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Energy awareness is idiopathic task in wireless sensor network. For prolonging lifetime of wireless sensor network, the use of sensors plays a prerequisite role. Saving sensors energy is the main outfit so that network lifetime will improve. So keeping in mind the sensor remaining energy; a new clustering protocol which will work in sleep awake mode is proposed. Along with this mutual exclusion is used in sleep awake mode to fetch cluster head over communication range. In modernistic stint none of the protocol uses mutual exclusion algorithm in sleep awake mode. The proposed protocol Mutual Exclusive Sleep Awake Distributive Clustering (MESADC) chooses a cluster head in such a manner so that sensor lifetime will improve. If sensor lifetime improves then network’s lifetime automatically improve. The performance of MESADC protocol is compared with HEED protocol. Experimental results were obtained with the help of MATLAB. On the groundwork of the comparison between two protocols one finds that the performance of MESADC protocol is prominent in prolonging lifetime of wireless sensor network as compared with HEED protocol.

Sleep Awake, Distributive, Clustering, Sensor, Network

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B. Gupta, S. Rana, "Mutual Exclusive Sleep Awake Distributive Clustering (MESADC): An Energy Efficient Protocol for Prolonging Lifetime of Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.1-7, 2018.

Cloud Computing has been widely adopted by many industries as a platform to support distributed applications. Cloud provides the advantages of reduced operation costs, flexible system configuration and elastic resource provisioning. Even though cloud has been rapidly getting adopted there are various open challenges in areas such as management of virtual resources, security and organizational issues. One of the prominent technologies used by cloud computing is the virtualization. The virtualization technology faces tremendous challenges in supporting real-time applications on cloud as these applications demand real-time performance in open, shared and virtualized computing environments. In this paper we are analyzing the usage of fuzzy logic in improving the performance of time constrained tasks. Our proposed system makes use of fuzzy logic in scheduling of tasks to Virtual machines and in identification of destination host in migrating the overloaded virtual machines which can give better performance than the traditional scheduling algorithms used on cloud systems.

: Cloud Computing, Fuzzy logic, VM management, Performance metrics.

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[2] Ehab NabielAlkhanak, Sai Peck Lee, Saif Ur Rehman Khan,
“Cost- aware challenges for workflow scheduling
approaches in cloud computing environments: Taxonomy and
opportunities”,Future Generation Computer Systems,ElseVier 50
(2015) 3–21
[3] Marisol García-Valls, Tommaso Cucinotta, Chenyang
Lu“Challenges in real-time virtualization and predictable cloud
computing”.
[4] Mohammad A H, Monil and Rashedur M. R,”VM consolidation
approach based on heuristics, fuzzy logic, and migration control”
Journal of Cloud Computing: Advances, Systems and
Applications (2016) 5:8DOI 10.1186/s13677-016-0059-7
[5] Ehab NabielAlkhanak, Sai Peck Lee, Saif Ur Rehman Khan,
“Cost-aware challenges for workflow scheduling approaches in
Cloud computing environments: Taxonomy and
opportunities”,Future Generation Computer Systems,ElseVier 50
(2015) 3–21
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[10] JawwadShamsi,• Muhammad Ali Khojaye • Mohammad Ali Qasmi“Data-Intensive Cloud Computing: Requirements, Expectations,
Challenges, and Solutions “, J Grid Computing (2013) 11:281–310 DOI 10.1007/s10723-013-9255-6
[11] Brendan Jennings Rolf Stadler “ Resource Management in Clouds: Survey and Research Challenges “ J NetwSyst Manage DOI
10.1007/s10922-014-9307-7
[12] Fei Teng, Frédéric Magoulès • Lei Yu • Tianrui Li “ A novel real-time scheduling algorithm and performance analysis of a MapReduce-based cloud “,J Supercomput (2014) 69:739–765 DOI 10.1007/s11227-014-1115-z
[13] Avtar Singh and Kamlesh Dutta “ A novel real-time scheduling
algorithm. and performance analysis of a MapReduce-based cloud” IEEK Transactions on Smart Processing and Computing, vol. 2, no. 6,December 2013.
[14] Tom Springer, Steffen Peter Tony Givargis “Fuzzy Logic Based
Adaptive HierarchicalScheduling for Periodic Real-Time Tasks”,
EWiLi’15, October 8th, 2015, Amsterdam, The Netherlands
[15] Kai Hwang , Xiaoying Bai , Yue Shi , Muyang Li, Wen-Guang

R.A. Kulkarni, S.B. Patil, N. Balaji, "Performance analysis of Fuzzy VM Management techniques for Task scheduling on Cloud systems," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.14-19, 2018.

