Volume-7 , Issue-3 , Jun 2019, ISSN 2321-3256 (Electronic Version) Go Back

• Open Access   Article

  Detection of Microaneurysm using Machine Learning Techniques

  Rohini M., Arsha P.

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.1-6, Jun-2019

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  Diabetic Retinopathy (DR) is a human eye disease which affects people with diabetics. DR affects retina of the eye and leads to blindness when it moves on to severe level. The early signs of diabetic retinopathy can be detected by screening of fundus image which is an effective method to prevent eye diseases. Detecting the disease at an earlier stage can prevent the patient from vision loss. This work aims to explore automatic methods for diabetic retinopathy (Microaneurysm) detection and eventually develop a successful system for detection and classification of diabetic retinopathy. In this work the proposed system consists of pre-processing, segmentation, feature extraction and classification of lesions. The retinal fundus images are taken from DIAbetic RETinopathy Database-calibration Level-1 (DIARETDB1). In pre-processing, the background pixels of the images are eliminated, resized, unwanted noise in the images are removed using average filter and median filter and then contrast enhancement is done using adaptive histogram equalization algorithm. The blood vessels of the image are detected using morphological operation (erosion and dilation). In segmentation phase the images are partitioned using k-means clustering algorithm for efficient image analysis. Statistical analysis is used for extracting the feature of the fundus image. The fundus image can be then classified with the help of support vector machine (SVM) classifier. The experiment results specificity, sensitivity, F-measure and accuracy are calculated based on the parameter of the proposed system. Based on the experiment result the accuracy achieved by SVM classifier is 95%.

  Key-Words / Index Term
  Diabetic Retinopathy; microaneurysm; pre- processing; k-means clustering; statistical feature extraction; SVM classifier

  References
  [1] Wen Cao*, Juan Shan, Nicholas Czarnek, “Microaneurysm Detection in Fundus Images Using Small Image Patches and Machine Learning Methods,” in 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
  [2] Lama Seoud “ Red Lesion Detection Using Dynamic ShapeFeatures for Diabetic Retinopathy Screening,” in 2016 IEEE transaction on medical imaging.
  [3] B´alint Antal “ An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading,” in 2012 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING.
  [4] Li Tang, “Splat Feature Classification With Application to Retinal Hemorrhage Detection in Fundus Images in 2013 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 32, NO. 2
  [5] Keerthi Ram “ A Successive Clutter-Rejection-Based Approach for Early Detection of Diabetic Retinopathyin 2011 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 58, NO. 3.
  [6] Ravi Kamble, Manesh Kokare, “DETECTION OF MICROANEURYSM USING LOCAL RANK TRANSFORM IN COLO FUNDUS IMAGES,”in IEEE International Conference on Image Processing (ICIP) 2017.
  [7] Mohammad A. Al-Jarrah “Non-proliferative diabetic retinopathy symptoms detection and classification using neural network in 2017 Journal of Medical Engineering & Technology.
  [8] I.S.Hephzi Punithavathi, Dr.P.Ganesh Kumar, “Severity Grading of Diabetic Retinopathy Using Extreme Learning Machine”,in IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNIQUES IN CONTROL, OPTIMIZATION AND SIGNAL PROCESSING 2017.
  [9] J. Shan and L. Li, “A Deep Learning Method for Microaneurysm Detection in Fundus Images,” in IEEE 1st International Conference on Connected Health: Applications, Systems and Engineering Technologies,CHASE 2016, 2016.
  [10] Valliappan Raman, Patrick Then, Putra Sumari, Proposed Retinal Abnormality Detection and Classification Approach Computer Aided Detection for Diabetic Retinopathy by Machine Learning Approaches in 8th IEEE International Conference on Communication S oftw are and N etw ork s 2016.
  [11] May Phu Paing*, Somsak Choomchuay**, Rapeeporn Yodprom, MD, “Detection of Lesions and Classification of DiabeticRetinopathy Using Fundus Images”, The 2016 Biomedical Engineering International Conference (BMEiCON-2016).
  [12] A.Rajan, “Detection of Diabetic Retinopathy in Fundus Image,” in International Journal of Science and Application, 2015,
  [13] Shah Syed Ayaz Ali , Tong Boon Tang ,* Augustinus Laude and Ibrahima Faye, “Making every Microaneurysm Count: A Hybrid Approach to Monitor Progression of DiabeticRetinopathy in 5th International Conference on Intelligent and Advanced Systems (ICIAS) 2014.
  [14] M. Usman Akram et al., “Detection and classification of retinal lesions for grading of diabetic retinopathy,” Comput. Biol. Med., vol. 45, no. 1,pp. 161–171, 2014
  [15] M. UsmanAkram a,n, ShehzadKhalid b, AnamTariq a, ShoabA.Khan a, Farooque Azam a, “Detection and classification of retinal lesions for gradingof diabetic retinopathy”,in Computers inBiologyandMedicine45(2014)161–171 2013.
  [16] Meindert Niemeijer*, Bram van Ginneken, Member, IEEE, Michael
  J. Cree, Senior Member, IEEEAtsushi Mizutani, Gwénolé Quellec, Clara I. Sánchez, Member, IEEE, Bob Zhang, “Retinopathy Online Challenge: AutomaticDetection of Microaneurysms in Digital Color Fundus Photographs in IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 29, NO. 1, JANUARY 2010
  [17] T. Kauppi et al., “DIARETDB1 diabetic retinopathy database and evaluation protocol,” Proceedings Br. Mach. Vis. Conf. 2007, vol. 1, p.15.1-15.10, 2007.
  [18] K. Ram, G. D. Joshi, and J. Sivaswamy, “A successive clutter- rejection based approach for early detection of diabetic retinopathy,”
  IEEE Trans.Biomed. Eng., vol. 58, no. 3, pp. 664–673, 2011
  [19] Harry pratt, Frans Coenen.B, “Convolution neural network for Diabetic Retinopathy”, in international conference on medical imaging understanding and analysis 2016.
  [20] Sean H.F and Han C.W .Haiso “ Fast Detection of Microaneurysm Color Fundus Image”, in IEEE 2nd International conference on Multimedia big data.
  

