Wan Azani Wan Mustafa
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Wan Azani Wan Mustafa
Official Name
Wan Azani, Wan Mustafa
Alternative Name
Mustafa, W.
Azani Mustafa, Wan
Mustaffa, Wan Azani
Wan Mustafa, Wan Azani
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Scopus Author ID
57219421621
Researcher ID
J-4603-2014

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Publication

PPG Segmentation Using Deep Learning

2023 , Mohammad Tabbakha , Hassan Al Masri , Abdullatif Hammad , Mohammed Alsulatie , Hiam Alquran , Wan Azani Wan Mustafa , Muntather Almusawi , Abbas Hameed Abdul Hussein

As an indicator regarding cardiovascular health, vascular dynamics, and more, Photoplethysmography (PPG) consists of a baseline with two pulsatile peaks that reflect the blood flow variations. In the absence of critical studies and a precise understanding of PPG signal this study proposes a deep learning approach to predict and define each phase of PPG waveform utilizing Gated recurrent unit (GRU) due to its optimal performance in the short-term dependencies in sequences, the model is composed mainly of GRU layer with 20 hidden units applying tanh and sigmoid activation function, followed by dropout layer and a fully connected layer, afterward a softmax layer was added, we conducted our study on a dataset combined of an accessible Bed-Based Ballistocardiography Dataset (BBB), after that, the data was manually labeled. Following up, hyperparameters such as learning rate, batch size, and other parameters were adjusted after numerous trials, which resulted in test accuracy, precision, and recall of 0.875, 0.892, and 0.854, respectively in the used dataset. These promising results might be the first step of more future investigations concerning PPG.

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Immersive Technologies: A Literature Review on Brand Engagement and Consumer Behaviour

2023 , Nor Hazlen Kamaruddin , Mohd Ekram Alhafis Bin Hashim , Wan Azani Wan Mustafa , Suraya Md Nasir , Mohd Fauzi Harun , Laith H. Jasim

The evolution of marketing through digital means has been greatly influenced by the emergence of virtual influencers on social media and the incorporation of immersive technologies such as AR, VR, and XR. This study examines the development of virtual influencers as an emerging frontier in consumer interaction, highlighting their unique benefits compared to traditional influencers and their potential for tailored and managed brand promotion. Digital avatars provide a unique method to engage audiences, but they also present ethical dilemmas and require scientific evidence to confirm their efficacy. The methodology includes a comprehensive literature study on many aspects of digital marketing, such as the influence of immersive technologies on brand storytelling and engagement, and the significance of gamification and video-based learning in improving user interaction from 2013 to 2024. The analysis highlights a significant deficiency in existing research about the enduring impacts of these technologies on brand loyalty and consumer behaviour. The digital age requires creative marketing methods that are ethical and align with consumers' desire for authenticity and engagement. Future studies should further investigate these aspects to ensure that virtual influencers and immersive technology are used properly to cultivate significant brand connections.

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Beyond trends: Tiktok’s educational symphony by unmasking the digital revolution

2023 , Miharaini Md Ghani , Wan Azani Wan Mustafa , Mohd Ekram Alhafis Bin Hashim , Hafizul Fahri Hanafi , Laith H. Alzubaidi

In the fast-paced digital age, TikTok has emerged as an unlikely protagonist in the realm of education, ushering in a bite-sized learning revolution. This comprehensive study delves into the captivating phenomenon of TikTok's educational content, unveiling its transformative impact on learners across generations and disciplines. Drawing from extensive empirical research and expert insights, the article will explore the intricate interplay between TikTok's snackable video format and its ability to foster knowledge acquisition and skill development. It illuminates how this platform's unique amalgamation of entertainment and education has redefined traditional learning paradigms, empowering users to consume and share knowledge in a highly engaging and democratized manner. Beyond trends unravels the cognitive mechanisms underpinning the effectiveness of bite-sized learning, shedding light on its potential to cater to diverse learning styles and attention spans. It examines the platform's role in democratizing access to education, enabling content creators and subject matter experts to reach unprecedented global audiences. Moreover, It provides a critical analysis of the challenges and opportunities that arise as bite-sized learning gains traction, offering invaluable insights for educators, policymakers, and stakeholders invested in shaping the future of education. With its multidisciplinary approach and forward-thinking perspectives, Beyond Trends serves as a comprehensive guide to navigating the digital learning landscape, empowering readers to harness the transformative potential of TikTok and its bite-sized educational content.