Sheet metal forming is an important process which causes some changes in the shape of solid metal parts via plastic (permanent) deformation. When deliberating with sheet metal forming process in this scenario, die and punch cost plays a vital role, making the processes costlier in whole production cycle. It is required to estimate the die life because it is repeatedly used in manufacturing process. Approximate calculation of fatigue life of axisymmetric forming dies helps in planning for the production. This is calculated using AI technique Expert system. In present research work, the development of expert system has been done using VB, python and AutoCAD environment. The developed ES is enabling to generate manufacturing drawing of the designed die which requires few input parameters. Based on few input parameters, ES predict the fatigue life of these dies during deep drawing forming operations.

Deep Drawing, Die Design, Fatigue, Expert System(ES), AI

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M.R Bhatt, H Mehta, S.H Buch, "Automatic die design and fatigue life prediction of forming die using AI technique: Expert System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.20-30, 2018.

This paper mainly assesses original image used within a mobile application to understand the differences and comparing them with the standard size. The purpose is to predict success rate of mobile applications prior availability to its customer. To do so, we considered sizes of Android based application which can be improved for the ease of user friendliness. In android package kit (.apk) the buttons are usually (.png) files where the size may differ based on various screen perspective. An application is developed to find and compare the existing button size found in a mobile application to the respective standard in terms of User Experience (UX) factor. Initially, the result in this work will produce a statistic for developers to compare button standard with the original standard and finally produce a generic overview to get a probable success rate with other products in the market. The main finding of this work are, consider an agile based approach during development including revising the developed applications if required before the final release to their user and to overcome the standard of the design issue in terms of standard button measurements with similar products.

User Experience Factor; Button Size; Android Package Kit; PPI; DPI

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Ishtiak Morshed,Huibin Shi , Saujanna Jafreen, Seraj Al Mahmud Mostafa, "Image Based User Experience (UX) Factor Analysis- Mobile Phone Perspective," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.31-36, 2018.

Cryptography is a intelligence to absorb the ambush of the accession by barter abstracts or admonition into advisement form, so the bulletin cannot be recognized. Today, there are abounding algorithms acclimated for the for Image encryption, but the chaotic encryption methods accept a acceptable aggregate of speed and high security. In abounding years, the chaotic based cryptographic apportioned accept been acceptable some new and abstruse means to advance defended Image encryption techniques. The chaos-based encryption schemes are composed of two steps: chaotic confusion and pixel diffusion. We aboriginal accord a explain addition into chaotic Image encryption and again we investigate some important backdrop and behavior of the logistic map. The logistic map, alternate trajectory, or random-like fluctuation, could not be acquired with some best of antecedent condition. Therefore, a blatant logistic map with accretion arrangement babble is introduced.

Chaotic Confusion,Pixel Diffsion,Image Encrytion,Logistic Mapping

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[3] Weihua Z. Ying S. “Encryption Algorithms Using Chaosand CAT Methodology,” International Conference onAnti-Counterfeiting Security and Identification in
Communication (ASID) ,pp. 20 - 23,2008

[4] Mohammad Ali Bani Younes and Aman Jantan, Image EncryptionUsing Block-Based Transformation Algorithm, IAENG International Journal
of Computer Science, 35:1, IJCS_35_1_03,2008

[5 ] C.K. Huang and H.H. Nien, Multi chaotic systems based pixel shuffle for image encryption, Optics Communications 282 2123–2127,2009

[6] Musheer Ahmed, M.shamsher Alam “A new algorithm of encryption and decryption of images using chaotic mapping” International Journal on computer science and engineering,vol.2(1),pp46-50,2009

[7] V. Patidar, N. K. Pareek, and K. K. Sud, “A new substitution- diffusion based image cipher using chaotic standard and logistic maps,” Communications in Nonlinear Science and Numerical Simulation,vol.14,no.7,pp.3056–3075,2009.

