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Security in the mobile ad hoc network is very challenging task due the open communication, absence of centralized control and authentication mechanism. In order to handle these security and reliability issues in the MANET (Mobile Ad hoc Networks), we have proposed a group digital signature and elective curve cryptography based modified AODV (Ad hoc On Demand Distance Vector Routing) routing protocol which provides authentication and reliable communication. Proposed digital group signature method has group manager which has administrative properties like to regulate the authentication mechanism and to handle the dispute or unauthorized node and it is able to check and verify the other node authenticity. We have tested our method on the basis of packet delivery ration, network throughput and the network load. Our approach will increase the transmission reliability and reduces the packet loss chance in comparison to existing approaches

Ad-hoc networks; Security; Digital group signature; Elliptic curve cryptography; Node authentication; AODV

[1] Jeenat Sultana; Tasnuva Ahmed2017 International Conference on Electrical, Computer and Communication Engineering (ECCE)Fröhlich, B. and Plate, J. 2000. The cubic mouse: a new device for three-dimensional input. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
[2] N Chaitanya Kumar; Abdul Basit; Priyadarshi Singh; V. Ch. Venkaiah2017 International Conference on Inventive Computing and Informatics (ICICI)
[3] Elbasher Elmahdi, Seong-Moo Yoo and Kumar Sharshembiev, 2018 securing data forwarding against black hole attacks in mobile Ad-hoc network.
[4] Amit Kumar Yogi; Jayesh Surana2016 International Conference on ICT in Business Industry & Government (ICTBIG)
[5] H.S. Chiu And K.S. Lui. DelPHI: Wormhole Detection Mechanism For Ad-Hoc Wireless Networks. In Proceedings International Symposium On Wireless Pervasive Computing, Phuket, Thailand, Jan. 2006.
[6] Ming-Yang Su. Warp: A Wormhole Avoidance Routing Protocol By Anamoly Detection In Mobile Ad-Hoc Networks. Computer Security, Vol.29, March 2010.
[7] F.Stanjano, R.Anderson, “The Resurrecting Duckling: Security Issues for Ubiquitous Computing,” Vol. 35, pp. 22-26, Apr, 2002.
[8] H.L.Nguyen,U.T.Nguyen, “Study of Different Types of Attacks on Multicast in Mobile Ad-Hoc Networks,” International Conference on Networking, Systems, Mobile Communications and Learning Technologies, Apr,2006.
[9] H.Deng, W.Li and D.P.Agrawal, “Routing Security in Wireless Ad-Hoc Networks,” University of Cincinnati, IEEE Communication Magzine, Oct, 2002.
[10] N.Shanti, Lganesan and K.Ramar, “Study of Different Attacks On Multicast Mobile Ad-Hoc Network”.
[11] V.Mahajan, M.Natue and A.Sethi, “ Analysis of Wormhole Intrusion attacks in MANETs,” IEEE Military Communications Conference, pp. 1-7, Nov, 2008.
[12] S. Kannan, T. Maragatham, Attack Detection and prevention methods in Proactive and Reactive Routing protocols, International Business Management 5(3), 2011
[13] Zhang, Lili, et al. "Group signature based privacy protection algorithm for mobile ad hoc network." Information and Automation (ICIA), IEEE International Conference on, 2017.
[14] Falgun Shah and Hitul Patel, “A Survey of Digital and Group Signature”, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.6, June- 2016, pg. 274-278.

Atul Dubey, "Node Authentication in MANET by using Digital Group Signature with Elliptic Curve Cryptography," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.261-265, 2019.

Face Recognition is an application in the computer vision industry .Many algorithms has been developed in order to achieve facial recognition with most accuracy. Face recognition is less sturdy than other biometric scanning systems like fingerprint and retina scanning. This report describes the face detection and recognition minor-project developed for the attendance system of the department where a student can view his attendance on the dates present and teacher can check the attendance and save it in pdf format. This project uses the technologies available in the OpenComputerVision (OpenCV) library in java interface and methods to implement them using . This project is accomplished using Haar-Cascades for face detection and Local binary pattern histograms(LBPH) for face recognition. The process is represented together with flow charts for every stage of the system. Next, the results are shown using screen-shots.