  Citation
  Rohini M., Arsha P., "Detection of Microaneurysm using Machine Learning Techniques," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.1-6, 2019

• Open Access   Article

  Security in Internet of Things (IoT) Hashing Cryptographic Functions

  Himanshu Kumar Shukla, Satyam Dubey

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.7-11, Jun-2019

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  Internet of Things (IoT) begins new era of wireless interconnected devices, where every device have connectivity among each other. As looking towards today IP-Based communication structure all protocols plays a vital role in providing ubiquitous connectivity in all existing devices. All these devices are connected to each other in IoT and perform communication by using IP-based protocol. Throughout this communicating structure devices under network connection can be protected but for IoT connecting every device with Internet may take network under unsecure zone. These small issues created big problem to challenge security measures existing these days in IoT. To resolve these type of problems of security we analysed existing algorithms and hash cryptographic function and presented a modified Algorithms to do same operation but in less time as well as in less memory space. We also discussed present research for IoT’s security requirement and with also about future research path for IoT security and privacy.

  Key-Words / Index Term
  Internet of Things (IoT); Wireless Sensor Networks (WSNs); Quality of Services(QoS); RC-5; Skipjack; AES; Low Power Wireless Personal Local Area Network (LoWPAN); Radio Frequency Identification (RFID).