[8]Xiang Di, L. X. and Wang P., “Analysis and Improvement of a Chaos Image Encryption Algorithm,”Chaos, Solution and Fractal .Journal on computer science and engineering,vol.2(1), 2009

[9]Jonathan M.Blackedge,Musheer Ahmed ,Omar Farooq“Chaiotic image encryption algorithm based onfrequency domain scrambling” ,School of ElectricalEngineering systems Articles,Dublin Institute ofTechnolog,2010

[10]. C. J., S. G. and S. R., “An Image Encryption Scheme Based on One Time Pads - A Chaotic Approach,” Int.Conf. on Computing , Communication and Networking
Technologies, pp. 1 – 6, July. 2010.

[11].Chenghang Yu, Baojun Zhang and Xiang Ruan,The Chaotic Feature ofTrigonometric Function and Its Use for Image Encryption, EighthInternational Conference on Fuzzy Systems and Knowledge Discovery(FSKD),2011
[12]. G.A.Sathishkumar, Dr.K.Bhoopathy bagan and Dr.N.Sriraam, ImageEncryption Based on Diffusion and Multiple Chaotic Maps, InternationalJournal of Network Security & Its Applications (IJNSA), Vol.3, No.2, March,2011.

[13] Komal D Patel, Sonal Belani,”Image Encryption Using DifferentTechniques”:A Review, International Journal of Emerging Technology andAdvanced Engineering Website: www.ijetae.com (ISSN 2250-2459, Volume1, Issue 1, November 2011

[14] John Justin M, Manimurugan S, A Survey on Various EncryptionTechniques, International Journal of Soft Computing and Engineering (IJSCE)ISSN: 2231-2307, Volume-2, Issue-1, March 2012.

[15] Ruisong, Y. and Haiying ,Z.(2012). An Efficient Chaos-based Image Encryption Scheme Using Affine Modular Maps. I. J. Computer Network and Information Security, 7, pp.41-50.

[16] LEI Li-hong ,BAI Feng-ming,HAN Xue-hui, New Image EncryptionAlgorithm Based on Logistic Map and Hyper-chaos, International Conferenceon Computational and Information Sciences,2013

[17] A Novel Image Encryption Using Arnold Cat proposed by Pan Tian-gong and Li Da-yong College of Measurement-Control Tech & Communications Engineering, International Journal of Security and Its Applications Vol.7, No.5 2013

[18] F.K Tabash, M.F Rafiq, M Izharrudin”Image Encryption Algorithm based on Chaotic Map, International Journal of Computer Applications (0975-8887) Vol 64, number13 2013

[19] Ninth International Conference on Computational Intelligence and Security, A SymmetricImage Encryption Scheme Using Chaotic Baker map and Lorenz System, Chong Fu*, Wen-jingLi, Zhao-yu Meng, Tao Wang, Pei-xuan Li, (2013), (IEEE).

[20] Sukhjeevan Kaur Et Al , Int.J.Computer Technology & Applications, , A Review Of ImageEncryption Schemes Based On The Chaotic Map, Vol 5 (1),144-149, 2014

[21] Sandhya Rani et al. International Journal of Advanced Computer Research (ISSN) (print):2249-7277 ISSN (online): 2277-7970) Volume-4 Number-2 Issue, 2014

[22] Jun-xinChen,Zhi-liangZhu, Li-boZhang, ChongFu, andHaiYu An Efficient Diffusion Scheme for Chaos-Based Digital Image Encryption, Volume 2014, Article ID 427349, 13 pages http://dx.doi.org/10.1155/2014/427349.

