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Towards explicit representation of an artificial neural network model: Comparison of two artificial neural network rule extraction approaches

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Petroleum 2020年第4期6卷 329-339页

作者： Veronica K.H.chan christine W.chan Energy Informatics Laboratory Faculty of Engineering and Applied ScienceUniversity of ReginaReginaSK S4S 0A2Canada

In the quest for interpretable models,two versions of a neural network rule extraction algorithm were proposed and *** two algorithms are called the Piece-Wise Linear Artificial Neural Network(PWL-ANN)and enhanced Piece-Wise Linear Artificial Neural Network(enhanced PWL-ANN)*** PWL-ANN algorithm is a decomposition artificial neural network(ANN)rule extraction algorithm,and the enhanced PWL-ANN algorithm improves upon the PWL-ANN algorithm and extracts multiple linear regression equations from a trained ANN model by approximating the hidden sigmoid activation functions using N-piece linear *** doing so,the algorithm provides interpretable models from the originally trained opaque ANN models.A detailed application case study illustrates how the generated enhanced-PWL-ANN models can provide understandable IF-THEN rules about a problem *** of the results generated by the two versions of the PWL-ANN algorithm showed that in comparison to the PWL-ANN models,the enhanced-PWL-ANN models support improved fidelities to the originally trained ANN *** results also showed that more concise rule sets could be generated using the enhanced-PWL-ANN *** a more simplified set of rules is desired,the enhanced-PWL-ANN algorithm can be combined with the decision tree *** application of the algorithms to domains related to petroleum engineering can help enhance understanding of the problems.

关键词： Artificial neural networks Rule extraction Regression problem Algorithm design

Recent progress and new developments of applications of artificial intelligence (AI), knowledge-based systems (KBS), and Machine Learning (ML) in the petroleum industry

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Petroleum 2020年第4期6卷 I0001-I0002页

作者： Paitoon(PT)Tontiwachwuthikul christine W.chan Fanhua(Bill)Zeng Zhiwu(Henry)Liang Teerawat Sema Chao Min Canadian Academy of Engineering(FCAE) Clean Energy Technologies Research Institute(CETRi)University of ReginaSKCanada Canadian Academy of Engineering(FCAE) Canada Research Chair Tier I in Energy and Environmental Informatics(2006-2020)Energy Informatics LaboratoryUniversity of ReginaSKCanada Faculty of Graduate Studies and Research University of ReginaSKCanada Joint International Center for CO2 Capture&Storage(iCCS) Hunan UniversityChangshaHunan410082China Sustainable Multiphase ARtificial-intelligence Technology(SMART)Laboratory Department of Chemical TechnologyChulalongkorn UniversityBangkokThailand Institute for Artificial Intelligence Southwest Petroleum UniversityChengduChina

Over the past two decades,broad-based and intense efforts have been devoted to apply concepts and methodologies from information technology(IT)and artificial intelligence(AI)to informatics research related to energy and environmental *** academic research and industrial practices have generated an impressive amount of literature,which spans virtually every aspect of synergistic work among these *** and systems analysis techniques are now being widely used by the practicing engineers and scientists to solve a broad range of problems in the petroleum *** at the World Economic Forum at Davos Switzerland in 2017,Ginni Rometty,IBM′CEO at that time(now Executive Chairperson of IBM),described AI's role in the partnership between humans and machines as“augmented cognition.”In other words,AI not only supports but augments human cognition so that humans can be more efficient and“do a better job”[1,2].This should also be true and very beneficial for the petroleum industry.

关键词： devoted petroleum knowledge

An Innovative Genetic Algorithms-Based Inexact Non-Linear Programming Problem Solving Method

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Journal of Environmental Protection 2017年第3期8卷 231-249页

作者： Weihua Jin Zhiying Hu christine chan Energy Informatics Laboratory Faculty of Engineering & Applied Science. University of Regina Regina SK Canada

In this paper, an innovative Genetic Algorithms (GA)-based inexact non-linear programming (GAINLP) problem solving approach has been proposed for solving non-linear programming optimization problems with inexact information (inexact non-linear operation programming). GAINLP was developed based on a GA-based inexact quadratic solving method. The Genetic Algorithm Solver of the Global Optimization Toolbox (GASGOT) developed by MATLABTM was adopted as the implementation environment of this study. GAINLP was applied to a municipality solid waste management case. The results from different scenarios indicated that the proposed GA-based heuristic optimization approach was able to generate a solution for a complicated nonlinear problem, which also involved uncertainty.

