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The theory of finite automata, formal languages and complexity are the modern branches in the field of computer theory and their mathematical models play a very important role in the practical world. This makes it really important, in theory as well as practice to translate a Non-deterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA). Many different approaches are developed for doing so. In this paper, an optimized algorithm for transition from NFA to DFA is given. This method is implemented using the programming language called python3. Along with this we have also used the pandas library of python for constructing the transition tables for NFA as well as DFA. A website for the same is also created to make it more user friendly by using the streamlit library of python.

DFA, Finite Automata, NFA, NFA to DFA, Streamlit Web Application

[1] Jing Maohua, G.-R. Li, W.-B. Shi, S.-X. Cai, “Improved conversion algorithm from NFA to DFA”, Dongbei Daxue Xuebao/Journal of Northeastern University, Vol.33(4), April 2012.
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[5] K. Salomaa, S. Yu, “NFA to DFA conversion for finite languages”, Lecture Notes in Computer Science, pp.149-158, 2006.
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[8] Raza, Mir Adil, Kuldeep Baban Vayadande, and H. D. Preetham. "DJANGO MANAGEMENT OF MEDICAL STORE.", International Research Journal of Modernization in Engineering Technology and Science, Vol.2, Issue.11, November 2020.
[9] K.B. Vayadande, Nikhil D. Karande,” Automatic Detection and Correction of Software Faults: A Review Paper”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653, Vol.8, Issue.4, April 2020.
[10] Kuldeep Vayadande, Ritesh Pokarne, Mahalaxmi Phaldesai, Tanushri Bhuruk, Tanmai Patil, Prachi Kumar, “SIMULATION OF CONWAY’S GAME OF LIFE USING CELLULAR AUTOMATA” International Research Journal of Engineering and Technology, Vol.9, Issue.1, Jan 2022, e-ISSN: 2395-0056, p-ISSN: 2395-0072.
[11] Kuldeep Vayadande, Harshwardhan More, Omkar More, Shubham Mulay, Atharva Pathak, Vishwam Talnikar, “ Pac Man: Game Development using PDA and OOP”, International Research Journal of Engineering and Technology (IRJET), Volume: 09 Issue: 01 | Jan 2022, e-ISSN: 2395-0056, p-ISSN: 2395-0072.

Kuldeep Vayadande, Krisha Patel, Nikita Punde, Shreyash Patil, Srushti Nikam, Sudhanshu Pathrabe, "Non-Deterministic Finite Automata to Deterministic Finite Automata Conversion by Subset Construction Method using Python," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.1-5, 2022.

The paper focuses a comprehensive review on implementation of e-Tendering solution in comparison to the conventional envelop-Box (manual Tendering) method in the State of Goa (India). Some of the key issues like Comparative analysis of pre-deployment and post deployment scenarios with the launch of e-Tendering Solution, highlighting the day-to-day problems faced by the System Users. And also, to consider the best practices that can be followed in improving rollout of e-Tendering solution. The study inferred that in spite of several challenges, how Vendors/Contractors and Departmental Users has accepted the e-Tendering system over manual tendering. This research paper is based on the descriptive and exploratory methods used for analysis of collected responses as the primary data for the study from Vendors/Contractors and Departmental Users through the online mode. This paper has targeted the end user of the e-Tendering solution their day-to-day issues and challenges and describing the advancement made by the Government for easy run of Tendering system.

