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An artificial intelligence framework for explainable drift detection in energy forecasting

Energy and AI 2024年第3期17卷 368-379页

作者： Chamod Samarajeewa Daswin De Silva Milos Manic Nishan Mills Harsha Moraliyage Damminda Alahakoon Andrew Jennings centre for data analytics and cognition La Trobe UniversityAustralia Department of Computer Science Virginia Commonwealth UniversityRichmondUSA

Accurate energy consumption forecasting is crucial for reducing operational costs, achieving net-zero carbon emissions, and ensuring sustainable buildings and cities of the future. Despite the frequent use of Artificial Intelligence (AI) algorithms for learning energy consumption patterns and predictions in Building Science, relying solely on these techniques for energy demand prediction addresses only a fraction of the challenge. A drift in energy usage can lead to inaccuracies in these AI models and subsequently to poor decision-making and interventions. While drift detection techniques have been reported, a reliable and robust approach capable of explaining identified discrepancies with actionable insights has not been discussed in extant literature. Hence, this paper presents an Artificial Intelligence framework for energy consumption forecasting with explainable drift detection, aimed at addressing these challenges. The proposed framework is composed of energy embeddings, an optimized dimensional model integrated within a data warehouse, and scalable cloud implementation for effective drift detection with explainability capability. The framework is empirically evaluated in the real-world setting of a multi-campus, mixed-use tertiary education setting in Victoria, Australia. The results of these experiments highlight its capabilities in detecting concept drift, adapting forecast predictions, and providing an interpretation of the changes using energy embeddings.

关键词： Building energy consumption forecasting Explainable drift detection Energy embedding Dimensional modeling

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Enhancing Telemarketing Success Using Ensemble-Based Online Machine Learning

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Big data Mining and analytics 2024年第2期7卷 294-314页

作者： Shahriar Kaisar Md Mamunur Rashid Abdullahi Chowdhury Sakib Shahriar Shafin Joarder Kamruzzaman Abebe Diro Department of Information Systems and Business analytics RMIT UniversityMelbourne 3000Australia School of Engineering and Technology Central Queensland UniversityRockhampton 4700Australia Faculty of Engineering Computer and Mathematical ScienceUniversity of AdelaideAdelaide 5005Australia centre for Smart analytics Federation University AustraliaBallarat 3350Australia School of Accounting Information Systems and Supply ChainRMIT UniversityMelbourne 3000Australia

Telemarketing is a well-established marketing approach to offering products and services to prospective *** effectiveness of such an approach,however,is highly dependent on the selection of the appropriate consumer base,as reaching uninterested customers will induce annoyance and consume costly enterprise resources in vain while missing interested *** introduction of business intelligence and machine learning models can positively influence the decision-making process by predicting the potential customer base,and the existing literature in this direction shows promising ***,the selection of influential features and the construction of effective learning models for improved performance remain a ***,from the modelling perspective,the class imbalance nature of the training data,where samples with unsuccessful outcomes highly outnumber successful ones,further compounds the problem by creating biased and inaccurate ***,customer preferences are likely to change over time due to various reasons,and/or a fresh group of customers may be targeted for a new product or service,necessitating model retraining which is not addressed at all in existing works.A major challenge in model retraining is maintaining a balance between stability(retaining older knowledge)and plasticity(being receptive to new information).To address the above issues,this paper proposes an ensemble machine learning model with feature selection and oversampling techniques to identify potential customers more accurately.A novel online learning method is proposed for model retraining when new samples are available over *** newly introduced method equips the proposed approach to deal with dynamic data,leading to improved readiness of the proposed model for practical adoption,and is a highly useful addition to the *** experiments with real-world data show that the proposed approach achieves excellent results in all cases(e.g.,98.6

关键词： machine learning online learning oversampling telemarketing imbalanced dataset ensemble model

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Approximations to Isentropic Planar Magneto-Hydrodynamics Equations by Relaxed Euler-Type Systems

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Chinese Annals of Mathematics,Series B 2024年第3期45卷 413-440页

作者： Yachun LI Zhaoyang SHANG Chenmu WANG Liang ZHAO School of Mathematical Sciences CMA-ShanghaiMOE-LSC and SHL-MACShanghai Jiao Tong UniversityShanghai 200240China School of Finance Shanghai Lixin University of Accounting and FinanceShanghai 201209China School of Mathematical Sciences Shanghai Jiao Tong UniversityShanghai 200240China School of Mathematical Sciences Harbin Engineering UniversityHarbin 150001China Mathematical Modelling&data analytics Center Oxford Suzhou Centre for Advanced ResearchSuzhou 215123JiangsuChina

In this paper, the authors consider an approximation to the isentropic planar Magneto-hydrodynamics(MHD for short) equations by a kind of relaxed Euler-type system. The approximation is based on the generalization of the Maxwell law for nonNewtonian fluids together with the Maxwell correction for the Ampe`re law, hence the approximate system becomes a first-order quasilinear symmetrizable hyperbolic systems with partial dissipation. They establish the global-in-time smooth solutions to the approximate Euler-type equations in a small neighbourhood of constant equilibrium states and obtain the global-in-time convergence towards the isentropic planar MHD equations. In addition, they also establish the global-in-time error estimates of the limit based on stream function techniques and energy estimates for error variables.