  References
  [1] Alberto M.C Souza and Jose R.A. Amazonas, `A Novel Smart Home Application Using an Internet of ThingsMiddleware`,European Conference on Smart Objects, Systems and Technologies, pp. 1-7, June 2013.
  [2] Andrea Zanella, Nicola Bui, Angelo Castellani, Lorenzo Vangelista, and Michele Zorzi, `Internet of Things for Smart Cities`, IEEE Internet of Things Journal, Vol. 1 No.1, pp. 22-32, February 2014.
  [3] Cristina Alcaraz, Pablo Najera, Javier Lopez, Rodrigo Roman,`Wireless Sensor Networks and the Internet of Things:Do We Need a Complete Integration?`, SecloT Japan, November 2010.
  [4] Chang, K. C. Gupta and M. Nandi, "RC4-Hash: A New Hash Function Based on RC4", Proc. INDOCRYPT, LNCS 4329, pp. 80-94, Springer, 2006.
  [5] Fagen Li and Pang Xiong , `Practical Secure Communication forIntegrating Wireless Sensor Networks Into the Internet of Things`
  [6] Kelly, S.D.T., Suryadevara, N.K., Mukhopadhyay, S.C.,`Towards the implementation of loT for Environmental Condition Monitoring in Homes`, Vol.I 3 No. 10, pp. 3846-3853, August 2013.
  [7] M.Tharani, M.Senthilkumar , `Integrating Wireless Sensor Networks into Internet Of Things For Security` IJIRCCE VoI.2 No.1, March 2014.
  [8] Ming Wang, Guiquing Zhang, Jianbin Zhang, Chengdong Li, `An loT-based Appliance Control System for Smart Homes` ICICIP , pp. 744-747, 2013.
  [9] Dr. Pritam Gajkumar Shah, Javeria Ambareen, `A Survey of Security Challenges in Internet of Things (loT) Integration with WSW, AUSJOURNAL,2014.
  [10] Pormante, L. Rinaldi, C. Santic, M.Tennina, S., `Performance analysis of a lightweight RSSI-based localization algorithm for Wireless Sensor Networks`, ISSCS , pp. 1-4, June 2013.
  [11] Sang-Eon Lee, Sang-Ho Shin, Geum-Dal Park and Kee-Young Yoo, `Wireless Sensor Network Protocols for Secure and Energy- Efficient Data Transmission` Proceedings of the CISIM`08 on Computer Information Systems and Industrial Management Applications, pp. 157-162, June 2008.
  [12] Sye Loong Keoh, Sandeep S. Kumar, and Hannes Tschofenig,`Securing the Internet of Things A Standardization Perspective`, IEEE INTERNET OF THINGS JOURNAL, Vol. I, No. 3, pp. 265-275, June 2014.
  [13] Wade Trappe, Lawrence C. Washington, `Introduction to Cryptography with Coding Theory.
  [14] Woo Kwon Koo, Hwaseong Lee, Yong Ho Kim, Dong Hoon Lee, `Implementation and Analysis of New Lightweight Cryptographic Algorithm Suitable for Wireless Sensor Networks` International conference on Information assurance and security, pp. 73-76., 2008.
  [15] Xu Li, Rongxing Lu, Xiaohui Liang, and Xuemin (Sherman) Shen, `Smart community An Internet of Things Application`, IEEE Communications magazine, Vol. 49 No.ll, pp. 68-75, November 2011.
  

  Citation
  Himanshu Kumar Shukla, Satyam Dubey, "Security in Internet of Things (IoT) Hashing Cryptographic Functions," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.7-11, 2019

• Open Access   Article

  Experimental Investigation on the use of Pond Ash in the Concrete

  Shrikant M. Harle

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.12-20, Jun-2019

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  The fly Ash generation in Indian thermal power stations is liable to shoot up to 365 Million tons. In India, about 200 million sq.m of land area is covered up with million tonnes of pond ash deposits. Although industry has claimed that fly ash is "neither toxic nor poisonous," this is disputed. To minimize the impact of such waste materials on environment proper management is required. Utilization of the waste materials in different purposes is an effective way of management. The utilization of the pond ash is studied as a construction material. Aim is to find out an effective way to use the pond ash as construction material so as to reduce the impact of the hazardous pond ash on environment and human health. Also finding the ways to efficiently use the pond ash waste in order to preserve our precious resources and reduce or eliminate the need for disposal of industrial waste in landfills. The use of pond ash in concrete and its properties such as compressive strength, particle size distribution, and cementitious nature of a pond ash is studied. The utilization of pond ash in different construction material effectively such that the strength and quality of construction increases but the cost of the construction decreases is studied.

