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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe
Published 2017“…Java programming language is used to implement the algorithm. …”
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Secure Image Steganography Using Encryption Algorithm
Published 2016“…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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Digitally signed electronic certificate for workshop / Azinuddin Baharum
Published 2017“…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…The rapid implementation of workflow in KNIME Analytics Platform provided the opportunity to process hyperspectral reflectance data to classify crop diseases.…”
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Suicide and self-harm prediction based on social media data using machine learning algorithms
Published 2023“…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
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Characterization of oil palm fruitlets using artificial neural network
Published 2014“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Oil palm maturity classifier using spectrometer and machine learning
Published 2021“…Each bunch was scanned at its different parts including apical, front equatorial, front basil, back equatorial and back basil. The reflectance data from these five parts was analyzed using statistical method and machine learning algorithm. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…In conclusion, the study of Econophysics principles with Python programming and machine learning algorithms has indicates that the predictive framework is reliable and effective in capturing stock price fluctuations, enhancing decision-making for investors based on data-driven insights.…”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Prediction of payment method in convenience stores using machine learning
Published 2023“…The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms. In this paper, individual classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k - Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree are experimented. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…However, a few overlapped NIRs’ spectral data between healthy and infected samples require for further validation which chemometric and machine learning (ML) classification technique are chosen. …”
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