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Sai, Settipalli, Sheshuvardhan, und Vannurappagari. International Journal of Innovative Research in Information Security, 09 (2):
39-44(Mai 2023)1. Gas booking system using VB software, Microcontroller and Gas Leakage Detection with SMS by Dr.D.B.Kadam,Sumedha shashikanth patil, Akshay Ananda Kumbhar, Rohit Ankush Tandle. 2. Gas Leakage Detection based on IoT using Raspberry Pi by Deepthi Miriyampalli , Ponnuri Anil Kumar , Abdul Khadir Shaik , Ravichandra Vipparla , Komalphanindra Potineni. 3. LPG Gas Leakage Detection System with GSM Module by Alan M John , Bhavesh Purbia , Ankit Sharma , Mrs. A.S Udapurkar. 4. Gas Leakage Detection Using GSM Module & Arduino with SMS Alert by Mr. Sivaprasad Lebaka, M. Ganga Rami Reddy,K. Devi Priya, N.V. Charan, N.V. Charan. 5. Gas Leakage Detection, prediction & Alert System Using Raspberry Pi & cloud computing by Pranav Mani Tripathi, Saket Kumar, Saksham Kumar, Veeresh Bhalke , Prof. Vidyashree K. 6. IoT Gas Leakage Detector and Warning Generator by Bader Farhan Alshammari , Muhammad Tajammal Chughtai. 7. J.Ding, J.Wang, N.Yuan, and Q.Pan, “The Monitoring System of Leakage Accidents in Crude Oil Pipeline based on Zigbee Technology”, IEEE Changzhou University. https://doi.org/10.1109/mace.2011.5987303.
Krithika, Lakshitha, Monica, Priya, und Veena. International Journal of Innovative Research in Information Security, 09 (2):
21-27(Mai 2023)1. Currency Recognition system using Image Processing. SANDEEP KUMAR CHAUBEY Andrew S. Morgan Kaufmann Publishers, 1995. 2. A Survey on Indian Currency Note Denomination Recognition System. Aruna Manpreet Bagga, Dr.Baljit Singh. 1995. 3. Dr. Baljith Singh, Aruna D H Indian currency note denomination system. 4. Ms. Monali Patil, Prof. Jayant Adhikari Detection of fake currency using digital image processing. 5. Arun Anoop M, Dr K.E. Kannammal Fake currency detection 6. Vidhi Roy and Sushanth Patil Fake Currency detection using image processing. 7. M. Deborah and Soniya Prathap Detection of Fake currency using edge detection. 8. Akash Rana, Avinash Kumar and Shivam Kumar Jha Detection of fake currency using machine learning technique. 9. Mayadevi, A. Gaikwad, Vaijinath, V. Bhosle and Vaibhav Currency note feature extraction. 10. Brinda M Object Detection using Haar-Like Feature Extraction..
Bhavya, Nalini, Deepika, Nagaraj, und Jagadamba. International Journal of Innovative Research in Information Security, 9 (2):
10-14(Mai 2023)1. Adler, A.; Schuckers, S. Biometric vulnerabilities, overview. In Encyclopedia of Biometrics; Li, S.Z., Jain, A., Eds.; Springer: Boston, MA, USA, 2009. https://doi.org/10.1007/978-0-387-73003-5_65 2. Nguyen, H.T. Fingerprints Classification through Image Analysis and Machine Learning Method. Algorithms 2019, 12, 241. https://doi.org/10.3390/a12110241 3. Biometric Systems Lab—FVC2000: Fingerprint Verification Competition. Available online: FVC2000 (unibo.it)(accessed on 22 January 2021). 4. Tang, Y.; Gao, F.; Feng, J. Latent fingerprint minutia extraction using fully convolutional network. In Proceedings of the 2017 IEEE International Joint Conference on Biometrics, Denver, CO, USA, 1–4 October 2017; pp. 117–123. https://doi.org/10.1109/btas.2017.8272689 5. Huang, X.; Qian, P.; Liu, M. Latent fingerprint image enhancement based on progressive generative adversarial network. In Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA, 14–19 June 2020; pp. 3481–3489. https://doi.org/10.1109/cvprw50498.2020.00408 6. Neurotechnology Company—Sample Fingerprint Databases. Available online: Download biometric algorithm demo software, SDK trials, product brochures. (neurotechnology.com)(accessed on 22 January 2021). 7. Fingerprint Image identification for crime detection (2019) Fingerprint Image Identification for Crime Detection | IEEE Conference Publication | IEEE Xplore https://doi.org/10.1109/iccsp.2019.8698014.
Sai, Jemeema, Mallu, und Puli. International Journal of Innovative Research in Information Security, 9 (2):
07-09(Mai 2023)1 Iqra Nissar; Waseem Ahmad Mir; Izharuddin; Tawseef Ayoub Shaikh.” Machine Learning Approaches for Detection and Diagnosis of Parkinson’s Disease”. 2021 IEEE. https://doi.org/10.1109/icaccs51430.2021.9441885 2 Pooja Raundale; Chetan Thosar; Shardul Rane.” Prediction of Parkinson’s disease and severity of the disease using Machine Learning and Deep Learning algorithm”.2021 IEEE. https://doi.org/10.1109/incet51464.2021.9456292 3 Son V T Dao “An Analysis of Vocal Features for Parkinson’s Disease Classification Using Evolutionary Algorithms” 2022. 4 Mohammed S Islam “Parkinson’s Disease Prediction Using Machine Learning” 2020..
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H. Nguyen, N. Nguyen, H. Doan, Z. Ahmadi, T. Doan, und L. Jiang. Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, New York, NY, USA, Association for Computing Machinery, (November 2022)
G. Singh. (2012)Fraud Detection is of great importance to financial institutions. In this paper we have tried to study the Outlier Analysis in Stock Market Fraud Detection. Outlier Analysis is a fundamental issue in Data Mining, specifically in Fraud Detection. While observing the Indian Stock Market, we could detect that some of the Trading Entities have suspicious trading patterns that give rise to a doubt of having some malpractices in stock transactions within Indian Stock Market. All the facts are presented on the basis of data obtained from the official sites of BSE (Bombay Stock Exchange), NSE (National Stock Exchange) and SEBI (Securities and Exchange Board of India)..
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