e-Procurement, e-Tender, Goa, Government, Vendors, Contractors, e-Payment

[1] Dr. Shruti Singh, Rubee Singh, “Impact of E-Governance in India: Opportunities & Challenges”, International Journal for Innovative and Management Research, Vol 07 Issue07, Jun 2018
[2] Nilesh B. Fal Dessai, Gaurav A. Naik, Vinay B. P., “e-Tendering Solution with e-Payment Integration for the State of Goa”, International Conference Series on Theory and Practice of Electronic Governance(ICEGOV`17) :March 2017.
[3] Circular bearing No. 7/13/2011/Fin-Exp dated 07/06/2011 issued by Government of Goa, Finance (Expenditure) Department, Secretariat, Porvorim-Goa.
[4] Circular bearing No. 7/13/2011/Fin-Exp dated 13/10/2011 issued by Government of Goa, Finance (Expenditure) Department, Secretariat, Porvorim-Goa.
[5] Circular bearing No. 7(314)/2009/DOIT/e- Tendering/e-Procurement/849 dated 04/08/2011 issued by Department of Information Technology, Government of Goa.
[6] Circular bearing No 7(373)2011/DOIT/e-Procurement correspondence/1053 dated 17/10/2019 issued by Department of Information Technology, Government of Goa.
[7] https://goaenivida.gov.in Goa e-Nivida e-Tendering portal
[8] https://infotech.goa.gov.in Info Tech Corporation of Goa Limited, Government of Goa Undertaking
[9] Vinit Parida, Kittipong Sophonthummapharn, Upasana Parida, “Understanding E-procurement: Qualitative Case Studies.
[10] Funlade T. Sunmolaa, Yusuf U. Shehua, “A Case Study on Performance Features of Electronic Tendering Systems”,30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021)
[11] K Bikshapathi, P Raghuveer, “Implementation of e-procurement
in the Government of Andhra Pradesh: A Case Study”,
[12] Sara Belisari, Daniele Binci, Andrea Appolloni, “E-Procurement Adoption: A Case Study about the Role of Two Italian Advisory Services”, Sustainability 2020, 12, 7476; doi:10.3390/su12187476
[13] Ewa Roszkowska , “Rank Ordering Criteria Weighting Methods – A Comparative Overview”, Jan 2013
[14] Mukhtar A. Kassem, Muhamad Azry Khoiry, Noraini Hamzah, “Using Relative Importance Index Method for Developing Risk Map in Oil and Gas Construction Projects”, Jurnal Kejuruteraan 32(3) 2020: 85-97
[15] Rakesh Rana, Richa Singhal, “Chi?square Test and its Application in Hypothesis Testing”, Journal of the Practice of Cardiovascular Sciences • January 2015
[16] Dr. Jenny V. Freeman, Steven A. Julious, “The visual display of quantitative information”, Book

Gaurav A. Naik, Vinita Korgaonkar, "Study of e-Tendering Solution Implemented by Government of Goa," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.6-12, 2022.

This article describes a JavaScript and GUI-based visualization tool for constructing, debugging, and testing DFA that can be utilized in the automata theory classroom. In automata, DFA is an important problem. What DFA is, DFA refers to deterministic finite automata. Deterministic refers to the uniqueness of the computation. If the machine reads an input string one symbol at a time, the finite automata are termed deterministic finite automata. In DFA, there is only one path from the current state to the next state for specific input. The null move is not accepted by DFA, which means it cannot change the state without any input character. Multiple final states can be found in DFA. Like other automata visualization tools, users can edit and construct DFA by adding states and transitions and can observe transition execution by providing string input for testing. This DFA simulator allows users to construct DFA by adding states, marking any state as a final state, and also checking for string if it is valid for constructed DFA or not.

HTML, CSS, jQuery, JavaScript, Bootstrap CSS, finite automata, visualization, simulator

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[7] Raza, Mir Adil, Kuldeep Baban Vayadande, and H. D. Preetham. "DJANGO MANAGEMENT OF MEDICAL STORE.", International Research Journal of Modernization in Engineering Technology and Science, Volume:02 Issue:11 November -2020
[8] K.B. Vayadande, Nikhil D. Karande,” Automatic Detection and Correction of Software Faults: A Review Paper”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653, Volume 8 Issue IV Apr 2020.
[9] Kuldeep Vayadande, Ritesh Pokarne, Mahalaxmi Phaldesai, Tanushri Bhuruk, Tanmai Patil, Prachi Kumar, “SIMULATION OF CONWAY’S GAME OF LIFE USING CELLULAR AUTOMATA” International Research Journal of Engineering and Technology (IRJET), Volume: 09 Issue: 01 | Jan 2022, e-ISSN: 2395-0056, p-ISSN: 2395-0072
[10] K. B. Vayadande, N. D. Karande, and S. Yadav, “A review paper on detection of moving object in dynamic background,” International Journal of Computer Sciences and Engineering, vol. 6, no. 9, pp. 877–880, 2018.
[11] Varad Ingale, Kuldeep Vayadande, Vivek Verma, Abhishek Yeole, Sahil Zawar, Zoya Jamadar. “Lexical analyzer using DFA”, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
[12] Kuldeep Vayadande, Harshwardhan More, Omkar More, Shubham Mulay, Atharva Pathak, Vishwam Talnikar, “ Pac Man: Game Development using PDA and OOP”, International Research Journal of Engineering and Technology (IRJET), Volume: 09 Issue: 01 | Jan 2022, e-ISSN: 2395-0056, p-ISSN: 2395-0072
[13] Rohit Gurav, Sakshi Suryawanshi, Parth Narkhede, Sankalp Patil, Sejal Hukare, Kuldeep Vayadande,” Universal Turing machine simulator”, International Journal of Advance Research, Ideas and Innovations in Technology, (Volume 8, Issue 1 - V8I1-1268, ISSN: 2454-132X

