Journal of Physics: Conference Series

Time management is very important and it may actually affect individual's overall performance and achievements. Students nowadays always commented that they do not have enough time to complete all the tasks assigned to them. In addition, a university environment's flexibility and freedom can derail students who have not mastered time management skills. Therefore, the aim of this study is to determine the relationship between the time management and academic achievement of the students. The factor analysis result showed three main factors associated with time management which can be classified as time planning, time attitudes and time wasting. The result also indicated that gender and races of students show no significant differences in time management behaviours. While year of study and faculty of students reveal the significant differences in the time management behaviours. Meanwhile, all the time management behaviours are significantly positively related to academic achievement of students although the relationship is weak. Time planning is the most significant correlated predictor.

Overfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data on training data, as well as unseen data on testing set. Because of the presence of noise, the limited size of training set, and the complexity of classifiers, overfitting happens. This paper is going to talk about overfitting from the perspectives of causes and solutions. To reduce the effects of overfitting, various strategies are proposed to address to these causes: 1) "early-stopping" strategy is introduced to prevent overfitting by stopping training before the performance stops optimize; 2) "network-reduction" strategy is used to exclude the noises in training set; 3) "data-expansion" strategy is proposed for complicated models to fine-tune the hyper-parameters sets with a great amount of data; and 4) "regularization" strategy is proposed to guarantee models performance to a great extent while dealing with real world issues by feature-selection, and by distinguishing more useful and less useful features.

This collaborative qualitative study of the Filipino Department, West Visayas State University, Iloilo Philippines, aimed to collect and categorize local/indigenous literatures of Western Visayas (Region VI). This study was based on Oral Tradition and was made possible through interviews with the informants from different provinces in Western Visayas. The researchers utilized compiled Panayanon literatures from the colleges and universities of the region as well as those downloaded from the internet. Guide questions, cassette and mobile phone recorders, digital cameras and tablets were used as instrument. The result showed that Western Visayas has a very rich local/indigenous literature that reflect the culture and traditions of its people. Literatures collected were categorized according to genre as follows: bulong, hurubaton, huding, and other short verses; folk songs, daigon and dayaw; passion and praises; and, lowa, riddles and short stories. Themes derived from these literatures were: thanksgiving, courtship and marriage, occupation and way of life, social problems, calamities, heroism, environmental consciousness, praises to muses and to the Virgin Mary, passion of Christ, plants and animals, places, foods and many others. Furthermore, people from Western Visayas were very creative, imaginative and intelligent to write and compose these literatures.

Assessment of discriminant validity is a must in any research that involves latent variables for the prevention of multicollinearity issues. Fornell and Larcker criterion is the most widely used method for this purpose. However, a new method has emerged for establishing the discriminant validity assessment through heterotrait-monotrait (HTMT) ratio of correlations method. Therefore, this article presents the results of discriminant validity assessment using these methods. Data from previous study was used that involved 429 respondents for empirical validation of value-based excellence model in higher education institutions (HEI) in Malaysia. From the analysis, the convergent, divergent and discriminant validity were established and admissible using Fornell and Larcker criterion. However, the discriminant validity is an issue when employing the HTMT criterion. This shows that the latent variables under study faced the issue of multicollinearity and should be looked into for further details. This also implied that the HTMT criterion is a stringent measure that could detect the possible indiscriminant among the latent variables. In conclusion, the instrument which consisted of six latent variables was still lacking in terms of discriminant validity and should be explored further.

Without substantial automation, individuals cannot manage the complexity of operations and the scale of information to be utilized to secure cyberspace. Nonetheless, technology and software with traditional fixed implementations are difficult to build (hardwired decision-making logic) in order to successfully safeguard against security threats. This condition can be dealt with using machine simplicity and learning methods in AI. This paper provides a concise overview of AI implementations of various cybersecurity using artificial technologies and evaluates the prospects for expanding the cybersecurity capabilities by enhancing the defence mechanism. We may infer that valuable applications already exist after the review of current artificial intelligence software on cybersecurity. First of all, they are used to protect the periphery and many other cybersecurity areas with neural networks. On the other hand, it was clear that certain cybersecurity problems would only be overcome efficiently if artificial intelligence approaches are deployed. In strategic decision making, for example, comprehensive information is important, and logical decision assistance is one of the still unanswered cybersecurity issues.