[23]. Mayank Mishra, Prashant Mishra, Chinmay Garg “A new Algorithm of encryption and decryption of images using Chaotic Mapping, International Journal of Information and computing Technology ISSN 0974-2239 Vol 4 November 7,2014

[24] Pawan Mishra, Surbhi Prakash “Encryption Of images By Multiple Chaotic Maps, IJAFRC Vol 2, Issues 4, April-.ISSN 2348-4853, 2015

[25] ]LingFeng Liu, Suoxia Miao,”A new image encryption algorithm based on logistic map with varying parameter, SpringerPlus, received 20 September 2015, Accepted 1 March 2016, Published 8 March, 2016.

Shweta Chauhan, Pawan Kumar Mishra, "A Neoteric Fractional Image Encryption Methods Based On Logistic Mapping," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.37-42, 2018.

Neural network computational techniques are a new alternative to conventional numerical modeling. This paper presents modeling using response surface methodology (RSM). Box and Wilson Central Composite Design (CCD) is used for preparing experiment matrix. The independent parameters in the experiment are speed, feed, force and number of tool passes. These variables are controlled during the burnishing process. The response parameter is micro hardness. Experimental samples are prepared using Single Roller Burnishing Tools (Carbide). Vickers micro hardness tester is used to measure micro hardness. A quadratic mathematical model is developed using RSM. An Artificial neural network (ANN) model is developed using three-layer feed-forward back-propagation. The neural network model is trained using measured values of micro hardness. The different algorithms are used to train the model. Best performance is achieved with correlation coefficient 0.9. This study concludes that an artificial neural network is the best alternative to fit the nonlinear data.

Burnishing , RSM, Micro Hardness, ANN

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[13] S. Makridakis and R. L. Winkler, "Averages of forecasts: Some empirical results," Management Science, vol. 29, pp. 987-996, 1983.

Vijay Kurkute, Sandip chavan, "Modeling the Process Parameters of Roller Burnishing using RSM and Prediction of Micro Hardness using Artificial Neural Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.43-50, 2018.

Passive Optical Networks (PONs), designed by Full Service Access Network (FSAN) working group, is the converged infrastructure standardized by ITU and IEEE. PONs support services such as traditional telephony, VoIP and various other multimedia services upto a logical reach of 60km with a split ratio of 1:128. Hence to enhance the reach and performance of PONs, one of the foremost solutions is the use of hybrid optical amplifiers. In this present paper, a model of bidirectional Time Division Multiplexing (TDM) PON using hybrid optical amplifiers configuration (Semiconductor Optical Amplifier (SOA), Raman Amplifier and Erbium Doped Fiber Amplifier (EDFA)) is presented. The performance of the designed system is evaluated for variation of Q Factor with transmission distance using (i) SOA-Raman (ii) SOA-EDFA and (iii) EDFA-EDFA hybrid configuration by carrying out simulations.

PON, FSAN, Optical Line Terminal (OLT), Optical Network Unit (ONU), Optical Distribution Network (ODN), EDFA, TDM, WDM SOA

