Volume-07 , Special Issue-13 , May - 2019 Go Back

The asymmetry in the information pertaining to agricultural supply chain is extremely evident in developing countries like India. Also, the entity worst affected by this asymmetry are the farmers, who do not receive their fair share of in spite of being the most crucial contributors to this food cycle. Moreover, dealing with specific agricultural produce which h ave a short shelf life becomes a complex task with higher rate of wastage every year. With the help of a distributed ledger system in place, we help track the agricultural produce supply chain in every part of the country by replacing whatever supply chain tracking or centralized record keeping mechanism is already in place to provide complete transparency of the lifecycle of produce and enabling faster transactions between nodes and in turn helping the farmers reap the best benefits of their hard work. This would bring complete transparency in nodes where the efficiency is lost, parti cularly, brokers, distributors, regulators, retailers, government departments, etc., Easy and accurate access to this information will improve the overall efficiency of the supply chain and in turn benefit all the entities involved equally.

blockchain, distributed ledger, agriculture, farmers, hyper ledger, agri-blockchain, supply chain management, smart contract, circular economy

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Spurthi N. Anjan, Johnson P. Sequeira, "Improving the Efficiency of Supply Chain in Agricultural Produce Using Blockchain", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.1-4, 2019.

Unattainable environments are monitored by low-power Multi-functional sensor nodes of WSN. Wireless Sensor nodes are capable of sensing, computing and communicating the happenings in the environment. Whenever an area monitored by wireless sensor networks, is exposed to radiations or electromagnetic waves, sensor nodes will be deactivated or damaged. Then nodes are temporarily isolated. This leads to the formation of the holes of dynamic nature and also functionality of WSN components will be stopped. Thus it has consider as transfaulty behavior of nodes in WSNs. This paper reviewed the existing systems in highly structured manner related with transfer of communication mode to work in radiation-prone environments and continue to communicate between sensor nodes to identify the better route to reach destination. so as to avoid work load of each node in finding route, to avoid drain of cluster head energy, and to reduce the amount of the data which will forwarded from cluster to base station for reliable data transaction during transfaulty behavior of nodes. In order to understand the factors related, here survey of several research approaches have been analysed and presented to give a best mechanisms for avoiding communication failure due to explosion of radiations in the area monitored by wireless sensor networks.

Acoustic communication; RF communication; Wireless sensor Networks

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K.R. Asha, M.C. Supriya, "Survey on Transfaulty Behaviour of Nodes in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.5-9, 2019.

Ever since the emergence of 1G in mobile technology, evolution of new mobile generations have introduced various protocols and interfaces, high data transmission capacity making way for different vulnerabilities which allows for launch of attacks on network components. Performance of mobile networks and security is of a major concern. Industrial networks and automation networks were isolated in a physical sense until the emergence of Supervisory Control and Data Acquisition (SCADA). Simplicity, more productivity, reduction in downtime for system adjustments are some advantages with the industrial networks going public on internet. The result is the increase in the number of attack vectors on the SCADA system. IoT to define is a transformative approach providing numerous services over internet. Integrating the existing smart devices to the internet introduces security issues, threat of cyber attacks and crime. In this paper, we discuss the various vulnerabilities, threats and attacks on these three systems namely Mobile networks, SCADA systems, and IoT systems.

Mobile networks, Mobile network security, SCADA systems, Internet of Things, security, vulnerabilities

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Latha. P, Andhe Pallavi, "Vulnerabilities, Threats and Attacks on SCADA, Mobile Networks and in IoT", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.10-15, 2019.

The era of automation, robotics, Internet of Things and collaborative networked systems generated an uniquely characterized data which is named as Big data due to the presence of sensor, camera and text generators poses challenges of storage, processing, and analysis. In this paper, the advanced health care system of future is discussed which generates the Big data along with the conventional methods of data analytics on medical Big data its trends, limitations and further research possibilities. In this paper, a general characteristic of Bigdata is discussed then a thorough study on the future healthcare process and management will be described. Then discuss how the data generated in the context of the Healthcare system will have big data characteristics. Finally, collect all the state of artwork for medical big data analytics and discuss the research gap and open issues.

