This page has only limited features, please log in for full access.

Unclaimed
Ryan H. L. Ip
School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW 2650, Australia

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 26 August 2021 in Sustainability
Reads 0
Downloads 0

Agriculture is vital to global food production. Around 550 million smallholding households produce most of the world’s food, and many rely on livestock rearing for a living. Smallholder farms must survive and thrive to maintain and increase food production. Baseline information is vital for further extension service interventions. The goal of this Malawian study was to collect quantitative baseline data on crop and livestock production, agriproduct sales, and other indicators through a household survey, and to compare the efficacy (in terms of income) of using the concept of “Lead and Follow” farmer training programs. The baseline study survey was carried out in 44 sections of 11 extension planning areas from Malawi’s five districts (Dowa, Kasungu, Mchinji, Mzimba, and Rumphi). In total, 1131 smallholder households were interviewed. Crop production, livestock farming, and providing casual labor for others were all identified as significant sources of income for smallholders, implying that all agriproducts (the whole-farm approach) is equally important for improving smallholder livelihoods. On the one hand, the whole-farm approach should improve smallholders’ resilience regarding climate change and poverty. Lower agriproduct sales, on the other hand, indicated that links to the market were frequently poor but an increased market focus should help smallholders sell their produce at a fair margin. In terms of best practices adoption, both Lead and Follow farmers adopted similar farm practices (crops and livestock) to increase income. In general, no significant difference in income was calculated from many farm enterprises for both Lead and Follow farmers. However, the income from pigs and firewood was significantly higher for Follow farmers than for Lead farmers. Lead farmers reported significantly higher off-farm income sources. Significant changes are proposed to the “Lead farmer extension approach”.

ACS Style

Muhammad Azher Bhatti; Sosheel Solomon Godfrey; Ryan H. L. Ip; Chipo Kachiwala; Håvard Hovdhaugen; Liveness J. Banda; Moses Limuwa; Peter C. Wynn; Tormod Ådnøy; Lars Olav Eik. Diversity of Sources of Income for Smallholder Farming Communities in Malawi: Importance for Improved Livelihood. Sustainability 2021, 13, 9599 .

AMA Style

Muhammad Azher Bhatti, Sosheel Solomon Godfrey, Ryan H. L. Ip, Chipo Kachiwala, Håvard Hovdhaugen, Liveness J. Banda, Moses Limuwa, Peter C. Wynn, Tormod Ådnøy, Lars Olav Eik. Diversity of Sources of Income for Smallholder Farming Communities in Malawi: Importance for Improved Livelihood. Sustainability. 2021; 13 (17):9599.

Chicago/Turabian Style

Muhammad Azher Bhatti; Sosheel Solomon Godfrey; Ryan H. L. Ip; Chipo Kachiwala; Håvard Hovdhaugen; Liveness J. Banda; Moses Limuwa; Peter C. Wynn; Tormod Ådnøy; Lars Olav Eik. 2021. "Diversity of Sources of Income for Smallholder Farming Communities in Malawi: Importance for Improved Livelihood." Sustainability 13, no. 17: 9599.

Journal article
Published: 13 July 2021 in International Journal of Environmental Research and Public Health
Reads 0
Downloads 0

In handling the COVID-19 pandemic, various mitigation policies aiming at slowing the spread and protecting all individuals, especially the vulnerable ones, were implemented. A careful evaluation of the effectiveness of these policies is necessary so that policy-makers can implement informed decisions if another wave of COVID-19 or another pandemic happens in the future. This paper reports an assessment of some policies introduced by the Australian governments using a generalised space-time autoregressive model which incorporates multiple exogenous variables and delay effects. Our results show that the number of daily new cases from the states and territories are influenced by both temporal and spatial aspects. Business and border restrictions are found helpful in reducing the number of new cases a few days after implementation while gathering restrictions may not be effective.

ACS Style

Ryan Ip; Dmitry Demskoi; Azizur Rahman; Lihong Zheng. Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models. International Journal of Environmental Research and Public Health 2021, 18, 7474 .

