Search Results - (( moderation classifications learning algorithm ) OR ( java implementation rsa algorithm ))

RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

“…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

“…Java programming language is used to implement the algorithm. …”
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Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

“…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 by Baharum, Azinuddin

“…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

“…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, and visualization. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

“…The algorithm’s distinctive feature lies in its ability to perform non-numeric computations, rendering it adaptable to intricate deep learning problems. …”
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Development of Deep Learning Classification Model for Diabetic Retinopathy Detection and Grading by Nurul Mirza Afiqah, Tajudin

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Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques by Al-Ezzi, A., Al-Shargabi, A.A., Al-Shargie, F., Zahary, A.T.

“…The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. …”
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An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Fuzzy Evaluation and Benchmarking Framework for Robust Machine Learning Model in Real-Time Autism Triage Applications by Shayea G.G., Zabil M.H.M., Albahri A.S., Joudar S.S., Hamid R.A., Albahri O.S., Alamoodi A.H., Zahid I.A., Sharaf I.M.

Investigating the relationship between the urban heat island effect and short-duration extreme rainfall in Kuala Lumpur by Tan, Yan Kai

“…LULC classification was performed using Support Vector Machine (SVM) and Random Forest (RF) algorithms, while LST was estimated using the Single Channel (SC) algorithm and surface urban heat island intensity (SUHII) was subsequently derived from the LST data. …”
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Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review by Ibrahim, Buhari, Suppiah, Subapriya, Ibrahim, Normala, Mohamad, Mazlyfarina, Abu Hassan, Hasyma, Syed Nasser, Nisha, Saripan, M. Iqbal

“…We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation by Liaghat, Shohreh

“…Reflectance spectra were pre-processed and principal component analysis (PCA) was performed to obtain PC scores as input features used in different pattern recognition algorithms in order to select the best learning model of Ganoderma discrimination. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…Even though at first glance the classification accuracy was moderate, the level of details provided by the imageries suggests that the accuracies were acceptable. …”
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