Marine Science and Technology, pp 172-180;2010.

20.     Chi G, Hausbach J and Hunter B. Segbot: Senior Design Project, University of Illinois at Urbana-Champaign, USA ; 2005.

21.     Bock H.G and Plitt K. A multiple shooting algorithm for direct solution of optimal control problems. 9th IFAC world congress Budapest. Pergamon Press; 1984.
22.     Klancar G, Skrjanc I. Tracking-error model-based predictive control for mobile robots in real time: Robotics and Autonomous Systems; 2007.
23.     Courtial E. Commande predictive et estimation d’état de systèmes non linéaires : Rapport de thèse université Claude Bernard – Lyon ;1996.

24.     Vallius T and Röning J. Embedded Object Concept: Case Balancing Two-Wheeled Robot: Proceedings of the SPIE, Vol. 6764; 2007.

25.     Bak M. Poulsen K, Ravn O. Path Following Mobile Robot in the Presence of Velocity Constraints: Kongens Lyngby, Denmark : Technical University of Denmark; 2000






Khan Zubair Zahoor, Shaikh Mohamedali A.R., Shaikh Arman Naseem, Shaikh Fuzelahmed  Mahabubali, Shaikh Shahrukh Shahid

Paper Title:

Design and Fabrication of Thal Pump

Abstract:  Thal-pump is a type of   infusion pump that is used for injecting iron chelating agent into the body of a patient suffering from Thalassemia disease. Currently the device used for treatment of Thalassemia patients in India is imported from European countries like Denmark and because of the import duty the cost of this equipment is considerably high(approx 50,000 INR) which makes it unaffordable to many hospitals in India. Similar desired output of Thal-pump has been developed by us with a total cost of 6,000 INR. The main objective of the Thal-pump is to inject the iron chelating agent at  a desired rate (ranges from 0.5ml/hr to 10ml/hr) with high precision. This paper explains the working of the Thal-pump based on the application of Mechatronics wherein the injecting rate of the chelating agent depends on the stepper motor speed used. The speed of this stepper motor is controlled through circuits governed by an arduino sketch. The discharge rate of Thal-pump can be varied and because of this it has different medical applications.

 (ranges from 0.5ml/hr to 10ml/hr), (approx 50,000 INR), 6,000 INR.

1.    Machine design by V. B. Bhandari


2.    http://micrelmed.com/

3.    www.wikipedia.com

4.    www.nhlbi.nih.gov





Santosh S.K, Shivashankar S.B, Noushad K.R, Kishan N.K, S.G. Goudar, Prabhu, K.

Paper Title:

An Experimental Study on Laterally Loaded Piles in Sand

Abstract:   The behaviour of pile under lateral load is studied through laboratory experiments on model cemented group of piles driven into testing tank containing dry river sand. The load-displacement diagrams were drawn to study the effect of strength comparison between the group of cemented piles and different densities of sand on the lateral load capacity of pile. It was found that the lateral load capacity of piles increases with increase in number of piles and increase in sand density. It is also found that lateral load capacity is more in high density sand as compared to that of low density sand.

  ultimate lateral load capacity, cemented pile, sand.


1.    Boominathan, A., and Ayothiraman R. (2007) “An experimental study on static and dynamic bending behaviour of piles in soft clay”, Journal of Geotechnical and Geoenvironmental Engineering, Vol. 25,No. 2, pp. 177 – 189.
2.    Gandhi, S. R., and Selvan, S. (1997) ‘‘Group Effect on Driven Piles Under Lateral Load’’ Journal of Geotechnical and Geoenvironmental Engineering, Vol. 123, No. 8, pp. 702 – 709.

3.    Fan, C. C., and Long, J. H. (2005) ‘‘Assessment of Existing Methods for Predicting Soil Response of Laterally Loaded Piles in Sand’’ Computers and Geotechnics, Vol. 32, pp. 274-289.

4.    IS: 2720 (Part 4) – 1985, Methods of Test for Soils: Grain Size Analysis, Bureau of Standards, New Delhi, India.
5.    IS 2720 (Part 13) – 1972, Method of Test for soils: Direct Shear Test (Second Revision), Bureau of Standards, New Delhi, India.
6.    IS: 2911-IV (1985), “Indian Standard code of practice for design and construction of pile foundations”, Part 4, Load test on piles, Bureau of Standards, New Delhi, India.

7.    Kim, B. T., Kim, N. K., Lee, W. J., and Kim, Y. S. (2004) “Experimental Load–Transfer Curves of Laterally Loaded Piles in Nak-Dong River Sand”, Journal of Geotechnical and Geoenvironmental Engineering, Vol. 130, No. 4, pp 416 – 425.

8.    Ranjan, N. P., and Jagannath, P. P. (2001) “Ultimate Lateral Resistance of Pile Groups in Sand”, Journal of Geotechnical and Geoenvironmental Engineering, Vol.127,
No.6, pp.481 – 486.

9.    Som, N. N. and Das, S. C. (2003) “Theory and Practice of Foundation Design”, Prentice Hall of India Private Limited, New Delhi, pp 232-250.






Chetan.B.P, Irana.K, Raghavendra.K.S, Shivabasava.M.P, S.G.Goudar, Prabhu, K

Paper Title:

Behaviour of Uplift Capacity of Piles in Sand

Abstract: Understanding the pile behavior and predicting the capacity of piles under uplift loading are important topics in foundation design. Experimental model tests have been conducted on single piles and pile groups embedded in cohesion less soil and subjected to pure uplift loading. The piles are made up of cement.  The influences of pile embedment depth, relative density of soil, and arrangement of piles in a group on the uplift capacity of piles are investigated. The study revealed that the behavior of single piles under uplift loading depends mainly on both the pile embedment depth-to-diameter ratio and the soil property . When the net uplift load per pile in a group is equal to a single pile load, the upward displacement increased in the pile group due to interaction effects between piles. The obtained group efficiency under uplift loading is illustrated and found to be in a good agreement with previous studies.

 cemented pile, sand. Testing tank


1.       Birger Schinidt (1987). Pull Out Capacity of Single Batter Pile in Sand. Canadian Geotechnical Journal. 24. pp. 467-468.
2.       Chattopadhyay and Pise, P.J. (1986a). Uplift Capacity of Pile in Sand. Journal of the Geotechnical Engineering Division ASCE. 112. No. 9 paper No. 20919.

3.       Clemence, C.P. and Brumund, W.F. (1975). Large Scale Model Test of Drilled Piers in Sand. Journal of the Geotechnical Engineering Division ASCE. 101. GT.6.paper No. 11369.

4.       Das, B. M. (1983). A Procedure for Estimation of Uplift Capacity of Rough Piles. Journal of Soil and Foundation Division ASCE. 109. No.3. pp. 122-126.

5.       Das, B. M. and Seeley, G. R. (1975b). Uplift capacity of buried model pile in Sand.

6.       Journal of the Geotechnical Engineering Division ASCE. 101. No. 20. pp. 1091-1094.

7.       Dickin, E.A. and Leung, C.F. (1990). Performance of Pile With Enlarge Base Subject to Uplift Force. Canadian Geotechnical Journal. 27. pp. 546-556.

8.       Meyerhof, G. G. and Adams (1968). The Ultimate Uplift Capacity of Foundations.

9.       Canadian Geotechnical Journal. 5. No. 4. Nov. pp. 225-244.

10.    Dickin, E.A. and Leung, C.F. (1992). The Influence of Foundation Geometry on the Uplift Behavior of Pile With Enlarge Bases. Canadian Geotechnical Journal. 29. pp. 498-505.

11.    Zheng zhang (2009), “Simplified nonlinear analysis methods for vertically loaded piles and piled raft in layered soil” Brdge science research institute, civil eng. Dalian university of technology, Dalian, Vol.14.

12.    Basu .D, Salgado .R, Prezzi.M, Lee.J and Paik.K “Recent advances in the design of axially loaded piles in sandy soils” GSP 132 Advances in deep foundation, ASCE, 2012.

13.    Poulos.G.H (1989), “Cyclic axial loading analysis of piles in sand” Journal of geotechnical and geo environmental engineering, ASCE, Vol.115. No.6, 1989.

14.    Indian Standard-IS: 2720 (Part 3)1980 “Methods of test for soils, determination of specific gravity, fine, medium and coarse grained soils”, New Delhi.

15.    Indian Standard-IS: 2720 (Part 4)-1985 “Methods of test for soils, grain size analysis-mechanical method”, New Delhi

16.    IS: 2386 (Part III) – 1963 “Part III Specific Gravity, Density, Voids, Absorption and Bulking” Indian standard methods of test for aggregates for concrete.

17.    2911 (Part4)-1985 “Part 4 Load Test on Piles” Indian Standard Code of Practice for Design and Construction of Pile Foundations.






