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.

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)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the (...) presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

This article explores the essence of the human (insān) as it is understood in Twelver Shīʿī philosophy and mysticism. It presents a Shīʿī philosophical elucidation regarding the possible existence of extraterrestrial intelligent lifeforms and what their relationship with “humanhood” might be. This line of reasoning is presented with a general sketch of how, in Shīʿī Islamic thought, a “human being” is characterized by specific traits and the relationship of human beings with the archetype of the Perfect Human (al‐Insān al‐Kāmil). Following (...) this is a review of Shīʿī Imāmī traditions regarding extraterrestrial intelligent life and the plurality of worlds. This sequence ultimately allows for a unique analysis of humanhood according to the Shīʿī philosophical viewpoint and helps determine if the term “human” can be used for other intelligent beings with similar ontological features and intelligence levels. (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)

This study aims to identify social media and its relation with depression and how social media affects the mental health of individuals. The general Pakistani public who have attended college and are well educated is the study's target population. This research is based on a quantitative technique. A modified questionnaire was used in accordance with the study's objectives. The data was collected using Google forms. Five-point likert scales were preferred for the data collection when convenience sampling was used. The five-point (...) Likert scale served as the foundation for the survey. The ADANCO software was used to carry out the testing. These tests include the convergent validity, discriminant validity, and Cronbach's alpha reliability and validity tests. ADANCO has been used to measure the path coefficient, adjusted (R2), and coefficient of determination (R2). The confined areas for answers in Pakistan were the main focus of this investigation. The sample size for this study is small relative to the population because it was completed in a short time. The findings of this study show that social media can eventually lead to depression. In this study, the elements that affect mental health by excessive use of social media were examined. Numerous studies have been conducted on the detection of depression by the use of social media through bagging classifiers. We have collected data on the detection of depression through bagging classifiers and have added it to our literature review. (shrink)

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)

The elderly face very challenging situations due to their mental and physical conditions. Like the other country in the world, Bangladesh Government has enacted laws to protect the elderly rights. However, the law does not seem to represent what the elderly actually needs. Therefore, 385 elderly people, aged between 60 and 90 years were surveyed to understand their expectations from family, society, and government. There were 57.1% men and 42.9% women. Most of the elderly (80%) were educated. Just over half (...) (53.5%) had ordinary mental and physical health, while a quarter (31.4%) had good status. More than half (53%) of the participants required 2000–5000 BDTK (Bangladeshi Taka) equivalent to $20-50 to cover monthly treatment expenditures. The majority (67.3%) felt government Old Age Allowance should be increased to BDT 5,000 ($50). Of 13.8% of individuals experienced harsh discourse from family because of the cost of therapy. However, 16.9% of people choose not to respond to this question. More than half (57.4%) of the respondents’ thought caregivers were insufficient. One-third felt that legislation should be changed to take care of parents (33.5%) and One-third felt that children should take care of more (33.5%). Some (3.6%) thought that children should act as they did in their childhood respectively. Almost half (44.2%) of respondents did not know that the elderly should receive a separate senior citizen card for preferential treatment, yet 51.9% thought this. Some (44.7%) felt the elderly should get priority in any queue and discounts in Bus/Uber/Rickshaw. Results also showed that expectation is more than the service provided. Further, a one-stop elderly care clinic is required to provide integrated care and support for the quality of life of the elderly. (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)