General Correlation Model Research Articles

Waveform Designs for Joint Wireless Communication and Radar Sensing: Pitfalls and Opportunities

Special attention has been devoted to joint wireless communication and radar sensing concepts over the past decades. Considerable confusion arose, however, with regard to waveform designs. In this paper, various joint wireless communication and radar sensing waveform schemes are reviewed and classified into two categories. Disadvantages and limitations of each category are clarified theoretically. It is shown that waveforms designed merely in conventional time and frequency domains cannot fulfill the conflict requirements posed by radar and wireless communication. As a solution to this fundamental challenge, the multidimensional waveform concepts, along with a generalized correlation model, are proposed for joint wireless communication and radar sensing. To showcase our current research advances in this emerging area, several concrete waveforms designed in multiple dimensions are introduced. Theoretical analysis is validated by simulations and outfield demonstration experiments. It is shown that the suggested waveforms can simultaneously achieve superior detection and communication performances with shared spectrum resources.

Monitoring simple linear profiles in the presence of within‐ and between‐profile autocorrelation

AbstractThe current study investigates the effect of within‐profile and between‐profile autocorrelations on the performance of four monitoring methods of simple linear profiles in Phase II. To this end, a general correlation model between error terms is considered such that the correlation structure of within‐profiles errors and the error terms between consecutive profiles follow an autoregressive (AR) times series model of order one. Extensive simulations have been done to assess the effect of both autocorrelation types and the profile size on the estimations of the model parameters as well as the performance of control charts. The performance of the monitoring schemes is investigated and compared with respect to the average run length (ARL) metric. The simulation study results show that the autocorrelation within and between profiles has a negative impact on the monitoring technique's performance. It reduces the control chart's ability to detect process shifts compared to no or weak autocorrelation cases. Moreover, the performance of all the methods is improved by increasing the profile size. An illustrative example is also provided to demonstrate the use of the proposed methods for monitoring the stability of profiles in the chemical industry.

THE EFFICIENCY RESEARCH OF MIMO SYS-TEMS WITH CORRELATED ELEMENTS OF A CHANNEL TRANSMISSION MATRIX

Currently, there is an active development of wireless data transmission systems. A solution widely used in improving existing and creating new wireless communication technologies, which allows increasing spectral efficiency and transmission speed, is the use of systems with Multiple-Input-Multiple-Output, MIMO. In this regard, research into the potential capabilities of MIMO systems under various operating conditions is an urgent task. In particular, the issue of the influence of the correlation of transmission matrix elements on the efficiency of the communication system is important. We will further consider cases of multipath propagation typical for urban conditions. We will also consider the signals transmitted by different antennas to be narrowband and independent of each other. For the two currently most commonly used MIMO radio channel models, the influence of the correlation between the elements of the transmission channel matrix on the efficiency of the MIMO system was studied using statistical tests. Dependences of the error probability per bit of transmitted information on the signal-to-noise ratio were obtained for channels with transmission matrices whose covariance matrices have varying degrees of difference from the diagonal (unit) matrix. When generating channel matrices with correlated elements, the unstructured (general correlation) model and the Kronecker model are used.

EFFICIENCY OF MIMO SYSTEMS WITH TRANSMISSION CHANNEL MATRIX CORRELATION ELEMENTS

Researching the potential capabilities of MIMO systems under various operating conditions is an urgent task. In particular, the issue of the influence of the correlation of the elements of the transmission matrix on the efficiency of the communication system is important. For the currently most commonly used MIMO radio channel model, the influence of the correlation between the elements of the transmission channel matrix on the efficiency of the MIMO system was studied using statistical tests. The dependences of the error probability per bit of transmitted information on the signal-to-noise ratio were obtained for channels with covariance matrices that have varying degrees of difference from the covariance matrix with uncorrelated elements. When generating channel matrices with correlated elements, the unstructured (general correlation) model and the Kronecker model are used.

Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).