  Key-Words / Index Term
  Pond ash, compressive strength, concrete, admixture and fine aggregate

  References
  [1] Aditya Verma, Abhishek Kumar, Ashish Mishra, Arjit Verma, “Utilization Of Pond Ash as Partial Replacement Of Cement Concrete Mix” International Research Journal of Engineering and Technology (IRJET), Vol. 3, Issue 3 Mar-2016.
  [2] G. Sudheer Kumar, T S D Aishwarya, E. Anusha Assistant Professor, Jntu-k , “Studies On Strength Characteristics Of Pond Ash Replaced By Fine Aggregate In Pavement Quality Concrete”, VFSTR Journal of STEM, Vol. 03, No 01, JUN 2017.
  [3] U.Bayarzul, J.Temuujin, A. Minjigma, A. Bekhbaatar, B. Battsetseg, J. Mapiravana, M. Dlamini, “Comparative study of morphology of various fly ashes and pond ashes from different thermal power station in mangolia”, Proceedings of the Mongolian Academy of Sciences, Vol. 54 No 04,2014
  [4] J. Temuujina, A. Minjigmaa, U. Bayarzula, D. S. Kimb, S-Ho Leeb, H. J. Leeb, C. H. Ruescherc, K.J.D.mackenzied, “Properties of geopolymer binders prepared from milled pond ash”, Materiales de construcción, Vol. 67, Issue 328,Dec 2017
  [5] Deepak Gupta, Arvind Kumar, “ Performance evaluation of cement-stabilized pond ash-rice husk ash clay mixture as a highway construction material”, Journal of Rock Mechanics and Geotechnical Engineering, vol. 9, issue 1, Dec 2016
  [6] B.R. Phanikumar, A. Sofi , “Effect of pond ash and steel fibre on engineering properties of concrete”, Ain Shams Engineering Journal, vol. 7, issue 1,Mar 2016
  [7] Sarat K. Das, Mahasakti Mahamaya, Ipshita Panda, Kajal Swain, “Stabilization of pond ash using bipolymer”, Procedia Earth and Planetary Science, vol. 11, issue 20,Jul 2015
  [8] A. Minjigmaa, Ts. Zolzaya, E. Bayanjargal, B. Davaabal, J. Temuujin, “Characterization of ash pond ashes from 3rd thermal power plant by SEM/EDX and XRD methods ”, Mongolian Journal of Chemistry , vol. 14, issue 40, Dec 2013
  [9] Arumugamk , ilangovanr , James Manohar, “A study on characterization and use of Pond Ash as fine aggregate in Concrete”,International Journal Of Civil And Structural Engineering, Vol. 2, issue 2,Nov 2011
  [10] Prof. P. P. Bhangale, Prof. P. M. Nemade, “Study of Pond ASH (BTPS) Use as A Fine Aggregate in Cement Concrete - Case Stud”, International Journal of Latest Trends in Engineering and Technology (IJLTET), Vol. 2 Issue 2, March 2013
  [11] Sreelakshmi R, Reshmi P R, “Durability Performance of Concrete Replaced with Pond ash as Fine Aggregate”, IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), vol. 6, issue 4, Jun 2013
  [12] Prasenjit Ghosh and Sudha Goel, “Physical and Chemical Characterization of Pond Ash”, International Journal of Environmental Research and Development, Volume 4, Number 2,2014
  [13] Rabi Narayan Behera Abhishek Kumar Chittaranjan Patra, “Geotechnical and Geoenviornmental Characterization of TTPS Pond Ash and Its Utilization”, Indian Geotechnical Conference, vol:14, issue16, Dec 2017
  [14] Shashi Sharma, Er. Ritu, “Characterization and Use of Pond Ash in Concrete as Replacement of Sand: A Review”, International Journal of Technical Research, Vol. 4, Issue 3, Nov-Dec 2015
  [15] Milind P. Bhamare, Yogesh N. Bafna, Arun K. Dwivedi, “Engineering Properties of Cement Containing Pond Ash”, IOSR Journal of Engineering, Vol. 2, Issue 10, Dec 2012
  [16] Raju Sarkar, A. R. Dawson, “Economic Assessment of Use of Pond Ash in Pavements”, International Journal of Pavement Engineering, vol. 18, issue 7,2017
  [17] Gaurav Kantibhai Patel, Prof. Jayeshkumar Pitroda, “Pond Ash and Foundry Sand: Opportunities for Development of Eco-Friendly High Strength Concrete”, International Journal of Engineering Trends and Technology (IJETT) – Volume 9 Number 6, 2014
  [18] Arumugamk , ilangovanr , James Manohar D ,“A study oncharacterizationand Use of Pond Ash as fine aggregate in Concrete”,International Journalof Civil and Structural Engineerisng, Volume 2, No2, 2011.
  

