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Sorting is a process of arranging the elements in specific order. Computer systems use many sorting algorithms to arrange the numbers in ascending or descending order and ‘quicksort’ is one of the better performing algorithms. This algorithm follows divide-and-conquer approach by compiling the large data set to partition the list of elements and then exchange the numbers after scanning the list. In today’s ever expanding world of technology, users find themselves in a situation where they have so many choices in selecting the best compilers. However, most of the time, technically the users are not able to identifying which translator is the best one for the completion of a particular assignment. The main aim of this paper is to find out the best compiler for ‘quick sort’ to reduce the execution time and automation through analyzing the performance of different compilers.

Borland, Digital Mars, Tiny C, Bloodshed, CC386

[1] Karp and H. T. Kung, “GPSR: greedy perimeter stateless routing for wireless networks”, in Mobile Computing and Networking, 2000, pp. 243–254.
[2] https://en.wikipedia.org/wiki/List_of_compilers
[3] https://en.wikipedia.org/wiki/Tiny_C_Compiler
[4] http://ladsoft.tripod.com/cc386_compiler.html

Mehzabeen Kaur, Surender Jangra, "Execution Time of Quick Sort on Different C Compilers: A Benchmark," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.786-788, 2018.

Incredible measures of exertion have gone into investigate on multicast switch texture outline and calculations. Switch measure is one of the primary factor which impacts the execution of throughput and deferral. In this work, execution of switch has been investigated by applying the progressed multicast planning calculation OQSMS (Optimal Queue Selection Based Multicast Scheduling Algorithm), due date based round-robin booking calculation MDDR(Multicast Due Date Round Robin) and double round-robin based multicast planning calculation MDRR(Multicast Dual Round Robin). Recreation results demonstrate that OQSMS accomplishes preferred exchanging execution over different calculations under the allowable movement conditions on the grounds that if the switch measure builds, OQSMS will gauge ideal line determination in view of more line mixes so it accomplishes greatest conceivable throughput.

Multicast, Throughout, MDRR, MDDR, OQSMS

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[12] K. Navaz “OQSMS: Optimal Queue Selection Based Multicast Scheduling Algorithm for Input-Queued Switches” on Australian Journal of Basic and Applied Sciences, 9(27) August 2015, Pages: 373-378.
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Shaik Jumlesha, K. Navaz, S. Athinarayanan, "Throughput Analysis of Multicast Scheduling Algorithms by Varying NxN IQ Switch," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.789-792, 2018.

Sentiment analysis is an examination philosophy for estimating the behavior of users through the investigation of past Opinion information. Behavioral financial aspects and quantitative examination utilize a large number of similar instruments of specialized study, which being a part of dynamic management. The capability of both dedicated and principal investigation is examined by the useful opinion mining which expresses that securities exchange logs are feedback. Sentiment analysis entirely relies on user enthusiasm and also user relationship about the feedback. Opinion mining is a way to deal with services connection with present and potential users. It utilizes information investigation about user history with a gathering to enhance services relationships with users, mainly concentrating on user maintenance and at last driving deals development. The issue of user premium expectation has been examined in the other circumstance, and there are a few strategies has been explored before. The effect of sentiment analysis in opinion mining could be adjusted for different issues like user seek, item inspiration, etc. To enhance the execution of user logs in opinion mining, a novel Feedback Rate based User Order Predication (FR-UOP) model for sentiment analysis scheme has been examined in this paper. The FR-UOP calculation first preprocesses the user log information to part them into the time-space. At that point, the strategy differentiates the rundown of user curiosity of the feedback rate in particular concern of the user and enhances the execution of user relationship in data mining.

Sentiment Analysis, opinion model, user log, feedback rate, data mining

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[10]. Tempelaar, Rienties, Giesbers, “In the search for the most informative data for feedback generation: Learning analytics in a data-rich context”. Computers in Human Behavior, 47, 157–167, 2015.
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A. Suriya, M. Prabakaran, "Feedback Rate Based User Order Predication (FR-UOP) Model for Sentiment Analysis in Data Mining," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.793-797, 2018.