Recently, two-dimensional-to-three-dimensional (2D-3D) deformable registration has been applied to deform liver tumor contours from prior reference images onto estimated cone-beam computed tomography (CBCT) target images to automate on-board tumor localizations. Biomechanical modeling has also been introduced to fine-tune the intra-liver deformation-vector-fields (DVFs) solved by 2D-3D deformable registration, especially at low-contrast regions, using tissue elasticity information and liver boundary DVFs. However, the caudal liver boundary shows low contrast from surrounding tissues in the cone-beam projections, which degrades the accuracy of the intensity-based 2D-3D deformable registration there and results in less accurate boundary conditions for biomechanical modeling. We developed a deep-learning (DL)-based method to optimize the liver boundary DVFs after 2D-3D deformable registration to further improve the accuracy of subsequent biomechanical modeling and liver tumor localization. The DL-based network was built based on the U-Net architecture. The network was trained in a supervised fashion to learn motion correlation between cranial and caudal liver boundaries to optimize the liver boundary DVFs. Inputs of the network had three channels, and each channel featured the 3D DVFs estimated by the 2D-3D deformable registration along one Cartesian direction (x, y, z). To incorporate patient-specific liver boundary information into the DVFs, the DVFs were masked by a liver boundary ring structure generated from the liver contour of the prior reference image. The network outputs were the optimized DVFs along the liver boundary with higher accuracy. From these optimized DVFs, boundary conditions were extracted for biomechanical modeling to further optimize the solution of intra-liver tumor motion. We evaluated the method using 34 liver cancer patient cases, with 24 for training and 10 for testing. We evaluated and compared the performance of three methods: 2D-3D deformable registration, 2D-3D-Bio (2D-3D deformable registration with biomechanical modeling), and DL-Bio (DL model prediction with biomechanical modeling). The tumor localization errors were quantified through calculating the center-of-mass-errors (COMEs), DICE coefficients, and Hausdorff distance between deformed liver tumor contours and manually segmented "gold-standard" contours. The predicted DVFs by the DL model showed improved accuracy at the liver boundary, which translated into more accurate liver tumor localizations through biomechanical modeling. On a total of 90 evaluated images and tumor contours, the average (± sd) liver tumor COMEs of the 2D-3D, 2D-3D-Bio, and DL-Bio techniques were 4.7 ± 1.9mm, 2.9 ± 1.0mm, and 1.7 ± 0.4mm. The corresponding average (± sd) DICE coefficients were 0.60 ± 0.12, 0.71 ± 0.07, and 0.78 ± 0.03; and the average (± sd) Hausdorff distances were 7.0 ± 2.6mm, 5.4 ± 1.5mm, and 4.5 ± 1.3mm, respectively. DL-Bio solves a general correlation model to improve the accuracy of the DVFs at the liver boundary. With improved boundary conditions, the accuracy of biomechanical modeling can be further increased for accurate intra-liver low-contrast tumor localization.

Generalized estimating equations for analyzing multivariate survival data

Generalized estimating equations (GEE) approach has been used to estimate the parameters in semiparametric accelerated failure time (AFT) models with clustered and censored data. However, the working correlation model has a substantial impact on estimator efficiency when using the GEE method. This article proposes a general correlation model to incorporate the correlations among the clustered and censored data and protect against avoidable loss of efficiency associated with misspecified correlation structure. The proposed estimator is consistent and asymptotically normal. Simulation studies are carried out to demonstrate the effectiveness of the proposed method. Finally, a real dataset from a toxicology study is analyzed for illustration.

Particle-Laden Bubble Size and Its Distribution in Microstructured Bubbling Bed in the Presence and Absence of a Surface Active Agent

This work reports experimental measurements of the bubble size and its distribution in the three-phase (air–water–coal and air–water–coal–surfactant) system. A thorough investigation of the effect of particle concentration, particle size, viscosity, and axial positions on bubble size and its distribution in the presence and absence of the surfactant is reported. Bubble size distribution (BSD) in three different experimental conditions is studied which follows the beta, Weibull, and log–logistic nature of the distribution function. Correlations are developed for estimation of parameters of each distribution function. A generalized correlation model is also developed for the estimation of the Sauter mean bubble diameter, aspect ratio, and interfacial area in the three-phase system by considering operating, geometric variables, and physical properties of the system. The current work will be useful for process intensification of chemical and biochemical processes based on the interfacial phenomena.

