IOP Conference Series: Materials Science and Engineering

As per ISO and ASTM standards, nanoparticles are particles of sizes ranging from 1 to 100nm with one or more dimensions. The nanoparticles are generally classified into the organic, inorganic and carbon based particles in nanometric scale that has improved properties compared to larger sizes of respective materials. The nanoparticles show enhanced properties such as high reactivity, strength, surface area, sensitivity, stability, etc. because of their small size. The nanoparticles are synthesised by various methods for research and commercial uses that are classified into three main types namely physical, chemical and mechanical processes that has seen a vast improvement over time. This paper presents a review on nanoparticles, their types, properties, synthesis methods and its applications in the field of environment.

Digital marketing is an integral part of the process of digital business transformation. It incorporates new marketing techniques that are based on information and communication technologies. For this reason, its application in practice is a prerequisite for the successful development of the business in the contemporary market conditions. The object of this paper is the digital marketing and the subject is the digital marketing advantages and disadvantages. The first purpose of this paper is to systemize the various terms for digital marketing used in the specialized literature and the Internet and to show the differences between them. The second is to present the characteristics of the main advantages and disadvantages of digital marketing. Knowing them in depth, companies will be able to develop effective digital marketing strategies that have high potential to achieve company goals and at the same time are suitable to their profile. Thereby, they will be able to determine to what extent and which tools of the whole digital marketing palette are best suited to their marketing activities.

Day by day the cases of heart diseases are increasing at a rapid rate and it's very Important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently. The research paper mainly focuses on which patient is more likely to have a heart disease based on various medical attributes. We prepared a heart disease prediction system to predict whether the patient is likely to be diagnosed with a heart disease or not using the medical history of the patient. We used different algorithms of machine learning such as logistic regression and KNN to predict and classify the patient with heart disease. A quite Helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of Heart Attack in any individual. The strength of the proposed model was quiet satisfying and was able to predict evidence of having a heart disease in a particular individual by using KNN and Logistic Regression which showed a good accuracy in comparison to the previously used classifier such as naive bayes etc. So a quiet significant amount of pressure has been lift off by using the given model in finding the probability of the classifier to correctly and accurately identify the heart disease. The Given heart disease prediction system enhances medical care and reduces the cost. This project gives us significant knowledge that can help us predict the patients with heart disease It is implemented on the.pynb format.

The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. A lot of research is already focused on detecting it. This paper makes an analysis of the research related to fake news detection and explores the traditional machine learning models to choose the best, in order to create a model of a product with supervised machine learning algorithm, that can classify fake news as true or false, by using tools like python scikit-learn, NLP for textual analysis. This process will result in feature extraction and vectorization; we propose using Python scikit-learn library to perform tokenization and feature extraction of text data, because this library contains useful tools like Count Vectorizer and Tiff Vectorizer. Then, we will perform feature selection methods, to experiment and choose the best fit features to obtain the highest precision, according to confusion matrix results.

Groundbreaking advancements have driven significant industries to adopt and take advantage of the key technologies in order to thrive in these adjustments coming from the Fourth Industrial Revolution (FIRe). However, with the threat of the Coronavirus disease 2019 (COVID-19) causing catastrophic setback to the society and economy, scientific endeavors have shifted towards finding a solution to this pandemic. It is high time to evaluate how the current technology from the FIRe can help a country, such as the Philippines, survive such outbreaks and unforeseen circumstances. Advancements in the field of nanotechnology aim to develop smaller and inexpensive testers, and overall newer and more effective medical solutions. However, the extent on how these technologies can be realized depends on the interplay between the country's policies, and the strong link between industry and academe. This paper raises policy recommendations from synthesizing the trends in nanotechnology and forecasting how it develops so as the country can readily adapt. Moreover, this paper identifies the barriers and constraints, as well as the factors necessary for the technology adoption in the country.

The uses of Artificial Intelligence (AI) seems to be relevant in many fields nowadays due to its ability in providing a simulation of human intelligence processes that are handled by machines; in particular computer systems. This paper concerns with reviewing the uses of AI in language teaching and learning. In particular, it reviews the research on the uses of AI in its application in the learning and teaching of language. Qualitative research method; specifically content analysis, is employed as the technique to review the articles that are obtained from relevant databases. Findings from the study reveal that there are four (4) themes emerge in the uses of AI in relation to teaching and learning a language. The uses of AI for pedagogy, therefore, prove that its uses eases language teaching and learning.

