DEVELOPMENT OF MODEL BASED AUTOMATIC ON-LINE FDD TECHNIQUE FOR AHU SYSTEM : INVESTIGATION USING REAL DATA SETS

From a statistical data bank containing only anonymous records, the records sometimes may be identified and then retrieved, as personal records, by on line dialogue. The risk mainly applies to statistical data sets representing populations, or samples with a high ratio n/N. On the other hand, access controls are unsatisfactory as a general means of protection for statistical data banks, which should be open to large user communities. A threat monitoring scheme is proposed, which will largely block the techniques for retrieval of complete records. If combined with additional measures (e.g., slight modifications of output), it may be expected to render, from a cost-benefit point of view, intrusion attempts by dialogue valueless, if not absolutely impossible. The bona fide user has to pay by some loss of information, but considerable flexibility in evaluation is retained. The proposal of controlled classification included in the scheme may also be useful for off line dialogue systems.

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A Modified Dugoff Tire Model for Combined-slip Forces

Tire Science and Technology ◽

10.2346/1.3481696 ◽

2010 ◽

Vol 38 (3) ◽

pp. 228-244 ◽

Cited By ~ 19

Author(s):

Nenggen Ding ◽

Saied Taheri

Keyword(s):

Vehicle Dynamics ◽

Tire Model ◽

Magic Formula ◽

Model Based ◽

Proposed Model ◽

Road Friction ◽

On Line ◽

Double Lane Change ◽

Tire Forces ◽

Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

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Selection of one-dimensional sedimentation: models for on-line use

Water Science & Technology ◽

10.2166/wst.1995.0100 ◽

1995 ◽

Vol 31 (2) ◽

pp. 193-204 ◽

Cited By ~ 7

Author(s):

Koen Grijspeerdt ◽

Peter Vanrolleghem ◽

Willy Verstraete

Keyword(s):

Steady State ◽

Selection Criteria ◽

Data Sets ◽

Concentration Profiles ◽

A Posteriori ◽

One Dimensional ◽

On Line ◽

Dynamic Concentration ◽

Selection Of ◽

Modelling Task

A comparative study of several recently proposed one-dimensional sedimentation models has been made. This has been achieved by fitting these models to steady-state and dynamic concentration profiles obtained in a down-scaled secondary decanter. The models were evaluated with several a posteriori model selection criteria. Since the purpose of the modelling task is to do on-line simulations, the calculation time was used as one of the selection criteria. Finally, the practical identifiability of the models for the available data sets was also investigated. It could be concluded that the model of Takács et al. (1991) gave the most reliable results.

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Components of a model-based operation system for wastewater treatment plants

Water Science & Technology ◽

10.2166/wst.1999.0195 ◽

1999 ◽

Vol 39 (4) ◽

pp. 103-111 ◽

Cited By ~ 1

Author(s):

Frank Obenaus ◽

Karl-Heinz Rosenwinkel ◽

Jens Alex ◽

Ralf Tschepetzki ◽

Ulrich Jumar

Keyword(s):

Wastewater Treatment ◽

Wastewater Treatment Plants ◽

Operation System ◽

Model Based ◽

Measuring Devices ◽

Crucial Component ◽

Simulation Calculation ◽

On Line ◽

Main Components

This report presents the main components of a system for the model-based control of aerobic biological wastewater treatment plants. The crucial component is a model which is linked to the actual processes via several interfaces and which contains a unit which can immediately follow up the current process state. The simulation calculation of the model is based on data which are yielded by on-line measuring devices. If the sensors should fail at times, there are available a number of alternative concepts, some of which are based on the calculations of artificial neural networks or linear methods.

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HealthMAP - A Model-Based Framework for On-Line Prognostics and Health Management (PHM)

AIAA Infotech@Aerospace 2010 ◽

10.2514/6.2010-3500 ◽

2010 ◽

Cited By ~ 2

Author(s):

Ravi Kapadia ◽

Mark Walker

Keyword(s):

Health Management ◽

Prognostics And Health Management ◽

Model Based ◽

On Line

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Transforming variables to central normality

Machine Learning ◽

10.1007/s10994-021-05960-5 ◽

2021 ◽

Author(s):

Jakob Raymaekers ◽

Peter J. Rousseeuw

Keyword(s):

Maximum Likelihood ◽

Maximum Likelihood Estimator ◽

Simulation Study ◽

Real Data ◽

Data Sets ◽

Transformation Parameter ◽

Likelihood Estimator ◽

Extensive Simulation ◽

Highly Sensitive

AbstractMany real data sets contain numerical features (variables) whose distribution is far from normal (Gaussian). Instead, their distribution is often skewed. In order to handle such data it is customary to preprocess the variables to make them more normal. The Box–Cox and Yeo–Johnson transformations are well-known tools for this. However, the standard maximum likelihood estimator of their transformation parameter is highly sensitive to outliers, and will often try to move outliers inward at the expense of the normality of the central part of the data. We propose a modification of these transformations as well as an estimator of the transformation parameter that is robust to outliers, so the transformed data can be approximately normal in the center and a few outliers may deviate from it. It compares favorably to existing techniques in an extensive simulation study and on real data.

