A new adaptive blind channel identification algorithm

This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.

Estimation of basis frequencies for time-varying SIMO channels : a second-order method

The complex exponential basis expansion model (CE-BEM) provides an accurate description for the time-varying (TV) channels encountered in mobile communications. Many blind channel identification and equalization approaches based on the CE-BEM require precise knowledge of the basis frequencies of TV channels. Existing methods for basis frequency estimation usually resort to the higher-order statistics of channel outputs and impose strict constraints on the source signal. In this paper, we propose a novel method to estimate the basis frequencies for blind identification and equalization of time-varying single-input multiple-output (SIMO) finite-impulse-response (FIR) channels. The proposed method exploits only the second-order statistics of channel outputs and does not require strong conditions on the source signal. As a result, it exhibits superior performance to the existing basis frequency estimation methods. The validity of our method is demonstrated by numerical simulations.

Effectiveness of national elite sport policies : a multidimensional approach applied to the case of Flanders

While the results of nations in international sport competitions are most often used as an evaluation of effectiveness of elite sport policies, they do not take into account the long-term duration of an athletic career, nor the many confounding variables influencing international success. This paper argues that output evaluation is a one-sided approach to policy assessment. It applies a multidimensional approach to the measurement of the effectiveness of elite sports policy evaluation (meso-level) by examining a four-year cycle of elite sport policies in Flanders. This study endeavors to advance the development of a framework to assess effectiveness of elite sport policies of nations. Data were collected at multiple points of the input-throughput-output and feedback cycle. It was found that in spite of the increasing elite sport expenditures in Flanders (inputs), and notwithstanding the development of the throughputs (processes), this has not as yet lead to acceptable results (outputs) at an international level.

A second-order blind equalization method robust to ill-conditioned SIMO FIR channels

This paper deals with blind equalization of single-input-multiple-output (SIMO) finite-impulse-response (FIR) channels driven by i.i.d. signal, by exploiting the second-order statistics (SOS) of the channel outputs. Usually, SOS-based blind equalization is carried out via two stages. In Stage 1, the SIMO FIR channel is estimated using a blind identification method, such as the recently developed truncated transfer matrix (TTM) method. In Stage 2, an equalizer is derived from the estimate of the channel to recover the source signal. However, this type of two-stage approach does not give satisfactory blind equalization result if the channel is ill-conditioned, which is often encountered in practical applications. In this paper, we first show that the TTM method does not work in some situations. Then, we propose a novel SOS-based blind equalization method which can directly estimate the equalizer without knowing the channel impulse responses. The proposed method can obtain the desired equalizer even in the case that the channel is ill-conditioned. The performance of our method is illustrated by numerical simulations and compared with four benchmark methods. © 2014 Elsevier Inc.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

Method for computing state transformations of time-delay systems

This study provides a systematic method for deriving state transformations of a class of time-delay systems with multiple output. The significance of this study is that such state transformations can be used to transform timedelay systems into new coordinates where all the time-delay terms in the system description are associated with the output and input only. Therefore, in the new coordinate system, a Luenberger-type state observer can be readily designed. Subsequently, of the three possible versions of the original state vector, namely, instantaneous, delayed, and a mixed of instantaneous and delayed, a state observer which estimates one of these versions can be obtained. This new finding allows the authors to design state observers for a wider class of time-delay systems. Conditions for the existence of such coordinate changes and an effective algorithm for computing them are provided in this study. A numerical example and simulation results are given to illustrate the simplicity and effectiveness of the proposed method.

Multi-surface sliding control of MIMO autonomous flight systems

In this paper, we present a hardware in the loop simulation of our proposed multi-surface sliding control (MSSC) for trajectory tracking of 6 degrees of freedom (6-DOF) inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). Using MSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. The control law is implemented on an onboard computer and is validated though Hardware-In-the-Loop (HIL) simulations, between the hardware and the flight simulator X-Plane, which simulates the unmanned aircraft dynamics, sensors, and actuators. Simulation results are presented to validate the analysis.

Measuring output structures of multinational construction industries using the World Input‒Output Database

In the context of international movement towards trade liberalization, increasing technological progress, open competition and social development have impacted deeply on the construction industry in all economies. Using the World Input–Output Database (WIOD), a multinational comparison of the construction industry is estimated from 1995 to 2011 to provide accurate and valid information on the changing patterns of its output structure. The output coefficients for 37 countries and regions are formulated to allow for inter-industry comparisons and to identify the major components of construction output. Changes of output structure are then elaborated over time across countries and regions. The research findings presented in this paper would provide a framework for identifying the output structure of a nation's construction industry and its change trends at an international level, which may help policymakers and enterprises with the formulation of their future development strategies.

Control-oriented modeling of a polymeric soft robot

This article describes an efficient control-oriented model of a soft robot made of electroactive polymers. The proposed soft robot is constructed from two flexible links and has a multiphysics dynamic model consisting of both an electrochemical and electromechanical model. The electrochemical model is based on a distributed RC line approach, and the electromechanical model, considering the continuum vibration of the robot, is derived based on Hamilton's principle. The governing equation of the soft robot is solved by means of the Rayleigh-Ritz-Meirovitch substructure synthesis method, and the Laplace operator is used to obtain the transfer function of the soft robot as a 2 by 2 multiple-input multiple-output system.

