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The healthcare industry is producing massive amount of data which need to be mine to discover hidden information for effective prediction, exploration, diagnosis and decision making. Chronic kidney disease (CKD), also known as chronic renal disease involves conditions that damage your kidneys and decrease their ability to keep you healthy. Early detection and treatment can often keep chronic kidney disease from getting worse. Machine learning techniques are commonly used to predict this situation. This research work mainly focused on finding the best classification algorithm based on different evaluation criteria like performance accuracy and root mean square error. We have performed a comparative study of the performance of machine learning algorithms J48, Support Vector Machine and Multilayer perceptron. The results show that MLP is giving minimum root mean square error value compared to J48 and SVM.

Data Mining, Neural Network, machine Learning, Kidney Disease Prediction, MLP, J48, SVM

[1]. Dr. S. Vijayarani1 , Mr.S.Dhayanand2 Assistant Professor1 , M.Phil Research Scholar2 “Kidney Disease Prediction Using SVM And ANN Algorithms”in 2015 international Journal of Computing and Business Research (IJCBR) Volume 6 Issue 2 March 2015
[2]. Parul Sinha, Poonam Sinha “Comparative Study of Chronic Kidney Disease Prediction using KNN and SVM” in 2015 International Journal of Engineering Research & Technology (IJERT) Vol. 4 Issue 12, December-2015
[3]. Harshali Patil, Manisha Divate “Kidney Disease Detection In Indian Patients In An Early Stage Using Weka Tool” in 2018 Proceedings of International Conference on Advances in Computer Technology and Management (ICACTM) In Association with Novateur Publications IJRPET-ISSN No: 2454-7875 ISBN No. 978-81-921768-9- 5 February, 23rd and 24th, 2018
[4]. N. Afhami “Prediction of Diabetic Chronic Kidney Disease Progression Using Data Mining Techniques”in 2018 International Journal of Computer Science Engineering (IJCSE), Vol. 7 No.02 Mar-Apr 2018
[5]. Lambodar Jena, Narendra Ku. Kamila “Distributed Data Mining Classification Algorithms for Prediction of Chronic- Kidney-Disease”, International Journal of Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-4, Issue-11) Research Article November 2015
[6]. S.S. Senthil priya1, P. Anitha “ Comparison Of Feature Selection Methods For Chronic Kidney Data Set Using Data Mining Classification Analytical Model”,International Research Journal Of Engineering And Technology (Irjet), Volume: 06 Issue: 2 | Feb 2019
[7]. https://archive.ics.uci.edu/ml/datasets.php
[8]. El-Houssainy A.RadyaAyman S.Anwarb “Prediction of kidney disease stages using data mining algorithms”, Informatics in Medicine Unlocked 15 (2019) 100178
[9]. Pushpa M. Patil “Review On Prediction Of Chronic Kidney Disease Using Data Mining Techniques”, International Journal of Computer Science and Mobile Computing, IJCSMC, Vol. 5, Issue. 5, May 2016
[10]. Sujata Drall, Gurdeep Singh Drall, Sugandha Singh, Bharat Bhushan Naib, “Chronic Kidney Disease Prediction: A Review”, International Journal of Management, Technology And Engineering, ISSN No : 2249-7455, Volume 8, Issue V, May/2018
[11]. Dr. S. Sasikala1, Dr. S. Jansi2, Ms. S. Saranya3,Ms. P. Deepika4, Ms. A. Kiruthika “Anticipating the Chronic Kidney Disorder (CKD) using Performance Optimization in AdaBoost and Multilayer Perceptron”, Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-2, 2017
[12]. International Journal of Scientific Research in Network Security and Communication (ISSN: 2321-3256)

Sayali Jadhav, Priya Chandran, Suhasini Vijaykumar, "Comparative Study of Chronic Kidney Disease Prediction using Machine Learning Techniques," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.501-506, 2019.

In this paper, we have presented simulated and measured results of tunable monopole circular microstrip antenna for dual frequency which covers L, C, and X band applications. The proposed antenna consists of two identical stubs placed along the patch axis having fixed width WS =1.0 cm. The slot is placed on left side of feed axis which is having fixed L1= 1.279 cm, L2 =1.3 cm and width W1= 0.1 cm. The upper and lower length of two identical stub is varied from LUS=0.483 to 1.83 cm and LLS=0.257 to 0.957 cm to tune an antenna for dual band. The first band varies from 1.8325 GHz to 1.5175 GHz having tuning range of 17.48% and 16.0% and second band varies from 8.5375 GHz to 7.2775 GHz having tuning range of 14.77% and 12.48% when simulated and measured respectively. The maximum impedance bandwidth of 111 % and 30.9 % is achieved for first and second band respectively. The antenna has peak gain of 3.0 dB. The VSWR is less 2 than for all tuned frequencies. The proposed antenna covers applications of L, C and X band. The simulated results are in good agreement with experimental results. The radiation patterns are nearly omni-directional nature both in E and H plane.

