Scopus ID: 85127593238
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
Complete Blood Count is one of the most commonly performed medical laboratory procedure today. It is required to detect various types of diseases. Presently, some small-scale clinics in the country still does the tedious, manual method of counting the blood cell. With Complete Blood Count Analysis System through Image Processing, automated CBC can be performed by mounting the smart phone camera on the viewer of the microscope. The input image will go through several image processing algorithms such as: Binary Thresholding, Clustering, and Hough Circle Technique. The result will be computed through the formulas used in the manual method of the CBC process. Experimental results show the developed system gains 94% of accuracy for counting the Hematocrit, Hemoglobin, Red Blood Cell, and White Blood Cell values.
Scopus ID: 85127569499
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
One of the most crucial parts of online learning is online testing. It is advantageous to users to save material resources while conducting an effective, quick, and secure inspection. The researchers created and built a web-based assessment system. This article discusses the system’s primary operations, objectives, and principles, as well as auto-generating test papers and questionnaires utilizing algorithmic analyses and presenting the system’s security.
Scopus ID: 85127570116
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
Some, if not all, veterinary clinics do not have a record of skin diseases of dogs when they diagnosed them; this is due to lack of manpower over the number of different kinds of animal patient that they cater per day. This also causes some delays in diagnosing other non-visually diseases that other patients might have. Having a system that can be used in pre-examination for visually available infections such as dog’s skin disease and automatically records this diagnosis, can give an advantage to veterinary clinics. This helps the clinics prepare for the kind of patients that they will tend in certain time of the year. Developing a system that can be used in identifying common dog skin diseases for the pre-examination purpose and creating a dashboard that generates a numerical result can be used as an advantage for the veterinary clinics. These can be achieved by using image processing techniques for the prediction model and Convolutional Neural Network (CNN). However, using a common CNN approach, where the main core uses the Central Processing Unit (CPU), tends to train the model longer. To overcome this problem, the use Graphics Processing Unit (GPU) is implemented to enhance the speed of training the model for the system. Having this kind of system really helps the veterinary clinic for their daily work, but this can still be improved by using other approaches to the trained model without ignoring the efficiency and accuracy of the algorithm that is being used.
Scopus ID: 85127555156
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
Shrimp species belong to the class of Crustacea under order Decapoda under suborder Natantia. The shrimp species are characterized with semi-transparent body which grow up to more than 20 cm. In terms of economic impact, the shrimp industry is considered highly profitable based on the studies by WorldAtlas and Philippine Statistics Authority. Therefore, as part of the necessary better management principles (BMPs), shrimp growth should be monitored. However, for the shrimp length is typically measured by a manual tool like rulers or calipers which is known to be a tedious process most especially when large number of samples are considered. Hence, in this study, image processing via OpenCV was utilized to estimate the length of shrimp species. The performance of the image-based approach is compared with the manual measurement and yielded a relative percent error of 6.23%. Based on the results, it can be concluded that the image-based approach can be utilized to determine the shrimp length.
Scopus ID: 85127599872
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 research aims to determine the demographics that affect the solid waste management behavior in San Martin Subdivision in Angono, Rizal, conducted during the time of pandemic. This aims to improve sustainability and help create programs that will improve the participation of the households towards positive waste management. Currently, there are limited studies involving waste management, especially in developing countries like the Philippines, where waste management problems are more prevalent, adding more solid wastes during the pandemic period. This will help developing countries improve their waste management system as it will open areas for research and development. The researchers seek through the study of the demographics that affects the attitude, knowledge, and practices of the households to create a more targeted solution for the area. Online questionnaires were distributed to the respondents and were analyzed using the Kruskal-Wallis test. The findings revealed the relevant demographics in the target area and created a conceptual framework that the administrators can adopt. For the knowledge, attitude, and practice of the households, the income of the family showed significance. The other significant demographics were the household size for the attitude section; educational attainment for the knowledge section; and all the demographics for the practice section. Knowing this relevance, the community can create policies that are catered more to the effective group equating to greater chance of success in the implementation. The significance of the study is that the household wastes comprise of more than half of the waste generation of the Philippines hence, targeting this sector of the society will greatly impact the solid waste problem in the country.
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: 85127610513
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
Automatic feeders remain the greatest alternative for feeding fish to replace the human technique, and they are also the cheapest and most accurate method due to the low cost of microcontrollers. The study aims to design a project that would automatically dispense feed based on the user’s preferences through timer and message the owner thru GSM, if the feeding process was done. Prototypes are used to see if design perform as they are supposed to. According to development and testing the project was proven that the design was effective and efficient. Based on the result of the evaluation. The proponents found out that the majority of the respondents agreed that the proposed application has met. The proposed application will be a great help to the fishermen and aquarium owners because they will be relaxing and defendant to the application.