The heavy metals in soil samples of Guntur auto nagar, Andhra Prdesh were analyzed using standard methodologies of soil analysis WHO and BIS, three sampling stations are studied in six months duration from February to July in the study area. The following metals were detected, Iron (Fe), Zinc (Zn), Chromium (Cr), Copper (Cu), Cadmium (Cd), Lead (Pb) and Nickel (Ni). Their minimum, maximum, average values (mg/kg-1) and standard deviation of three sampling stations were observed and the maximum values are recorded as follow Fe-131.05 mg/kg-1, Cr-1.91 mg/kg-1, Zn-98.37 mg/kg-1, Cu-69.9 mg/kg-1, Cd-9.31 mg/kg-1, Ni-14.32 mg/kg-1, according to the standard values in three sampling stations of soil samples exceeded due to improper sanitation and lack of rainfall the heavy metals are stored in soils.

Analyses, Heavy Metals, soil, Auto nagar, Industrial Area

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Jyothi. M, G. Sudhakar, P. Brahmajirao, "Heavy Metals in Soil Samples of Guntur Auto Nagar, Andhra Pradesh," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.798-802, 2018.

Procedural Content Generation (PCG) : A significant research area in the domain of digital games, which provides techniques to automatically generate game content such as levels, narratives, landscape, game rules and mechanics, etc. without or with least human effort. In these days, video games are usually backed by web services in order to fetch game content directly from game servers rather than storing everything at client side, for better controllability over the game content. Semantic Web technologies play an important role in World Wide Web (WWW) with the objectives to ¬create and maintain structured Web of Data to make it more machine understandable. Potentially, Semantic Web may contribute to PCG by enhancing its capabilities in terms of computational creativity, better algorithmic efficiency, scalability, interoperability etc. In this paper, first, the role of PCG and Semantic Web in games has been explored. Second, a Semantic Based PCG Framework has been proposed, which combines strength of both the fields and exploit the content of existing knowledge repositories such as DBPedia, WordNet, Freebase, etc. to generate interesting puzzles. Third, proposed framework has been supported by taking the case study of a popular word game Hangman. Finally, emphasis on exploring various concerns is made towards the role of Semantic Web in procedural content generation in games.

Semantic Web, Procedural Content Generation in Games, Quiz Games, Educational Games, DBPedia

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V. K. Vashistha, S.K. Malik, "Procedural Content Generation in Games towards Semantic Web," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.803-812, 2018.

In all the fields of steganography such as image, text, audio, video there are many techniques used totransfer the secret messages without known to other person. Using the Steganography technique to hide the data or message in an image,LSB and DWT are two easy techniques which are usefull and implemented easily to improve robustness and performance of algorithms. LSB method used to transfer the large data and replace some information in pixel with information from the data in image. Overall use of LSB doesn’t affect the representation of image. In this technique, LSB method will be used to transfer the large data and replace some information in pixel with information from the data in an image.DWT method is used to embed converted data into cover medium to conceal its presence. For the security, we will use the technique DWT which is used with the low frequency (used for narrow bandwidths) and high frequencies (for wider bandwidths) and for the flexibility.

Steganography, Least-significant-bit (LSB), Discrete Wavelet Transform(DWT)