Identical stubs, slot, CMCMSA and TMCMSADF

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Biradar Rajendra, S. N. Mulgi, "Tunable Monopole Circular Microstrip Antenna for Dual frequency Covering L, C and X band Applications," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.507-511, 2019.

One of the most common attack known as DDOS(distributed denial-of-service) attack are threat to the net. In DDOS attack the intruder makes use of scattered zombies in order to transfer a huge quantity of traffic to the targeted host, so that the legal users will not be able to access the network services or resources. The main cause for this attack to happen is the use of static PID’s, as this static PID’s remain constant throughout the session the intruder can easily trap these PID’s used and launch the DDOS attack. In order to overcome this problem, here in this project work we plan, estimate and evaluate the use of dynamic PID. Here we make use of 16 characters pseudorandom dynamic PID’s . In dynamic mode these PID’s keep on changing throughout the session , this makes hard for the intruders to track the PID’s and launch the attack

DDOS, Static PID, Zombies, Dynamic PID

[1]. Yang Xiang, Ke Li, and Wanlei Zhou, Low-Rate DDoS Attacks Detection and Traceback by Using New Information Metrics, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 6, NO. 2, JUNE 2011.
[2]. Vijayalakshmi, Shalinie, Arun Pragash, IP Traceback System for Network and Application Layer Attacks, Recent Trends In Information Technology (ICRTIT), 2012 International Conference
[3]. Ahmad Sanmorino1, Setiadi Yazid2, DDoS Attack detection method and mitigation using pattern of the flow,2013 International conference of Information and communication technology(ICoICT)
[4]. Muhammad Aamir , Muhammad Arif, Study and Performance Evaluation on Recent DDoS Trends ofAttack & Defense, I.J. Information Technology and Computer Science, 2013, 08, 54-65
[5]. PyungKoo Park, SeongMin Yoo, Chungnam Nat, Service-Oriented DDoS Detection Mechanism Using Pseudo State in a Flow Router , 2013 International Conference on Information Science and Applications (ICISA)
[6]. Saman Taghavi Zargar, Joshi, Member, IEEE, and David Tipper,A Survey of Defense Mechanisms Against Distributed Denial of Service (DDoS) Flooding Attacks, IEEE COMMUNICATIONS SURVEYS & TUTORIALS, ACCEPTED FOR PUBLICATION (2013)
[7]. Ilker Ozcelik, Yu Fu , Richard R. Brooks ,DoS Detection is Easier Now, 2013 Second GENI Research and Educational Experiment Workshop.
[8].Monowar H. Bhuyan1, H. J. Kashyap1,D. K.Bhattacharyya, Detecting Distributed Denial of Service Attacks: Methods, Tools and Future Directions, The Computer Journal first published online March 28, 2013

Vinutha Yadav D, Nagaraj J, "Dynamic PID based approach for preventing DDOS attack in IP network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.512-517, 2019.

NYSC Posting Information system is designed to overcome the problems encountered with the existing system in terms of insecurity, data redundancy, Information time management and data protection, misplacement and mismanagement of files etc. The new system is designed in such a way that information about each corps member is effectively managed within the database for easy retrieval of information. The Top-down design approach model was used in the course of this research and data collected were implemented using Visual Basic 6 for the front end design and Microsoft Access for the Back end.

Corps, Database, Graduates, NYSC, Posting

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A. Sunday Olowookere, J. Oluwafemi Ayangbekun, S. Babatunde Oluwasola, "Design and Implementation of NYSC Orientation Posting scheme in Nigeria," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.518-522, 2019.

Medical imaging solution technology plays a vital role in the diagnosis and treatment of patients suffering from serious illness. In medical images, edge detection plays a vital role for recognition of the human organs. The performance of the edge detection determines the result of the processed image. Unfortunately, medical images like CT and MRI encounter a various number of noises such as Gaussian, Poisson and salt and pepper noise. Salt and pepper noise is frequently encountered in acquisition, transmission, and storage and processing of images. The presence of salt and pepper noise in an image may be either relatively high or low. Various filtering techniques have been proposed for removing salt and pepper noise. Conventional edge detection algorithms are belong to the high pass filtering which are not fit for noisy medical image edge detection because noise and edge belong to the scope of high frequency. In real world applications, medical images contain object boundaries, object shadows and noise. Therefore, they may be difficult to extract the edges in the presence of noise in medical images. Hence, a modified morphological edge detection algorithm is proposed to detect the edges in medical image. The performance of the proposed method is found to be better for detecting the edges and noise filtering than conventional techniques

MRI, Edge Detection, Morphology, Image Analysis, Brain Tumor

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J. Mehena , "Medical Image Edge Detection Using Modified Morphological Edge Detection Approach," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.523-528, 2019.

