Search results for: Term Weighting

Authors: Ruili Zhou, Yuesheng Zhu

Abstract:

In this paper, a new robust audio fingerprinting algorithm in MP3 compressed domain is proposed with high robustness to time scale modification (TSM). Instead of simply employing short-term information of the MP3 stream, the new algorithm extracts the long-term features in MP3 compressed domain by using the modulation frequency analysis. Our experiment has demonstrated that the proposed method can achieve a hit rate of above 95% in audio retrieval and resist the attack of 20% TSM. It has lower bit error rate (BER) performance compared to the other algorithms. The proposed algorithm can also be used in other compressed domains, such as AAC.

Keywords: Audio Fingerprinting, MP3, Modulation Frequency, TSM

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Authors: N. Popovich, P. Yan

Abstract:

In this paper a controller for the pitch angle of an aircraft regarding to the elevator deflection angle is designed. The way how the elevator angle affects pitching motion of the aircraft is pointed out, as well as, how a pitch controller can be applied for the aircraft to reach certain pitch angle. In this digital optimal system, the elevator deflection angle and pitching angle of the plane are considered to be input and output respectively. A single input single output (SISO) system is presented. A digital pitch aircraft control is demonstrated. A simulation for the whole system has been performed. The optimal control weighting vectors, Q and R have been determined.

Keywords: Aircraft, control, digital, optimal, Q and Rmatrices.

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Authors: Yoong H. Chan, Brenda C. T. Lee, Jin C. Lee

Abstract:

As Malaysia aims to be a developed country by year 2020; the construction industry has since been identified as a major catalyst for the country to attain the status. It is one of the sectors that contribute to most environmental pollutions. It is, therefore, important for the industry to implement sustainable construction practices to reduce the negative impacts that it has on the environment. However, most Malaysian developers have placed much focus on market demand and economic factors; neglecting the need for attention on environmental issues. The practice of sustainable construction is deemed to be an obstacle to achieve short-term economic goals due to the higher cost incurred in the operations. Hence, choices need to be made and a balance needs to be struck in weighing the long-term environmental benefits against immediate economic factors. This paper discusses the challenges faced by Malaysian developers in adopting sustainable practices in the construction industry and the cause of these challenges. It also looks into the achievements and breakthroughs that developers in Malaysia have achieved so far. The paper aims explores the long-term benefits of sustainable practices that would potentially raise awareness on the feasibility and economic potential of sustainable construction.

Keywords: Construction industry, construction method, sustainability.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, non-reference quality measures, objective quality measures.

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: Short term load forecasting, prediction interval, type 2 fuzzy logic systems.

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Authors: F. Alborzi, H. Vafaei, M.H. Gholami, M.M. S. Esfahani

Abstract:

In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

Keywords: Mixed Integer Programming, Multi-objective Optimization, Stochastic Demand, Supply Chain Design, Two Stage Programming

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Authors: Rami A. Maher, Ibraheem K. Ibraheem

Abstract:

This work presents a comparison study between the state-space and polynomial methods for the design of the robust governor for load frequency control of steam turbine power systems. The robust governor is synthesized using the two approaches and the comparison is extended to include time and frequency domains performance, controller order, and uncertainty representation, weighting filters, optimality and sub-optimality. The obtained results are represented through tables and curves with reasons of similarities and dissimilarities.

Keywords: Robust control, load frequency control, steam turbine, H∞-norm, system uncertainty, load disturbance.

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Authors: Changchun Shen, Shouming Zhong

Abstract:

This paper investigates the problem of absolute stability and robust stability of a class of Lur-e systems with neutral type and time-varying delays. By using Lyapunov direct method and linear matrix inequality technique, new delay-dependent stability criteria are obtained and formulated in terms of linear matrix inequalities (LMIs) which are easy to check the stability of the considered systems. To obtain less conservative stability conditions, an operator is defined to construct the Lyapunov functional. Also, the free weighting matrices approach combining a matrix inequality technique is used to reduce the entailed conservativeness. Numerical examples are given to indicate significant improvements over some existing results.

Keywords: Lur'e system, linear matrix inequalities, Lyapunov, stability.

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Authors: Panos D. Kotsas

Abstract:

This paper presents the application of a signal intensity independent registration criterion for 2D rigid body registration of medical images using 1D binary projections. The criterion is defined as the weighted ratio of two projections. The ratio is computed on a pixel per pixel basis and weighting is performed by setting the ratios between one and zero pixels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the one areas of the two projections and it is minimized using the Chebyshev polynomial approximation using n=5 points. The sum of x and y projections is used for translational adjustment and a 45deg projection for rotational adjustment. 20 T1- T2 registration experiments were performed and gave mean errors 1.19deg and 1.78 pixels. The method is suitable for contour/surface matching. Further research is necessary to determine the robustness of the method with regards to threshold, shape and missing data.