FRICTIONAL PRESSURE DROP OF GAS–LIQUID–LIQUID DISPERSION IN AN EJECTOR-INDUCED DOWNFLOW COLUMN

The dispersion of gas-aided immiscible liquids in the ejector-induced downflow column has an advantage for the separation of contaminants in wastewater and the synthesis of various chemicals in the chemical and biochemical industries. To design scale-up and studies on the kinetics of liquid–liquid reactions in the downflow system, the hydrodynamics characteristics are essential elements. Several other issues regarding the hydrodynamic characteristics should be addressed in the downflow unit with the gas-aided liquid–liquid system. In the present study, the frictional pressure drop of gas–liquid–liquid dispersion was investigated in a gas-aided liquid–liquid downflow column. Two different liquids, water–paraffin and water–kerosene of different viscosities and densities were studied and analyzed in detail. Different models such as Lockhart–Martinelli, Kato, Wallis, and Gharat and Joshi models were considered to interpret the results based on the present operating conditions. A general correlation model was also developed based on the experimental results incorporating dynamic, geometric, and physical properties of the system. The present study may be useful for further understanding of the liquid–liquid operation for industrial applications.

Asymptotic Performance Analysis of Massive MIMO Relay Systems With Multi-Pair Devices Over Correlated Fading Channels

In this paper, we investigate a relay system with multi-pair single-antenna devices, where massive antenna array (also known as massive multiple-input-multiple-output (MIMO) technology) is deployed at the relay with low-complexity maximum-ratio combining/maximum-ratio transmission precoding scheme. By combining massive MIMO and relay cooperation, the performance of relay-assisted communication systems is predicted to be dramatically improved in many areas, e.g., spectral efficiency, energy efficiency, inter-user interference cancelation, and so on, by exploring the abundant spatial degree of freedom of massive MIMO. However, a large number of antennas employed at relay node inevitably leads to antenna correlation because of small antenna spacing subjected to the limited size of the relay node, which may affect the system performance and has not yet been compressively studied. Thus, we focus on analyzing the effect of antenna correlation on the asymptotic performance of system ergodic rate by using a general channel correlation model. First, by means of the deterministic equivalent technology, the analytical expression of the ergodic rate with arbitrary channel correlations is derived, which presents the quantitative relations among system parameters, i.e., the numbers of relay antennas and device-pairs, the channel spatial correlations at the relay's receiver side and the transmitter side, and the transmit powers of the source devices and the relay. By using a general scaling model for system parameters with respect to the relay antenna number, the asymptotic performance of the ergodic rate under spatially correlated channel and the corresponding scaling laws of the system parameters are obtained, which provides useful guidelines to trade off the transmit power and the ergodic rate as well as the number of the served device-pairs. It is further revealed that the influence degrees of the antenna correlations at the relay's receiver and the transmitter on the ergodic rate is nearly the same. Finally, the analytical conclusions are justified through the numerical simulations.

Throughput-Optimal Scheduling and Rate Adaptation for Reduced Feedback Best- $M$ Scheme in OFDM Systems

In orthogonal frequency division multiplexing systems, reduced feedback schemes provide essential channel state information from the users to the base station (BS) without overwhelming the uplink. For the practically important best- $M$ scheme, in which each user feeds back only its $M$ strongest subchannels and their indices to the BS, we derive a novel, throughput-optimal scheduling and rate adaptation policy that enables the BS to schedule the best user and its data rate for all the subchannels. The policy exploits the structure of the information fed back by the best- $M$ scheme and the correlation among subchannel gains. We present it in closed-form for the widely studied exponential correlation model. Using insights gleaned from the optimal policy, we propose a novel, low-complexity two subchannel reduction approach, which is seen empirically to be near-optimal and easily handles practically important general channel correlation models, quantized feedback, and co-channel interference in multi-cell scenarios. Compared with several ad hoc approaches, the proposed approaches improve the cell throughput without any additional feedback. A modified gradient-based opportunistic scheduler is also proposed to ensure user fairness.

Surface tension of refrigerants: A new correlation using the boiling point as reference

A new general corresponding-states correlation model for the calculation of the surface tension of refrigerants is proposed. The main difference with respect to other models available in the literature is that, in addition to the critical point temperature, the proposed model includes the temperature and surface tension values at the boiling point as input properties to define the reduced (non-dimensional) properties. Only three general adjustable coefficients are needed, which were obtained by a fitting procedure to the data presently available for 80 refrigerants. Averaged absolute deviations below 9.5% are found in all cases, being below 5% for 67 out of the 80 fluids considered. Results for another four corresponding-states models available in the literature are also obtained. The correlation model proposed here gives clearly better overall results, and it is the only one including exclusively temperature and surface tension values as inputs.

