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Intrusion Detection System (IDS) is a promised research field in the cybersecurity due to the rapid development of the Internet. Many IDS employ classification algorithms for classifying network traffic, and these classification algorithms failed to achieve accurate attack detection due to the huge amount of data. However, by applying dimensional reduction, data can be efficiently reduced and achieve accurate attack detection. The main work in this paper is to provide a comprehensive review of the IDS types and methods used to detect attack, advantages and disadvantages of each type. Furthermore, the authors focus on the Network Intrusion Detection System (NIDS) type and introduce the ten characteristics of Big Data and the challenges of Big Data in NIDS. Furthermore, we analyze different approaches used in NIDS based on machine learning algorithms, for each approach we study the performance of classifiers (Binary or Multi classification) under eight datasets and dimensional reduction techniques. A comparison of some machine learning algorithms and the five tools used for analyzing Big Data are presented. Discussions came from our analysis of current research. Finally, we will finish this paper by representing conclusions and describe future work

Big Data, Network Intrusion Detection System, Classification, Big Data Techniques

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Reem Alshamy, Mossa Ghurab, "A Review of Big Data in Network Intrusion Detection System: Challenges, Approaches, Datasets, and Tools," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.62-75, 2020.

English is one of the languages used throughout the world and has also been established as an international language. So the interest in learning English must start early. Children who are raised in elementary school must have been introduced to English. This paper aims to develop an educational-based chatbot and provide an evaluation of its use as a medium for learning English vocabulary for grade elementary school children using the Machine Learning method. With the dataset is the vocabulary obtained from a second grade elementary school book. The results showed that the development of chatbots could motivate elementary school children to learn English vocabulary more often

chatbot, english, elementaryschool

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K.G. Yohandi, M.I. Sani, "Designing a Mobile Chatbot For Elementary School Vocabulary," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.76-81, 2020.

The smart walking stick helps blind people to do their work easily and comfortably. To normal stick, the detection of the obstacle is extremely difficult and normal stick isn?t efficient for visually impaired persons. Because the blind person doesn?t know what sort of things happening ahead of them. It?s difficult to manoeuvre here and there. Here we use a fresh stick which uses Machine Learning and Artificial Intelligence to guide blinds on their daily lives. It Consists of Integrated Sensors for measuring distance between a vehicle and the user, and informs the user whether they can able to cross the road so they won`t have to rely on anyone to guide them. It also predicts or informs the obstacles ahead of the user, so it will help the user to understand whether there is steps or anything that causes the user fall down. This stick even has built-in Cameras and Headphone to recognize people who move towards the user, only the saved one will be recognized, new person are going to be informed to the user that ?A stranger is approaching"

Smart Blind Stick,Raspberry Pi,Ultrasonic Sensor,Face Detection,Vehicle Detection

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Beksy Anna Prasad, Athira Rachel Varghese, Roshan B., Anish George, "Smart Blind Stick Using Face Recognition," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.82-85, 2020.

Flood Rescue System will monitor the disastrous situation and share real time details with the rescuer. This is an offline communication system, by which a user can send a message in the absence of the internet and cellular data. We have developed an IoT based android application to rescue people affected in emergency situations like flood, disaster etc. The features like live location, photo sharing and information to the rescuer can be taken. The rescuers will get the details from the database of the person who needs to be rescued in the nearby area where the rescuers belong to. The rescue operation can be done in priority wise, and it will be constituted by villagers, fishermen, army etc. These rescuers will be guided to a place that is appropriate for them. This will definitely be a huge contribution to the community, for disaster management