关键词： Genetic Algorithms Inexact Non-Linear Programming (INLP) Economy of Scale Numeric Optimization Solid Waste Management

Special issue on, Carbon Capture, Utilization and Storage (CCUS): Technological developments and future opportunities for petroleum industry

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Petroleum 2017年第1期3卷 1-2页

作者： Paitoon(PT) Tontiwachwuthikul Fanhua(Bill)Zeng christine W.chan Canadian Academy of Engineering University of ReginaCanada Petroleum Systems Engineering University of ReginaCanada University of Regina Canada

Carbon Capture,Utilization and Storage(CCUS)plays a key role in addressing two important problems of our life-time:(i)climate-change and(ii)energy *** International Energy Agency(IEA)study reports that there is a significant opportunity of storing up to 360 Gt of CO2 through enhanced oil recovery(EOR)applications over the next 50 *** is also an opportunity to potentially and simultaneously increase oil production by up to 375 billion barrels at the same time[1].From the perspective of life cycle assessment,the total emission of CO2 per unit energy produced from the oil produced by CO2 EOR flooding is much less than that from natural gas[2].

关键词： CCUS Storage Carbon

TUNED MEchanICAL PROPERTIES ACHIEVED BY VARYING POLYMER STRUCTURE-KNOWLEDGE THAT GENERATES NEW MATERIALS FOR TISSUE ENGINEERING

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Chinese Journal of Polymer Science 2007年第2期25卷 113-118页

作者： Anna Finne Wistrand Ann-christine Albertsson Department of Fiber and Polymer Technology Royal Institute of TechnologyStockholmSweden

By changing both the monomer composition and the polymer structure, we have varied the mechanical properties of resorbable polymers. The polymers were synthesized by ring-opening polymerization using L-lactide （LLA）, ε-caprolactone （εCL）, trimethylene carbonate （TMC） and 1,5-dioxepan-2-one （DXO） as monomers. Well-defined triblock copolymers, microblock copolymers and networks have been evaluated, and comparisons between them show that it is possible to tune the mechanical properties. Triblock copolymers with an amorphous middle block of poly（1,5-dioxepan-2- one）（PDXO） and semi-crystalline end-blocks of poly（ε-caprolactone）（PCL） were stronger and had a higher strain at break than triblock copolymers with poly（L-lactide）（PLLA） as end-blocks. Polymers with both DXO and TMC in the amorphous middle-block and PLLA as end-blocks showed a lower stress at break, but the material gained elasticity, a property which is very valuable in tissue engineering. Mechanical properties of networks, synthesized by a novel method, containing PDXO and PCL are also presented. Although it is difficult to compare them with the uncross-linked polymers, this is an additional way to modify and widen the properties.

关键词： Degradable polymer Tuneable mechanical properties Molecular architecture Block copolymers Networks.

Link prediction in complex networks via modularity-based belief propagation

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Chinese Physics B 2017年第3期26卷 604-614页

作者：赖大荣舒欣 christine Nardini School of Computer Science and Engineering Southeast University Nanjing 211189 China Key Laboratory of Computer Network and Information Integration of Ministry of Education Southeast University Nanjing 210096 China College of Information Science and Technology Nanjing Agricultural University Nanjing 210095 China CNR-IAC 'Mauro Picone' Via dei Taurini 19 00185 Roma Italy Personalgenomics Via delle Grazie Verona Italy

Link prediction aims at detecting missing, spurious or evolving links in a network, based on the topological information and/or nodes＇ attributes of the network. Under the assumption that the likelihood of the existence of a link between two nodes can be captured by nodes＇ similarity, several methods have been proposed to compute similarity directly or indirectly, with information on node degree. However, correctly predicting links is also crucial in revealing the link formation mechanisms and thus in providing more accurate modeling for networks. We here propose a novel method to predict links by incorporating stochastic-block-model link generating mechanisms with node degree. The proposed method first recov- ers the underlying block structure of a network by modularity-based belief propagation, and based on the recovered block structural information it models the link likelihood between two nodes to match the degree sequence of the network. Experiments on a set of real-world networks and synthetic networks generated by stochastic block model show that our proposed method is effective in detecting missing, spurious or evolving links of networks that can be well modeled by a stochastic block model. This approach efficiently complements the toolbox for complex network analysis, offering a novel tool to model links in stochastic block model networks that are fundamental in the modeling of real world complex networks.