Exceptionally monotone models—the rank correlation model class for Exceptional Model Mining

Exceptional Model Mining strives to find coherent subgroups of the dataset where multiple target attributes interact in an unusual way. One instance of such an investigated form of interaction is Pearson's correlation coefficient between two targets. EMM then finds subgroups with an exceptionally linear relation between the targets. In this paper, we enrich the EMM toolbox by developing the more general rank correlation model class. We find subgroups with an exceptionally monotone relation between the targets. Apart from catering for this richer set of relations, the rank correlation model class does not necessarily require the assumption of target normality, which is implicitly invoked in the Pearson's correlation model class. Furthermore, it is less sensitive to outliers. We provide pseudocode for the employed algorithm and analyze its computational complexity, and experimentally illustrate what the rank correlation model class for EMM can find for you on six datasets from an eclectic variety of domains.

The diversity of STF-coded MIMO-OFDM systems with a general correlation model

Owing to insufficient antenna spaces, mobile scenarios, and multipaths in practice, transmission correlations in space, time, and frequency domains are inevitable in wireless communications. This paper studies the effect of general spatial, temporal, and frequency/path correlations on the performance of space-time-frequency (STF)-coded multiple-input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems over frequency-selective block-fading channels. Specifically, we first derive an upper bound on the maximum achievable diversity by Hadamard and tensor products and analyze the effect of general spatial, temporal, and frequency/path correlations on it using rank properties of block matrices. We then address STF code designs and give two examples, one traditional STF code and another quasi-SF code, to show that our upper bound on the maximum diversity is achievable. The decoding complexity is considered in the MIMO system with arbitrary correlated fading channels using the traditional STF code. We also identify the newly developed statistical channel models for MIMO LTE and 802.11n as special cases of our STF-coded MIMO-OFDM system by showing that our theoretical diversity results match those simulated from these statistical channel models. Finally, we show that our general diversity result recovers various maximum diversity gains for different special correlation scenarios that have appeared in the literature.

Oxygen Mass Transfer in an Aerated Stirred Tank with Double Impellers: A Generalized Correlation Including Spacing Impact

Stirred aerated tanks by double impellers are used in fermentation and various biological processes for water treatment, food industry, and pharmaceutical production. In this study, a generalized correlation model was developed for the dependent parameter (kla/N). The oxygen mass transfer from air to liquid takes place by rotating the double impellers (IBRC and PBPU) in the aerated tank. This model considers Reynolds number, Froude number, power number, the liquid height, and the spacing between impellers as the most significant specifications that are related to aerated tank performance. The spacing between the impellers is considered to be a design factor of such industrial equipment due to its remarkable impact on the oxygen mass transfer.

Integrative Innovation as Core Determinant for Sustainable Progress

Integrative innovation is a core determinant of competitiveness and sustainable progress. This is confirmed by the history of Nature and Mankind. The present work defines in a systemic manner the typology of innovation and integrative sustainable innovation, based on new models: a general model of the cycle of change in the Universe / Multiverse, a general correlation model environment – resources and a model of innovative clusters. It critically examines the current state of innovation and proposes principle ways to improve the integrative innovation in the European Union and Romania.

Ergodic Capacity Analysis of MISO/SIMO-OFDM With Arbitrary Antenna and Channel Tap Correlation

We analyze the ergodic capacity of multiple-input-single-output/single-input-multiple-output orthogonal frequency-division multiplexing (MISO/SIMO-OFDM) systems with arbitrary antenna and channel tap correlations. Existing works in literature consider the Kronecker model of antenna and channel tap correlations for capacity analysis. However, the applicability of such a model does not hold for all practical scenarios. Here, we assume a generalized correlation model, and the Kronecker model is a special case of our model. We analyze additional conditions beyond that needed by the Kronecker model to maximize capacity and conditions that reduce capacity and derive a closed-form capacity expression. Our results are validated using Monte Carlo simulations.

