Abstract :

This classroom action research focuses on increasing student engagement in civic education through cognitive load theory and interactive multimedia. Strategies include structured group discussions, problem-based learning, and others. The results showed an increase in student involvement of up to 86.25%. Data analysis uses a mixture of qualitative and quantitative methods. This research is motivated by the low involvement of students in civic education. By applying the principles of cognitive load theory and interactive multimedia, hoped that it can create a more effective learning environment. Overall, this study shows the potential of this approach in improving learning effectiveness and helping students understand the concepts of citizenship, making a significant contribution to the development of more effective learning strategies.

Abstract :

The dissertation showcased the comprehensive exploration of a specific bamboo species, Bambusa blumeana, the mechanical properties specifically focusing on its tension parallel characteristics. The study employs a rigorous methodology, including one-way analysis of variance, t-test, and multiple linear regression as statistical treatment methods, to characterize tension parallel properties of Bambusa blumeana. By subjecting bamboo specimens, Bambusa blumeana, Bambusa vulgaris, and Dendrocalamus asper, to controlled tension forces, the research team meticulously analyzes a key mechanical parameter: tensile parallel strength to fiber. The findings enhanced understanding on its potential applications in various structural contexts. The results suggest that both Dendrocalamus asper and Bambusa vulgaris contain higher allowable tensile strength compared to Bambusa blumeana. This then indicates that Dendrocalamus asper and Bambusa vulgaris emerge as a material with their tensile parallel strength mechanical attributes. The study outcomes presented herein aim to inform future research endeavors and inspire innovative bamboo applications in structural engineering.

Index Terms: Bambusa blumeana Mechanical Properties, Structural Applications, Tension Parallel Properties

Abstract :

This capstone project, titled "Enhancing Leadership and Organizational Effectiveness: A Case Study of Civil Engineering Faculty", investigates leadership dynamics and organizational culture within the Civil Engineering Department. The study aims to assess the current leadership styles, evaluate organizational culture and climate, develop communication strategies, and propose effective decision-making models to enhance team performance and overall departmental effectiveness. Additionally, the research focuses on leading organizational change initiatives and promoting ethical, innovative leadership practices. The methodology employs both qualitative and quantitative approaches, including surveys and interviews, to gather data from faculty members on leadership effectiveness, communication practices, and organizational behavior. The findings highlight the significance of transformational leadership in motivating faculty and fostering a positive organizational climate, while also identifying areas for improvement in participative leadership and communication strategies. Barriers to innovation and challenges related to decision-making processes are also explored, leading to recommendations for fostering an inclusive, dynamic environment that supports academic excellence and faculty development. The results of this study contribute to the ongoing discourse on leadership in higher education, particularly in engineering faculties, offering insights for optimizing leadership practices and organizational performance. The proposed changes aim to enhance leadership capacity, foster collaboration, and create a supportive culture that drives innovation and academic success within the Civil Engineering Department.

Keywords: Leadership, Organizational Effectiveness, Civil Engineering, Academic Development, Decision-Making, Communication Strategies, Transformational Leadership

Abstract :

Concrete is a well-known composite material valued for its high compressive resistance. Its most significant disadvantage is having a deficient tensile strength that causes the development and propagation of cracks—these properties of concrete limit its application with tensile stresses. To improve concrete's tensile strength, durability, and mechanical behavior, uniformly distributing fibers throughout its volume is now widespread and referred to as fiber-reinforced concrete. The study examined how the addition of polypropylene fibers influences the pull-out strength of expansion anchor bolts in concrete. An investigation into the influence of fiber content (0%, 0.1%, 0.2%, and 0.3%) on the material's resistance to splitting, compression, and pull-out was conducted. 56 cylindrical samples were tested for split tensile and compression tests, while 24 rectangular samples were tested for the pullout test. The inclusion of polypropylene fiber reinforcement led to significant enhancements in the splitting strength, compressive strength, and pull-out strength of ordinary concrete.