Analysis, Bigdata, Healthcare, Medical, Machine Learning

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Madhu H K, Prakash B R, "A Survey: Big Data Ethics and Challenges in Healthcare Division", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.16-24, 2019.

Big data is a term that is used to describe huge data sets having large, varied and complex structure with the hardness of analysing, storing and visualizing for further analysis or results. The analysis into large amounts of data to expose secret correlations and hidden patterns can be termed as big data analytics. [1] Big Data has proved to be beneficial as it helps to gain richer and deeper insights into the underlying mass of data. Common Entrance Test is a flat form for the students to opt for colleges to pursue Under graduation. Every year approximately 150000 students take up CET. Thus, these students will compete for seat among 220 engineering colleges across Karnataka, that are enrolled to the CET cell. Student can opt for a College based on availability of seat or branch for the rank they obtain in CET. Predictive analytics is the basic enabler for big data. On a day to day basis, Businesses collect large quantity of customer data which is used by predictive analytics along with historical data, coupled with customer insight, to forecast future events. For predicting a college several tools are taken into consideration they are: HBase for database, MapReduce for data processing mahout’s distributed naive Bayes classification for classifying and training data.

CET, HADOOP, PIG, MAHOUT, MAPREDUCE

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[7] http://kea.kar.nic.in/

Ravikiran M D, Poonam Gouli, "Novel Approach to Seat Matrix Prediction using Hadoop", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.25-32, 2019.

Obesity is a condition of being overweight. It’s a case where an individual weigh greater than healthy weight. Obesity and overweight have become a common problem of the entire population in the world. The effect of obesity in women’s health is eye-opening and undeniable which in turn is the main cause for women infertility. Obesity influences all the systems of our body including the reproductive system. The fact that obesity in infertile women is very high and there is a strong association between infertility and obesity. This paper shows increased rate of obesity and infertility over a decade. This paper also addresses the various cause for infertility in obese women.

BMI, Obesity, Infertility

[1] Eden R. Cardozo, MD, Lisa M. Neff, MD, MS, Maureen E.
Brocks, BA, Geraldine E. Ekpo, MD, Tanaka J. Dune, MD,Randall B. Barnes, MD, and Erica E. Marsh, MD, MSCI “Infertility patients’ knowledge of the effects of obesity on reproductive health outcomes” PMCID: PMC3935017, NIHMSID: NIHMS401524
[2] http://www.med.hku.hk/healthedu/issue77/e-issue77.pdf
[3] http://www.mapsofindia.com/my-india/india/survey-reveals- infertility-among-indians
[4] Marc M. Beuttler, MA, Kara N. Goldman, MD, and Jamie A.
Grifo, MD, PhD “Informing Patients about Declining Fertility” by
Virtual Mentor. October 2014, Volume 16, Number 10: 787-792.
[5] Anjani Chandra, Ph.D., and Casey E. Copen, Ph.D., National Center for Health Statistics; and Elizabeth Hervey Stephen, Ph.D., Georgetown University “Infertility and Impaired Fecundity in the United States, 1982–2010: Data From the National Survey of Family Growth” Number 67 n August 14, 2013
[6] Cynthia L. Ogden, Ph.D.; Margaret D. Carroll, M.S.P.H.; Cheryl D. Fryar, M.S.P.H.; and Katherine M. Flegal, Ph.D. Prevalence of Obesity Among Adults and Youth: United States, 2011–2014
[7] https://www.cdc.gov/nchs/data/hestat/obesity_child_13_14/obesity
_child_13_14.htm
[8] https://www.downtoearth.org.in/news/health/nfhs-4-highlights- india-has-become-obese-more-than-doubled-in-one-decade-only-
52527
[9] L. Mertz, "Taking on the Obesity Epidemic : Researchers Wage a Big
Fat Fight in Efforts to Combat This Global Health Issue," in IEEE
Pulse, vol. 8, no. 4, pp. 15-19, July-Aug. 2017. doi: 10.1109/MPUL.2017.2701491
[10] Ö. Taçyıldız, D. Ç. Ertuğrul, Y. Bitirim, N. Akcan and A. Elçi, "Ontology-Based Obesity Tracking System for Children and Adolescents," 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Tokyo, 2018, pp. 329-334. doi: 10.1109/COMPSAC.2018.10252

Rakshitha Kiran P, Naveen N C, "A Detailed Survey on Alarming growth of Obesity and Infertility", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.33-37, 2019.