Alert Correlation through a Multi Components Architecture

Alert correlation is a process that analyzes the raw alerts produced by one or more intrusion detection systems, reduces nonrelevant ones, groups together alerts based on similarity and causality relationships between them and finally makes aconcise and meaningful view of occurring or attempted intrusions. Unfortunately, most correlation approaches use just a few components that aim only specific correlation issues and so cause reduction in correlation rate. This paper uses a general correlation model that has already been presented in [9] and is consisted of a comprehensive set of components. Then some changes are applied in the component that is related to multi-step attack scenario to detect them better and so to improve semantic level of alerts. The results of experiments with DARPA 2000 data set obviously show the effectiveness of the proposed approach. DOI: http://dx.doi.org/10.11591/ijece.v3i4.2771

Binary L12 Intermetallics: A Statistical‐Thermodynamic Modeling of Ordering Phenomena, Behavior and Properties

AbstractThe main objective of this paper is aimed towards a correct statistical‐thermodynamic modeling and description of the effects and changes associated with the creation of different defects in the crystal structure and their connection and influence on the properties of the binary L12 intermetallic systems. This was done by the using of a General Defect Correlation Model (GDCM), employing applications of the Bragg‐Williams‐Gorsky mean‐field approximation. The obtained results are compared to a model based on the Wagner‐Schottky approach with application of the grand canonical ensemble for non‐interacting point defects for description of the arrangement of anti‐structure and vacancy defects. The basic concept includes the evaluation of such characteristics of the intermetallic materials with L12 structures as the virtual critical temperatures of order‐disorder transformations, the pair‐wise interaction and defect formation energies, thermodynamic activities and defect concentrations, and also descriptions of long‐ranged (LRO) and short‐ranged (SRO) atomic correlations in the crystal lattice (including the possible correlation of nearest neighbor point defect combinations), which is difficult to obtain by other methods. The model calculations also are tested using experimental data on thermodynamic and structural properties.

Assessment of the three dimensional temperature and salinity observational networks in the Baltic Sea and North Sea

Abstract. The spatial averaged correlations are presented in 1.5° × 1.5° bins for the North and Baltic Sea region. The averaged correlations are computed based on the proxy ocean data generated by the operational forecast model of Danish Meteorology Institute (DMI). It is shown that the spatial distribution of the averaged correlations could reflect the overall influence of the local atmospheric forcing, complex topography, coastlines, boundary and bottom effect, etc. Comparisons with the satellite SST data demonstrate that the proxy ocean data reproduce realistic results at the surface. Based on the spatial bin-averaged correlations, a general correlation model is assumed to approximate the spatial and temporal correlation structure. Parameters of the correlation model are obtained on the standard Levitus levels. It is found that the correlation model is not the typical Guaussian-type function. For instance, the exponents of the correlation model vary in the longitudinal direction from 0.75 at the surface to 1.33 at the depth of 250 m for temperature. For salinity, the temporal correlation can be approximated with an exponential function. Two complementary quality-indicators, effective coverage rate and "explained" variance, are defined based on the correlation models obtained above. The two indicators are able to identify the "influence area" of the information content in a given observation network and the relative importance of observations at different locations. By these indicators, the 3-D temperature and salinity observational networks are assessed in the Baltic Sea and North Sea for the period 2004–2006. It is found that the surface level is more effectively covered than the deep waters with existing networks. In addition, the Belt Sea and the Baltic Proper also show good coverage for both temperature and salinity. However, more observations are required in the Norwegian Trench and Kattegat. In the vertical, the two indicators show smaller values from 50 m to 125 m in this region, indicating the need for more observations.

Impact d'un choc sur les corrélations de trois indices boursiers

Résumé Notre objectif est de mesurer l’impact de chocs sur les corrélations conditionnelles de trois indices boursiers majeurs : le S&P 500, le ftse 100 et le Nikkei 225. Nous estimons une version étendue du modèle à corrélations conditionnelles dynamiques avec effet d’asymétrie ( ga-dcc ) de Cappiello, Engle et Sheppard [2006] et procédons à une analyse impulsion-réponse en suivant l’approche de Koop, Pesaran et Potter [1996]. Nous étudions I’impact du choc en date du 14 août 2007 au moment du déclenchement de la crise de subprimes et de celui de la semaine du 16 septembre 2008, après la faillite de la banque Lehman Brothers. Nos estimations montrent que ces deux chocs ont eu des impacts nettement différents sur les trois corrélations.