Image processing plays an important role in extracting useful information from images. However, the image processing and the process of translating an image into a statistical distribution of low-level features is not an easy task. These tasks are complicated since the acquired image data often noisy, and target objects are influenced by lighting, intensity or illumination. In the case of flower classification, image processing is a crucial step for computer-aided plant species identification. Flower image classification is based on the low-level features such as colour and texture to define and describe the image content. Colour features are extracted using normalized colour histogram and texture features are extracted using gray-level co-occurrence matrix. In this study, a dataset consists of 180 patterns with 7 attributes for each type of flower has been gathered. The finding from the study reveals that the number of images generated to represent each type of flower influences the classification accuracy. One interesting observation is that duplication of very hard to learn images assist Neural Network to improve its classification accuracy. This is also another area that could lead to better understanding towards the behaviour of images when applied to Neural Network classification.
Students’ attendance in a university is commonly being monitored by lecturers and the Academic Affairs Division (AAD) as it may help to identify students’ problems at an early stage. This project aims to monitor the students who have the possibility to be absent from classes for more than the permissible percentage. Thus, the purpose of this research is to develop a students’ attendance monitoring system with Short Message Services (SMS) notification (SAMS). This system helps the AAD to manage the absenteeism report from lecturers and it automatically sends the information through SMS notification to the parents and the students themselves. The system has been developed using the Waterfall Model methodology that consists of five phases which are analysis, design, implementation, testing, and documentation. The results from the usability testing show that SAMS can help lecturers to monitor students’ absenteeism more easily and efficiently. Furthermore, the integration of the system with SMS is very useful as it can directly notify the parents regarding their children’s attendance problem.
Nowadays, technology has played a vital role in revolutionizing the food delivery service and benefits the students, runners, and food outlets in many ways. Life as a student is known to be challenging due to academic load, assignment deadlines, bouncing back and forth to class, extra-curricular activities, etc. This is a typical daily scenario on campus that require good time management. In the preliminary investigation of this study, students prefer to take away their food and dine in their rooms so that they will not waste their time by spending too much time in the cafeteria. It is found that convenience is the prime factor for the students as the orders can be made as simple as a few clicks on any mobile device, and the food and beverages are delivered to their doorstep. Additionally, this can prevent them from spending too much or wasting time buying food. Since food delivery becoming popular and preferable recently, thus, this study is aimed to develop a mobile application named e-Runner for the campus food delivery system. Students can make a food order, check the order status, and view a variety of food and beverages from several food outlets. The modified Waterfall Model has been used as the methodology of this study and consists of 4 phases, namely Requirement Analysis, Design, Implementation, and Testing. The application has been tested using two types of testing; Functionality and Usability Testing. The testing results show that this application has many benefits, such as saving time, convenience and act as an all-in-one platform. Furthermore, it can enhance students' lifestyles and can improve customer experience.
This study presents the use of web SMS technology as an alternative method for primary school notification system. By integrating the system with SMS gateway, it will enable the primary school notification system to send information to parents’ mobile phone directly. The traditional methods of notifying parents about the school matters by sending letter and written memo are time consuming and the updated information may not reach the parents. This integration allows information to be disseminated from computer to mobile phone at any time without requiring face to face meeting or the use of other media such as paper-based notice or verbal notice from the students. Furthermore, parents can always be alert and aware of the latest announcement or information no matter where they are. A usability testing was conducted to 20 users to survey the feedback on SMS technology to notify parents. The results from the testing stated that 100% of users give positive feedback about the ease of use and satisfied that the system can replace old systems. Based on the results, it shows that the integration of primary school notification system with SMS technology is highly recommended.
Sign language is the communication language used by people with disabilities, especially deaf and hearing-impaired people. The communication between normal and disabled people using sign language will help them carry out their daily activities. Unfortunately, normal people are not aware of the importance of sign language because they are not directly dealing with disabled persons. Besides, some normal people found that sign language is difficult to learn. This study focuses on developing a mobile application for sign language with augmented reality features. This application is targeted at normal people as a sign language learning tool, and augmented reality will make the learning process effective and exciting. The methodology for this study is the ADDIE model that consists of five phases, namely Analysis, Design, Development, Implementation, and Evaluation. This application will assist the users in learning sign language interactively and interestingly. The evaluation of the application was done by the expert in the related background and the normal people. The usability test result revealed that the sign language application is usable for normal people to know and learn the basic sign language. In conclusion, the sign language application is an interesting application for normal people to use and learn sign language.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.