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[3]L.Baby Victoria, “A Study on Spatil Domain and Transform Domain Steganography Techniques used in Image Hiding,” International Journal of Innovative Technology and Creative Engineering, Vol.5 No.5 May 2015.
[4]Sukhjinder Singh, KulbhushanSingla, Dr. Rahul Malhohtra, “A Robust Image Steganography Technique using Quantized Range Table and Local Area Pixel Value Differencing,” International Journal of Advanced Research in Electronic and Communication Engineering, Vol. 5, Issue 2, February 2016.
[5]S.Thenmozhi, M.Chandrasekaran, “Multilayered, High Capacity, Distortionless Image Steganogaphy using ANN,” South Asian Journal and Technology, Vol.2,No.21 pp.63- 73, 2016.
[6]Mamta Jain and Saroj Kumar Lenka, “A Review on Data Leakage Prevention using Image Steganography,” Mamta Jain et al./ International Journal of Computer Science Engineering, Vol.5, No.002, Mar 2016.
[7]S.Krishnan, M.S. Abdullah, “Enhanced Security Audio Steganography by Using Higher Least Significant Bit,” Journal of Advanced Research in Computing and Applications ISSN(ONLINE), Vol.2,No.1.pp.39-54, 2016.
[8]Ms.Kajal Prakash kamble, Ms SwapnaliVasantKhabale, Mr. AnkushShahu Morale, “An Infallible Method to Transfer Confidential Data using Delta Steganography,”International Research Journal of Engineering and Technology, Vol.03, Issue:02, Feb-2016.
[9]Komal Kapoor, “Digital Image Steganography based Security Model using Wavelet for Internet Voting Environment,” International Journal of Advanced Research in Electronics and Communication Engineering, Volume 5, Issue 2, February 2016.
[10] Ashley S.Kelsey, CajetanM.Akujuobi, “ A Discrete Wavelet Transform Approach for Enhanced Security in Image Steganography,” International Journal of Cyber-Security and Digital Forensics(IJCSDF) 5(1):10-20,The Society of Digital Information and Wireless Communications, 2016 (ISSN:2305-0012).
[11]DeepakGarg, Gourav Sharma, “Applications of Steganography in Information Hiding,” International Journal of Advanced Research in Education Technology, Vol.3, Issue 1, Jan-Mar. 2016.
[12]MsVedantiM.Khandare, Dr. SiddharthA.Ladhake,Mr.U.S.Ghate, “An Approach of ECG Steganography to Secure the Patient’s Confidential Information,” International Research Journal of Engineering and Technology, Volume: 03, Issue: 03| Mar-2016.
[13]Sumanth C, Dr. M B Meenavathi, “Audio-Video Steganography using Face Recognition Technique for Authentication,” International Journal of Advanced Research in Electronics and Communication Engineering, Volume 5, Issue 5, May 2016.
[14] Md. Mizanur Rahman, Pronab Kumar Mondal, Indrani Mandal, Habiba Sultana, “Secure RGB Image Steganography Based on Triple-A Algorithm and Pixel Intensisty,” International Journal of Scientific & Engineering Research, Volume 7, Issue 3, March- 2016.
[15]Seema S. Girare, Malvika U. Saraf, “Literature Review on Different Watermarking & Steganography Technique,” International Research Journal of Engineering and Technology, Volume: 03, Issue: 04| Apr-2016.
[16] Don Caeiro and Sanjana S, “Detection of Steganography Using Metadata in JPEG Files,” The International Journal of FORENSIC COMPUTER SCIENCE( www.IJoFCS.org),2015.
[17]SaurabhPaliwal, “ A Surve& Applications of Various Image Steganography Techniques,” International Journal of Scientific & Engineering Research, Volume 7, Issue 1, January-2016.
[18]RiyadhBassilAbduljabbar, “ Steganography System using Slantlet Transform,” Journal of Information, Communication, and Intelligence Systems(JICIS), Volume 2, Issue 1, February2016.
[19]Hamad A. Al- Korbi, Ali Al- Ataby, Majid A.Al-Taee and Waleed Al-Nuaimy, “ Highly Efficient Image Steganography Using Haar DWT for Hiding Miscellaneous Data,” Jordanian Journal of Computers and Information Technology (JJCIT), Vol.2,No. 1,April 2016.
[20] Mamta Jain and Saroj Kumar Lenka, “ A Review of Digital Image Steganography Using LSB and LSB Array,” International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 3(2016).
[21] Mr. Mohit “An Enhanced Least Significant Bit Steganography Technique,” International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) Volume 5, Issue 6, June 2016.
[22]G. Raj Kumar, M. MaruthiPrasada Reddy, T. LalithKumar,“An Implementation of LSB Steganography Using DWT Technique,” International Journal of Engineering Research and General Science Volume 2, Issue 6, October-November,2014.
[23]Juned Ahmed Mazumder, KattamanchiHemachandran, “Color Image Steganography Using Discrete Wavelet Transformation and Optimized Message Distribution Method,” International Journal of Computer Sciences and Engineering, Volume-2, Issue-7, July 2014.
[24]Vanitha T, Anjalin D Souza, Rashmi B, SweetaDSouza, “ A Review on Steganography- Least Significant Bit Algorithm and Discrete Wavelet Transform Algorithm,” International Journal of Innovative Research in Computer and Communication Engineering Vol.2, Special Issue 5, October 2014.
[25]M Abhilash Reddy, P. Sanjeeva Reddy, GS Naveen Kumar, “DWT AND LSB ALGORITHM BASED IMAGE HIDING IN A VIDEO,” International Journal of Engineering Science & Advanced Technology Volume-3, Issue-4, Aug-Sep 2013.
[26]KalpanaShete, MangalPatil, J.S. Morbale “FPGA Implementation of Image Steganography Using LSB & DWT,” International Journal of Computer Science and Network, Volume 4, Issue 6, December 2015.
[27] Kalpana Sanjay Shete, MangalPatil and J.S. Chitoda, “Least Significant Bit and Discrete Wavelet Transform Algorithm Realization for Image Steganography Employing FPGA,” I. J. Image, Graphics and Signal Processing Vol.6, June 2016.
[28]StutiGoel, ArunRana&Manpreet Kaur, “ A Review of Comparison Techniques of Image Steganography,” Global Journal of Computer Science & Technology Graphics & VisionVolume-13, Issue-4 Version 1.0, 2013.
[29]Manisha and DeepkiranMunjal, “Dual Steganography Technique Using Status LSB and DWT Algorithms,” International Journal of Innovative Research in Computer and Communication Engineering, Volume 4, Issue 6, June 2016.

