Scopus ID: 85064126714
2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), (2018), pp. 1-6
Francis B. Malit, Irister M. Javel, ... Melodia Pahati
Conference Paper | Published: July 2, 2018
Abstract
A design of a secondary power supply using Proportional-Integrative-Derivative (PID) controller has been implemented for better compensation, response and output in comparison with a conventional control strategy of a switch mode converter. A boost converter for an automobile battery as a power source with adaptive control has been introduced in the design. The offsetting and joggling of a 3D printer is manifested as electronic load during the testing. An analysis about the modes of controlling a switch mode power supply (SMPS) has been made using: (1) MATLAB for simulation of graphical presentation of the method and for analysis of transient response of the design and (2) NI Multisim for simulation of SMPS circuit including PID control and conventional SMPS circuit with a fundamental compensation circuit. The two approaches are compared in this paper. The simulations have shown that PID compensates for error in output response and decreases the response time of the converter circuit. Overall the entire design scheme is successfully verified through simulations and by prototyping that shown improvement on dynamic performance (response and efficiency) as compared with the conventional scheme. With the use of adaptive controller, the performance of the boost converter has improved mainly with reduced its response time (3.64ms settling time and 467μs peak time) ensuring its effectiveness in adapting to changes in the power demanded by the load.
Scopus ID: 85064124861
2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), (2018), pp. 1-5
Conference Paper | Published: July 2, 2018
Abstract
Predicting the compressive strength of self-compacting concrete (SCC) is one of the complicated tasks because of its complex behavior due to the reaction of chemical and mineral content and the hydration process of cement. The distinct difference of SCC to normal concrete is its improved workability or also known as rheology that is divided into four categories namely viscosity, flow ability, passing ability, and resistance to segregation. It was proposed in this study to include the rheological behavior of SCC to the prediction of its compressive strength. Neural network was utilized for predicting the 28th day compressive strength of SCC. A 97.78% prediction rate was achieved using a feed-forward back-propagation ANN with 1 hidden layer and 8 hidden nodes. Tansig transfer function was used as activation function. The model has a Pearson R value of 0.991 and mean square error (MSE) of 3.42.
Scopus ID: 85064126672
2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), (2018), pp. 1-6
Conference Paper | Published: July 2, 2018
Scopus ID: 85063188183
TENCON 2018 - 2018 IEEE Region 10 Conference, (2018)
Conference Paper | Published: July 2, 2018
Abstract
One of the predominant cause of the diminishing productivity of the Philippines that affects its residents and industry sectors alike is no other than the unresolved traffic. Numerous efforts have been implemented in the country to regulate traffic including road expansion, highway development and application of several traffic schemes. One of the research thrust being studied is the solution to the limitation of traditional traffic light systems. Existing literatures in traffic light system embarked on intelligent transportation system (ITS) that is typically based its operation on real-time traffic density data, however implemented in limited control. This paper discussed an approach in developing traffic signaling system capable of prioritizing congested lanes based on real-time traffic density data and integrated with an automated and manual control ported in a mobile android-based application. The system worked with CCTV cameras positioned at every lane of the intersection for the acquisition of traffic images transmitted to the Raspberry Pi 3 microcontroller for traffic density calculation using image processing. It utilized a traffic monitoring system and traffic lights operation control via a mobile android-based application. The system was tested and yielded an average of 92.83% and 85.77% vehicle detection rate for daytime and nighttime respectively. Moreover, an overall system reliability of 92.82% and 85.77% were obtained during daytime and nighttime testing based on the android GUI, lane prioritization and traffic light response. Future work involved integrating the Internet of Things (IoT) on the traffic light system for a wider scope interconnected implementation.
Scopus ID: 85063226839
TENCON 2018 - 2018 IEEE Region 10 Conference, (2018), pp. 0194-0198
Conference Paper | Published: July 2, 2018
Abstract
This paper presents a classification algorithm for air quality index (AQI) using fuzzy logic (FL) system. AQI tells the level of cleanliness of the air and provides a corresponding health warning. In this study, two types of input pollutants are only considered which are the carbon monoxide (CO) and nitrogen dioxide (NO2). Each input is classified into six categories that include very low, low, moderate, high, very high and extremely high. Mamdani fuzzy inference system (FIS) is used to process the FL system giving an output of AQI values expressed in six categories: good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy and hazardous. Simulation is performed using MATLAB fuzzy logic toolbox, which provides effective and reliable results.