[1] R. Kaur, Sanjeev Dewra, “A Review on Passive Optical Network”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 3, Issue 4, April 2015.
[2] M. Agarwal, M.G.Wani, “Four Extended-Reach TDM PONs Sharing a Bidirectional Hybrid CWDM Amplifier,” International Journal of Current Trends in Engineering & Research (IJCTER) e-ISSN 2455–1392 Volume 2 Issue 6, June 2016 pp. 321 – 327
[3] S. Khant, A. Patel, “Designing four-Channel High Rate TDM Passive Optical Network with NRZ Scheme for Wired Environment”. International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 22 (2017) pp. 12746-12751
[4] A.B. Dar, F Zahoor, RK Jha, N Tripathi, M Sabraj, “An Analysis of 16 Channel 64 User Hybrid WDM/TDM Topology in the Optiwave Simulation Environment,” International Journal of Computer Sciences and Engineering. VOL-4 Issue 5 pp(31-35). ISSN 2347-2693. 2016
[5] F. Effenberger et al., "An introduction to PON technologies [Topics in Optical Communications]," in IEEE Communications Magazine, vol. 45, no. 3, pp. S17-S25, March 2007. doi: 10.1109/MCOM.2007.344582
[6] P. P. Iannone et al., "Four Extended-Reach TDM PONs Sharing a Bidirectional Hybrid CWDM Amplifier," in Journal of Lightwave Technology, vol. 26, no. 1, pp. 138-143, Jan.1, 2008.
doi: 10.1109/JLT.2007.913072
[7] K. Khairi, Z. A. Manaf, D. Adriyanto, M. S. Salleh, Z. Hamzah and R. Mohamad, "CWDM PON system: Next generation PON for access network," 2009 IEEE 9th Malaysia International Conference on Communications (MICC), Kuala Lumpur, 2009, pp. 765-768. doi: 10.1109/MICC.2009.5431392
[8] B. Zhu and D. Nesset, "GPON reach extension to 60 km with entirely passive fibre plant using Raman amplification," 2009 35th European Conference on Optical Communication, Vienna, 2009, pp. 1-2.
[9] C. Zhang, J. Huang, C. Chen, and K. Qiu, "All-optical virtual private network and ONUs communication in optical OFDM-based PON system," Opt. Express 19, 24816-24821 (2011).
[10] B. Chen, C. Gan, Qi, Y., et al. “A Novel Reliable WDM-PON System”. Journal of Optical Communications, 32(4), pp. 247-250. (2011) doi:10.1515/JOC.2011.050
[11] B. Zhu, D. Au, F. Khan, and Y. Li, "Coexistence of 10G-PON and GPON Reach Extension to 50-km with Entirely Passive Fiber Plant," in 37th European Conference and Exposition on Optical Communications, OSA Technical Digest (CD) (Optical Society of America, 2011), paper Th.13.B.5.
[12] C. H. Yeh, C. W. Chow, H. Y. Chen and J. Y. Sung, "Hybrid OFDM-based multi-band wireless and baseband signal transmission in PON access," in Electronics Letters, vol. 48, no. 7, pp. 390-392, March 29 2012. doi: 10.1049/el.2011.3635
[13] T. Cevik, “A Hybrid OFDM-TDM Architecture with Decentralized Dynamic Bandwidth Allocation for PONs,” The Scientific World Journal, vol. 2013, Article ID 561984, 9 pages, 2013. doi:10.1155/2013/561984
[14] Niazi, Shahab & Zhang, Xiaoguang & Xi, Lixia & Munir, Abid & Afridi, Muhammad & Khan, Dr.Yousaf. (2013). “A Viable Passive Optical Network Design for Ultrahigh Definition TV Distribution.” Advances in Opto-Electronics. 2013. 10.1155/2013/219271.
[15] Chen, H., Gan, C., Gong, Y., et al. “Novel Colorless WDM-PON Featuring Optional Broadcast Service and High Reliability”. Journal of Optical Communications, 35(1), pp. 71-75. (2013). doi:10.1515/joc-2013-0155
[16] A Sharma, D. Dhawan, “Cost Effective Long Reach Hybrid WDM-TDM Passive Optical Network Using Bidirectional EDFA,” International Journal of Scientific & Engineering Research, Volume 4, Issue 5, pp( 2126-2130) May-2013 ISSN 2229-5518
[17] K. Nyachionjeka and W. Makondo, “Effects of Modulation Techniques (Manchester Code, NRZ or RZ) on the Operation of Hybrid WDM/TDM Passive Optical Networks,” International Scholarly Research Notices, vol. 2014, Article ID 984157, 8 pages, 2014. doi:10.1155/2014/984157
[18] Song, Y., Gan, C., Gong, Y., et al. “A Survivable WDM-PON Architecture Using Optical Carrier Suppression Technique”. J. Opt. Commun., 34(4), pp. 357-360. (2013) doi:10.1515/joc-2013-0041
[19] S. Chen, Wei Nai, F. Zhang, S. Wang, D Dong, and Yi Yu, “Mathematical Verification for Transmission Performance of Centralized Lightwave WDM-RoF-PON with Quintuple Services Integrated in Each Wavelength Channel,” Advances in OptoElectronics, vol. 2015, Article ID 183675, 13 pages, 2015. doi:10.1155/2015/183675
[20] M Morant, J Pérez, and R Llorente, “Polarization Division Multiplexing of OFDM Radio-over-Fiber Signals in Passive Optical Networks,” Advances in Optical Technologies, vol. 2014, Article ID 269524, 9 pages, 2014. doi:10.1155/2014/269524
[21] Li, L. & Zhao, D.. “Performance of Phase Modulation in WDM-PON Transmission System”. Journal of Optical Communications, 36(1), pp. 57-65. (2015) doi:10.1515/joc-2014-0050.
[22] Payal, Rajbir Singh, Deepak Sharma, “Performance Comparison of Hybrid Optical Amplifiers with Different Modulation Formats”. International Journal of Electronics Electrical and Computational Systems (IJEECS) ISSN: 2348 117X Vol. 6 Issue 11 , Nov- 2017 pp(315-320 ).
[23] Payal , S. Kumar, D. Sharma, “Performance Analysis of NRZ and RZ Modulation Schemes in Optical Fiber Link Using EDFA.” International Journal of Computer Science and Software Engineering Vol. 7, Issue 8 ,pp(161-168) August 2017 ISSN. 2277-128. doi:10.23956/ijarcsse/V7I8/0102.

