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The organizing and scheduling of the network to conserve the energy of the node to accomplish better communication with the sink is the key challenge in a network. The numbers of techniques are established to cluster the network according to the distance of nodes from the sink. This paper presents a technique which allows the cluster to divide its load equally which helps to minimize the data loss. The cluster head selection takes place in two levels according to probability, threshold and its distance from sink. At level 0 cluster head selected will not take part in level 1 cluster head selection and aggregated data at level 0 is forwarded to level 1 cluster head according to their minimum distance concept. The data from cluster heads at level 1 is divided into two equal part so that to minimize the energy consumption and data loss

Load Divide, Reclustering, Network levels, Stability period

[1] 1Jaswant Singh Raghuwanshi,2Neelesh Gupta,3Neetu Sharma, “ENERGY FFICIENT DATA COMMUNICATION APPROACH IN WIRELESS SENSOR NETWORKS”, International Journal of Advanced Smart Sensor Network Systems (IJASSN), Vol 4, No.3, July 2014.
[2] Ashim Kumar Ghosh1, Anupam Kumar Bairagi2, Dr. M. Abul Kashem3, Md. Rezwan-ul-Islam1, A J M Asraf Uddin1, “ Energy Efficient Zone Division Multihop Hierarchical Clustering Algorithm for Load Balancing in Wireless Sensor Network”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No. 12, December 2011.
[3] I.F. Akyildiz, W. Su*, Y. Sankarasubramaniam, E. Cayirci,” Wireless sensor networks: a survey”, Elsevier, Computer Networks 38 (2002) 393–422.
[4] 1M. Shanmukhi, 2G. Nagasatish, “LOAD BALANCING USING CLUSTERING IN WSN WITH FUZZY LOGIC TECHNIQUES”, International Journal of Pure and Applied Mathematics Volume 119 No. 14 2018, 61-69.
[5] Koulin Yuan1, a, Lin Qiao1, b and Lei Han1, c, “Level and Cluster Based Routing for Wireless Sensor Network”, ISSN: 1662-7482, Vols. 321-324, pp 515-522, 2013.
[6] Veena Anand , Deepika Agrawal, Preety Tirkeyb, Sudhakar Pandey, “An energy efficient approach to extend network life time of wireless sensor networks”, Elsevier, Procedia Computer Science 92 ( 2016 ) 425 – 430.
[7] S. Rani and S.H. Ahmed, Multi-hop Routing in Wireless Sensor Networks, Springer Briefs in Electrical and Computer Engineering, DOI 10.1007/978-981-287-730-7_2.
[8] Shankar Sachdev1, Laxman Yalmar2, Nilesh Gaykhe3, “ Energy Efficient Cluster Based Routing Algorithm in Wireless Sensor Networks”, IJESC ISSN 2321 3361 © 2016.
[9] Shakshi Mehta et al “ Improved Multi-Hop Routing Protocol in Wireless Body Area Networks “, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 7, July 2015.
[10] Li, Hongjuan, Kai Lin, and Keqiu Li. "Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks." Computer Communications 34.4 (2011): 591-597.
[11] Raju, G. T., D. K. Ghosh, T. Satish Kumar, S. Kavyashree, and V. Nagaveni. "Wireless sensor network lifetime optimization." (2011): 244-248.
[12] Dipak Wajgi1 and Dr. Nileshsingh V. Thakur2, “load balancing based approach to improve lifetime of wireless sensor network”, International Journal of Wireless & Mobile Networks (IJWMN) Vol. 4, No. 4, August 2012.
[13] Manel Khelifi, Assia Djabelkhir,” LMEEC: Layered Multi-Hop Energy Efficient Cluster-based Routing Protocol for Wireless Sensor Networks”, 2016.
[14] Dipak Wajgi et al,” Load Balancing Algorithms in Wireless Sensor Network : A Survey”, IRACST – International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501 Vol.2, No4, August 2012.
[15] R . Shantha Selva Kumari1*, A. Chithra2 and M. Balkis Devi3,” Efficient 2-level Energy Heterogeneity Clustering Protocols for Wireless Sensor Network”, Indian Journal of Science and Technology, Vol 9(8), DOI: 10.17485/ijst/2016/v9i8/87961, February 2016.
[16] Amarjeet Kaur1, T P Sharma2,” FTTCP: Fault Tolerant Two-level Clustering Protocol for WSN”, Proc. of Int. Conf. on Advances in Computer Science 2010.
[17] Rahul K Ghotekar et al,” Load Balancing for Achieving the Network Lifetime in WSN-A Survey”, International Journal of Innovative Research in Advanced Engineering (IJIRAE), Volume 1 Issue 4 (May 2014).
[18] Emad Ibbini, Student Member, Kweh Yeah Lun, Mohamed Othman, Zurina Mohd Hanapi,” An Efficient Mechanism Protocol for Wireless Sensor Networks by using Grids”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 9, No. 3, 2018.

