Scopus ID: 85141980537
DOI: 10.1063/5.0072449
AIP Conference Proceedings, (2022), Vol. 2433, pp. 030016
Diana Rose T. Rivera, Ivan Henderson V. Gue, ... Leif Oliver B. Coronado
Conference Paper | Published: October 26, 2022
Abstract
Decision-making in choosing a degree in engineering, especially for women, involves trade-offs between numerous conflicting objectives. To increase the number of female students enrolling in the Mechanical Engineering Department of Far Eastern University, a survey was conducted among the 30 female engineering students of the Mechanical Engineering Department of Far Eastern University, Institute of Technology. In this study, the objective is to determine the factor that affects female students in choosing engineering field. A multi-criteria decision analytical process was done using a pairwise comparison matrix wherein the goal is to rank the n alternatives. The results of the study revealed that 39.48% of their decision is based on their own choice. It is followed by the influence of the economy with 19%, while the influence of family, available opportunity and the impact of the latest trend have close relative weights, with value within 10% to 12%. Lastly, peer pressure had the least influence with relative weights of 7%. Since personal choice is based on individual's skills, it is recommended that universities should invest in various activities and workshops during their promotional campaign. This will help incoming college students to familiarized and be confident to include engineering in their degree of choice.
Scopus ID: 85141991563
DOI: 10.1063/5.0108615
AIP Conference Proceedings, (2022), Vol. 2502, pp. 020001
Conference Paper | Published: October 26, 2022
Abstract
Hearing is one of the most basic human senses. Research shows that 97 percent of the total population of elderly people suffer from hearing loss. This project is designed to address problems that the existing hearing aid users face throughout their use of the product which includes prices, high maintenance, sensitivity to noise, limited functional range and low-quality sound produced. This project aims to provide a hearing aid with noise filtration using Noise Reduction (NR) algorithm. NR algorithm which uses Multi-channel Wiener Filter is implemented to reduce noise and improve speech intelligibility. The proponents create a program for the Intel compute stick using NR algorithm to function as the filter and for the Raspberry Pi as the user interface of the device. The signal gathered by the microphone was processed by the Intel compute stick then outputted through the earphone audio output. The system is tested through simulation in terms of filtering the noise.
Scopus ID: 85141988568
DOI: 10.1063/5.0108977
AIP Conference Proceedings, (2022), Vol. 2502, pp. 030002
Leif Oliver B. Coronado & Diana Rose T. Rivera
Conference Paper | Published: October 26, 2022
Abstract
The firearms manufacturing industry has investigated replacing firearms frames with lightweight materials, such as polymer, in recent years. This kind of innovation in the manufacturing industry can help the users be more comfortable and reduce possible injuries. Using additive manufacturing or 3D printing, prototyping the firearms' frame made of polymer is possible. Additive manufacturing uses a 2-dimensional layer fabrication approach to form almost any 3-dimensional object. However, there are no studies published yet regarding the performance of the firearms frames made of polymer. In addition, supporting studies regarding the capability to withstand the pressure and stress from the blowback and recoil process should also be done. To solve the gap, this study investigates the stress and deformation of a 3D-printed pistol frame made of polymer using Finite Element Analysis (FEA). A comparison between steel and polymer frame materials is also analyzed to show its performance. The analysis results revealed that changing the frame's material to polymer will decrease the weight by 51.73%. The resulting stress is slightly comparable for both materials but with an increase in the displacement due to recoil. The study is expected to provide valuable theoretical references for the design. Employing better structure, other curves, and increasing the thickness are recommended to remove the high concentration of stress on some model areas.
Scopus ID: 85126615287
2022 4th Asia Pacific Information Technology Conference, (2022), pp. 138-143
Conference Paper | Published: January 14, 2022
Abstract
The Learning Management System is an innovative tool to facilitate online learning using technology. It monitors students’ learning progress and actions. As most academic institutions are already shifted from the traditional learning to online and blended learning approaches, analysis of students’ learning behaviors is empirical to design necessary and suited academic intervention programs. With this, the researchers aimed to identify significant attributes affecting student academic performance in an online education environment. The knowledge discovery in databases (KDD) was used to provide step by step process in extracting and evaluating the predictive and cluster models which aim to classify students who will have academic learning difficulty based on sets of parameters and constraints. The study reveals that students with low engagement in online learning are those with problems in terms of their academic performance. Therefore, the study reaffirmed that there is a strong relationship between student behaviors in LMS and academic achievement.
Scopus ID: 85126595729
2022 4th Asia Pacific Information Technology Conference, (2022), pp. 111-115
Conference Paper | Published: January 14, 2022
Abstract
The sudden transition to emergency remote education (ERE) caused by the pandemic has been a highly complex undertaking for teachers and students alike. For developing countries, such a disruption only aggravates the pre-existing global education crisis and influences the sector in unprecedented ways. Thus, we explored how teachers and students from higher education in a developing country adapt to ERE during the pandemic. Specifically, we attempted to identify the common challenges faced by teachers and students and their coping strategies to handle pandemic-induced stress. To this end, we conducted a comparative cross-sectional study from October to November 2021 with 78 teachers and 94 students from a higher education institution in Manila, Philippines. Our results show that while self-regulation is the greatest challenge among students, it is the conduciveness of the home environment for teachers. Interestingly, although teachers and students have varying concerns, both groups rely on acceptance, humor, and positive reframing as their coping strategies. By painting a holistic picture of the challenges and coping strategies of both teachers and students, education policymakers and administrators can make an informed decision on how to best continue ERE and prepare in advance for the resumption of school in the new normal.