Kuldeep B. Vayadande, Parth Sheth, Arvind Shelke, Vaishnavi Patil, Srushti Shevate, Chinmayee Sawakare, "Simulation and Testing of Deterministic Finite Automata Machine," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.13-17, 2022.

Social networking sites have become popular and common places in which short texts share emotional diversity. These emotions are sadness, happiness, fear, anxiety, and so on. In order to identify sentiments expressed by the crowd, it helps in analyzing short texts. On IMDb movie reviews, sentiment analysis identifies a reviewer`s overall sentiment or opinion on a movie. We worked on the IMDb movie dataset in this paper. which was retrieved from Kaggle which was crawled and labelled positive/negative. The available dataset consists of emoticons, Id, Data, Query, username and converted into a standard from. We get these results by utilizing a Voting Classifier with Logistic Regression & Random Forest, which is a traditional machine learning algorithm. Furthermore, the results of these algorithms were compared using five evaluation criteria. metrics – accuracy(89.34),precision(88.71),recall(90.35), F1 measure(89.52),and Area under Curve (89.33).

Sentiment Analysis, Feature Extraction, Voting classifier, Machine Learning, IMDb data

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[6] Kumar, V., & Subba, B. (2020). A TfidfVectorizer and SVM based sentiment analysis framework for text data corpus. 2020 National Conference on Communications (NCC). doi:10.1109/ncc48643.2020.9056085
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[14] https://github.com/jalbertbowden/large-movie-reviews-dataset/tree/master/acl-imdb-v1

Karishma Kaushik, Mahesh Parmar, "IMDb Movie Data Classification using Voting Classifier for Sentiment Analysis," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.18-23, 2022.

The Internet of Things (IoT) is basically viewed as a system which consists of smart objects with various sensors, networks, & processing technologies. IoT transforms the way internet works and carries together the domains such as big data technologies, communication between different machines, artificial intelligence etc. to work underneath the similar canopy so that internet and humans are entangled together. Hence IoT offers pervasive computing giving growth to cyber systems. IoT is an integrated system and works collectively to offer smart services to the end-users. IoT gives several advantages to us by an environment where smart services are offered to use any activity anytime & anywhere. These smart services are offered through different applications executing in the IoT environment. IoT applications monitor & consequently assist in fast decision-making process for client management. In the present work, the different approaches of IoT and its applications unfolding the key components and features are presented. The present work also explores IoT challenges.

IoT, Smart applications, Wireless Sensor Networks (WSNs), Quality of Service (QoS).

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A. Thakur, "A Comprehensive study on Internet of Things Applications and Challenges," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.24-27, 2022.

Data mining conciliations talented ways to expose secreted designs within huge volumes of data. These hidden designs can possibly be used to prediction forthcoming performance. The descriptive data mining tasks characterize the general properties of the data present in the database, while in contrast predictive data mining technique perform inference from the current data for making prediction. This overview briefly introduces these two most important techniques that perform data mining task as Predictive and Descriptive. Between this predictive and descriptive they consist of their own method as Classification, clustering, Data mining (knowledge discovery from data) may be viewed as the abstraction of interesting (non-trivial, implicit, previously unknown and potentially useful) patterns and models from observed data or a method used for analytical process designed to explore data. We know Data mining as knowledge discovery. Basically, Extraction or “MINING” means knowledge from large amount of data. the prediction analysis technique provided by the data mining the future scenarios regarding to the current information can be predicted. The prediction analysis is the combination of clustering and classification. In order to provide prediction analysis there are several techniques presented through many researchers. In this paper describes various techniques proposed by various authors are analysed to understand latest trends in the prediction analysis.