Lateritic soils is formed by soft sediments, entangled between rigid to soft lateritic rock, and are seeped due to the entry of water in rainy seasons forming cavities which span over large lengths and considerable depth. Mainly in southern and central parts of India the Lateritic soils are formed. The proposed research work aims at the detection of cavities and formation of sink holes in lateritic soil. The data used in this proposed work is obtained from project site in Kannur District, Kerala State, India. To detect the heterogeneities in lateritic soils and formation of cavities, a Geophysical survey method, namely ground penetrating radar (GPR) with 100 MHz and 500 MHz (for confirmative survey) Ground Coupled antennae were used. The proposed work involves two dimensional 2D image pre-processing of the radargram obtained from GPR. The pre-processing involves data editing, time zero correction, Dewow filter, gain control, Background noise removal and edge detection to improve the detection of cavities in lateritic soil. This provides a means for interpreting the raw GPR data.

Ground penetrating radar, underground utility mapping,cavity detection and Dewow filter

[1] P.Anbazhagan, Divyesh Rohit, Athul Prabhakaran and B.
Vidyaranya“Identification of Karstic Features in Lateritic Soil by an Integrated Geophysical Approach” Pure Appl. Geophys. 175
(2018), 4515–4536, Springer International Publishing, ISSN 0033-
4553, Volume 175, Number 12.
[2] A.P. Daniels, D J "Ground Penetrating Radar" 2nd ed. 2004, London Institution of Electrical Engineers. ISBN 978-0-86341-
360-5.
[3] Nga-Fong Cheng, Hong-Wai Conrad Tang and Ching-To Chan “Identification and positioning of underground utilities using ground penetrating radar (GPR)" Sustain. Environ. Res., 23(2),
141-152 (2013).
[4] Warishah Abdul Wahab, Jasmee Jaafar,Ihsan Mohd Yassin and Mat Rahim Ibrahim “Interpretation of Ground Penetrating Radar (GPR) Image for Detecting and Estimating Buried Pipes and Cables” 2013 IEEE International Conference on Control System,Computing and Engineering, 29 Nov. - 1 Dec. 2013, Penang,alaysia.
[5] K.L Lee, M.M Mokji “Automatic Target Detection in GPR Images Using Histogram of Oriented Gradients (HOG)” Electronic Design (ICED), 2014 2nd International Conference on, 181-186.
[6] Prabhat Sharma, S. P. Gaba, Dharmendra singh “Study of Background Subtraction for Ground Penetrating Radar”, National Conference on Recent Advances in Electronics & Computer Engineering, RAECE -2015, Feb.13-15, 2015, IIT Roorkee, India
[7] Magdalena Szymczyk Piotr Szymczyk “Preprocessing of GPR Data”, Image Processing & Communication, vol. 18, no. 2-3, pp.
83-90.
[8] Spanoudakis S. Nikolaos and Vafidis Antonios “GPR-PRO: A MATLAB module for GPR data processing”, 978-1-4244-4605-
6/09/$25.00 ©2009 IEEE.
[9] Graham Parkinson, Csaba Ékes “Ground Penetrating Radar Evaluation of Concrete Tunnel Linings”, 12th International Conference on Ground Penetrating Radar, June 16-19, 2008, Birmingham, UK.
[10] N Muaniapan and A. V. Hebsur and E. P. Rao and G.
Venkatachalam, “Radius Estimation of Buried Cylindrical Objects using GPR – A Case Study”, 2012 14th International Conference
on Ground Penetrating Radar (GPR). Shanghai, China. ISBN 978-
1-4673-2663-6, 2012.
[11] Pedro Xavier Neto, Walter Eugeˆnio de Medeiros “A practical approach to correct attenuation effects in GPR data” Journal of Applied Geophysics 59 (2006) 140–151.
[12] A.P Annan “Practical Processing of GPR data” Proceedings of second Government workshop on GPR.