Facial Recognition, Local Binary Patterns Histograms, Facial detection, Haar features, Computer Vision, OpenCV

[1] Ayushi gupta, Ekta Sharma, Neha sachan and neha Tiwari, “Door Lock System through Face Recognition Using MATLAB”, IJSRCSE (International Journal of Scientific Research in Computer Science andEngineering), 2013
[2] Face Recognition Based on HOG and Fast PCA Algorithm Xiang-Yu Li(&) and Zhen-Xian Li
[3] Dinalankara, Lahiru. (2017). Face Detection & Face Recognition Using Open Computer Vision Classifies.
[4] Study of Various Face Detection Methods , Ms.Varsha Gupta1 , Mr. Dipesh Sharma2,ijarcce vol.3
[5] Prabhjot Singh1 and Anjana Sharma “Face Recognition Using Principal Component Analysis in MATLAB” ”, IJSRCSE (International Journal of Scientific Research in Computer Science andEngineering), vol 3,issue 1 2014
[6]. Kelvin Salton do Prado “Face Recognition: Understanding LBPH Algorithm” towardsdatascience.com
[7] Nicolas Delbiaggio “A comparison of facial recognition’s algorithms “ Hagga-Helia university of applied science
[8] Ahonen, Timo, Abdenour Hadid, and Matti Pietikäinen. “Face recognition with local binary patterns.” Computer vision-eccv 2004 (2004): 469–481.
[9] Matti Pietikäinen (2010) Local Binary Patterns. Scholarpedia, 5(3):9775

Anjana Pandey, Kanika Gupta, Shivang Agrawal, "Automatic Attendance Recording Using Face Recognition," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.266-275, 2019.

Plants plays important role in our lives, as it provides us food and oxygen which is needed by all living things. There are thousands of kinds of trees in this world, and it is very difficult to distinguish between them. Experts can however identify by using characteristics of leaves but a common man cannot. Recognition of Plant from images is a challenging computer vision task. Proposed System is deployed to classify Indian local leaves automatically using deep learning. Deep Learning is a self-learning technique used for massive data and recent development in hardware and big data have turned out as a blessing. We have considered 10 different Indian plants leaves. Recognition rate of proposed system is 93%.

Indian leaf, Plant Recognition, Machine Learning, Deep Learning, and VGG 16

[1] James S.Copea ,DavidCorney ,Jonathan Y.Clark ,PaoloRemagninoa and Paul Wilkinc, “Plant species identification using digital morphometrics: A review”Expert Systems with Applications Volume 39, Issue 8, 15 June 2012
[2] Neeraj Kumar ,Peter N Belhumeur, Arijit Biswas, David W Jacobs, W John Kress, Ida C Lopez and Joao VB Soraes “Leafsnap: A Computer Vision System for Automatic Plant Species Identification”,inECCV,pp 502-516. Springer,2012
[3] JyotismitaChaki, Ranjan Parekh, Samar Bhattacharya, “Plant Leaf Recognition Using a Layered Approach” , 978-1-4673-6621-2/16/$31.00 © 2016IEEE
[4] T L I Sugata and C K Yang ,”Leaf App: Leaf recognition with deep convolutional neural networks” ,IOP Conference Series: Materials Science and Engineering, Volume273.
[5] Aparajita Sahay and Min.”Leaf Analysis for Plant Recognition”, 978-1-4673-9904-3/16/$31.00 ©2016IEEE
[6] .H.Rankothge , D.M.S.B Dissanayake, U.V.K.T Gunathilaka, S.A.C.M Gunarathna, C.M Mudalige and R.P, PlantRecognitionSystemBasedonNeuralNetworks”,
ICATE 2013
[7] Bin Wang,, Douglas Brown, Yongsheng Gao, John La Salle, “Mobile Plant Leaf Identification using smartphones”, 978-1-4799-2341-0/13/$31.00 ©2013IEEE
[8] Wang-Su Jeon, and Sang-Yong Rhee, “Plant Leaf Recognition Using a Convolution Neural Network”, I nt. J. Fuzzy Log. Intell. Syst. 2017;17(1):26-34 published online March 31,20
[9] Du, JX, Wang, XF, and Zhang, GJ (2007). “Leaf shape based plant species recognition”. Applied Mathematics and Computation..Volume 185, Issue 2, 15 February 2007, Pages 883-893
[10] Deepali Naglot, Milind Kulkarni “Real Time Sign Language Recognition using the Leap Motion Controller”, 2016 International Conference on Inventive Computation Technologies (ICICT),26-27 Aug.2016
[11] R. Priyadharshini, G. B. Nivetha, G. Kausalya, P. Anantha Prabha , "Fungus Detection using Convolutional Neural Networks", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5 Issue 2, pp. 205-209, March-April 2019.
[12] Prashant Udawant, Atul Patidar, Abhijeet Singh, Atyant Yadav, "Comparative Study of Artificial Intelligence Techniques for Image Classification", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456- 3307, Volume 5 Issue 2, pp. 904-910, March-April 2019.