Prashant A.Bhalge, Salim.Y.Amdani

Paper Title:

Categories for Fast Block Matching Algorithm

Abstract:  Motion  Estimation  plays  a  vital role  in  a  motion compensated  hybrid  DCT  video  compression  scheme.  To reduce the computational complexity in finding the near to exact match of the block, many fast search algorithms have been proposed. This paper is survey paper in  which fast block matching algorithm are categorized. Unsymmetrical multi hexagon search, Adaptive rood pattern search, Fast full search are described.

  Block matching, Hexagonal search, Adaptive rood pattern, Validity Metrics


1.       Yue Chen, Yu Wang, Ying Lu, “ A New Fast Motion Estimation Algorithm” ,  Literature     Survey        October (1998).
2.       Fulvio Moschetti, “A Statistical  Approach to Motion Estimation”,  École    Polytechnique Fédérale  De Lausanne, a  Thesis  report, Lausanne,   EPFL      (2001).

3.       Zaynab Ahmed , Abir Jaafar Hussain and Dhiya Al-Jumeily, “ Fast Computations        Of   Full Search Block Matching Motion Estimation  (FCFS)”, 2011.

4.       Aroh Barjatya ,“ Block Matching  Algorithms For Motion Estimation  ”,DIP 6620   Final Project Paper ,  2004 .

5.       Yih-Chuan Lin and Shen-Chuan      Tai, “Fast Full-Search Block- Matching Algorithm for Motion- Compensated Video Compression”, IEEE Transactions On      Communications, Vol. 45, No. 5,      May 1997.

6.       Michael Santoro, “Valid Motion   Estimation For Super-Resolution Image Reconstruction”, A Dissertation, School of Electrical and Computer Engineering  Georgia Institute of Technology ,August 2012.

7.       Yuan Gao, Peng-yu Liu and Ke-bin Jia, “ A Fast Motion Estimation Algorithm Based on Motion Vector Distribution Prediction”, Journal of Software, Vol. 8, No. 11, November  2013.

8.       V.K.Ananthashayanal,Pushpa.M.K,“ Joint Adaptive Block Matching Search(JABMS) Algorithm for Motion Estimation”,  International Journal of Recent Trends   in Engineering, Vol 2, No. , November 2009.

9.       S. Sowmyayani, P. Arockia Jansi  Rani, “Block based Motion Estimation using    Octagon and

10.    Square Pattern”, International Journal  of Signal Processing, Image   Processing and Pattern Recognition   Vol.7, No.4 , pp.317-324,2014.

11.    Ou Yu,“Research and optimization  of  a H.264AVC motion estimation algorithm based on a 3G network”  ,report Uppsala university,2013.

12.    Ismael Daribo, Dinei  Florencio,Gene Cheung” Arbitrarily Shaped Motion  Prediction for Depth Video   Compression Using Arithmetic Edge Coding”, IEEE Transactions On   Image Processing, Vol. 23, No. 11,   November 2014.






Dhanraj Suman, Rajesh Bhatt

Paper Title:

Comparative Analysis of PID and Fuzzy Controller for Control of Magnetic Levitation System

Abstract:   This paper provides a comparative analysis of performance of different controllers for magnetic levitation system. Magnetic levitation system is a highly nonlinear and unstable system and it is very challenging to develop accurate controller for the same. This paper provides mathematical model of magnetic levitation system and develops controller for the same. Two different controllers such as PID controller and fuzzy controller have been designed and simulation results have been provided.

   Magnetic levitation system; PID controller; Fuzzy controller


1.       Rafael Morales, Vicente Feliu, and Hebertt Sira-Ramírez, “Nonlinear control for magnetic levitation system based on fast online algebric identification of the input gain,” IEEE Transactions on Control System Technology, vol. 19. No. 4, Jul 2011, pp. 757-771.
2.       Panayiotis S. Shiakolas, Stephen R. Van Schenck, Damrongrit Piyabongkarn, and Ioannis Frangeskou, “Magnetic Levitation Hardware-in-the-Loop and MATLAB-Based Experiments for Reinforcement of Neural Network Control Concepts,” IEEE Transactions on Education, vol. 47, no. 1, Feb 2004, pp. 33-1

3.       F. Beltran-Carbajal, A. Valderrabano-Gonzalez, J.C. Rosas-Caro, A. Favela-Contreras, “Output feedback control of a mechanical system using magnetic levitation,” ISA Transactions, 57, 2015, pp. 352-359

4.       Jinquan Xu, He-Hwa Chen, Hong Guo, “Robust levitation control for maglev systems with guranteed bounded airgap,” ISA Transactions, 59, 2015, pp. 205-214.

5.       Yemei Qin, Hui Peng, Wenjie Ruan, Jun Wu, Jiacheng Gao, “A modeling and control approach to magnetic levitation system based on state-dependent ARX model,” Journal of Process Control, 24, 2014, pp. 93-112.

6.       Thomas Bachle, Sebastian Hentzelt, Knut Graichen, “Nonlinear model predictive control of a magnetic levitation system,” Control Engineering Practice, 21, 2013, pp. 1250-1258.

7.       Wen Yu, Xiaoou Li, “A magnetic levitation system for advanced control education,” in Proc. International Federation of Automatic Control, 2014, pp. 9032-9037.

8.       Vinodh Kumar E, Jovitha Jerome, “LQR based optimal tuning of PID for trajectory tracking of magnetic levitation system,” Procedia Engineering, 64, 2013, pp. 254-264.

9.       Santanu Kumar Pradhan, Bidyadhar Subudhi, “Nonlinear control of a magnetic levitation system using a new input-output feedback linearization,” in Proc. International Federation of Automatic Control, 49-1, 2016, pp. 332-336

10.    Shekhar Yadav, S K Verma, S K Nagar, “Optimized PID controller for magnetic levitation system,” in Proc. International Federation of Automatic Control, 49-1,
2016, pp. 778-782

11.    Jing-Chung Shen, “H-∞ control and sliding mode control of magnetic levitation system,” Asian Journal of Control, vol. 4, no. 3, 2002, pp. 333-340

12.    Hatem Elaydi and Mohammed Elamassie, “Multi-rate ripple free dead beat control for nonlinear system using diophantine equations,” IACSIT International Journal of Engineering and Technology, vol. , no. 4, 2012, pp. 489-494

13.    Zi-Jiang Yang, Michitaka Tateishi, “Adaptive robust nonlinear control of a magnetic levitation system,” Automatica, 37, 2001, pp. 1125-1131
14.    Walter Barie, John Chiasson, “Linear and nonlinear state space controllers for magnetic levitation,” International Journal of Systems Science, vol. 27, no. 11, 1996, pp. 1153-1163
15.    Zi-Jiang Yang, Kazuhiro Kunitoshi, Shunshoku Kanae and Kiyoshi Wada, “Adaptive robust output-feedback control of magnetic levitation system by K-filter approach,” IEEE Transactions on Industrial Electronics, vol. 55, no. 1, Jan 2008, pp. 390-399

16.    Rong-Jong Wai, Kun-Lun Chuang, and Jeng-Dao Lee, “On-line supervisory control design for Maglev transportation system via total sliding mode approach and particle swarm optimization, IEEE Transactions on Automatic Control, vol. 55, no. 7, July 2010, pp. 1544-1559

17.    CHAO-LIN KUO, TZUU-HSENG S. LI and NAI REN GUO, “Design of a novel fuzzy sliding mode control for magnetic ball levitation system,” Journal of Intelligent and Robotic Systems, 42, 2005, pp. 295-316

18.    Zi-Jiang Yang, Kouichi Miyazaki, Shunshoku Kanae, and Kiyoshi Wada, “Robust position control of a magnetic levitation system via dynamic surface control technique,” IEEE Transactions on Industrial Electronics, vol. 51, no. 1, Feb 2004, pp. 26-34
19.    Faa-Jeng Lin, Li-Tao Teng, and Po-Huang Shieh, “Intelligent adaptive backstepping control system for magnetic levitation apparatus,” IEEE Transactions on Magnetics, vol. 43, no. 5, May 2007, pp. 2009-2018
20.    Kent H. Lundberg, Katie A. Lilienkamp, and Guy Marsden, “Low-cost magnetic levitation project kits,” IEEE Control System Magazine, 2004, pp. 65-69

21.    Rong-Jong Wai, Jeng-Dao Lee, and Kun-Lun Chuang, “Real-time PID control strategy for Maglev transportation system via particle swarm optimization,” IEEE Transactions on Industrial Electronics, vol. 58, no. 2, Feb 2011, pp. 629-646





Legeto Cosmas Kirui, Kivaa Titus Mbiti, Ahmed Alkizim

Paper Title:

Investigating the Effect of Chemical Admixtures on the Quality of Concrete in the Construction Industry in Kenya

Abstract: Quality of concrete has been the focus of key stakeholders of the construction industry in Kenya for sometimes now after several storey buildings have collapsed. The question has been what really leads to concrete failure; quality of material used; design mix adopted; method of batching concrete; method of handling and placing. This study has set out to find whether chemical admixtures are being used in the construction industry in Kenya and their influence on quality of concrete in a bid to solve the problem. The study adopted a mixed design approach which incorporates both qualitative and quantitative elements of research.  The study came to several conclusions key among them; that chemical admixture are used in the construction sector with good effect on the quality of concrete; chemical admixtures enable projects to be managed easily. The study recommended formulation of legislation to guide the use of admixtures which will lead to solving of the current challenges of counterfeit chemical admixtures, lack of proper training by contractors and lack of interest from building statutory bodies on its use.