  Citation
  Shrikant M. Harle, "Experimental Investigation on the use of Pond Ash in the Concrete," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.12-20, 2019

• Open Access   Article

  A Proposed Model for Enhanced Security against Key Reinstallation Attack on Wireless Networks

  G. Abare, E. J. Garba

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.21-27, Jun-2019

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  Abstract
  Wireless network security is advancing consistently. This progress can be easily seeing by recounting the success stories achieved through the years since the modification of its first security protocol, WEP; then the WPA and finally the WPA2. The Wireless Protocol Access Pre-Shared Key (WPA2-PSK) mode is usually adopted by Small Office Home Office (SOHO) environments as it does not require a costly investment on a dedicated authentication system. Nevertheless, despite the fact that this mode was improved consistently, the core part (4-way handshake) still presents several vulnerabilities such as the key reinstallation attack (KRACK) which was discovered by Vanhoef and Piessens in 2016 and published in October, 2017. Here, we proposed an enhanced model which involved a Boolean variable that switches from true to false once the Key is installed; also, we include handshake messages encryption with Pair-wise Master Key as the encryption/decryption key, using Advance Encryption Standard (AES). Results obtained from the simulations of the enhanced model were compared with that of the existing model. The message execution time measured in micro seconds shows that the proposed model is more efficient than the existing four-way handshake model and it prevent the reinstallation of the Pair-wise Master key (PTK) during the handshake process.

  Key-Words / Index Term
  Wireless Protocol Access, Wireless Local Area Networks Security, Pire-wise Transient Key, Group Temporal Key, Key Reinstallation Attack.

  References
  [1] Alblwi, S., & Shujaee, K. (2017). A Survey on Wireless Security Protocol WPA2. In International Conference Security and Management.
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  [3] Arana, P. (2006). Benefits and Vulnerabilities of Wi-Fi Protected Access2 (WPA2). INFS 612–Fall.
  [4] Benton, K. (2010). The evolution of 802.11 wireless security. Journal, UNLV Informatics- Spring, n. INF, 795, 1-56.
  [5] Hailemariam, M. A. (2016). Securing the Transmission of Group Addressed Data Frames by Enhancing the IEEE 802.11i Security Protocol (Doctoral dissertation, Addis Ababa University).
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  [9] Kumkar, V., Tiwari, A., Tiwari, P., Gupta, A., &Shrawne, S. (2011). Vulnerabilities of Wireless Security protocols (WEP and WPA2). International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 1(2), pp-34.
  [10] Liu, Y. L., & Jin, Z. G. (2015). SAEW: A security Assessment and Enhancement System of Wireless Local Area Networks (WLANs). Wireless Personal Communications, 82(1), 1-19.
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  [12] Naitik, T., Raiton L., Pradnya, V., & Vamshi, S. (2018). Mitigation of Key Reinstallation Attack in WPA2 Wi-Fi networks by detection of Nonce Reuse. International Research Journal of Engineering and Technology (IRJET), 5(5),pp-4.
  [13] Nikita, B., Ian, G., & David, W.(2001).Intercepting Mobile Communications. The Insecurity of IEEE802.11. 7th Annual International Conference on Mobile Computing and Networking, July 2001.
  [14] Nowicki, G. D. (2004). Wireless Security:The Draft IEEE 802. 11i Standard.
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  [18] Singh, S., & Amit G. (2014). Study and Analysis of Dictionary attack and Throughput in WEP for CRC-32 and SHA-1. International Journal of Computer Applications 96.( pp. 15-18).
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  Citation
  G. Abare, E. J. Garba, "A Proposed Model for Enhanced Security against Key Reinstallation Attack on Wireless Networks," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.21-27, 2019

• Open Access   Article

  Design and Analysis of Pattern Reconfigurable Dual Band MIMO Antenna using 5G Smartphone Application

