Scopus ID: 85127580665
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
Abstract
The scope of this study folds out the terms of electrical power output generated by the combustion of methane gas in the production of the portable anaerobic digester in kilo Watthour. When the gas flow meter indicated that there is sufficient gas to enter the generator, gas chromatography will again be conducted this time to ensure that the entering gas is really methane. Since there is small load to be powered and only 0.3 m3 of methane that would enter the generator, 1 kW generator would be used to yield sufficient energy which is equivalent to theoretical value of 4.5811 kWh (usable energy) as further explained.
Scopus ID: 85218440706
Computers and Concrete, (2021), pp. 1-25
Journal Article | Published: January 1, 2021
Abstract
Ultra-High Strength Concrete (UHSC) is known for its brittleness compared to traditional concrete, which can lead to sudden collapses. When it comes to columns, failures are particularly serious and require the use of confinement models to accurately predict the strength and strain of confined UHSC columns. While previous confinement models exist, many equations either underestimate or overestimate the confinement of concrete due to idealized assumptions and the exclusion of significant variables. This study employs a hybrid machine learning approach to capture the complex interactions in confinement behavior and accommodate a broader range of peak strength and axial strain parameters in UHSC. Statistical performance measures indicate the superiority of the proposed models over existing equations. Through causal inference, the study assesses the effects and relative importance of each parameter on peak strength and axial strain. The visualizations provided by the performance plots helped identify patterns and correlations that would have been difficult to discern through numerical analysis alone. The developed NN-PSO models are proven effective in reasonably predicting the peak strength and axial strain of UHSC columns.
Scopus ID: 85112824462
International Journal of Emerging Technologies in Learning (iJET), (2021), Vol. 16, No. 15, pp. 31
Journal Article | Published: January 1, 2021
Abstract
Attaining high retention rates among engineering institutions is a predominant is-sue. A significant portion of engineering students face challenges of retention. Academic advising was implemented to resolve the issue. Decision support sys-tems were developed to support the endeavor. Machine learning have been inte-grated among such systems in predicting student performance accurately. Most works, however, rely on a black box model approach. Rule induction generates simpler if-then rules, exhibiting clearer understanding. As most research works considered attributes for positive academic performance, there is the need to con-sider ‘negative’ attributes. ‘Negative’ attributes are critical indicators to possibility of failure. This work applied rule induction techniques for course grade predic-tion using ‘negative’ attributes. The dataset is the academic performance of 48 mechanical engineering students taking a machine design course. Students’ at-tributes on workload, course repetition, and incurred absences are the predictors. This work implemented two rule induction techniques, rough set theory (RST) and adaptive neuro fuzzy inference system (FIS). Both models attained a classifi-cation accuracy of 70.83% with better performance for course grades of ‘Pass’ and ‘High’. RST generated 16 crisp rules while ANFIS generated 27 fuzzy rules, yielding significant insights. Results of this study can be used for comparative analysis of student traits between institutions. The illustrated framework can be used in formulating linguistic rules of other institutions.
Scopus ID: 85127613733
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Mark Justine I. Balbenta, Anton Dominic P. Capistrano, ... Melvin B. Solomon
Conference Paper | Published: January 1, 2021
Abstract
Flood is a natural disaster mostly caused by typhoons that deal with health, property, and economic damages to areas affected by the inundation, especially on low lying areas such as Marikina, like in the times of typhoon Ondoy and typhoon Ullyses. This study aims to develop an accurate flood hazard map with the use of interval rough numbers to improve the urban management and flood response of the local government. The methodology considered elevation, Slope, distance from water surfaces, drainage density, land use/land cover, and soil profile as factors that would be relevant to the flooding of Marikina city. Online surveys were distributed to different experts under the scene of urban planning, hydrology, environmental protection, water supply and sanitation, and transportation to rate each individual factor’s importance with regards to the other factors by using the Saaty rating scale. Interval rough numbers, fuzzy, and crisp AHP were applied to the matrices of the experts’ rating of the factors and integrated with the generated flood hazard map. The generation of flood hazard maps was done with ArcGIS by utilizing different spatial maps gathered from online sites. After integrating the different MCDA techniques, a comparison was done to identify the most accurate on all the techniques and validation was done through utilizing historical flood data of Marikina City. After the application of the different MCDA techniques to the produced flood hazard map and validation by utilizing flood points of Marikina, the Rough Interval AHP proved to be the most consistent out of the two methods with an accuracy of 95.82%, 90.23%, and 80.72%, respectively. The results showed that from the total area of Marikina City, 33.16% out of it is under the classification of “very high” hazard, 24.42% is under the “high” hazard category, 17.67% is under the “moderate” hazard, 13.20% is under the “low” hazard, and 11.55% is under the “very low” hazard.
Scopus ID: 85127555504
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021)
Conference Paper | Published: January 1, 2021
Abstract
In a worldwide perspective of the most common cancer diseases, cervical cancer is ranked fourth most frequent whereas the worldwide mortality rate is at 54.56%. In the Philippines, the second leading site among women is cervical cancer next to breast cancer. Research shows that cervical cancer is one of the most treatable cancer forms if detected and managed early. Currently, the most reliable diagnosis and prevention method of cervical cancer is thru a regular testing via Pap Smear test and HPV vaccination being performed in hospitals worldwide. However, according to the Centers for Disease Control and Prevention in California, the cervical cancer screening rate of regular testing in hospitals went down significantly during the stay-at-home order by the government due to the COVID-19 pandemic. Also, there are limited research based on the behavior information in relation to cervical cancer risk prediction, but existing studies proves the possibility of the risk prediction based on behavior information. This paper presents an Artificial Neural Network-based model for early cervical cancer risk detection based on behavior information. The neural network was trained using scaled conjugate gradient back propagation. The system showed 98% overall correctness in early cervical cancer risk prediction.