 Quality of Concrete, Construction Chemicals, Construction Industry.


1.       Abidollah, J. & Hojjati, A. (2013). Evaluation of Admixtures and Their Effect on Concrete Properties and Mechanism of Additives. Switzerland Research ark Journal, Vol 102, No. 11
2.       American Concrete Institute, (1999). Hot Weather Concreting. Report of ACI Committe, 305

3.       Alsadey, S. (2015). Effect if Superplasticizer on Fresh and Hardened Properties of     Concrete. Journal of Agricultural Science and Engineering Vol. 1.  No. 2, pp 70-74.

4.       Arditi, D., & Gunaydin, H. M. (1997). Total quality management in the construction process. International Journal of Project Management, 15(4), 235–243. doi:10.1016/S0263 7863(96)00076-2
5.       Cement Admixtures Association (2006), “Admixture Sheet”, ATS5 Concrete Air-entraining admixtures.
6.       Collepardi, M. (2005, July). Admixture-enhancing concrete performance. Ultimate Concrete Opportunities. Proceeding of the 6th International Congress, Global
Construction, Dundee, U.K.

7.       Juran, J.M. & Blaton A.G. (1988). Juran’s Quality Handbook (5th ed.). New York: McGraw-Hill.

8.       Kuta. J, & Nyaanga D. M. (2014). Effect of Quality of engineering materials on construction: a quality of buildings. A case study of Nairobi, Kenya.

9.       Mugenda, O.M, & Mugenda, A.G. (2003). Business Research Methods : Quantitative and Qualitative Approaches. Nairobi: Acts Press.

10.    Neville A.M., & Brooks J.J. (2010). Concrete Technology (2nd ed.). UK: Longman Group Ltd.

11.    Nyambura H.N, Mutuku R.N & Abiero Z.G. (2014). Effects of Sand Quality on Compressive strength of concrete; A case study of Nairobi County and its Environs, Kenya. Open Journal of Civil Engineering. Vol. 4, pp 255-273.

12.    Zhang S. Q., Chen H.F., Zhong H., Leung F.M, & Nick P. (2008, August). Use of Concrete Admixture to produce ‘Waterproof’ Concrete-Asia Results. 33rd Conference on Our World in Concrete & Structures.




Volume-5 Issue-3

 Download Abstract Book

S. No

Volume-5 Issue-3, July 2016, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



S. Hitesh Kumar, R. Kavya Reddy, Preetha K.S

Paper Title:

Fall Detection System for Monitoring Elderly People

Abstract: Different fall-recognition arrangements have been already proposed to make a dependable observation framework for elderly individuals with high necessities on exactness, affectability and specificity. In this paper, an improved fall recognition framework is proposed for elderly individual observing that depends on keen sensors worn on the body and working through purchaser home systems. With treble limits, inadvertent falls can be distinguished in the home social insurance environment. By using data assembled from an accelerometer, cardio tachometer and shrewd sensors, the effects of falls can be logged and recognized from ordinary every day exercises. The proposed framework has been conveyed in a model framework as itemized in this paper.

ARM, pulse sensor, GSM, GPS, MMA7660FC MEMS accelerometer, LPC2148 microcontroller


1.       Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey,” Journal of Computer Networks, vol. 38, no. 4, pp. 393-422, March 2002.
2.       J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Journal of Computer Networks, vol. 52, no. 12, pp. 2292-2330, Aug. 2008.
3.       K. Kinsella and D. R. Phillips, “Global aging: the challenge of success,” Population Bulletin, vol. 60, 2005..
4.       Q. Zhang, L. Ren, and W. Shi, “HONEY a multimodality fall detection and telecare system,” Telemedicine and e-Health, vol. 19, no. 5, pp. 415-429, Apr. 2013.
5.       F. Bagalà, C. Becker, A. Cappello, L. Chiari, and K. Aminian, “Evaluation of accelerometer-based fall detection algorithm in realworld falls,” PLoS ONE, vol. 7, no. 5, pp. 1-8, May 2012.
6.       S. Abbate, M. Avvenuti, F. Bonatesta, G. Cola, P. Corsini, and A.Vecchio, “A smartphone-based fall detection system,” Pervasive and Mobile Computing, vol. 8, no. 6, pp. 883-899, Dec. 2012.
7.       S. Abbate, M. Avvenuti, G. Cola, P. Corsini, J.V. Light, and A.Vecchio, “Recognition of false alarms in fall detection systems,” in Proc. 2011 IEEE Consumer Communications and Networking Conference, Las Vegas, USA, pp. 23-28, Jan. 2011.
8.       Y.W Bai, S.C. Wu, and C.L. Tsai, “Design and implementation of a fall monitor system by using a 3-axis accelerometer in a smart phone,” IEEE Trans. Consumer Electron., vol. 58, no. 4, pp. 1269-1275, Nov.






Fatah Bouteldjaoui, Ahmed Kettab, Mohamed Bessenasse

Paper Title:

Evaluation of Spatiotemporal Variability of Groundwater Level Fluctuations in Zahrez basin, Algeria: Geostatistical Approach

Abstract: Groundwater level fluctuation in aquifer system plays the main role in quantitative water management especially in semi arid and arid areas. In practice, due to aspects of time and cost, data monitoring of water levels is conducted at a limited number of sites, and interpolation technique such as kriging is widely used for estimation of this variable in unsampled sites. The main objective of this study is to get a better understanding of the temporal and spatial variability of the groundwater level fluctuation in regular monitoring wells constructed by the ministry of water resources in zahrez basin, Algeria. In this study, seasonal groundwater level data for 57 wells were collected from 1994 to 2011 and analyzed using the geostatistical approach. The Kolomogorov–Semirnov test revealed that all data followed normal or log-normal distribution. Experimental variograms are fitted by variogram models and computed to be used in the kriging estimations. The results of variographic analysis indicate that experimental variograms are best fitted by the gaussian model and the exponential model. Nugget-sill ratio (<25%) revealed that the groundwater levels have strong spatial dependence in the area. Kriging interpolation techniques have indicated the groundwater flow directions remained almost constant over the years

  Geostatistics, Groundwater levels, Semivariogram, Universal kriging, Zahrez basin


1.     Kettab, “Water resources in Algeria : strategies, investments, and vision”, Desalination, vol.136, no.1-3, pp.25-33, 2001. 
2.     Kettab, R. Mitiche, N. Bennaçar, “Water for a sustainable development: challenges and strategies”, Revue des Sciences de l’Eau 21 (2): 247-256, 2008.

3.     M. Aflatooni, M. Mardaneh, “Time series analysis of groundwater table fluctuations due to temperature and rainfall change in Shiraz plain”, International Journal of Water Resources and Environmental Engineering 3 (9): 176– 188, 2011.

4.     RW. Healy, PG. Cook, “Using groundwater levels to estimate recharge”,  Hydrogeology Journal 10: 91–109, 2002.

5.     S. Ahmadi, A. Sedghamiz, “Geostatistical analysis of spatial and temporal variations of groundwater level”, Environmental Monitoring Assessement 129(1–3):277–294, 2007.

6.     D. Kumar, Sh. Ahmed, “Seasonal behaviour of spatial variability of groundwater level in a granitic aquifer in monsoon climate”, Current Science 84: 188–196, 2003.

7.     N.Theodossiou, P. Latinopoulos, “Evaluation and optimization of groundwater observation networks using the kriging methodology.” Environmental Modelling and Software: 21: 991– 1000, 2006.

8.     V. Kumar, Remadevi, “Kriging of groundwater levels—a case study.” Journal of Spatial Hydrology 6 (1): 8 1–92, 2006.

9.    ANRH, “Synthèse hydrogéologique du synclinal de Djelfa.” Agency for Water Ressources, 1997, unpublished.

10.  M. F. Sidi Moussa,  “ Ressources Hydrauliques de la zone du projet GTZ-HCDS.” Coopération Algero-Allmande, 176 P, 2000,  unpublished.

11.  M. F. Sidi Moussa , M.Deramchi, “Synthèse des études et exploitation des données existantes sur le Synclinal de Djelfa”, Agence Nationale des Ressources Hydrauliques (ANRH), Rapport Technique, 40P, 1993, unpublished.

12.  B.Chibane, A. Boutaleb, “Geochemistry study and Isotopic Approach in Semi-Arid Region: Case of the Djelfa Syncline (Algeria).” European Journal of Scientific Research 45(2):270-290, 2010.

