Physical Sciences and Mathematics Commons^™

The Performance Of Arima And Arfima In Modelling The Exchange Rate Of Nigeria Currency To Other Currencies, Adewole Ayoade I.

Al-Bahir Journal for Engineering and Pure Sciences

Economic performance of a nation depends majorly on the stability of foreign exchange rate; the economic viability hangs on the exchange rate of local currencies against other currencies across the globe. Box – Jenkins Approach was employed to model the Naira exchange rate to other major currencies using Autoregressive Integrated Moving Average (ARIMA) and The autoregressive fractional integral moving average (ARFIMA) models. This studies aimed on measuring forecast ability of Autoregressive Integrated Moving Average (ARIMA) (p,d,q) and autoregressive fractional integral moving average (ARFIMA) (p, fd, q) models for stationary type series that exhibit features of Long memory properties. Results indicate …

Significant Predictors Of Suicide Rates In The United States: A Multiple Regression Analysis, Alexa L. Darak, Gary Popoli

Undergraduate Research Journal for the Human Sciences

Inspired by Stack's (2021) research, this study investigated the influence of 19 variables on suicide rates across all 50 United States. The variables included political party, gun ownership, registered guns, religion, alcohol consumption, state safety, depression, marriage, divorce, domestic violence, race, mean elevation, and region. Regression analyses revealed that gun ownership significantly impacts suicide rates, with stricter firearm laws correlating with lower suicide rates. Other crucial contributors to suicide risk were alcohol consumption, domestic violence, marital status, divorce, mean elevation, and political party affiliation. The five most statistically significant predictor variables were gun ownership, divorce rates, percentage of White individuals, …

Research On Chinese Data Sovereignty Policy Based On Lda Model And Policy Instruments, Han Qiao, Junru Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data sovereignty has become an important component of national sovereignty in the dual context of the digital economy development and the overall national security concept. Major countries and regions are actively carrying out data sovereignty strategic deployment and engaging in fierce competition in data resources, data technology, and data rules. This work adopts the policy text analysis method to study China’s data sovereignty policy, and employs the LDA model and policy instruments to quantitatively analyze the process evolution and thematic characteristics of China’s data sovereignty policy. Drawing on these findings, this study comprehensively considers the global data sovereignty policy and …

Application And Effectiveness Of Artificial Intelligence For The Border Management Of Imported Frozen Fish In Taiwan, Wen-Chin Tu, Wan-Ling Tsai, Chi-Hao Lee, Chia-Fen Tsai, Jen-Ting Wei, King-Fu Lin, Shou-Mei Wu, Yih-Ming Weng

Journal of Food and Drug Analysis

In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these border sampling inspections. Previously, border management has used an automated border inspection system (import food inspection (IFI) system) to select batches via a random sampling method to manage the risk levels of various food products complying with regulatory inspection procedures. Several countries have implemented artificial intelligence (AI) technology to improve domestic governmental processes, social service, and public feedback. AI technologies are applied in border inspection by the Taiwan Food and Drug Administration (TFDA). Risk management of border inspections …

A Novel Fuzzy Time Series Forecasting Method Based On Probabilistic Fuzzy Set And Cpbd Approach, Krishna Kumar Gupta, Suneet Saxena

Applications and Applied Mathematics: An International Journal (AAM)

Probabilistic fuzzy set is used to model the non-probabilistic and probabilistic uncertainties simultaneously in the system. This study proposes a cumulative probability-based discretization and probabilistic fuzzy set based novel fuzzy time series forecasting method. It also proposes a novel discretization approach based on cumulative probability to tackle the probabilistic uncertainty in partitioning of datasets. Gaussian probability distribution function has been used to construct probabilistic fuzzy set. The advantage of the proposed work is that it addresses the uncertainties due to randomness and fuzziness simultaneously and also improves accuracy rate in time series forecasting. A proposed forecasting method is applied on …

Stability Of Predator-Prey Model For Worm Attack In Wireless Sensor Networks, Rajeev Kishore, Padam Singh

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we propose a predator-prey mathematical model for analyzing the dynamical behaviors of the system. This system is an epidemic model, and it is capable of ascertaining the worm's spreading at the initial stage and improving the security of wireless sensor networks. We investigate different fixed points and examine the stability of the projected model.