Deepali Naglot,Prachi Sandeep Kasliwal, Swati Jayaji Gaikwad, Nisha Deepak Agrawal, "Indian Plant Recognition System Using Convolutional Neural Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.276-280, 2019.

We live in a country where the incidents of ambulances not reaching on time are indicative enough of the dismal state of transportation for patients in need of emergency care across the country. Delhi, a city of 22 million people, has only 152 state-run ambulances. More than 20 percent of patients needing emergency treatment have died on their way to the hospital because of delays due to traffic jams. in Delhi, an ambulance takes an average of 27 minutes to reach the site. Response time can even extend into hours. Seeing the current scenario of traffic, time taken is only going to increase. And yet, no steps are being taken to improve the situation. Measures of optimizing ambulance response time prove to be widely unsuccessful due to the lack of a targeted approach. This results in sub-optimal allocation of already overstretched healthcare resources. In 2017 alone, there were more than 8,000 road accidents in Delhi. Ironically enough, about 3,000 accidents led to deaths due to ambulances not reaching on time as they were stuck in Delhi’s traffic. By virtue of the factors discussed above, there arises a need for a scientific approach to optimizing the ambulance response time.

Mathematical model, response optimization, speed-density equation. algorithmic paradigms

[1] K. Saha, S. Rathee “Agent- Based Traffic Simulator for Autonomous Vehicles” International Journal of Scientific Research in Computer Science and Engineering Vol.5, Issue.2, pp.42-45, 2017
[2] K. Saha, S. Rathee “Agent- Based Traffic Simulator for Autonomous Vehicles” International Journal of Scientific Research in Computer Science and Engineering Vol.5, Issue.2, pp.42-45, 2017

Sarthak Khanna, "Ambulance Response Optimization," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.281-286, 2019.

Quality Analysis of Storage Drives is an important thing to be done before actual use of drives in the market. Finding the failure reason of drives and reporting it in an automated way is a challenging work to do. There is no direct solution available to find the actual cause of failure, the cause of failure can be related to drives, firmware, or testing environment. So using various techniques such as drive analysis based upon various parameters of hard disk drive we can predict the cause of failure. Storage drives are important component of any computing devices which needs to be analyzed using different techniques. This paper is an attempt to explore the quality analysis of storage drives.

