Research Publications

Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/4194

This main community comprises five sub-communities, each representing the academic contribution made by SLIIT-affiliated personnel.

Browse

Filters

2021 - 20222

Advanced Search

Filter by

Settings

Type: search.filters.itemtype.Thesis

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationEmbargo
    Identifying Objects with related Angles using Vision-based System integrated with Service Robots
    (2022) Lakshan, K.K. Pasindu
    Manipulation an object can be done with the collaboration of a human to a robot by introducing the object in a proper way. To do this in an easy way, we can model the object inside the robot head and add some sensors and cameras to identify the specific object. But when it comes to the real world, we cannot model all the objects in the world inside a robot head. If we can manipulate every object there can be more work would have done by the robots in efficient way. This research will present a strategy to identify the unknown objects using a visionbased system and with the perspective angles of the detected object and the system is integrated with service robots. This will go in a way when the robot should be able to identify the objects around the robot in an asynchronous manner with rotational angles and the pitch and roll angles, perspective to the robot standing surface. The research will be based on Artificial intelligence, Machine learning, and Robotics. Robotics operating system is used for simulating the robots and identification. For the identification process, a few ways can be used. Vision-based identification using color and depth images from an RGB camera, and this research is mainly based on this RGB, and depth feature integrated with YoloV5. And there are some other ways to identify objects like using a 3D-LiDAR laser scanner. However, this learning process, should have a stable object to model and train the object. After the object recognition, by using the proposed methodology robots can calculate and estimate the angles of the detected object. After the acquisition, the robot should be able to identify the object any time when it sees the object. Since this is a robot, we can use this to model unknown objects and retrieve the data from its database and manually name them if there is no one to name it in the time being
  • Thumbnail Image
    PublicationEmbargo
    Analysis on the Risk and the Categorization on Test Automation in Sri Lankan Software Industry
    (2021-08) Sundaralingam, Sakthi
    Delivering quality software to customer is the key objective of software industry. One of the essential fragment of life cycle of software is software testing. In software testing test automation is playing a major role. Test automation is an art which needs to be managed and executed properly in order to provide quality software. If test automation cannot be practiced in proper way the delivery of the software quality would impact directly and leads to loss of customer, which is a failure of business. Test automation contain several phases from scoping to maintenance. Each phase has several steps which require right analyzing, decision making and operating. Test automation has several problems which needs to address in each stage. Test automation cause several issues when execute test automation in a company. All these issues need to be handled by different people, therefore initially issues need to be identified and classified and then solve properly. This research is to identify the improvements to categorize the problems automatically and find the solution for the problem in test automation process and hence to practice the test automation in healthier way in order to achieve better software quality. Test automation issue are analyzed and the solutions are proposed. On which stage, the test automation is causing problems and how to solve them are recommend in this research, Test automation issues are categorized and under relevant category therefore issues can be solved speedily. The automation cause huge amount of issues. Test automation is running over nigh in most of the companies and it result lots of issues. These issues can’t be analyzed one by one and allocated to relevant people. The implementation of this research will categorize the issues under relevant category and which would lead for speedy allocation under relevant person and solution. This research produced a system to categorize the test automation problems in automatic way using text classification approach. The issues are passed as sentence and they are categorized under the relevant category to fix them quickly. The sentences are preprocessed and conducted feature selection using filter methods and predict under appropriate category. The issue has been cleaned in preprocess stage. Implemented LSTM base algorithm using filter method to categorize the issues.Find the solution for the problem in test automation process and how to practice the test automation in healthier and proper way in order to achieve better software quality. In this research an implementation to categorize test automation problems were formed. Recommendation and solutions are proposed on test automation which would aid to practice test automation in better way and that would leads to better software quality delivery.