Keywords: Polypropylene fiber, compressive strength, anchor bolt, pull-out strength

Abstract :

Application of ISO 14001-EMS standard in construction firms is used and being studied in different countries. In the Philippines, the province of Palawan, declared as the last frontier, considers environmental protection as its culture where constructions firms are being established through various and vast construction projects. This study aims to develop environmental management system assessment model instrument standard for construction firms in Palawan based on the ISO 14001:2015 – Environmental Management System. The survey questionnaire was constructed by the certified internal audit of ISO 14001:2015 EMS standard and distributed to the population of the construction firms in Palawan. The analysis of data includes descriptive statistical analysis such as mean and frequency. The results revealed that most of the construction firms in Palawan are private owned and did not apply ISO 14001:2015 in their construction firm. Most issues contraries and self-implication of assessment model are it requires more stable worker cost and most of the indicators in their firm has most criterion met but need more improvement. The assessment model instrument of ISO 14001:2015 EMS was further revised and analyzed using the principal component analysis and further its reliability using Cronbach alpha. The assessment model instrument was develop through data reduction using the Principal component analysis. It undergoes evaluation by as ISO certified individual.

Keywords: ISO 14001, Environmental Management System (EMS), Construction Firm, Palawan, Pincipal component analysis

Abstract :

This study investigates the machining behavior of Ti-6Al-4V alloy through finite element modeling (FEM) using ABAQUS software. Despite its widespread applications in aerospace, automotive, and biomedical industries due to its exceptional mechanical properties, Ti-6Al-4V presents significant machining challenges attributed to its low thermal conductivity, low modulus of elasticity, and high chemical reactivity. The research focuses on understanding the relationships between cutting parameters and machining outcomes, particularly examining the effects of friction coefficients and cutting speeds on chip formation, surface integrity, and subsurface deformation. FEM simulations revealed that increased friction at the tool-workpiece interface leads to serrated chip formation under unstable cutting conditions. Higher friction levels were also associated with increased surface roughness and deeper subsurface plastic deformation, potentially impacting component performance and fatigue life. The study demonstrates that optimized cutting parameters, including reduced cutting speeds and moderate feed rates, can maintain superior surface quality and minimize subsurface deformation. The research also examines the influence of plastic strain, stress, and cutting force on surface integrity, highlighting how excessive plastic deformation affects surface roughness and material hardness, while residual stress patterns impact fatigue performance. The simulation results showed good correlation with existing experimental data from literature, particularly in predicting the effects of varying cutting speeds and friction coefficients on surface integrity. Study limitations are addressed, and recommendations for future research, including cutting direction optimization and model improvements, are presented to enhance the understanding of Ti-6Al-4V alloy machining processes.

Abstract :

This study introduces an Enhanced Random Forest model for a course recommendation system aimed at supporting waitlisted applicants. The study integrates feature engineering, feature selection, and a hybrid hyperparameter tuning approach to improve the model’s classification accuracy, reliability, and interpretability. Feature engineering was used to capture interrelationship between program choices and associated college departments, allowing the model to recognize nuance relationships. Recursive Feature Elimination systematically eliminated the least significant features, ensuring that the model focuses on features that have high predictive attributes. To mitigate the limitations of traditional hyperparameter tuning methods, a hybrid approach of RandomizedSearchCV and GridSearchCV was utilized to effectively find optimal parameters while minimizing computation costs. A dataset of 1,505 applicants who underwent the Pamantasan ng Lungsod ng Maynila Admission Test for school year 2024 was utilized to train models. The Enhanced Random Forest was compared against Traditional Random Forest, AdaBoost, Gradient Boosting, and Extra Trees Classifier using an 8-fold cross-validation with different scoring metrics such as accuracy, F1-Score, and ROC-AUC. Results show a significant improvement, where the enhanced model achieved an accuracy of 75.10% with an F1-Score of 74.23% and an ROC-AUC score of 96.57%, outperforming other models across all metrics. The Enhanced Random Forest also achieved a lower standard deviation across all metrics resulting in a stable model compared to the other models. A web application using the enhanced model was developed to support the course recommendation process. The findings demonstrate the effectiveness of the proposed enhancements in addressing challenges in an admission-based recommendation system by offering a robust framework for academic decision-making.

Keywords: Course Recommendation, Feature Engineering, Feature Selection, GridSearchCV, Hyperparameters, Random Forest, RandomizedSearchCV.

