The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)最新文献

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A survival analysis of COVID-19 cases for Bah cluster in Malaysia 马来西亚Bah聚集性COVID-19病例生存分析

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092650

Nazrina Aziz, N. Zainalabidin, Nor Jannih Saukani, Kaveen Dameon Mahendran, Nurshahirah Samihah Shamsudinan

In 2019, SARS-CoV-2, a newly detected coronavirus, has shocked the world. The virus is affecting the human respiratory system. This disease has been called COVID-19 by the World Health Organization. The outbreak originated from Wuhan City, Hubei Province, China, that emerge in December 2019. By March 2020, the disease had spread to nations around the world. The Bah cluster is one of the COVID-19 cases clusters in Malaysia. The purpose of this study is to perform a survival analysis in order to determine the regional and cluster-based variability in survivorship of Bah cluster. The time frame for this analysis is 13 weeks started from 1st October to 30th December 2020. Kaplan Meier Estimator and K-Log rank test were used in this study. According to region, Labuan shows the lowest regional survival rate and the K-Log rank test result indicates that there is a significant difference in regional survival curves. For Bah cluster, Bah Manggis has the lowest survival rate for cluster-based survival. K-Log-rank also indicates that there are significant differences in cluster-based survival curves. SMR was calculated to estimate the relative risk of the Bah cluster in Malaysia. Later, disease mapping has been developed based on SMR value to visualize and differentiate between high and low-risk among region in Bah cluster. © 2022 Author(s).

2019年，新发现的冠状病毒SARS-CoV-2震惊了世界。这种病毒正在影响人类的呼吸系统。这种疾病被世界卫生组织称为COVID-19。疫情起源于中国湖北省武汉市，于2019年12月出现。到2020年3月，这种疾病已蔓延到世界各国。巴哈群集是马来西亚的COVID-19病例群集之一。本研究的目的是进行生存分析，以确定Bah集群的区域和基于集群的生存变异性。该分析的时间框架为13周，从2020年10月1日至12月30日。本研究采用Kaplan Meier估计和K-Log秩检验。从区域来看，纳闽岛的区域存活率最低，K-Log秩检验结果表明，区域生存曲线存在显著差异。对于Bah集群，Bah Manggis在集群生存中存活率最低。K-Log-rank也表明基于聚类的生存曲线存在显著差异。计算SMR来估计马来西亚Bah集群的相对风险。后来，基于SMR值的疾病制图被开发出来，以可视化和区分Bah集群区域的高、低风险。©2022作者。

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引用次数: 0

Wing sequence construction from half butterfly method 用半蝴蝶法构建翅膀序列

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092651

S. Karim, H. Ibrahim, Maizon Mohd Darus

引用次数: 0

Stock return volatility during SARS and COVID-19: Comparison between Malaysia and China's stock markets SARS和COVID-19期间股票收益波动:马来西亚和中国股票市场的比较

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092822

S. R. Hamzah, Azah Syafinaz Azhar, N. Ishak, Ahmad Fadly Nurullah Raseedee

This study analyses return volatility for Malaysia and China's stock markets during the SARS and COVID-19 pandemics. Stock return volatility is estimated using GARCH family models (GARCH (1,1), TGARCH and EGARCH). Generally, GARCH (1,1) estimates symmetric conditions, whereas TGARCH and EGARCH estimate the asymmetric condition or leverage effect of return volatility. Stock return volatility in China and Malaysia are then compared to assess the severity of pandemic cases during the study period. Post pandemic, Malaysia is seen to experience higher decrements in leverage effect when using the TGARCH model. Conversely, the effect is higher for China when using the EGARCH model for the SARS pandemic. To aid in predicting future return volatility after the COVID-19 pandemic, return volatility after the SARS pandemic is forecast, with the forecast value serving as the basis for evaluating the error using the mean absolute error (MAE), root mean square error (RMSE) and Theil inequality coefficient (TIC) approaches. The forecast error performance is ranked to identify outperforming GARCH family models for the pandemic period: the TGARCH model for China's stock market but the GARCH model for Malaysia's stock market. © 2022 Author(s).

本研究分析了SARS和COVID-19大流行期间马来西亚和中国股市的回报波动性。使用GARCH族模型(GARCH (1,1)， TGARCH和EGARCH)估计股票收益波动率。一般来说，GARCH(1,1)估计对称条件，而TGARCH和EGARCH估计不对称条件或收益波动的杠杆效应。然后比较中国和马来西亚的股票回报波动性，以评估研究期间大流行病例的严重程度。大流行后，马来西亚在使用TGARCH模型时，杠杆效应下降幅度较大。相反，当使用EGARCH模型预测SARS大流行时，对中国的影响更大。为了预测新冠肺炎大流行后的未来收益波动率，对SARS大流行后的收益波动率进行了预测，并利用平均绝对误差(MAE)、均方根误差(RMSE)和泰尔不等式系数(TIC)方法，将预测值作为误差评估的依据。对预测误差表现进行排序，以确定在大流行期间表现较好的GARCH家族模型:中国股市的TGARCH模型和马来西亚股市的GARCH模型。©2022作者。

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引用次数: 0

Hybrid restarting-Lanczos-SVR for solving high dimensions of PDE engineering problems 混合重启- lanczos - svr解决高维PDE工程问题

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092775

Rehana Thalib, M. Bakar

引用次数: 0

Iteration functions for complex solutions of cubic polynomial equations 三次多项式方程复解的迭代函数

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0093099

Enrico M. Yambao, M. Decena

引用次数: 0

Cluster detection for spatio-temporal dengue cases at Selangor districts using multi-EigenSpot algorithm 基于多特征点算法的雪兰莪地区登革热病例时空聚类检测

