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Managing flash flood crises with cultural perspectives: A user-centric feature identification study
No full textFlash floods are severe disaster that have caused enormous damage to people, property, and the environment. Despite the conventional emphasis on technical and engineering solutions in controlling flash flood disasters, this study investigates the understudied issue of user-centric cultural viewpoints, inspired by Grid-Group Cultural Theory, and their potential impact on crisis management. The study collected 351 responses, primarily targeting adults in flood-prone areas using convenience sampling method with the goal of exploring cultural bias for feature identification of in-vehicle flash flood app. Accordingly, the research investigates the participants responses using quantitative approach which includes descriptive statistics, exploratory factor analysis, average factor, and rank scoring analysis to uncover critical user-centric cultural traits that might improve preparedness, response, and recovery activities during flash flood disasters. The findings of the study identified distinct cultural biases that impact perceptions and preferences regarding features of an in-vehicle flash flood app. By integrating Grid-Group Cultural Theory as a framework for analysis, the study highlights the importance of incorporating diverse cultural perspectives into flash flood management strategies. The result emphasizes the need to apply a holistic approach that integrates people’s knowledge and practices with technical solutions. Recommendations of features for future development of in-vehicle flash flood app is provided based on each cultural bias aligned with the theory to build more resilient communities in the face of flash flood occurrence
Catalysing sustainable change: the role of digital finance in poverty alleviation in Asia
No full textPoverty continues to be a major global issue, disproportionately affecting low-income
populations. In recent years, the advent of digital finance has presented itself as a potential
remedy, offering innovative ways to circumvent the traditional obstacles that have historically hindered low-income individuals’ access to essential financial services. Nevertheless, despite these opportunities, there remains a dearth of research examining whether
increased usage of digital financial services contributes to poverty reduction. The main
objective of this study is to bridge this research gap by conducting an empirical investigation into the relationship between digital finance usage and poverty levels in Asia spanning from 2014 to 2021. Analysis employing traditional regression models (ordinary least
square, fixed-effect, and random-effect) indicates a positive relationship between digital
finance usage and poverty reduction. To enhance the robustness of these findings, this
study additionally employed quantile regression, instrumental variables regression, and
ridge regression, which collectively reinforce the initial results. Overall, this study highlights that digital finance can be an effective way to reach low-income individuals with
financial services that allow them to manage finances, build savings, and access credit.
Building on these findings, this study suggests implementing policy measures to further
promote the use of digital finance in poverty alleviation efforts
Remanufactured consumer goods buying intention in circular economy: Insight of value-belief-norm theory, self-identity theory
No full textThis study investigates the direct and mediated impact of ethical sensitivity, pro-environmental self-identity, and ecological consciousness on consumers’ intentions to purchase remanufactured electronic devices, focusing on computers, through the lens of the Value-Belief-Norm (VBN) theory and Self-Identity Theory. Utilizing a cross-sectional research framework, data from 349 respondents were analyzed using Structural Equation Modeling (SEM). The findings reveal that ethical sensitivity and pro-environmental self-identity significantly enhance purchasing intentions, with ecological consciousness serving as both a direct predictor and a mediator. Interestingly, perceived costs negatively influence purchasing intentions, while perceived benefits emerge as a strong positive determinant. However, heightened price consciousness showed no significant effect, suggesting a shift in consumer priorities towards value and sustainability over cost. These results highlight the critical role of aligning marketing strategies with consumers’ ethical and environmental values, emphasizing transparency in marketing and inventory management. The study also offers actionable insights for businesses and policymakers, including strategies to reduce cognitive burdens, foster pro-environmental identities, and enhance trust in remanufactured products. By addressing key psychological and practical barriers, this research contributes to advancing sustainability goals and promoting the circular economy in an era of escalating environmental challenges
IM- LTS: An Integrated Model for Lung Tumor Segmentation using Neural Networks and IoMT
No full textIn recent days, Internet of Medical Things (IoMT) and Deep Learning (DL) techniques are broadly
used in medical data processing in decision-making. A lung tumour, one of the most dangerous
medical diseases, requires early diagnosis with a higher precision rate. With that concern, this
work aims to develop an Integrated Model (IM- LTS) for Lung Tumor Segmentation using Neural
Networks (NN) and the Internet of Medical Things (IoMT). The model integratestwo architectures,
MobileNetV2 and U-NET, for classifying the input lung data. The input CT lung images are preprocessed using Z-score Normalization. The semantic features of lung images are extracted based
on texture, intensity, and shape to provide information to the training network.
