The conceptual design of Malaysia geopostcode and its implementation issues

The study of Malaysia Geopostcode structure has been done by Wan Mohamad Nazmeen et al. (2015) and Nur Baizura (2015). Their study area covered the states of Johor Bahru (Othman et al. , 2015), Kuala Lumpur and Selangor (Napiah, 2015). They proposed the structure to be in eight alphanumerical characters. The structure by Wan Mohamad Nazmeen et al. (2015), Nur Baizura (2015) and this study was named as Geopostcode V1, Geopostcode V2 (Napiah, 2015) and Geopostcode V3 respectively. Geopostcode V1, Geopostcode V2 and the potential Geopostcode V3 structure being presented to the stakeholders in order to collect their perceptions on these Malaysia Geopostcode structures. Geopostcode V3 was designed by considering the administrative boundaries for every state in Malaysia and enhanced according to the input from the interviews with the stakeholders. The issues in Malaysia Geopostcode implementation have also been discussed. The structure of Geopostcode V3 has been shortened to seven characters. On top of that, the implementation issues are ranked in order to determine the biggest issues in Malaysia Geopostcode Implementation. The methodology of interviewing the stakeholders, analysing and designing the Malaysia Geopostcode are presented in this report. The final product from this study is the enhanced Malaysia Geopostcode structure which look suitable to be used for every states in Malaysia and the biggest issues in Malaysia Geopostcode implementation

Character Recognition Using A Modular Spatiotemporal Connectionist Model

We describe a connectionist model for recognizing handprinted characters. Instead of treating the input as a static signal, the image is scanned over time and converted into a time-varying signal. The temporalized image is processed by a spatiotemporal connectionist network suitable for dealing with time-varying signals. The resulting system offers several attractive features, including shift-invariance and inherent retention of local spatial relationships along the temporalized axis, a reduction in the number of free parameters, and the ability to process images of arbitrary length. Connectionist networks were chosen as they offer learnability, rapid recognition, and attractive commercial possibilities. A modular and structured approach was taken in order to simplify network construction, optimization and analysis. Results on the task of handprinted digit recognition are among the best report to date on a set of real-world ZIP code digit images, provided by the United States Postal Service. The system achieved a 99.1% recognition rate on the training set and a 96.0% recognition rate on the test set with no rejections. A 99.0% recognition rate on the test set was achieved when 14.6% of the images were rejected