D. Sharma, Payal, S. Kumar, "Q Factor Based Performance Evaluation of Bidirectional TDM PON Network Using Hybrid Amplifier Configurations," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.51-60, 2018.

This study was carried out to predict meaningful information from large data set of soil parameters and representation in graphical manner to make its clear understanding This analysis help in determining role of dependent variable and independent variable in the system and their relationships, their dependability for designing any prediction system. A field study is carried out to collect information for assessing soil parameter. Soil parameters analysis is done on 902 soil samples collected from KrushiVighan Kendra, Ghatkhed, Amravati. The values of C, N, P, K, Mg, C, Fe, Cu, Zn, B, Mo, Lime, Saline, CEC, Mn, OM and pH of soil sample collected for the year 2011-2012 and 2012-2013 andPrinciple Component Analysis (PCA) is used to predict these soil parameters as a dependent and independent parameter that have direct/indirect effects on productivity.

complex analysis.soilparameter,Principle Component Analysis,Cu_copper, Fe_iron; ; K_potassium; Mn_manganese; OC_organic content: P_ phosphorus; Zn_zinc.

[1] Kevin Mc-Sweeney, Sabine Grunwald,,Soil Morphology, Classification, and Mapping, University of Wisconsin- Madison , 1999
[2] R. M. Larka, S. R. Kaffkab, D. L. Corwinca, Multi-resolution analysis of data on electrical conductivity of soil using wavelets, Journal of Hydrology Vol. 272, pp 276–290, 2003
[3] Abdi. H. & Williams L. J., Principal component analysis, Wiley Interdisciplinary Reviews Computational Statistics, Vol. 2, pp. 433– 459, 2010.
[4] Ali Salehi1 and G. ZahediAmiri, Study of Physical and Chemical Soil Properties Variations Using Principal Component Analysis Method in the Forest, North of Iran, Caspian J. Env. Sci. Vol. 3 No. 2, pp. 131-137, 2005.
[5] A Xing Zhu,Feng Qi,Amanda Moore,James E Burt,Prediction of soil properties using membership values Geoderma, Vol.158, pp.199–206, 2010.
[6] P. Bhargavi , Dr. S. Jyothi, Soil Classification Using Data Mining Techniques:A Comparative Study, International Journal of Engineering Trends and Technology- July to Aug,Vol.2, Issue 1,pp.55-59,2011.
[7] M. Kumar & A. L. Babel, Available Micronutrient Status and Their Relationship with Soil Properties of Jhunjhunu Tehsil, District Jhunjhunu, Rajasthan, India, Journal of Agricultural Science, Vol 3, No 2, pp 102-118, 2011.
[8] J.O. Ogunwole, E.N. O. Iwuafor, N.M. Eche, J. Diels, Effect of organic and inorganic soil amendments on soil physical and chemical properties in a west africa savanna agroecosystem,Tropical and Subtropical Agroecosystems, Vol. 12, No. 2, pp. 247-255, 2010.
[9] A.Akbarzadeh,R.Taghizadeh,Mehrjardi H. Rahimi Lake & H.Ramezanpour,Application of artificial intelligence in modeling of soil properties,Enviromental Research Journal Vol.3,No.2,pp.19-24,2009.