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

The research aimed to produce natural wrapping paper from banana (Musa Paradisiaca Linn.) peel waste with additive essentials oils. The method used in this research was alkalization. The delignification process is done with the use of NaOH 4% at the temperature of 100°C for 1.5 hours. Additive materials in the form of essential oils are added as a preservative and aroma agent, namely cinnamon oil, lemon oil, clove oil and lime oil respectively 2% and 3%. Chemical and physical properties of the produced papers are tested included water content (dry-oven method SNI ISO 287:2010), pH (SNI ISO 6588-1.2010), grammage (SNI ISO 536:2010) and brightness (SNI ISO 2470:2010). Testing results of each paper were compared with commercial wrapping paper. The result shows that the natural paper from banana peel waste with additive essential oil meets the standard of ISO 6519:2016 about Basic Paper for Laminated Plastic Wrapping Paper within the parameter of pH and water content. The paper produced also meet the standard of ISO 8218:2015 about Food Paper and Cardboard within the grammage parameter (high-grade grammage), except the paper with 2% lemon oil. The paper which is closest to the characteristic of commercial wrapping paper is the paper with the additive of 2% cinnamon oil, with pH of 6.95, the water content of 7.14%, grammage of 347.6 gram/m² and the brightness level of 24.68%.

A low level of hemoglobin is one of the health and fitness issues often experienced by anyone including students. If a student experiences a disorder of Hemoglobin levels, his physical fitness will be affected. The study aims to examine the effect of jogging exercise to improve students' hemoglobin levels. A quasi-experiment method was employed in this study. The population of this study is a group of students of the Faculty of Sports Science, Universitas Negeri Padang. The samples of this study were 20 students obtanined by purposive sampling technique. The data of hemoglobin levels were measured by the cyanmethemoglobin method. Jogging exercises were carried out 18 times with a frequency of 3 times a week. The results of the study were analyzed statistically using a comparison test (t-test) at a significance level (α) of 5%. The results of this study indicated that the average of hemoglobin level of respondents before being treated was 14.18, while after being given treatment, it was 15.66. This means that there is a significant effect of jogging exercise on increasing students' haemoglobin level (Hb), with value of t_observed (3.80) > t_table (1.73).

The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications' describing it's what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.

In the Philippines, youth unemployment continues to hinder meaningful economic development due to job-skills mismatch, lack of knowledge and skills training, and work experiences. To address the problem, Department of Education's (DepEd) K to12 Program added two (2) years of Senior High School which is an advantage for students to develop relevant skills as early as high school. One of the goals of the K to 12 Basic Education Program is to develop the competencies, work ethic, and values relevant to pursuing further education and/or joining the world of work among learners. This study involved twenty-five (25) Grade 12 STEM strand students who were immersed in a science and technology-based industries. The work immersion lasted for eighty (80) hours where students performed different tasks assigned to them by the work immersion partner institution supervisors. The students' performance appraisal and evaluation were evaluated by their respective supervisors. Results showed that most of the students were evaluated outstanding and that their performance exceeds the required standard. The positive learning gains suggest that work immersion enables the students to acquire and develop the skills of teamwork, communication, attendance and punctuality, productivity and resilience, initiative and proactivity, judgment and decision making, dependability and reliability, attitude, and professionalism. Moreover, the students perceived their experiences as an avenue to test themselves and apply what they have learned in a non-school scenario where they were not only able to apply their previous training but are also able to experience the social interactions in a work environment. Their experiences in science-based work immersion partner institutions developed many skills and values that would help them as they move from high school to real life.

It is our great pleasure to present the proceedings of the 8th International Conference on Mechanical, Aeronautical, and Automotive Engineering (ICMAA 2024), held virtually from February 2-4, 2024. We are happy to report that the meeting went exceptionally smoothly, safety protocols were followed, and an enjoyable and stimulating meeting was held.