Abstract :

This study investigates the influence of the sustainable entrepreneurship ecosystem on social networks and their subsequent role in institutional emergence. Leveraging technological advancements and social networks, the research also explores the mechanisms through which crowdfunding fosters institutional diversity. A quantitative approach was employed, analyzing data from 256 participants, including angel investors, venture capitalists, regulators, and educationists involved in entrepreneurial promotion. Using the PLS-SEM method and convenience sampling, the findings reveal that the sustainable entrepreneurship ecosystem significantly enhances institutional emergence, particularly institutions funded through crowdfunding. Moreover, technological advancements and robust social networks positively mediate this relationship. The results emphasize the need for organizations to integrate social media analytics and technological tools to deepen their understanding of the demand for new institutions. Entrepreneurs and innovators must examine how technological advancements impact markets, regulatory frameworks, and environmental dynamics. Policymakers and community leaders are urged to foster social networking spaces as strategic components to support entrepreneurial ecosystems. The dynamic interplay between technological progress and social networks drives the creation of new entities with specialized objectives, reinforcing the ecosystem's capacity for growth. This study contributes to the literature by unveiling the nuanced role of social networks and technological innovation in institutional formation. The findings provide actionable insights for stakeholders aiming to optimize entrepreneurial ecosystems and promote institutional diversity, emphasizing the critical role of supportive networks and technological tools in adapting to evolving environments.

Abstract :

This paper presents the development of two offline augmented reality (AR) systems—ID-QUBE and ID-MAP—to enhance rural tourism in areas with limited internet connectivity. ID-QUBE, a solar-powered portable AR server, and ID-MAP, an interactive digital poster, are designed to deliver cultural and tourism-related content to users offline. These systems provide scalable and sustainable solutions for immersive AR experiences, fostering cultural preservation, community empowerment, and economic development. The paper discusses system architecture, offline marker-based applications, and scalability in underserved areas, concluding with recommendations for further commercialization and innovation.

Index Terms: Augmented Reality (AR), Offline Systems, Rural Tourism Development, Cultural Heritage Preservation

Abstract :

The Discrete Wavelet Transform (DWT) is widely used in medical image com-pression for its ability to capture spatial and frequency characteristics. However, DWT's inability to retain phase information—critical for maintaining the alignment of edges and textures in images—can result in distortions and loss of essential details, potentially affecting clinical diagnosis. This paper presents an enhanced DWT algorithm designed to address this limitation by incorporating a trained Autoencoder to learn and preserve essential image features for improved reconstruction. The Autoencoder comprises an encoder with convolutional layers using non-separable filters to enforce orthogonality, and a decoder with trans-posed convolutions for image reconstruction. JPEG2000 was employed as the compression technique, with the proposed method achieving a similar compression ratio to traditional DWT, indicating no compromise in efficiency. Experimental results show that the enhanced DWT with autoencoder significantly out-performs the traditional DWT method, achieving up to 61.90% improvement in Peak Signal-to-Noise Ratio (PSNR), thereby reducing distortions and preserving critical image details more effectively. This improvement is crucial for maintaining the integrity and diagnostic quality of medical images, ensuring that essential features are accurately represented.

Abstract :

Support Vector Machines (SVM) have proven to be effective in many classification tasks. However, SVM& 39s performance deteriorates when faced with high-dimensional data due to the curse of dimensionality, where the increasing number of features reduces the model’s ability to generalize and increase computational complexity. This study addressed this challenge by using an enhanced SVM model that incorporates a Term Frequency-Inverse Document Frequency - Class Variance (TF-IDF-CV) feature extraction method applied in spam email classification. Unlike traditional methods, TF- IDF-CV considers class variance during feature extraction, which helps mitigate the negative effects of high-dimensional data. Experimental results demonstrate that the enhanced SVM outperforms traditional feature extraction techniques, including TF-IDF, Bag of Words, and Word2Vec, achieving an accuracy of 99.42%, precision of 99.43%, recall of 99.42%, and an F1-score of 99.42%. These findings underscore the enhanced robustness and reliability of the SVM model, positioning it as a promising solution for efficient and accurate spam detection in high-dimensional datasets.