S.J. Savita, P. Anbazhagan, Andhe Pallavi, "GPR Preprocessing Methods to Identify Possible Cavities in Lateritic Soil", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.38-43, 2019.

Metastatic cancer remains a key task in medical management of the disease, since most cancer mortality rates are accredited to metastatic spread of cancer rather than the primary tumor. Despite the noteworthy improvements in the diagnosis, treatment and clinical management, prediction of prognosis, breast cancer relapse and death rates remain unacceptably high in women worldwide. Magnetic Resonance Imaging serves as an important source in detection, diagnoses and treatment monitoring of Breast Cancer. Image processing techniques like pre-processing using different filters to remove the noise content, image segmentation methods to extract the feature such as major axis length, minor axis length are applied to breast MRI images. A mobile app is developed to send the pre-processed MRI images to the doctors’ smart phone. The aim is to augment the view of the MRI images and interpret the condition of the patient as well as to enrich the overall interpretation process. The objective of the work is the analysis of MRI images which reflect the response of the neoadjuvant therapy administered at each successive stage to breast cancer patients in steps.

Metastatic Breast Cancer, Neoadjuvant therapy, Magnetic Resonance Imaging, Image processing

[1] Yeong Yi An, Sung Hun Kim,2 Bong Joo Kang and Ah Won Lee, Treatment Response Evaluation of Breast Cancer after Neoadjuvant Chemotherapy and Usefulness of the Imaging Parameters of MRI and PET/CT. Journal of Korean Medical Science, June, Vol.30(6), pp. 808–815. 2015 May 13, doi: 10.3346/jkms.2015.30.6.808
[2]URLhttps://www.hopkinsmedicine.org/breast_center/treat ments_services/medical_oncology/neoadjuvant_adjuvant_ch emotherapy.html. Neoadjuvant and Adjuvant Therapy in Breast Cancer.
[3] Mario Mustra, Mislav Grgic. Detection of Areas Containing Microcalcifications in Digital Mammograms. lWSSIP 2014, 21st International Conference on Systems, Signals and Image Processing, 12-15 May 2014, Dubrovnik, Croatia
[4] Bhagyashri G. Patil , Prof. Sanjeev N. Jain. Cancer Cells Detection Using Digital Image Processing Methods. International Journal of Latest Trends in Engineering and Technology (ILJET), Vol 3, Issue 4, March 2014, ISSN: 2278-621X.
[5] Sivaranjini S and Nirmala K. Breast Cancer Response PostNeoadjuvant Chemotherapy Using MRI Measurements. 2017 4th International Conference on Signal Processing, Communications and Networking (ICSCN -2017), 978-1-5090-4307-1/17. 2017.
[6] Arijit Ukil, Soma Bandyoapdhyay, Chetanya Puri, Arpan Pal. ioT Healthcare Analytics: The Importance of Anomaly Detection. 2016 IEEE 30th International Conference on Advanced Information Networking and Applications 1550-445X/16. 2016 IEEE DOI 10.1109/AINA.2016.158.
[7] Luqman Mahmood Mina, Nor Ashidi Mat Isa .Breast Abnormxality Detection in Mammograms using Artificial Neural Network. 2015 IEEE 2015 International Conference on Computer, Communication, and Control Technology (I4CT 2015), April 21 - 23 in Imperial Kuching Hotel, Kuching, Sarawak, Malaysia,978-1-4799-7952, 3-15.
[8] John T. Gohring, Paul S. Dale, Xudong Fan .Detection of HER2 breast cancer biomarker using the opto-fluidic ring resonator biosensor. Elsevier Journal on Sensors and Actuators B Chemical, Vol. 146(1),pp. 226-230, 2010

Madhura Gangaiah, Andhe Pallavi, "IOT based Breast Cancer Monitoring using MRI images Post Neoadjuvant Therapy", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.44-48, 2019.