Keywords: Medical image, projections, registration, rigid.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

Abstract:

In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, nonreferencequality measures, objective quality measures.

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Authors: Einalou Z., Najafi Z., Maghooli K. Zandi Y, Sheibeigi A

Abstract:

In this study, an investigation over digestive diseases has been done in which the sound acts as a detector medium. Pursue to the preprocessing the extracted signal in cepstrum domain is registered. After classification of digestive diseases, the system selects random samples based on their features and generates the interest nonstationary, long-term signals via inverse transform in cepstral domain which is presented in digital and sonic form as the output. This structure is updatable or on the other word, by receiving a new signal the corresponding disease classification is updated in the feature domain.

Keywords: Cepstrum, databank, digestive disease, acousticsignal.

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Authors: Hiroki Satou, Kayoko Yamamoto

Abstract:

This study aims to propose three evaluation methods to evaluate the Tokyo Cap and Trade Program when emissions trading is performed virtually among enterprises, focusing on carbon dioxide (CO2), which is the only emitted greenhouse gas that tends to increase. The first method clarifies the optimum reduction rate for the highest cost benefit, the second discusses emissions trading among enterprises through market trading, and the third verifies long-term emissions trading during the term of the plan (2010-2019), checking the validity of emissions trading partly using Geographic Information Systems (GIS). The findings of this study can be summarized in the following three points. 1. Since the total cost benefit is the greatest at a 44% reduction rate, it is possible to set it more highly than that of the Tokyo Cap and Trade Program to get more total cost benefit. 2. At a 44% reduction rate, among 320 enterprises, 8 purchasing enterprises and 245 sales enterprises gain profits from emissions trading, and 67 enterprises perform voluntary reduction without conducting emissions trading. Therefore, to further promote emissions trading, it is necessary to increase the sales volumes of emissions trading in addition to sales enterprises by increasing the number of purchasing enterprises. 3. Compared to short-term emissions trading, there are few enterprises which benefit in each year through the long-term emissions trading of the Tokyo Cap and Trade Program. Only 81 enterprises at the most can gain profits from emissions trading in FY 2019. Therefore, by setting the reduction rate more highly, it is necessary to increase the number of enterprises that participate in emissions trading and benefit from the restraint of CO2 emissions.

Keywords: Emissions Trading, Tokyo Cap and Trade Program, Carbon Dioxide (CO2), Global Warming, Geographic Information Systems (GIS)

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Authors: Fatemeh Mosalman Yazdi

Abstract:

One of the most important requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as short term load forecasting. This paper presents the development of an artificial neural network based short-term load forecasting model. The model can forecast daily load profiles with a load time of one day for next 24 hours. In this method can divide days of year with using average temperature. Groups make according linearity rate of curve. Ultimate forecast for each group obtain with considering weekday and weekend. This paper investigates effects of temperature and humidity on consuming curve. For forecasting load curve of holidays at first forecast pick and valley and then the neural network forecast is re-shaped with the new data. The ANN-based load models are trained using hourly historical. Load data and daily historical max/min temperature and humidity data. The results of testing the system on data from Yazd utility are reported.

Keywords: Artificial neural network, Holiday forecasting, pickand valley load forecasting, Short-term load-forecasting.

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Authors: Meng Hu, Lili Wang

Abstract:

In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.

Keywords: Hopfield neural network, linear matrix inequality, exponential stability, time delay, T-S fuzzy model.

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Authors: Fuzhang Zhao

Abstract:

Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: Diversification search, intensification search, optimal weighting, particle swarm optimization.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

Abstract:

The Minimum Weighted Vertex Cover (MWVC) problem is a classic graph optimization NP - complete problem. Given an undirected graph G = (V, E) and weighting function defined on the vertex set, the minimum weighted vertex cover problem is to find a vertex set S V whose total weight is minimum subject to every edge of G has at least one end point in S. In this paper an effective algorithm, called Support Ratio Algorithm (SRA), is designed to find the minimum weighted vertex cover of a graph. Computational experiments are designed and conducted to study the performance of our proposed algorithm. Extensive simulation results show that the SRA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Keywords: Weighted vertex cover, vertex support, approximation algorithms, NP-complete problem.