Case study of demolition costs of residential buildings

Building demolition is one of the most common activities in the construction industry. Several demolition techniques are commonly used, including mechanical demolition, deconstruction and hybrid demolition. Although deconstruction has been advocated for its environmentally friendly approaches, the cost comparison of a demolition project under different techniques is rarely researched. In this paper, the cost of a demolition project is broken down to input and output costs, which are further broken down to more countable sections. Through an empirical study in Victoria, Australia, project costs of mechanical demolition, hybrid demolition and deconstruction are investigated. It is found that deconstruction has the greatest profitability among the three techniques. Hybrid demolition, which is the actual technique adopted by the contractor, has a slightly lower profit, and mechanical demolition is the most expensive. Although deconstruction has the best overall economical performance, the small extra gain comes with increased complexity and risk that deters demolition contractors from its attempt. It is found in the paper that an optimized demolition project strategy exists between hybrid demolition and deconstruction with the greatest profitability among various building demolition techniques.

Life-cycle energy analysis of building integrated photovoltaic systems (BiPVs) with heat recovery unit

Building integrated photovoltaic (BiPV) systems generate electricity, but also heat, which is typically wasted and also reduces the efficiency of generation. A heat recovery unit can be combined with a BiPV system to take advantage of this waste heat, thus providing cogeneration. Two different photovoltaic (PV) cell types were combined with a heat recovery unit and analysed in terms of their life-cycle energy consumption to determine the energy payback period. A net energy analysis of these PV systems has previously been performed, but recent improvements in the data used for this study allow for a more comprehensive assessment of the combined energy used throughout the entire life-cycle of these systems to be performed. Energy payback periods between 4 and 16.5 years were found, depending on the BiPV system. The energy embodied in PV systems is significant, emphasised here due to the innovative use of national average input–output (I–O) data to fill gaps in traditional life-cycle inventories, i.e. hybrid analysis. These findings provide an insight into the net energy savings that are possible with a well-designed and managed BiPV system.

Nonlinear identification of pneumatic servo-drive

Three nonlinear approaches to model the nonlinear pneumatic servo- drive are presented. The three nonlinear approaches are: (1) the multi input-single output (MISO) approach, which describes the single input-single output (SISO) nonlinear plant using a MISO linear representation which allows replacement of the nonlinear analysis by a linear one without approximation, and is studied in both time and frequency domains; (2) piecewise linearization, which systematically replaces, using artificial neural network, the nonlinear surface representing the plant in the hyper input-output space by a number of linear planes that are continuous over the boundaries between them; and (3) Adaptive Neuro-Fuzzy Inference System (ANFIS), in which the fuzzy rules are placed in a neural network structure, and which consequently utilizes neural networks learning rules to systematically tune the nonlinear fuzzy model. The superiority of these nonlinear models over the best model that can be developed using linear identification techniques is shown.

Analysis of stamping production data with view towards quality management

A quality analysis trial was undertaken at Ford Geelong Stamping Plant on a press line that was fitted with standard press sensors to measure press and binder force over the stamping cycle for each panel. The quality of randomly sampled panels was measured by obtaining the panel thicknesses at five points, for 135 panels in total. These points were chosen such that they exhibited different forming modes. This paper analyses the input force data and the output quality data from the trial to determine any potential relationships. The analysis of the production data was performed using statistical correlation techniques to determine initial potential relationships between input and output variables. An Active Shape Model was used to extract features when identifying the major sources of variation within the input data. However, the initial analysis of the data elicited no direct relationship between the input variables measured and the panel thicknesses. This result is significant as the data collected is from a standard sensor configuration found in many press lines through-out the world. The reason for the lack of a direct relationship is believed to come from the lack of sensitivity in the force measurements which are not able to identify small changes in the process, whereas gross geometric variations have in previous studies shown an obvious relationship with changes in the force press profile. This means that existing force sensors require augmentation by additional sensors if a detailed automatic quality control system for the press lines based on input sensors alone.

Embodied energy in buildings : wood versus concrete - reply to Börjesson and Gustavsson

We analyse the wood and concrete designs of the Wälludden building described by Börjesson et al. (Energy Policy 28 (2000) 575) in terms of their embodied energy, employing an environmentally extended input–output framework in a tiered hybrid life-cycle assessment, and in a structural path analysis. We illustrate the complexity of the inter-industry supply chains underlying the upstream energy requirements for the building options, and demonstrate that higher-order inputs are difficult to capture in a conventional process analysis. Our calculations show that Börjesson and Gustavsson's estimates of energy requirements and greenhouse gas emissions are underestimated by a factor of about 2, and that corresponding greenhouse gas balances are positive at about 30 t C-eq. Nevertheless, Börjesson and Gustavsson's general result—the concrete-framed building causing higher emissions—still holds.

System boundary selection in life-cycle inventories using hybrid approaches

Life-cycle assessment (LCA) is a method for evaluating the environmental impacts of products holistically, including direct and supply chain impacts. The current LCA methodologies and the standards by the International Organization for Standardization (ISO) impose practical difficulties for drawing system boundaries; decisions on inclusion or exclusion of processes in an analysis (the cutoff criteria) are typically not made on a scientific basis. In particular, the requirement of deciding which processes could be excluded from the inventory can be rather difficult to meet because many excluded processes have often never been assessed by the practitioner, and therefore, their negligibility cannot be guaranteed. LCA studies utilizing economic input−output analysis have shown that, in practice, excluded processes can contribute as much to the product system under study as included processes; thus, the subjective determination of the system boundary may lead to invalid results. System boundaries in LCA are discussed herein with particular attention to outlining hybrid approaches as methods for resolving the boundary selection problem in LCA. An input−output model can be used to describe at least a part of a product system, and an ISO-compatible system boundary selection procedure can be designed by applying hybrid input−output-assisted approaches. There are several hybrid input−output analysis-based LCA methods that can be implemented in practice for broadening system boundary and also for ISO compliance.