Search Results - (( developing using eucs algorithm ) OR ( java application tree algorithm ))

  • Showing 1 - 8 results of 8
Refine Results
  1. 1
  2. 2

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    An automated approach to elicit and validate security requirements of mobile application by Yusop, Noorrezam

    Published 2018
    “…Mobile phone usage has continued to rise,and it is becoming more convenient for users to use mobile applications for booking hotels,conducting online transaction and online payment.In this case,secured applications are required to increase the confidence among mobile users.In order to achieve correct secure application,a correct security requirements needs to be elicited and defined.Additionally,it is also crucial for security requirements of mobile apps to fulfill basic quality attributes such as correct,consistent and complete (3Cs).However,few problems are found in eliciting security requirements for mobile apps.Firstly, most requirements engineers (RE) are identified to have less knowledge and understanding of security requirements attributes,leading to the failure of implementing the 3Cs of security requirements.Secondly,most of the elicitation and the validation of security requirements are conducted at the later stage of the development and leads to poor quality security requirements implementation which might resulted to project failure.Motivated from these problems,the objectives of this thesis are three-folds; 1) To analyze the security requirements for mobile apps, 2) To propose an approach to elicit and end-to-end validation of security requirement,and 3)To evaluate the efficacy in term of correctness and performance as well as usability of the approach.This thesis proposes a new automated approach to assist the elicitation and validation of security requirements.Here an automated tool support called MobiMEReq is also developed.For this, we have adopted Test Driven Development (TDD) methodology with semi-formalized models:i) Essential Use Cases (EUCs) and ii) Essential User Interface (EUI).We then divided our approach into two parts:1)Elicitation and 2)End-to-end validation security requirements.Further,we have developed pattern libraries to assist on the correct elicitation and validation.They are mobile Security attributes pattern library and mobile security pattern library.Then,we have constructed a new algorithm using fuzzy logic to assist on the prioritization of the test for better performance of validation.Finally,a comprehensive evaluation of the approach,comprising experiments of correctness test and usability test were conducted.Here,we have also evaluated the feedback from the industry experts especially on the usability of the automated approach and tool support.In summary,the findings of the evaluations show that our approach is able to contribute to the body of knowledge of mobile security requirements engineering especially in enhancing the performance and correctness level of security attribute elicitation and its usability for end-to-end elicitation and validation.It is found that the approach able to enhance the correctness level of the elicited security attribute compared to the manual approach,and produce correct generation of test.Then,the results of the usability test by the novice and experts show that the approach is useful in eliciting and validating security requirements at the early stage of application development and is able to ease the elicitation and validation process of security requirements of mobile apps.…”
    Get full text
    Get full text
    Get full text
    Thesis