Quality Analysis, Drives Security, Performance, Drive analysis

[1] Tom Coughlin, Roger Hoyt, and Jim Handy ”Digital Storage and Memory Technology (Part 1)” IEEE Advancing Technology for humanity.(2017)
[2] RINO MICHELONI, Senior Member IEEE”SCANNING THE ISSUE Solid-State Drives (SSDs)”(2017)
[3] Raja Subramani, BharathRadhakrishnan, Krishnamurthy Puttaiah(2013) “Complete Device Level Validation of Solid State Flash Drives – An Approach” IEEE 15th International Conference on Computer Modelling and Simulation
[4] Nematollah Bidokhti “SSD Next Gen RDT” Annual Reliability and Maintainability Symposium.(2016)
[5] “Data Security Features for SSDs” A MICRON WHITE PAPER
[6] Iyswarya Narayanan, Di Wang, Myeongjae Jeon, Bikash Sharma, Laura Caulfield, AnandSivasubramaniam, Ben Cutler, Jie Liu, BadriddineKhessib, KushagraVaid.(2016) “SSD Failures in Datacenters: What? When? and Why?” ACM 978-1- 4503-4381-7/16/06.
[7] Dongho Won (2007) ”Vulnerability Analysis of Secure USB Flash Drives” IEEE
[8] Sonali Patra, N C Naveen, Omkar Prabhakar(2016) “An AutomatedApproach For Mitigating Server Security Issues” IEEE International Conference On Recent Trends In Electronics Information Communication Technology

Rakesh S. Surve, Vikas N. Honmane, "Quality Analysis of Storage Drives," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.287-290, 2019.

The network is moving towards the wired to wireless. It has created a great challenge in the design and implementation of the networks. The Medium Access Control (MAC) protocol of the IEEE 802.11 standard plays a major role in the management and coordination of shared channel access and data transmission. This research work focuses on developing new efficient model to enhance the DCF that improves the performance of WLANs. The data rate of the node with packet size is considered and new Multi Priority DCF (MP-DCF Algorithm) is proposed. The proposed scheme decreases the delay and increases the throughput.

