Geometry Learning Through Batik Reconstruction

In this world, the shapes of objects, including Batik motifs in Indonesia, are regular and irregular. One of the regular Batik motifs is Surya Kawung Batik from Mojokerto. The purpose of this research is to observe the ability of the Electrical Engineering Department students in Maranatha Christian University to study and reconstruct the geometric shapes of Surya Kawung Batik. In the making of the Batik motifs, the research methods employed are survey, observation, exploration, testing, and improvement, while in the learning process, the method applied is descriptive qualitative, in which the researchers check the data credibility. Turtle graphics algorithm and mathematical calculations are used to form Batik geometric motifs. The result of this research shows an increase in the students' ability to learn the geometric shapes and to reconstruct digital Batik motifs which resemble the original Batik motifs and which can be stored using a smaller memory. If the memory for storing motifs is small, the required storage space will be more efficient.

DESIGN OF IMPROVED GRID FOR TURTLE ROBOT

Turtle robot is known as a two-wheel mobile robot which can be programmed to do various task such as line following, grid following, wall or obstacle detection and the list goes on. Common turtle robot has the capability of performing line following function only. Another turtle robot’s capability is to do grid following, but this function is limited to the designed grid which is 90 degree grid. The objectives of this project are to design an improved grid including new algorithm that suitable for the use with a turtle robot which allows more than straight line and 90 degree grid. The method used in this project is by exploring several implementation of turtle robot with its grid design. This is the followed by developing improved grid design with new algorithm which is then tested continuously to ensure its functionality working flawlessly. As the result, turtle robot now has the capability to follow 45 and 135 as well as 90 degree grid following. In order to follow the grid designed, it must be preprogrammed with only its orientation and the coordinate. It is recommended to improve the algorithm of this turtle robot so that in can follow grid with less mistakes and to achieve its ultimate goal which is for learning purposes

DESIGN OF IMPROVED GRID FOR TURTLE ROBOT

Turtle robot is known as a two-wheel mobile robot which can be programmed to do various task such as line following, grid following, wall or obstacle detection and the list goes on. Common turtle robot has the capability of performing line following function only. Another turtle robot’s capability is to do grid following, but this function is limited to the designed grid which is 90 degree grid. The objectives of this project are to design an improved grid including new algorithm that suitable for the use with a turtle robot which allows more than straight line and 90 degree grid. The method used in this project is by exploring several implementation of turtle robot with its grid design. This is the followed by developing improved grid design with new algorithm which is then tested continuously to ensure its functionality working flawlessly. As the result, turtle robot now has the capability to follow 45 and 135 as well as 90 degree grid following. In order to follow the grid designed, it must be preprogrammed with only its orientation and the coordinate. It is recommended to improve the algorithm of this turtle robot so that in can follow grid with less mistakes and to achieve its ultimate goal which is for learning purposes

Towards Synthetic Dataset Generation for Semantic Segmentation Networks

Recent work in semantic segmentation research for autonomous vehicles has shifted towards multimodal techniques. The driving factor behind this is a lack of reliable and ample ground truth annotation data of real-world adverse weather and lighting conditions. Human labeling of such adverse conditions is oftentimes erroneous and very expensive. However, it is a worthwhile endeavour to identify ways to make unimodal semantic segmentation networks more robust. It encourages cost reduction through reduced reliance on sensor fusion. Also, a more robust unimodal network can be used towards multimodal techniques for increased overall system performance. The objective of this thesis is to converge upon a synthetic dataset generation method and testing framework that is conducive towards rapid validation of unimodal semantic segmentation network architectures. We explore multiple avenues of synthetic dataset generation. Insights gained through these explorations guide us towards designing the ProcSy method. ProcSy consists of a procedurally-created, virtual replica of a real-world operational design domain around the city of Waterloo, Ontario. Ground truth annotations, depth, and occlusion data can be produced in real-time. The ProcSy method generates repeatable scenes with quantifiable variations of adverse weather and lighting conditions. We demonstrate experiments using the ProcSy method on DeepLab v3+, a state-of-the-art network for unimodal semantic segmentation tasks. We gain insights about the behaviour of DeepLab on unseen adverse weather conditions. Based on empirical testing, we identify optimization techniques towards data collection for robustly training the network

Turtle Geometry in Computer Graphics and Computer Aided Design

LOGO is a programming language incorporating turtle graphics, originally devised for teaching computing to young children in elementary and middle schools. Here we advocate the use of LOGO to help introduce some of the basic concepts of computer graphics and computer aided design to undergraduate and graduate students in colleges and universities. We shall show how to motivate affine coordinates and affine transformations, fractal curves and iterated function systems, relaxation methods and subdivision schemes from elementary notions in turtle geometry and turtle programming