Extraction, Predictive Techniques, Database, Classification, SVM, Clustering

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[14] K. Rajalakshmi, Dr. S. S. Dhenakaran and N. Roobin “Comparative Analysis of K-Means Algorithm in Disease Prediction”, International Journal of Science, Engineering and Technology Research (IJSETR), Vol. 4, 2015.
[15] BalaSundar V, T Devi and N Saravan, “Development f a Data Clustering Algorithm for Predicting Heart”, International Journal of Computer Applications, vol. 48, pp. 423-428,2012.
[16] DaljitKaur and KiranJyot “Enhancement in the Performance of K-means Algorithm”, International Journal of Computer Science and Communication Engineering, vol. 2 pp. 724-729,2013.
[17] Ming, J., Zhang, L., Sun, J.& Zhang, Y, “Analysis models of technical and economic data of mining enterprises based on big data analysis”, International Conference on Cloud Computing and Big Data Analysis (ICCCBDA), 2018, IEEE, 3rHimani Rani et al, International Journal of Computer Science and Mobile Computing, Vol.8 Issue., pg. 15-22, 5 may 2019.
[18] Sakhare, A. V., & Kasbe, P. S “A review on road accident data analysis using data mining techniques”, International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017
[19] Chauhan, C., & Sehgal, S, “A review: Crime analysis using data mining techniques and algorithms”, International Conference on Computing, Communication and Automation (ICCCA), 2017
[20] Anoopkumar M, & Rahman, A. M. J. M. Z, “A Review on Data Mining techniques and factors used in Educational Data Mining to predict student amelioration, International Conference on Data Mining and Advanced Computing.
[21] Lee, E., Jang, Y., Yoon, D.-M., Jeon, J., Yang, S., Lee, S, “Kim, K.-JGame Data Mining Competition on Churn Prediction and Survival Analysis” using Commercial Game Log Data Transactions on Games, IEEE, 2018.
[22] Mortenson, M. J., Doherty, N. F., & Robinson, S. (Operational research from Taylorism to tera bytes:a research agenda for the analytics age. European Journal of OperationalResearch, 583-595,2014
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[24] .Lechevalier, D., Narayanan, A., &Rachuri, S. Towards a DomainSpecific Framework for PredictiveAnalytics in Manufacturing. IEEE International Conference on Big Data Gaithersburg: National Institute of Standards and Technology, (pp. 987-995),2014.

C. Ganesh, E. Kesavulu Reddy, "Overview of the Predictive Data Mining Techniques," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.28-36, 2022.

We live in the twenty-first century, which is full of computers and electrical technologies that make human existence simpler. Artificial intelligence and machine learning are crucial in making life simpler for humans. In contrast, several ailments have evolved as a result of making life simpler, one of which is silent heart attack. Although there are medical treatments for this condition, there are only a few approaches that can forecast the silent heart. We can create models that can predict and detect heart attacks using artificial intelligence and machine learning. Some analysis has been done in this research while working on the road of predicting and detecting heart disease. Artificial neural network techniques are applied. Age , sex , cholesterol are some of the parameters that are set to predict silent heart attack.

predict, silent heart attack, analyze

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[3] 4 silent heart attack signs Available on https://www.pennmedicine.org/updates/blogs/heart-and-vascular-blog/2019/august/4-silent-heart-attack-signs
[4] What Is a Silent Heart Attack? Avaiable on https://www.verywellhealth.com/silent-heart-attacks-1746018
[5] Silent Heart Attacks Available on : https://familydoctor.org/condition/silent-heart-attacks/
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Bhuvan Sharma, Spinder Kaur, "Analysis and Solutions of Silent Heart Attack Using Python," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.37-40, 2022.

In this paper, initially we describe the present antivirus in aspects like –memory[1] they are consuming, and how efficiently they are protecting the system. In the next section of this paper we briefly discuss the design methodologies that are practiced presently, their drawbacks and limitations. Finally we describe an effective design methodology which uses SecurityTAG to protect the system. SecurityTAG is generated by the SecurityTAG generator which takes some parameters as inputs and gives the SecurityTAG as the output. This gives better protection against any virus and detection of infected files is very easy and effective.

