Measure Of Information Content Research Articles

VSmartMOM: A vector matrix operator method-based radiative transfer model linearized with respect to aerosol properties

In this paper, we build up on the scalar model smartMOM to arrive at a formalism for linearized vector radiative transfer based on the matrix operator method (vSmartMOM). Improvements have been made with respect to smartMOM in that a novel method of computing intensities for the exact viewing geometry (direct raytracing) without interpolation between quadrature points has been implemented. Also, the truncation method employed for dealing with highly peaked phase functions has been changed to a vector adaptation of Wiscombe's delta-m method. These changes enable speedier and more accurate radiative transfer computations by eliminating the need for a large number of quadrature points and coefficients for generalized spherical functions.We verify our forward model against the benchmarking results of Kokhanovsky et al. (2010) [22]. All non-zero Stokes vector elements are found to show agreement up to mostly the seventh significant digit for the Rayleigh atmosphere. Intensity computations for aerosol and cloud show an agreement of well below 0.03% and 0.05% at all viewing angles except around the solar zenith angle (60°), where most radiative models demonstrate larger variances due to the strongly forward-peaked phase function.We have for the first time linearized vector radiative transfer based on the matrix operator method with respect to aerosol optical and microphysical parameters. We demonstrate this linearization by computing Jacobian matrices for all Stokes vector elements for a multi-angular and multispectral measurement setup. We use these Jacobians to compare the aerosol information content of measurements using only the total intensity component against those using the idealized measurements of full Stokes vector [I,Q,U,V] as well as the more practical use of only [I,Q,U]. As expected, we find for the considered example that the accuracy of the retrieved parameters improves when the full Stokes vector is used. The information content for the full Stokes vector remains practically constant for all azimuthal planes, while that associated with intensity-only measurements falls as we approach the plane perpendicular to the principal plane. The [I,Q,U] vector is equivalent to the full Stokes vector in the principal plane, but its information content drops towards the perpendicular plane, albeit less sharply than I-only measurements.

Exploiting disjointness axioms to improve semantic similarity measures

Representing domain knowledge in biology has traditionally been accomplished by creating simple hierarchies of classes with textual annotations. Recently, expressive ontology languages, such as Web Ontology Language, have become more widely adopted, supporting axioms that express logical relationships other than class-subclass, e.g. disjointness. This is improving the coverage and validity of the knowledge contained in biological ontologies. However, current semantic tools still need to adapt to this more expressive information. In this article, we propose a method to integrate disjointness axioms, which are being incorporated in real-world ontologies, such as the Gene Ontology and the chemical entities of biological interest ontology, into semantic similarity, the measure that estimates the closeness in meaning between classes. We present a modification of the measure of shared information content, which extends the base measure to allow the incorporation of disjointness information. To evaluate our approach, we applied it to several randomly selected datasets extracted from the chemical entities of biological interest ontology. In 93.8% of these datasets, our measure performed better than the base measure of shared information content. This supports the idea that semantic similarity is more accurate if it extends beyond the hierarchy of classes of the ontology. joao.ferreira@lasige.di.fc.ul.pt. Supplementary data are available at Bioinformatics online.

Information content of kinetic measurements and inverse problems of chemical kinetics

position (parallelism) of these problems rather than the CPU time reduction in solving inverse problems. Parallelism is meant to be partition of the entire prob� lem into subproblems of lower dimension. Analysis of these subproblems significantly increases the reliabil� ity of the solution of inverse problems. The possibili� ties of such “internal parallelisms” should follow from the physical content of the problems to be solved. The major problem solved in this work is to create a method that can significantly simplify study of the information content of kinetic models of complex reactions. This method is based on the graph theoreti� cal analysis [4] of independent routes [5, 6]. Analysis of the information content of a complex reaction scheme consists in analysis of the information content of the schemes responsible for the reaction that occurs along each of the independent routes. Instead of one complex system, we deal with several significantly simpler systems. The number of simplified systems is equal to the number of independent routes.