Sonia Sethi, Deepak Kumar , "Load Dividing and Reclustering technique to Improve the Reliability of Data In a Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.522-525, 2018.

A disorder in genetic chromosome 21 is popularly known as the Down syndrome (trisomy 21). It results in development and intellectual delays, but if we are able to give the exact care early on, it can make a good difference. Studies show that we can detect the Down syndrome in the early stages of pregnancy by identifying the absence of the fetal nasal bone. The common method followed in this issue is the visual identification of the ‘absence’ using ultra sonogram image of the nasal bone region. However, the visual identification technique is inefficient and difficult to follow. Thus, image processing based visual extraction technique can play a role in this case. In this paper, we have the raw data, which is employed to train the Back Propagation Neural Network (BPNN). The ultrasonogram images can be analyzed using this feed forward trained neural network and the detection can be made with appreciably low error rates. MATLAB is the platform used in this work for training the Artificial Neural Network (ANN).

Down syndrome, Back Propagation Neural Network, Feature extraction, chromosomal abnormalities

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[20] Mosbesh R.Kaloop and Jong Wan Hu, “Optimizing the De-Noise Neural Network Model for GPS Time Series Monitoring of Structures”, Sensors, Vol. 15, No. 9, pp. 24428-24444, 2015.
[21] Kayhan Gulez et.al., “Power Op-Amp Based Active Filter Design with Self Adjustable Gain Control by Neural Networks for EMI Noise Problem”. In: D.S Huang, X.P Zhang, G.B Huang (eds), Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, Vol. 3644. Springer, Berlin, Heidelberg Huang (Eds.): ICIC 2005, Part I, LNCS 3644, pp. 243 – 252, 2005.
[22] P Kaur et.al., “Accurate Prediction of Fetal Images for measuring growth of Fetus using Genetic Algorithm and Back -Propagation Technique of Neural Network”, Int. J. Sci. Res. in Computer Science and Engineering, Vol.5, Issue 3, pp. 30-41, 2017.
[23] V. Davis and S. Devane, “Diagnosis of Brain Hemorrhage Using Artificial Neural Network”, Int. J. Sci. Res. in Network Security and Communication, Vol. 5, Issue 1, pp. 20-23, 2017.
[24] Vijo M Joy and S. Krishnakumar, “ANN Based Load Scheduling Method for Power Management Systems”, IJEECS, Vol. 6, Issue 10, pp. 310-313, 2017.
[25] Vijo M Joy and S. Krishnakumar, “Optimal Design of Power Sheduling using Artificial Neural Network in An Isolated Power System”, International Journal of Pure and Applied Mathematics, Volume 118 No. 8, pp. 289-294, 2018.
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Vincy Devi V. K, Rajesh R, "Revelation of Down Syndrome Using Artificial Neural Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.526-530, 2018.

A video is termed as the sequence of kinetic frames captured/ play backed into some sequences. The rapid development of video capturing systems changed the word from recording the still frames on tapes to the storing frame digitally through charge coupled devices. The Video recording system changes from past analog era to digital era which made editing and manipulation very easy. This paper explained how Matlab is used for making the video from the still images and its performance in the sense of storage and time. Different video generation tools are elaborated and compared with the Matlab generated tools.

Matlab, frames, Video generation, Recording systems, CCD

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Neetish Kumar, Deepa Raj, "Video Generation using Still Images," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.531-534, 2018.