Effects Of Maternal Anthropometry On Infant Anthropometry: A Cross-Sectional Study At Public Hospital X In Ternate, Indonesia, Yuni Nurwati, Hardinsyah Hardinsyah, Sri Anna Marliyati, Budi Iman Santoso, Dewi Anggraini

Kesmas

Infant anthropometry is an indicator of neonatal survival. This study aimed to determine the effects of maternal anthropometry on estimating infant anthropom­etry. This cross-sectional study on 173 pregnant women at Public Hospital X in Ternate, Indonesia, was conducted from August 2018 to March 2023. The el­igible criteria were pregnant women aged ≥18 years, single pregnancy, and antenatal care (ANC) visits to the same hospital. The variables used included ma­ternal anthropometric measurements (body weight, body height, third-trimester weight (TTW)), gestational weight gain (GWG), education, age, ANC visits, and gestational age at delivery (GAD). A logistic regression model was employed to estimate …

Road Traffic Noise Annoyance And Cardiovascular Disease Risk In Population: A Case Series Study In Kota Bharu, Malaysia, Faridah Naim, Nurin H M Nasir

Kesmas

Noise pollution can cause annoyance, significantly threatening the population’s health and well-being. This study aimed to find an association between road traffic noise exposure and cardiovascular disease (CVD) risk among residents in Kota Bharu, Malaysia. This descriptive study used a case series approach and surveyed 34 residents in selected residential areas near main roads. An adapted questionnaire was distributed to residents using a purposive sampling method. Questions related to sociodemographic information, self-reporting about CVD, and road traffic noise assessment were asked to investigate the underlying risk factors for CVD. The average score of CVD assessment was classified as moderate risk. …

Implementation Of Digital Health In Addressing Global Threats: Lessons From The Use Of Technology During Covid-19 Pandemic In Indonesia, Naili Shifa, Anisa Tiasari, Kemal N. Siregar

Kesmas

This research conducted a systematic literature review to explore the implementation of digital health in Indonesia, focusing on the digital health policies, usage during the COVID-19 pandemic, benefits, and lessons learned. The study identified 10 relevant journals through database searches and analyzed the trends in publication, productive journals, and top institutions involved in digital health research. The findings revealed an increasing interest in digital health, with a growing number of published articles from 2021 to 2023. ScienceDirect emerged as the most productive journal, followed by PubMed and MDPI. The University of Indonesia and the University of Gajah Mada were the …

Optimizing Buying Strategies In Dominion, Nikolas A. Koutroulakis

Rose-Hulman Undergraduate Mathematics Journal

Dominion is a deck-building card game that simulates competing lords growing their kingdoms. Here we wish to optimize a strategy called Big Money by modeling the game as a Markov chain and utilizing the associated transition matrices to simulate the game. We provide additional analysis of a variation on this strategy known as Big Money Terminal Draw. Our results show that player's should prioritize buying provinces over improving their deck. Furthermore, we derive heuristics to guide a player's decision making for a Big Money Terminal Draw Deck. In particular, we show that buying a second Smithy is always more optimal …

Model Selection Through Cross-Validation For Supervised Learning Tasks With Manifold Data, Derek Brown

The Journal of Purdue Undergraduate Research

No abstract provided.

Sensitivity Analysis Of Prior Distributions In Regression Model Estimation, Ayoade I Adewole, Oluwatoyin K. Bodunwa

Al-Bahir Journal for Engineering and Pure Sciences

Bayesian inferences depend solely on specification and accuracy of likelihoods and prior distributions of the observed data. The research delved into Bayesian estimation method of regression models to reduce the impact of some of the problems, posed by convectional method of estimating regression models, such as handling complex models, availability of small sample sizes and inclusion of background information in the estimation procedure. Posterior distributions are based on prior distributions and the data accuracy, which is the fundamental principles of Bayesian statistics to produce accurate final model estimates. Sensitivity analysis is an essential part of mathematical model validation in obtaining …

A Quantitative Analysis Of Seaplane Accidents From 1982-2021, David C. Ison

International Journal of Aviation, Aeronautics, and Aerospace

This study aimed to assess and analyze all historical National Transportation Safety Board accident reports since 1982. For analysis, reports were bisected into seaplane (float, amphibian, and hull) and non-seaplane groups. Findings showed that there is a deficiency in the level of available detail on the seaplane fleet and cadre of seaplane pilots in the U.S. During the most recent ten years of complete data (2012-2021) showed a negative trend in all accidents and fatal accidents, although only the latter being statistically convincing. During this timeframe, seaplane accident pilots had significantly higher total time and age than other groups (non-seaplane …

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Atmospheric 14Co2 Observation: A Novel Method To Evaluate Carbon Emissions, Zhenchuan Niu, Peng Wang, Shugang Wu, Weijian Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

