Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

This article explores the relationship between the bodily presence of other humans in the lived urban world and the experience of everyday architecture. We suggest, from the perspectives of phenomenology and architecture, that being in the company of others changes the way the built environment appears to subjects, and that this enables us to perform simple daily tasks while still attending to the built environment. Our analysis shows that in mundane urban settings attending to the environment involves a unique attentional (...) mode, which does not rely on concentrating on, or appreciating the architectural objects, but rather on social attention and on the subject’s kinesthesis in relation to the built environment. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly advanced, offering significant potential to transform business decision-making. This paper delves into how AI can be harnessed to enhance strategic decision-making within business contexts. It investigates the integration of AI-driven analytics, predictive modeling, and automation, emphasizing their role in improving decision accuracy and operational efficiency. By examining current applications and case studies, the paper underscores the opportunities AI offers, including improved data insights, risk management, and personalized customer experiences. It also addresses the challenges businesses (...) face when adopting AI, such as data privacy concerns, integration difficulties, and the need for skilled professionals. The paper concludes by offering recommendations for successfully implementing AI solutions to maximize benefits while mitigating potential challenges. (shrink)

Abstract: This research paper presents the development and evaluation of a neural network-based model for predicting fire alarms in smoke detection systems. Using a dataset from Kaggle containing 15 features and 3487 samples, we trained and validated a neural network with a three-layer architecture. The model achieved an accuracy of 100% and an average error of 0.0000003. Additionally, we identified the most influential features in predicting fire alarms.

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...) sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (shrink)

Objectives: This study aimed to fill the gap between Vietnamese diabetic patients' needs and care through a qualitative study asking about their experiences with diabetes and quality of care. -/- Methods: Interviews with five diabetic patients were conducted at a tertiary general hospital located in southern Vietnam. The transcribed data were first subjected to quantitative text analysis using KH Coder to identify major categories of frequently used words, followed by a qualitative analysis of selected cases using the Steps for Coding (...) and Theorization (SCAT) method. -/- Results: The major categories of frequently used words were chronic health conditions, services, facilities, insurance, patient-doctor communication, and medication. SCAT analysis of three selected cases identified six themes: “Disregarding the disease at the early stage,” “Fear of complications,” “Satisfaction with hospital services and medical staff,” “Insurance-related problems,” “Long waiting times,” and “Communication barriers between patients and doctors.” Patients were satisfied with improved hospital facilities and services; however, the overloading of one hospital led to long waiting times and communication difficulties with doctors. Difficulties with health insurance were also observed, and patients were rather passive in disease management and needed to be empowered through improved communication with doctors and other care providers. -/- Conclusion: These findings from our trial of introducing a qualitative study into service evaluation suggest that listening to patients can help health providers learn their perspectives and be more responsive to their needs. (shrink)

Ang pag-aaral na ito ay naglalayong alamin ang kapaligirang pampagkatuto, klimang pangklasrum at performans sa Filipino ng mga mag-aaral sa grado labing-isa (11) ng Mataas na Paaralang Nasyonal ng Ajuy. Ito rin ay naglayong matukoy kung mayroong makabuluhang pagkakaiba sa kapaligirang pampagkatuto at klimang pangklasrum at kung mayroon bang makabuluhang kaugnayan sa performans sa Filipino. Ang mga kinakailangang datos ay tinipon sa pamamagitan ng pagbigay ng talatanungan sa kapaligirang pampagkatuto, klimang pangklasrum at pagsusulit sa performans sa Filipino. Isandaan na nagmula (...) sa Mataas na Paaralang Nasyonal ng Ajuy ang naging kalahok sa pagaaral na ito. Sila ay pinili gamit ang stratified quota random sampling. Ang mga datos ay sinuri sa larangan ng computerprocessed statistics, percentage mean, frequency count, standard deviation, One Way ANOVA (Analysis of Variance), t-test at Pearson’ r. Ang alpha level ay nakaset sa .05 sa lahat ng inferensyal na pagsusulit. Ang mga natuklasan ay nagpakita na may “kaaya-aya” na antas ang kapaligirang pampagkatuto at may “kaaya-aya” na antas ang klimang pangklasrum. Napag-alaman din na mayroon silang “katamtamang” performans sa Filipino. Nakita rin sa pananaliksik na ito na “walang makabuluhang kaugnayan” ang performans sa Filipino sa antas ng kapaligirang pampagkatuto at antas ng klimang pangklasrum. Napag-alaman din na “walang makabuluhang pagkakaiba” ang kapaligirang pampagkatuto sa performans sa Filipino. “Wala ring makabuluhang pagkakaiba” ang klimang pangklasrum ng mga mag-aaral sa Filipino sa performans sa Filipino. Napag-alaman din na “walang makabuluhang kaugnayan” ang kapaligirang pampagkatuto sa klimang pangklasrum maging ang kapaligirang ampagkatuto sa performans sa Filipino gayundin ang klimang pangklasrum at performans sa Filipino. (shrink)