There are various applications in industries where it has become essential to employ multiple motors to drive a common load. This necessity of multiple motor employment has aroused due to several reasons such as the presence of large loads, lack of space for a large motor, need for redundancy and process requirements. Also, there are some of the processes such as conveyor belt and mills which cannot operate with merely one motor. Any process that necessitates the employment of multiple motors to drive a common load will have to adopt load sharing arrangement which is essentially the usage of multiple motor-drive set. With the advancements that has happened in Power Electronics and Electric Drive streams, the user has a wide range of motors and drives to choose from, for load sharing. However, a study of behavior of these motors and drives when employed for load sharing is of utmost importance, as this helps the user to choose the appropriate motor -drive set for the required application. Induction motors are used in majority of the applications in industry. Scalar control and vector control are adopted for induction motor control. Understanding the behavior of induction motor under scalar and vector control in a load sharing arrangement will ease the selection of appropriate control strategy. Therefore, a comparative study of V/f and Field Oriented Control strategies for controlling induction motor in a load sharing arrangement is carried out and results are discussed

Load Sharing, Multiple Motor Drive, Torque sharing, V/f control, Field Oriented Control

[1] Rockwell Automation, “Load Sharing Applications for AC Drive” Publication Number DRIVES-WP001A-EN- P— June 2000
[2] Jaishankar Iyer, Mehdrad Chapariha, Francis Therrien, Juri Jatskevich,”Improved Torque Sharing In Multi Induction Motor VFD Systems Using Current Feedback”, 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012.
[3] Jaishankar Iyer, Mehdrad Chapariha, Milad Gougani, Juri Jatskevich, “Torque sharing between V/F controlled vehicular wheels under slippery ground conditions”, Transportation Electrification Conference and Expo (ITEC), IEEE, 2012.
[4] Sruthi M , Chilakapati Nagamani , Ganesan Saravana Ilango, “Dynamic Load Sharing in Multi-Machine Conveyor Belt Systems”, Asia Pacific Power and Enery Engineering Conference, 2017.
[5] M. H. Haque, Senior Member, IEEE, “Determination of NEMA Design Induction Motor Parameters From Manufacturer Data”, IEEE Transactions On Energy Conversion, Vol. 23, No. 4, December 2008.
[6] Hussein Khreis, Andrea Deflorio, Wei-Lung Lee, Miguel Ruiz De Larramendi, “Sensitivity Analysis for Induction Machine Manufacturing Tolerances: Modelling of Electrical Parameters Deviation”, Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER), 2017.
[7] Rachid Beguenane, Mohamed Benbouzid, “Induction Motors Thermal Monitoring by Means of Rotor Resistance Identification” IEEE Transactions on Energy Conversion, Institute of Electrical and Electronics Engineers, Vol.14, No.3, pp-566-570, , 1999.
[8] Amit Kumar, Tejavathu Ramesh, “Direct Field Oriented Control of Induction Motor Drive”, Second International Conference on Advances in Computing and Communication Engineering, 2015

Roopa Nayak, Andhe Pallavi, "A Comparison of V/f and Field Oriented Control of Three Phase Induction Motors Employed in Load Sharing", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.49-56, 2019.

Lung cancer disease is the most widely recognized deadly disease in the world for loss of life. Throughout this research, Electronic Health Records (EHRs) textual data are investigated and survivability rates for lung cancer affected patients are predicted. If the patients are survivable more than one year, chemotherapy treatment can be started for those patients. This research paper examines an effective Batch Size-Optimizer based Deep Neural Network (Op-DNN) classifier framework model, which is developed to predict the patient’s survivability based on status dead or alive. Considering only the patients who are alive, prediction is done to know how many months the patients will survive by Op-DNN regression technique. Here the textual data set is classified and processed in batches for each iteration. The errors generated from the original classification of the first batch size is fed back to the Op-DNN algorithm for further iterations with the reduced error loss that are free from underfitting and overfitting. The proposed method is compared with various parameters for Machine learning classifier algorithms demonstrating that the Op-DNN model has achieved better accuracy.

Lung Cancer, Diabetes, Survivable Rate, Artificial Neural network, DNN, Op-DNN, Classifier, SVM, NBs, C4.5, Optimizer, Adam, Relu, Epoch, Batchsize,Op-DNN Regression

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Pradeep K.R, Naveen N.C, "A Framework for Lung Cancer Survivability Prediction Using Optimized-Deep Neural Network Classification and Regression technique", International Journal of Computer Sciences and Engineering, Vol.07, Issue.13, pp.57-66, 2019.