13.  Y. Pannatier, “Variowin Software for Spatial Data Analysis in 2D”, edited by Springer, New York,1996.

14.  D.G. Krige, “A statistical approach to some basic mine valuation problems on the Witwatersrand”, Journal of the Chemical, Metallurgy and Mining. Society. Southern. Africa 52 (6): 119–139, 1951.

15.  G. Matheron, “Principles of geostatistics.” Economic. Geology 58: 1246–1266, 1963.

16.  A.G. Journel,  C.J. Huijbregts, “Mining Geostatistics”, edited by Academic Press Inc, London, UK, 1978,  600pp.

17.  EH. Isaaks, RM. Srivastava, “An Introduction to Applied Geostatistics”, edited by Oxford University Press: New York,1989, 322 pp.

18.  M. David, “Geostatistical ore reserve estimation.”, edited by Elsevier, Amsterdam, 1977.

19.  P. Goovaerts, “Geostatistics for natural resources evaluation”, edited by Oxford University Press, New York,1997.






Suresha Gowda M. V., Ranganatha S., Vidyasagar H. N.

Paper Title:

Role of Ball and Coating Materials under Un-lubricated Condition

Abstract:  The performance, reliability and load transferring capabilities of bearing elements are very important in industrial applications. The newer design of high speed machines demands better bearing system. The reliability is of primary importance in case of bearing elements used in aerospace industries. Exhaustive studies have been carried out by different researchers under two extreme conditions. One is using a fluid as lubricants which do not bear shear loads. The other extreme were using hard coatings which bears enormous amount of shear loads. In the present investigation an attempt has been made to understand the kinematics of deformation of balls and coatings which are not as hard as conventional coatings without lubricants. Different ball materials like case hardened carbon steel, high carbon high chromium steel and stainless steel, case hardened carbon steel and high carbon high chromium steel balls were coated with tin and case hardened carbon steel and stainless steel balls were coated with zinc by electroplating coating technique. The thickness of the coating was maintained at 25 µm. Four ball test rig was used to simulate the field condition. The experiments were conducted without lubricants. The normal loads were 100N, 300N and 500N respectively for case hardened carbon steel and high carbon high chromium steel, run for a period of 5 minutes. The normal loads were 50N, 75N and 100N respectively for stainless steel and run for a period of 5 minutes. The frictional load and normal load were monitored and co-efficient of friction was estimated. The wear scar was studied under scanning electron microscope. The co-efficient of friction was found to be dependent on normal load and type of coating material. The co-efficient of friction was found to be minimum of value 0.27 for a maximum normal load of 500N for tin coatings and 0.41 for a maximum load of 500N for zinc coatings. The morphology of wear scar studied in scanning electron microscope explains the dependency of co-efficient of friction on normal load and different coating materials.

   Rolling contact fatigue, four ball tester, Coatings.


1.             R. Ahmed and M. Hadfield, Wear 203/204     (1997) 98–106.
2.             Makela, P. Vouristo, M. Lahdensuo, K. Niemi and T. Mantyla, Proceedings of the 7th International Thermal Spray Conference, Boston,

3.             Massachuesetts, 20–24 June 1994, pp. 759–763.

4.             M. Faraday, Philos. Trans. R. Soc. 147 (1857) 145.

5.             K. Kirner, Schweissen Schnieden 41 (1989) 583–586.

6.             M.E. Vinayo, F. Kassabji, J. Guyonnet and P. Fauchais, J. Vac. Sci. Technol. A3 (1985) 2483–2489.

7.             J. Nerz, B.A. Kushner and A.J. Rotolico, Proceedings of the Thermal Spraying Conference, Essen, Germany, 29–31 August 1990, pp. 47–51.

9.             M.P. Subrahmanyam, M.P. Srivastava and R. Sivakumar, Mater. Sci. Eng. 84 (1984)209–214.

10.          R. Nieminen, P. Vouristo, K. Niemi, T. Mantyla and G. Barbezat, Wear 212 (1997) 66–77.

11.          R. Ahmed and M. Hadfield, Tribol. Int. 30 (1997) 129–137.

12.          R. Ahmed and M. Hadfield, Surf. coatings Technol. 82 (1996) 176–186.
13.          R. Ahmed and M. Hadfield, Wear 230 (1999) 39–55.
14.          S. Tobe, S. Kodama and H. Misawa, Proceedings of the National Thermal Spray Conference, Tokoyo, Japan, 1990, pp. 171–178.

15.          R. Ahmed and M. Hadfield, Proceedings of the International Thermal Spray Conference, Singapore, ISBN 0871707373, 2001, pp. 1009– 

16.          1015.

17.          M. Yoshida, K. Tani, A. Nakahira, A. Nakajima and T. Mawatari, Proceedings of ITSC, Kobe, May 1995, 1992, pp. 663–668.

18.          R. Ahmed and M. Hadfield, Wear 209 (1997) 84–95.19.          Nakajima, T. Mawatari, M. Yoshida, K. Tani and A. Nakahira, Wear 241 (2000) 166–173.

20.          S. Kuroda, T. Fukishima and S. Kitahara, Proceedings of the International Thermal Spray Conference, Orlando,OH, 1992, pp. 903–909.

21.          T. Morishita, E. Kuramochi, R.W. Whitfield and S. Tanabe, Proceedings of the International Thermal Spray Conference, Orlando, OH,   1992, pp. 1001–1004.

22.          O.C. Brandt, J. Therm. Spraying 4 (1995) 147–152.

23.          G.R. Millar, L.M. Keer and H.S. Cheng, Proc. R. Soc. London, Ser. A 397 (1985) 197–209.

24.          T.A. Harris, Rolling Bearing Analysis, 3rd ed., Wiley, New York, 1991, p. 23.

25.          H.S. Cheng, T.P. Chang and W.D. Sproul, Proceedings of the 16th Leeds–Lyon Symposium, Elsevier, 1990, pp. 81–88.

26.          R. Thom, L. Moore, W.D. Sproul and T.P. Chang, Surf. Coatings Technol. 62 (1993) 423–427.

27.          O. Knolek, B. Bosserhoff, A. Schrey, T. Leyendecker, O. Lemmer and S. Esser, Surf. Coating Technol. 54/55 (1992) 102–107.

28.          L. Rosado, V.K. Jain and H.K. Trivedi, Wear 212(1997) 1–6.

29.          I.A. Polonsky, T.P. Chang, L.M. Keer and W.D. Sproul, Wear 208 (1997) 204–219.

30.          Suresha Gowda M. V, Vidyasagar H. N and Ranganatha S, IJRTE, ISSN: 2277-3878,Vol 4 Jan 2016, 1-8.

31.          Suresha Gowda M. V, Ranganatha S and Vidyasagar H. N, IJITEE, ISSN: 2278-3075, Vol 5, Feb 2016, 24-31.






Abhinav V. Deshpande

Paper Title:

Analysis of Current Steering Digital to Analog Converter

Abstract:   The current steering Digital to Analog Converter (DAC) with a Digital random return to zero technique in order to improve the namic performance is presented in this research paper. In order to demonstrate the proposed technique, an 8 bit CMOS DAC is designed and the layout is prepared in 90 nm technology. The chip layouts run on low power and have small area overhead.

 DAC, Current Steering, Converter


1.        R. Bugeja, B.S. Song, P. L. Rakers and S. F. Gillig, “A 14-b 100-MS/sec CMOS DAC Designed for Spectral Performance”, IEEE Journal of Solid State Circuits, Volume 34, No. 12, pp. 1719-1732, December 1999.
2.        R. Bugeja and B. S. Song, “A Self-Trimming 14-b 100-MS/sec CMOS DAC”, IEEE Journal of Solid State Circuits, Volume 35, No. 12, pp. 1841-1852, December 2000.

3.        Q. Huang, P.A. Francese, C. Martelli and J. Nielsen, “A 200 MS/sec 14 b 97 mW DAC in 0.18 mµm CMOS”, in Proceedings of IEEE International Solid State Circuits Conference Dig. Tech. Papers, February 2004, pp. 364-532.

4.        S. Park, G. Kim, S. C. Park and W. Kim, “A Digital-to-analog Converter Based on Differential Quad Switching”, IEEE Journal of Solid State Circuits, Volume 37, No. 10, pp. 1335-1338, October 2002.

5.        Wei-Hsin Tseng, Jieh-Tsorng Wu and Yung-Cheng Chu, “A CMOS 8 bit 1.6 GS/sec DAC with Digital Random Return-to-Zero”, IEEE Transactions on Circuits and Systems II: Express Briefs, Volume 58, No. 1, pp. 01-05, January 2011.