In this paper, a new method is proposed for improvement of speech which is distorted by acoustic noise. Acoustic noise reduction is done through a proposed post processed adapted cascaded median filter based on spectral subtraction technique. This method use two stages of filter, in which background noise is eliminated by first stage cascaded median filter and then output speech is post processed by second stage adaptive filter, to reduce musical and residual noise. Proposed post processing algorithm is compared to conventional single stage cascaded median filter based on subjective listening tests and perception evaluation of speech quality (PESQ) scores. Simulation is done in Matlab-15 and results show that enhanced speech generated by proposed algorithm has better quality than conventional cascaded median filter.

Speech Enhancement, Noise Estimation, Spectral Subtraction, Cascaded Median Filter, Musical Noise

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Dhiraj Nitnaware, "Spectral Subtraction based Speech De-noising using Adapted Cascaded Median Filter," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.535-541, 2018.

Author Identification is one of the application of text mining and is the task of investigating author of the anonymous text document. Application of author Identification includes in digital forensic, plagiarism detection, copyright issues, etc. The numerous amount of work is already done on English language perhaps Author identification of Indian regional languages is limited. This research paper presents Author identification on Indian regional Marathi Language. In this paper proposing a technique for identifying probabilistic authors via linguistic stylometry i.e. the statistical analysis of variations in literary style between one author or genre with another. In total 11 features are extracted with 8 lexical and syntactic features and 3 word N-gram features. Experimentation is performed with 8 features and machine learning algorithms, i.e. k-nearest neighbor, Naïve Bayes and Support Vector Machine. Moreover, result based on word n-gram i.e. unigram, bigram and trigram are also presented. Experimentation result shows better result with word N-gram method.

Author Identification, Text Mining, Machine Learning, Marathi Language, Stylometry

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Sunil D. Kale, Rajesh S. Prasad, "Author Identification on Imbalanced Class Dataset of Indian Literature in Marathi," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.542-547, 2018.

Commercial Off-The-Shelf (COTS) components are being used in increasing number to reduce cost and delivery time of software. A commercial Off-The-Shelf (COTS) component is becoming more and more important since it promotes reuse to higher levels of abstraction. As a consequence, many components are available either being open-source software (OSS) or commercial-off-the shelf (COTS). Component - Based Software Development has evolved as a popular software development technique since the introduction of Microsoft’s Component Object Model (COM) in the early 90s. This paper presents review literature that has been published on empirical research of COTS. We were interested to describe the empirical research on COTS to see that if there are any areas of CBSD that are yet to be touched in the research process. Empirical studies are the proofs of the hypothesis about the industry’s perception of CBSD process.

CBSD, Component object model (COM), COTS

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[7] Tekumalla, B., “Status of Empirical Research in Component Based Software Engineering-A Systematic Literature Review of empirical studies”, 2012.

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Reena, Pradeep kumar Bhatia, "Empirical Studies on COTS Methodology," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.548-559, 2018.

Congestion of roads particularly at different junction points due to vehicular traffic has become a chronic problem all around. Right now in India, a static timer is used to control the timing of the traffic light which results in a lot of problems. This paper introduces a fuzzy logic (FL) based decision support system (DSS) for intelligent traffic control system. The primary focus of the paper is on the algorithm used to reduce the time spent extra on the traffic light junction so as to save the fuel, time and to reduce the possibility of accidents occurring at the traffic light junction. The proposed system uses three input parameters; namely maximum length of vehicles behind traffic light, left green time, and no. of vehicles reaching the traffic light in a short period of time and one output, extension time which is used to control the congestion at the traffic light junction. Through decision support system, the meaning of transferred data is translated into linguistic variables that can be understood by non-experts. Mamdani inference engine is used to deduce from the input parameters.

Fuzzy Logic, Fuzzy Inference Systems (FIS), Decision support system, Traffic control system

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Monika Varshney, Azad Kumar Srivastava, Alok Aggarwal, "A Rule based Fuzzy controlled Decision Support System for Intelligent Traffic Control System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.560-564, 2018.

