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COVID-19 pandemic in Baguio city, Philippines: A spatio-temporal analysis 菲律宾碧瑶市COVID-19大流行:时空分析
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092722
Karen D. Taclay, Richard J. Taclay, Wilfredo T. Dizon, R. Addawe
This article explores the clustering of COVID-19 incidences in the City of Baguio using spatio-temporal analysis. The GIS maps of the cumulative incidence rates of 129 barangays of the city were investigated in the span of ten months from March 2020 to December 2020. A thorough investigation of the CIR in the city may contribute to proper formulation and or implementation of policies to lessen the growing number of COVID-19 cases in the city. The Moran's index was used to determine significant spatial autocorrelations on the CIR before undergoing hotspot analysis. The Getis-Ord Gi∗ and Local Moran's I of QGIS were used to determine hotspots and coldspots, confirmed through the cluster and outlier analysis, respectively. The months of October and November registered clustering patterns and hotspots. The increasing number of test kits available were also considered in the analysis of the increasing COVID-19 cases in the city. Moreover, results showed that most of the incidences occurred at the center of city, that is, the business districts where most people go. It was found that cluster distribution of COVID-19 with high CIR has less than 1% likelihood to be random for the months of October 2020 and November 2020. This implies that the barangays with high CIR are significantly clustered. Hence COVID-19 protocols such as social distancing must be strictly implemented. © 2022 Author(s).
本文采用时空分析方法对碧瑶市新冠肺炎疫情的聚类情况进行了探讨。对2020年3月至2020年12月10个月期间我市129个村的累计发病率GIS图进行了调查。对我市疫情情况进行彻底调查，有助于制定和/或实施适当的政策，以减少我市日益增加的新冠肺炎病例。在进行热点分析之前，使用Moran's指数确定CIR的显著空间自相关性。利用QGIS的Getis-Ord Gi∗和Local Moran's I分别通过聚类分析和离群分析确定热点和冷点。10月和11月出现了群集模式和热点。在分析该市不断增加的COVID-19病例时，也考虑了可用检测试剂盒数量的增加。此外，研究结果表明，大多数事故发生在城市中心，即人们最多去的商业区。研究发现，2020年10月和2020年11月，高CIR的COVID-19聚集性分布随机概率小于1%。这意味着高CIR的乡村明显聚集。因此，必须严格执行社交距离等COVID-19协议。©2022作者。
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引用次数: 0
Coherent state quantization of time of arrival functions of confined and free particles 受限和自由粒子到达时间函数的相干态量子化
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092906
D. A. Romeo, Job A. Nable
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引用次数: 0
Accuracy of the Rasch rating scale person estimates using maximum likelihood approach with skewed distributions: A Markov chain Monte Carlo simulation analysis 偏斜分布下使用最大似然方法的Rasch评定量表人估计的准确性:马尔科夫链蒙特卡罗模拟分析
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092759
Nurul Hafizah Azizan, Z. Mahmud, A. Rambli
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引用次数: 0
The role of ICT development in knowledge creation and the burden of knowledge nexus: A threshold analysis 信息通信技术发展在知识创造中的作用和知识联系负担:一个阈值分析
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092765
N. Mohammad, Nur Lina Abdullah, Zuriana Zahrin, Norlaila Abdullah Cik
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引用次数: 0
Corporate social responsibility disclosure and informational quality of audit reports 企业社会责任披露与审计报告的信息质量
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0094842
Fong Yew Ong
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引用次数: 0
Can internal audit function impact artificial intelligence? Case of public listed companies of Oman 内部审计职能会影响人工智能吗?阿曼上市公司案例
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092755
Ali Rehman, Fathyah Hashim
{"title":"Can internal audit function impact artificial intelligence? Case of public listed companies of Oman","authors":"Ali Rehman, Fathyah Hashim","doi":"10.1063/5.0092755","DOIUrl":"https://doi.org/10.1063/5.0092755","url":null,"abstract":"","PeriodicalId":427046,"journal":{"name":"The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125357627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Soil analysis using diffuse reflectance infrared Fourier transform spectroscopy and partial least square model 利用漫反射红外傅立叶变换光谱和偏最小二乘模型进行土壤分析
