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Cancer is the world’s most proliferating and dangerous disease. Due to lack of proper knowledge of cancer, it is spreading among the people and a large number of people are dying from cancers such as lung, blood, breast, palm, liver, stomach, colorectal, prostate, bladder, pancreatic cancer etc. There were an estimated 14.1 million cancer cases around the world in 2012 and out of these 7.4 million and 6.7 million cases were in men and women respectively [21,22,23]. Cancer cells continue to increase new abnormal cells, many cellular changes have been reported to be associated with malignant process till date. For cancer detection a versatile method such as finite difference time domain is very frequently used in this era. In this paper we propose a two-dimensional finite difference time domain (FDTD) numerical simulation technique using Scilab, for early detection of cancer tissue, early phase can provide more treatment options, less invasive surgery and increases the survival rate.

Finite Difference Time domain (FDTD), Cancer detection, Ultra wide Band, Scilab

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pp. 143-157,2008
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pp. 6346-6349,2011
[14] Vipul Sharma, S.S. Pattnaik, “Microwaves, Metamatetrial and Skin Cancer Detection” LAP LAMBERT Academic Publishing Germany, Jan 2014
[15] Shelendra Pal, Vipul Sharma, Raj Kumar, Shyam Kamal, “Using Finite Difference Time Domain for Cancer Detection: A Selective Review” International Journal of Sensors, Wireless Communications and control Volume 6 (2), ISSN: 2210-3287 (Online) ISSN: 2210-3279 (Print), 2016
[16] Shelendra Pal, Vipul Sharma, Raj Kumar “Cancer Detection in Human Beings Based Artificial Neural Network” National Conference on Science & Technology for Human Development" organized by ISCA: Haridwar, 2016
[17] Sharmistha Sharma, Subhadeep Bhattacharjee, Aniruddha Bhattacharya “Operation cost minimization of a micro Grid using Quasi-Opppsitional Swine Influenza Model Based Optimization with Quarantine” Ain Shams Eng J , 2015
[18] Seyyed M. Hesabgar, Ali Sadeghi-Naini, Gregory Czarnota, Abbas Samani “Dielectric properties of normal and malignant breast tissue in xenagraft mice at low frequencyies (100Hz-1 MHz)”,Elsevier Ltd Vol-105, pp.56-65, 2017
[19] Rathod, V., Shaikh, U., Yadav, O. P., Rathore, A. “Swine Influenza Model Based Optimization using seasonal flu shots (SIMBO-SS)” Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), 4th International Conference Noida , 2015
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[23] Rebecca Siegel, Jiemin Ma, Zhaohui Zou, Ahmedin Jemal. Cancer Statistics, 2014. CA: A Cancer Journal for Clinicians, DOI: 10.3322/caac.21208, 2014

Shelendra Pal, Rajkumar, Vipul Sharma, "Two Dimensional Finite Difference Time Domain Tool for Cancer Detection on Scilab," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.844-850, 2018.

Software engineers waste a lot of time during software testing. The goal of testing is to determine error in a system. Test case generation is the procedure of developing test suites for identifying system errors. A test set is a collection of applicable test cases bunched together. It is also seen in the industry with large amount of funds being used during the software process. During software testing, we have used test case as input and has determined the final output. So, our first objective is to choose the right test case for the software testing process. In order to give correct output, it is very difficult to select test cases. So, the test case generation is an NP (non-deterministic polynomial-time hardness) problem. There are numbers of algorithms available for software testing but to choose the best algorithm as per the requirement is mostly needed. In this research work, to solve the NP hard problem of software testing, we have used Fuzzy logic classifier. Fuzzy logic is a rule based algorithm that works on if - else statement. The test input is applied as an input to the fuzzy membership function. The classifier works on the defined rules and provides us a rule based output. Fuzzy classifier helps to find error in less time on the basis of rule set. To determine the performance of the designed test case generation system the performance parameters such as accuracy, FAR (False acceptance rate) and FRR (False Rejection rate) are evaluated in MATLAB.