Cellular, IoT, location

[1]Oliver M. Junio& Enrico P. Chavez, ?Development of Offline Chat Application: Framework for Resilient Disaster Management ? inferred from 978-1-5386-5514-6/18, 2018.
[2]Rakshith K & Mahesh Rae , ?Wi-Fi Enabled Device-to-Device Communications in underlying Cellular Networks? inferred from 978-1-4673-9338-6/16, 2016
[3] Neha Patel and Rucha Bhatt ?Mobile to Mobile Communication Application on Wi-Fi Grid?inferred from 978-1-5090-3745-2/16, 2016
[4] ?Image Transfer Using Modified D2d Of 5g Technologies In Adhoc Network? Senan Ali , Manjunath. S. S & Sayed Abdulhayan
[5] Iniya Shree S. , Ramya R. Arkko & Dinesh P S et al., ?Emergency Reporting using Smartphone? June 2017
[6] David K, S. Dixit, and N. Jefferies, ?2020 Vision the Wireless world Research Forum Looks to the Future,? IEEE Vehicular Technology Magazine, vol 5, September 2010.
[7] Klaus Doppler, Mika Rinne ?Device-to-Device Communication as an Underlay to LTE-Advanced Networks? IEEE Communications Magazine, December 2009.
[8] G. Sabeena Gnanaselvi ,T.V.Ananthan2 ?An Analysis of Applications, Challenges and Security Attacks in MANET ?
[9] H. Park, R. I. Ratzin, and M. van der Schaar, ?Peer-to-peer networkspro- tocols, cooperation and competition,? Streaming Media Architectures, Techniques, and Applications: Recent Advances, pp. 262?294, 2010.
[10] N. Daswani, H. Garcia-Molina, and B. Yang, ?Open problems in data- sharing peer-to-peer systems,? in International conference on database theory. Springer, 2003, pp. 1?15.
[11] Overview of D2D Proximity Services Standardization in 3GPP LTE EUCNC 2014 Workshop on radio access and spectrum, Device to Device Communication and Public Safety, Michael Gundlach, Nokia Bologna, Italy, 2014-06-23
[12] Reuse Hyang Sin Chae, Jaheon et al., ?Radio Resource Allocation Scheme for Device-t o-Device Communication in Cellular Networks Using Fractional Frequency? 2011 17th Asia-Pacific Conference on Communications (APCC) 2nd ? 5th October 2011
[13] Chia-Hao Yu, Klaus, ?Doppler Performance Impact of Fading Interference to Device-to-Device Communication Underlaying Cellular Networks? IEEE 2009
[14] Huy-Dung Han, Chenxi Zhu ?Resource Allocation and Beam forming Algorithm Based on Interference Avoidance Approach for Device-to- Device Communication Underlying LTE Cellular Network? Communications and Network, 2013

Jithin Jacob Issac, Nidina Raichel Mathew, Ranjitha Ravi, Reshma Regi, Imthiyas M.P, "Flood Rescue System Using IoT and Android Applications," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.86-91, 2020.

Information and communication technology (ICT) play a key role in rural development and the economy of a country. The present rural development strategy mainly focuses on poverty alleviation, better livelihood, provision of basic amenities and infrastructure facilities.. Usage of ICT in rural area, not only speed up the development process but also reduce the gaps between urban and rural sectors of the society. The ICT applications have lot of opportunities for rural development and will also have some challenges. It can be used to distribute its services to all - citizens, businesses, and government. ICT is changing at a rapid speed but its application in rural area is very progressing slowly, because of lack of literacy and resources. It is necessary to focus on the scope of ICT in rural development, the opportunities and the challenges [1].Major problems in rural areas are electricity, communication, transportation and lack of knowledge about new technology [2]. This paper is to focus on reviewing and analyzing interpreting existing ideas of the researchers and to explain the role of information communication technology in the rural development and to show how ICT approaches will be effective in helping the rural people for their sustainable development

