Diabetic retinopathy is a serious complication needing prompt diagnosis and medication to avert vision loss. Lesions caused by the condition are difficult to track because they are hidden behind the eye's structure in small and subtle forms. To extract relevant features., we created a robust pipeline using multiple preprocessing techniques., image segmentation architecture (DR-UNet) with atrous spatial pyramid pooling., and an attention-aware deep learning convolutional network with different modules based on ResidualNet. Empirical results show that our framework has segmentation accuracies of 87.10% (intersection over union) and 84.50% (dice similarity coefficient). Moreover., classification performance of 99.20% provided better results than existing schemes., as reinforced by the smooth convergence of training/validation loss and accuracy. This study has the potential to supplement traditional diagnosis to identify better the ailment in its early and advanced stages.

Technological advancements and modernization of different industries and disciplines contributed to more consumption of oil and electricity which powers these industries. Aligned with the United Nations (UN) Sustainable Development Goals (SDG), the use of alternative and renewable energy (RE) sources is encouraged as it allows the utilization of clean energy resources and access of populations in developing countries to electricity and energy. Forecasting and maximizing the harvest for renewable energy requires an understanding of the mechanics behind the variables that impact solar photovoltaic production. 755 datasets were created from 150 days of recorded data and used in the model building and sensitivity analysis. The approach used in this study to identify the variable importance of each meteorological variable to the solar photovoltaic (PV) production was the Garson’s algorithm (GA). In this study, an artificial neural network (ANN)-based sensitivity analysis (SA) using Garson’s algorithm (GA) was implemented to identify the relative importance (RI) of the factors influencing the solar PV output including the solar irradiance (SI), rainfall, maximum temperature (MaT), minimum temperature (MiT), relative humidity (RH), and wind speed (WS). The model also considers the relative significance of these parameters to the solar PV output. Results indicate that, with a relative value of 29.48% and 5.01%, respectively, solar irradiance and wind speed are the most and least important factors.

FEU Tech’s College of Computer Studies hosts an annual event known as Technology Innovation on Capstone Project (TICaP), which exhibits the different capstone projects of each specialization. This event allows the students to view the different projects of the FEU Tech PBL students and recognizes the group with the best capstone project and other special awards. However, problems were encountered while managing the event resulting in disorganized planning and management. The proponents developed an event management system named TICaP HUB to solve the different problems experienced by the organizers in planning and managing the event. The team conducted a system evaluation and survey of the PBL and non-PBL students, including FEU Tech faculties. Using the Likert scale for the system evaluation, the Web application has an overall weighted mean of 4.72 and 4.71 for the mobile application. This outcome can be interpreted that the users strongly agreed with the FURPS evaluation of the system. With the results acquired from the respondents, the proponents conclude that using the TICaP HUB can significantly help the users efficiently manage the TICaP event and lessen the time consumed in planning and organizing for the said event.

E-commerce plays an essential role in selling products or services online because it can reach more customers than traditional retail. If the customer data is appropriately mishandled, it disrupts the business’ data organization and poor customer relationship management. The study focuses on creating an e-commerce website that efficiently handles the data and integrates a personalized hybrid recommender system. Content-based and collaborative filtering methods were used in the recommender system to improve customer relationship management, streamline procedures, organize inventory and sales, and increase profits. Sales forecasting using ARIMA was also added to use the customer data for efficient business decisions. ISO 9126 was the software quality model used to evaluate the developed system using the software quality characteristics functionality, usability, maintainability, and efficiency. The system got an overall mean score of 4.57, which is excellent, which means the system can perform smooth transactions from ordering up to the checkout and organized products, sales, and inventory. The integration of the recommender systems was able to give recommendations based on the customer's preferences, which enhances the user experience that may lead to an increase in sales of the business since the suggestions are tailored recommendations to the users.

E-Government systems have brought significant changes on the way public services are easily being delivered nowadays. This motivates the researchers to contribute to this innovation by developing a system named “BALANGAY” which makes barangay services more accessible to the constituents. This is anchored with the objectives of the study which is mainly to build a centralized database for barangays and design modules with the purpose of streamlining barangay processes. Part of it is to generate an incident heatmap that will assist barangay officials in creating better programs and project developments. The study is a combination of qualitative and quantitative type of research which is reflected on the use of interview and survey questionnaires. An iterative waterfall methodology was also adopted as a guide in the development process. Meanwhile, the ISO 9126 Software Quality Model was used in the system evaluation wherein each response is measured using the 5-point Likert scale and respondents were selected using purposive sampling. The result shows that out of sixteen (16) barangay constituents and sixteen (16) IT experts who participated, most of them were very satisfied with the system with a weighted mean of 4.45 and a verbal interpretation of “Very Satisfied”.