AMA Style

Ryan Ip, Dmitry Demskoi, Azizur Rahman, Lihong Zheng. Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models. International Journal of Environmental Research and Public Health. 2021; 18 (14):7474.

Chicago/Turabian Style

Ryan Ip; Dmitry Demskoi; Azizur Rahman; Lihong Zheng. 2021. "Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models." International Journal of Environmental Research and Public Health 18, no. 14: 7474.

Journal article
Published: 13 May 2021 in Information Sciences
Reads 0
Downloads 0

The foremost requirement for a decision forest to achieve better ensemble accuracy is building a set of accurate and diverse individual decision trees as base classifiers. Existing decision forest algorithms mainly differ from each other on how they induce diversity among the decision trees. At the same time, most of the drawbacks of existing algorithms originate from their induction processes of diversity. In this paper, we propose a new decision forest algorithm that is more balanced through effective synchronization between different sources of diversity. The proposed algorithm is balanced theoretically and empirically. We carried out experiments on 25 well-known data sets that are publicly available from the UCI Machine Learning Repository, to perform an extensive empirical evaluation. The experimental results indicate that the proposed algorithm has the best average ensemble accuracy rank of 1.8 compared to its closest competitor at 3.5. Using the Friedman and Bonferroni-Dunn tests, we also show that such an improvement is indeed statistically significant. In addition, the proposed algorithm is found to be competitive in terms of complexity and other relevant parameters.

ACS Style

Nasim Adnan; Ryan H.L. Ip; Michael Bewong; Zahidul Islam. BDF: A new decision forest algorithm. Information Sciences 2021, 569, 687 -705.

AMA Style

Nasim Adnan, Ryan H.L. Ip, Michael Bewong, Zahidul Islam. BDF: A new decision forest algorithm. Information Sciences. 2021; 569 ():687-705.

Chicago/Turabian Style

Nasim Adnan; Ryan H.L. Ip; Michael Bewong; Zahidul Islam. 2021. "BDF: A new decision forest algorithm." Information Sciences 569, no. : 687-705.

Journal article
Published: 18 April 2021 in Agriculture
Reads 0
Downloads 0

The resilience and profitability of livestock production in many countries can be impacted by shocks, such as drought and market shifts, especially under high debt levels. For farmers to remain profitable through such uncertainty, there is a need to understand and predict a farming business’s ability to withstand and recover from such shocks. This research demonstrates the use of biophysical modelling linked with copula and Monte Carlo simulation techniques to predict the risks faced by a typical wool and meat lamb enterprise in South-Eastern Australia, given the financial impacts of different debt levels on a farming business’s profitability and growth in net wealth. The study tested five starting gearing scenarios, i.e., debt to equity (D:E) ratios to define a farm’s financial risk profiles, given weather and price variations over time. Farms with higher gearing are increasingly worse off, highlighting the implications of debt accumulating over time due to drought shocks. In addition to business risk, financial risk should be included in the analyses and planning of farm production to identify optimal management strategies better. The methods described in this paper enable the extension of production simulation to include the farmer’s management information to determine financial risk profiles and guide decision making for improved business resilience.

ACS Style

Sosheel Godfrey; Thomas Nordblom; Ryan Ip; Susan Robertson; Timothy Hutchings; Karl Behrendt. Drought Shocks and Gearing Impacts on the Profitability of Sheep Farming. Agriculture 2021, 11, 366 .

AMA Style

Sosheel Godfrey, Thomas Nordblom, Ryan Ip, Susan Robertson, Timothy Hutchings, Karl Behrendt. Drought Shocks and Gearing Impacts on the Profitability of Sheep Farming. Agriculture. 2021; 11 (4):366.

Chicago/Turabian Style

Sosheel Godfrey; Thomas Nordblom; Ryan Ip; Susan Robertson; Timothy Hutchings; Karl Behrendt. 2021. "Drought Shocks and Gearing Impacts on the Profitability of Sheep Farming." Agriculture 11, no. 4: 366.