Niharika Soni, Rajesh Bhatt, Girish Parmar

Paper Title:

Comparative study of PSO/PI and PSO/PID Approaches for AGC of Two Area Interconnected Thermal Power System

Abstract: The solution of one or more control optimization problems regarding automatic generation control (AGC) through the efficient techniques are required in interconnected areas of power system.  Heuristic optimization methods have replaced the analytical methods to tune the parameters of controllers used in power system since the analytical methods suffer from slow convergence and the curse of dimensionality. In the same direction, the Particle Swarm Optimization (PSO) technique among the swarm intelligence family has been applied in order to improve the performance of the two area interconnected thermal power plants. Proportional Integral Derivative (PID) controllers and Proportional Integral (PI) controllers  have been employed in the system under study and the PSO optimization technique has been used to optimize the parameters of PI and PID controllers by considering the Integral Time Multiplied by Absolute Error (ITAE) as the objective function. Both the approaches PSO/PI and PSO/PID have been compared for the same system under investigation to show the superiority of the PSO/PID approach. The results have been simulated with the MATLAB /SIMULINK environment and it has been shown that PSO optimized PID controllers for the LFC provides the better dynamic responses than PSO optimized PI controllers for same system.

automatic generation control, two areas interconnected power systems, PID-controllers, particle swarm optimization.


1.       Kundur, P. Power System Stability and Control. New Delhi: Tata McGraw Hill, 2009.
2.       Elgerd, OI. Electric Energy Systems Theory – An Introduction, New Delhi: Tata McGraw Hill, 2000.

3.       H. Shayeghi, H.A. Shayanfar, A. Jalili, Load frequency control strategies: A state-of-the art survey for the researcher, Int J of Energy Conversion and Management, Vol. 50, No. 2, pp. 344–353, 2009.

4.       L.C. Saikia, J. Nanda, S. Mishra, Performance comparison of several classical controllers in AGC for multi-area interconnected thermal system. Int J Elect Power &
Energy Systs 2011; 33: 394-401.

5.       E.S. Ali, S.M. Abd-Elazim, Bacteria foraging optimization algorithm based load frequency controller for interconnected power system. Int J Elect Power & Energy Systs 2011; 33: 633–638.

6.       H. Gozde, M.C. Taplamacioglu, Automatic generation control application with craziness based particle swarm optimization in a thermal power system. Int J Elect Power & Energy Systs 2011; 33: 8–16.

7.       H. Shabani, B. Vahidi, M. Ebrahimpour, A robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems. ISA Transactions 2012:52:88–95.

8.       U.K. Rout, R.K. Sahu, S. Panda,  Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Engineering Journal 2013; 4(3):409-421.

9.       B. Mohanty, S. Panda, P.K. Hota, Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system, Int. J. Elect. Power & Energy Syst 2014; 54:77–85.

10.    A.K. Barisal, Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-sources power systems, Int. J. Electr. Power Energy Syst. 66 (2015) 67–77.

11.    R. Farhangi, M. Boroushaki, S.H. Hosseini,  Load frequency control of inter- connected power system using emotional learning based intelligent controller, Int. J. Electr. Power Energy Syst. 36 (1) (2012) 76–83.

12.    K. Naidu, H. Mokhlis,  A.H.A. Bakar, V. Terzija,  H.A. Illias, Application of firefly algorithm with online wavelet filter in automatic generation control of an interconnected reheat thermal power system, Int. J. Electr. Power Energy Syst. 63 (2014) 401–413.

13.    H. Gozde, M.C. Taplamacioglu, I. Kocaarslan,  Comparative performance analysis of Artificial Bee Colony algorithm in automatic generation control for interconnected reheat thermal power system, Int. J. Elect. Power Energy Systs, 42 (2012) 167–178.

14.    R.K. Sahu, S. Panda, S. Padhan, Optimal gravitational search algorithm for interconnected power systems, Ain Shams Eng. J.5 (3) (2014) 721–733.

15.    Y. L. Abdel-Magid and M. A. Abido, “AGC tuning of interconnected reheat thermal systems with particle swarm optimization,” Proc.10th IEEE International Conference on Electronics, Circuits and Systems, ICECS, vol. 1, 2003, pp. 376- 379.

16.    S. P. Ghoshal, “Application of GA/GA-SA based fuzzy automatic generation control of a multi-area thermal generating system,” Electric Power Systems Research, vol. 70, no. 2, pp. 115-127, July 2004.

17.    G. A. Chown, R. C. Hartman, “Design & experience of fuzzy logic controller for automatic generation control (AGC),” IEEE Trans. on Power Systems, vol. 13, no. 3, pp. 965-970, Aug. 1998.

18.    Earl Cox, Fuzzy Fundamentals. IEEE Spectrum, Oct 1992, pp. 58-61.

19.    P. Saraswat, G. Parmar, A comparative study of Differential Evolution and Simulated Anealing  for order Reduction of Large Scale Systems, International Conference on Communication, Control and Intelligent Systems (ICCIS), Nov. 7-8, 2015

20.    Soni, g. Parmar, m. Kumar and s. Panda, hybrid grey wolf optimization-pattern search (hgwo-ps) optimized 2dof-pid controllers for load frequency control (lfc) in interconnected thermal power plants, ictact journal on soft computing, volume: 06, Issue: 03, April 2016.






Rahul Hodage, Ravindra K. Lad

Paper Title:

Multi Criteria Decision Making Approach for Success Potential of Real Estate Project

Abstract:  The main purpose of this study is to develop a comprehensive success model for real estate projects considering both external and internal factors. In this respect, a wide range of success criteria are identified based on an extensive literature survey, and these criteria are classified into their respective sub criteria. In this context, a questionnaire was developed to facilitate systematic data collection in this study. In this survey, experts’ opinion from professionals and academicians of civil engineering field is taken through questionnaire. Top level managers, Senior civil engineer and Professors were involved for data gathering and finalizing the project Success Criteria and their respective sub Criteria. Further attempt has been made to formulate a fuzzy set numbers and employing Fuzzy Multiple Criteria Decision Making technique with a view to determine success potential of real estate project. The two main objectives achieved from this study, first, to provide a success potential index for completed projects in order to compare them with each other and to establish for improvement in future projects. Real estate companies may benefit from the findings of the proposed model in assessing the performance of their projects and may take the necessary actions to achieve better success in their projects to make a reputation in market.

 Fuzzy logic, Multi Criteria, Project success, Real Estate, Success potential index.


1.       Chien-Chang Chou, “Integrated Short- Term and Long-Term MCDM Model for solving location selection problem” Vol. 135, No. 11, November 1, 2009, ©ASCE
2.       Chua, D. K. H., Kog, Y. C., and Loh, P. K. (1999). “Critical success factors for different project objectives.” Journal Of Construction Engineering And Management , Vol. 125, No. 3, May/June, 1999. ©ASCE, pp 142-150.               

3.       C.S. Lim, M.Z. Mohamed. Criteria of project success: an exploratory re-examination. International Journal of Project Management. 1999, 17(4), pp 243-48.

4.       Didem Erdem and Beliz Ozorhon. (2014), “Assessing Real Estate Project Success Using an Analytic Network Process.” Journal Of Construction Engineering And Management , Vol. 31, No. 4, July, 2015. ©ASCE, pp 142-150. 

5.       D. Singh and Robert L. K. Tiong, “A Fuzzy Decision Framework for Contractor Selection” Journal of construction Engineering and management @  Vol. 1, No. 62, January, 2005, ©ASCE, pp 62-70.               

6.       Eric, C.E., (2003) Facility Design and Management Hand book, McGraw-Hill, New York.

7.       Khosravi Shahrzad  and Afshari Hamidreza, (2011) “A Success Measurement Model for Construction Projects.” 2011 International Conference on Financial Management and Economics IPEDR vol.11 (2011) © (2011) IACSIT Press, Singapore

8.       M. Medineckiene, E.K. Zavadskas and Z. Turskis, “Dwelling selection by applying fuzzy game theory” Vol. XI, No. 3, @ Archives of civil and Mechanical engineering

9.       Prabhakar, G. P. (2008), “What is project success: A literature review”. International Journal of Business and Management, ISSN 1833-3850 Vol 3 (9). pp 3-10.

10.    Stoy Christian and  Hans-Rudolf Schalcher “Residential Building Projects: Building Cost Indicators and Drivers.” Journal Of Construction Engineering And Management, Vol. 133, No. 2, February 1, 2007. ©ASCE, pp 139-145

11.    Syed Zafar Shahid Tabish and Kumar Neeraj Jha (2012). “Success Traits for a Construction Project.” Journal of Construction Engineering And Management, Vol. 138, No. 10, October 1, 2012. ©ASCE, pp 1131-1138




Volume-5 Issue-4

 Download Abstract Book

S. No

Volume-5 Issue-4, September 2016, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Th. Rupachandra Singh, Irengbam Tilokchan Singh, Tejmani Sinam

Paper Title:

Analysis of Skype and its Detection

Abstract:  This paper gives a complete analysis of Skype Traffic. Based on the analysis of Skype Traffic, we proposed a heuristic based detection method which classified the Skype Signaling and Skype Media Traffic. We properly categorized the Skype Media traffic as audio or video conversation. In this paper, we also propose a novel approach to identify VoIP Network Traffic in the first few seconds of initial state of communication. The proposed classifier works with Machine Learning Techniques based on the statistical features. The experimental results show that the proposed method can achieve over 99% accuracy for all testing dataset.