Anthocyanins are naturally occurring pigments of red and purple. Red anthocyanin pigments provide a strong and sharp and widely applied in various industries such as food coloring or drink. Anthocyanins isolated by maceration, extraction and thin layer chromatography (TLC). The extract has been obtained from the initial stages of maceration then separated into several fractions by chromatography to isolate fractions colored dark red. Identification of chemical compounds with TLC (Thin Layer Chromatography) is able to distinguish the fraction of anthocyanin produced. FTIR (Fourier Transform Infrared Spectroscopy) used to identification of the functional group of a compound. The UV-Vis absorption spectra have to produce maximum absorbance values that describe the intensity of anthocyanin spectra in different colors for different pH. Anthocyanins are more stable at low pH (acidic conditions) which gives a red pigment. Meanwhile, the higher the pH value of anthocyanin will provide color fading of the color blue. So as a food colorant, anthocyanin with a low pH or height pH has a significant effect on the food colorant.

Soursop (Annona muricata) is a plant that is widely available in Indonesia. Of all parts of the soursop plant, the leaves are the most interesting parts to be studied. Soursop leaves are the most interesting part to be investigated because soursop leaves have many benefits and benefits that have been applied in the health sector, both traditional and modern. This is because soursop leaves contain many active compounds such as alkaloids, terpenoids, flavonoids, tannins, saponins, acetogenins, and others. The purpose of this review is to compare the best methods commonly used to extract active compounds from soursop leaves. The methods studied were maceration, soxhletation and microwave assisted extraction (MAE). The mechanism of the extraction processes and the percentage of yield achieved from the three methods are also reviewed. The results of the review show that MAE is the method that produces the highest yield of the three methods with a yield of 33.98%. This method also has another advantage that is a shorter extraction time.

The aim of this work is to determine the fatigue life of 316L stainless steel. The mechanisms of fatigue of 316L stainless steels were investigated and discussed. The fatigue tests were carried out at constant-amplitude cyclic loading with load ratio R=0.1. Scanning Electron Microscope (SEM) is then used to examine the fracture surface. The results show that the fatigue limit of 316L stainless steel was 146.45 MPa.

The paper presents the results of a study concerning the use of the Ishikawa diagram in analyzing the causes that determine errors in the evaluation of theparts precision in the machine construction field. The studied problem was"errors in the evaluation of partsprecision" and this constitutes the head of the Ishikawa diagram skeleton.All the possible, main and secondary causes that could generate the studied problem were identified. The most known Ishikawa models are 4M, 5M, 6M, the initials being in order: materials, methods, man, machines, mother nature, measurement. The paper shows the potential causes of the studied problem, which were firstly grouped in three categories, as follows: causes that lead to errors in assessing the dimensional accuracy, causes that determine errors in the evaluation of shape and position abnormalities and causes for errors in roughness evaluation. We took into account the main components of parts precision in the machine construction field. For each of the three categories of causes there were distributed potential secondary causes on groups of M (man, methods, machines, materials, environment/ medio ambiente-sp.). We opted for a new model of Ishikawa diagram, resulting from the composition of three fish skeletons corresponding to the main categories of parts accuracy.

"Nuclear Science and Technology For Socio-economic Development"

Bangi, Selangor, Malaysia

14-16 October 2024

MESSAGE FROM: PRESIDENT, MALAYSIAN NUCLEAR SOCIETY (MNS)

I am really pleased to congratulate all keynote speakers, sponsors, presenters, and participants for the contribution and participating in the International Nuclear Science, Technology and Engineering Conference (iNuSTEC2024). Ideally, the iNuSTEC2024 is organized to enhance the importance of nuclear science, technology, and engineering in developing socio-economic in Malaysia. Successful conferences from previous years, at both national and international levels, have brought this event to be more meaningful to strengthen nuclear development for global growth under challenging situation

With the support from the American Society of Mechanical Engineers (ASME) Malaysia Section, and Malaysian Welding and Joining Society (MWJS), the MNS is indeed honored to co-organise this event with organizations such as Nuclear Malaysia Agency, UNITEN, UTM, UKM, UM, UiTM, USIM and UTHM. The affiliation of the Institute of Nuclear Energy of UNITEN and advanced Nuclear Engineering Research Group of UTM and Institute of Nuclear Engineers (INE) of MNS, to make iNuSTEC2024 a success is a good testament that nuclear still remain relevant in the heart of the young generation to move towards greater strength in nuclear fields. In the future, MNS members shall strive to reach out to more diverse population in order to make nuclear ecosystem more conducive and stronger.

