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Abstract: In this technical paper, the review of literature for entropy generation in a helical coil heat exchanger was presented. The pressure drop, friction factor, heat transfer rates and flow distribution like velocity and temperature field are essential properties to control the entropy generation in a heat exchanger process are fairly presented in this article.
Keywords: entropy, heat transfer, friction factor
References:
1. Shaukat Ali Pressure drop correlations for flow through regular helical coil tubes Fluid Dynamics Research, V 28(4),2015
2. T. H. Ko Numerical Investigation of Laminar Forced Convection and Entropy Generation in a Helical Coil with Constant Wall Heat Flux Numerical Heat Transfer, Part A: Applications: An International Journal of Computation and Methodology V 49(3), 2006 pp- 257-278
3. T.H. Ko, , K. Ting Entropy generation and thermodynamic optimization of fully developed laminar convection in a helical coil International Communications in Heat and Mass Transfer V 32(2), 2005, pp-214–223
4. T.H. Ko Thermodynamic analysis of optimal mass flow rate for fully developed laminar forced convection in a helical coiled tube based on minimal entropy generation principle Energy Conversion and Management V 47(19), 2006, pp-3094–3104
5. T.H. Ko Thermodynamic analysis of optimal curvature ratio for fully developed laminar forced convection in a helical coiled tube with uniform heat flux International Journal of Thermal Sciences V 45(7), 2006, pp-729–737
6. Mohammad Ahadi, Abbas Abbassi Entropy generation analysis of laminar forced convection through uniformly heated helical coils considering effects of high length and heat flux and temperature dependence of thermophysical properties Energy V 82(3), 2015,pp-322–
7. T.H. Ko, , K. Ting Optimal Reynolds number for the fully developed laminar forced convection in a helical coiled tube Energy, V31(12), 2006, pp-2142–2152
8. T.H. Ko, , K. Ting Entropy generation and thermodynamic optimization of fully developed laminar convection in a helical coil International Communications in Heat and Mass Transfer Volume 32, Issues 1–2, 2005, pp- 214–223
9. Jiangfeng Guo, , Xiulan Huai Numerical investigation of helically coiled tube from the viewpoint of field synergy principle Applied Thermal Engineering V 98(5), 2016, pp-137–143
10. M. Hasanuzzaman,, R. Saidura, and N.A. Rahim Effectiveness Enchancement Of Heat Exchanger By Using Nanofluids 2011 IEEE First Conference on Clean Energy and Technology CET
11. M. Mohanraj, S. Jayaraj , C. Muraleedharan Applications of artificial neural networks for thermal analysis of heat exchangers e A review International Journal of Thermal Sciences V 90 2015 pp-152
12. M.A. Khairul , R. Saidur , M.M. Rahman , M.A. Alim , A. Hossain , Z. Abdin Heat transfer and thermodynamic analyses of a helically coiled heat exchanger using different types of nanofluids International Journal of Heat and Mass Transfer V 67 2013 pp-398–403
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1-3
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Abstract: Now a day, there are a number of techniques used for waste collection. In this system, there is lift container for the collection of garbage in residential area. To give a brief description of the project, the sensors are placed in the storage area, when the garbage reaches the level of sensor; the controller will give indication to the driver of garbage collection truck that the garbage bin is completely filled and needs urgent attention. Indication is done by sending SMS using GSM technology.
Keywords: Garbage level sensor, GSM technology, SMS.
References:
1. Gaikwad Prajakta , Jadhav Kalyani, Machale Snehal,”Smart Garbage Collection System In Residential Area”,IJRET ,2015
2. Kanchan Mahajan , Prof. J.S. Chitode,” Wate Bin Monitorin System Using Integreated Technologies”,IITRSET,2014.
3. Islam, M.S. Arebey, M. ; Hannan, M.A. ; Basri, H,”Overview for solid waste bin monitoring and collection system” Innovation Management and Technology Research (ICIMTR), 2012 International Conference , Malacca, 258 – 262
4. Raghumani Singh, C. Dey, M. Solid waste management of Thoubal Municipality, Manipur- a case study Green Technology and Environmental Conservation (GTEC 2011), 2011 International Conference Chennai 21 – 24.
5. Latifah, A., Mohd, A. A.,& NurIlyana, M. (2009).solid waste management in Malaysia: Practices and challenges. Waste Management, 29,2902-2906.