Rural, e-governance , Rural development, Opportunities, Challenges

[1] Sushmita Mukherjee ?Application Of ICT in Rural Development: Opportunities and Challenges? Global Media Journal ? Indian Edition/ISSN 2249-5835 Winter Issue / Vol. 2/No.2 Decr 2011
[2] Department of Environmental Affairs ?Climate Change Adaptation : Perspectives on Urban , Rural and Coastal Human Settlements in South Africa?, Vol 4, pp. 1?72.2014
[3] Keshari Nandan Tiwari, Dr. CB Dubey, Impact of information technology in rural development: An analytical study in Allahabad, International Journal of Academic Research and Development ISSN: 2455-4197, Volume 2; Issue 1; January Page No. 01-04, 2017;
[4] Ankur Mani Tripathi et al. ? Information and Communication Technology for Rural Development? / International Journal on Computer Science and Engineering (IJCSE) Vol. 4 No. 05,pp 824-828 , May 2012
[5] Sunita ?Research development in environment , social sciences and humanity?in the preceedings of 4th annual conference on pp 109 -113, Nov 2017
[6] Charru Malhotra, V. M. Chariar, L.K. Das, and P. V. Ilavarasan , ICT for Rural Development: An Inclusive Framework for eGovernance, Indian Institute of Technology Delhi, New-Delhi, India.pp-216-226 , 2006
[7] Department of Communications (2013) South Africa Connect: Creating Opportunities Ensuring Inclusion, Electronic Communications Act No.36 of 2005..
[8] Ankita Gupta and Dr. S.S. Gautam ?ICT for Rural Development: Opportunities and Challenges? International Journal of Information & Computation Technology. ISSN 0974-2239 Volume 7, pp. 13-23 Issuer 1, 2017,
[9] Monga, A ? Opportunities and challenges ? E-government in India: JOAAG, Vol. 3. No. 2 2008
[10] V. Parashar ?Use of ICT in AgricultureInt? J. Sci. Res. in Network Security and Communication Volume-4, Issue-5, Review Paper ISSN:2321-3256.pp 8-11,Oct 2016
[11] A.Padmapriya:?E-Governance,A move towards paperless Administration in India?, International Journal of Computer Trends and Technology, Vol.4, Issue.3. 2013
[12] Andersen, K.V. and H.Z. Henriksen. (2006). E-Government maturity models: Extension of the Layne and Lee model? Government Information Quarterly, Volume 23, Issue 2 236-248,2006
[13] B S Bhagwanl, Singh Ramdeep ? Role of ICT in agricultural sector Journal of pharmacognosy and psychochemestry SPI: 665-669, 2019
[14] C. Premalatha, ? Automatic Smart Irrigation System Using IOT ? , International Journal of Scientific Research in Computer Sciences and Engineering Vol.7, Issue.1, pp.1-5, E-ISSN: 2320-7639, Feb 2019
[15] Rekha Sharma ? WSN for Computerized Irrigation System in Tea Gardens? International Journal of Scientific Research in Computer Sciences and Engineering Vol.4 , Issue.2, pp.26-30 Apr 2016
[16] Amit Palve, Amol Potgantwar ? Big Data Analysis Using Distributed Approach on Weather Forecasting Data? Int. J. Sc. Res. in Network Security and Communication ISSN: 2321-3256, Volume-5, Issue-3,, pp 39-43 .June 2017
[17] www.ecpediasolutions,com

Ramanna Havinal, "Effective Implementation of ICT for rural development: Opportunities and Challenges," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.92-97, 2020.

Machine learning plays a major role from past years in image detection, Spam recognition, normal speech command, product recommendation and medical diagnosis along it provides better customer service and safer automobile systems. This shows that ML is trend in almost all fields so we try to coined up ML in our project for betterment. Nowadays, people looking to buy a new home tend to be more conservative with their budgets and market strategies. The current systems main disadvantage is that the calculation of house prices are done without the necessary prediction about future market trends and price increase. The goal of the project is to predict the efficient house pricing for real estate customers with respect to their budgets and priorities. In the present paper we discuss about the prediction of future housing prices that is generated by machine learning algorithm. In-order to select the prediction methods we compare and explore various prediction methods. To predict the future price, the previous market trends, price ranges and also upcoming development will be analyzed. Every year House prices increase , so there is a need for a system to predict house prices in the future. We create a housing cost prediction model in view of Machine Learning algorithm models such as Lasso Regression, Ridge Regression, Ada-Boost Regression, XGBoost Regression, Decision Tree Regression, Random Forest Regression. House price prediction on a data set has been done by using all the above mentioned techniques to find out the best among them. The developer and customer will be benefited by this model on determining the selling price of a house and helps the latter to arrange the right time to purchase a house