 Skype; Network Traffic Analysis; Traffic Classification; Machine Learning


1.       S. Sen, O. Spatscheck, and D. Wang, “Accurate, scalable in- network identification of p2p traffic using application signatures,” in Proceedings of the 13th International Conference on World Wide Web. New York, NY, USA: ACM, 2004, pp. 512–521.
2.       “l7-filter application layer packet classifier for linux,” 2009, http:  //l7filter.sourceforge.net.

3.       T. Sinam, I. T. Singh, P. Lamabam, and N. N. Devi, “An efficient technique for detecting skype flows in udp media streams,” in Advanced Networks and Telecommuncations Systems (ANTS), 2013 IEEE International Conference, Dec 2013, pp. 1–6.

4.       T. Sinam, I. T. Singh, P. Lamabam, N. N. Devi, and S. Nandi, “A technique for classification of voip flows in udp media streams using voip signalling traffic,” in Advance Computing Conference (IACC), 2014 IEEE International, Feb 2014, pp. 354–359.

5.       T. Sinam, N. N. Devi, P. Lamabam, I. T. Singh and S. Nandi, “Early Detection of VoIP Network Flows based on Sub-Flow Statistical Characteristics of Flows using Machine Learning Techniques,” in Advanced Networks and Telecommuncations Systems (ANTS), 2014 IEEE International Conference, Dec 2014.

6.       L. Grimaudo, M. Mellia, E. Baralis, and R. Keralapura, “Select: Self- learning classifier for internet traffic,” IEEE Transactions on Network and Service Management, vol. 11, no. 2, pp. 144–157, 2014.

7.       T. T. Nguyen and G. Armitage, “A survey of techniques for internet traffic classification using machine learning,” Commun. Surveys Tuts., vol. 10, no. 4, pp. 56–76, Oct. 2008.

8.       J. Chandrakant and D. Lokhande Shashikant, “Analysis of early traffic processing and comparison of machine learning algorithms for real time internet traffic identification using statistical approach,” in Advanced Computing, Networking and Informatics- Volume 2, ser. Smart Innovation, Systems and Technologies, M. Kumar
Kundu, D. P. Mohapatra, A. Konar, and A. Chakraborty, Eds. Springer International Publishing, 2014, vol. 28, pp. 577–587.

9.       R. Yan and R. Liu, “Principal component analysis based network traffic classification,” JCP, vol. 9, no. 5, pp. 1234–1240, 2014.

10.    J. M. Reddy and C. Hota, “P2p traffic classification using ensemble learning,” in Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop, ser. I
CARE ’13. New York, NY, USA: ACM, 2013, pp. 14:1–14:4.

11.    M. Korczynski and A. Duda, “Markov chain fingerprinting to classify encrypted traffic,” in IEEE Conference on Computer Communikations, INFOCOM , Toronto, Canada, April 27 – May 2, 2014. IEEE, 2014, pp. 781–789.

12.    “libsvm-3.0,” http://www.csie.ntu.edu.tw/cjli n/libsvm/.

13.    N. Cristianini and J. Shawe-Taylor, An Introduction to support Vector Machines and other Kernel-based Learning Methods. Cambridge University Press, 2003.

14.    H. Witten and E. Frank, Data Mining: Practical Machine Learning Tools and techniques. Elsevier Inc., 2005.

15.    J. Han and M. Kamber, Data Mining: Concepts and Techniques. Elsevier Inc., 2006.

16.    T. Karagiannis, A. Broido, N. Brownlee, K. C. Claffy, and M. Faloutsos, “Is p2p dying or just hiding?” in Proceedings of the GLOBECOM 2004 Conference. IEEE Computer Society Press, November 2004.

17.    P. Haffner, S. Sen, O. Spatscheck, and D. Wang, “Acas: Automated construction of application signatures,” in Proceedings of the 2005 ACM SIGCOMM Workshop on Mining Network Data, ser. MineNet ’05. New York, NY, USA: ACM, 2005, pp. 197–202.

18.    J. Erman, A. Mahanti, M. F. Arlitt, I. Cohen, and C. L. Williamson, “Semi-supervised network traffic classification,” in SIGMETRICS, 2007, pp. 369–370.

19.    J. Erman, M. Arlitt, and A. Mahanti, “Traffic classification using clustering algorithms,” in Proceedings of the 2006 SIGCOMM Workshop on Mining Network Data, ser. MineNet ’06. New York, NY, USA: ACM, 2006, pp. 281–286.

20.    Y. Wang, Y. Xiang, and S.-Z. Yu, “An automatic application signature construction system for unknown traffic.” Concurrency and Computation: Practice and Experience, vol. 22, no. 13, pp. 1927–1944.

21.    X. Li, F. Qi, D. Xu, and X. Qiu, “An internet traffic classification method based on semi-supervised support vector machine.” in ICC. IEEE, 2011, pp. 1–50.

22.    T. N. Thuy T. and G. Armitage, “Training on multiple sub-flows to optimise the use of machine learning classifiers in real-world ip networks,” in in Proceedings of the IEEE 31st Conference on Local Computer Networks, 2006.

23.    S. Zander, T. T. T. Nguyen, and G. J. Armitage, “Sub-flow packet sampling for scalable ml classification of interactive traffic,” in LCN, 37th Annual IEEE Conference on Local Computer Networks. Clearwater Beach, FL, USA: IEEE, October 22-25 2012, pp. 68–75.

24.    G. Xie, M. Iliofotou, R. Keralapura, M. Faloutsos, and A. Nucci, “Sub-flow: Towards practical flow-level traffic classification,” in Proceedings of the IEEE INFOCOM. Orlando, FL, USA: IEEE, March 25-30 2012, pp. 2541–2545.

25.    Este, F. Gringoli, and L. Salgarelli, “On the stability of the information carried by traffic flow features at the packet level,” SIGCOMM Comput. Commun. Rev., vol. 39, no. 3, pp. 13–18, Jun. 2009.

26.    L. Peng, H. Zhang, B. Yang, and Y. Chen, “Feature evaluation for early stage internet traffic identification,” in Algorithms and Architectures for Parallel Processing, ser. Lecture Notes in Computer Science, X.-h. Sun, W. Qu, I. Stojmenovic, W. Zhou, Z. Li, H. Guo, G. Min, T. Yang, Y. Wu, and L. Liu, Eds. Springer International Publishing, 2014, vol. 8630, pp. 511–525.

27.    “Tstat – skype traces,” http://tstat.tlc.polito.it/ traces-skype.shtml.

28.    “Tstat – tcp statistic and analysis tool,” http://tstat.tlc.polito.it/index. shtml.

29.    F. Gringoli, L. Salgarelli, M. Dusi, N. Cascarano, F. Risso, and kc Claffy, “Gt: picking up the truth from the ground for internet traffic,” Computer Communication Review, vol. 39, no. 5, pp. 12–18, 2009.

30.    “Napatech,” http://www.napatech.com/.

31.    “Weka3.6.2,” 2011, http://www.cs.waikato.ac. nz /ml/weka.

32.    www.halcyon.com/pub/journals/21ps03-vidmar






K.A.M. Sajad Hyder, M. Vanitha

Paper Title:

Segmentation of Liver and Retrieval Procedure by Feature Extraction for CT-Scan Abdominal Image Processing

Abstract:  Liver is an important vital organ. In these days medical professionals utilize CT scan abdominal images for the diagnosis of liver disorders. There arise the problem of liver segmentation and image processing for recapturing the matching image of predetermined image of liver ill state. In this present work a new way of methodology has been introduced for the pulling out liver image in a large dataset of abdominal scanned images. Further the segmented liver images are preprocessed for the feature extractions of Shape, Intensity and Texture. An automatic system of Least Distance Method (LDM) is used for the recalling of image is run into the system. There is a significant speed and accuracy have been notified by this LDM. The above results are discussed with earlier related works and concluded with the application in clinical practice.

Automatic retrieval technique, Digital image processing, Liver Segmentation, Least Distance method for recapturing matching image.


1.    R. Punia and S. Singh, “Review on Machine Learning Techniques for Automatic Segmentation of Liver Images,” International Journal of Advanced Research in
Computer Science and Software Engineering, Vol. 3, No. 4, 2013, pp. 666-670

2.    M. Erdt, et al., “Fast Automatic Liver Segmentation Combining Learned Shape Priors with Observed Shape Deviation,” Computer-Based Medical Systems, 2010, pp. 249-254

3.    M. Sammouda, et al., “Tissue Color Images Segmenta-tion Using Artificial Neural Networks,” Biomedical Im-aging: Nano to Macro, 2004

4.    G.G. Rajput and Anand M.Chavan (2016) “Atomic Detection of Abnormalities Associated with Abdomen and Liver Images : A survey on Segmentation methods”, International Journal of Computer Applications, Volume 140-No.4, pp. 1 to 8

5.    Lav R.Varshney (2002), “Abdominal Organ Segmentation in CT-Scan Images : A Survey”, International Journal of Information Technology, Volume 100. pp. 200 to 215

6.    Luo et. al., (2014), “Review on the methods of Automatic Liver Segmentation from Abdominal Images” Journal of Computer and Communications, 2, pp. 1-7

7.    X. Zhang, et al., “Automatic Liver Segmentation Using a Statistical Shape Model With Optimal Surface Detection,” IEEE Transaction on Biomedical Engineering, Vol. 57, No. 10, 2010, pp. 2611-2626

8.    M. Erdt, et al., “Fast Automatic Liver Segmentation Combining Learned Shape Priors with Observed Shape Deviation,” Computer-Based Medical Systems, 2010, pp.