This conference had been supported by experienced and young researchers that can give a platform for them to discuss and debate on the latest development in all areas of nuclear technology applications for friendly purposes at the international level. This would spur and catalyse further research and development leading to the sustainability and improvement of the quality of life without compromising the quality of the environment in Malaysia and the world.

List of Editors, Supporting/Sponsoring Organisations, Contents, iNuSTEC2024 Organising Committee, Technical Committee, Nuclear Youth Competition 2024, iNuSTEC2024 Poster Competition, Acknowledgement, Sponsors and MNS Council Members 2023/2025 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: Single Anonymous

• Conference submission management system: Morressier

• Number of submissions received: 16

• Number of submissions sent for review: 16

• Number of submissions accepted: 16

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

• Average number of reviews per paper: 2.87

• Total number of reviewers involved: 20

• Contact person for queries:

Name: Faridah Mohamad Idris

Email: faridah246@gmail.com

Affiliation: Universiti Tenaga Nasional

The mass attenuation coefficient becomes an important parameter to determine the attenuation property of a material towards photons. The study focused on the measurement of mass attenuation coefficients of several phantom materials in comparison to water by using effective energies of kilovoltage X-rays. The mass attenuation coefficient of Perspex®, solid water phantom and paraffin wax regularly used in diagnostic radiology and radiotherapy is measured by using effective energies of 60, 81 and 125 kVp X-rays based on the common diagnostic imaging set ups and compared to water. The results indicated that the mass attenuation coefficients of Perspex®, solid water and paraffin wax are in agreement with water with percentage of discrepancies between 22 and 13%. The percentage differences to water also becoming smaller when higher x-ray energies are used. The results indicated the suitability of the X-ray effective energy method for the measurement of mass attenuation coefficients of materials.

This paper presents an automated data collection system for gammaray measurement using the Python programming language. The system automates experimental data collection from gamma-ray detection systems, providing greater confidence in research results. The objective of this study is to develop a Python coding system for automated data collection and to produce significant graphical data results. The study used Python coding to continuously measure and analyze gamma rays emitted from Ba-133 radioactive material, which were detected using a scintillation detector and counted using a scaler ratemeter. The coding system used NumPy, Pandas, Matplotlib, and Tkinter Python packages, and Microsoft Visual Studio Community for integration. The Beer-Lambert attenuation law formula is embedded in the coding system to produce intensity against time graphical data results for various sample materials. The developed Python code was integrated into the gamma-ray detection system. The automated data collection system operates without significant lag or errors for 3 hours of gamma-ray measurements with 6 to 10 seconds of time interval speed. The graphical user interface (GUI) and data output are visualized immediately and continuously, and all data output can be safely stored on the computer. A Python-based automated data collection system was successfully developed, allowing efficient visualization of significant graphical data results. This system can reduce radiation exposure for radiation workers and may integrate with cloud computing for remote operation in the future.

Gamma-ray spectrometry is a vital technique for identifying and measuring radioactivity in environmental samples, offering high energy resolution. However, the accuracy of measurements in bulk samples is often compromised due to geometric and compositional variations from reference samples, leading to self-attenuation effects. This study aims to improve the accuracy of gamma-ray activity measurements in bulk soil samples by applying a self-attenuation correction across various geometric shapes and sample matrices. The correction methodology was implemented by comparing the photon attenuation within the sample to a standard air sample, taking into account the linear attenuation coefficient and sample thickness. This method was experimentally verified using High Purity Germanium (HPGe) detectors, resulting in improved accuracy of activity concentration measurements by 3.88% to 6.72%. The proposed method provides a practical alternative to existing techniques, including LabSOCS simulations and empirical corrections by offering a practical, adaptable solution without the need for extensive computational resources. The self-attenuation correction reduced measurement discrepancies by 4.3% to 10.8%, particularly in samples with significant density variations. Beyond environmental monitoring, this correction methodology has potential applications in other fields requiring precise radioactivity measurements, such as medical physics, industrial radiography, and nuclear safety protocols. These findings underscore the critical importance of accurate self-attenuation corrections for reliable environmental and radiological monitoring.