Research article
Published: 12 November 2020 in Acta Agriculturae Scandinavica, Section A - Animal Science
Reads 0
Downloads 0

Although Norway is the largest sheep meat producer in Scandinavia and Norwegian Muslims are expected to double in population in the next decade, the overall local per capita red meat consumption is still low. Meanwhile, Norwegian Muslims’ purchasing preferences on lamb meat products have not been investigated. This paper presents the results of a choice-based conjoint survey which would help stakeholders to understand the niche Muslim immigrant halal meat market and potentially increase meat consumption. Post-hoc market segmentation was performed using latent class analysis, and factors affecting consumers’ purchase intentions were studied within each segment. Results show that purchasing halal meat from a butcher was the top preference while there was a higher willingness to purchase from national supermarkets among younger second-generation Pakistanis. In order to benefit from niche halal meat market, Norwegian supermarkets are recommended to adapt some of the services that halal butchers are offering to their consumers.

ACS Style

Muhammad Azher Bhatti; Sosheel Solomon Godfrey; Ryan H. L. Ip; Mari Øvrum Gaarder; Shakar Aslam; Geir Steinheim; Peter Wynn; David L. Hopkins; Reinert Horneland; Lars Olav Eik; Tormod Ådnøy. An exploratory study of Muslim consumers’ halal meat purchasing intentions in Norway. Acta Agriculturae Scandinavica, Section A - Animal Science 2020, 70, 61 -70.

AMA Style

Muhammad Azher Bhatti, Sosheel Solomon Godfrey, Ryan H. L. Ip, Mari Øvrum Gaarder, Shakar Aslam, Geir Steinheim, Peter Wynn, David L. Hopkins, Reinert Horneland, Lars Olav Eik, Tormod Ådnøy. An exploratory study of Muslim consumers’ halal meat purchasing intentions in Norway. Acta Agriculturae Scandinavica, Section A - Animal Science. 2020; 70 (1):61-70.

Chicago/Turabian Style

Muhammad Azher Bhatti; Sosheel Solomon Godfrey; Ryan H. L. Ip; Mari Øvrum Gaarder; Shakar Aslam; Geir Steinheim; Peter Wynn; David L. Hopkins; Reinert Horneland; Lars Olav Eik; Tormod Ådnøy. 2020. "An exploratory study of Muslim consumers’ halal meat purchasing intentions in Norway." Acta Agriculturae Scandinavica, Section A - Animal Science 70, no. 1: 61-70.

Short communication
Published: 19 August 2019 in Statistics & Probability Letters
Reads 0
Downloads 0

Markov random field (MRF) is commonly used in modelling spatially dependent data. These models are often referred to as auto-models. While univariate auto-models have been extensively studied in the literature, discrete multivariate MRF has not attracted much attention. This paper attempts to fill the research gap by providing some results on the discrete multivariate MRF scheme, which forms the theoretical foundation to construct models for spatially dependent categorical data. The results presented in this paper allow the formulation of a novel auto-model and justify the validity of the recently proposed auto-multinomial model.

ACS Style

Ryan H.L. Ip; K.Y.K. Wu. A note on discrete multivariate Markov random field models. Statistics & Probability Letters 2019, 156, 108588 .

AMA Style

Ryan H.L. Ip, K.Y.K. Wu. A note on discrete multivariate Markov random field models. Statistics & Probability Letters. 2019; 156 ():108588.

Chicago/Turabian Style

Ryan H.L. Ip; K.Y.K. Wu. 2019. "A note on discrete multivariate Markov random field models." Statistics & Probability Letters 156, no. : 108588.