Accurary of Oxygen Desaturation of Hemoglobin in Muscle by Near-Infrared Oximeters

Dear Editor-in-Chief A recent article (1) has demonstrated that maximal lactate steady state can be accurately determined in healthy subjects in response to an incremental cycling test up to exhaustion based on measures by near-infrared spectroscopy (NIRS) of vastus lateralis deoxygenated hemoglobin concentration (HHb) (considered as an index of O2 extraction). Although the proposed method is very interesting in sports science, the presentation of the NIRS technique and the NIRS muscle oxygenation data are incomplete and raise questions about some of the conclusions drawn by the authors. For measuring muscle oxygenation, Bellotti et al. (1) used a multidistance frequency-domain oximeter (rather than a continuous-wave instrument as stated by the authors), commercially introduced in 1998, and equipped with a rigid muscle probe in which four source-detector distances ranging from 2 to 3.5 cm implement a multidistance data collection (2). Given typical values of the near-infrared optical properties in muscle tissue (absorption coefficient approximately 0.08 cm−1, reduced scattering coefficient approximately 6 cm−1), the mean and maximal penetration depths can be estimated at about 1 and 2–2.5 cm, respectively (5). Accordingly, the continuous-wave technique adopted in the most recent portable/wearable/wireless devices provides a typical depth sensitivity of approximately 1.5 cm (3) and not 3 cm as stated by Bellotti et al. (1). Although NIRS undoubtedly offers several advantages for muscle studies (4), some questions (other than its applicability to subjects with a thick fat layer) are still open: for instance, 1) the contribution of myoglobin desaturation to the NIRS signal during exercise; 2) the effect of scattering changes during exercise; 3) the effect of changes in skin perfusion, particularly during prolonged exercise; and 4) the lack of standardization for NIRS instrumentation (3). Bellotti et al. (1) as well as other researchers in the past have evaluated the kinetics of muscle oxygenation using continuous-wave or frequency-domain oximeters and have drawn the physiological conclusions of their studies on the basis of the interpretation of the changes in HHb only. HHb changes (reported erroneously by the authors in their Fig. 1 as millimolar instead of micromolar) might represent tissue oxygenation changes only when tHb (tHb = O2Hb + HHb) is stable (3). Unfortunately, Bellotti et al. (1) did not report or comment on changes in tHb that are necessary for a correct interpretation of muscle oxygenation changes. NIRS oximeters offer the great advantage to also provide measurements of muscle hemoglobin saturation (SmO2), expressed in percent (%). This parameter reflects the dynamic balance between O2 supply in the muscle microcirculation and O2 consumption demand by the muscle. In addition, SmO2 measurements are unaffected by a systematic bias in absorption measurements and, compared with HHb measurements, are not as sensitive to the optical coupling to tissue and to the superficial skin/fat layers. As recently suggested (6), the combined measurement of changes in HHb, O2Hb, and SmO2 allows for novel comparisons of these variables during exercise. Considering the significant physiological information content of NIRS measurements, we recommend that NIRS studies report HHb, O2Hb, and SmO2 data for a comprehensive characterization and thorough discussion of the results. Valentina Quaresima Marco Ferrari Department of Life, Health, and Environmental Sciences University of L’Aquila L’Aquila, Italy Sergio Fantini Department of Biomedical Engineering Tufts University Medford, MA

A new approach for measuring the work and quality of histopathology reporting

Cancer datasets drive report quality, but require more work to inform compliant reports. The aim of this study was to correlate the number of words with measures of quality, to examine the impact of the drive for improved quality on the workload of histopathology reporting over time. We examined the first 10 reports of colon, breast, renal, lung and ovarian carcinoma, melanoma resection, nodal lymphoma appendicitis and seborrhoeic keratosis (SK) issued in 1991, 2001 and 2011. Correlations were analysed using Pearson's partial correlation coefficients. Word count increased significantly over time for most specimen types examined. Word count almost always correlated with units of information, indicating that the word count was a good measure of the amount of information contained within the reports; this correlation was preserved following correction for the effect of time. A good correlation with compliance with cancer datasets was also observed, but was weakened or lost following correction for the increase in word count and units of information that occurred between time points. These data indicate that word count could potentially be used as a measure of information content if its integrity and usefulness are continuously validated. Further prospective studies are required to assess and validate this approach.