House Price Prediction, Machine Learning, Regression

[1] P. Durganjali, M. Vani Pujitha, ?House Resale Price Prediction Using Classification Algorithms?, 2019 International Conference on Smart Structure and Systems(ICSSS), Chennai, India, 2019, pp.1-4, doi:10.1109/ICSSS.2019.8882842.
[2] Ayush Varma, Abhijit Sarma, Rohini Nair and Sagar Doshi, ?House Price Prediction Using Machine Learning And Neural Networks?, @2018 IEEE, 2018 Second International Conference on Inventive Communication and Computational Technologies(ICICCT), Coimbatore, India, DOI:10.1109/ICICCT.2018.8473231.
[3] Sifei Lu, Zengxiang Li, Zheng Qin, Xulei Yang, Rick Siow Mong Goh, ?A Hybrid Regression Technique for House Prices Prediction?, @2017 IEEE, 2017 IEEE International Conference on Industrial Engineering and Engineering Management(IEEM), Singapore, DOI:10.1109/IEEM.2017.8289904.
[4] Paul K. Asabere and Forrest E. Huffman. ?Price Concessions, Time of the Market, and the Actual Sale Price of Homes?, In: Journal of Real Estate Finance and Economics 6 (1993), pp. 167?174. https://doi.org/10.1007/BF01097024.
[5] Nihar Bhagat, Ankit Mohokar, Shreyaash Mane, ?House Price Forcasting Using Data Mining?, International Journal of Computer Applications Foundation of Computer Science(FCS),NY, USA, 2016 vol. 152- number 2 DOI:10.5120/ijca.2016.911775.
[6] Atharva chogle, Priyanka khaire, Akshata gaud, Jinal Jain, ?House Price Forecasting using Data Mining Techniques?, International Journal of Advanced Research in Computer and Communication Engineering ISO 3297:2007 Certified Vol. 6, Issue 12, December 2017, DOI:10.17148/IJARCCE.2017.61216.
[7] Steven C. Bourassa, Eva Cantoni, Martin Edward Ralph Hoesli, Spatial Dependence, ?Housing Submarkets and House Price Prediction?, The Journal of Real Estate Finance and Economics, 143-160, 2007. https://doi.org/10.1007/s11146-007-9036-8.
[8] Rakesh Kumar Saini, ?Data Mining tools and challenges for current market trends?, Journal(IJSRNSC) Vol.7, Issue.2, pp.11-14, Apr-2019. https://doi.org/10.26438/ijsrnsc/v7i2.11104.
[9] Atharva Chouthai, Mohammed Athar Rangila, Sanveed Amate, Prayag Adhikaari, Vijay Kukre, ?House Price prediction Using Machine Learning?, IRJET, Vol.6, Issue:03, Mar 2019.
[10] Thuraiya Mohd, Suraya Masrom, Noraini Johari, ?Machine Learning Housing Price Prediction in Petaling Jaya, Selangor, Malayasia?, IJRTE, ISSN:2277-3878, Vol.8, Issue-2S11, Sept 2019,Blue Eyes Intelligence Engineering & Science Publication, DOI:10.35940/ijrte.B1084.0982S1119.

Bindu Sivasankar, Arun P. Ashok, Gouri Madhu, Fousiya S., "House Price Prediction," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.98-102, 2020.

In today?s world, women come across many situations that make them feel unsafe. 66% percent of women has reported sexual harassment in the year 2010 in Delhi. In such situations, the aid of a safety device that will inform the victim?s family members or the authorities (in severe situations) may help women feel safer, confident and reduce the chances of harassment. An advanced system can be built that can capture the video of the event as well as send the emergency SMS messages of the victim to respective mobile numbers. The idea to develop a smart system for women is completely comfortable and also easy to use as compared to existing women security solutions such as infamous mobile apps, bulky belts and a separate garment that are just very abstract and obsolete