Abstract :

Aluminum alloys are the most usable material in industrial markets such as aerospace, marine, and automotive due to their excellent performance in resisting fatigue and corrosion. As the demand for aluminum alloys increases, these materials are growing in the global market due to their low cost, machinability, and mechanical properties. However, once it comes to the machining and particularly the drilling process, the quality of the drilled hole should be considerable to investigate the effect of cutting parameters, namely spindle speed and feed rate, on the inner surface of these holes, where they play a crucial role in many industrial areas. For instance, an aircraft’s wing requires namouras holes to be attached to the main structure by using rivets and bolts. This investigation might be beneficial for the manufacturers to save time and money with optimal hole quality. The current research study examines the effect of cutting parameters (feed rates and spindle speed) on hole quality in aluminum alloy Al5083 by using HSS drill bits. A CNC machine was utilized for the drilling process, where 48 holes were drilled without using any coolant and 48 holes under flooded cutting fluid. The experimental results revealed that both R a and R z increased by increasing the spindle speed and feed rate. However, the drilled holes with coolant have minimum R a and R z . In general, the holes were oversized at the entry and reduced at the exit, and by increasing the feed rate, the hole size declined. Moreover, an acrylic backup support is used to reduce the burr formation at the hole’s exit. The results were supported by using the full factorial method and ANOVA (analysis of variance) to evaluate each input parameter’s contribution to the hole’s quality.

Abstract :

The influx of job seekers who have applied for work-from-home (WFH) jobs after the pandemic has shifted the expectations and needs of employees involved with online and freelance work. To better understand the shift within the industry, this study aimed to determine the current sentiments and issues being encountered by people involved in the post-pandemic WFH market with the use of Natural Language Processing (NLP) tools. A total of 11,868 posts and comments were collected from the social media platform Reddit for analysis. Sentiment analysis was first conducted using the NLTK VADER model. It was found that the overall sentiment of users towards WFH jobs was slightly positive, with a compounded score of 0.1905, showing that many employees still feel that the benefits of WFH jobs still outweigh the issues that they have been encountering in recent years. Topic modeling was then conducted using a Latent Dirichlet Allocation (LDA) model and it was found that the biggest concerns users had towards WFH jobs were “salary and compensation”, “time management”, “company policies and culture”, “job stability”, and “skills management”. These issues highlight the need for better policies and government regulations towards WFH jobs, to ensure employees who do remote jobs will be protected by the same laws and regulations as traditional employees. The findings also highlight the need for better platforms for WFH employees to engage in personal and professional development, so that they can keep up with the ever-growing needs and requirements of remote jobs.

Abstract :

The integration of metallic elements into diamond-like carbon (DLC) coatings, particularly cobalt (Co-DLC), has attracted significant attention for enhancing functionalities in various applications. This study explores the interaction between functionalized polymers and Co- DLC coatings to elucidate their tribological properties and wear resistance. Co-DLC coatings were deposited on steel substrates using deep oscillation magnetron sputtering, and different Co concentrations were achieved by varying cobalt pallets. Tribological tests were conducted using ball-on-disk tribometry, revealing reduced friction and improved wear resistance of Co- DLC coatings when paired with PLMA-b-PDMAEMA polymer compared to PLMA. Surface characterization through SEM-EDS analysis unveiled the formation of transfer films derived from carbon-rich polymers, contributing to the observed reduction in wear rates. Overall, Co- doped DLC coatings exhibited promising potential in mitigating friction and enhancing wear resistance when combined with specific functionalized polymers, indicating avenues for diverse industrial applications. This comprehensive investigation not only advances the understanding of tribological behavior but also facilitates the development of tailored materials with superior performance in real-world applications.

Abstract :

Entrepreneurship education plays a crucial role in equipping students with the skills and confidence to pursue entrepreneurial opportunities, fostering their intentions to engage in entrepreneurial activities. This study explores the influence of entrepreneurship education on the entrepreneurial intentions of business students in Cebu City, Philippines, focusing on perceived desirability, perceived feasibility, and propensity to act. It highlights how education shapes students’ entrepreneurial aspirations while addressing the barriers they face. A quantitative research design was employed, using Structural Equation Modeling (SEM) to analyze data from 300 business students across three universities: the University of San Carlos, the University of San Jose-Recoletos, and Cebu Technological University. Data were gathered through a structured questionnaire covering demographics, key constructs, and perceived obstacles. The analysis provided insights into the direct and indirect effects of entrepreneurship education on entrepreneurial intentions. The findings indicate that entrepreneurship education significantly enhances students’ perceptions of entrepreneurship as desirable and strengthens their willingness to take entrepreneurial action. These factors, in turn, positively influence entrepreneurial intentions. While perceived feasibility is moderately influenced by education, it does not directly contribute to entrepreneurial intentions in this context. Major barriers identified include lack of capital, fear of failure, and market competition. This study emphasizes the importance of experiential learning approaches, such as mentorship programs and business simulations, in making entrepreneurship education more effective. By addressing perceived challenges and fostering proactive attitudes, educational institutions can better prepare students for entrepreneurial success. The findings provide actionable insights for designing educational programs that inspire and support aspiring entrepreneurs.