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Authors: Fahmi Kammoun, Mohamed Salim Bouhlel

Abstract:

In the framework of the image compression by Wavelet Transforms, we propose a perceptual method by incorporating Human Visual System (HVS) characteristics in the quantization stage. Indeed, human eyes haven-t an equal sensitivity across the frequency bandwidth. Therefore, the clarity of the reconstructed images can be improved by weighting the quantization according to the Contrast Sensitivity Function (CSF). The visual artifact at low bit rate is minimized. To evaluate our method, we use the Peak Signal to Noise Ratio (PSNR) and a new evaluating criteria witch takes into account visual criteria. The experimental results illustrate that our technique shows improvement on image quality at the same compression ratio.

Keywords: Contrast Sensitivity Function, Human Visual System, Image compression, Wavelet transforms.

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Authors: Woo-tai Jung, Sung-yong Choi, Young-hwan Park

Abstract:

The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: Creep, Lean concrete, Pavement, Fiber reinforced concrete, Base.

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Authors: Woo-Tai Jung, Sung-Yong Choi, Young-Hwan Park

Abstract:

The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: Creep, Lean concrete, Pavement, Fiber reinforced concrete, Base.

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Authors: Ferdi Sönmez, Başak Buluz

Abstract:

Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: Knowledge management, agility requirements, agility in knowledge management, knowledge.

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Authors: M.Sujaritha, S. Annadurai

Abstract:

An adaptive spatial Gaussian mixture model is proposed for clustering based color image segmentation. A new clustering objective function which incorporates the spatial information is introduced in the Bayesian framework. The weighting parameter for controlling the importance of spatial information is made adaptive to the image content to augment the smoothness towards piecewisehomogeneous region and diminish the edge-blurring effect and hence the name adaptive spatial finite mixture model. The proposed approach is compared with the spatially variant finite mixture model for pixel labeling. The experimental results with synthetic and Berkeley dataset demonstrate that the proposed method is effective in improving the segmentation and it can be employed in different practical image content understanding applications.

Keywords: Adaptive; Spatial, Mixture model, Segmentation, Color.

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Authors: O. V. Missioura

Abstract:

MC (Management Control)& IC (Internal Control) – what is the relationship? (an empirical study into the definitions between MC and IC) based on the wider considerations of Internal Control and Management Control terms, attention is focused not only on the financial aspects but also more on the soft aspects of the business, such as culture, behaviour, standards and values. The limited considerations of Management Control are focused mainly in the hard, financial aspects of business operation. The definitions of Management Control and Internal Control are often used interchangeably and the results of this empirical study reveal that Management Control is part of Internal Control, there is no causal link between the two concepts. Based on the interpretation of the respondents, the term Management Control has moved from a broad term to a more limited term with the soft aspects of the influencing of behaviour, performance measurements, incentives and culture. This paper is an exploratory study based on qualitative research and on a qualitative matrix method analysis of the thematic definition of the terms Management Control and Internal Control.

Keywords: Management Control (MC), Internal Control (IC), definition, causal link, COSO 1992/2004, CoCo (Canadian Institute of Chartered Accountants), Russian CG code (КОДЕКС) , limited and broad concepts MC and IC.

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Authors: Pedro F. Albuquerque, Pedro V. Gamboa, Miguel A. Silvestre

Abstract:

The present work describes the implementation of the Enhanced Collaborative Optimization (ECO) multilevel architecture with a gradient-based optimization algorithm with the aim of performing a multidisciplinary design optimization of a generic unmanned aerial vehicle with morphing technologies. The concepts of weighting coefficient and dynamic compatibility parameter are presented for the ECO architecture. A routine that calculates the aircraft performance for the user defined mission profile and vehicle’s performance requirements has been implemented using low fidelity models for the aerodynamics, stability, propulsion, weight, balance and flight performance. A benchmarking case study for evaluating the advantage of using a variable span wing within the optimization methodology developed is presented.

Keywords: Multidisciplinary, Multilevel, Morphing, Enhanced Collaborative Optimization (ECO).

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Authors: Jeļena Tretjakova

Abstract:

Metaphor has recently gained extensive interest most probably due to developments in cognitive sciences and the study of language as the reflection of humans- world perception. Metaphor is no longer reckoned as solely literary expressive means. Nowadays it is studied in a whole number of discourses, such as politics, law, medicine, sports, etc. with the purpose of the analysis and determining its role. The scientific language is not an exception. It might seem that metaphor cannot suit it; we would dare to draw a hypothesis that metaphor has indeed found its stable place in terminology. In comprehension of metaphorically represented terms the stage of visualization plays a significant role. We proceeded on the assumption that this stage is the main in provision of better term comprehension and would try to exemplify it with metaphoricallyoriented terms.