The information content of stock markets around the world: A cultural explanation

We draw on the psychology literature on cross-country cultural differences to explain the information content of stock markets around the world. We show that cultural dimensions in the studies of Hofstede (1980, 2001) such as individualism and uncertainty avoidance closely relate to several behavioral biases widely discussed in accounting and finance research. These cultural dimensions also signal different risk preferences. We argue that behavioral biases and risk preferences influence how international investors act on firm-specific information and empirically test whether individualism and uncertainty avoidance indexes can explain the cross-country information content of stock markets. We compute R2 from the market model to measure the general information content of stock markets in the long term, abnormal return variance, and abnormal trading volume around earnings announcements to measure the short-term information content of earnings announcements. Using more than 150,000 earnings announcements from 42 countries for the period 1990–2006, we find that the information content of stock markets is higher in more individualistic countries and in low uncertainty-avoiding countries. The relations between cultural dimensions and measures of information content are robust to the inclusion of several control variables or the use of updated cultural indexes that account for possible changes in cultures over time.

HydroZIP: How Hydrological Knowledge can Be Used to Improve Compression of Hydrological Data

From algorithmic information theory, which connects the information content of a data set to the shortest computer program that can produce it, it is known that there are strong analogies between compression, knowledge, inference and prediction. The more we know about a data generating process, the better we can predict and compress the data. A model that is inferred from data should ideally be a compact description of those data. In theory, this means that hydrological knowledge could be incorporated into compression algorithms to more efficiently compress hydrological data and to outperform general purpose compression algorithms. In this study, we develop such a hydrological data compressor, named HydroZIP, and test in practice whether it can outperform general purpose compression algorithms on hydrological data from 431 river basins from the Model Parameter Estimation Experiment (MOPEX) data set. HydroZIP compresses using temporal dependencies and parametric distributions. Resulting file sizes are interpreted as measures of information content, complexity and model adequacy. These results are discussed to illustrate points related to learning from data, overfitting and model complexity.

Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database

With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed.

Comparative Value-Relevance of GAAP, IBES, S&P Core, Cash Earnings and Cash Flows

This study examines the impact the global financial crisis had on the value relevance of GAAP and non-GAAP earnings. We adopt the Ohlson (1995) valuation and CAR models to test the value relevance and information content of alternative earnings measures. We use six different earnings measures comprising IBES earnings, Standard & Poor’s (S&P) core earnings, cash earnings, cash flows from operations, earnings from operations adjusted to exclude special items under GAAP and income before extraordinary items under GAAP. We draw our sample from US publicly traded firms between 2002 and 2010. Our sample is partitioned into Financial and non-Financial firms, and S&P 500 and non-S&P 500 firms. The results show that investors place greater value relevance on GAAP earnings during the GFC period relative to the pre-GFC period.

New Inequalities between Information Measures of Network Information Content

We refine a classical logarithmic inequality using a discrete case of Bernoulli inequality, and then we refine furthermore two information inequalities between information measures for graphs, based on information functionals, presented by Dehmer and Mowshowitz in (2010) as Theorems 4.7 and 4.8. The inequalities refer to entropy-based measures of network information content and have a great impact for information processing in complex networks (a subarea of research in modeling of complex systems).

Extracting conflict-free information from multi-labeled trees

BackgroundA multi-labeled tree, or MUL-tree, is a phylogenetic tree where two or more leaves share a label, e.g., a species name. A MUL-tree can imply multiple conflicting phylogenetic relationships for the same set of taxa, but can also contain conflict-free information that is of interest and yet is not obvious.ResultsWe define the information content of a MUL-tree T as the set of all conflict-free quartet topologies implied by T, and define the maximal reduced form of T as the smallest tree that can be obtained from T by pruning leaves and contracting edges while retaining the same information content. We show that any two MUL-trees with the same information content exhibit the same reduced form. This introduces an equivalence relation among MUL-trees with potential applications to comparing MUL-trees. We present an efficient algorithm to reduce a MUL-tree to its maximally reduced form and evaluate its performance on empirical datasets in terms of both quality of the reduced tree and the degree of data reduction achieved.ConclusionsOur measure of conflict-free information content based on quartets is simple and topologically appealing. In the experiments, the maximally reduced form is often much smaller than the original tree, yet retains most of the taxa. The reduction algorithm is quadratic in the number of leaves and its complexity is unaffected by the multiplicity of leaf labels or the degree of the nodes.