Software engineering, software testing, test case prioritization, fuzzy logic, Accuracy

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[10] De S Campos Junior, H., Araújo, M. A. P., David, J. M. N., Braga, R., Campos, F., & Ströele, V. (2017, September). Test case prioritization: a systematic review and mapping of the literature. In Proceedings of the 31st Brazilian Symposium on Software Engineering (pp. 34-43). ACM.
[11] Dalal, S., & Hooda, S. (2017, September). A Novel Technique for Testing an Aspect Oriented Software System using Genetic and Fuzzy Clustering Algorithm. In Computer and Applications (ICCA), 2017 International Conference on (pp. 90-96). IEEE.
[12] Rhmann, W., & Saxena, V. (2017). Fuzzy Expert System Based Test Cases Prioritization from UML State Machine Diagram using Risk Information. IJ Mathematical Sciences and Computing, 2017(1), 17-27.
[13] Joseph, A. K., & Radhamani, G. (2017). Hybrid Test Case Optimization Approach Using Genetic Algorithm with Adaptive Neuro Fuzzy Inference System for Regression Testing. Journal of Testing and Evaluation, 45(6), 2283-2293.

Taranum Thakur, Narinder Rana, "Fuzzy Expert System Based Test Cases Prioritization," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.851-857, 2018.

After 2000 revolutionary changes have been seen in Dehradun city that time Dehradun formed the capital of Uttarakhand state. A sizable amount of immigration from rural areas and nearby adjoining states such as Uttar Pradesh, Haryana, Punjab, and Delhi has also resulted in the gradual expansion of Dehradun city. Earlier Dehradun was famous for its Litchi fruit & good quality rice grains. Almost up to the year 1990 exporting litchi and rice to all the parts of India and now the condition of the city is that even the people of Dehradun not get sufficient supply. It is due to decreasing agriculture land, the cultivation is affected. The aim of this paper is to recognize changes in built-up areas and open areas of Dehradun city using the geographical information system to analyze land use changes of the period 1998, 2008 & 2017. To achieve the objectives three digital images The satellite image downloaded from earth explorer USGS of the year 1998, 2008 & 2017 has been taken to calculate the areas of three main categories they are built-up, vegetation & non-built-up area. The areas changes in three years gap 1998-2008, 2008-2017 and 1998-2017 have been calculated. The downloaded images converted into shape files of the study area as per Dehradun municipal map 2011 using Arc GIS10.3 and last ERDAS for classification of buildup and open areas. The researcher found a lot of changes in these categories. One category decreases with the time where other increases. There is a lot of new development occurred during the two later periods i.e. 1998-2008 & 2008-2017. In the period 1998-2008 vegetation area decreases 15.31% from overall vegetation where built-up 8.89% increases and 6.41% non-built-up area increases. (Refer to Table 5.2 graph 5.5). In the period 1998-2017 the 38.36% vegetation decreases. Where built area increases prominently 32.45% from the year 1998 and 5.91 % increase in non-built-up area. The result of the study shows the open area is decreased and built up area is increased in the last 20 years

Revolutionary changes, immigration, expansion, earth explorer, development

[1]. Yuji Murayama, Rajesh Bahadur Thapa , “Spatial Analysis and Modeling in Geographical Transformation Process.” nature, chapter 1 of book GIS based Application of Springer publications, india
[2]. Gupta, R. "The Pattern of Urban Land-use Changes: A Case Study of the Indian Cities", Environment and Urbanization Asia, India
[3]. Yeshika Budhwar , Uttarakhand glacial rivers converting into seasonal rivers , article in Times of India, Uttarakhand news paper article dated Feb 23, 2018.
http://timesofindia.indiatimes.com/articleshow/63048992.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst
[4]. Vinod Pundir , Tributary Suswa carries Doon`s waste to Ganga, Oct 12, 2015.
[5]. http://www.tribuneindia.com/news/uttarakhand/community/tributary-suswa-carries-doon-s-waste-to-ganga/144769.html
[6]. Varun pawal and mansi Puri , Landuse/Land cover chnge study of district dehradun, Uttarakhand using Remote Sensing and GIS technologies. Cloud publication dated 22/07/2018.

Bindu Agarwal, Satish Kulkarni, Aanchal Sharma, Simran Agarwal, "Land Use Land Changes in Land Area of Dehradun City, Uttarakhand, India: Analysis Using Digital Maps and Remote Sensing Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.858-866, 2018.