Neha, Mr Mohit, "A Review on “Image Steganography with LSB & DWT Techniques”," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.813-818, 2018.

Enterprise Resource Planning (ERP) system is an integral component of IT infrastructure in many organizations. They are the vital asset to any organization in carrying out various operational tasks with greater reliability and efficiency. Most of the Indian SMEs have adopted the traditional ERP systems and have incurred heavy cost while implementing these systems. Cloud computing has changed the era of doing the business in the global market. SMEs will not have to invest more for the implementation of cloud ERP they can utilize the resources as a service and pay as per their usage. Cloud ERP is nothing more than ERP software that had been implemented on cloud. This paper present to review a deeper understanding of Cloud ERP , emerging technologies such as Cloud Computing , Software as Service (SaaS), to frame the multi-tenant assured framework which are more relevant and beneficial for SMEs.

ERP, Component, Cloud Computing, Cloud ERP, Multi-tenancy , Saas ERP adoption

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Sunaina Mehta, Ashish Oberoi, Sarvjit Singh Bhatia, "A Cloud based Assurance Framework for Implementation of ERP in SMEs: A Literature Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.819-829, 2018.

The diagnostic formulations in patients rest on a tripod consisting of clinical history, physical examination and laboratory investigations. In most of the cases diagnoses are mainly done based on laboratory medicine. Current manual techniques lack precision and reproducibility and hence automated methods where an image of the smear is captured and analyzed offers more precision and accuracy. Accurate analysis of the cells including the red cells in the blood smear images is vital for the diagnosis of various diseases and pathological conditions in patients. This calls for accurate detection and segmentation of the Red Blood Cells (RBCs) prior to analysis. Normal RBCs are biconcave in shape with a central pale area and any deviation in most of the RBCs in their size and ratio of the total surface area of the cell to the central pale area from the normal represents an abnormality. If the size and volume of an RBC is less than a normal cell it is indicative of a pathological process called as microcytosis and on the other hand macrocytosis is the condition where the cell is enlarged. This paper proposes an automated method of analyzing the RBCs in blood smear images for morphological abnormalities, which is an extension of an earlier work focusing on segmentation of all the cells in the blood smear images using Watershed Transform.