• In this work, the transfer learning technique is incorporated, and the pre-trained NN was used
as an encoder for the U-NET model for segmentation. Furthermore, Support Vector Machine
is used here to classify input lung data as benign and malignant.
• The results are measured based on the metrics such as, specificity, sensitivity, precision, accuracy and F-Score, using the data from benchmark datasets. Compared to the existing lung
tumor segmentation and classification models, the proposed model provides better results and
evidence for earlier disease diagnosis
Analyzing factors influencing students’ decisions to adopt smart classrooms in higher education
No full textSmart classrooms which are facilitated by advanced technology have become a digital learning platform for all university students. Despite their signifcance in higher
education, the number of students adopting the current technology has remained signifcantly low; thus, universities have to fnd new solutions to convince their students
to quickly adopt smart classrooms. In response to this issue, this study aims to analyze students’ intention to adopt smart classrooms by examining the associated sections between resource availability (technology readiness), technological advantages
(perceived usefulness and ease of use), user attitudes (trust and perceived value),
and user decisions (adoption intention). 630 students from diferent universities in
Thailand were approached and asked for their consent to fll in the questionnaires
with an approximate time of 10–15 min. Researchers applied the SEM technique
to analyze the data. Results revealed that technology readiness positively afected
ease of use in smart classrooms. Meanwhile, technology readiness and ease of use
positively infuenced students’ perceived usefulness. In addition, perceived usefulness and ease of use had positive associations with perceived value. After that, only
perceived value and usefulness were the key determinants of student trust. Finally,
perceived value and trust showed signifcant impacts on students’ intention to adopt
smart classrooms. To fasten smart classroom adoption in higher education, universities should have technological resources available for advancing and upgrading their
teaching facilities so that students can see more technological advantages assisting
their studies and have more positive attitudes toward the new technology which can
strongly convince students’ decision to immediate adopt the smart classrooms
The data scientist as a mainstay of the tumor board: global implications and opportunities for the global south
No full text1.1 Importance of tumor boards in cancer treatment
Tumor boards are multidisciplinary teams of healthcare professionals that are working together to encompass the full spectrum of care around diagnosing, planning treatment, and advising outcomes for individual cancer patients. These boards typically consist of oncologists, radiologists, pathologists, geneticists, surgeons, nurse practitioners, and other palliative care professionals (1). These boards create a collaborative space for experts from various disciplines to assess clinical factors and patient circumstances, ensuring the application of appropriate care standards and personalized recommendations from the National Comprehensive Cancer Network (NCCN) Guidelines to enhance cancer treatment are met. Since no patient fits the “textbook” cancer profile, oncologists benefit from discussing tailored treatment plans and learning from their colleagues' experiences. When tumor boards are functioning well, they can have a significant impact on patient care (2). For instance, a thoracic oncology board in Munich, Germany, found that 90% of their recommendations met or exceeded clinical standards, with nearly 90% being implemented in practice (3).
Tumor boards are increasingly used worldwide, but expertise and resources for conducting multidisciplinary tumor boards are still limited in the Global South. However, this does not mean they cannot be implemented in developing countries. A 2020 survey from Southeast Asia found that 80.4% of pediatric solid tumor units had pediatric-trained specialists, including oncologists, surgeons, radiologists, pathologists, radiation oncologists, nuclear medicine physicians, and nurses. This indicates that multidisciplinary tumor boards are already in place and that these specialists play a critical role in cancer care (4). With full implementation in the global south, data scientists can further enhance tumor boards with AI and data analytics to improve decision-making and personalize cancer care
Quantum Neural Networks: A Path to Lower Emissions Through Fuel Consumption Prediction in Shipping
No full textThis paper proposes Quantum Neural Networks (QNNs) as a data-driven approach for predicting fuel consumption. We utilize various layer architecture designs available in the Torchquantum framework, including both entangled and non-entangled circuit designs.