Video, SMS, Victim, Mobile

[1] B.Vijaylashmi1, Renuka.S2, Pooja Chennur3, Sharangowda.Patil4, "Self defence system for women safety with location tracking and SMS alerting through Gsm network.IJRET:International Journal of Research in Engineering and Technology ISSN: 2319-1163 ISSN: 2321-7308.
[2] Mr.Amar Saraswat Assistant Professor Department of Computer Science andEngineering, ?Sensing Heart beat and Body Temperature Digitally using Arduino?,2016.
[3] Jijesh J. J, Suraj S, D. R. Bolla, Sridhar N K and Dinesh Prasanna A, "A method for thePersonal safety in a real scenario," 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), Bangalore,2016, pp. 440-444.
[4] A.H.Ansari1, BalsarafPratiksha P.2, MaghadeTejal R.3, YelmameSnehal M.4, ?Women Security System using GSM & GPS?,Vol. 6, Issue 3, March 2017.
[5] Dr. Sridhar Mandapati, Sravya Pamidi, Sriharitha Am-bit, ?A Mobile Based Women Safety Application (I Safe Apps)?, IOSR Journal of Computer Engineering (IOSR-JCE): Jan ?Feb.2015.
[6] Madhura Mahajan, KTV Reddy, Manita Rajput ?Designand Implementation of a Rescue System for Safety of Women?, Dept. of Electronics & Telecommunication Fr. C. Rodrigues Institute of Technology Vashi, NaviMumbai, India, 2016(IEEE).
[7] Ramesh Kumar P , Srikanth , KL Sailaja ," Location Identification of the Individual based on Image Metadata?, Procedia Computer Science 8 ( 2016 ) 451 ?454.
[8] Dongare Uma, Vyavahare Vishakha and Raut Ravina, ?An Android Application for Women Safety Based on Voice Recognition?, Department of Computer Sciences BSIOTR wagholi, Savitribai Phule Pune University India, ISSN 2320?088X International Journal of Computer Science and Mobile Computing (IJCSMC) online at www.ijcsmc.com,Vol.4 Issue.3, pg. 216-220, March-2015.
[9] G C Harikiran,Karthik Menasinkai and Suhas Shirol, ?Smart Security Solution For Women Based On Internet Of Things(IOT)?, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) ? 2016 IEEE.
[10] Vaibhav A. Alone, Ashish Manusmare,? A Study Based On Women Security System?, International Journal of Science, Engineering and Technology Research (IJSETR) Volume 6, Issue 8, August 2017, ISSN: 2278 -7798.
[11] Vamil B. Sangoi, ?Smart security solutions,? International Journal of Current Engineering and Technology, Vol.4, No.5, Oct-2014.
[12] Simon L. Cotton and William G. Scanlon, ?Millimeter -wave Soldier ?to soldiercommunications for covert battlefield operation,? IEEE communication Magazine, October 2009.
[13] Alexandrous Plantelopoulous and Nikolaos.G.Bourbakis, ?A Survey on Wearable sensor based system for health monitoring and prognosis,? IEEE Transaction on system, Man and Cybernetics, Vol.40, No.1, January 2010.
[14] B.Chougula, ?Smart girls security system,? International Journal of Application or Innovation in Engineering & Management, Volume 3, Issue 4,April 2014.

Julie Elizabeth John, Neethu Prasannan, Nimra Sumayya Mahamood, Parvathy Venu, Imthiyas M.P., "Women Safety System using Internet of Things (IoT)," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.103-106, 2020.

Relentless scaling to minimum dimensions for achieving higher packing density, reduced power dissipation and aggrandized integrated circuit speed, has made CMOS a prevailing technology for very large scale integration (VLSI) applications in the last few decades. CMOS operational amplifier (Op Amp) as a building block in analogue integrated circuits and mixed signal system has compelled researchers to execute efficient designing model and its analysis. This study was aimed to accomplish the design, simulation and inquisitive behavioral analysis of a Three-Stage OP-AMP at 100 nm technology node using 1 volt as power supply (Vdd). Transfer function, input resistance, output resistance, average power, slew-rate, phase margin, DC gain and many other parameters were duly taken into consideration during simulation processes. High DC gain (69.69 dB), high bandwidth (52.619 KHz), low output resistance (25.0718 ohm.) and low power dissipation were achieved successfully by applying the designed model proposed in the present study which satisfy the requirement of highly efficient Op Amp. This CMOS-dependent-three-stage OP AMP architectonic with various promising specifications is suitable for applying in different amplifier architectures and other related designs in nano level CMOS technology