6. Vicentini, F. Giusti, A., Rovetta, A., Fan, X., He, Q., Zhu, M., & Liu, B. (2008). Sensorized waste collection container for content estimation and collection optimization. Waste Management.29, 1467-1472
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4-6
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Abstract: Speaker recognition is a recognition purpose that articulates words. The speaker recognition process relies on physical structure of an individual’s person’s vocal tract and the behavioral characteristics of the individual. Speaker verification is evolved with the technologies of speech recognition and speech synthesis because of the similar characteristics in the voice and challenges associated with it. Speaker recognition has two forms which is text dependent or text independent. In text dependent method a particular phrase or password is stored into the system, whereas in text independent method the speaker will not be aware that his voice is being collected. In the proposed algorithm, speech signal has been recorded in the database. And the speaker is verified using the input the speaker provides by comparing with the database. The time domain, frequency domain and power domain features of the speech is extracted. For validating the performance, a comparative analysis has been carried out with various other methods. These methods exhibit some unique behavior.
Keywords: Spectral Characteristics, Speech Recognition, Text Dependent, Text Independent
References:
1. Douglas A. Reynolds and Larry P.Heck, “Automatic Speaker Recognition: Recent Progress, Current Applications and Future Trends”, 19 February 2000, http://www.ll.mit.edu/IST/pubs/aaas00-dar-pres.pdf
2. Joseph P. Campbell, “Speaker Recognition”, Identification in Networked Society, 1999
3. Samudravijaya K, “Speech and Speaker Recognition: A Tutorial”, 2001
4. Bojan Imperl, “Speaker recognition techniques”, Maribor, Slovenia, 2000
5. Rosenberg, “L16: Speaker recognition”, Benesty, 2008
6. W. M. Campbell, D. E. Sturim, and D. A. Reynolds, “Support Vector Machines Using GMM Supervectors for Speaker Verification”, IEEE Signal Processing Letters, vol. 13, no. 5, may 2006
7. Md Jahangir Alam, Pierre Ouellet, Patrick Kenny, Douglas O’Shaughnessy, “Comparative Evaluation of Feature Normalization Techniques for Speaker Verification”, Springer, 2011
8. Santosh K.Gaikwad, Bharti W.Gawali, Pravin Yannawar, “A Review on Speech Recognition Technique”, International Journal of Computer Applications (0975 – 8887), Volume 10– No.3, November 2010
9. Zhang Wanli, Li Guoxin, “Application of Improved Spectral Subtraction Algorithm for Speech Emotion Recognition”, IEEE Fifth International Conference, 2015
10. Luciana Ferrer, Yun Lei, Mitchell McLaren, and Nicolas Scheffer, “Study of Senone-Based Deep Neural Network Approaches for Spoken Language Recognition” IEEE/ACM Transactions, 2015
11. S. K. Singh, “Features and Techniques for Speaker Recognition”, 2003
12. W. M. Campbell, D. E. Sturim, and D. A. Reynolds, “Support Vector Machines Using GMM Supervectors for Speaker Verification”, IEEE Signal Processing Letters, vol. 13, no. 5, may 2006
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20-26
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Abstract: Wireless mesh Network (WMN) is rapidly catching momentum in developing countries like India for providing seamless internet services and for disaster time emergency networking. QOS is one of the hurdles for acceptance of WMN because as more people start using the network for internet services, latency, session drops, and packet loss are noticed. Many solutions for improving QOS in terms of placement of components, QOS based routing, cross layer optimizations, MAC layer scheduling etc. are proposed to improve the QOS. In this work, we review all these solutions and problems in these solutions for large scale acceptance of WMN.
Keywords: (WMN), QOS, WMN, MAC, Wireless
References:
1. Anis Ouni, Herv´e Rivano, Fabrice Valois, Catherine Rosenberg. Energy and Throughput Optimization of Wireless Mesh Network with Continuous Power Control. [Research Report] RR- 7730, 2013, pp.27.
2. Mathilde Benveniste “A Distributed QoS MAC Protocol for Wireless Mesh” The Second International Conference on Sensor Technologies and Applications, 2008.
3. Kwan-Wu Chin, Sieteng Soh, Chen Meng, “ A Novel Spatial TDMA Scheduler for Concurrent Transmit Receive WMN” 24th IEEE International Conference on Advanced Information Networking and Applications, 2010.
4. Mauro Leoncini, Paolo Santi, Paolo Valente, “An STDMA Based Framework for QoS Provisioning in Wireless Mesh Network”, IEEE 2008.
5. Jaydip Sen “A Throughput Optimizing Routing Protocol for Wireless Mesh Networks”. 12th IEEE International Conference on High Performance Computing and Communications.2010.