Scopus ID: 85054578633
Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering (WCSE 2018), (2018), pp. 730-734
Conference Paper | Published: January 1, 2018
Abstract
The study aims to create an application using openCV that can identify and calculate the vegetation part of a satellite image. The study utilized the two out of seven Landsat-8 band images over a part of Metro Manila in Philippines acquired on Feb. 13, 2016. These band images are Bands 4 and 5 which are normally used to compute the vegetation index of a satellite image. The algorithm calculates the relative area of the vegetation using Normalized Difference Vegetation Index or NDVI formula. The output of the NDVI creates a single-band dataset that only shows greenery. Values close to zero represent rock and bare soil and negative values represent water, snow and clouds. Taking ratio or difference of two bands makes the vegetation growth signal differentiated from the background signal. Water has an NDVI value less than 0, bare soils between 0 and 0.1, and vegetation over 0.1. Increase in the positive NDVI value means greener the vegetation. The sample satellite image is Manila with Landsat-8 operational land imager (OLI) images. The study aims to test the NDVI formula in extracting vegetation index of Manila region which can be used to monitor the urban and classification of a certain region.
Scopus ID: 85054601813
Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering (WCSE 2018), (2018), pp. 298-302
Conference Paper | Published: January 1, 2018
Abstract
Academic Analytics is extracting hidden patterns from educational databases. The main goal of this area is to extract hidden patterns from student academic performances and behaviors. One of the main topics in academic analytics is to study the academic performance of freshman students. Students enrolled in first year are the most vulnerable to low student retention in higher education institution. Research studies from different Higher Educational Institutions already indicated that early identification of students with academic difficulty is very crucial in the development of intervention programs. As such, early identification of potential leavers and successful intervention program(s) are the keys for improving student retention. The study will utilize the available enrollment and admission data. Feature selection technique will be used to determine significant attributes. The study aims to produce predictive and cluster model in which can early identify students who are in need of academic help and program interventions. The extracted predictive and cluster models will be evaluated using confusion matrix and be integrated in the decision support application.
Scopus ID: 85045215426
Journal of Telecommunication, Electronic and Computer Engineering, (2018), pp. 15-20
Pocholo James M. Loresco
& Aaron Don Munsayac AfricaJournal Article | Published: January 1, 2018
Abstract
Analyzing cardiovascular activity of patients using ECG clinical paper printouts requires prior knowledge and practice. This research used spatial-oriented image processing methods for analyzing ECG readings by retrieving only the essential features, and not all ECG data, to assist physicians in diagnosis. Different values such as Atrial (rate/min) and Ventricular (rate/min), QRS interval (sec), QT interval (sec), QTc (sec), and PR interval (sec) were successfully extracted with indication as to whether the values are within the accepted normal values, given the patient’s gender and age. Performance of the system was tested based on accuracy, RMSE and normalized RMSE. The methodology achieved average accuracy as high as 95.424 % while the PR interval feature extraction achieved a relatively low average accuracy of 87.196%.
Scopus ID: 85045512343
Proceedings of the 2017 International Conference on Information Technology, (2017), pp. 184-189
Gene Justine P. Rosales &
Ace C. Lagman
Ace C. Lagman
Conference Paper | Published: December 27, 2017
Abstract
The study focused on developing Industry Academe Linkage Alumni and Placement Portal for FEU Institute of Technology that will monitor student progress in their internship and monitor alumni in their job placement. The purpose of the development is to automate the workflow and processes of interns for industry placement and tracking of alumni. The study is designed to eliminate the manual process of alumni tracking, student application for internship and industry job opening postings. The main gist of the project consists of intern monitoring module that monitors who are deployed and accepted already; alumni monitoring module to trace and monitor alumni if there are in their field of specialization and report generation module that it capable of generating dynamic reports of alumni, industry partners and interns. The study used Incremental Model Process as software process model in which is combined by the elements of the waterfall model with the iterative philosophy of prototyping. The proponent considered iterative life cycle model which consists of four phases. To determine the acceptability of the developed prototype ISO 9126 was used. The metrics consist of criteria such as functionality, usability, reliability, portability, and sup portability as perceived by end users. The overall evaluation of the system is 4.21 with an interpretation of Satisfactory. This concludes that the application is ready for deployment.
Scopus ID: 85045518861
Proceedings of the 2017 International Conference on Information Technology, (2017), pp. 206-211
Conference Paper | Published: December 27, 2017
Abstract
Event Management Solution is a web application for EINS Consultancy that allows users to manage events, announcements, and content of the website. Management includes creation, deletion, update, and view. Both the System Manager and Administrator have the privilege to manage events, announcements, and content of the website. Only the System Manager has the privilege to manage user accounts and view the audit trail. While the end-user is able to view the created events and posted announcements. Also, an end-user could register to available events through an electronic form. EINS event management solution is a platform that handles event management and registration modules. With the above mentioned features, the system can produce easy access reports from the centralized repository of data. This leads to lessen or illuminate inaccurate reports from the current processes used by EINS Consultancy. The researcher used prototyping model as a software developmental technique in developing the application. Different test levels were conducted in order to determine the acceptability of the software which include alpha, beta and user acceptance test.