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Animating sustainable tourism: a literature review analysis of technology's role, challenges, and opportunities

2023 , Suraya Md Nasir , Mohd Ekram Alhafis Bin Hashim , Wan Azani Wan Mustafa , Nor Hazlen Kamaruddin , Haider Alabdeli , Hafizul Fahri Hanafi

This research article explores the intricate nexus between animation technology and sustainable tourism animation, conducting an extensive literature review to scrutinize the role, hurdles, and prospects that technology presents in promoting sustainability within the realm of tourism. The outcomes enrich our comprehension of how animation technology intersects with and shapes sustainable practices in tourism, illuminating potential advancements and areas necessitating attention. By dissecting the key technologies employed in sustainable tourism animation, scrutinizing the challenges in their integration, identifying opportunities for their utilization, and assessing their impact on the sustainability of animation, each facet contributes to a comprehensive understanding of sustainable tourism animation's influence on contemporary artistic practices, technological innovations, and educational strategies. Drawing insights from diverse academic sources, peer-reviewed journals, and case studies, this study offers an integrated perspective on the transformative capacity of sustainable animation. It delves into fostering creative expression, encouraging interdisciplinary collaboration, and promoting critical engagement with emerging technologies in the digital age.

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Whisper of understanding: age differences in algorithmic literacy across generations

2024-07 , Miharaini Md Ghani , Wan Azani Wan Mustafa , Mohd Ekram Alhafis Bin Hashim , Hafizul Fahri Hanafi , Haider Alabdeli

In today's digital landscape, algorithms play a pivotal role in shaping our experiences and decision-making processes. From social media feeds to online recommendations and search results, algorithms influence our daily interactions with technology. However, the understanding and literacy surrounding these algorithms vary significantly across different age groups, leading to a potential divide in how individuals engage with and comprehend the digital world. This research delves into the age differences in algorithmic literacy, exploring the contrasting experiences and challenges faced by younger generations, often referred to as "digital natives,"and older generations, termed "digital immigrants."By examining factors such as access to technology, educational opportunities, and cultural attitudes, this study aims to shed light on the root causes of these disparities. Through a multifaceted approach, including surveys, interviews, and observational studies, the research investigates the varying levels of algorithmic literacy across different age groups. It explores the potential advantages of younger generations, who have grown up immersed in digital environments, as well as the challenges faced by older generations, who may encounter resistance or difficulties in adapting to new technologies. Furthermore, this study examines the implications of age-related algorithmic literacy gaps, including the potential for digital exclusion, ethical concerns surrounding algorithmic bias and transparency, and the need for inclusive design and education initiatives. By highlighting these issues, the research aims to foster intergenerational dialogue and collaborative efforts to bridge the algorithmic literacy divide. Ultimately, this exploration of age differences in algorithmic literacy aims to contribute to the ongoing discourse on digital literacy, promoting a more inclusive and equitable digital landscape where individuals of all ages can engage with and critically understand the algorithms that shape their daily lives.

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Enhancing data quality in image pre-processing: a case study on plant disease classification

2023 , Ge Ye Ong , Nurzulaikha Abdullah , Fakhitah Ridzuan , Wan Azani Wan Mustafa , Laith H. Alzubaidi

Data quality plays a vital role in image pre-processing for machine learning applications. The effectiveness of building accurate and reliable models lies in the high-quality of data. Prioritizing data quality in the initial stages of the image pre-processing pipeline lays a strong foundation for subsequent machine learning stages. Therefore, this research aims to identify the appropriate steps for image pre-processing and compare the performance of machine learning model based on different pre-processing approaches. In this study, we utilized a plant diseases dataset sourced from Kaggle, comprising approximately 87,000 RGB images of both healthy and diseased crop leaves, categorized into 38 distinct classes. To significantly enhance the image quality, we implemented a range of transformation techniques, including resizing, normalization, data augmentation, and cropping. The analysis clearly indicates that implementing comprehensive pre-processing techniques enhances data quality and improves the machine learning model's classification performance.

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Navigating the ethical landscape of Artificial Intelligent(AI): a syntesis analysis across diverse disciplines

2024-07 , Mohd Ekram Alhafis Bin Hashim , Nor Hazlen Kamaruddin , Wan Azani Wan Mustafa , Suraya Md Nasir , Laith H. Jasim , Miharaini Md Ghani

