Scopus ID: 85127580954
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Richard D. Andress, Jason James V. Robin, ... Bon Ryan P. Aniban
Conference Paper | Published: January 1, 2021
Abstract
Solid waste management has been a major issue in developing countries such as the Philippines, as the nation improves living, economic growth, industrialization, and increase in population. Another major issue is the lack of electricity in the Philippines, particularly in the province. The Philippines’ plan for full electrification of all households becomes difficult due to its topography, and geography. This study aims to provide an alternative solution for both issues by innovating through Waste-to-Energy. Waste-to-Energy is one of the alternative solutions in response to the worsening municipal solid waste in the world and source of electrical energy. A small-scaled incinerator was built for an alternative solid waste management machine and micro-electricity supply for rural communities. Instead of burning the waste or dumping it in the landfills, it will be processed in the prototype to lessen its environmental impact. This is possible using air filter bags and crushed mussels, which lessen the air pollution produced during the incineration process of the waste as it builds up heat. The thermoelectric converter would absorb the build-up heat, convert heat to electricity, and store in a battery. The findings demonstrated that it is possible to generate up to 0.317 kW of electricity from 8 kilograms of waste using thermoelectric converters. This quantity can produce electricity for several households in municipal rural areas.
Scopus ID: 85127548069
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 threat of a massive spread of the SARS-CoV-2 virus in the Philippines prompted its government to implement community lockdowns all across the country. The first of which was implemented in Metro Manila beginning on 15 March 2020 and lasted up to 15 May 2020. During the lockdown, all schools were prohibited to conduct face-to-face classes while businesses were encouraged to implement work-from-home arrangements. FEU Institute of Technology (FEU Tech), located in Metro Manila, Philippines, was able to quickly adapt to the health crisis mainly due to its previous implementation of Canvas, an online learning management system, in 2017. The mechanical engineering department at FEU Tech revised its strategy in its implementation of its undergraduate Mechanical Engineering Project Study course (MEPROSTUD) to adapt to the class disruptions caused by the community quarantines imposed in Metro Manila. Comparing student performance before and during the pandemic, it was observed that there was a significant decline in oral communication and a significant improvement in written communication in MEPROSTUD1 and MEPROSTUD2, respectively. This paper documents the experiences of the mechanical engineering department at FEU Tech in its implementation of MEPROSTUD courses during the pandemic and intends to provide additional information to other engineering schools about how to remotely implement their undergraduate thesis courses.
Scopus ID: 85127585497
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Sophia Chloe Caress, Angela Abigail Belen, ... Melvin B. Solomon
Conference Paper | Published: January 1, 2021
Abstract
Agriculture relies heavily on weather forecasts, and a reliable weather forecasting system can help mitigate the calamities which can affect this industry. Rainfall and meteorological drought duration forecasting are some of the most important yet challenging tasks. This paper presents the creation of feedforward backpropagation artificial neural networks for daily rainfall forecasting and monthly meteorological drought forecasting. Artificial Neural Networks can capture the variability of these phenomena. Rainfall data from nine stations all over Albay, the Philippines, spanning from 1967 to 2000, were used to create the models. The input parameters used for developing the models for daily rainfall forecasting were 14-day antecedent rainfall, current-day rainfall, relative humidity, mean temperature, and sunshine duration. The monthly meteorological drought forecasting parameters were 1-month SPI, current-month rainfall, relative humidity, mean temperature, and sunshine duration. Having the results presented in this paper, the performance of the ANN Models of the stations were compared based on R and RMSE. The rainfall forecasting models and meteorological drought forecasting models have provided satisfactory performance. A satisfactory performance for forecasting has an R-value ranging from 0.2 to 0.5. Sensitivity analysis indicated that the most significant parameter for rainfall forecast is the relative humidity and mean temperature for drought forecast.
Scopus ID: 85127561009
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-5
Janice A. Abellana
& Ephraimuel Jose L. AbellanaConference Paper | Published: January 1, 2021
Abstract
Noise pollution from public trains in the metro impacts both children and adults daily, posing a challenge in their daily lives. Noise has an impact on the community’s psychological and physical well-being. The Philippine National Railways trains are an integral component of the daily lives of the city’s passengers. Trains are a popular means of transportation for commuters, as it is the best and only option to travel quickly and get to your destination. Because of the severe traffic circumstances and conditions of land transportation such as jeepneys, private vehicles, and others, Filipino commuters are significant respondents to the study.
Scopus ID: 85127559713
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
Coding is widely regarded as a fundamental skill of the 21st century. Yet, there is still a shortage of programmers worldwide which disproportionately affect the innovation goals of many sectors. In this study, we evaluated the installment of a Python programming gamified course in higher education, and measure its effect on students’ knowledge, attitude, self-efficacy, and skills performance. Two sections with 50 students each were randomly assigned to experimental or control groups. After one semester, the experimental group exhibited significantly higher scores in laboratory activities (skills performance) compared to the control group. Furthermore, they demonstrated a significant improvement with reference to attitude and self-efficacy before and after intervention. Therefore, we concluded that the use of a Python programming gamified course was an effective method for students to learn coding and programming concepts. The use and installation of a gamified course in learning other computer programming languages is highly recommended.