Keywords: Entrepreneurship Education, Entrepreneurial Intentions, Perceived Desirability, Perceived Feasibility, Propensity to Act, Business Students, Structural Equation Modeling (SEM).

Abstract :

Gamification has gained significant popularity in education due to its interactive and engaging nature, making it particularly effective for teaching abstract concepts like programming. Studies highlight the advantages of Gamification and Game-Based Learning Environments (GBLE) in programming education, emphasizing interactivity as a key motivator. This study investigates the impact of integrating personalized learning experiences into a GBLE on teaching programming fundamentals. Using Roblox Studio, a customized GBLE was developed to teach basic programming concepts, allowing respondents to explore the environment freely while data collected during their interactions informed personalized adaptations. Results indicate that GBLEs are especially beneficial for learners with little or no prior programming knowledge, enhancing their understanding and engagement. The findings suggest that gamification, game-based learning, and similar approaches should be explored for teaching abstract, interactive, and visualization-heavy subjects. Moreover, integrating personalization within GBLEs significantly enhances their effectiveness in catering to diverse learning styles and experiences.

Keywords: Gamification, Game-based Learning, Programming Education, Educational Technology

Abstract :

In today's interconnected world, virtual interviews have become increasingly popular for job interviews and other professional interactions remotely. With advancements in technology and the widespread availability of video conferencing tools, virtual interviews offer convenience, cost- effectiveness, and accessibility to employers and candidates. This empirical paper aims to explore the concept of virtual interviews, their uses, and the challenges of demographic perspectives.

Keywords: Virtual Interviews, Covid-19, Remote Hiring JEL Classification: O15.

Abstract :

Due to industrialization, deforestation and many other anthropogenic activities, carbon emission is increasing at a rate of approximately at a rate of 1% in past few years. Now, reduction of atmospheric carbon dioxide (CO 2 ) has become a significant concern and challenge for every country across the globe. This paper is a sincere effort to study, analyse and further optimize, amine based post-combustion carbon (PCC) capture. Monoethanolamine (MEA) in rotating packed beds (RPB) has been extensively studied for CO 2 chemical absorption. Enhancing CO 2 capturer efficiency necessitates a thorough comprehension of the complex interrelationships within the key parameters. This study focuses on modelling and optimisation of CO 2 absorption efficiency in MEA by artificial intelligence and genetic algorithms (GA). Machine learning (ML) and Artificial Neural Networks (ANN) are versatile instruments employed to model and forecast diverse complex and highly non-linear phenomena. The established process models have been established by published steady-state experimental data. Subsequently, SHAP analysis has been applied that reveals the input factors such as solvent concentration, flow rate, and rotational speed are the primary determinants of CO 2 absorption in RPB. To assess the model's performance, the acquired results have been examined using statistical measures, including MSE, RMSE, and R2 value. The modelling results have been utilised to optimise CO 2 absorption, employing GA under various operating conditions to ascertain the optimal values for the input variables that correlate to maximized CO 2 capture.

Index Terms: CO 2 absorption, machine learning, modeling, optimization.

Abstract :

The Indian Ocean Tripole (IOT) mode, associated with the third mode of sea surface temperature anomaly (SSTA) variability, exhibits a unique pattern characterized by positive SSTA dominating the central Tropical Indian Ocean (TIO), while negative SSTA prevail in the western and eastern regions. This distinct mode of variability significantly influences the surrounding climate. In this study, the underlying causes of SSTA variability in the central TIO during tripole events are investigated through an SST heat budget analysis. Specifically, the anomalous warming in the central TIO is examined. A multiple linear regression analysis is performed using climate indices linked to most dominant SSTA-based climate modes, El Nino Southern Oscillations (ENSO), Indian Ocean Dipole (IOD), and IOT on SST budget terms to determine key drivers. The results reveal that net heat flux is the primary contributor to the positive SSTA in the central TIO. To further disentangle this influence, the individual contributions of radiative and turbulent heat flux components are analysed. This study enhances our understanding of TIO dynamics during IOT events and their broader implications for regional and global climate systems.