6. Catalan-Cid M, Ferrer JL, Gomez C, Paradells J: Contention- and interference-aware flow-based routing in wireless mesh networks: design and evaluation of a novel routing metric. EURASIP J. Wirel. Commun. Netw. 2010, 2010: 1-20.
7. Xi Fang "Consort: Node-Constrained Opportunistic Routing in wireless mesh networks" INFOCOM, 2011 Proceedings IEEE.
8. T. Le, N. G. Nguyen, and D. H. Nghia, “A novel PSO-based algorithm for gateway placement in wireless mesh networks,” in Proc, 3 rd IEEE International Conference on Communication Software and Networks (ICCSN), China, 2011, pp. 41-46
9. Mojtaba Seyedzadegan "Internet Gateway Placement Optimization in Wireless Mesh Networks" Springer August 201310. Awadallah, Hashim and A. Hashim , Aisha Hassan (2015) A genetic approach for gateway placement in wireless mesh networks. Journal of Computer Science and Network Security, 15 (7). pp. 11-19. ISSN 1738-7906
11. Wangkit Wong "Optimizing Router Placement for Wireless Mesh Deployment" IEEE ICC 2014 - Mobile and Wireless Networking Symposium
12. J. Wang, K. Cai, and D. R. Agrawal, “A multi-rate based router placement scheme for wireless mesh networks,” in Mobile Adhoc and Sensor Systems, 2009. MASS’09. IEEE 6th International Conference on. IEEE, 2009, pp. 100–109.
13. Wireless Communications & Signal Processing (WCSP), 2013 International Conference IEEE
14. Ernst, J.B "Cross-Layer Mixed Bias Scheduling for Wireless Mesh Networks" Communications (ICC), 2010 IEEE International Conference
15. Cheng, M "Cross-Layer Schemes for Reducing Delay in Multihop Wireless Networks" Wireless Communications, IEEE Transactions on 2012
16. Xiang Li "Cross-Layer Routing Metric for Wireless Mesh Networks" Third International Conference, ICICA 2012, Chengde, China, September 14-16, 2012.
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27-29
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Abstract: Orthogonal frequency division multiplexing is widely recognized as the one important technology in broadband wireless communication systems. In wireless communication orthogonal frequency division multiplexing render higher spectral efficiency as well as enhanced performance over fast fading channel. The time domain synchronous orthogonal frequency division multiplexing also offers enhanced spectral efficiency compared to cyclic prefix orthogonal frequency division multiplexing. But interference cancellation problem degrades performance loss in high speed communication channel. The compressed sending based channel estimation increases the spectral efficiency by using time delay and reducing number of pilot symbols. This paper proposes a new scheme called compressed sending time frequency training orthogonal frequency division multiplexing. This scheme uses training information in time and frequency domain. The simulation shows that the proposed scheme outperforms TFT orthogonal frequency division multiplexing, cyclic prefix orthogonal frequency division multiplexing and TDS orthogonal frequency division multiplexing in high speed mobile environments.
Keywords: Wireless, Frequency, Channel, Multiplexing, Pilot, Training
References:
1. D. linglong, Z.Wang and Z.Yang , “Time-Frequency Training OFDM with High Spectral Efficiency and Reliable Performance in High Speed Environments” IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 30, NO. 4,pp-695-707, MAY 2012.
2. F. Adachi and E. Kudoh, “New direction of broadband wireless technology,” Wireless. Communication Mob. Com., vol. 7, no. 8, pp. 969–983, Oct. 2007.
3. X. Yuan, Q. Guo, X. Wang, and L. Ping, “Evolution analysis of low cost iterative equalization in coded linear systems with cyclic prefixes,” IEEE J. Sel. Areas Communication, vol. 26, no. 2, pp. 301–310, Feb. 2008.
4. B. Muquet, Z. Wang, G. Giannakis, M. De Courville, and P. Duhamel, “Cyclic prefixing or zero padding for wireless multicarrier transmissions?” IEEE Trans. Communication, vol. 50, no. 12, pp. 2136–2148, Dec. 2002.
5. C. yen Ong, J. Song, C. Pan, and Y. Li, “Technology and standards of digital television terrestrial multimedia broadcasting,” IEEE Communication Mag., vol. 48, no. 5, pp. 119–127, May 2010.
6. Wang, P. Ho, and Y. Wu, “Robust channel estimation and ISI cancellation for OFDM systems with suppressed features,” IEEE J. Sel. Areas Communication, vol. 23, no. 5, pp. 963–972, May 2005. On Computers, 61, 2012, pp. 1507-1520.