This in-depth examination of 27 Scopus-indexed papers delves into the complex field of artificial intelligence (AI), emphasizing three key themes: "AI in Practice,""Ethical Considerations,"and "Holistic Impact."The synthesis emphasizes AI's revolutionary influence in a variety of fields, including art, advertising, renewable energy, and mental health therapy. However, an urgent need for more prominent labeling systems in AI-generated art emerges, necessitating additional study for practical application. Ethical considerations, such as privacy, surveillance, and responsible AI use, take center stage, pushing for ethical prioritizing in human behavior detection, advertising, and emotion recognition from text. Looking ahead, future research might delve deeper into the "AI in Practice"theme, including specific case studies and real-world implementations, to provide a thorough knowledge of actual benefits and obstacles. Exploring the development of strong ethical frameworks and norms within the "Ethical Considerations"dimension is critical for responsible AI deployment, as it addresses issues of prejudice and privacy concerns. To gain a better grasp of the "Holistic Impact,"interdisciplinary research might look into AI's impact on complex dynamics like doctor-patient interactions, environmental consequences, and overarching effects on human creativity. Finally, including these issues into future research endeavors is critical for developing a comprehensive perspective on the diverse influence of artificial intelligence. This approach not only improves our grasp of practical applications, ethical concerns, and social ramifications, but it also sets the framework for responsible AI integration in a variety of scenarios.

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Artificial Intelligence Law for Malaysia

2023 , Nor Ashikin Mohamed Yusof , Intan Sazrina Saimy , Siti Hasliah Salleh , Amirah 'Aisha Badrul Hisham , Wan Azani Wan Mustafa , Hassan Alkafaji

This study examines the proposed artificial intelligence (AI) law in Malaysia, exploring its distinctive approach within the global landscape. While adopting the established "AI Principles,"it rebrands them as "Seven Responsible AI Principles"and introduces the novel concept of "pursuit of happiness"as one of the core principles. This reflects Malaysia's commitment to forging its own path in AI governance, aligning with global standards while embedding unique cultural values and aspirations as expounded by the Federal Constitution and Rukun Negara Principles. Employing a qualitative approach, data was gathered through literature review and Focus Group Discussions (FGDs) with 80 participants representing diverse Quad Helix groups. Thematic and content analysis, along with triangulation, allowed for identification of key themes related to the perceived uniqueness of the proposed law and its alignment with national values. This research contributes significantly by shedding light on Malaysia's innovative approach to AI governance. By prioritizing national values and happiness alongside adherence to global standards, the proposed law has the potential to serve as a model for other nations seeking responsible and culturally sensitive AI regulations. This study offers valuable insights into the early stages of Malaysia's AI journey, paving the way for further discussions and research as the law progresses towards implementation.

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Unveiling The Digital Realm: A Systematic Review on Regulating Blockchain for Online Breast Milk Services

2023 , Amirah ‘Aisha Badrul Hisham , Nor Ashikin Mohamed Yusof , Zilal Shaari , Hafiza Abas , Shazana Mustapa , Syakirah Zahar , Wan Rusydiah Salehudin , Syamilah Saliman , Muntather Almusawi , Wan Azani Wan Mustafa , Farah Norwahidah Mohd Yunus

The traditional or modern practice of sharing breastmilk raises concern regarding security, traceability, safety, and quality assurance. This systematic review explores the application of blockchain technology in addressing these issues, aiming to enhance the security and efficiency of breastmilk sharing in healthcare settings. This systematic review delves into the burgeoning intersection of blockchain technology and online breast milk services, exploring the multifaceted landscape encompassing healthcare data management, privacy, safety, security, quality assurance, governance, interoperability, and legal and regulatory challenges. Employing a comprehensive research methodology, we conducted an extensive review of scholarly articles of Scopus, Web of Science and PubMed databases using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique. The final main data is n = 26 and analyzed using synthesis approach. Four main themes were generated: (i) blockchain for healthcare data management, (ii) privacy of data, safety, security, and quality assurance for donated breastmilk, (iii) governance and interoperability, (iv) legal and regulatory challenges. This systematic review highlighted the vast potential, capabilities, opportunities, and challenges of using blockchain for a noble cause of sharing or donating breastmilk. The inputs are useful for policymakers, healthcare professionals, and researchers in fostering an introducing better policy, policy interventions and legal mechanisms for a better, secure, transparent, and ethical digital ecosystem in maternal and child healthcare.

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Supervised machine learning approach to housing market

2023 , Izat Hakimi Mohd Ismayatim , Hanis Najiah Zakaria , Ihsanul Arifin Ramadhani , Nurzulaikah Abdullah , Fakhitah Ridzuan , Wan Azani Wan Mustafa , Mohammed H. Al-Farouni

Understanding the multifaceted factors influencing housing prices is crucial for facilitating informed decision-making among diverse stakeholders, including homebuyers, sellers, investors, and policymakers. Therefore, the primary objective of this research is to develop a predictive model for housing prices utilizing regression analysis. By leveraging machine learning techniques, such as regression and classification analysis, this study aims to uncover the intricate relationships between various factors and housing prices, ultimately providing valuable insights to stakeholders involved in the real estate market. Through rigorous data analysis and model development, this research seeks to enhance understanding and contribute to more accurate predictions in the realm of housing price dynamics.

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