<span>Presently, the demands for rice are increasing. This will affects the need for producing and sorting rice grain in faster and exceed the normal requirement. However, the manual rice classification using naked eyes are not very accurate and only professionals are able to do it. Machine learning is found to be a suitable technique for rice classification in producing an accurate result and faster solution. Thus, a study on the classification of rice grain using an image processing technique is presented. The rice grain image went through the pre-processing process which includes the grayscale and binary conversion, and segmentation before the feature extraction process. Four attributes of shape descriptor which are area, perimeter, major axis length, and minor axis length and three attributes of color descriptor which are hue, saturation and value were extracted from each rice grain image. In another note, a Multi-class Support Vector Machine (SVM) is used to classify the three types of rice grain which are basmathi, ponni and brown rice. The performance of the proposed study is evaluated to 90 testing images which returned 92.22% of classification accuracy. The study is expected to assist the Agrotechnology industry in automatic classification of rice grain in the future.</span>
Fitness and keeping a balanced lifestyle are an important aspect in our daily lives. Being healthy will allow us to conduct our daily activities in a more productive manner. However, it is sidelined by the fact the people now a days are mostly busy with their work and other things, added the fact of the lack of motivation to conduct the physical activities, lead to people not having a balanced life. For that reason, the aim of the developed application is to provide users with an immersive and interactive jogging application which will help in motivating the user into wanting to conduct fitness activities. The interactivity is provided by implementing Geofencing technique, which is by generating a parameter around certain coordinates which when entered by a device will create certain events such as sending notification or directing to a different page. While the immersiveness aspect is implemented using Augmented Reality, which is where a 3D model is anchored into a certain plane which can be seen by using the mobile phones rear camera. The Rapid Development Life Cycle (RDLC) have been chosen as the methodology for the development of the application because it allows developer to iteratively change the system requirements during the development and presentation phase. Functionality testing have been conducted to the developed application.
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