M.V.Mawale, V.N.Chavan, "Complex analysis of classified of Soil parameters and its relationship identification using PCA," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.61-70, 2018.

Wireless Sensor Network (WSN) consists of small sensor nodes that cooperate with each other to send sensed data to the Base-Station (BS). Several challenges are imposed in WSN with energy consumption being the most important. Clustering improves energy efficiency in WSN by sending data through CHs in one-hop and multi-hop communication. Distributed clustering methods are more efficient as compared to centralized clustering methods in terms of energy efficiency and the choice of the optimal parameter value is important in distributed clustering as it acts as a significant part in preserving energy. Individual parameters like the position of BS, the optimal number of CHs, heterogeneity factor etc. impact the performance in distributed protocols. This work evaluates the performance of well-known distributed protocols by varying the values of different parameters to study their effect on network performance. Simulations are performed and results are analyzed to check the effect of performance parameters.

Wireless Sensor Network (WSN), Clustering, Distributed protocols, Centralized protocols, Stability

[1] S. Kaur and R. N. Mir. "Clustering in Wireless Sensor Networks-A Survey" International Journal of Computer Network and Information Security, Vol.8, No.6, 2016
[2] R.M.B. Hani and A.A. Ijjeh, “A survey on leach based energy aware protocols for wireless sensor networks”, Journal of communication, Vol. 8, 2013.
[3] T. Gao, R. Jin, “A regional centralized clustering routing algorithm for wireless sensor networks”, IEEE, 2008.
[4] K. Padmanabhan, P. Kamalakkannan, “Energy-efficient Dynamic Clustering Protocol for Wireless Sensor Networks”, International Journal of Computer Applications, Vol.38, No.11, 2012.
[5] N. Kamyabpour, D.B. Hoang, “Modeling overall energy consumption in wireless sensor networks”, 11th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT-10, pp. 8–11, 2010.
[6] W.Heinzelman, A.Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocols for Wireless Microsensor Networks”, Proceedings of the 33rd Hawaaian International Conference on Systems Science (HICSS), 2000.
[7] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan,“An application specific protocol architecture for wireless microsensor networks” IEEE Transactions on Wireless Communications, Vol. 4,pp. 660-670, 2002.
[8] L. Qing, Q. Zhu, M. Wang, "Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks" ELSEVIER, Computer Communications, Vol. 29, pp 2230-2237, 2006.
[9] S. Georgios, I. Matta, and A. Bestavros. “SEP: A stable election protocol for clustered heterogeneous wireless sensor networks”. Boston University Computer Science Department, 2004.
[10] S. Faisal, "Z-SEP: Zonal-stable election protocol for wireless sensor networks." arXiv preprint arXiv: 1303.5364, 2013.

Sukhkirandeep Kaur, R.N Mir, "Impact of Various Performance Parameters on Distributed Protocols in Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.65-69, 2018.

Users opinion about different entities forms the huge repository of data over internet. It is highly impossible to accurately monitor and find what actually a user wants to say about an entity from this large amount of data. Data analyst these days concentrates on finely analyzing opinions about particular entity and for this reason the extraction of aspects and its corresponding opinions of that entity are important. This work concentrates on identifying aspects and their corresponding opinion from the provided user opinions which helps to obtain fine grained knowledge about the entity. To obtain aspects and related opinions custom heuristic rules are created by using regular expression on the parts-of-speech tagging. The created rules are provided to Stanford natural language processing (SNLP) classifier and finds association of aspect words and opinion words from the opinion corpus. The classification is done by SNLP classifier and Naïve Bayes (NB) classifier. Identification of aspects and aspect specific opinions are accurately obtained using custom heuristic rules applied over SNLP compared to NB.