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092761

Nurul Husna Mohd Nor, H. Daud, Sami Ullah

Detecting clusters for spatio-temporal cases are becoming important to help hotspots detection for any seasonal outbreaks' cases such as dengue, covid-19, malaria etc. Cluster detection is classified into three types of clustering groups, which are spatial clustering, temporal clustering, and spatio-temporal clustering. In this study, spatio-temporal clustering is carried out to dengue datasets that were obtained from the Ministry of Health (MoH), Malaysia. Generally, the datasets were analyzed based on dengue cases reported for Selangor districts in years 2009 until 2013 to detect abnormal regions between the study areas. In health organization and epidemiology sectors, detection of cluster disease plays an important role to understand disease etiology and improve public health interventions strategy. Parametric assumptions commonly implemented in most of algorithm in cluster detections. However, the main limitation of the parametric assumptions are restrictions on the datasets' quality and type of clusters shapes. This study aims to detect the spatio-temporal clustering or hotspot regions of dengue cases for the districts of Selangor, Malaysia using a nonparametric algorithm (Multi-EigenSpot) to detect dengue clusters. The algorithm was deployed to the datasets using MATLAB software. This study has found that the most likely clusters were detected more efficiently when the algorithm removed the low-risk regions and low-risk time-point during scanning window search to avoid any false detection clusters. Different scope of clustering and geometric form of scanning window has significant contribution to the detected clusters. The finding in this study indicates that Petaling district is the most likely clusters which contributed the most of the reported dengue cases in Malaysia. © 2022 Author(s).

对时空病例的聚集性检测对于帮助热点地区发现任何季节性疫情(如登革热、covid-19、疟疾等)变得越来越重要。聚类检测分为空间聚类、时间聚类和时空聚类三种聚类类型。在本研究中，对马来西亚卫生部(MoH)获得的登革热数据集进行了时空聚类。总的来说，根据2009年至2013年雪兰莪地区报告的登革热病例对数据集进行分析，以发现研究区域之间的异常区域。在卫生组织和流行病学部门，聚集性疾病的检测对了解疾病病因和改进公共卫生干预策略具有重要作用。参数假设是聚类检测中常用的算法。然而，参数假设的主要限制是对数据集质量和聚类形状类型的限制。本研究旨在利用非参数算法(Multi-EigenSpot)检测马来西亚雪兰莪地区登革热病例的时空聚类或热点区域。利用MATLAB软件对该算法进行了实际应用。本研究发现，当算法在扫描窗口搜索过程中去除低风险区域和低风险时间点时，可以更有效地检测到最可能的聚类，以避免错误的检测聚类。不同的聚类范围和扫描窗口的几何形式对检测到的聚类有显著的贡献。本研究结果表明，Petaling区最有可能是马来西亚报告登革热病例最多的聚集性病例。©2022作者。

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引用次数: 0

Perception on Malaysia fundmyhome crowdfunding initiative for affordable housing 对马来西亚集资myhome计划的看法

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092730

Nurul Faziera Khairul Adlee, M. Misiran, Zahayu Md. Yusof, Hasimah Sapiri, N. Amit

引用次数: 0

Physical distancing evaluation for classroom layout management during COVID-19 pandemic era COVID-19大流行时期教室布局管理的物理距离评估

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092821

M. Nawawi, Ruzelan Khalid, Aida Mauziah Benjamin, A. Wibowo, Amalia Zahra

Mass gathering has been identified as one of the causes of fast-spreading of COVID-19. Physical distancing practices and large gathering control in Malaysia and all over the world are likely to be continued until the end of the year, even after Movement Control Order (MCO) has been lifted. This has imposed event organizers to redesign their events into virtual events where attendees are to stay at their houses and meet with the host and other attendees virtually. However, certain types of educational events or activities such as practical and hands-on classes are not to be virtually conducted as it by nature carries a competency for the students. This paper evaluates the standard classroom layout by comparing with optimal layout based on circle packing problem (CPP) solution. CPP solution is used to optimize the physical distancing-constrained for the student seat layout as in it happens in real life. The findings can provide an effective exit strategy for Malaysia to deal with this COVID-19 pandemic or other pandemics in the future. © 2022 Author(s).

大规模聚集已被确定为COVID-19快速传播的原因之一。即使解除了行动管制令，马来西亚和世界各地的物理距离和大型集会控制措施可能会持续到年底。这迫使活动组织者将他们的活动重新设计为虚拟活动，参与者将呆在他们的家里，与主持人和其他参与者虚拟会面。然而，某些类型的教育事件或活动，如实践和动手类，不能虚拟地进行，因为它本质上是对学生的能力的一种考验。通过与基于圆形布局问题(CPP)的最优布局的比较，对标准教室布局进行了评价。CPP解决方案用于优化物理距离约束的学生座位布局，就像在现实生活中发生的那样。研究结果可以为马来西亚应对2019冠状病毒病大流行或未来其他大流行提供有效的退出策略。©2022作者。

引用次数: 0

A systematic literature review on the agricultural technology adoption decision among Asian farmers 亚洲农民农业技术采用决策的系统文献综述

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0092882

Mohd Harith Jalil, M. M. Mohamad, Mohd Ikram A. Hamid

引用次数: 1

Prioritising the preference criteria for an internship undergraduate programme based on gender differences: An application of analytical hierarchy process 基于性别差异的本科实习项目优先选择标准:层次分析法的应用

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)

Pub Date : 1900-01-01 DOI: 10.1063/5.0093030

Azatuliffah Alwi, N. Z. Abidin, Z. Hashim, Norul Shahera Yahya

引用次数: 0

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The 5th Innovation and Analytics Conference &amp; Exhibition (IACE 2021)最新文献

The 5th Innovation and Analytics Conference & Exhibition (IACE 2021)最新文献