Multi-hop wireless networks and Routing management, it has is a vital and challenging resource allocation technique in Scheduling process. A distributed low-complexity scheduling algorithm develops into more challenging tasks, even if taking into account a physical interference model. At previous years a number of scheduling algorithms were presented, but pre-existing scheduling algorithm does not solve the drawbacks to implement in multi hop networks to overcome these issues, proposed a new scheduling approach Ant Colony Optimization Max-Weight Scheduling (ACO-MWS) for scheduling and routing in multi-hop wireless networks. The combination of proposed approaches such as ACO Algorithm and Max-Weight Scheduling that overcome the pre-existing scheduling problems and it accomplish maximum throughput at the distributed low complexity. The performance evolution of ACO, Max-Weight, and ACOMWS are presented in this paper.

Wireless Ad Hoc Network, Heavy Tail, Ant Colony Optimization, Max-Weight Scheduling, Throughput, Routing

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B. Sindhupiriyaa, D. Maruthanayagam, "Analysis of Scheduling Performance and Stability in Wireless Ad-Hoc Networks Using ACO, MWS and Novel ACO-MWS," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.867-876, 2018.

Recent work in computer vision and image processing has increasingly focused on developing systems for monitoring humans and understanding their look, activities, and behaviour providing advanced interfaces for interacting with human beings, and developing sensible models of humans for various purposes. Moving target detection is a fundamental problem in computer vision, due to the features of moving target, such as strong speed degeneration, uncertain route, dynamic background, it becomes hard to detect moving object. The study on moving object in literature do not guarantee high precision and recall, so there is chance of improvement in detecting moving object in dynamic background with greater precision and recall.

Moving Target, Dynamic Background, Speed Degeneration

[1]. Yanzhu Zhang, Xiaoyan Wang, Biao Qum, Three-Frame Difference Algorithm Research Based on Mathematical Morphology, SciVerse Science Direct, Elsevier Proceeding, 2011.
[2]. Huijuan Zhang, Hanmei Zhang, A Moving Target Detection Algorithm Based on Dynamic Scenes, The 8th International Conference on Computer Science & Education (ICCSE 2013) April 26-28, 2013. Colombo, Sri Lanka.
[3]. D Stalin Alex, Dr. Amitabh Wahi, BSFD: Background Subtraction Frame Difference Algorithm for Moving Object Detection and Extraction, Journal of Theoretical and Applied Information Technology, 28th February 2014. Vol. 60 No.3.
[4]. Jun Zhang, Shukui Xu, Kuihua Huang, and Tingjin Luo, Accurate Moving Target Detection Based on Background Subtraction and SUSAN, International Journal of Computer and Electrical Engineering, Vol. 4, No. 4, August 2012.
[5]. Yangquan Yu, Chunguang Zhou, Lan Huang, Zhezhou Yu, A Moving Target Detection Algorithm Based on the Dynamic Background, IEEE Conference, 2009
[6]. Nishu Singla, Motion Detection Based on Frame Difference Method, International Journal of Information & Computation Technology, ISSN 0974-2239 Volume 4, Number 15 (2014).
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[9]. Jiajia Guo, Junping Wang, Ruixue Bai, Yao Zhang, Yong Li, A New Moving Object Detection Method Based on Frame-difference and Background Subtraction, ICAMMT 2017.
[10]. Yachi Zhang, Guolin Li, Xiang Xie,Zhihua Wang, A New Algorithm for Fast and Accurate Moving Object Detection Based on Motion Segmentation by Clustering, 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) Nagoya University, Nagoya, Japan, May 8-12, 2017.

Kuldeep B. Vayadande, Nikhil D. Karande, Surendra Yadav, "A Review paper on Detection of Moving Object in Dynamic Background," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.877-880, 2018.

Technology makes life easier but at the same time generating bundles of data which is difficult to manage in traditional data stores. To manage this huge data, new data stores called NoSQL came into existence, they resolve the problem of data management by using partitioning. This paper discusses different partitioning techniques named horizontal, Vertical and Workload Driven Partitioning. Focus of this paper is to compare these partitioning techniques on the bases of important parameters named communication cost, complexity of search, quality and scalability. It provides the result on the basis of analysis which helps to choose the relevant partitioning technique.

Horizontal partitioning, Vertical partitioning, Workload Driven partitioning, Communication cost, Complexity of search, Quality, Scalibility

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Kiranjit Kaur, Vijay Laxmi, "Parametric Analysis of Cloud Data Partitioning Techniques: Review Paper," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.881-884, 2018.

