Week 6:
- Accurate and Factual Information Support by Evidence (Refereed journals or publications are the ones that contain information reviewed by several experts in the field)
- Does the information you have located come from authoritative sources?
- If you obtained the information from a website, how reliable is the information?
All information obtained is from IEEE website and Google Scholar which are University Teknologi Malaysia accepted. Most the information was obtained from websites, and I trust that the information should be reliable as most of the papers are from the authoritative sources.
- The Timeliness of the Publication. (For very current info then timeliness is a must but for historical perspective then timeliness may not be crucial)
- Is the information timely or out-of-date for your topic?
Most of the information I found was around 90’s and only few with the latest year of publication in 2019. So, I believed that the information I found would be timely as Fractal Image decoding is still will use in daily life.
- Type of Publication (This indicated different levels of complexity in introducing ideas)
- Is the source scholarly, popular, trade or government publication?
Most of the information I found are mostly scholarly in my opinion. Most of paper or article found are done by other universities who have same idea to implement this fast fractal image decoder.
During this week, I had reviewed 2 articles with related to Fractal Image.
The first article I reviewed with title of A Novel Interactive Progressive Decoding Method for Fractal Image Compression. The article state that progressive fractal decoding approach will works by sending only part of the compressed file to generate a preview image and suspending the rest of transmission until further instruction from user is received.
The second article I reviewed with title of Attractor Image Compression with A Fast Non-Iterative Decoding Algorithm. The article was mentioned the problem of the decoder is that the decoding rests on an interactive procedure whose complexity is image-dependent.
Week 7:
- List the relationship of proposed idea to the system/end user/stakeholder in terms of daily or routine use.
- End user – Graphic Designer - They can produce better quality photo with the shorter time use as the Fractal Image Decoder process are faster so the productivity may increase and less time spending on a same Image.
- List the relationship of proposed idea to the system/end user/stakeholder in terms potentials.
- It would have a potential to ensure the user can complete the fractal image decoding with a faster time compared to older version of the fractal image decoder.
- List the relationship of proposed idea to the system/end user/stakeholder in terms of frequency of use.
- The frequency of use would vary depending on user usage during they need. In my opinion in working hour will be highest usage due to most user need this product are for professional purpose.
During this week, I did not further review other new article as this week I am busy with several Test from difference subject. This causes I am fully focus on my other subject test and spending a lot of time in revision on test.
Week 8:
During this week, I had created the theoretical framework which showing the relationships between concepts, including cross connections among concepts, and their examples.
During this week, I had reviewed 2 articles with related to Fractal Image.
The first article I reviewed with title of Hardware Architecture of a Decoder for Fractal Image Compression. The article mentions that they face some issues during the Implementation. First issue they face is the bit length of the data stored in the memory at the output of the encoder, the amount of space it acquires and the method of how to read them from the memory. Then, the output decoder chooses to need to decide with enough number of bits for input and output.
The second article I reviewed with title of Speeding up Fractal Image De-Compression. The article was mentioned that they implement two type of algorithm for the Fractal Image Decoder and they make a conclusion of the second algorithm with using average domain for the input.
Week 9:
During this week, I had created the conceptual diagram is a systematic depiction of an abstract concept in pre-defined category boxes with specified relationships, typically based on a theory or model
During this week, I had reviewed 1 article with related to Fractal Image.
The article I reviewed with title of Hardware Implementation of Quadtree Based Fractal Image Decoder. The article mentions that the decoding process in fractal-based compression technique is an iterative process and utilizes the parameters extracted during encoding for converging to a fixed point, that approximates the original image. The adaptive sized partitioning scheme provides details of various regions at different resolutions.