CMOS, Three-stage op-amp, Low voltage, Transistors, DC gain

[1] H. Iwai, ?Cmos Technology-Year 2010 And Beyond,? Ieee Journal of Solid-State Circuits, Vol.34, Issue.3, pp.357-366, 1999.
[2] D. Lakshmaiah, S. Pothalaiah, M. Praveen Kumar, G. Krishna Kishore, ?Theoretical Analysis of CMOS circuits in 90 nm Technology?, International Journal of Innovative Technology and Exploring Engineering, Vol.8, Isssue.4S2, pp.368-370, 2019.
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[4] P. Kakoty, ?Design of A High Frequency Low Voltage Cmos Operational Amplifier?, International Journal of Vlsi Design & Communication System, Vol.2, Issue.1, pp.73-85, 2011.
[5] R.D. Isaac, ?The Future of Cmos Technology?, IBM Journal of Research and Development, Vol.44, Issue.3, pp.369-378, 2000.
[6] J. Cheng, J.F. Jiang, Q.Y. Cai, ?Dc Gain Analysis of Scaled Cmos Op Amp in Sub-100 Nm Technology Nodes: A Research Based On Channel Length Modulation Effect?, Journal of Shanghai Jiaotong University, Vol.14, Issue.5, pp.613, 2009.
[7] B. Razavi, ?Design of Analog Cmos Integrated Circuits?, Tata McGraw-Hill Education, 2002.
[8] X. Peng, W. Sansen, ?Transconductance with Capacitance Feedback Compensation for Multistage Amplifiers?, Ieee J SolidState Circuits, Vol.40, Issue.7, pp.1514, 2005.
[9] K.M. Sudharshan, B.P. Divakar, ?Design and Simulation of Error Amplifier used in Power Management chips?, International Journal of Recent Technology and Engineering, Vol.8, Issue.4, pp. 2277-3878, 2019.
[10] R.J. Baker, ?Cmos: Circuit Design Layout, And Simulation?, John Wiley & Sons, 2019.
[11] B.K. Ahuja, ?An Improved Frequency Compensation Technique for Cmos Operational Amplifiers?, Ieee Journal of Solid-State Circuits, Vol.18, Issue.6, pp.629-633, 1983
[12] M.H. Shen, L.H. Hung, P.C. Huang, ?A 1.2 V fully differential amplifier with buffered reverse nested Miller and feed forward compensations. In the proceedings of the 2006 Ieee Asian Solid-State Circuits conference, pp.171-174, 2006.
[13] F. You, S.H.K. Embabi, E.S. Sinencio, ?A multistage amplifier topology with nested Gm-C compensation for low-voltage application?, In proceedings of the 1997 Ieee International Solids-State Circuits Conference, pp.348-349, 1997.
[14] K.N. Leung, P.K. Mok, ?Analysis of Multistage Amplifier-Frequency Compensation?, Ieee Transactions On Circuits and Systems I: Fundamental Theory and Applications, Vol.48, Issue.9, pp.1041-1056, 2001.
[15] J.S. Lee, J.H. Bae, H.Y. Kim et al., ?A Design Guide of 3-Stage Cmos Operational Amplifier with Nested Gm-C Frequency Compensation?, Journal of Semiconductor Technology and Science, Vol.7, Issue.1, pp.20-27, 2007
[16] P.L. Suryawanshi, V.R. Pawar, ?Design of Low Power Pierce Crystal Oscillator Using CMOS Technology,? International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.421-423, 2018.
[17] B. Hernes, W. Sansen, ?Distortion in Single Two-And Three-Stage Amplifiers?, IEEE Transactions on Circuits and Systems I: Regular Papers, Vol.52, Issue.5, pp.846-856, 2005.
[18] J. Solanki, Shah. Kehul, ?Design and Implementation of High Gain, High Bandwidth CMOS Folded cascode Operational Transconductance Amplifier?, International Journal of Engineering Development and Research, pp.532-536, 2014.
[19] K. Bult, G.J.G.M Geelen, ?A Fast-Settling Cmos Op Amp for Sc Circuits with 90-dB Dc Gain?, IEEE Journal of Solid-State Circuits, Vol.25, Issue.6, pp.1379-1384, 1990.
[20] M. Nizamuddin, S.A. Loan, A.R. Alamoud, S.A. Abbassi, ?Design, Simulation and Comparative Analysis of Cnt Based Cascode Operational Transconductance Amplifiers?, Nanotechnology, Vol.26, Issue.39, p.395201, 2015.
[21] S.A. Loan, M. Nizamuddin, A.R. Alamoud, S.A. Abbasi, ?Design and Comparative Analysis of High Performance Carbon Nanotube-Based Operational Transconductance Amplifiers?, Nano, Vol.10, Issue.03, pp.1550039, 2015.
[22] M.U. Vadodaria, R. Patel, J. Popat, ?Design and Implementation of High Gain, High Unity Gain Bandwidth, High Slew Rate and Low Power Dissipation CMOS Folded Cascode OTA for Wide Band Applications?, Journal of Electrical & Electronics, Vol.4, Issue.2, p.1, 2015.
[23] M. Nizamuddin, D. Sharma, ?Finfet Based Operational Transconductance Amplifier for Low Power Applications?, International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.578-581, 2019.
[24] M. Nizamuddin, S.A. Loan, S.A. Abbasi, A.R.M. Alamoud, ?Design and Simulation of High Performance Carbon Nanotube based Three Stage Operational Amplifiers?, Elsevier, materials today proceedings, Vol.3, Issue.2, pp.449 ? 453, 2016.

