Search Results - (( data navigation learning algorithm ) OR ( java application 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

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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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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms by Sariman, Muhammad Shazmin, Othman, Maisara, Mat Akir, Rohaida, Mahamad, Abd Kadir, Ab Rahman, Munirah

“…Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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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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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

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Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review by Khan, Mazbahur Rahman, Mohd Ibrahim, Azhar, Al Mahmud, Suaib, Samat, Farah Asyiqin, Jasni, Farahiyah, Mardzuki, Muhammad Imran

“…The advent of Deep Reinforcement Learning (DRL) has spurred significant research into enabling mobile robots to learn effective navigation by optimizing actions based on environmental rewards. …”
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Supervisory fuzzy learning control for underwater target tracking by Kia, Chua, Arshad, Mohd Rizal, Adom, Abd Hamid, Wilson, Philip A.

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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. The MANFIE has shown the ability to reduce and form the robust minimal rules (Rules reduced on average 97.95% and 96.90% accuracy for pattern classifications, rules reduced on average 97.15%, 75% and 98.43% for time series predictions, modeling with inverse learning control and mobile robot navigation respectively) to make an appropriate structure and minimize the root mean square error (RMSE - 0.024, 0.149 for time series predictions, 0.007 for modeling with learning control, 0.027 for mobile robot navigation) with the best accuracy. …”
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Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

Improvement of an integrated global positioning system and inertial navigation system for land navigation application by Hasan, Ahmed Mudheher

“…The developed navigators utilize artificial intelligence (AI) based on adaptive neuro-fuzzy inference system (ANFIS), to fuse data from both systems and estimate position and velocity errors. …”
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Data Analytics on student response via social media on the educational landscape (learning, experience, humanization) during the COVID-19 pandemic by Zaiful Anuar, Muhamad Zarif

“…All comments from particularly selected posts are retrieved via a data extraction tool. Then, a sentiment analysis of the comments is carried out using machine learning algorithms such as Support Vector Machine to analyse the sentiments conveyed by the students via their comments. …”
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Automatic Detection of Damaged Roads and Lane Detection using Deep Learning by Kotakonda Sandhya, Rani, Kommi, Chandana, Nallamalla, Kavya, Kasireddy, Poojitha, Thalla, Pallavi

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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

“…This research contributes novel insights into the application of clustering algorithms in banking, proposing pragmatic solutions for efficient data analysis and campaign optimization. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…As a consequence, the agent is expected to have trained behaviors and navigation without crashing. The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

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Thyroid Insight: navigating disease data through interactive visualization with prediction by Osman, Mohd Nizam, Md Nasib, Azim, Sedek, Khairul Anwar, Othman, Nor Arzami, Maghribi, Mushahadah

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Challenges in supervised and unsupervised learning: a comprehensive overview by Almuqati, Mohammed Tuays, Sidi, Fatimah, Mohd Rum, Siti Nurulain, Zolkepli, Maslina, Ishak, Iskandar

“…In unsupervised learning, difficulties encompass issues like overfitting, choosing the appropriate algorithm, and interpreting results. …”
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