9.    H. Badakhshannoory and P. Saeedi, “A Model-Based Validation Scheme for Organ Segmentation in CT Scan Volumes,” IEEE Transaction on Biomedical Engineering, 2009, pp. 2681-2693






Sourav Sarkar, J. Shah, R. K. Kotnala, M. C. Bhatnagar

Paper Title:

Effect of Zn and Mn Substitution on Structural, Dielectric, Magnetic and Optical Properties of Multiferroic CoFe2O4-BaTiO3 Core-Shell Type Composites

Abstract: In this paper, we have reported the synthesis of Zn and Mn substituted cobalt ferrite by chemical co-precipitation method and used it as core material in barium titanate sol to finally prepare core-shell type composite material. Amount of ferrite was varied in the final composite samples from 30% to 50%. X-ray diffraction show prominent spinel and perovskite peaks corresponding to ferrite and titanate phases respectively. HRTEM micrographs reveal core-shell type nature with presence of a well-defined interface. Our proposed substitutions increase the resistivity of pure cobalt ferrite by one order which has been verified through I-V measurement. SEM micrographs show dense microstructure and particle formation of both phases in the composites. Substitution of Zn at the site of Co is supported by the peak shift in Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy. Maxwell Wagner relaxation phenomena at the interface and hopping conduction in ferrites explain both frequency and temperature variation of dielectric parameters. Substitution of Zn and Mn result in super-paramagnetic type behavior with coercively  few Oe and very negligible remnant magnetization (MR). Photoluminescence (PL) spectra show slight decrease in energy band gap of ferrite as a result of these substitutions.

 Sol-gel process (A); Composites (B); Dielectric properties (C); Optical properties (C)


1.       J. Ryu, S. Priya, K. Uchino, H.E. Kim, Magnetoelectric Effect in Composites of Magnetostrictive and Piezoelectric Materials,J. Electroceram, (2002) 107–119. doi:10.1023/A.
2.       G.V. Duong, R. Groessinger, R.S. Turtelli, Magnetoelectric properties of CoFe2O4 –BaTiO3 magnetoelectric composites, J. Magn. Magn. Mater. 316 (2007) 624–627. doi:10.1016/j.jmmm.2007.03.142.

3.       N.A. Spaldin, M. Fiebig, The Renaissance of Magnetoelectric Multiferroics, Science 309 (2005) 391–392. doi:10.1126/science.1113357.

4.       Corral-Flores, D. Bueno-Baques, R.F. Ziolo, Synthesis and characterization of novel CoFe2O4-BaTiO3 multiferroic core-shell-type nanostructures, Acta Mater. 58 (2010) 764–769. doi:10.1016/j.actamat.2009.09.054.

5.       G. V. Duong, R. Groessinger, M. Schoenhart, D. Bueno-Basques, The lock-in technique for studying magnetoelectric effect, J. Magn. Magn. Mater. 316 (2007) 390–393. doi:10.1016/j.jmmm.2007.03.185.

6.       Gupta, R. Chatterjee, Dielectric and magnetoelectric properties of BaTiO3-Co0.6Zn0.4Fe1.7Mn0.3O4 composite, J. Eur. Ceram. Soc. 33 (2013) 1017–1022. doi:10.1016/j.jeurceramsoc.2012.11.003.

7.       P. Zhu, Q. Zheng, R. Sun, W. Zhang, J. Gao, C. Wong, Dielectric and magnetic properties of BaTiO3/Ni0.5Zn0.5Fe2O4 composite ceramics synthesized by a co-precipitation process, J. Alloys Compd. 614 (2014) 289–296. doi:10.1016/j.jallcom.2014.06.065.

8.       G.S. Shahane, A. Kumar, M. Arora, R.P. Pant, K. Lal, Synthesis and characterization of Ni-Zn ferrite nanoparticles, J. Magn. Magn. Mater. 322 (2010) 1015–1019. doi:10.1016/j.jmmm.2009.12.006.

9.       K. Raidongia, A. Nag, A. Sundaresan, C.N.R. Rao, Multiferroic and magnetoelectric properties of core-shell CoFe2O4 @ BaTiO3 nanocomposites, Appl. Phys. Lett. 97 (2010) 2010–2012. doi:10.1063/1.3478231.

10.    R.K. Singh, A. Narayan, K. Prasad, R.S. Yadav, A.C. Pandey, A.K. Singh, L. Verma, R.K. Verma, Thermal, structural, magnetic and photoluminescence studies on cobalt ferrite nanoparticles obtained by citrate precursor method, J. Therm. Anal. Calorim. 110 (2012) 573–580. doi:10.1007/s10973-012-2728-1.

11.    S. Sarkar, M.C. Bhatnagar, Effect of Mn substitution on acetone and ammonia sensing in CoFe2O4nanoparticles, 2nd Int. Symp. Phys. Technol. Sensors, IEEE, 2015: pp. 253–256. doi:10.1109/ISPTS.2015.7220123.

12.    G. Vaidyanathan, S. Sendhilnathan, R. Arulmurugan, Structural and magnetic properties of Co1-xZnxFe2O4 nanoparticles by co-precipitation method, J. Magn. Magn. Mater. 313 (2007) 293–299. doi:10.1016/j.jmmm.2007.01.010.

13.    L. Zhao, H. Zhang, Y. Xing, S. Song, S. Yu, W. Shi, X. Guo, J. Yang, Y. Lei, F. Cao, Studies on the magnetism of cobalt ferrite nanocrystals synthesized by hydrothermal method, J. Solid State Chem. 181 (2008) 245–252. doi:10.1016/j.jssc.2007.10.034.

14.    S. Singhal, S. Bhukal, J. Singh, K. Chandra, S. Bansal, Optical, X-ray diffraction, and magnetic properties of the cobalt-substituted nickel chromium ferrites (CrCox Ni1-xFeO4, x = 0, 0.2, 0.4, 0.6, 0.8, 1.0) synthesized using sol-gel autocombustion method, J. Nanotechnol. 2011 (2011) 2–7. doi:10.1155/2011/930243.

15.    R.M. Mohamed, M.M. Rashad, F.A. Haraz, W. Sigmund, Structure and magnetic properties of nanocrystalline cobalt ferrite powders synthesized using organic acid precursor method, J. Magn. Magn. Mater. 322 (2010) 2058–2064. doi:10.1016/j.jmmm.2010.01.034.

16.    H. Deligöz, A. Baykal, M.S. Toprak, E.E. Tanriverdi, Z. Durmus, H. Sözeri, Synthesis, structural, magnetic and electrical properties of Co1-xZnxFe2O4 (x = 0.0, 0.2) nanoparticles, Mater. Res. Bull. 48 (2013) 646–654. doi:10.1016/j.materresbull.2012.11.032.

17.    S.J. Chang, W.S. Liao, C.J. Ciou, J.T. Lee, C.C. Li, An efficient approach to derive hydroxyl groups on the surface of barium titanate nanoparticles to improve its chemical modification ability, J. Colloid Interface Sci. 329 (2009) 300–305. doi:10.1016/j.jcis.2008.10.011.

18.    U.-Y. Hwang, H.-S. Park, K.-K. Koo, Behavior of Barium Acetate and Titanium Isopropoxide during the Formation of Crystalline Barium Titanate, Ind. Eng. Chem. Res. 43 (2004) 728–734. doi:10.1021/ie030276q.

19.    H. Reverón, C. Aymonier, A. Loppinet-Serani, C. Elissalde, M. Maglione, F. Cansell, Single-step synthesis of well-crystallized and pure barium titanate nanoparticles in supercritical fluids, Nanotechnology. 16 (2005) 1137–1143. doi:10.1088/0957-4484/16/8/026.

20.    Y. Wang, Y. Wang, W. Rao, M. Wang, G. Li, Y. Li, J. Gao, W. Zhou, J. Yu, Dielectric, ferromagnetic and ferroelectric properties of the (1 − x)Ba0.8Sr0.2TiO3–xCoFe2O4 multiferroic particulate ceramic composites, J. Mater. Sci. Mater. Electron. 23 (2012) 1064–1071. doi:10.1007/s10854-011-0548-x.