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A New Extension of Thinning-Based Integer-Valued Autoregressive Models for Count Data

Entropy ◽

10.3390/e23010062 ◽

2020 ◽

Vol 23 (1) ◽

pp. 62

Author(s):

Zhengwei Liu ◽

Fukang Zhu

Keyword(s):

Likelihood Estimation ◽

Real Data ◽

Autoregressive Models ◽

Superior Performance ◽

Data Sets ◽

Binomial Thinning ◽

Free Case ◽

Two Parameters ◽

Conditional Maximum ◽

Thinning Operator

The thinning operators play an important role in the analysis of integer-valued autoregressive models, and the most widely used is the binomial thinning. Inspired by the theory about extended Pascal triangles, a new thinning operator named extended binomial is introduced, which is a general case of the binomial thinning. Compared to the binomial thinning operator, the extended binomial thinning operator has two parameters and is more flexible in modeling. Based on the proposed operator, a new integer-valued autoregressive model is introduced, which can accurately and flexibly capture the dispersed features of counting time series. Two-step conditional least squares (CLS) estimation is investigated for the innovation-free case and the conditional maximum likelihood estimation is also discussed. We have also obtained the asymptotic property of the two-step CLS estimator. Finally, three overdispersed or underdispersed real data sets are considered to illustrate a superior performance of the proposed model.

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Goodness-of-Fit Tests for Bivariate Time Series of Counts

Econometrics ◽

10.3390/econometrics9010010 ◽

2021 ◽

Vol 9 (1) ◽

pp. 10

Author(s):

Šárka Hudecová ◽

Marie Hušková ◽

Simos G. Meintanis

Keyword(s):

Goodness Of Fit ◽

Probability Generating Function ◽

Parametric Bootstrap ◽

Real Data ◽

Data Sets ◽

Test Statistics ◽

Finite Sample ◽

Generalized Poisson ◽

Goodness Of Fit Tests ◽

Monte Carlo Experiments

This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being entirely nonparametric and the second one being semiparametric computed under the corresponding null hypothesis. The asymptotic distribution of the proposed tests statistics both under the null hypotheses as well as under alternatives is derived and consistency is proved. The case of testing bivariate generalized Poisson autoregression and extension of the methods to dimension higher than two are also discussed. The finite-sample performance of a parametric bootstrap version of the tests is illustrated via a series of Monte Carlo experiments. The article concludes with applications on real data sets and discussion.

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Predicting Damage to Hop Cones by Tetranychus urticae (Acari: Tetranychidae)

Environmental Entomology ◽

10.1093/ee/nvab008 ◽

2021 ◽

Author(s):

Joanna L Woods ◽

Anne E Iskra ◽

David H Gent

Keyword(s):

Risk Factors ◽

Tetranychus Urticae ◽

Crop Damage ◽

Equation Modeling ◽

Data Sets ◽

Current Management ◽

Late Season ◽

Model Based ◽

Predatory Arthropods ◽

Cone Damage

Abstract Twospotted spider mite (Tetranychus urticae Koch) is a cosmopolitan pest of numerous plants, including hop (Humulus lupulus L.). The most costly damage from the pest on hop results from infestation of cones, which are the harvested product, which can render crops unsalable if cones become discolored. We analyzed 14 yr of historical data from 312 individual experimental plots in western Oregon to identify risk factors associated with visual damage to hop cones from T. urticae. Logistic regression models were fit to estimate the probability of cone damage. The most predictive model was based on T. urticae-days during mid-July to harvest, which correctly predicted occurrence and nonoccurrence of cone damage in 91 and 93% of data sets, respectively, based on Youden’s index. A second model based on the ratio of T. urticae to predatory arthropods late in the season correctly predicted cone damage in 92% of data sets and nonoccurrence of damage in 77% of data sets. The model based on T. urticae abundance performed similarly when validated in 23 commercial hop yards, whereas the model based on the predator:prey ratio was relatively conservative and yielded false-positive predictions in 11 of the 23 yards. Antecedents of these risk factors were explored and quantified by structural equation modeling. A simple path diagram was constructed that conceptualizes T. urticae invasion of hop cones as dependent on prior density of the pest on leaves in early spring and summer, which in turn influences the development of predatory arthropods that mediate late-season density of the pest. In summary, the biological insights and models developed here provide guidance to pest managers on the likelihood of visual cone damage from T. urticae that can inform late-season management based on both abundance of the pest and its important predators. This is critically important because a formal economic threshold for T. urticae on hop does not exist and current management efforts may be mistimed to influence the pest when crop damage is most probable. More broadly, this research suggests that current management practices that target T. urticae early in the season may in fact predispose yards to later outbreaks of the pest.

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TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories

Information ◽

10.3390/info12050202 ◽

2021 ◽

Vol 12 (5) ◽

pp. 202

Author(s):

Louai Alarabi ◽

Saleh Basalamah ◽

Abdeltawab Hendawi ◽

Mohammed Abdalla

Keyword(s):

Infectious Diseases ◽

Infected Patient ◽

Public Health Problem ◽

Real Data ◽

Exposure Period ◽

Contact Tracing ◽

Data Sets ◽

Major Public Health Problem ◽

Real Time Processing ◽

Recent Developments

The rapid spread of infectious diseases is a major public health problem. Recent developments in fighting these diseases have heightened the need for a contact tracing process. Contact tracing can be considered an ideal method for controlling the transmission of infectious diseases. The result of the contact tracing process is performing diagnostic tests, treating for suspected cases or self-isolation, and then treating for infected persons; this eventually results in limiting the spread of diseases. This paper proposes a technique named TraceAll that traces all contacts exposed to the infected patient and produces a list of these contacts to be considered potentially infected patients. Initially, it considers the infected patient as the querying user and starts to fetch the contacts exposed to him. Secondly, it obtains all the trajectories that belong to the objects moved nearby the querying user. Next, it investigates these trajectories by considering the social distance and exposure period to identify if these objects have become infected or not. The experimental evaluation of the proposed technique with real data sets illustrates the effectiveness of this solution. Comparative analysis experiments confirm that TraceAll outperforms baseline methods by 40% regarding the efficiency of answering contact tracing queries.

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