  B. Asha, R. Gomathi

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.28-30, Jun-2019

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  Abstract
  Double band MIMO radio wire for the 5G correspondence is proposed in this paper. The proposed radio wire comprises of four radio wire, it working at 3300-3600 MHz and 4800-5000 MHz. The radio wire planned in this letter are extraordinary from conventional 5G radio wires, the reception apparatus of this paper is opposite to the edge of the framework circuit board, it tends to be connected to the well known full-screen cell phone. As indicated by the recreation results, reflection coefficient of the modulus is less than - 6 dB, and the separation is superior to 12 dB over the band frequency of 3300-3600 MHz and 4800-5000 MHz, it will met the necessities of future 5G applications.

  Key-Words / Index Term
  smart phone , 5g operation, MIMO antenna

  References
  [1] Azremi, H., Costa, M., Koivunen, V., et al.: ‘Ambiguity analysis of isolation –based multi-antenna structures on mobile terminal`. fifth European Conf.Antennas and Propagation(EUCAP), 2011, pp. 552–556
  [2] Y.-X. Guo, H. Chu, “Broadband 60-GHz beam-steering vertical off-center dipole antennas in LTCC," IEEE Antenna Technology (iWAT), International Workshop on., pp. 177-180, Mar. 2012.
  [3] W.-M.-A. Wahab, S.-S. Naeini, "Low loss H-shape SIW hybrid coupler for millimeter wave phase arrays antenna systems," IEEE Antennas and Propagation Society International Symposium (APSURSI)., pp. 1-2, Jul. 2012.
  [4] Wen T, Zhu PY. 5G: A technology vision. Huawei, 2013
  [5] A. Pal, A. Mehta, R. Lewis, and N. Clow, “Phase array system consisting of unit pattern reconfigurable square loop antennas,” IEEE Antennas and Propagation Society International Symposium (APSURSI)., pp. 1658-1659, Jul. 2014.
  [6] M. Roig, M. Maasch, C. Damm, and R. Jakoby, "Electrically tunable liquid crystal based composite right/left-handed leak-eave antenna at 26.7GHz,” Microwave Conference (EuMC) ., pp. 331-334, Oct. 2014.
  [7] C. Damm, M. Maasch, R. Gonzalo, and R. Jakoby, "Tunable composite right/left-handed leaky wave antenna based on a rectangular waveguide using liquid crystals,” IEEE in Microwave Symposium Digest (MTT) MTT-S International, pp. 53 –56, Oct 2014.
  [8] Cheng-Nan Hu, Kevin Peng, Chung-Hang Yu, Tsai-Wen Hsaio and DerPhone Lin. Design of an mm-Wave Microstrip Antenna Array. Electromagnetics: Applications and Student Innovation Competition (iWEM), 2015.
  [9] Wei-Shiuan Chang, Chang-Fa Yang, Chih-Kai Chang, Wen-Jiao Liao; Liang Cho, Wen-Shih Chen. Pattern Reconfigurable MillimeterWave Antenna Design for 5G Handset Applications. 2016 10th European Conference on Antennas and Propagation (EuCAP).
  [10] Wei-Shiuan Chang, Chang-Fa Yang, Chih-Kai Chang, Wen-Jiao Liao; Liang Cho, Wen-Shih Chen. Pattern Reconfigurable MillimeterWave Antenna Design for 5G Handset Applications. 2016 10th European Conference Antennas and Propagation (EuCAP).
  [11] Yong-Ling Ban, Zhong-Xiang Chen, Zhi Chen, Kai Kang; Joshua Wei Li. Decoupled Closely Spaced Heptaband Antenna Array for WWAN/LTE Smartphone Applications. IEEE Antennas and Wireless Propagation Letters
  [12] Yong-Ling Ban, Chuan Li Chow-Yen-Desmond Sim, Gang Wu, Kin-Lu Wong 4G/5G Multiple Antennas for Future Multi-Mode Smartphone Applications. IEEE Access.
  