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0100510
C. Liong, Nurul Farzana Mohamad Basri, Hafizah Mansor, S. A. Kamaruddin, Bai Qin Lee, T. T. Chin
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引用次数: 0
Modulating functions method for coefficients estimation in the sixth order generalized Boussinesq equation 六阶广义Boussinesq方程系数估计的调制函数方法
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092769
Sharefa Asiri
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引用次数: 0
A social network analysis of COVID-19 transmission in Rosales, Pangasinan, Philippines 菲律宾邦加西南州罗萨莱斯市COVID-19传播的社会网络分析
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0092746
R. Mina, R. Addawe
In this study, we use social networks to analyze the spread of Coronavirus Disease (COVID-19) in Rosales, Pangasinan, Philippines. The igraph package of the software R was used to create network graphs and analyze the node and edge attributes. The nodes represent the infected individuals, and the edges represent the directed links from sources to target patients. We apply three centrality measures: degree, closeness, and betweenness centrality, to identify patterns and characteristics of primary nodes that caused the majority of the infections in the municipality. Out of the seventy-eight cases recorded from 23 March 2020 to 27 December 2020, 42.3% are in the age range (20, 40]. The average age of infected individuals is 43 years with a standard deviation of 21. However, all the deaths occurred in older patients. Only four health workers were infected, all of whom are isolated cases. There were twenty-eight isolated cases, while the number of contacts per patient (outdegree) is 0.53. About a third of the cases have travel history from different provinces or countries, and 64.1% of them are sources of infections. Almost half of the infected individuals are symptomatic. Among the identified central cases, 70% have no travel history, and 60% are asymptomatic. This study further demonstrates the importance of effective contact tracing and isolation protocols to reduce the spread of COVID-19. © 2022 Author(s).
在本研究中，我们利用社交网络分析了菲律宾邦加西南州罗萨莱斯市冠状病毒病(COVID-19)的传播情况。利用R软件中的igraph包创建网络图，分析节点和边属性。节点表示受感染个体，边缘表示从源到目标患者的直接链接。我们应用三个中心性措施:程度，亲密度和中间中心性，以确定导致大多数感染的主要节点的模式和特征。在2020年3月23日至2020年12月27日记录的78例病例中，42.3%为年龄范围[20,40]。感染者的平均年龄为43岁，标准差为21岁。然而，所有的死亡都发生在老年患者中。只有4名卫生工作者受到感染，他们都是孤立病例。隔离病例28例，人均接触人数(外出度)0.53人。约三分之一的病例有不同省份或国家的旅行史，64.1%的病例是感染源。几乎一半的感染者有症状。在已确定的中心病例中，70%无旅行史，60%无症状。这项研究进一步证明了有效的接触者追踪和隔离方案对减少COVID-19传播的重要性。©2022作者。
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引用次数: 0
The application of chaos theory in COVID-19 data analysis 混沌理论在COVID-19数据分析中的应用
The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)
Pub Date : 1900-01-01 DOI: 10.1063/5.0093272
Nurul Umirah Mohd Fauzi, Muhammad Al-Aniq Abu Bakar, Nurul Hidayah Zolkply, Siti Hidayah Muhad Saleh, M. L. Sapini, N. M. Yusof
This research presents a study on the existence of chaotic behaviour in COVID-19 time series data using the Largest Lyapunov Exponent (LLE) and forecasts the outcome of the new daily cases of infected people until 2023 by chaos indicators tools, Logistic Map. The study also chooses another mathematical model, Linear Regression, to verify the accuracy of the Logistic Map by comparing both methods. The comparison between these methods is analyzed by using Mean Square Error (MSE). The data was collected from the end of January until early December 2020 involving Malaysia, China, Singapore, the USA and Italy. The result shows the countries tested have the existence of chaotic behaviour. Meanwhile, forecasting depicts some countries whose cases are declining and some are increasing. © 2022 Author(s).
本研究利用最大李雅普诺夫指数(LLE)对COVID-19时间序列数据中存在的混沌行为进行了研究，并利用混沌指标工具Logistic Map预测了2023年之前每日新增感染病例的结果。本研究还选择了另一种数学模型线性回归，通过比较两种方法来验证Logistic Map的准确性。采用均方误差(Mean Square Error, MSE)对两种方法进行比较分析。这些数据是从2020年1月底到12月初收集的，涉及马来西亚、中国、新加坡、美国和意大利。结果表明，被测国家存在混沌行为。与此同时，预测显示有些国家的病例正在减少，有些国家的病例正在增加。©2022作者。
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