S. Bashiruddin, "Design and Analysis of 3 Stage OP AMP for VLSI Applications," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.107-110, 2020.

the objective of this paper is to review on soar cognitive architecture?s programming aspect.to create the intelligent agents for solving any artificial intelligence problem. we discusses the procedure with sequential steps in which soar execution cycle executes within soar programming .The purpose of this paper is to give a programmer?s fundamental understanding of how a running Soar program works, with as little theoretical baggage as possible. This will involve stepping through a program?s behaviour and describing what?s happening, with special attention to the ?hidden? parts of Soar

VisualSoar, Soar Debugger, Production Rules, Chunking, datamap, Subgoaling, States

[1] Laird, J., ?Extending the Soar Cognitive Architecture?, Artificial General Intelligence Conference, Pp 224-235, and ISBN: 978-1-58603-833-5, 2008.
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[3] Nuxoll, A. and Laird, J., ?Extending Cognitive Architecture with Episodic Memory?, 22nd National Conference on Artificial Intelligence (AAAI), 2007.
[4] John rieman., ?an introduction to soar programming?, mrc-apu 15 march 1995.
[5] John laird, A Soar`s eyeview of ACT-R, 24th soar workshop, june 2004.
[6] James, Working memory element (WME) Decay in Soar: University of Michigan, Pp 1-50
[7] Rosenbloom, P. S., Laird, J. E., & Newell, A. (1993) The Soar papers: Research on Integrated Intelligence.MIT Press, Cambridge, MA, 1993
[8] Nuxoll, Laird and james, Comprehensive working memory activation in SOAR, Pp226-230.
[9] Stuart J. Russell, Peter Norvig ,?Artificial Intelligence: Modern Approach? by Practice Hall Series in Artificial Intelligence, Pp-22-40, 2006.
[10] Laird, J. E., ?Soar9 Tutorial Part, the Soar 9 Tutorial?, University of Michigan, 1?44, 2014.
[11] Bansal. N,Srinivasan. S., March 30, 2013, ?Multi?Memory System: The Cognitive Architecture SOAR?, NCACT-2013.
[12] Nason, S., & Laird, J. E. (2005) Soar-RL: Integrating reinforcement learning with Soar. Cognitive Systems Research, 6(1),Pp 51-59, 2005.
[13] Nuxoll, A. & Laird, J. (2004). A Cognitive Model of Episodic Memory Integrated With a General Cognitive Architecture. International Conference on Cognitive Modeling 2004.
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[16] M.M. Mastoli, U.R. Pol, Rahul D. Patil, ?Reasoning with Certainty Factor for Prediction of Diabetes Disease on Machine Learning Platform,? International Journal of Scientific Research in Computer Science and Engineering, Vol.8, Issue.1, pp.93-97, 2020.
[17] A.K. Bhatia, H. Kaur, "Security and Privacy in Biometrics: A Review", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.2, pp.33-35, 2013
[18] N. SelvaKumar, M. Rohini, C. Narmada, M. Yogeshprabhu, "Network Traffic Control Using AI," International Journal of Scientific Research in Network Security and Communication, Vol.8, Issue.2, pp.13-21, 2020
[19] 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