  Citation
  B. Asha, R. Gomathi, "Design and Analysis of Pattern Reconfigurable Dual Band MIMO Antenna using 5G Smartphone Application," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.28-30, 2019

• Open Access   Article

  Machine Learning – A New Paradigm of AI

  Hemant Kumar Soni

  Review Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.31-32, Jun-2019

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  Artificial intelligence is a field of programming building which gives PCs an ability to learn without being unequivocally modified. Computer based intelligence is used in a combination of computational errands where organizing and programming unequivocal algorithms with extraordinary execution isn`t basic. Applications fuse email isolating, affirmation of framework gate crashers or threatening insiders advancing toward a data break. One of the foundation objectives of AI is to get ready PCs to utilize data to deal with a foreordained issue. An extraordinary number of usages of AI like classifier getting ready on email messages to isolate among spam and non-spam messages, blackmail revelation, etc. In this article we will focus on stray pieces of AI, AI endeavors and issues and diverse AI algorithms.

  Key-Words / Index Term
  Machine learning, supervised learning, unsupervised learning, classification

  References
  [1] R. Maruthaveni and V. Kathiresan, “A Critical Study on RFID”, IJSRNSC, Volume-6, Issue-2, pp. 62-65, April 2018.
  [2] Rakesh Kumar Saini, “Data Mining tools and challenges for current market trends-A Review”, International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.2, pp.11-14, 2019.
  [3]. Talwar, A. and Kumar, Y. “Machine Learning: An artificial intelligence methodology”. International Journal of Engineering and Computer Science, 2, pp.3400-3404, 2013.
  [4]. Muhammad, I. and Yan, Z.,. “Supervised Machine Learning Approaches: A Survey”. ICTACT Journal on Soft Computing, 5(3), 2015.
  [5]. Singh, S., Kumar, N. and Kaur, N. “Design And development Of RFID Based Intelligent Security System. International”, Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume, 3, 2014.
  

  Citation
  Hemant Kumar Soni, "Machine Learning – A New Paradigm of AI," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.31-32, 2019

• Open Access   Article

  QoS Parameters for Cloud Using Swarm Optimization Dynamic Load Balancing Algorithm

  Sanjay G. Patel, S.D. Panchal

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.33-39, Jun-2019

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  Abstract
  Due to popularity of Cloud computing environment, the cloud computing users are increasing day by day and that has become one of the important challenges for the cloud providers in terms of load balancing. Load balancing distributes the traffic evenly over multiple paths. In this research work, we have proposed the Dynamic Improved PSO Load balancing algorithm and implement it over CloudSim toolkit. This toolkit assisted the modeling and generation of virtual machines in a simulated manner such that datacenters, jobs and their mapping to VMs can be done on a same node whereas provide the desirable result. Therefore, the results are compared with the existing load balancing algorithms namely Modified Throttled, FCFS and Particle Swam Optimization based on their performance using CloudSim Simulator. Simulation outcomes are recorded in terms of the Response time and datacenter processing time of these algorithms along with its performance and cost details.

  Key-Words / Index Term
  Cloud Computing, Load Balancing, Virtual Machine, Scheduling, Particle Swarm Optimization, Modified Throttled, FCFS, CloudSim, Response time, Data Center Processing Time, Cost