Keywords:Tropical Indian Ocean, Indian Ocean Tripole, Sea Surface Temperature, Heat budget analysis, Multiple Linear Regression.

Abstract :

Speaking anxiety is a persistent problem among English as a Second Language (ESL) learners, often impairing effective communication during oral presentations. While extensive research has examined language anxiety, there remains a critical gap in understanding how anxiety manifests itself in both verbal and non-verbal communication, particularly in the context of online presentations. This gap is further compounded by the limited understanding of the underlying strategies employed by ESL learners to mitigate anxiety during online presentations. This study employs a qualitative methodology that includes in-depth interviews with ten ESL learners and three expert educators. Thematic coding of the interview data was conducted using Atlas Ti 22 to capture perspectives on the coping mechanisms. Findings of the interviews highlighted that ESL learners employed seven strategies to cope with anxiety, which were categorised into one internal and six external approaches, indicating a preference for externally oriented coping mechanisms. This study provides new theoretical and practical insights into the complex dynamics of speaking anxiety in online presentations and offers valuable guidance to educators and policymakers in developing interventions tailored to the specific needs of ESL learners in Malaysia. By enhancing our understanding of anxiety triggers and effective strategies, this study aims to support the development of targeted pedagogical practices that promote greater confidence and communication efficacy among ESL learners.

Abstract :

This study explores the effectiveness of two instructional materials—Storyline Online storytelling videos and picture books—in enhancing the reading comprehension of second-year Bachelor of Secondary Education students majoring in English at the Polytechnic University of the Philippines, Santa Maria Bulacan Campus. Using a quantitative research design, pre-tests and post-tests were administered to assess changes in students' comprehension skills. The study involved 80 participants divided into two groups. Pre-test results showed both groups had low baseline reading comprehension levels. Post-intervention analysis revealed that storytelling videos produced a higher mean improvement (0.73 points, Cohen's d = 0.199) compared to picture books (0.25 points, Cohen's d = 0.062). Storytelling videos demonstrated greater effectiveness, attributed to their multisensory engagement and audiovisual features, which aligned with multimedia learning theories. While picture books showed limited improvement, they remain valuable for fostering critical thinking and imagination, making them a complementary tool for long-term interventions. The findings suggest that storytelling videos are more effective for immediate comprehension gains, while picture books can support deeper cognitive engagement. This study highlights the potential of interactive multimedia tools in addressing diverse learning needs and provides insights for educators seeking to enhance literacy instruction. The results advocate for integrating these materials into teaching strategies to optimize students’ reading comprehension outcomes.

Abstract :

Today, Campus networks face unprecedented challenges in terms of scalability, security and performance wherein traditional network architecture is striving hard to achieve this goal. This systematic review evaluates Software-Defined Networking (SDN) as transformative solution to centralized yet dynamic network control and management and increased operational efficiency for an academic institution. Software-Defined Networking (SDN) decouples the control and data plane, it is possible to make real-time changes and quick reconfigurations to optimize the flow of traffic and minimize problems such as latency and packet loss. This flexibility comes along with vulnerabilities notably in central control points who is susceptible to Distributed Denial of Service Attacks (DDoS) and spreading of malware which requires robust security measures. While Integration of artificial intelligence (AI) into SDN, SDN can strengthens intrusion detection it also opens the floodgates for vulnerabilities and heightens the risk of cyberattacks. Strategies to mitigate these problems include the use of multiple controller clusters, load-balancing architecture, and federated learning for privacy preserving intrusion detection. This paper shows that the academic institution should adopts strict and proactive security measures and monitoring to protect against cyber threats, through SDN since it emphasizes scalability and resilience. SDN can also transform the network administration efficiently.

Keywords: SDN Challenges in Campus Network, SDN Challenges, SDN Vulnerabilities in Campus Network, Software-Define Networking Vulnerabilities, Challenges in Software-Define Networking