Aspects, Opinions, Heuristic Rules, SNLP, NB.

[1] Quan Fang, Changsheng Xu, Jitao Sang, M. Shamim Hossain and Ghulam Muhammad,”Word-of-mouth understanding: entity-centric multimodal aspect-opinion mining in social media,” IEEE transaction on multimedia, volume 17.No. 12, pp. 2281-2296, December 2015.
[2] Masud Karim, Rashedur M. Rahman, “Decision tree and naïve bayes algorithm for classification and generation of actionable knowledge for direct marketing,” Journal of Software Engineering and Applications, 6, pp 196-206, 2013.
[3] F. Chua, W. Cohen, J. Betteridge, E. Lim, “Community-Based Classification of Noun Phrases in Twitter,” In the Proceedings of the 21st international ACM conference of information and knowledge management (CIKM’ 12), pp 1702-1706, 2012.
[4] Richard Socher and et. Al, “Recursive deep models for semantic compositionality over sentiment a Treebank,” In the Proceedings of the conference on empirical methods in natural language processing, EMNLP’13, 2013.
[5] Bo Pang, Lillian Lee, Shivakumar Vaithyanathan, “Thumbs up? Sentiment Classification using Machine Learning Techniques,” In Proceedings of the EMNLP 2002, pp. 79–86, 2002.
[6] Sida Wang and Christopher Manning, “Baselines and bigrams: simple, good sentiment and topic classification,” In Proceedings of the 50th Annual Meeting of the Association for computational Linguistics (ACL’12), volume 2, July 08 – 14, pp 90-94, 2012.
[7] B. Liu and L. Zhang,“A survey of opinion mining and sentiment analysis,” in Mining Text Data. New York, NY, USA: Springer, 2012, pp. 415–463, 2012.
[8] Moghaddam, S., Popowich F., “Opinion polarity identification through adjectives”, CoRR arXiv: 1011.4623 (2010).
[9] S. Moghaddam and M. Ester, “On the design of lda models for aspectbased opinion mining,” In the Proceedings of 21st ACM International Conference on Information and Knowledge Management (CIKM’12), pp. 803–812, 2012.
[10] W. X. Zhao, J. Jiang, H. Yan, and X. Li, “Jointly modeling aspects and opinions with a MaxEnt-LDA hybrid,” in the proceedings of the conference on the Empirical Methods in Natural Language Processing (EMNLP 2010), MIT, Massachusetts, USA, pp. 56–65, 2010.
[11] A. Mukherjee and B. Liu, “Aspect extraction through semi-supervised modeling,” In the Proceedings of Assoc. Comput. Linguistics, 2012, pp. 339–348, 2012.
[12] M. Hu and B. Liu, “Mining and summarizing customer reviews,” In the Proceedings of the Tenth ACM SIGMOD International Conference on Knowledge Discovery and Data Mining (KDD 2004), pp. 168–177, 2004.
[13] Qian Liu, Zhiqiang Gao, Bing Liu3 and Yuanlin Zhang, “Automated Rule Selection for Aspect Extraction in Opinion Mining,” In the Proceedings of Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), pp 1291-1297, 2015.
[14] Y. Yang, C. Chen, M. Qiu, F. s. Bao, “Aspect extraction from product reviews using category hierarchy information,” In the Proceedings of the 15th Conference of the European Chapter of Association for Computational Linguistics: Volume 2, Short Papers, pages 675–680, 2017.
[15] Y. Fang, L. Si, N. Somasundaram, and Z. Yu, “Mining contrastive opinions on political texts using cross-perspective topic model,” In the Proceedings of the Fifth ACM WSDM 2012, pp. 63–72, 2012.
[16] A. McCallum and K. Nigam, “A comparison of event models for naïve bayes text classification,” In the Proceedings of the ICML/AAAI-98 workshop on learning for text categorization, Madison, WI, pp. 41–48, 26–27 July 1998.

T. U. Kadam, P. Kaur, "Aspect-Opinion Identification and Classification Using Custom Heuristic Rules," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.76-80, 2018.