SecurityTAG, generator, key, virus

[1] Memory- memory refers to the main memory or physical memory.
[2] van der Meulen, M.J.P., et al. Protective Wrapping of Off-the-Shelf Components. in the 4th International Conference on COTS-Based Software Systems (ICCBSS `05). Bilbao, Spain: Springer. 2005.
[3] Strigini, L., Fault Tolerance Against Design Faults, in Dependable Computing Systems: Paradigms, Performance Issues, and Applications, H. Diab and A. Zomaya, Editors. J. Wiley & Sons. p. 213-241, 2005.
[4] http://www.raymond.cc/blog/archives/2008/07/11/ -free-antivirus-is-the-lightest-on-system-memory-usage/
[5] Fred Cohen, “Computer Viruses”, Computers €4 Security 0, 22-35.
[6] Computers & Security 7, Specid Issue on Viruses.
[7] Marvin Minsky, Computation: Finite and Infinite Machines, Prentice-Hall.

Boddepalli Kiran Kumar, Korla Swaroopa, "SecurityTAG’S," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.41-44, 2022.

This model for price estimation of houses helps in finding the deviation in price for houses. Prices of house are strongly related with various parameter such as crime rate, location, employment rate and market reach. For estimating we required to collect many other information related to real state for estimating the prices. Over the year there are lot of paper published about the use of traditional machine learning to estimate house price, but they rarely concern about the performance of individual model, but most of them are not focused on performance of each model and ignores the less popular yet complex models. So as a result, this research paper focuses on all the traditional and latest machine learning algorithms along with considering various required parameter to estimate house prices in more effective way. This research paper will provide sufficient study and references for various models to prove their efficiency in estimating house prices based on statistical operations and provide an optimistic method to achieve price estimating model.

House price prediction, Linear regression, Inferential statistic, Machine learning, Ridge regression

[1] House Price Index. Federal Housing Finance Agency. https://www.fhfa.gov/, accessed September 1, 2019.
[2] Fan C, Cui Z, Zhong X. House Prices Prediction with Machine Learning Algorithms. Proceedings of the 2018 10th International Conference on Machine Learning and Computing - ICMLC 2018. doi:10.1145/3195106.3195133.
[3] Phan TD. Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia. 2018 International Conference on Machine Learning and Data Engineering (ICMLDE) 2018. doi:10.1109/icmlde.2018.00017.
[4] Mu J, Wu F, Zhang A. Housing Value Forecasting Based on Machine Learning Methods. Abstract and Applied Analysis 2014; 2014:1–7. doi:10.1155/2014/648047.
[5] Lu S, Li Z, Qin Z, Yang X, Goh RSM. A hybrid regression technique for house prices prediction. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2017. doi:10.1109/ieem.2017.8289904.
[6] House Price Index. Federal Housing Finance Agency. https://www.fhfa.gov/, accessed September 1, 2019.
[7] Fan C, Cui Z, Zhong X. House Prices Prediction with Machine Learning Algorithms. Proceedings of the 2018 10th International Conference on Machine Learning and Computing - ICMLC 2018. doi:10.1145/3195106.3195133.
[8] House Price Index. Federal Housing Finance Agency. https://www.fhfa.gov/, accessed September 1, 2019.
[9] Fan C, Cui Z, Zhong X. House Prices Prediction with Machine Learning Algorithms. Proceedings of the 2018 10th International Conference on Machine Learning and Computing - ICMLC 2018. doi:10.1145/3195106.3195133.
[10] Rhan GJ. Housing Price Prediction Through Machine Learning Algorithms: The Case of Moskov City, Russia. 2019 International Conference on Machine Learning and Data Engineering (ICNLDE) 2019. dai:19.1209/icnlde.2019.00026.
[11] Su J, Tu G, Thang A. Housing Value Predicting Based on Machine Learning Methods. Abstract and Applied Analysis 2015; 2015:1–7. doi:10.1175/2015/647947.

Chandra Prakash Patidar, "House Price Prediction through Machine Learning Technique," International Journal of Computer Sciences and Engineering, Vol.10, Issue.1, pp.45-48, 2022.