Business with information technology has bought a revolutionary change in the digital world in terms of the huge amount of data available for processing. Mining techniques are playing a key role in enterprises as it is being used to search vast amounts of data for vital insight and knowledge. The sheer amount of data is posing challenges in terms of representation, analysis etc., which has given emphasis to pictorial representation of the same which for easy visualization and understanding. The mining tools are automated software tools used to achieve business intelligence by finding hidden relations, and predicting future events from vast amounts of data. This uncovered knowledge helps in gaining completive advantages, better customer relationships, etc. To process the data the techniques of process mining is used to discover and analyse the process. Process activity diagrams are often used to model business processes. One of the important modelling artefacts used is the activity diagrams which are further used to model the sequence of actions as part of the process flow. Process mining techniques use Petri nets which are best investigated process modelling language allowing for the modelling of concurrency. This paper emphasizes the comparison of the given process activity model to corresponding petri nets for analysis and verification. The process activity diagram and petri nets are used to demonstrate the applicability of process mining techniques.

Business Processes, Process Mining, Process Activity Diagram, Petri Nets

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Aruna Devi .T, Kumudavalli M.V, Sudhamani, "A Comparative Case Study of Business Process Model with Petri Nets and Process Activity Diagram," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.565-570, 2018.

Image compression in medical image processing is a most significant technique which reduces the burden of storage and transmission time over the network with less degradation in the visual quality and without information loss. Image compression techniques are used to reduce the volume of data for effective storage and transmission. They are classified into lossy compression and lossless compression. In this work, Magnetic Resonance Imaging (MRI) of brain and Computer Tomography (CT) of lung images are used for analyzing compression. The images are compressed using Discrete Wavelet Transform (DWT)-Set Partitioning In Hierarchical Trees (SPIHT) and Integer Wavelet Transform (IWT)-SPIHT with three wavelets such as Haar, Sym4 and Coif1. DWT is used for lossy compression and IWT is used for lossless compression of images. The performance metrics such as Peak signal-to-noise ratio (PSNR), Bit Per Pixel (BPP) and Mean square error (MSE) are measured for lung and brain images. The comparative analyses for SPIHT with DWT and IWT are calculated based on the performance of wavelet. The dataset has been collected from various scan centers.

Compression, SPIHT, DWT, IWT, BPP, PSNR, MSE

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Revathi M., R. Shenbagavalli, "Performance analysis of SPIHT codec on medical images using DWT and IWT," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.571-578, 2018.

Instinctive person verification system still faces various challenges in desirable performance due to dependent and independent noise. Most of the physiological biometric modalities are 2-D images, which may have high probability to get affected from noise. This work proposes a comprehensive analysis of robustness of various unimodal and multimodal biometric systems in clean and noisy conditions. On each stage of biometric system we emphasize, feature extraction, level of fusion and suitable normalization schemes. For feature extraction, methods we have employed subspace, kernel and texture based methods and we have subjected the data on all four levels of fusion schemes- sensor, feature, match score and decision level. The objective of this paper is to analyze the robustness of unimodal systems with distinct modalities and evaluate the robustness of a multimodal system with combinations of two, three and four modalities at different levels. All the experiments were evaluated for both clean and noisy data with virtually generated noises of Gaussian and Salt & Pepper methods, and were applied on all biometrics modalities considered for experimentation. The synthetic multimodal database was prepared from standard database of Face, Palmprint, Finger knuckleprint and Handvein. The obtained results and observations in terms of GAR (Genuine Acceptance Rate) show that palmprint with LPQ features are most effective in unimodal systems. In case of multimodal systems, combination of Face (KICA) and Palmprint (LPQ) are most beneficial. This work also suggests some important guidelines on selection of suitable biometric modality, feature extraction algorithms and fusion scheme.

Robustness, Noise, Subspace, Multimodal, Biometric

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Supreetha Gowda H D, G Hemantha Kumar, Mohammad Imran, "Robust Analysis of Multimodal Biometric Verification System Under Various Spatial Noise Conditions," International Journal of Computer Sciences and Engineering, Vol.6, Issue.11, pp.579-590, 2018.