WLAN, DCF, MDCF, Multi Priority DCF, delay, throughput

[1] Anders Lindgren, Andreas Almquist, Olov Schelen, “Quality of Service Schemes for IEEE 802.11 Wireless LANs – An Evaluation”, Mobile Networks and Applications, Kluwer Academic Publishers, 223–235, 2003.
[2] Yang Xiao, “Enhanced DCF of IEEE 802.11e to Support QoS”, IEEE, 2003.
[3] Jochen H. Schiller, “Mobile Communications”, Second Edition, Pearson Education Limited, 2003.
[4] S. Rajesh Kumar, “Improving the Efficiency of Wireless Multi-Hopping of MPEG-4 AVC Video Stream in WAN”, International Journal of Computer Sciences and Engineering, Volume-3, Issue-5, 2015.
[5] Sanjaya Gupta, Vijay Sahu, Brejesh Lall, “Modified Isochronous Coordination Function for Enhancement of VoIP Call Capacity over IEEE 802.11 WLAN”, Hindawi Publishing Corporation, EURASIP Journal on Wireless Communications and Networking, Volume 2008.
[6] Md. Atiur Rahman Siddique and Joarder Kamruzzaman, “Performance Analysis of PCF based WLANs with Imperfect Channel and Failure Retries”, IEEE Communications Society , IEEE Globecom 2010 Proceedings, 2010.
[7] Md. Abbas Ali Khan, Khalid Been Md. Badruzzaman Biplob and Md. Sadekur Rahman, “A Study on Delay, Throughput and Traffic Measurement for Wi-Fi Connected Stations Based on MAC Sublayer”, American Journal of Computer Science and Engineering Survey, AJCSES[4][2], 019-028, 2016.
[8] Hazem Noori Abdulrazzak, Aya Ayad Hussein, “Performance Analysis of CSMA/CA Based on D2D Communication”, International Journal of Computer Sciences and Engineering, Vol.-7, Issue-2, Feb 2019.
[9] Brian P. Crow, Indra Widjaja, Jeong Geun Kim, Prescott T. Sakai, “IEEE 802.11 Wireless Local Area Networks”, IEEE Communications Magazine, September 1997.
[10] Haniyeh Kazemitabar, Sameha Ahmed, Kashif Nisar, Abas B Said, Halabi B Hasbullah, “A Survey on Voice over IP over Wireless LANs”, World Academy of Science, Engineering and Technology 71, 2010.
[11] Alok K. Jangid, Naresh Sharma, “Modified DCF for Throughput Enhancement in WLAN”, 2008.
[12] Rama Krishna Challa, Saswat Chakrabarti, Debasish Datta, “An Improved Analytical Model for IEEE 802.11 Distributed Coordination Function under Finite Load”, Int. J. Communications, Network and System Sciences, 3, 169-247, 2009.
[13] Woo-Yong Choi, “Enhancing MAC performance of DCF protocol for IEEE 802.11 wireless LANs”, Journal of ELECTRICAL ENGINEERING, VOL 68, NO1, 83–86, 2017.
[14] L. Zheng M. Ni, L. Cai, J. Pan, C. Ghosh, K. Doppler, “Performance Analysis of Group - Synchronized DCF for Dense IEEE 802.11 Networks”, IEEE Transactions on Wireless Communications, Volume 13, Issue: 11, Nov. 2014.
[15] Li Feng, Jiguo Yu, Xiuzhen Cheng and Shengling Wang, “Analysis and optimization of delayed channel access for wireless cyber-physical systems”, Feng et al. EURASIP Journal onWireless Communications and Networking, 2016
[16] Ikram Syed and Byeong-hee Roh, “Adaptive Backoff Algorithm for Contention Window for dense IEEE 802.11 WLANs”, Hindawi Publishing Corporation Mobile Information Systems Volume 2016, Article ID 8967281, 2016
[17] Chand T. and Srivastava V., “Analysis and Performance Evaluation of Technique to Increase the Call Capacity of WLAN”, International Journal of Computer Technology and Electronics Engineering, 2(3), 154-158, 2012.
[18] Maali Albalt, Qassim Nasir, “Adaptive Backoff Algorithm for IEEE 802.11 MAC Protocol”, Int. J. Communications, Network and System Sciences, , 4, 249-324, 2009.
[19] Idigo V.E, Okezie C.C, Nnebe S.U, Onwubalili C, “Performance Evaluation of IEEE 802.11 Distributed Coordination Function (DCF) in a Multi-Rate WLAN”, International Journal of Engineering and Innovative Technology (IJEIT), Volume 1, Issue 5, May 2012.
[20] Haithem Al-Mefleh, J. Morris Chang, “High Performance Distributed Coordination Function for Wireless LANs”, IFIP International Federation for Information Processing, pp. 812–823, 2008.
[21] Manjusha Mathew, Mary John, “Performance Analysis of IEEE 802.11 Modified Distributed Coordination Function for Wireless LANs Based on Data rate”, IOSR Journal of Computer Engineering (IOSR-JCE), e-ISSN: 2278-0661, Volume 16, Issue 6, Ver. VII, PP 08-13, (Nov – Dec. 2014)
[22] Seyed Davoud Mousavi, Rasool Sadeghi, Mohamadreza Karimi, Erfan Karimian and Mohammad Reza Soltan Aghaei, “A Fair Cooperative MAC Protocol in IEEE 802.11 WLAN”, www.mdpi.com/journal/futureinternet, Future Internet, 10, 39, 2018.
[23] Keerthi D, Shobha Rani, Basavaraju T, “Delay-Based Routing Mechanism for Load Balanced Routing in Wireless Mesh Networks”, www.ijcseonline.org/IJCSE-07142-12, Vol.-7, Issue-5, May 2019 E-ISSN: 2347-2693.
[24] Syed Muqtar Ahmed1, Syed Abdul Sattar, “Detection of Collaborative Wormhole Attack in Wireless Mobile Adhoc Network”, www.ijcseonline.org/, Vol.-7, Issue-5 ,May2019 E-ISSN: 2347-2693.

Savitri Sharma, Vishnu Sharma, Ankur Goyal, "QoS Analysis of Multi Priority DCF Algorithm in Wireless Local Area Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.291-294, 2019.