Scopus ID: 85127588959
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
John Mark Cagurungan, Royvin Factuar, ... Jon Arnel S. Telan
Conference Paper | Published: January 1, 2021
Abstract
Solid waste generation is one of the world’s most prevalent challenges, especially in places with crowded populations and inadequate solid waste disposal strategies. There are several extant influencing variables on solid waste creation. In this regard, the researchers focus on five (5) elements or categories that contributed the most to solid trash generation. The researchers sought to determine which one has the greatest influence on solid waste generation in Barangay Sagrada Familia among these five categories. This will contribute to their future solid waste management plan through minimizing, segregating, and recycling the solid waste, which is one of the causes of their flooding problem. ANN (Artificial Neural Network) is a simplified computational brain model that is one of the most often utilized artificial intelligence in solid waste management. To get the desired outcomes, Matrix Laboratory (MATLAB) testing is essential. The researchers gathered information from studies, theories, and literature in the field. The researchers then performed a survey to gather data and existing data in the barangay and used Excel and Matrix Laboratory (MATLAB) to construct the model for a Neural Network analysis. Finally, the authors analyzed the Neural Network, with the goal value varying according to Pearson’s Correlation Coefficient (R).
Scopus ID: 85126632773
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
Higher education institutions (HEIs) are looking for new methods to assess and monitor student learning outcomes, as well as objectively determine the circumstances that contribute to their growth in different courses. Advances in new analytics tools that put visualizations and dashboards on top of live student data are making learning analytics more powerful than ever. This study utilized a participatory design (PD) technique to formulate an analytics dashboard intended for higher education. The rationale behind the study lies on the belief that an information system must be designed for users, rather than users having to accommodate a wide range of adjustments just to utilize such application. Students and teachers were recruited for their feedback and observations, respectively. After multiple PD sessions, four main crucial factors were derived: (1) who has access to data, (2) importance of time, (3) learning analytics should help students make the transition to university life, and (4) it should be discipline-specific. This study opens up a discussion on the importance of human-centered design through the use of PD and how learning analytics dashboard can be maximized to its potential when deployed in the academe.
Scopus ID: 85127578555
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
This device can be useful by rice field owners to decrease the number of pests in rice fields, also this will provide a non-chemical and energy saving way utilizing UV LEDs to attract bugs and capturing them then the system will be controlled by a microcontroller. Rice, the staple food of over half of the world’s population, is locally known in the Philippines as palay, bigas, or kanin. As population grows, demand for rice increases. Thus, the need for sufficient rice production is also needed. Different agrarian problems come with the production of rice the most destructive are pests. The results we’ve yield were, the pests were attracted best in UV light. Also, the laser sensors we’re effective in detecting and capturing the pests. Basically this device won’t harm the rice crops resulting to a greater production and more profit because it is a non-chemical device and energy saving way utilizing UV LEDs to attract bugs and capturing them.
Scopus ID: 85127601486
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 construction industry is heavily reliant on the production of laborers, and construction labor costs share a big part in the total cost of the projects. Due to the emergence of the COVID-19, the construction industry has been experiencing restrictions and limitations in their project sites, affecting labor productivity. This paper aims to determine which factors are critical in influencing Construction Labor Productivity in the National Capital Region (NCR) in the Philippines during the COVID-19 pandemic by obtaining each of the critical factors’ respective relative importance index. In order to achieve the study’s objective, the researchers asked experts under the category AAAA companies who have a site and managerial experience during the pandemic to participate in an online questionnaire survey. 34 factors were considered for this study and categorized into four groups: (1) Human/labor; (2) Management; (3) Technological; and (4) COVID-19. The findings of the study were able to identify the 10 significant factors affecting labor productivity during the pandemic: (1) Laborer’s Experience and Skill; (2) Availability of Materials; (3) Clarity of Instructions and Daily Task Assignments; (4) Coordination among Level Design Disciplines; (5) Shortage of Laborers, Construction Method; (6) Prolonged Delivery Period, Limited Number of Work Personnel Per Zone, Leadership of Construction Management; (7) Clarity of the Drawings and Specifications; (8) Communication among Laborers, Rework; (9) Social Distancing, Laborer’s Absenteeism; and (10) Availability of Personal Protective Equipment. The study can guide construction firms for efficient management of laborers during a pandemic to improve construction labor productivity and accomplish a cost-effective project.
Scopus ID: 85127594567
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-5
Diana Rose T. Rivera, Terrence Adrian Arce, ... Adrian Alan Palo
Conference Paper | Published: January 1, 2021
Abstract
In this paper, a Multi-Criteria Decision Analysis (MCDA) is utilized to provide a better strategy and increase the efficiency of solid waste management. The method aims to determine the suitable Waste-to-Energy (WTE) technology for Manila City, Philippines using a pairwise comparisons method known as Analytical Hierarchy Process (AHP). AHP utilized a hierarchy structure consists of objectives, criteria, sub criteria, and alternatives. The criteria selected were environmental, economic, technical, and sociocultural. The WTE technologies selected were anaerobic digestion, incineration, and pyrolysis. Results show that the environmental aspects with 63.80% is the chosen priority. It is followed by the economic and technical aspect with a close relative value of 14.86% and 13.32%, respectively. The sociocultural aspect is the least priority with 8.02%. Using the criteria, WTE technologies were scored and tabulated. After evaluation, it revealed that an anaerobic digester is suitable WTE technology for Manila City, Philippines. Using the chosen WTE technology, result also revealed that 249,318 m3 biogas can be generated after 21 days.