Journal article
Published: 01 April 2019 in Addiction Science & Clinical Practice
Reads 0
Downloads 0

A substantial increase in substance treatment episodes for methamphetamine problems suggests characteristics of the treatment population could have changed and that targeted treatment programs are required. To determine who methamphetamine treatment should be designed for this study has two aims. First, to empirically describe changes in amphetamine treatment presentations to a rural NSW drug and alcohol treatment agency over time. Second, to examine how these characteristics may affect the likelihood of being treated for amphetamines compared to other drugs. The Australian Alcohol and Other Drug Treatment Services National Minimum Data Set (AODTS-NMDS) containing closed treatment episodes from a single agency from three time periods was used. Characteristics of people receiving amphetamine treatments in these three periods were compared and the effects of these characteristics on the odds of being treated for amphetamine were estimated using a logistic regression model. The characteristics utilised in the analysis include age, sex, Indigenous status, usual accommodation, living arrangement, source of referral and source of income. The proportion of amphetamine treatment episodes doubled from 2006/2007 to 2015/2016 and overtook alcohol as the most commonly treated principal drug of concern. The estimated proportion of amphetamine treatments showed an increment across all ages and for men and women. It was found that younger people, women, people in temporary accommodation or homeless, people who were self-referred and people whose main source of income was not through employment are more likely to be treated for amphetamine use. Significant changes over time in the age, sex and Indigenous status of people receiving treatment for amphetamine as the principal drug of concern requires service delivery to match demand from younger people, particularly women; and Indigenous people. The needs and preferences for treatment of younger women who use amphetamine will be important factors in treatment planning service providers who are more used to providing treatment for young men who use cannabis and older men who use alcohol. Further research on women’s experiences in treatment and outcomes would be useful for informing treatment practices.

ACS Style

Julaine Allan; Ryan H. L. Ip; Michael Kemp; Nicole Snowdon. Increased demand for amphetamine treatment in rural Australia. Addiction Science & Clinical Practice 2019, 14, 13 .

AMA Style

Julaine Allan, Ryan H. L. Ip, Michael Kemp, Nicole Snowdon. Increased demand for amphetamine treatment in rural Australia. Addiction Science & Clinical Practice. 2019; 14 (1):13.

Chicago/Turabian Style

Julaine Allan; Ryan H. L. Ip; Michael Kemp; Nicole Snowdon. 2019. "Increased demand for amphetamine treatment in rural Australia." Addiction Science & Clinical Practice 14, no. 1: 13.

Conference paper
Published: 16 February 2019 in Communications in Computer and Information Science
Reads 0
Downloads 0

With the increasing availability and trendiness of “big data”, data science has become a fast growing discipline. Data analysis techniques are shifting from classical statistical inferences to algorithmic machine learnings. Will the rise of data science lead to the fall of statistics? If education is the key to defend statistics as a discipline, what should statisticians teach to respond to the challenges brought by big data? This paper aims to provide the current situation of data science and statistics programs within the higher education sector in Australia and some personal thoughts on statistics education in this era.

ACS Style

Ryan H. L. Ip. The Role of Statistics Education in the Big Data Era. Communications in Computer and Information Science 2019, 281 -288.

AMA Style

Ryan H. L. Ip. The Role of Statistics Education in the Big Data Era. Communications in Computer and Information Science. 2019; ():281-288.

Chicago/Turabian Style

Ryan H. L. Ip. 2019. "The Role of Statistics Education in the Big Data Era." Communications in Computer and Information Science , no. : 281-288.

Research article
Published: 01 January 2019 in Crop and Pasture Science
Reads 0
Downloads 0

Charles Sturt University has operated a commercial herbicide resistance testing service since 1991, following a random survey of the South West Slopes region of New South Wales that identified significant incidence of herbicide resistance in annual ryegrass (Lolium rigidum Gaud.). Other surveys of cropping regions of southern Australia conducted at that time also found a significant incidence of resistance. In the subsequent 25-year period, the testing service has received samples from the majority of the southern Australian cropping belt. Overall, 80% of samples tested were resistant to acetyl-CoA carboxylase (ACCase) inhibiting aryloxyphenoxypropionate and phenylpyrazole herbicides, 56% to acetolactate synthase (ALS) inhibiting herbicides, and 24% to ACCase-inhibiting cyclohexanedione herbicides. The incidences of resistance to inhibitors of photosynthesis at PSII, tubulin-formation inhibitors, and 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase inhibiting herbicides have remained <10% of samples tested. The relationships between many herbicide groups and subgroups are discussed, as is the variability in resistance incidence and the forms of cross or multiple resistance for each state. This paper builds on an earlier publication of 14 years of testing history. At >5000 samples, the size and geographical spread of this dataset allows for valuable analyses of the relationships present in herbicide-resistant populations of annual ryegrass.