As an important carbon emitter, China faces the stress of carbon peaking and carbon neutrality goals and international carbon reduction duty. The accurate data of carbon emissions are important to evaluate the carbon peaking and carbon neutrality goals and fulfill the international duty of carbon reduction. The Intergovernmental Panel on Climate Change (IPCC) report recommends the combination of top-down atmospheric CO₂ observation with atmospheric inversion to verify the bottom-up inventory of carbon emissions, and the atmospheric ¹⁴CO₂ observation can make the verification more accurate. Radiocarbon (14C) is the most precise tracer of fossil fuel CO₂ and …

Challenges And Countermeasures For Treatment And Remediation Of Contaminated Mega-Sites In China, Xiaoyong Liao, Yixuan Hou, You Li, Tianyi Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The treatment and remediation of pollution at contaminated mega-sites poses a significant challenge in the environmental science both domestically and internationally. Contaminated mega-sites are characterized by their widespread impact, multiple types of pollutants, and significant ecological and environmental threats. The environmental behavior cognition and efficient remediation at contaminated mega-sites face enormous challenges, among which key technological issues such as the formation mechanism of soil and groundwater pollution, accurate identification of pollution sources, and intelligent decision-making optimization urgently need to be solved. In China, contaminated mega-sites are concentrated in economically developed regions such as Beijing-Tianjin-Hebei, the Yangtze River Economic Belt, and …

Spatial Agglomeration And Environmental Effects Of Heavy Polluting Industries In China: Characteristics And Enlightenment, Hongyang Chen, Jianhui Yu, Wenzhong Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Heavy polluting industries are the important sources of industrial pollutant. Understanding the spatial agglomeration characteristics, influencing factors, agglomeration mechanism and environmental effects of China’s heavy polluting industries can help identify potential pollution risk areas to cope with increasingly severe environmental pollution problems. Based on the industrial economic data from 1999 to 2021, the spatial distribution and agglomeration characteristics of heavy polluting industries are characterized. It is found that: (1) Shandong, Jiangsu, Zhejiang, and Guangdong are the regions with high output value of the development of heavy polluting industries in the past 20 years, while Xinjiang, Inner Mongolia, Shanxi, Shaanxi, Henan, …

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Differentiation Of Human, Dog, And Cat Hair Fibers Using Dart Tofms And Machine Learning, Laura Ahumada, Erin R. Mcclure-Price, Chad Kwong, Edgard O. Espinoza, John Santerre

SMU Data Science Review

Hair is found in over 90% of crime scenes and has long been analyzed as trace evidence. However, recent reviews of traditional hair fiber analysis techniques, primarily morphological examination, have cast doubt on its reliability. To address these concerns, this study employed machine learning algorithms, specifically Linear Discriminant Analysis (LDA) and Random Forest, on Direct Analysis in Real Time time-of-flight mass spectra collected from human, cat, and dog hair samples. The objective was to develop a chemistry- and statistics-based classification method for unbiased taxonomic identification of hair. The results of the study showed that LDA and Random Forest were highly …

Teaching Reproducibility To First Year College Students: Reflections From An Introductory Data Science Course, Brennan L. Bean

Journal on Empowering Teaching Excellence

Access the online Pressbooks version of this article here.

Modern technology threatens traditional modes of classroom assessment by providing students with automated ways to write essays and take exams. At the same time, modern technology continues to expand the accessibility of computational tools that promise to increase the potential scope and quality of class projects. This paper presents a case study where students are asked to complete a “reproducible” final project in an introductory data science course using the R programming language. A reproducible project is one where an instructor can easily regenerate the results and conclusions from the submitted …

Composite Index Of Anthropometric Failure And Early Childhood Cognitive Development Based On The 2018 Indonesian Basic Health Research Data, Safira Zamrudiani, Abdul Wahab, Rosalia Kurniawati Harisaputra

Kesmas

Delays in early childhood cognitive development may have profound long-term implications on health and life expectancy. Optimal nutrition supports early life development, including a child's cognitive development. This study aimed to determine the association between the Composite Index of Anthropometric Failure and early childhood cognitive development among children aged 36-59 months in Indonesia. This cross-sectional study utilized data from the 2018 Indonesian Basic Health Research that involved 18,027 participants aged 36-59 months. This study outcome demonstrated that children who were stunted-underweight were potentially susceptible to delayed cognitive development compared to those with normal nutritional status (aOR = 1.30; 95% CI …

Editorial: The Public Health Scholars As The Health Leaders, Al Asyary, Meita Veruswati, Putri Bungsu Machmud, Indri Hapsari Susilowati

Kesmas

No abstract provided.