In Image encryption scheme, the permutation operation plays an important role in confusing the pixels of image and is used in combination with diffusion operation. This paper proposes an efficient 3D permutation strategy for color image that is free from sorting operation and is based on Lorenz map. It has good confusion properties than permutation algorithms that do not involve sorting operation and in comparison to permutation algorithms with similar security that involves use of sorting operation, the proposed method has lower complexity. Performance and Security of proposed permutation algorithm are analysed and results further justify that the permutation scheme is secure is computationally efficient for application in image encryption scheme.

Image Scrambling, 3D Lorenz system, Random number generator, Encryption, Complexity

[1] Y. Patil and P. Deshmukh, “A review: Mobile cloud computing: Its challenges and security,” International Journal of Scientific Research in Network Security and communication, vol. 6, no. 1, pp. 11–13, 2018.
[2] P. Devi, “Attacks on cloud data: A big security issue,” International Journal of Scientific Research in Network Security and communication, vol. 6, no. 2, pp. 15–18, 2018.
[3] L. Chen, S. Tang, Q. Li, and S. Zhong, “A new 4D hyperchaotic system with high complexity,” Mathematics and Computers in Simulation, vol. 146, pp. 44–56, 2018.
[4] N. Yujun, W. Xingyuan, W. Mingjun, and Z. Huaguang, “A new hyperchaotic system and its circuit implementation,” Communications in Nonlinear Science and Numerical Simulation, vol. 15, no. 11, pp.3518–3524, 2010.
[5] A. Jain and N. Rajpal, “A robust image encryption algorithm resistant to attacks using DNA and chaotic logistic maps,” Multimedia Tools and Applications, vol. 75, no. 10, pp. 5455–5472, May 2016.
[6] G. Chen, Y. Mao, and C. K. Chui, “A symmetric image encryption scheme based on 3D chaotic cat maps,” Chaos, Solitons & Fractals, vol. 21, no. 3, pp. 749–761, 2004.
[7] K. Wang, L. Zou, A. Song, Z. He et al., “On the security of 3D cat map based symmetric image encryption scheme,” Physics Letters A, vol. 343, no. 6, pp. 432–439, 2005.
[8] F.-G. Jeng, W.-L. Huang, and T.-H. Chen, “Cryptanalysis and improvement of two hyper-chaos-based image encryption schemes,” Signal Processing: Image Communication, vol. 34, pp. 45–51, 2015.
[9] K. Panwar, R. Purwar, and A. Jain, “Cryptanalysis and improvement of a color image encryption scheme based on DNA sequences and multiple 1D chaotic maps,” International Journal of Bifurcation and Chaos, 2019 (in press).
[10] K. Panwar, R. K. Purwar, and A. Jain, “Cryptanalysis of an image encryption scheme using reverse 2-dimensional chaotic map and dependent diffusion,” in the proceedings of 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN), IEEE, Feb 2018, pp. 236–239.
[11] A. Gerosa, R. Bernardini, and S. Pietri, “A fully integrated chaotic system for the generation of truly random numbers,” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 49, no. 7, pp. 993–1000, 2002.
[12] L. Kocarev and G. Jakimoski, “Pseudorandom bits generated by chaotic maps,” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 50, no. 1, pp. 123–126, 2003.
[13] C. Li, S. Li, M. Asim, J. Nunez, G. Alvarez, and G. Chen, “On the security defects of an image encryption scheme,” Image and Vision Computing, vol. 27, no. 9, pp. 1371–1381, 2009.
[14] C. Li, D. Lin, and J. L¨u, “Cryptanalyzing an image-scrambling encryption algorithm of pixel bits,” IEEE MultiMedia, vol. 24, no. 3, pp. 64–71, 2017.
[15] Q. Yin and C. Wang, “A new chaotic image encryption scheme using breadth-first search and dynamic diffusion,” International Journal of Bifurcation and Chaos, vol. 28, no. 04, p. 1850047, 2018.
[16] H. Zhu, X. Zhang, H. Yu, C. Zhao, and Z. Zhu, “An image encryption algorithm based on compound homogeneous hyper-chaotic system,” Nonlinear Dynamics, vol. 89, no. 1, pp. 61–79, 2017.
[17] F. O¨ zkaynak and A. B. O¨ zer, “A method for designing strong s-boxes based on chaotic Lorenz system,” Physics Letters A, vol. 374, no. 36, pp. 3733–3738, 2010.
[18] M. Moghtadaei and M. H. Golpayegani, “Complex dynamic behaviours of the complex lorenz system,” Scientia Iranica, vol. 19, no. 3, pp. 733– 738, 2012.
[19] C. Li, M. Z. Chen, and K.-T. Lo, “Breaking an image encryption algorithm based on chaos,” International Journal of Bifurcation and Chaos, vol. 21, no. 07, pp. 2067–2076, 2011.
[20] C. Li, D. Lin, B. Feng, J. L¨u, and F. Hao, “Cryptanalysis of a chaotic image encryption algorithm based on information entropy,” IEEE Access, vol. 6, pp. 75 834–75 842, 2018.
[21] C. Li, B. Feng, S. Li, J. Kurths, and G. Chen, “Dynamic analysis of digital chaotic maps via state-mapping networks,” IEEE Transactions on Circuits and Systems I: Regular Papers, 2019.
[22] Z. Li, C. Peng, L. Li, and X. Zhu, “A novel plaintext-related image encryption scheme using hyper-chaotic system,” Nonlinear Dynamics, vol. 94, no. 2, pp. 1319–1333, 2018.
[23] Z. Galias and W. Tucker, “Short periodic orbits for the lorenz system,” in the proceedings of 2008 International Conference on Signals and Electronic Systems. IEEE, pp. 285–288, 2008.
[24] K. Panwar, R. Purwar, and A. Jain, “Cryptanalysis and improvement of an image encryption scheme using combination of one-dimensional chaotic maps,” Journal of Electronic Imaging, vol. 27, no. 5, pp. 1 –18, 2018.

