Reengineering Legacy Embedded Systems
Systems that require reengineering are a fact of life in both the commercial and military arenas. The authors have developed a systematic methodology based on virtual prototyping, with accompanying tools and libraries, for rapidly upgrading electronic systems.
Application of MVP Architecture in Reengineering of Legacy Financial System
As the progress of information technology, some financial systems used for long time can no longer meet the requirement of customers in both user interface and business process, and need reengineering imminently. In order to save the human resource and financial effort, this article raises a reengineering approach by encapsulating the back-end data access code of legacy system and only refactoring the front-end user interface and business logic. In the reengineering work, this article uses MVP (Model-View-Presenter) Architecture. By extracting screen logic into Presenters, the display code in View is independent from logic code in Presenter. Also, the introduction of MVP Architecture greatly enhances the reusability and the testability of business logic code, and finally improves the efficiency of development and test work significantly.
Detection and Counting of On-Tree Citrus Fruit for Crop Yield Estimation
In this paper, we present a technique to estimate citrus fruit yield from the tree images. Manually counting the fruit for yield estimation for marketing and other managerial tasks is time consuming and requires human resources, which do not always come cheap. Different approaches have been used for the said purpose, yet separation of fruit from its background poses challenges, and renders the exercise inaccurate. In this paper, we use k-means segmentation for recognition of fruit, which segments the image accurately thus enabling more accurate yield estimation. We created a dataset containing 83 tree images with 4001 citrus fruits from three different fields. We are able to detect the on-tree fruits with an accuracy of 91.3%. In addition, we find a strong correlation between the manual and the automated fruit count by getting coefficients of determination R2 up to 0.99.