Now-a-days, finding an interesting pattern from the given dataset is an emerging trend to learn more about user behaviour and patterns of interest. Prior work on this problem many pattern mining approaches use two-phase pattern mining with one exception that are however inefficient and scalable to mine high utility sequential pattern mining. The way mention above suffers scalability issue for numerous candidates and growing sequence. This paper proposes an approach to apply tight upper bound for pruning patterns. Whereas, the freshness lies in the implemented algorithm that helps to prune tight sequence utility. The applied data structure helps us to maintain sequence patterns whose values are greater than applied thresholds. Extensive experiments on real datasets show that the defined algorithm is able to mine high utility sequential pattern incrementally.

Data-mining, High Utility Patterns, Sequential Pattern Mining, Pattern Mining, Pruning, Itemset share framework

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A. A. Tale, N. R. Wankhade, "Mining High Utility Pattern from Sequential Database," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.529-533, 2019.

Electrical and electrochemical properties of PEO based hot pressed nanocomposite polymer electrolyte (NCPE) membrane (1-x)[70PEO:30AgNO3]:xTiO2 where x=0-20 wt% , casted by using a novel hot pressed technique for prperation of electrochemical devices viz. supercapacitor, battery etc. have been studied. Solid Polymer Electrolyte (SPE) composition (70PEO:30AgNO3) reported earlier identified as highest conducting film at room temperature, has been used as 1st phase host matrix and nano-size (~8nm) filler TiO2 as 2nd phase dispersion. As a consequence of dispersal in SPE host, highest conductivity was achieved in at 5wt% of TiO2. This composition has been referred as optimum composing composition (OCC). Addition of KOH is OCC shows further increase in conductivity. The ion transport behavior in NCPE membrane have been discussed on the basis of ionic conductivity(σ), ionic transferred number(tion) and activation energy Ea. Morphology study and compositional veriation also performs by SEM .

Hot pressed polymer electrolyte, ionic conductivity, Activation energy,Scanning electron microscopic(SEM),

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Satpreet Singh Gill, Manish Kurre, "Preperation of Materia and Their Chemical, Physical and Electrical Analysis for HEV," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.534-537, 2019.

Bag of Features or BoF approach has been used in many computer vision tasks, including image classification, video search, robot localization, and texture recognition. It is so widely popular because of its simplicity. These methods are based on unordered collections of image descriptors which are then quantized and are discarded spatial information, therefore conceptually and computationally simpler than many alternative methods, because of this; BoF based systems have set new performance standards on popular image classification benchmarks and have achieved scalability breakthroughs in image retrieval. This paper reviews related works based on the issues of improving and/or applying BoF. Emphasis is placed on recent techniques that mitigate quantization errors, improve feature detection, and speed up image retrieval. Meanwhile, unresolved issues and fundamental challenges are also raised. Among those issues the best techniques for sampling images, describing local image features, and evaluating system performance. Among those the fundamental challenges are how the BoF methods can contribute in localizing the objects in more complex images, or associating high-level semantics with natural images. Moreover, many recent works are compared in terms of the methodology of BoF feature generation and experimental design. Different Classification Models are also discussed.

Bag Of Features, Feature Extraction, Quantization, Clustering, Image Representation, Image Classification, Support Vector Machine

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Santosh Kumar Panda, Chandra Sekhar Panda, "A Review on Image Classification Using Bag of Features Approach," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.538-542, 2019.

Despite many sincere attempts from the authorities to increase the quality of power supplied to the rural households of India, a large population of rural India is still remains power-deprived. To change this situation, renewable energy along with distributed generation can become a feasible solution. In this paper, an in-depth analysis of the potential of renewable distributed generation is presented to tackle this power crisis. It also takes into account the government initiatives taken so far and the challenges lying ahead in this field.

Renewable, Distributed Generation, Grid, Utility, Supply

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Suranjana Bharadwaj, "Renewable Distributed Generation and its Impact in Rural India," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.543-547, 2019.

With the rapid growth of cloud computing technology, more and more users store and share their data through cloud storage. Major concern is the inadvertent exposure of sensitive data of potential cloud users. Sometimes the cloud server may not delete the data honestly for financial intensives so that data deletion becomes a security challenge. Sometimes unintended disclosure leads to heavy financial penalties and reputational damage. The traditional approach to this problem is encryption of the data before outsourcing and destruction of the encryption key when detecting. Moreover, most of the existing methods can be summarized with the one-bit-return protocol. In which, cloud storage server deletes the data and returns one-bit as a result either 0 or 1 means failure/success. Sometimes this result misguides the user, but user has to believe the returned result because user can not verify it. As userslose their direct control over their data in cloud storage. Hence, assured data deletion is highly required in cloudstorage. In this paper, we aim to analyze assured deletion methods for the cloud, identifying the cloud features that pose a threat to assured deletion and described various assured deletion challenges.

Assured data deletion, User assurance, Cloud storage, Cloud security

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Seema B. Joshi, Shaileshkumar D. Panchal, "A Survey on Assured Data Deletion in Cloud Storage," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.548-553, 2019.