Keywords: Comprehension, metaphor, terminology, visualization.

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Authors: Jitendra Jain, Cassandra Hidajat, Hansraj Riteesh Bookun

Abstract:

Graft patency underpins long-term prognosis after coronary artery bypass grafting surgery (CABG). The benefits of the combined use of only the left internal mammary artery and radial artery, referred to as total arterial revascularisation (TAR), on long-term clinical outcomes and quality of life are relatively unknown. The aim of this study was to identify whether there were differences in long term clinical outcomes between recipients of TAR compared to a cohort of mostly arterial revascularization involving the left internal mammary, at least one radial artery and at least one saphenous vein graft. A retrospective analysis was performed on all patients who underwent TAR or were re-vascularized with supplementary saphenous vein graft from February 1996 to December 2004. Telephone surveys were conducted to obtain clinical outcome parameters including major adverse cardiac and cerebrovascular events (MACCE) and Short Form (SF-36v2) Health Survey responses. A total of 176 patients were successfully contacted to obtain postop follow up results. The mean follow-up length from time of surgery in our study was TAR 12.4±1.8 years and conventional 12.6±2.1. PCS score was TAR 45.9±8.8 vs LIMA/Rad/ SVG 44.9±9.2 (p=0.468) and MCS score was TAR 52.0±8.9 vs LIMA/Rad/SVG 52.5±9.3 (p=0.723). There were no significant differences between groups for NYHA class 3+ TAR 9.4% vs. LIMA/Rad/SVG 6.6%; or CCS 3+ TAR 2.35% vs. LIMA/Rad/SVG 0%.

Keywords: CABG, MACCEs, quality of life, total arterial revascularization.

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Authors: Tomohiro Hachino, Kengo Nagatomo, Hitoshi Takata

Abstract:

This paper deals with an on-line identification method of continuous-time Hammerstein systems by using the radial basis function (RBF) networks and immune algorithm (IA). An unknown nonlinear static part to be estimated is approximately represented by the RBF network. The IA is efficiently combined with the recursive least-squares (RLS) method. The objective function for the identification is regarded as the antigen. The candidates of the RBF parameters such as the centers and widths are coded into binary bit strings as the antibodies and searched by the IA. On the other hand, the candidates of both the weighting parameters of the RBF network and the system parameters of the linear dynamic part are updated by the RLS method. Simulation results are shown to illustrate the proposed method.

Keywords: Continuous-time System, Hammerstein System, OnlineIdentification, Immune Algorithm, RBF network.

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Authors: S. Logeswari, K. Premalatha

Abstract:

Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.

Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.

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Authors: Jyh-Da Wei, Hsin-Chen Tsai

Abstract:

This work presents a novel means of extracting fixedlength parameters from voice signals, such that words can be recognized in linear time. The power and the zero crossing rate are first calculated segment by segment from a voice signal; by doing so, two feature sequences are generated. We then construct an FIR system across these two sequences. The parameters of this FIR system, used as the input of a multilayer proceptron recognizer, can be derived by recursive LSE (least-square estimation), implying that the complexity of overall process is linear to the signal size. In the second part of this work, we introduce a weighting factor λ to emphasize recent input; therefore, we can further recognize continuous speech signals. Experiments employ the voice signals of numbers, from zero to nine, spoken in Mandarin Chinese. The proposed method is verified to recognize voice signals efficiently and accurately.

Keywords: Speech Recognition, FIR system, Recursive LSE, Multilayer Perceptron

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Authors: Bachir Boucheham, Youcef Ferdi, Mohamed Chaouki Batouche

Abstract:

We suggest a novel method to incorporate longterm redundancy (LTR) in signal time domain compression methods. The proposition is based on block-sorting and curve simplification. The proposition is illustrated on the ECG signal as a post-processor for the FAN method. Test applications on the new so-obtained FAN+ method using the MIT-BIH database show substantial improvement of the compression ratio-distortion behavior for a higher quality reconstructed signal.

Keywords: ECG compression, Long-term redundancy, Block-sorting, Curve Simplification.

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Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

Abstract:

Industrial end users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both Machine Learning and First Principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed from breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems and humans – including asset maintenance operations – in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: Degradation models, ageing, anomaly detection, soft sensor, incremental learning.

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