ACS Style

J. C. Broster; J. E. Pratley; R. H. L. Ip; Li-Minn Ang; K. P. Seng. A quarter of a century of monitoring herbicide resistance in Lolium rigidum in Australia. Crop and Pasture Science 2019, 70, 283 -293.

AMA Style

J. C. Broster, J. E. Pratley, R. H. L. Ip, Li-Minn Ang, K. P. Seng. A quarter of a century of monitoring herbicide resistance in Lolium rigidum in Australia. Crop and Pasture Science. 2019; 70 (3):283-293.

Chicago/Turabian Style

J. C. Broster; J. E. Pratley; R. H. L. Ip; Li-Minn Ang; K. P. Seng. 2019. "A quarter of a century of monitoring herbicide resistance in Lolium rigidum in Australia." Crop and Pasture Science 70, no. 3: 283-293.

Research article
Published: 01 January 2019 in Crop and Pasture Science
Reads 0
Downloads 0

Herbicide resistance is a common occurrence in southern Australia. The evolution of herbicide resistance is influenced by the selection pressure placed on the weed species controlled by that herbicide. Results from resistance screening of ~4500 annual ryegrass (Lolium rigidum Gaud.) samples were entered in a GIS database, together with several agricultural parameters used in the Australian Bureau of Statistics Agricultural Surveys. This allowed a study of the associations between mode of action of resistance, geographic distribution of resistance across southern Australia, and farming practices employed in particular regions. Cultivation was negatively associated with resistances in acetyl-CoA carboxylase (ACCase)-inhibiting cyclohexanedione and acetolactate synthase (ALS)-inhibiting herbicides. Higher proportions of wheat sown were associated with higher incidences of resistance. ACCase-inhibiting aryloxyphenoxypropionate and cyclohexanedione and ALS-inhibiting resistances were higher in those shires where soils were predominantly acidic. This study demonstrates the association between farm practice and the evolution of herbicide resistance. The analysis provides reinforcement to the principle of rotating chemical modes of action with non-chemical weed control measures to minimise the risk of herbicide resistance evolution in any farming system.

ACS Style

J. C. Broster; J. E. Pratley; R. H. L. Ip; Li-Minn Ang; K. P. Seng. Cropping practices influence incidence of herbicide resistance in annual ryegrass (Lolium rigidum) in Australia. Crop and Pasture Science 2019, 70, 77 .

AMA Style

J. C. Broster, J. E. Pratley, R. H. L. Ip, Li-Minn Ang, K. P. Seng. Cropping practices influence incidence of herbicide resistance in annual ryegrass (Lolium rigidum) in Australia. Crop and Pasture Science. 2019; 70 (1):77.

Chicago/Turabian Style

J. C. Broster; J. E. Pratley; R. H. L. Ip; Li-Minn Ang; K. P. Seng. 2019. "Cropping practices influence incidence of herbicide resistance in annual ryegrass (Lolium rigidum) in Australia." Crop and Pasture Science 70, no. 1: 77.