The difficulty with manually analyzing and processing data is that it takes too long, prone to degradation and other problems. Government agencies cannot reduce cases due to a lack of sufficient knowledge and analysis to determine the fundamental trend of RTI cases. Besides, the general public is utterly uninformed of road situations. Roadcast, a Vehicle Incident Management System, is a practical approach to minimizing road incidents. This study presents the automation of the manual process of collecting and analyzing incident data and transparency with the general public. The output of the study will be a web application system that will produce descriptive analytics, hot spots, and forecasting (7MA), supporting the PNP’s preparation for the projected future incident cases in the following week and determining the hazardous area in Pasig City through the hot spots. The general public will be informed of the number of road incidents in a particular barangay, entire cases in Pasig City, and other data visualizations integrated into the dashboard. Scrum Methodology was used to construct the system, and numerous users with varying responsibilities and administrator permissions were necessary to access and control the system. Alpha and Beta Testing examined the system’s functionality, usability, reliability, performance, and supportability. The researchers used purposive sampling to survey (11) technical and (49) non-technical respondents. The researchers received a score of 4.74, which translates to “Strongly Agree.” The system received positive feedback from both technical and non-technical respondents.

This capstone project aims to create a visual book with an augmented reality feature and a CMS-based website. The application uses augmented reality technology to track target images on the book and display 3D models and animations of the 30 endangered bird species in the Philippines. To elaborate, when a target image is found, the application will display the 3D model of the bird and two different animations for the user to explore. The application was developed using Vuforia and Unity; the 3D models of the endangered bird species will be modeled and animated using Autodesk Maya, Substance Painter, and ZBrush, and the design and layout of the book were created using Adobe Photoshop and Adobe InDesign. The developed system is one of the first AR books about endangered bird species in the country, attempting to disseminate information and raise awareness about the status of endangered birds using augmented reality. To prove that the application is practical and usable, the researchers surveyed 70 respondents consisting of ten from the client’s organization, 40 from the general public, ten bird lovers, and ten I.T. professionals. Based on the survey results, the system proves to be practical and usable in disseminating information and raising awareness about the status of endangered birds. Future researchers can improve the system by adopting some features and enhancing the application so that users can still utilize the mobile application even without the visual book. The researchers also encourage future researchers to implement the application in other devices with different operating systems, such as iOS and Windows, to cater to a broader range of users.

Nanolearning (NL) is a promising approach to education and training as it delivers small, bite-sized chunks of learning content that can be easily consumed and retained by learners. This allows quickly accessing specific pieces of information and knowledge, which can be delivered through a variety of mediums, such as videos, podcasts, or mobile applications, etc. NL has significant potential in educational and training settings, where learners or trainers can quickly upskill or reskill in specific contexts, improving their productivity and mastering some topics. This study provides an overview of NL, addressing the design of NL educational materials and its implementation in several educational applications. It also highlights some considerations and issues. In conclusion, it is recommended that reliable learning resources be used by teachers, the content be closely assessed, the source format be considered, bias be checked for, and learner feedback be obtained to ensure the quality of NL materials. By following the proposed NL framework, teachers can provide their learners with top-notch and productive NL resources.

When it comes to asynchronous online learning, the literature recommends multimedia content like videos of lectures and demonstrations. However, the lack of emotional connection and the absence of teacher support in these video materials can be detrimental to student success. We proposed incorporating talking heads and annotations to alleviate these weaknesses. In this study, we investigated the cognitive and affective effects of integrating these solutions in asynchronous video lectures. Guided by the theoretical lens of Cognitive Theory of Multimedia Learning and Cognitive-Affective Theory of Learning with Media, we produced a total of 72 videos (average = four videos per subtopic) with a mean duration of 258 seconds (range = 193 to 318 seconds). To comparatively assess our video treatments (i.e., regular videos, videos with face, videos with annotation, or videos with face and annotation), we conducted an educational-based cluster randomized controlled trial within a 14-week academic period with four cohorts of students enrolled in an introductory web design and development course. We recorded a total of 42,425 total page views (212.13 page views per student) for all web browsing activities within the online learning platform. Moreover, 39.92% (16,935 views) of these page views were attributed to the video pages accumulating a total of 47,665 minutes of watch time. Our findings suggest that combining talking heads and annotations in asynchronous video lectures yielded the highest learning performance, longest watch time, and highest satisfaction, engagement, and attitude scores. These discoveries have significant implications for designing video lectures for online education to support students’ activities and engagement. Therefore, we concluded that academic institutions, curriculum developers, instructional designers, and educators should consider these findings before relocating face-to-face courses to online learning systems to maximize the benefits of video-based learning.

The impact of digital games on chemistry education has received less attention compared to other scientific fields. This research gap resulted in a limited understanding of how to effectively design mobile chemistry games (MCG) distinct from non-science mobile learning games (MLG). This study aims to explore students' attitudes toward MCG and gather their opinions on the game components using a mixed-methods research design. A total of 698 students from urban universities, categorized into technology, chemistry, and education cohorts based on their academic majors, participated to provide diverse perspectives. The results revealed significant disparities in gameplay experience, particularly in competence and relatedness, between MLG and MCG. Students' educational background significantly influenced their confidence and leisure levels. Concerningly, students exhibited a negative attitude towards MCG. The study provides game developers with a guideline for developing MCG and offers chemistry teachers a framework for selecting appropriate MLG in the context of chemistry education.