Scopus ID: 85127571860
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
Abstract
Air pollution is the atmospheric condition in which substances are present in the air in such concentrations and duration that are detrimental to human health and the environment. The effects of air pollution on public health are being felt worldwide. These are the common air pollutants, including lead, nitrogen oxide, Sulphur dioxide, carbon monoxide, and Total Suspended Particulates (TSP), the latter being the most widespread and the most serious for human health. This study presents a GIS-based mapping as a means for generating high-resolution maps over large geographic areas. A wide range of data collected from different air monitoring stations in the Metro Manila, Philippines, can be managed in the frame of spatial models developed in GIS. The approach of this study is demonstrated by modeling concentrations of Total Suspended Particles for Metro Manila. Mapping of the air pollution using the GIS for seven different stations during the dry and wet seasons from 2016 up to 2020 was developed. The concentration of TSP for the dry and wet seasons were visualized in planar view. The visualized result generated by the GIS has the potential to offer valuable information in demonstrating the air quality index of Metro Manila over the span of 5 years. The results showed that during the wet seasons, the air quality became good. On the other hand, the dry seasons showed the air quality being consistently moderate and, in some parts, changing from being good to moderate. Generally, we can conclude that the public can still enjoy and experience usual activities outdoors, although the results may seem to be at no risk, it is best to be mindful of the current conditions, especially in the present-day, climate change is getting worse.
Scopus ID: 85127565706
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
Abstract
Knowledge in Braille is ultimately necessary to maintain learning for the visually impaired. In the Philippines, class attendance has been showing low rates for visually impaired students caused by the shortages of teachers and the absence of the specialized tools intended for teaching them. A proposed solution in addressing this problem is the usage of computers for the automation in the process of the extraction of information in Braille which can facilitate teaching. In recent years, a considerable amount of effort and attention have been devoted to the development of this kind of technology however in languages other than Filipino Braille. Codes in Filipino Braille with its contractions, and even the Filipino language itself has unique features as compared with other languages. In this paper, a system is proposed which uses machine vision in recognizing Filipino Braille codes including one-cell and two-cell contractions. Synthetic Braille images undergo cascade object detection, image processing, extraction of HOG features to develop the three-stage multiclass SVM classifier. Experimental evaluation results reveal a good performance of Filipino Braille classification and translation to texts.
Scopus ID: 85127599578
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
Abstract
Children storybooks have gone far, from flat books to embossed to Audio-book to Pop-up book and now Augmented Reality books. Augmented Reality or AR is one of the innovative technologies that will be universally used given its potential and fascination.The goal of this study is to create a new way of learning with children storybooks with new technology. The innovation underpinning this research is the embedded Augmented Reality 2-Dimensional of children’s book on a mobile application. The research provides an insight into what was done using AR on children’s story books enabling the reader to place this example of AR in perspective and understand it more clearly. This paper specifically highlights an innovative development of the interfaces for providing an AR children storybook that enhances story reading and learning experience for preschool and young schoolers children via mobile AR application.
Scopus ID: 85127599093
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-5
Conference Paper | Published: January 1, 2021
Abstract
As people remain confined in their homes, more and more turn to the internet and social media daily for support, comfort, opportunities, and access to information. This presents an opportunity for businesses and e-commerce platforms to harness their own data and reach wide audiences through social media. An online store, Anywhere Fitness PH, took this opportunity which was launched to bring gym equipment to the comfort and safety of the homes of its consumers. However, the client, Anywhere Fitness PH, struggled in customer reviews and difficulties with its current e-commerce platforms. The researchers proposed a web application system that will provide their client an e-commerce platform that will utilize data analytics and sentiment analysis for its customer reviews and provide further improvements for the overall business operations of the client. The system passed for both evaluation of Customer Interface and Admin Interface with means of 4.27 and 4.49 respectively, making the Overall Evaluation have a mean of 4.3S. All means are interpreted as “Strongly Agree” which means that the admins, the non-IT, and the IT staff strongly agree that the system passed Functionality, Usability, Reliability, Performance, Security, pertaining that the system is now ready for the use of the client.
Scopus ID: 85125815284
Journal of Engineering Science and Technology, (2021), pp. 33-45
Journal Article | Published: January 1, 2021
Abstract
Data analysis is an integral part of research. Most researchers examine their results by using graphs, tables, charts, and figures. These methods are effective, but knowledge transfer is limited because it only depends on what the authors or researchers have presented. The need to scrutinise further the given data is essential. One way of addressing this problem is to utilise a graphical user interface (GUI), wherein a user can manually choose some parameters of an extensive dataset to display and analyse. In this paper, the results of the four variants of clustering techniques, namely the Ant Colony Optimization (ACO), Gaussian Mixture Model (GMM), K-Power Means (KPM), and Kernel-Power Density-Based Estimation (KPD), in grouping the wireless multipath propagations, are evaluated through the use of a GUI. The accuracy performance of each clustering algorithm can be obtained by choosing in the GUI the corresponding channel scenario that the user would like to investigate. A deeper analysis of the clustering characteristics can also be done by selecting other parameters in the GUI. This selection gives a better understanding of the behaviour of each clustering technique and provides an effective way of presenting and analysing the different sets of data.