This year, ICMAA is sponsored by Singapore Institute of Electronics (SIE), with support from Sichuan Institute of Electronics, China, National Taiwan University of Science and Technology and Multimedia University, Malaysia, with an emphasis on theoretical and practical aspects, ICMAA 2024 provided a comprehensive platform for researchers and scholars to share their knowledge, insights, and experiences.

The Proceedings of the conference contain many excellent papers representing the participants' research and innovative thinking. All the papers have been checked through rigorous review and processes to meet the requirements of publication. These papers featured a wide range of topics, including but not limited to Applied Mechanics, Automation, Aerospace Propulsion, Computational Fluid Dynamics, Combustion and Emission Control, and Energy Management. We want to express our sincere gratitude to all the authors who contributed their papers to ICMAA 2024. We would also like to thank the members of the organizing committee, the technical program committee, and the reviewers for their hard work and dedication in ensuring the quality of the conference.

We hope that the papers included in these proceedings will serve as a valuable resource for researchers and practitioners in mechanical, aeronautical, and automotive engineering. We also hope that ICMAA 2024 has provided a platform for fruitful collaborations and new research initiatives.

We look forward to welcoming you to future editions of ICMAA and continuing our journey of exploration and discovery in mechanical, aeronautical, and automotive engineering.

Prof. Jia-Yush Yen

National Taiwan University of Science and Technology, Taiwan

Conference Chair of ICMAA2024

List of Organizing Committees and Peer Review Statement are available in this Pdf.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Double Anonymous

• Conference submission management system: Morressier

• Number of submissions received: 39

• Number of submissions sent for review: 29

• Number of submissions accepted: 17

• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 43.6

• Average number of reviews per paper: 2

• Total number of reviewers involved: 27

• Contact person for queries:

Name: Mei Lin

Email: neo_meilin@sie.sg

Affiliation: SIE, Sinagpore - Excutive Office

Additive manufacturing enables the production of complex shapes with a large degree of freedom compared to conventional manufacturing techniques such as injection molding, thermoforming or pressing. In particular, the creation of moving parts, complex structures and large-scale printing remains underexplored and research is constantly expanding. Due to design limitations related to the construction of currently available printers, 3D printing technology is increasingly being combined with robotics. Using a robot to 3D print products eliminates the need to design complex printer structures, which ultimately should simplify the process of manufacturing large-scale products and shorten the time required for preparation and production. The paper deals with the description of the designed 3D printing system and the procedure of the steps of creating a robotic simulation model with the generation of a control program for the FDM 3D printing process by an industrial robot.

This paper presents a cyber-physical production system that consists of a simulation, an industrial robot cell, and sensors. The industrial robot hardware, used for welding and additive manufacturing applications, is connected or "in-the-loop" with a real-time target machine on which simulations are running. These simulations are updated in real-time by the data provided by process sensors. Particular focus is given to wire-arc additive manufacturing (WAAM). Still, the cyber-physical system allows use in other robot-based material processes, such as sheet forming, (dis)assembly and material handling applications. It is also argued that the proposed cyber-physical system can be used so that it competes against the concept of using machine learning to optimize manufacturing processes. The proposed cyber-physical system enables the transition from traditional robot automation to autonomous robot systems.

In the realm of conventional affordance detection, the primary objective is to provide insights into the potential uses of objects. However, a significant limitation remains as these conventional methods merely treat affordance detection as a semantic segmentation task, disregarding the crucial aspect of interpreting affordances for actions that can be performed by manipulator. To address this critical gap, we present a novel pipeline incorporating the Intelligent Action Library (IAL) concept. This framework enables affordance interpretation for various manipulation tasks, allowing robots to be taught and guided on how to execute specific actions based on the detected affordances and human-robot interaction. Through real-world experiments, we have demonstrated the ingenuity and dependability of our pipeline, effectively bridging the gap between affordance detection and manipulation task planning and execution. The integration of IAL facilitates a seamless connection between understanding affordances and empowering robots to perform tasks with precision and efficiency. The demo link is available to the public: https://youtu.be/_oBAer2Vl8k