Scopus ID: 85132195726
2022 10th International Conference on Information and Education Technology (ICIET), (2022)
Conference Paper | Published: January 1, 2022
Abstract
Recent studies have acknowledged social media as a valuable pedagogical tool for connecting the formal and informal learning gap. However, as a new platform, the literature is sparse on the potential of TikTok as a knowledge source. In this study, we explored programming TikTok videos in the #LearnProgramming webpage in terms of content (programming languages and topics) and characteristics (video styles and types). Although TikTok is principally an entertainment destination, our results show that the platform likewise has informative videos. The 349 videos that we examined received a total of 10,046,000 views, 10,523 comments, 932,871 likes, and 35,095 shares, implying extremely high levels of user engagement. Tiktokers showing tips and tricks are the most recurring content type. From a macro perspective, we noticed that TikTokers do not follow the ethos of the platform (e.g., dancing) when producing educational content. This deviation demonstrates the intent of TikTokers to educate than to entertain. Although it is too early to conclude that TikTok can operate as a nanolearning platform, we discovered a substantial amount of content for and engagement from programming learners. Our results lay a potent foundation for devising actionable scholastic implications, policies, and recommendations concerning TikTok consumption. Future works and research prospects were also discussed to propel the social media and nanolearning literature forward.
Scopus ID: 85141846470
2022 9th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), (2022)
Conference Paper | Published: January 1, 2022
Abstract
With the aggravation of the Russia-Ukraine conflict and the rising involvement of foreign powers, it has become more substantial to identify whether an endorsement or condemnation of war efforts is the universal message. This goal is empowered by the clear literature on the vital linkage between public opinion and international relations. Thus, we investigated the sentiments and emotions of the international community on the Russian invasion of Ukraine. A total of 27,894 tweets posted within the first day in the #UkraineRussia hashtag were analyzed. Results show that "war", "people", "world", "putin", and "peace" were some of the most frequently occurring words in the tweets. There were more negative sentiments than positive sentiments, and sadness was the most salient emotion. To date, this study is the first to examine the Russo-Ukrainian War and one of the few sentiment and emotion analyses for exploring Twitter data in the context of modern war.
Scopus ID: 85144027068
2022 IEEE 13th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), (2022)
Renato R. Maaliw, Alvin S. Alon, ... Alexander A. Hernandez
Conference Paper | Published: January 1, 2022
Abstract
Automated medical image analysis driven by artificial intelligence can revolutionize modern healthcare in producing swift and precise diagnostics. Due to doctors’ varying breadths of training and expertise, traditional leukemia screening methods frequently involve considerable subjectivity. Using a 3-stage transfer learning approach and stacks of convolutional neural networks, we constructed an efficient pathway for automatic leukemia identification and classification through various phases. Experimental findings disclosed that our pipeline powered by InceptionResNetV2 architecture decisively affects the accuracy with 99.60% (normal vs. leukemia) and 94.67% (normal to L3). Moreover, it reduces error rates by 1.65% and 6.05%, respectively. A consistent result via the T-test confirms our proposed framework robustness with a significant positive difference of 4.71% over the standard transfer learning mechanism (p-value = 0.0001 & t = 0.85310). This research could aid and support oncologists in early yet reliable prognoses of acute lymphoblastic leukemia types.
Scopus ID: 85159403155
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-5
Conference Paper | Published: January 1, 2022
Abstract
Computer programming is now one of the most critical competencies taught in computer courses. [1]. Students require any assistance they can get when learning programming in order to acquire the necessary abilities to excel in the field of computing [2]. This paper aims to investigate the C compiler error logs of Computer Science freshmen students. A prototype was developed and pilot-tested to obtain C source code snippets focusing on assignment statements. The dataset consisting of 1013 logs were extracted from the initial prototype then followed the data science approach of [3] for pre-processing. A Person correlational analysis was conducted on eight features to investigate the relationship between all variables in the dataset. Results of the study show that there is a strong relationship between wrong expression and operator (0.806), wrong expression and numeric value (0.794), operator and numeric value (0.663). Implications of this study is also helpful to computing instructors to improvise the delivery of their teaching pedagogy.
Scopus ID: 85159233468
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2022), pp. 1-6
Conference Paper | Published: January 1, 2022
Abstract
In this study, we developed a PC-based video game that aims to promote awareness of Persistent Depressive Disorder (PDD), also known as dysthymia. Anchored to the survival horror subgenre and a hack and slash gameplay, we constructed "Escape from Oblivion" as a single-player platformer game that highlights eerie game world environments and scenarios indicative of mental health conditions. It exhibits different mental states under terrible circumstances, forcing players to see and feel what it is almost like when suffering from a mental health condition like PDD. With the necessary expertise on PDD and mental health, we consulted with an expert to co-design the video game. We also evaluated the game prototype with players in terms of game characteristics. The initial version of our game received acceptable scores during the virtual open house event. Although there are several enhancements to be incorporated, our video game Escape from Oblivion demonstrates potential in being a promotional tool for mental health awareness.