An inter industry analysis of EVA<SUP align="right">®</SUP> versus traditional corporate financial performance measures: evidence from Indian market

The main purpose of this paper is to test the efficacy of economic value added (EVA) and traditional performance measures in Indian industries. Using data from 23 Indian industries for a period of 2000–2009, the present study applies pooled data regression to test the relative and incremental information content of EVA and other conventional financial performance measures in explaining the market value added. Regression analysis indicate that net income (NI), net operating profits after taxes (NOPAT), cash flow from operations (OCF), earnings per share (EPS) and even residual income (RI) in some industries outperform EVA in explaining the changes in MVA in majority of the industries during the study period. The results of the present study fail to support the hypothesis as EVA although exhibit significant association with MVA but underperform traditional measures in explaining the MVA in majority of the sample industries. Thus, overall results refute the claim of EVA superiority in explaining the MVA as compared to traditional measures.

Indian Banking and Information Content of EVA and Traditional Measures

The rationale behind the study lies in the facts that about superiority of EVA over traditional matrices is mixed and were focused on manufacturing sectors. Hence, relationship between the Market Value Added (MVA), EVA, and accounting performance measures such as net earnings (PAT), earning per share (EPS), return on investment (ROI), return on net worth (RONW), and return on capital employed, Economic Value Added (EVA), and Market value Added (MVA) has not been grossly researched to Indian Banking Sector. The data has been collected through most worthy ‘PROWESS’ database of Centre for monitoring Indian Economy (CMIE). The reference period of the study is fourteen financial years i.e. 2000-2013.The multiple regression and Biddle’s et. al. (1997), Bao and Bao (1998) approach is selected for studying relative and incremental informational of EVA vis-a-vis other traditional financial performance measures. The result of cross-section regression reveals that earning (PAT) having highest explanatory power than EVA, ROI and EPS to explain market value added by sample banks. Fourth, the relative and incremental informational test present that The PAT having highest relative explanatory (66.7 percent) power do explain market value added as compared to EVA, ROI, EPS, ROCE alone and the relative informational content of EVA is lower than PAT, which, accounting for only 57.4 present of variation in market value added (MVA). Thus, the usefulness of EVA for decision making can’t be ruled out based on the results and it can be used as an internal as well as external performance measurer. As Solomon (1965) suggested that residual income be used as an internal performance measure and Anthony (1973, 1982, and 1982) suggested that it is suitable to measure external performance.

Sum of parts is greater than the whole: inference of common genetic history of populations

BackgroundReconstructability of population history, from genetic information of extant individuals, is studied under a simulation setting. We do not address the issue of accuracy of the reconstruction algorithms: we assume the availability of the theoretical best algorithm. On the other hand, we focus on the fraction (1 - f) of the common genetic history that is irreconstructible or impenetrable. Thus the fraction, f, gives an upper bound on the extent of estimability. In other words, there exists no method that can reconstruct a fraction larger than f of the entire common genetic history. For the realization of such a study, we first define a natural measure of the amount of genetic history. Next, we use a population simulator (from literature) that has at least two features. Firstly, it has the capability of providing samples from different demographies, to effectively reflect reality. Secondly, it also provides the underlying relevant genetic history, captured in its entirety, where such a measure is applicable. Finally, to compute f, we use an information content measure of the relevant genetic history. The simulator of choice provided the following demographies: Africans, Europeans, Asians and Afro-Americans.ResultsWe observe that higher the rate of recombination, lower the value of f, while f is invariant over varying mutation rates, in each of the demographies. The value of f increases with the number of samples, reaching a plateau and suggesting that in all the demographies at least about one-third of the relevant genetic history is impenetrable. The most surprising observation is that the the sum of the reconstructible history of the subsegments is indeed larger than the reconstructible history of the whole segment. In particular, longer the chromosomal segment, smaller the value of f, in all the demographies.ConclusionsWe present the very first framework for measuring the fraction of the relevant genetic history of a population that is mathematically elusive. Our observed results on the tested demographies suggest that it may be better to aggregate the analysis of smaller chunks of chromosomal segments than fewer large chunks. Also, no matter the richness of samples in a population, at least one-third of the population genetic history is impenetrable. The framework also opens up possible new lines of investigation along the following. Given the characteristics of a population, possibly derived from observed extant individuals, to estimate the (1) optimal sample size and (2) optimal sequence length for the most informative analysis.