In general, QNNs can achieve comparable Root Mean Square Error
(RMSE) and Mean Absolute Percentage Error (MAPE) with significantly fewer trainable parameters. Neither pure QNNs nor hybrid
QNN models exhibit the underfitting tendencies seen in classical
neural networks (CNNs). Notably, one of the most significant findings of this work is that hybridizing or ”dressing” the quantum circuit leads to substantial improvements in RMSE and MAPE for pure
QNNs. These promising results suggest potential optimizations for
reducing emissions in green shipping
Internship programme and work readiness among vocational students
No full textThis study investigates how internship experiences influence job readiness perceptions among Business Administration students at Politeknik Negeri Padang, aiming to enhance vocational education and human resource quality in a global context. The literature review examines employment readiness and internship impacts on skill development and industry exposure, emphasising the role of internships in improving students' preparedness for work. This research uses descriptive and associative methods to explore the relationship between internship programmes and work readiness. Surveys were employed for data collection, with analysis techniques including validity testing, Spearman's rank correlation, and hypothesis testing. The study, which surveyed 115 Business Administration students, found strong agreement that internships enhance job knowledge, skills, attitudes, and workplace familiarity. Statistical analysis reveals a significant relationship (Spearman's rho = 0.773) between internships and work readiness(R² = 59.7%), underscoring the importance of internship programmes for student workforce preparation and advocating continued implementation at Politeknik Negeri Padan
The Effectiveness of Samsung Product Placement in Korean Drama
No full textThe worldwide success of placing products in Korean dramas as a powerful advertising tool inspired this study. However, past studies have shown inconsistent and contradictory findings regarding product placement in Korean dramas, which has a significant relationship with brand recall. Thus, this study aims to determine how recent Korean dramas use product placement to promote and raise awareness of South Korean products. The objectives of this study are 1) to understand the impact of Korean drama script placement (audio) on brand recall; 2) to examine the impact of Korean drama screen placement (visual) on brand recall; 3) to investigate the impact of Korean drama plot placement on brandrecall. The tripartite Typology of Product Placement was derived as the theoretical research of this study. The quantitative method in the form of a survey was applied to assess the important relationship between independent and dependent variables. The research respondents were active international Korean drama viewers in the KFriend Facebook group. SPSS was utilised to analyse and evaluate the relationships between the study's hypotheses. The findings indicate that script placement (audio), screen placement (visual), and plot placement have a significant relationship with brand recall among Korean drama viewer
Enhancing Financial Literacy: A Progressive Web Application Approach for Malaysian Youth
No full textFinancial management is a crucial skill that individuals of all age ranges should acquire and master. It offers a transparent view of our financial status, enabling us to comprehend where our expenses are directed and manage every facet of our finances. Studies have indicated that Malaysian youth lack understanding in financial management. Nowadays, with so many people using the internet, we have the opportunity to share this expertise with a larger audience. Providing easily accessible materials for learning about and managing personal finances is essential to comprehending people's individual financial circumstances. In light of this, the purpose of this article is to develop a useful, progressive web system for personal finance management that makes budgeting and cost tracking easier. This personal finance management system will be implemented using the Tailwind Cascading Style Sheets, Firebase, and React framework as development tools. React frameworks are used due to their ability to produce dynamic user interfaces. To sum up, this user-friendly interface mechanism enables the formulation of budgets and the tracking of expenses. It also consists of other features for data visualization, such as charts. This research has the potential to add some additional enhancements to its existing functionality. For instance, it could introduce a predictive budgeting function that uses historical user spending data to perform predictive analysis