Volume-9 , Issue-7 , Jul - 2021 Go Back

India is a country where agricultural and agriculture-related sectors provide the majority of the country`s income. Agriculture is the country`s main source of revenue. It is also one of the countries that has major natural disasters such as drought or flooding, which have caused crop devastation and repeated crop cultivation leads to soil degradations due to this farmers suffer significant financial losses as a result of this, leading to suicide. The goal is to build a machine learning model for crop and fertilizer recommendations system based on soil features which includes different types of parameters value such as PH, Organic Carbon, Nitrogen, phosphorus, potassium, sulphur, zinc, iron, temperature, rainfall. Naïve Bayes and LVQ algorithms are used for crop recommendations and KNN classifier are used for fertilizer recommendations. This system displays the results of a study on the machine learning approaches and compare with the neural networks to forecast the best crops recommendations. The Machine Learning algorithm gives more accurate results than CNN.

Crop and Fertilizer Recommendation, Naïve Bayes (NB), Machine Learning, Agriculture, Learning vector quantization (LVQ)

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[7] R. N. Bhimanpallewar and M. R. Narasingarao, "Alternative approaches of Machine Learning for Agriculture Advisory System," 2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 27-31, 2020, doi: 10.1109/Confluence47617.2020.9058152.
[8] Nischitha K, DhanushVishwakarma, Mahendra N, Ashwini, Manjuraju M.R, “Crop Prediction using Machine Learning Approaches”, International Journal of Engineering Research & Technology (IJERT), Vol. 9 Issue 08, August-2020.
[9] Fahim Jawad, Tawsif Ur Rahman Choudhury, S M Asif Sazed, Shamima Yasmin , Kanaz Iffat Rishva, Fouzia Tamanna, Rashedur M Rahman ,”Analysis of Optimum Crop Cultivation Using Fuzzy System”, 978-1-5090-0806-3/16/$31.00 copyright 2016 IEEE ICIS 2016, June 26-29, 2016, Okayama, Japan.
[10] R. B. Guruprasad, K. Saurav and S. Randhawa, "Machine Learning Methodologies for Paddy Yield Estimation in India: a Case Study," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, pp. 7254-7257, 2019, doi: 10.1109/IGARSS.2019.8900339.

Supriya M.S., Nagarathna, "A Machine Learning Based Crop and Fertilizer Recommendation System," International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.64-68, 2021.

In India Ministry of Education statistics, about one million graduates each year, some of them will goto countries, high schools or tertiary institutions to continue to attend, and some will be ready to enter the workplace employment. During the course of study, the students’ all kinds of excellent performance certificates, score transcripts, diplomas, etc., will become an important reference for admitting new schools or new works. As schools make various awards or diplomas, only the names of the schools and the students are input. Due to the lack of effective anti-forge mechanism, events that cause the graduation certificate to be forged often get noticed. In order to solve the problem of counterfeiting certificates, the digital certificate system based on block chain technology would be proposed. By the modifiable property of block chain, the digital certificate with anti-counterfeit and verifiability could be made. The procedure of issuing the digital certificate in this system is as follows. First, generate the electronic file of a paper certificate accompanying other related data into the database, meanwhile calculate the electronic file for its hash value. Finally, store the hash value into the block in the chain system. The system will create a related QR-code and inquiry string code to affix to the paper certificate. It will provide the demand unit to verify the authenticity of the paper certificate through mobile phone scanning or website inquiries. Through the modifiable properties of the block chain, the system not only enhances the credibility of various paper-based certificates, but also electronically reduces the loss risks of various types of certificates.

Custom Blockchain, Digital Certificate, Hashing, Mining, Smart Contrast

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P.S. Gayke, Jayesh Chennur, Mulla Muzzamil, Jathin Joy, Kunal Gosavi, "Digital Certificate System for Verification of Educational Certificates Using Blockchain," International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.69-73, 2021.

An automated method utilized for biometric identification which includes various mathematical patterns recognition methods in it known as the iris recognition method. The images of the irises of various individuals` eyes are studied in this technique. The complex random patterns present within this approach are single, constant and can as well be viewed from a particular distance. In the base paper, intensity transformation is applied with edge detection. The image processing techniques are applied which will extract the contrast, energy, entropy and heterogeneity of the detected iris has been calculated. To increase the accuracy of iris detection and reduce execution time, improvement in existing algorithms, feature extraction techniques are being proposed and also evaluate the ROC curve for performance analysis and achieve 0.81 area under curve.

Iris, localization, Image Processing

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[19] Peter Chondro, Hao-Chun Hu, Hsuan-Yen Hung, Shin-Yuan Chang, Lieber Po-Hung Li, and ShanqJang Ruan,” An Effective Occipitomental View Enhancement Based on Adaptive Morphological Texture Analysis”, 2016, IEEE, 2168-2194
[20] Juan E. Tapia, Claudio A. Perez, Kevin W. Bowyer,” Gender Classification from the Same Iris Code Used for Recognition”, 2015, IEEE, 1556-6013

Ashwini Chate, Pramod Kumar, Sushilkumar Holambe, "Detection and Localization of Iris using Digital Image Processing Techniques," International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.74-77, 2021.

Steganography is the art and science for hiding information by embedding data into cover media. Image processing in steganography is done mainly by using spatial domain and frequency domain. In this review literature, hiding spatial domain using LSB technique and hiding frequency domain using DCT technique is studied and compared. BMP cover images with 256x256 and 512x512 resolutions for LSB and DCT techniques are used for experimental study. For DCT technique, various BMP image is converted to JPEG image. The DCT technique is used to hide the data into the JPEG cover image. The resultant stego image obtained in JPEG is converted to BMP stego image. Thereafter, the comparison tool PSNR is used to compare the BMP images obtained from LSB and DCT. The data security and privacy play an important role for data transmission for exchanging information over internet. The two techniques like; cryptography and steganography both are pillars to be utilized for securing digital data by using different methods specifically DES (Data Encryption Standard) and DCT (Discrete Cosine Transform). The mixture of DES and DCT improves the digital data security with multiple level of security for encryption process which shows better results. In this research, we analyze the combination of cryptographic method with DES technique and stenographic method with DCT technique to develop a framework for digital data security environment. This paper also presents a proposed least significant bit (LSB) based framework for DES and DCT to secure digital data with better compression approach.

LSB, DCT, DES, Stego Image

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Vikas Singhal, Devendra Singh, Sanjai Gupta, "Literature Review on Improving Data Security using DES and DCT," International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.78-83, 2021.