Nitin, Brij Bhushan, S. Srinivasan, "A Review on Soar Programming," International Journal of Computer Sciences and Engineering, Vol.8, Issue.7, pp.111-115, 2020.

Vision Impairment has been treated as a deterrent to normal functioning in human beings, so for such people, it is difficult to recognize the notes. The current system uses Malaysian Ringgit banknotes and extracts RGB values from the banknotes. The algorithms used were KNN, SVM, Naive Bayes, Decision Tree, and deep learning Alexnet. The proposed system uses Indian Currency and is divided into 3 phases. In phase I four features are extracted, phase II RGB values are extracted, and finally, in phase III, phase I and phase II are concatenated to produce better results. The algorithms used are KNN, Decision tree, SVM, Naive Bayes and deep learning VGGnet. Our system provides an accuracy of 98 percent in KNN, 95 percent in Decision Tree, 100 percent in SVM and 90 percent in Naive Bayes

Banknote Recognition, Deep Learning, Machine Learning

[1] Snigdha Kamal, Simarpreet Singh Chawla, Nidhi Goel, and Balasubramanian Raman, ?Feature extraction and identification of indian currency notes?, In 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pages 1?4, IEEE, 2015.
[2] Gouri Sanjay Tele, Akshay Prakash Kathalkar, Sneha Mahakalkar, Bharat Sahoo, and Vaishnavi Dhamane, ?Detection of fake indian currency?, International Journal of Advance Research, Ideas and Innovations in Technology, 4(2):170?176, 2018.
[3] Naga Sri Ram B Yamini Radha V Rajarajeshwari P Navya Krishna G, Sai Pooja G, ?Recognition of fake currency note using convolutional neural networks?, 4(2):182?186, 2018.
[4] NAJ Sufri, NA Rahmad, NF Ghazali, N Shahar, and MA As?ari, ?Vision based system for banknote recognition using different machine learning and deep learning approach?, In 2019 IEEE 10th Control and System Graduate Research Colloquium (ICSGRC), pages 5?8, IEEE, 2019.
[5] Carlos M Costa, Germano Veiga, and Armando Sousa, ?Recognition of banknotes in multiple perspectives using selective feature matching and shape analysis?, In 2016 International Conference on Autonomous Robot Systems and Competitions (ICARSC), pages 235?240, IEEE, 2016.
[6] NA Jasmin Sufri, NA Rahmad, MA As?ari, NA Zakaria, MN Jamaludin, LH Ismail, and NH Mahmood, ?Image based ringgit banknote recognition for visually impaired?, Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-9):103?111, 2017.
[7] Hemant Kumar Soni, ?Machine Learning a?C? A New Paradigm of AI,? ?International Journal of Scientific Research in Network Security and Communication?, Vol.7, Issue.3, pp.31-32, 2019.
[8] Jesse Davis and Mark Goadrich, ?The relationship between precision, recall and roc curves?, In Proceedings of the 23rd international conference on Machine learning, pages 233?240, 2006.
[9] B. Sun and J. Li, ?The recognition of new and old banknotes based on svm?, In 2008 Second International Symposium on Intelligent Information Technology Application, volume 2, pages 95?98, 2008.
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