Segmentation, Watershed Algorithm, Morphological Operations, Mean Corpuscular Volume

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[10] F. Sheeba, T. Robinson, J.J. Mammen, R. Nithish, S. Karthick, “Detection Of Overlapping Tuberculosis Bacilli in Sputum Smear Images”, in the IFMBE Proceedings of the 7th WACBE World Congress on Bioengineering, pp 54-56, 2015.
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[14] A.P Janwale, “Plant Leaves Image Segmentation Techniques: A Review”, International Journal of Computer Sciences and Engineering 5(5), pp. 147-150, 2017
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[16] S. Kulasekaran; F. Sheeba; J.J. Mammen; B. Saivigneshu; S. Mohankumar, “Morphology Based Detection of Abnormal Red Blood Cells in Peripheral Blood Smear Images”, in the IFMBE Proceedings of the 7th WACBE World Congress on Bioengineering pp 57-60, 2015.
[17] D. N. Patil, U. P. Khot, “Image Processing Based Abnormal Blood Cells Detection”, International Journal of Technical Research and Applications Special Issue 31, pp. 37-43, 2015.
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[19] S. Bala, A. Doegar , “Automatic Detection of Sickle cell in Red Blood cell using Watershed Segmentation” International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, Issue 6, June 2015.

F. Sheeba, T. Robinson, J.J. Mammen, J.M.S. Philips, T. Sathyaraj, S.V. Prabhu, "Analysis of Abnormality based on Size in Red Blood Cells in Peripheral Blood Smear Images," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.830-834, 2018.

In computer science, textual similarity used for detecting the similarity between words, terms, sentences, paragraph, and document. In natural language processing, sentence similarity performs the tasks such as document summarization, word sense disambiguation, short answer grading , and information retrieval. The lexical overlapping approach evaluates the similarity between the sentence and finds whether a sentence pair is semantically equivalent or not. Existing methods are used for checking the similarity of long text documents. These methods process sentences in high-dimensional space and are not much efficient, requires human input and also not adaptable to some application domains. Semantic textual similarity methods improved in two areas -(a) in the semantic relation between the words and (b) in semantic resources to reduce the dimension. The proposed architecture uses the two methods for directly computing the similarity between very short texts of the sentence and long text sentences. The Weighted Overlap Approach based proposed method provides a nonparametric similarity by comparing the similarity of the rankings for an intersection of the senses in both the sentences. The Cosine similarity based proposed method identify all distinct words from the sentences. In the proposed work the similarity detection methods are focused to check the synonyms similarity between the sentences.

Natural Language Processing, Semantic Textual Similarity, Word Similarity, Sentence similarity, Text Similarity

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S.L. Patil, K.P. Adhiya, "Textual Similarity Detection from Sentence," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.835-839, 2018.

The researchers have already worked with many supervised and unsupervised methods for the purpose of credit card fraud detection. The supervised models have been found more efficient for the purpose of credit card fraud detection. The major goal of the credit card fraud detection research is to improve the accuracy while decreasing the elapsed time. The proposed credit card fraud detection models purposes the use of feature extraction and selection of the credit card data with linear regression algorithm for the credit card fraud detection. The feature engineering and analysis would be performed over the given trans-actional data and then final classification of the anomalies or outliers is done using linear regression classifier. The proposed model has been tested under the various experiments from the various groups of test cases. The test case groups have been ob-tained after applying the various levels of the feature elimination and feature selection over the collection of credit card transac-tion data. The proposed credit card fraud classification model is based upon two different models, which includes the Naïve Bayes and Support Vector Regression. The main aim of the research is to achieve the higher credit card fraud recognition accuracy, with the minimum classification complexity.

Credit card fraud detection, Early Fraud Detection, Regressive analysis, Linear regression models

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Nikita Sawhney, B. Kaur, H. Kaur, "Probabilistic Support Vector Regression Classification Model for Credit Card Fraud Detection," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.840-843, 2018.