Search Results - (( java applications server algorithm ) OR ( framework implementation tree algorithm ))

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  1. 1

    Network game (Literati) / Chung Mei Kuen by Chung, Mei Kuen

    Published 2003
    “…Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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    Thesis
  2. 2

    Quantum Processing Framework And Hybrid Algorithms For Routing Problems by Soltan Aghaei, Mohammad Reza

    Published 2010
    “…The framework is used to increase the implementation performance of quantum algorithms. …”
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    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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    Conference or Workshop Item
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    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider by Omer Fadlelmola Elkhider, Samih

    Published 2011
    “…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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  8. 8

    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

    Published 2004
    “…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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    Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

    Published 2014
    “…On the basis of the results of this research, it can be concluded that the developed prototype had high accuracy and security when transferring the file between the sender and receiver that was implemented in client-server application. This research hopes to give a clear idea to the readers about ABS algorithm. …”
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    Undergraduates Project Papers
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    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. …”
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    Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

    Published 2021
    “…The machine learning model in the two platforms were tested on breast cancer and tax avoidance datasets with Decision Tree algorithm. The results indicated that although the software framework is easier than the programming platform for implementing the machine learning model, the results from the software framework were highly accurate and reliable. …”
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    Article
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    Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image by Zainal Azali, Muhammad Nazmi

    Published 2024
    “…The final step of the proposed algorithm framework is refinement stage. At this stage, Bilateral filter (BF) and Weighted Median (WM) filter are utilized. …”
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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    Article
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    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…It is organized into three phases: preliminary investigation, implementation and analysis, and validation. The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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    Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

    Published 2016
    “…The plugin can be 'installed' on any other web application with minimum efforts. The algorithm can be implemented as part of Web Server layer, not as part of the business logic layer. …”
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    Conference or Workshop Item
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    Improved random forest for feature selection in writer identification by Sukor, Nooraziera Akmal

    Published 2015
    “…Discretization process was proven to increase the classification performances and improved the identification performance in WI. An algorithm and framework of Improved Random Forest (IRF) tree was applied for feature selection process. …”
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    An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study by Sutanto, Daniel Hartono

    Published 2018
    “…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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