21.    I.H. Gul, A. Maqsood, M. Naeem, M.N. Ashiq, Optical, magnetic and electrical investigation of cobalt ferrite nanoparticles synthesized by co-precipitation route, J. Alloys Compd. 507 (2010) 201–206. doi:10.1016/j.jallcom.2010.07.155.

22.    Gupta, R. Chatterjee, Study of dielectric and magnetic properties of PbZr0.52Ti0.48O3-Mn0.3Co0.6Zn0.4Fe1.7O4 composite, J. Magn. Magn. Mater. 322 (2010) 1020–1025. doi:10.1016/j.jmmm.2009.12.007.

23.    V Shvartsman, F. Alawneh, P. Borisov, D. Kozodaev, D.C. Lupascu, Converse magnetoelectric effect in CoFe2O4 –BaTiO3 composites with a core–shell structure, Smart Mater. Struct. 20 (2011) 075006. doi:10.1088/0964-1726/20/7/075006.

24.    S. Singhal, T. Namgyal, S. Bansal, K. Chandra, Effect of Zn Substitution on the Magnetic Properties of Cobalt Ferrite Nano Particles Prepared Via Sol-Gel Route, J. Electromagn. Anal. Appl. 02 (2010) 376–381. doi:10.4236/jemaa.2010.26049.

25.    Y. Fu, H. Chen, X. Sun, X. Wang, Combination of cobalt ferrite and graphene: High-performance and recyclable visible-light photocatalysis, Appl. Catal. B Environ. 111-112 (2012) 280–287. doi:10.1016/j.apcatb.2011.10.009.

26.    N. V. Dang, T.L. Phan, T.D. Thanh, V.D. Lam, L. V. Hong, Structural phase separation and optical and magnetic properties of BaTi1-xMnxO3 multiferroics, J. Appl. Phys. 111 (2012). doi:10.1063/1.4725195.

27.    K. Vanheusden, W.L. Warren, C.H. Seager, D.R. Tallant, J.A. Voigt, B.E. Gnade, Mechanisms behind green photoluminescence in ZnO phosphor powders, J. Appl. Phys. 79 (1996) 7983. doi:10.1063/1.362349.

28.    Warren, W.L., Vanheusden, K., Dimos, D., Pike, G.E. and Tuttle, B.A., 1996. Oxygen vacancy motion in perovskite oxides. J. Am. Ceram. Soc. 79(2), pp.536-538.






Naina Lohana, M. Mani Roja

Paper Title:

A Review of the Internet of Things

Abstract:  In this paper an effort is taken to review the concept of the Internet of Things (IoT). It has gained popularity in the recent years due to its wire-ranging applications. As the world moves towards a future with more and more devices linked to the Internet, this paper looks at the elements of IoT, its communication models, the challenges it faces and its applications.



1.    M. Rouse Internet of  Things. Retreived from http://internetofthingsagenda.techtarget.com/definition/Internet-of-Things-IoT
2.    L. Atzori et al., The Internet of Things: A survey, Comput. Netw. (2010), doi:10.1016/j.comnet.2010.05.010

3.    K. L. Lueth, IoT Basics: Getting Started with the Internet of Things, IoT Analytics(2015). Retrieved from https://iot-analytics.com/product/whitepaper-iot-basics-getting-started-with-the-internet-of-things/

4.    K. Rose, S. Elridge, L. Chapin  The Internet of Things: An Overview, Internet Society (2015). Retrieved from http://www.internetsociety.org/doc/iot-overview

5.    D. Hamilton The Four Internet of Things Connectivity Models Explained. Retrieved from http://www.thewhir.com/web-hosting-news/the-four-internet-of-things-connectivity-models-explained

6.    T.T. Mulani, S.V. Pingle  Internet of Things, IRJMS Vol 2  Special Issue 1, March 2016.

7.    B. Katole, M. Sivapala, V. Suresh,Principle Elements and Framework of Internet of Things, Research Inventy: IJES Vol 3 Issue 5, July 2013.

8.    J. Gubbi, R. Buyya, S Marusic, M. Paluniswami, Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions,Future Generation Computer Systems Vol.29 Issue 7, September 2013.






Ahmed H.Almutairi

Paper Title:

Laser Diode and Applications

Abstract: This paper shows how to use the P-N Junction to generate the Laser (Laser Diode) and how we use this laser Diode in many applications.

 Introduction, P-N Junction, Biased p-n Junction, Laser diodes, Turning semiconductor amplifiers into laser diodes, Applications of Laser Diodes, Conclusion and References.


1.       J. Gowar, Optical Communication Systems, Prentice Hall, London, 1984.
2.       Kittel, Introduction to Solid State Physics, 6th Edition, Wiley, New York,1986.

3.       Reif, Fundamentals of Statistical and Thermal Physics, McGraw Hill, NewYork, 1965.

4.       Yariv, Introduction to Optical Electronics, 1st Edition, Holt Rinehart and Winston Inc., New York, 1971.

5.       M.I. Nathan, “Semiconductor Lasers,” Appl. Opt. 5, 1514–1528, 1966.

6.       H.C. Casey, Jr, and M.B. Panish, Heterostructure Lasers, Parts A and B, Academic Press, New York, 1978; see also M.B. Panish, “Heterostructure Injection Lasers,” Proc. IEEE, 64, 1512–1540, 1976.

7.       C.A. Burrus and B.I. Miller, “Small-area, double heterostructure, aluminum gallium arsenide electroluminescent diode source for optical-fiber transmission lines,” Opt. Commun. 4, 307–309, 1971.

8.       Chandra and L.F. Eastman, “Rectification at n−nGaAs : (Ga,Al)As heterojunctions,” Electron. Lett., 15, 90–91, 1979.

9.       J.F. Womac and R.H. Rediker, “The graded-gap Alxga1 − xAs-GaAs heterojunction,” J. Appl. Phys. 43, 4129–4133, 1972.

10.    M.G. Bernard and G. Duraffourg, “Laser conditions in semiconductors,” Phys.Stat. Solids, 1, 699–703, 1961.

11.    I.F. Wu, I. Riant, J-M. Verdiell, and M. Dagenais, “Real-time in situ monitoring of antireflection coatings for semiconductor laser amplifiers by ellipsometry,” IEEE Photonics Technology Letters, 4, 991–993, 1992.

12.    R.L. Hartmann and R.W. Dixon, “Reliability of DH GaAs lasers at elevated temperatures, Appl. Phys. Lett. 26, 239–240, 1975.

13.    G.H. Olsen, C.J. Nuese, and M. Ettenberg, Appl. Phys. Lett. 34, 262–264,1979.354 Semiconductor Lasers

14.    Yonezu, I. Sakuma, K. Kobayashi, T. Kamejima, M. Unno, and Y. Nannichi, “A GaAs-AlxGa1−xAs double heterostructure planar stripe laser,” Japan J. Appl. Phys., 12, 1585–1592, 1973.

15.    Kressel, M. Effenberg, J.P. Wittke, and I. Ladany, “Laser diodes and LEDs for optical fiber communication,” in Semiconductor Devices for Optical Communication, H. Kressel, Ed., Springer-Verlag, New York, 1982.

16.    D.R. Scifres, R.D. Burnham and W. Streifer, “High Power Coupled Multiple Stripe Quantum Well Injection Lasers,” Appl. Phys. Lett., 41, 118–120 (1982).

17.    I.P. Kaminow, L.W. Stulz, J.S. Ko, A.G. Dentai, R.E. Nahory, J.C. DeWinter, and R.L. Hartman, “Low threshold IngaAsP ridge waveguide lasers at 1.3 μm,” IEEE J. Quant. Electron. QE-19, 1312–1319, 1983.

18.    Botez, “CW high-pressure single-mode operation of constricted double heterojunction AlgaAs lasers with a large optical cavity,” Appl. Phys. Lett. 36, 190–192, 1980.

19.    P.K. Cheo, Fiber Optics and Optoelectronics, 2nd Edition, Prentice Hall, Englewood Cliffs, New Jersey 1990; A. Yariv, Optical Electronics, 3rd Edition, Holt, Rinehart and Winston, New York, 1985.

20.    K. Aiki, M. Nakamura, J. Umeda, A. Yariv, A. Katziv, and H.W. Yen, “GaAs-GaAlAs distributed feedback laser with separate optical and carrier confinement,” Appl. Phys. Lett., 27, 145–146, 1975.

21.    D.F.Welch, R. Parke, A. Hardy, R.Waaits, W. Striefer, and D.R. Scifres.“High-power, 4W pulsed, grating-coupled surface emitting laser,” Electron. Lett. 25, 1038–1039, 1989.

22.    J.S. Mott and S.H. Macomber, “Two-dimensional surface emitting distributed feedback laser array, IEEE Photon. Technal. Lett. 1, 202–204, 2989.

23.    J.L. Jewel, “Microlasers,” Sci. Am., Nov. 1991, 86–94.

24.    Yariv, Quantum Electronics, 3rd Edition, Wiley, New York, 1989.