K. Panwar, R.K. Purwar, "Design and Analysis of a Permutation Strategy using 3D Chaotic Map," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.295-299, 2019.

In this omnipresent IT world even the non-living items communicate amongst themselves and smartly react depending on dynamic situations. IOT (Internet of Things) is a technology which is highly emerging that understands and conceptualizes this nature of computing. The paper gives a brief review on water bottle using IOT technology. Water is very important part of human life. Variety of parameters effect the quality of water. The smart bottle monitors these parameters constantly in real time using input sensors, the system then processes the input data and performs necessary actions if required using actuators. This system will be helpful for health conscious human beings in today’s life. This system can also be greatly utilized in healthcare domain where extra care needs to be taken in all aspects.

Sensors, Actuators, IOT, Internet of Things, Smart Water Bottle

[1] Mohammad Abdur Razzaque, Marija Milojevic-Jevric, Andrei Palade, and Siobhán Clarke, Middleware for Internet of Things: A Survey, IEEE INTERNET OF THINGS JOURNAL, VOL. 3, NO. 1, FEBRUARY 2018,70-95.
[2] Jianli Pan, Raj Jain, Subharthi Paul, TamVu, Abusayeed Saifullah, andMo Sha, An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype and Experiments, IEEE INTERNET OF THINGS JOURNAL, VOL. 2, NO. 6, March 2018,527-537.
[3] Luca Catarinucci, Danilo de Donno, Luca Mainetti, Luca Palano, Luigi Patrono, Maria Laura Stefanizzi, and Luciano Tarricone, An IoT-Aware Architecture for Smart Healthcare Systems, IEEE INTERNET OF THINGS JOURNAL, VOL. 2, NO. 6, March 2018, 515-526.
[4] 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, FEBRUARY 2018,22-32.
[5] Guidelines for drinking water quality.(2018,July 09). [Online] Available http://www.who.int/water_sanitation_health/dwq/gdwqvol32ed.pdf
[6] Drinking water quality surveillance program (2018,July 09). [Online] Available : http://kmam.moh.gov.my/public-user/drinking-water-quality-standard.html
[7] Drinking water Standards(2018, July 10)[Online] Available : https://en.wikipedia.org/wiki/Drinking_water_quality_standards
[8] Thoraya Obaid, HaleemahRashed, Ali Aou-Elnour, Muhammad Rehan, Mussab Muhammad Saleh, and Mohammed Tarique, ZIGBEE TECHNOLOGY AND ITS APPLICATION IN WIRELESS HOME AUTOMATION SYSTEMS: A SURVEY, International Journal of Computer Networks & Communications (IJCNC) Vol.6, No.4, July 2014,115-131.
[9] Smart Water Sensors to monitor water quality in rivers, lakes and the sea | Libelium(2018,July 09)[Online] Available :http://www.libelium.com/smart-water-sensors-to-monitor-water-quality-in-rivers-lakes-and-the-sea/
[10] Sangeetha Rajesh, Saurabh Jadhav, Neha Singh, Ubiquitous Aquarium Management System,IOSR Journal of Computer Engineering (IOSR-JCE), e-ISSN: 2278-0661,p-ISSN: 2278-8727, July 2018, 66-69

