Search Results - (( variable data compression algorithm ) OR ( java application customization algorithm ))

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  1. 1
    Optimizing lossless compression by normalized data length in Huffman Algorithm

    Optimizing lossless compression by normalized data length in Huffman Algorithm by Tonny, Hidayat

    Published 2022
    “…Huffman Algorithms is currently still very effective at compressing 8-bit data, which can be grouped into Static, Dynamic, and Adaptive extensions, however its performance cannot be determined if it is performed on data that has several variables and probabilities. …”
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  2. 2
    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

    Published 2025
    “…Therefore, it is recommended to utilize the prediction algorithms within the range of input variables employed in this investigation for optimal results. ? …”
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  3. 3
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…To address these shortcomings, a technique to classify the compressive strength grades for lightweight aggregate concrete containing POFA using a machine learning algorithm has been developed. …”
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  4. 4
    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers

    Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

    Published 2025
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  5. 5
    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate

    Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

    Published 2025
    “…This study investigates the use of ML algorithms to predict the compressive strength of grade 30 concrete, incorporating shredded PET bottles and M-sand as fine aggregates. …”
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  6. 6
    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…To address these shortcomings, a technique to classify the compressive strength grades for lightweight aggregate concrete containing POFA using a machine learning algorithm has been developed. …”
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  7. 7
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  8. 8
    Efficient reconfigurable architectures for 3-D medical image compression

    Efficient reconfigurable architectures for 3-D medical image compression by Ahmad, Afandi

    Published 2010
    “…Furthermore, a novel hardware implementation of 3-D medical image compression system with context-based adaptive variable length coding (CAVLC) has been proposed. …”
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  9. 9
    Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study

    Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study by Abdellatief M., Hassan Y.M., Elnabwy M.T., Wong L.S., Chin R.J., Mo K.H.

    Published 2025
    “…Through the application of ML models, this study not only ascertains the significance of algorithms including RF, SVR, and XGB in precisely forecasting the CS of UHPGC, but also reveals essential understandings regarding the importance of steel fiber content, L/B ratio, and various other pivotal variables, consequently facilitating the development of refined formulations and improved functionalities in eco-friendly construction materials. ? …”
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  10. 10
    Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows

    Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows by Afzal, Asif, Aabid, Abdul, Khan, Ambareen, Khan, Sher Afghan, Rajak, Upendra, Verma, Tikendra Nath, Kumar, Rahul

    Published 2020
    “…The K-means algorithm performs a clustering analysis of this enormous data, which provides useful information and patterns. …”
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  11. 11
    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine

    Application of artificial neural network to predict brake specific fuel consumption of retrofitted cng engine by Jahirul, M.I., Saidur, Rahman, Masjuki, Haji Hassan

    Published 2009
    “…The training data for ANN is obtained from experimental measurements. …”
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  12. 12
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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  13. 13
    4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer

    4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer by Ahmed, R., Mahadzir, S., Mota-Babiloni, A., Al-Amin, M., Usmani, A.Y., Ashraf Rana, Z., Yassin, H., Shaik, S., Hussain, F.

    Published 2023
    “…Therefore, this work aims to study a two-stage vapor compression refrigeration system (VCRS) through a novel and robust hybrid multi-objective grey wolf optimizer (HMOGWO) algorithm. …”
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