Wireless Sensor networks (WSNs) is collection of various sensor devices and used to capture the environment conditions. Node deployment, limited energy capacity, location of sensor devices, Quality of Services (QoS) and data aggregation are the critical design challenges in WSNs. To overcome these design challenges in WSNs, many techniques have proposed. Swarm Intelligence (SI) is one of the most appropriate techniques to overcome the design challenges in WSNs.SI shows a current computational and behavioral similarity for taking care of disseminated issues. Initially took its motivation from the biological illustrations gave by social insects like ants, termites, honey bees, wasp and bee. In this paper, implement performance analysis of many SI techniques such that Ant Colony Optimization (ACO), Elephant swarm Optimization (ESO), Hnee based optimization (HBO), Particle Swarm Optimization (PSO) and Modified Artificial Bee Colony (MABC) to improve the WSNs lifespan.

Wireless Sensor networks (WSNs), Swarm Intelligence (SI), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO), Modify Artificial Bee Colony (IABC)

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Brahm Prakash Dahiya, Shaveta Rani, Paramjeet Singh, "Performance Analysis of Swarm Intelligence Techniques to improve lifetime of Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.885-895, 2018.

Multilingual Information Retrieval System (MLIR) allows users to provide queries in one language and extract the relevant content in multiple languages. Appraising the quality of these systems is a promising task. A wide variety of metrics are available for estimating the performance of IR systems, Precision and Recall are considered as the basic measures among them. However, less number of metrics is available in the literature to analyze the performance of MLIR Systems. This paper demonstrates the significance of MLIR systems when the retrieved documents are in various languages and the weights assigned by the user based on his preference languages. This is achieved by comparing the performances of IR and MLIR using the proposed weight based Precision oriented metrics. In addition, four essential parameters of the retrieval systems are considered to compare the significance of the proposed metrics with traditional metrics. The analyses of these metrics demonstrate positive and promising results. Statistical Analyses are also performed to show the importance of the proposed metrics. Thus we can conclude that weight based precision oriented metrics plays a vital role in MLIR domain area.

Average Precision, Information Retrieval, MLIR, Precision, Normalized Precision, P@k

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Pothula Sujatha, Prasad Koti T, Dhavachelvan P, "Appraisal of MLIR systems using Weight Based Precision Metrics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.896-904, 2018.

The exploration of Business Process Outsourcing (BPO) is a huge attention in India. A concern, the performance outcomes and hope of Indian service workers are efficient. To motivate the employee developing and managing levels of their hope, and also their problems such as erosion, pressure, and burnout that have afflicted the BPO industry. The main motivation is to reduce the stress level of employees in BPO field with data mining techniques. The data mining is to demonstrate the potential of gathering large collections of data, and analyzing these data sets to gain useful business oriented information. In this paper, for all the above algorithms the input data set will be considered as Employees issues. Based on the given input each algorithm will be processed and the respective solution is obtained. As per the performance of the given algorithm is not that much predictive in the accuracy and high error rate we propose a new method called Proposed Fast Boosting Decision Tree Algorithm (PFBDT) which will enhance accuracy rate and reduce in error rate.

BPO, Stress, Data Mining, Classifier, Algorithms

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K. Tamizharasi, G. Ramesh, "Efficiency Stress Prediction in BPO Industries Using PFBDT Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.905-912, 2018.

Most of sentiment based image classification approaches have done lots of complex calculation such as number of feature was collected for identifying correct class. In case of supervised learning models prediction of sentiment class for the unknown image leads to false alarm. So this work take facial input image features and find the sentiment of image by genetic approach. In this work grouping of various sort of information was managed without bargaining the security using genetic algorithm TLBO teacher Learning Based Optimization. Experiment was done on real dataset of JAFEE Images. Results show that execution time for the sentiment identification of image information was low. Here proposed work was capable to classify input data with high accuracy as compared to previous machine learning approaches.

Color format, digital image processing, facial sentiment detection, and genetic algorithm

[1]. WU, B. F., & LIN, C. H. (2014, FEBRUARY 14). Adaptive Feature Mapping For Customizing Deep Learning Based Facial Expression Recognition Model. Hsinchu 30010, Taiwan.
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Rahul chaurasia, Jitendra Agrawal, "Genetic Algorithm Based Facial Sentiments Recognition using Edge Feature," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.913-917, 2018.