关键词： link prediction complex network belief propagation modularity

Role of Mdm2 and Mdmx in DNA repair

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Journal of Molecular Cell Biology 2017年第1期9卷 69-73页

作者： christine M. Eischen Department of Cancer Biology Sidney Kimmel Cancer Center Thomas Jefferson University Philadelphia PA 19107 USA

Mdm2 and Mdmx are critical regulators of the p53 tumour suppressor and are overexpressed in many human malignancies. However, in recent years, their impact on genome instability was shown to be at least, in part, independent of p53. Both Mdm2 and Mdmx inhibit DNA break repair through their association with the Mrell/RadSO/Nbs1 DNA repair complex. Recent evidence indicates that harnessing Mdm2 and/or Mdmx-mediated inhibition of DNA break repair in cancer cells could provide a therapeutic opportunity, particularly for those malignancies that have lost functional p53.

关键词： Mdm2 Mdmx Nbsl DNA repair

Saliva:a challenging human fluid to diagnose brain disorders with a focus on Alzheimer's disease

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Neural Regeneration Research 2023年第12期18卷 2606-2610页

作者： christine Zürcher Christian Humpel University Hospital for Restorative Dentistry and Periodontology Medical University of InnsbruckInnsbruckAustria Laboratory of Psychiatry&Experimental Alzheimer’s Research Department of Psychiatry IMedical University of InnsbruckInnsbruckAustria

Biomarkers are molecules of biological processes that help in both the diagnosis of human diseases and in follow-up assessments of therapeutic responses. Biomarkers can be measured in many human fluids, such as blood, cerebrospinal fluid, urine, and saliva. The-omics methods(genomics, RNomics, proteomics, and metabolomics) are useful at measuring thousands of markers in a small volume. Saliva is a human fluid that is easily accessible, without any ethical concerns. Yet, saliva remains unexplored in regard to many human disease biomarkers. In this review, we will give an overview on saliva and how it can be influenced by exogenous factors. As we focus on the potential use of saliva as a diagnostic tool in brain disorders(especially Alzheimer's disease), we will cover how saliva is linked to the brain. We will discuss that saliva is a heterogeneous human fluid, yet useful for the discovery of biomarkers in human disorders. However, a procedure and consensus that is controlled, validated, and standardized for the collection and processing of saliva is required, followed by a highly sensitive diagnostic approach.

关键词： Alzheimer's disease biomarkers diagnosis oral-gut-brain axis periodontitis saliva

Valuable Beyond Vulnerable: A Scoping Review on the Contributions of Older Forced Migrants in Post-migration Recovery

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International Journal of Disaster Risk Science 2024年第2期15卷 186-197页

作者： Prince Chiagozie Ekoh christine A.Walsh Faculty of Social Work University of CalgaryCalgaryAB T2N 1N4Canada Department of Social Work University of NigeriaNsukka 410001Nigeria

During times of crisis, including pandemics, climate change, and forced migration, much of the discourse in ageing research and intervention centers on the vulnerabilities of older adults. Unfortunately, the valuable contributions of older adults to post-disaster recovery and healing are often overlooked and undervalued. Our aim in this scoping review is to shed light on the critical contributions of older forced migrants to post-migration recovery. We set the scene by introducing the two significant global demographic changes of the twenty-first century: forced migration and ageing. We provide a discourse on older forced migrants, ageing in situations of forced migration, and some of the challenges faced by older forced migrants. We then present some of the substantial roles of older forced migrants in post-migration recovery, including building resilience, contributing to culture and language transfer, providing emotional support, offering mentorship and leadership, participating in community building, and fostering social integration. We close by highlighting some of the lessons that can be drawn from understanding the unique roles played by older adults in post-forced migration recovery and the key actions necessary to promote these roles.

关键词： Older displaced persons Older forced migrants Older refugees Post-forced migration recovery