关键词： Planar MHD equations Relaxation limits Global convergence Stream function

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A Bayesian hierarchical model for the inference between metal grade with reduced variance:Case studies in porphyry Cu deposits

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Geoscience Frontiers 2024年第2期15卷 304-314页

作者： Yufu Niu Mark Lindsay Peter Coghill Richard Scalzo Lequn Zhang CSIRO Mineral Resources Lucas HeightsNew South Wales 2234Australia Mineral Exploration Cooperative Research centre Centre for Exploration TargetingSchool of Earth ScienceThe University of Western AustraliaPerthWA 6009Australia ARC centre for data analytics for Resources and Environments(DARE) Perth and SydneyAustralia CSIRO Mineral Resources Australian Resources Research CentreWA 6151Australia CSIRO data61 ClaytonVIC 3168Australia

Ore sorting is a preconcentration technology and can dramatically reduce energy and water usage to improve the sustainability and profitability of a mining *** porphyry Cu deposits,Cu is the primary target,with ores usually containing secondary‘pay’metals such as Au,Mo and gangue elements such as Fe and *** to sensing technology limitations,secondary and deleterious materials vary in correlation type and strength with Cu but cannot be detected simultaneously via magnetic resonance(MR)ore *** the relationships between Cu and other elemental abundances is particularly critical for mineral *** variations in metal grade relationships occur due to the transition into different geological *** raises two questions-how to define these geological domains and how the metal grade relationship is influenced by these geological *** this paper,linear relationship is assumed between Cu grade and other metal *** applies a Bayesian hierarchical(partial-pooling)model to quantify the linear relationships between Cu,Au,and Fe grades from geochemical bore core *** hierarchical model was compared with two other models-‘complete-pooling’model and‘nopooling’*** blocks were split based on spatial domain to construct hierarchical *** bore core data records metal grades measured from laboratory assay with spatial coordinates of sample *** case studies from different porphyry Cu deposits were used to evaluate the performance of the hierarchical *** chain Monte Carlo(MCMC)was used to sample the posterior *** results show that the Bayesian hierarchical model dramatically reduced the posterior predictive variance for metal grades regression compared to the no-pooling *** addition,the posterior inference in the hierarchical model is insensitive to the choice of *** data is wellrepresented in the posterior which indicates a robust *** results show that the spatial dom

关键词： Bayesian hierarchical model Porphyry Cu deposit Ore sorting Metal grade Linear regression

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Development and application of feature engineered geological layers for ranking magmatic,volcanogenic,and orogenic system components in Archean greenstone belts

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Geoscience Frontiers 2024年第2期15卷 251-273页

作者： R.M.Montsion S.Perrouty M.D.Lindsay M.W.Jessell R.Sherlock Mineral Exploration Research centre Harquail School of Earth SciencesGoodman School of MinesLaurentian UniversitySudburyOntario P3E 2C6Canada centre for Exploration Targeting School of Earth SciencesThe University of Western Australia35 Stirling HighwayCrawley 6009Australia Commonwealth Scientific and Industrial Research Organization Mineral Resources26 Dick Perry AveKensingtonWA 6151Australia ARC centre for data analytics for Resources and Environments(DARE) Perth and SydneyAustralia

Geologically representative feature engineering is a crucial component in geoscientific applications of machine *** commonly applied feature engineering techniques used to produce input variables for machine learning apply geological knowledge to generic data science techniques,which can lead to ambiguity,geological oversimplification,and/or compounding subjective *** that utilize minimally processed input variables attempt to overcome these issues,but often lead to convoluted and uninterpretable *** address these challenges,new and enhanced feature engineering methods were developed by combining geological knowledge,understanding of data limitations,and a variety of data science *** include non-Euclidean fluid pre-deformation path distance,rheological and chemical contrast,geologically constrained interpolation of characteristic host rock geochemistry,interpolation of mobile element gain/loss,assemblages,magnetic intensity,structural complexity,host rock physical *** methods were applied to compiled open-source and new field observations from Archean greenstone terranes in the Abitibi and western Wabigoon sub-provinces of the Superior Province near Timmins and Dryden,Ontario,*** feature maps represent conceptually significant components in magmatic,volcanogenic,and orogenic mineral systems.A comparison of ranked feature importance from random forests to conceptual mineral system models show that the feature maps adequately represent system components,with a few exceptions attributed to biased training data or limited constraint *** study also highlights the shared importance of several highly ranked features for the three mineral systems,indicating that spatially related mineral systems exploit the same features when *** feature importance when classifying orogenic Au mineralization in Timmins and Dryden provides insights into the possible cause of contrasting endowment be

