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TC2013 Assignment

SEMESTER 1/2023-2024

ABOUT THE ASSIGNMENT

Date release: 16 October 2023

Duration: 8 weeks

Deadline 1: Report Submission on Week 10 (26th Dec 2023)

Deadline 2: Demo on Week 11 & 12 (Lecture & Tutorial slots)

Course Learning Outcome to achieve: CLO 3

-Menilai teknik taakulan dan pembelajaran mesin dalam penyelesaian masalah yang berkaitan kecerdasan.

-To evaluate inferencing and machine learning technique on intelligence related problem.

Marks distribution: 15(system demo), 35(report) and 10 (peers evaluation)

ASSIGNMENT QUESTION

Each group (of four members) are required to develop an intelligent system. At the end of week 11, each group must produce TWO item for this assignment: the developed system and the report. Each group were to choose their own preferred tools such as (but not limited to) java, prolog, python, weka etc..

These are same sample of a well-developed AI system available for you to play around and follow if you like:

1. Coronavirus early diagnosis: https://www.doctoroncall.com.my/coronavirus/how-to-find-out-if-i-have-coronavirus-online-test ]

2. The breast cancer risk assessment tool: https://bcrisktool.cancer.gov/

3. Dr.Lada apps: The black paper disease diagnosis:

https://play.google.com/store/apps/details?id=my.edu.ukm.aninterface

And these are six available examples of Intelligent system project report for your reference:

1. blood cell classification

a. https://link.springer.com/chapter/10.1007/978-981-13-3600-3_13

b. https://link.springer.com/article/10.1007/s42979-021-00458-2

2. Eye Disease Intelligent system

a. https://ieeexplore.ieee.org/document/7005925

b. DOI: http://dx.doi.org/10.18517/ijaseit.9.3.7025

3. Dr.Lada Apps to Diagnose Black Pepper diasease :

a. DOI: http://dx.doi.org/10.18517/ijaseit.8.4-2.6818

You’ll be assigned the dataset and machine learning model to work with.

Table 1: mark distributions for project report.

Items

a) Introduction

The domain, the importance and the knowledge source                       3

b) Methods

i) Knowledge Acquisition

Explain in details of the dataset that you have. What are the understanding you gain and where do you acquire them.              2

ii) Knowledge Representation

Represents the acquired knowledge into a structured and suitable manner. Explanation of the knowledge must be reported as a text in paragraph as well as the Equations, Diagrams or/and Table (which ever suitable)

Please also enclose the reason of using the selected knowledge representation form.

Eg: the characteristics of objects need to be detected have similarities/inheritance/relations etc.                3

iii) The machine learning techniques

Reports on the machine learning techniques tested for this project. Should include number of train/test/validation data and what are the performance measurement used.                     5

c) Results (Diagram and Table)

i) Interface (Input, Output, Backtracking as well as the explanation facilities.               Bonus (capped at 3)

ii) Machine learning result (accuracy percentage etc)            3

d) Analysis

i) Inference Engine

Reports on how the inference engine were use (forward/backward chaining)

[reference]https://www.javatpoint.com/forward-chaining-and-backward-chaining-in-ai             3

ii) Handling uncertainties and conflicting knowledge

Choose at least any 2 knowledge from your knowledge base. Change it into two conflicting rules (if necessary) and show the whole fuzzification process in the report.                        2

e) Conclusion                   2

f) Abstract (problem to solve, tested method by other authors, your planned method & the result)                 4

g) Contribution of members

No marks but if omitted, 10 marks from peer evaluation will be lost.

h) Reference                     3

TOTAL                             30

Report must be prepared following any one of these template:

1. the IEEE Transaction https://journals.ieeeauthorcenter.ieee.org/create-your-ieee-journal-article/authoring-tools-and-templates/ieee-article-templates/templates-for-transactions/

2. Springer https://www.springer.com/gp/authors-editors/journal-author/word-template-zip-154-kb-/22044

3. Elsevier

https://typeset.io/formats/search/?formatId=8cd073ef58e7a786219fa01d7bf46073Paper Format

Minimum number of pages is 7 and maximum number of pages is 10 only

THE MARKING SCHEME

Table 2: The marking scheme.

Table 3: Peers evaluation

Please rate 1/0 (1 for agree and 0 for do not agree)