7. J. Wang, Z. Yang, C. Pan, and J. Song, “Iterative padding subtraction of the PN sequence for the TDS-OFDM over broadcast channels,” IEEE Trans. Consume. Electron, vol. 51, no. 11, pp. 1148–1152, Nov. 2005.
8. J. Song, Z. Yang, L. Yang, K. Gong, C. Pan, J. Wang, and Y. Wu, “Technical review on Chinese digital terrestrial television broadcasting standard and measurements on some working modes,” IEEE Trans. Broadcast., vol. 53, no. 1, pp. 1–7, Feb. 2007.
9. Framing Structure, Channel Coding and Modulation for Digital Television Terrestrial Broadcasting System. Chinese National Standard, GB 20600-2006, Aug. 2006.
10. J. Kim, S. Lee, and J. Seo, “Synchronization and channel estimation in cyclic postfix based OFDM system,” in Proc. IEEE 63rd Vehicular Technology Conference (VTC’06-Spring), Melbourne, Vic, May 2006, pp. 2028–2032.
11. Synchronization and channel estimation in cyclic postfix based OFDM system,” IEICE Trans. Communication., vol. E90-B, no. 3, pp. 485– 490, Mar. 2007.
12. S. Tang, K. Peng, K. Gong, and Z. Yang, “Channel estimation for cyclic post fixed OFDM,” in Proc. International Conference on Communications, Circuits and Systems (ICCCAS’08), Fujian, China, May 2008, pp. 246–249.
13. M. Huemer, C. Hofbauer, and J. Huber, “Unique word prefix in SC/FDE and OFDM: A comparison,” in Proc. IEEE Global Telecommunications Conference (GLOBECOM’10), Miami, USA, Dec. 2010, pp. 1321– 1326.
14. Onic and M. Huemer, “Direct vs. two-step approach for unique word generation in UW-OFDM,” in Proc. the 15th International OFDM Workshop (InOWo’10), Los Alamitos, CA, Sep. 2010, pp. 145–149.
15. J. Fu, J. Wang, J. Song, C. Pan, and Z. Yang, “A simplified equalization method for dual PN-sequence padding TDS-OFDM systems,” IEEE Trans. Broadcast., vol. 54, no. 4, pp. 825–830, Dec. 2008.
16. L. Bomer and M. Antweiler, “Perfect N-phase sequences and arrays,” IEEE J. Sel. Areas Communication., vol. 10, no. 4, pp. 782–789, May 1992. 17. V. Oppenheim, R. Schafer, and J. Buck, Discrete-Time Signal Processing, 4th ed. NJ, USA: Prentice Hall, 2010.
18. L. Dai, Z. Wang, C. Pan, and S. Chen, “Positioning in Chinese digital television network using TDS-OFDM signals,” in Proc. IEEE International Conference on Communications (ICC’11), Kyoto, Japan, Jun. 2011, pp. 1–5.
19. Frame Structure, Channel Coding and Modulation for a Second Generation Digital Terrestrial Television Broadcasting System (DVB-T2). ETSI Standard, EN 302 755, V1.1.1, Sep. 2009.
20. X. Wang, H. Li, and H. Lin, “A new adaptive OFDM system with pre-coded cyclic prefix for dynamic cognitive radio communications,” IEEE J. Sel. Areas Communication, vol. 29, no. 2, pp. 431–442, Feb. 2011.
21. W. Song and J. Lim, “Channel estimation and signal detection for MIMO-OFDM with time varying channels,” IEEE Communication. Lett., vol. 10, no. 7, pp. 540–542, Jul. 2006.
22. W. Jeon, K. Chang, and Y. Cho, “An equalization technique for orthogonal frequency division multiplexing systems in time variant multipath channels,” IEEE Trans. Communication, vol. 47, no. 1, pp. 27–32, Jan. 1999.
23. P. Schniter, “Low complexity equalization of OFDM in doubly selective channels,” IEEE Trans. Signal Process., vol. 52, no. 4, pp. 100–1011, Apr. 2004.
24. Namboodiri, H. Liu, and P. Spasojevi`c, “Low complexity turbo equalization for mobile OFDM systems with application to DVB-H,” in Proc. IEEE Global Telecommunications Conference (GLOBECOM’10), Miami, USA, Dec. 2010, pp. 1328–1333.
25. X. Wang, Y. Wu, J. Chouinard, and H. Wu, “On the design and performance analysis of multi symbol encapsulated OFDM systems,” IEEE Trans. Veh. Technol., vol. 55, no. 3, pp. 990–1002, May 2006.
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