Why Did High Productivity Growth of Banks Precede the Financial Crisis?

The observed high levels of banks’ operating efficiency, profi ts and market values in the years before the fi nancial crisis raise reasonable doubts about the information content of conventional performance measures for the accurate assessment of the effi ciency of banking intermediation. In this paper we estimate the productivity of individual Spanish banks and the industry’s productivity growth over time using the methodology of Olley and Pakes (1996) and Levinsohn and Petrin (2003), which controls for simultaneity bias. We then examine the contributions of two sets of factors to productivity growth: banking practices that have been signalled as the proximate causes of the crisis, and technical progress in the industry. We obtain that more than two thirds of the estimated productivity growth in the years 2000-2007 is attributable to practices such as the expansion of the housing market, the high recourse to securitization and short-term fi nance, and the leveraging of banks’ balance sheets. The remaining 2.8% cumulative annual growth rate is our estimate for the technical progress in the industry, similar to the estimated rate in the period 1993-2000.

Semantic similarity in the biomedical domain: an evaluation across knowledge sources

BackgroundSemantic similarity measures estimate the similarity between concepts, and play an important role in many text processing tasks. Approaches to semantic similarity in the biomedical domain can be roughly divided into knowledge based and distributional based methods. Knowledge based approaches utilize knowledge sources such as dictionaries, taxonomies, and semantic networks, and include path finding measures and intrinsic information content (IC) measures. Distributional measures utilize, in addition to a knowledge source, the distribution of concepts within a corpus to compute similarity; these include corpus IC and context vector methods. Prior evaluations of these measures in the biomedical domain showed that distributional measures outperform knowledge based path finding methods; but more recent studies suggested that intrinsic IC based measures exceed the accuracy of distributional approaches. Limitations of previous evaluations of similarity measures in the biomedical domain include their focus on the SNOMED CT ontology, and their reliance on small benchmarks not powered to detect significant differences between measure accuracy. There have been few evaluations of the relative performance of these measures on other biomedical knowledge sources such as the UMLS, and on larger, recently developed semantic similarity benchmarks.ResultsWe evaluated knowledge based and corpus IC based semantic similarity measures derived from SNOMED CT, MeSH, and the UMLS on recently developed semantic similarity benchmarks. Semantic similarity measures based on the UMLS, which contains SNOMED CT and MeSH, significantly outperformed those based solely on SNOMED CT or MeSH across evaluations. Intrinsic IC based measures significantly outperformed path-based and distributional measures. We released all code required to reproduce our results and all tools developed as part of this study as open source, available under http://code.google.com/p/ytex. We provide a publicly-accessible web service to compute semantic similarity, available under http://informatics.med.yale.edu/ytex.web/.ConclusionsKnowledge based semantic similarity measures are more practical to compute than distributional measures, as they do not require an external corpus. Furthermore, knowledge based measures significantly and meaningfully outperformed distributional measures on large semantic similarity benchmarks, suggesting that they are a practical alternative to distributional measures. Future evaluations of semantic similarity measures should utilize benchmarks powered to detect significant differences in measure accuracy.

Detection of long-term change in hydroelectric reservoir inflows: Bridging theory and practise