Sonali Vishwakarma, Anushree Goud, "A Literature Review on: Smart Bottle using IOT," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.300-302, 2019.

Power and speed are the two important design aspects that impact the designing of any circuits. One of the most widely used arithmetic operation in digital circuits is Multiplication. There are different Multipliers designed depending on the speed and the hardware. There are different technologies with different features. In this paper 4- bit and 8- bit Array Multipliers are been designed using different designing techniques. The Multipliers are designed using CMOS Logic Configuration, Pseudo-NMOS Logic Configuration and Transmission gate Logic Configuration and are compared in terms of Power and delay. The Power Delay Product (PDP) gives the overall performance of the Multipliers.

Multiplier, CMOS Logic, Pseudo-NMOS Logic, Transmission Gate Logic, Power, Delay

[1] A. P. Chandrakasan, S. Sheng, and R. W. Brodersen, Low power CMOS digital design, IEEE J. Solid-State Circuits, vol. 27, pp. 473–484, 1992.
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[3] I. S. A. Khater, A. Bellaouar, and M. I. Elmastry, Circuit techniques for CMOS low power high-performance multipliers, IEEE J. Solid-State Circuits, vol. 31, pp. 1535–1546, 1996.
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[5]R. Zimmermann and W. Fichtner, Low power logic styles: CMOS versus pass transistor logic, IEEE J. Solid State Circuits, vol. 32, pp. 1079– 1090, 1997.
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Swetha B N, Satish Kumar B, "Performance Analysis of Array Multipliers Using Different Logic Configurations," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.303-306, 2019.

The main objective behind this paper was to provide a brief overview about some of the well-known multiplication algorithms and design an Arduino based calculator working on the principles of the Booth’s multiplication Algorithm in the simplest and cheapest possible way. Our study surrounds some of the algorithms that existed before and around the time when Booth’s multiplication Algorithm came into the scene. The study found that each of the algorithms had some problems which ultimately galvanized the popularity of the Algorithm proposed by Arnold Donald Booth. The calculator we designed is capable of taking a four-bit binary multiplier and a four-bit binary multiplicand as input and will produce the product in an eight-bit sequence as the output. The calculator is basically constructed with the help of a central controlling Arduino connected to various input and output specified electronic components such as push buttons and LEDs. The circuit constructed to perform the algorithm is the simplest possible circuit. The input to the Arduino can be given from the hardware itself and the output also gets reflected through the hardware.

Arduino, Booth’s Algorithm, Multiplier, Multiplicand, Internet of Things, Multiplication algorithms, Calculator, Algorithm, LSB, MSB, Partial Product, Left Shift (LS), Right Shift (RS)

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Kushankur Ghosh, Arghasree Banerjee, "A Brief Study and An Arduino Based Implementation of Booth’s Multiplication Algorithm," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.307-313, 2019.