The Impacts Of The Covid-19 Pandemic On Mental Health Across Different Genders And Sexualities, Jiale Zhu, Jonas Katona

Undergraduate Research Journal for the Human Sciences

Current studies report an increase in psychological distress as a result of the COVID-19 pandemic. This study is interested in examining mental health disparities and how the COVID-19 pandemic has disproportionately impacted marginalized groups—and more specifically, those identified by sex, gender, and sexuality—compared with the general population. This study also considers the effects and ramifications of different policy measures taken during the course of the pandemic. We perform exploratory data modeling and analysis on several important and publicly available datasets taken during the pandemic on mental health and COVID-19 infection data across various identity groups to look for significant disparities, …

Divisibility Probabilities For Products Of Randomly Chosen Integers, Noah Y. Fine

Rose-Hulman Undergraduate Mathematics Journal

We find a formula for the probability that the product of n positive integers, chosen at random, is divisible by some integer d. We do this via an inductive application of the Chinese Remainder Theorem, generating functions, and several other combinatorial arguments. Additionally, we apply this formula to find a unique, but slow, probabilistic primality test.

Does The Design And Personalization Of Mailed Invitations Influence Online Survey Response Rates?, Brock Ternes

The SUNY Journal of the Scholarship of Engagement: JoSE

Nonresponse to online surveys has been a notable concern of survey methodologists, who continue to implement strategies and incentives to boost returns. Don Dillman’s methods emphasize tailored designs to maximize response rates, and this paper assesses how mailed notification designs and requested deadlines for completion influence online survey response rates. Using a target population of rural Kansans, this paper assesses how minor changes in printed notifications are connected to participation in an online survey. Postcards were mailed to private water well owners inviting recipients to complete a 40-item online questionnaire about their water usage; notifications varied in their personalization of …

A Model For The Multi-Virus Contact Process, Xu Huang

Rose-Hulman Undergraduate Mathematics Journal

We study one specific version of the contact process on a graph. Here, we allow multiple infections carried by the nodes and include a probability of removing nodes in a graph. The removal probability is purely determined by the number of infections the node carries at the moment when it gets another infection. In this paper, we show that on any finite graph, any positive value of infection rate $\lambda$ will result in the death of the process almost surely. In the case of $d$-regular infinite trees, We also give a lower bound on the infection rate in order for …

Decentralized Science (Desci): A New Paradigm For Diverse And Sustainable Scientific Development, Feiyue Wang, Wenwen Ding

Bulletin of Chinese Academy of Sciences (Chinese Version)

The rise of artificial intelligence for science (AI4S) has made it particularly important and urgent to ensure the openness, fairness, impartiality, diversity, and sustainability of scientific systems. This is significant to the discourse power and leadership of countries in global innovation and industrial revolution, and also affects the security, stability, and sustainable development of a community with a shared future for mankind. To address these challenges, AI4S needs to adopt new scientific organizational and operational methods. Decentralized science (DeSci) has emerged to vitalize AI4S and provide strong support, effectively addressing issues such as information silos, biases, unfair distribution, and monopolies …

Exploring Parameter Sensitivity Analysis In Mathematical Modeling With Ordinary Differential Equations, Viktoria Savatorova

CODEE Journal

This paper presents an exploration into parameter sensitivity analysis in mathematical modeling using ordinary differential equations (ODEs). Taking the first steps in understanding local sensitivity analysis through the direct differential method and global sensitivity analysis using metrics like Pearson, Spearman, PRCC, and Sobol’, we provide readers with a basic understanding of parameter sensitivity analysis for mathematical modeling using ODEs. As an illustrative application, the system of differential equations modeling population dynamics of several fish species with harvest considerations is utilized. The results of employing local and global sensitivity analysis are compared, shedding light on the strengths and limitations of each …

All-Cause And Opioid-Related Mortality Compared Between Traumatic Spinal Cord Injury And The Us General Population, Jaden Whitehead, Beatrice Ugiliweneza

The Cardinal Edge

Individuals with spinal cord injury (SCI) are susceptible to the misuse of opioids due to the introduction of these substances for pain management. There are very few studies examining the relationship between unintentional deaths caused by opioid usage following spinal cord injury. The objective of this study was to evaluate the trend of opioid-related mortality of individuals with spinal cord injury (SCI) over the years and compare these findings to the mortality rates due to opioid misuse in the general population. In this study, we used data provided by the National Spinal Cord Injury Model Systems (NSCIMS) for SCI 1999-2016 …