We studied long-term monotonic trend in inflow volume to 20 reservoirs, plus a measure of system-wide hydroelectric power potentially available for generation, in British Columbia, Canada. The primary analysis involved application of a linear method with explicit signal-to-noise ratio (S:N) estimation to monthly and annual mean inflows over the period of record common to all basins, providing a broad and convenient overview of changes across the hydroelectric system. Additional analyses then investigated the sensitivity of the results to methodological choices, focussing on annual inflow volume for eight indicator basins and system power. In these auxiliary analyses, alternative data selection and processing schemes were explored: full period of record for each indicator basin; residual after Pacific Decadal Oscillation signal removal; and data from streamgauges on catchments within or near each indicator basin. Alternative analysis techniques were also applied: nonparametric Spearman rank correlation with adjustment for serial dependence; change point detection using Mann–Whitney sliding window analysis; and visual assessment of data low-pass filtered using polynomial fits of various orders. Finally, we studied changes in year-to-year water supply variability, employing a split-sample approach implemented using a standard F-test; a nonparametric Ansari–Bradley test; and a novel Monte Carlo-based test on the Shannon entropy, a measure of hydroclimatic information content. The results provided no substantial evidence for decreased annual water supply and pointed to some increases; seasonal inflow pattern shifts were also detected for many basins, in particular a wintertime flow increase. The split-sample tests yielded no evidence for shifts in the volatility and predictability of annual inflow. One of the more intriguing and perhaps broadly important findings was that methodological choices ultimately made little difference to final outcomes.

Using passive remote sensing to retrieve the vertical variation of cloud droplet size in marine stratocumulus: An assessment of information content and the potential for improved retrievals from hyperspectral measurements

We present a theoretical study into the information content of solar reflectance measurements at multiple near‐infrared wavelengths in the context of deriving the vertical variation of cloud droplet size from marine stratocumulus. We employ a Bayesian optimal estimation approach to retrieve a profile of droplet effective radius as a function of optical depth in the cloud. This allows an assessment of the information content of the measurement of reflectance at different wavelengths and the potential for a new generation of hyperspectral sensors to improve the retrieval. Our results show that using the three absorbing near‐infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) centered at 1.6, 2.1 and 3.7 μm a retrieval of droplet sizes lower in the cloud is highly sensitive to small changes in reflectance. Consequently instrument and modeling errors must be reduced to <1% in order to gain a useful uncertainty constraint on droplet size near to cloud base. By introducing many high spectral resolution wavelength channels, such as those available from hyperspectral sensors, we find that the information content pertaining to all retrieval variables increases significantly. This results in a reduction in the uncertainty estimates on all retrieved quantities. We also test the ability of a vertical profile retrieval to provide improved liquid water path estimates by using several in situ profiling measurements of marine stratocumulus in the South‐East Pacific region. We find that a vertical profile retrieval significantly improves the liquid water path estimate when compared to a two‐band lookup table retrieval.

A spectral order for infinite-dimensional quantum spaces

In this paper we extend the spectral order of Coecke and Martin to infinite-dimensional quantum states. Many properties present in the finite-dimensional case are preserved, but some of the most important are lost. The order is constructed and its properties analysed. Most of the useful measurements of information content are lost. Shannon entropy is defined on only a part of the model, and that part is not a closed subset of the model. The finite parts of the lattices used by Birkhoff and von Neumann as models for classical and quantum logic appear as subsets of the models for infinite classical and quantum states.

Information content in Lagrangian sensor measurements for reservoir characterization

The prospect of injecting particles or sensors of sufficiently small size into reservoirs for improved reservoir characterization has become an active topic of research, yet little is known about the possible improvements in model resolution or reduction in uncertainty that could be achieved through in-situ sensor observations. In this paper, we investigate the information content provided by potential repeated measurements of particle pressure and/or location for particles that are transported passively with an injected fluid in heterogeneous reservoirs.Observations of locations of drifting particles at relatively frequent intervals provide substantial reduction in uncertainty in reservoir properties, except in regions through which the particles are unable to travel. Low permeability regions within flow zones, however, do affect the flow paths and are mapped relatively well through assimilation of the data. Pressure observations appear to be much less useful than observations of location, except in the neighborhood of wells where pressure gradients are quite high. The reservoir properties near the well, however, can be estimated relatively well using pressure data at wells.The results of this study show quantitatively that potential Lagrangian sensor measurements can provide additional information compared to standard production data for reservoir characterization. Despite the small size of the sensors, the model resolution is limited due to the spatial averaging in the sensitivity of the Lagrangian data to reservoir model parameters. High frequency of sensor measurements can improve the model resolution, but the improvement is marginal unless the accuracy of the measurements is quite high.