Data fusion approaches and applications for construction engineering

Data fusion can be defined as the process of combining data or information for estimating the state of an entity. Data fusion is a multidisciplinary field that has several benefits, such as enhancing the confidence, improving reliability, and reducing ambiguity of measurements for estimating the state of entities in engineering systems. It can also enhance completeness of fused data that may be required for estimating the state of engineering systems. Data fusion has been applied to different fields, such as robotics, automation, and intelligent systems. This paper reviews some examples of recent applications of data fusion in civil engineering and presents some of the potential benefits of using data fusion in civil engineering.

Sensor data scheduling for linear quadratic Gaussian control with full state feedback

Networked control systems (NCSs) have attracted much attention in the past decade due to their many advantages and growing number of applications. Different than classic control systems, resources in NCSs, such as network bandwidth and communication energy, are often limited, which degrade the closed-loop system performance and may even cause the system to become unstable. Seeking a desired trade-off between the closed-loop system performance and the limited resources is thus one heated area of research. In this paper, we analyze the trade-off between the sensor-to-controller communication rate and the closed-loop system performance indexed by the conventional LQG control cost. We present and compare several sensor data schedules, and demonstrate that two event-based sensor data schedules provide better trade-off than an optimal offline schedule. Simulation examples are provided to illustrate the theories developed in the paper. © 2012 AACC American Automatic Control Council).

Discovering transcriptional modules by Bayesian data integration.

MOTIVATION: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets. RESULTS: We find that by working on a gene-by-gene basis, our model is able to extract clusters with greater functional coherence than existing methods. By combining gene expression and transcription factor binding (ChIP-chip) data in this way, we are better able to determine the groups of genes that are most likely to represent underlying TMs. AVAILABILITY: If interested in the code for the work presented in this article, please contact the authors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Minimum sensor duty cycle with guaranteed estimator performance

In this paper, we consider Kalman filtering over a network and construct the optimal sensor data scheduling schemes which minimize the sensor duty cycle and guarantee a bounded error or a bounded average error at the remote estimator. Depending on the computation capability of the sensor, we can either give a closed-form expression of the minimum sensor duty cycle or provide tight lower and upper bounds of it. Examples are provided throughout the paper to demonstrate the results. © 2012 IEEE.

Towards robust part tracking in an automated manufacturing process using RFID

Automated Identification and in particular, Radio Frequency Identification (RFID) promises to assist with the automation of mass customised production processes. RFID has long been used to gather a history or trace of part movements, but the use of it as an integral part of the control process is yet to be fully exploited. Such use places stringent demands on the quality of the sensor data and the method used to interpret that data. in particular, this paper focuses on the issue of correctly identifying, tracking and dealing with aggregated objects with the use of RFID. The presented approach is evaluated in the context of a laboratory manufacturing system that produces customised gift boxes. Copyright © 2005 IFAC.

System combination and score normalization for spoken term detection

Spoken content in languages of emerging importance needs to be searchable to provide access to the underlying information. In this paper, we investigate the problem of extending data fusion methodologies from Information Retrieval for Spoken Term Detection on low-resource languages in the framework of the IARPA Babel program. We describe a number of alternative methods improving keyword search performance. We apply these methods to Cantonese, a language that presents some new issues in terms of reduced resources and shorter query lengths. First, we show score normalization methodology that improves in average by 20% keyword search performance. Second, we show that properly combining the outputs of diverse ASR systems performs 14% better than the best normalized ASR system. © 2013 IEEE.

Numerical simulations supporting the process design of ring rolling processes

In conventional Finite Element Analysis (FEA) of radial-axial ring rolling (RAR) the motions of all tools are usually defined prior to simulation in the preprocessing step. However, the real process holds up to 8 degrees of freedom (DOF) that are controlled by industrial control systems according to actual sensor values and preselected control strategies. Since the histories of the motions are unknown before the experiment and are dependent on sensor data, the conventional FEA cannot represent the process before experiment. In order to enable the usage of FEA in the process design stage, this approach integrates the industrially applied control algorithms of the real process including all relevant sensors and actuators into the FE model of ring rolling. Additionally, the process design of a novel process 'the axial profiling', in which a profiled roll is used for rolling axially profiled rings, is supported by FEA. Using this approach suitable control strategies can be tested in virtual environment before processing. © 2013 AIP Publishing LLC.