Journal article
Published: 01 August 2018 in Computers and Electronics in Agriculture
Reads 0
Downloads 0

Crop protection is the science and practice of managing plant diseases, weeds and other pests. Weed management and control are important given that crop yield losses caused by pests and weeds are high. However, farmers face increased complexity of weed control due to evolved resistance to herbicides. This paper first presents a brief review of some significant research efforts in crop protection using Big data with the focus on weed control and management followed by some potential applications. Some machine learning techniques for Big data analytics are also reviewed. The outlook for Big data and machine learning in crop protection is very promising. The potential of using Markov random fields (MRF) which takes into account the spatial component among neighboring sites for herbicide resistance modeling of ryegrass is then explored. To the best of our knowledge, no similar work of modeling herbicide resistance using the MRF has been reported. Experiments and data analytics have been performed on data collected from farms in Australia. Results have revealed the good performance of our approach.

ACS Style

Ryan H.L. Ip; Li-Minn Ang; Kah Phooi Seng; John Broster; J.E. Pratley. Big data and machine learning for crop protection. Computers and Electronics in Agriculture 2018, 151, 376 -383.

AMA Style

Ryan H.L. Ip, Li-Minn Ang, Kah Phooi Seng, John Broster, J.E. Pratley. Big data and machine learning for crop protection. Computers and Electronics in Agriculture. 2018; 151 ():376-383.

Chicago/Turabian Style

Ryan H.L. Ip; Li-Minn Ang; Kah Phooi Seng; John Broster; J.E. Pratley. 2018. "Big data and machine learning for crop protection." Computers and Electronics in Agriculture 151, no. : 376-383.

Journal article
Published: 01 November 2017 in Statistics & Probability Letters
Reads 0
Downloads 0
ACS Style

Ryan H.L. Ip; W.K. Li. A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields. Statistics & Probability Letters 2017, 130, 115 -119.

AMA Style

Ryan H.L. Ip, W.K. Li. A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields. Statistics & Probability Letters. 2017; 130 ():115-119.

Chicago/Turabian Style

Ryan H.L. Ip; W.K. Li. 2017. "A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields." Statistics & Probability Letters 130, no. : 115-119.

Journal article
Published: 01 January 2017 in Statistica Sinica
Reads 0
Downloads 0
ACS Style

Ryan H.L. Ip; W.K. Li. ON SOME MATÉRN COVARIANCE FUNCTIONS FOR SPATIO-TEMPORAL RANDOM FIELDS. Statistica Sinica 2017, 1 .

AMA Style

Ryan H.L. Ip, W.K. Li. ON SOME MATÉRN COVARIANCE FUNCTIONS FOR SPATIO-TEMPORAL RANDOM FIELDS. Statistica Sinica. 2017; ():1.

Chicago/Turabian Style

Ryan H.L. Ip; W.K. Li. 2017. "ON SOME MATÉRN COVARIANCE FUNCTIONS FOR SPATIO-TEMPORAL RANDOM FIELDS." Statistica Sinica , no. : 1.

Conference paper
Published: 08 September 2016 in Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing 2016
Reads 0
Downloads 0
ACS Style

Ahmed Al-Humairi; XiaoMing Zheng; Ryan H.L. Ip; Bilal El Masoud. Computed Tomography Image Quality Evaluation for pre-surgical dental implant site assessment using Different Exposure Setting Protocols: Mandibular Phantom Study. Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing 2016 2016, 300 -305.

AMA Style

Ahmed Al-Humairi, XiaoMing Zheng, Ryan H.L. Ip, Bilal El Masoud. Computed Tomography Image Quality Evaluation for pre-surgical dental implant site assessment using Different Exposure Setting Protocols: Mandibular Phantom Study. Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing 2016. 2016; ():300-305.

Chicago/Turabian Style

Ahmed Al-Humairi; XiaoMing Zheng; Ryan H.L. Ip; Bilal El Masoud. 2016. "Computed Tomography Image Quality Evaluation for pre-surgical dental implant site assessment using Different Exposure Setting Protocols: Mandibular Phantom Study." Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing 2016 , no. : 300-305.

Journal article
Published: 01 August 2016 in Spatial Statistics
Reads 0
Downloads 0
ACS Style

Ryan H.L. Ip; W.K. Li. Matérn cross-covariance functions for bivariate spatio-temporal random fields. Spatial Statistics 2016, 17, 22 -37.