  References
  [1] P. J. Angeline, "Using selection to improve Particle Swarm Optimization," Proc. IEEE Int. Conf. Computational Intelligence, pp.84-89, 1998
  [2] W. Li, H. Shi, "Dynamic Load Balancing Algorithm Based on FCFS," IEEE (ICICIC) Fourth International Conference on Innovative Computing, Information and Control, pp.1528 - 1531, December 2009
  [3] S. G. Domanal, G. R. Mohana Reddy, "Load Balancing in cloud computing Using Modified Throttled Algorithm," IEEE International Conference on Cloud Computing in Emerging Markets (CCEM).
  [4] S. Mohapatra, K. Smruti Rekha, S. Mohanty, "A comparison of Four Popular Heuristics for Load Balancing of Virtual Machines in Cloud Computing," IJCA Journal, vol. 68(6), pp. 34-38, April 2013.
  [5] B. Mondal, K. Dasgupta, P. Dutta, "Load Balancing in Cloud computing using stochastic hill climbing-a soft computing approach," In Proceedings of 2nd International Conference on Computer, Communication, Control and Information Technology (C3IT), Elsevier, Procedia Technology, vol. 4, pp. 783 -789, February 2012.
  [6] B. Mondal, K. Dasgupta, P. Dutta, "Load Balancing in Cloud computing using stochastic hill climbing-a soft computing Approach, “In Proceedings of 2nd International Conference on Computer, Communication, Control and Information Technology(C3IT), Elsevier, Procedia Technology, vol. 4, pp. 783 -789, February 2012.
  [7] Q. Bai, "Analysis of Particle Swarm Optimization," Computer and Information Science (CCSE), IEEE, vol. 3(1), pp. 180-184, February 2010.
  [8] Anju Baby, “Load Balancing In Cloud Computing Environment Using PSO Algorithm”, International Journal for Research in Applied Science and Engineering Technology, Vol 2 Issue IV, April 2014.
  [9] Vidhi Tiwari1*, Pratibha Adkar2, Implementation of IoT in Home Automation using android application, International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.2, pp.11-16, April (2019), E-ISSN: 2320-7639.
  [10] Amogha A.K., Load Forecasting Algorithms with Simulation & Coding, International Journal of Scientific Research in Computer Science and Engineering, Vol.7 , Issue.2 , pp.16-21, Apr-2019, E-ISSN: 2320-7639.
  

  Citation
  Sanjay G. Patel, S.D. Panchal, "QoS Parameters for Cloud Using Swarm Optimization Dynamic Load Balancing Algorithm," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.33-39, 2019

• Open Access   Article

  Implementation of Raspberry functionality with RFID

  Hemant Kumar Soni

  Research Paper | Journal (IJSRNSC)

  Vol.7 , Issue.3 , pp.40-42, Jun-2019

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  Radio Frequency Identification(RFID), is a remote ID strategy and now-a-days it become exceptionally mainstream. This is utilized for keen. This is secure framework and what`s more, do challenge stock by the use of radio repeat. This advancement is used in bank, and in book shop of universities and schools and so on. This innovation is exceptionally helpful, easy to use with lower overheads then again with the other standard methodology, for instance, scanner tag, biometrics, etc. It is of two sort RFID tag and RFID per client. RFID per client is a device that is prepared for examining and find information which set away in RFID marks. RFID names can take the extent of data from one sequential number to a couple of pages of data. Per clients will be a versatile that can without quite a bit of a stretch pass on in hands. Per clients can be worked in a structure of a room, assembling, etc. In this paper we discuss the RFID hardware, software, programming language used for RFID and future scope of RFID.

  Key-Words / Index Term
  RFID, RFID Reader, RFID Tag, Data Analysis, Real Time System

  References
  [1] R. Maruthaveni and V. Kathiresan, “A Critical Study on RFID”, IJSRNSC, Volume-6, Issue-2, pp. 62-65, April 2018.
  [2]. Mandeep Kaur, Manjeet Sandhu, Neeraj Mohanand Parvinder S. Sandhu, “RFID Technology Principles, Advantages, Limitations & Its Applications”, IJCEE, Vol.3, No.1, February, 2011
  [3]. T. Kindberg et al., “People, Places, and Things: Web Presence of the Real World”, ACM Mobile Networks & Applications J., pp. 365 – 376, 2002
  [4]. Dibyendu Bikash Datta, “Radio Frequency Identification Technology: An Overview of its Components, Principles and Applications”.IJSETR, Volume 5, Issue 2,February 2016.
  [5]. Juels, A., Rivest, R. L., & Szydlo, M. “The blocker tag: Selective blocking of RFID tags for consumer privacy”. In Proceedings of the 10th ACM conference on Computer and communications security pp.103-111, 2003
  [6] https://www.indiamart.com/proddetail/em-18-rfid-reader-with-rs-232-125-khz-9157003455.html
  [7] Jilani Sayyad, Mukadam Taha and Amol Sankpal, “Advanced Car Security System”, IJSRNSC, Volume-5, Issue-3, pp. 165-169, June 2017.
  

  Citation
  Hemant Kumar Soni, "Implementation of Raspberry functionality with RFID," International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.3, pp.40-42, 2019