Scopus ID: 85114852372
2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), (2021), pp. 8-13
Shadi M S Hilles, Abdilahi Liban, ... Jennifer Contreras
Conference Paper | Published: June 15, 2021
Abstract
Image enhancement and segmentation is widely used for fingerprint identification and authorization in biometrics devices, criminal scene is most challenges due to low quality of fingerprint, the most significant efforts is to develop algorithm for latent fingerprint enhancement which become challenging problem due to the complex and existing problem for instance, developing algorithms of latent fingerprint is able to extract features of image blocks and removing overlapping and isolate the poor and noisy background. however, it’s still challenging and interested problem specifically latent fingerprint enhancement and segmentation. The aim study of this paper is to propose latent fingerprint enhancement and segmentation based on hybrid model and Chan-Vese method for segmentation, in order to reduce low image quality and increase the accuracy of fingerprint. The desired characteristics of intended technique are adaptive, effective and accurate, hybrid model of edge adaptive direction achieves accurate latent fingerprint enhancement and segmentation, the target needs to improve feature detection and performance, this research has proposed system architecture of research method in fingerprint enhancement and segmentation where is the method content two stages, the first is normalization and second is reconstruction, using EDTV model is required for adaptive noise, in addition Chan-vase technique contributed for identification of fingerprint image features, the result and testing using RMSE with three categories of fingerprint images good, bad and ugly show better performance for all three categories, as well RMSE shows the average of good latent fingerprint before and after enhancement. Latent Fingerprint Enhancement and Segmentation Technique Based on Hybrid Model Edge Adaptive Directional Total Variation.
Scopus ID: 85103163120
Education and Information Technologies, (2021), Vol. 26, No. 4, pp. 4839-4856
Journal Article | Published: March 24, 2021
Abstract
Computer programming education is often delivered using individual learning strategies leaving group learning techniques as an under-researched pedagogy. This pose a research gap since novice programmers tend to form their own group discussions after lecture meetings and laboratory activities, and often rely on peers when a topic or activity is difficult. Thus, this study intends to evaluate the impact of cooperative learning using jigsaw technique when teaching computer programming to novice programmers. A quasi-experimental research using a nonequivalent control group pretest-posttest design was adopted to examine the impact of jigsaw teaching strategy. After a 14-week programming course, pre- and post-test results revealed a significant increase in terms of attitude and self-efficacy, and the experimental group demonstrated significantly higher scores than in the control group. Therefore, it was concluded that cooperative learning using Jigsaw technique is a valid and effective teaching strategy when handling novice programmers in an introductory programming course.
Scopus ID: 85105390853
2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), (2021), pp. 384-388
Conference Paper | Published: March 17, 2021
Abstract
People are anxious about the potential dangers of scuba diving and like in all sports, there are dangers involved in it. Typically, people think sharks and shark attacks are the dangers of scuba diving, as sharks are one of the ocean's biggest predators, and the great white shark, in particular, is one of the primary threats to divers. The study proposes a deep learning approach to shark detection for underwater diving surveillance. A large collection of great white sharks' datasets underwater is used by the system for training as sharks are hard to differentiate from other sharks like animals in an underwater environment. A YOLOv3 algorithm that uses convolutional neural networks for object detection, multiscale prediction, and bounding box prediction through the use of logistic regression is used in the study. And with this approach, the testing of the shark detection system generates a good result.
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: 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: 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.
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: 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: 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: 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.