关键词： Machine learning Random forests Mineral systems Magmatic Ni-Cu-PGE Volcanogenic Massive Sulfide(VMS)Cu-Zn-Pb-Ag(-Au) Orogenic Au Abitibi Wabigoon

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Comparative analysis of SIMILAR to RCD ONE(SRO)family from tetraploid cotton species and their diploid progenitors depict their significance in cotton growth and development

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Journal of Cotton Research 2024年第1期7卷 45-57页

作者： SHABAN Muhammad TABASSUM Riaz RANA Iqrar Ahmad ATIF Rana Muhammad AZMAT Muhammad Abubakkar IQBAL Zubair MAJEED Sajid AZHAR Muhammad Tehseen Department of Plant Breeding and Genetics University of Agriculture FaisalabadSub-Campus BurewalaVehari 61010Pakistan Department of Chemistry and Biochemistry University of AgricultureFaisalabad 38400Pakistan centre of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabad 38400Pakistan Department of Plant Breeding and Genetics University of AgricultureFaisalabad 38400Pakistan Precision Agriculture and analytics Lab National Centre in Big Data and Cloud ComputingCentre for Advanced Studies in Agriculture and Food SecurityUniversity of Agriculture FaisalabadFaisalabad 38400Pakistan Department of Plant Pathology University of CaliforniaDavisCA 95616USA State Key Laboratory of Cotton Biology Institute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangHenan 455000China Federal Seed Certification and Registration Department Ministry of National Food Security and ResearchIslamabad 44090Pakistan School of Agriculture Sciences Zhengzhou UniversityZhengzhou 450000China

Background SRO(Similar to RCD1)genes family is largely recognized for their importance in the growth,develop-ment,and in responding to environmental ***,genome-wide identification and functional characteri-zation of SRO genes from cotton species have not been reported so *** A total of 36 SRO genes were identified from four cotton *** analysis divided these genes into three groups with distinct *** and chromosomal distribution analysis indicated uneven distribu-tion of GaSRO,GrSRO,GhSRO,and GbSRO genes on A2,D5 genomes,Gh-At,Gh-Dt,Gb-At,and Gb-Dt subgenomes,*** duplication analysis revealed the presence of six duplicated gene pairs among GhSRO *** promoter analysis,several elements responsive to the growth,development and hormones were found in GhSRO genes,implying gene induction during cotton growth and *** miRNAs responsive to plant growth and abiotic stress were predicted to target 12 GhSRO ***-specific expression profiling demonstrated the roles of GhSRO genes in one or more *** addition,specific expression pattern of some GhSRO genes dur-ing ovule development depicted their involvement in these developmental *** The data presented in this report laid a foundation for understanding the classification and functions of SRO genes in cotton.

关键词： Cotton SRO miRNAs Gene duplications Gene expression Ovule development

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Rational and Continuous Measurement of Emotional-Fingerprint, Emotional-Quotient and Categorical vs Proportional Recognition of Facial Emotions with M.A.R.I.E., Second Half

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Open Journal of Psychiatry 2024年第4期14卷 400-450页

作者： Philippe Granato Shreekumar Vinekar Jean-Pierre Van Gansberghe Raymond Bruyer Unit de Rhabilitation Psycho-Sociale Service de Psychiatrie Centre Hospitalier de Denain Denain France Department of Psychiatry and Behavioral Sciences College of Medicine University of Oklahoma Oklahoma City USA Mathematics Consultant Brussels Belgium Institute of Psychological Sciences Center of Neuroscience Cognition and Systems University of Louvain Louvain-la-Neuve Belgium

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual obse

关键词： M.A.R.I.E. Universality Idiosyncrasy Measurement of Emotional Quotient Emotional Fingerprint Emotional Decision-Making Limbic Lobe

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Epidemiology and Clinical Outcomes of Metabolic(Dysfunction)-associated Fatty Liver Disease

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Journal of Clinical and Translational Hepatology 2021年第6期9卷 972-982页

作者： Huapeng Lin Xinrong Zhang Guanlin Li Grace Lai-Hung Wong Vincent Wai-Sun Wong Department of Medicine and Therapeutics State Key Laboratory of Digestive diseaseand Medical Data Analytics CentreThe Chinese University of Hong KongHong KongChina

Metabolic(dysfunction)-associated fatty liver disease(MAFLD)is currently the most common chronic liver disease and affects at least a quarter of the global adult *** has rapidly become one of the leading causes of hepatocellular carcinoma and cirrhosis in Western *** this review,we discuss the nomenclature and definition of MAFLD as well as its prevalence and incidence in different geographical *** cardiovascular disease remains the leading cause of death in MAFLD patients,the proportion of patients dying from hepatic complications increases sharply as the disease progresses to advanced liver fibrosis and *** addition,patients with MAFLD are at increased risk of various extrahepatic *** a causal relationship between MAFLD and extrahepatic cancers has not been established,clinicians should recognize the association and consider cancer screening(e.g.,for colorectal cancer)as appropriate.