AMA Style

Ryan H.L. Ip, W.K. Li. Matérn cross-covariance functions for bivariate spatio-temporal random fields. Spatial Statistics. 2016; 17 ():22-37.

Chicago/Turabian Style

Ryan H.L. Ip; W.K. Li. 2016. "Matérn cross-covariance functions for bivariate spatio-temporal random fields." Spatial Statistics 17, no. : 22-37.

Conference paper
Published: 01 January 2016 in Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling
Reads 0
Downloads 0
ACS Style

Ahmed Al-Humairi; XiaoMing Zheng; Ryan H.L. Ip; Bilal El Masoud. Radiation Dose Image Quality Optomization in Dental Implantalogy. Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling 2016, 1 .

AMA Style

Ahmed Al-Humairi, XiaoMing Zheng, Ryan H.L. Ip, Bilal El Masoud. Radiation Dose Image Quality Optomization in Dental Implantalogy. Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling. 2016; ():1.

Chicago/Turabian Style

Ahmed Al-Humairi; XiaoMing Zheng; Ryan H.L. Ip; Bilal El Masoud. 2016. "Radiation Dose Image Quality Optomization in Dental Implantalogy." Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling , no. : 1.

Journal article
Published: 01 November 2015 in Spatial Statistics
Reads 0
Downloads 0

In this paper, we introduce valid parametric covariance models for univariate and multivariate spatio-temporal random fields. In contrast to the traditional models, we allow the model parameters to vary over time. Since variables in applications usually exhibit seasonality or changes in dependency structures, the allowance of varying parameters would be beneficial in terms of improving model flexibility. Conditions in constructing valid covariance models and discussions on practical implementation will be provided. As an application, a set of air pollution data observed from a monitoring network will be modeled. It is found that the time varying model performs better in prediction compared with the traditional models. © 2015 Elsevier Ltd.postprin

ACS Style

Ryan H.L. Ip; W.K. Li. Time varying spatio-temporal covariance models. Spatial Statistics 2015, 14, 269 -285.

AMA Style

Ryan H.L. Ip, W.K. Li. Time varying spatio-temporal covariance models. Spatial Statistics. 2015; 14 ():269-285.

Chicago/Turabian Style

Ryan H.L. Ip; W.K. Li. 2015. "Time varying spatio-temporal covariance models." Spatial Statistics 14, no. : 269-285.

Evaluation study
Published: 08 August 2013 in Marine Pollution Bulletin
Reads 0
Downloads 0

Large scale environmental remediation projects applied to sea water always involve large amount of capital investments. Rigorous effectiveness evaluations of such projects are, therefore, necessary and essential for policy review and future planning. This study aims at investigating effectiveness of environmental remediation using three different Seemingly Unrelated Regression (SUR) time series models with intervention effects, including Model (1) assuming no correlation within and across variables, Model (2) assuming no correlation across variable but allowing correlations within variable across different sites, and Model (3) allowing all possible correlations among variables (i.e., an unrestricted model). The results suggested that the unrestricted SUR model is the most reliable one, consistently having smallest variations of the estimated model parameters. We discussed our results with reference to marine water quality management in Hong Kong while bringing managerial issues into consideration.

ACS Style

Ryan H.L. Ip; W.K. Li; Kenneth M.Y. Leung. Seemingly unrelated intervention time series models for effectiveness evaluation of large scale environmental remediation. Marine Pollution Bulletin 2013, 74, 56 -65.

AMA Style

Ryan H.L. Ip, W.K. Li, Kenneth M.Y. Leung. Seemingly unrelated intervention time series models for effectiveness evaluation of large scale environmental remediation. Marine Pollution Bulletin. 2013; 74 (1):56-65.

Chicago/Turabian Style

Ryan H.L. Ip; W.K. Li; Kenneth M.Y. Leung. 2013. "Seemingly unrelated intervention time series models for effectiveness evaluation of large scale environmental remediation." Marine Pollution Bulletin 74, no. 1: 56-65.