关键词： Nonalcoholic fatty liver disease Nonalcoholic steatohepatitis Obesity Prevalence Incidence Hepatocellular carcinoma Cirrhosis

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Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

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Open Journal of Psychiatry 2024年第3期14卷 223-264页

作者： Philippe Granato Shreekumar Vinekar Jean-Pierre Van Gansberghe Raymond Bruyer Unité de R&#233habilitation Psycho-sociale Service de Psychiatrie Centre Hospitalier de Denain Denain France Department of Psychiatry and Behavioral Sciences College of Medicine University of Oklahoma Oklahoma City USA Brussels Belgium Institute of Psychological Sciences Center of Neuroscience Cognition and Systems University of Louvain Louvain la Neuve Belgium

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individu

关键词： M.A.R.I.E. Universality Idiosyncrasy Measurement of Emotional Quotient Emotional Fingerprint Emotional Decision-Making Limbic Lobe

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Effectiveness of post-COVID-19 primary care attendance in improving survival in very old patients with multimorbidity:a territory-wide target trial emulation

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Family Medicine and Community Health 2024年第3期12卷 25-35页

作者： Cuiling Wei Vincent Ka Chun Yan Camille Maringe Wenxin Tian Rachel Yui Ki Chu Wenlong Liu Boyan Liu Yuqi Hu Lingyue Zhou Celine Sze Ling Chui Xue Li Eric Yuk Fai Wan Ching Lung Cheung Esther Wai Yin Chan William Chi Wai Wong Ian Chi Kei Wong Francisco Tsz Tsun Lai centre for Safe Medication Practice and Research Department of Pharmacology and PharmacyLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongHong Kong Department of Health Services Research and Policy Faculty of Public Health and PolicyLondon School of Hygiene and Tropical MedicineLondonUK School of Nursing Li Ka Shing Faculty of MedicineThe University of Hong KongHong KongHong Kong School of Public Health Li Ka Shing Faculty of MedicineThe University of Hong KongHong KongHong Kong Laboratory of data Discovery for Health(D24H) Hong KongHong Kong Advanced data analytics for Medical Science(ADAMS)Limited Hong KongHong Kong Department of Medicine School of Clinical MedicineLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongHong Kong Department of Family Medicine and Primary Care School of Clinical MedicineLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongHong Kong Department of Pharmacy The University of Hong Kong-Shenzhen HospitalShenzhenPeople's Republic of China Aston Pharmacy School Aston UniversityBirminghamUK School of Pharmacy Macao University of Science and TechnologyTaipaMacao

Objectives Older individuals with multimorbidity are at an elevated risk of infection and complications from *** of post-COVID-19 interventions or care models in reducing subsequent adverse outcomes in these individuals have rarely been *** study aims to examine the effectiveness of attending general outpatient within 30 days after discharge from COVID-19 on 1-year survival among older adults aged 85 years or above with *** Retrospective cohort study emulating a randomised target trial using electronic health *** We used data from the Hospital Authority and the Department of Health in Hong Kong,which provided comprehensive electronic health records,COVID-19 confirmed case data,population-based vaccination records and other individual characteristics for the *** Adults aged 85 years or above with multimorbidity who were discharged after hospitalisation for COVID-19 between January 2020 and August *** Attending a general outpatient within 30 days of last COVID-19 discharge defined the exposure,compared to no outpatient *** outcome measures Primary outcome was all-cause mortality within one *** outcomes included mortality from respiratory,cardiovascular and cancer *** A total of 6183 eligible COVID-19 survivors were included in the *** all-cause mortality rate following COVID-19 hospitalisation was lower in the general outpatient visit group(17.1 deaths per 100 person-year)compared with non-visit group(42.8 deaths per 100 person-year).After adjustment,primary care consultations within 30 days after discharge were associated with a significantly greater 1-year survival(difference in 1-year survival:11.2%,95%CI 8.1%to 14.4%).We also observed significantly better survival from respiratory diseases in the general outpatient visit group(difference in 1-year survival:6.3%,95%CI 3.5%to 8.9%).In a sensitivity analysis for different grace period lengths

关键词： morbidity visit records

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