The airport city : a new business model for airport development

The airport city concept has been embraced by many airports of different scales and in varied ways around the world. Airports everywhere have diversified their landside revenues with non-aviation commercial and industrial development in order to increase revenues and spread risk in the notoriously volatile aviation market. As intermodal hubs in a connected, globalised world, airports have evolved from transportation nodes into multi-faceted business enterprises. They have assumed a critical role as ‘transactional’ spaces in the global economy (Gottdiener 2001).

Development of new evaluation methods for qualitative alternatives, using fuzzy calculations

Evaluation, selection and finally decision making are all among important issues, which engineers face in long run of projects. Engineers implement mathematical and nonmathematical methods to make accurate and correct decisions, whenever needed. As extensive as these methods are, effects of any selected method on outputs achieved and decisions made are still suspicious. This is more controversial and challengeable, where evaluation is made among non-quantitative alternatives. In civil engineering and construction management problems, criteria include both quantitative and qualitative ones, such as aesthetic, construction duration, building and operation costs, and environmental considerations. As the result, decision making frequently takes place among non-quantitative alternatives. It should be noted that traditional comparison methods, including clear-cut and inflexible mathematics, have always been criticized. This paper demonstrates a brief review of traditional methods of evaluating alternatives. It also offers a new decision making method using, fuzzy calculations. The main focus of this research is some engineering issues, which have flexible nature and vague borders. Suggested method provides analyzability of evaluation for decision makers. It is also capable to overcome multi criteria and multi-referees problems. In order to ease calculations, a program named DeMA is introduced.

Application of higher order spectra to identify epileptic EEG

Epilepsy is characterized by the spontaneous and seemingly unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into this phenomenon. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, we made a comparative study of the performance of Gaussian mixture model (GMM) and Support Vector Machine (SVM) classifiers using the features derived from HOS and from the power spectrum. Results show that the selected HOS based features achieve 93.11% classification accuracy compared to 88.78% with features derived from the power spectrum for a GMM classifier. The SVM classifier achieves an improvement from 86.89% with features based on the power spectrum to 92.56% with features based on the bispectrum.

Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

Shape discrimination using invariants defined from higher-order spectra

An approach to pattern recognition using invariant parameters based on higher-order spectra is presented. In particular, bispectral invariants are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale- and amplification-invariant. A minimal set of these invariants is selected as the feature vector for pattern classification. Pattern recognition using higher-order spectral invariants is fast, suited for parallel implementation, and works for signals corrupted by Gaussian noise. The classification technique is shown to distinguish two similar but different bolts given their one-dimensional profiles

A general procedure for the derivation of principal domains of higher-order spectra

A general procedure to determine the principal domain (i.e., nonredundant region of computation) of any higher-order spectrum is presented, using the bispectrum as an example. The procedure is then applied to derive the principal domain of the trispectrum of a real-valued, stationary time series. These results are easily extended to compute the principal domains of other higher-order spectra

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

Neural interface systems : a new legal frontier?

In an age where digital innovation knows no boundaries, research in the area of brain-computer interface and other neural interface devices go where none have gone before. The possibilities are endless and as dreams become reality, the implications of these amazing developments should be considered. Some of these new devices have been created to correct or minimise the effects of disease or injury so the paper discusses some of the current research and development in the area, including neuroprosthetics. To assist researchers and academics in identifying some of the legal and ethical issues that might arise as a result of research and development of neural interface devices, using both non-invasive techniques and invasive procedures, the paper discusses a number of recent observations of authors in the field. The issue of enhancing human attributes by incorporating these new devices is also considered. Such enhancement may be regarded as freeing the mind from the constraints of the body, but there are legal and moral issues that researchers and academics would be well advised to contemplate as these new devices are developed and used. While different fact situation surround each of these new devices, and those that are yet to come, consideration of the legal and ethical landscape may assist researchers and academics in dealing effectively with matters that arise in these times of transition. Lawyers could seek to facilitate the resolution of the legal disputes that arise in this area of research and development within the existing judicial and legislative frameworks. Whether these frameworks will suffice, or will need to change in order to enable effective resolution, is a broader question to be explored.

Infrastructure charges and increases to new house prices : a preliminary analysis of the US empirical models

Sourcing appropriate funding for the provision of new urban infrastructure has been a policy dilemma for governments around the world for decades. This is particularly relevant in high growth areas where new services are required to support swelling populations. The Australian infrastructure funding policy dilemmas are reflective of similar matters in many countries, particularly the United States of America, where infrastructure cost recovery policies have been in place since the 1970’s. There is an extensive body of both theoretical and empirical literature from these countries that discusses the passing on (to home buyers) of these infrastructure charges, and the corresponding impact on housing prices. The theoretical evidence is consistent in its findings that infrastructure charges are passed on to home buyers by way of higher house prices. The empirical evidence is also consistent in its findings, with “overshifting” of these charges evident in all models since the 1980’s, i.e. $1 infrastructure charge results in greater than $1 increase in house prices. However, despite over a dozen separate studies over two decades in the US on this topic, no empirical works have been carried out in Australia to test if similar shifting or overshifting occurs here. The purpose of this research is to conduct a preliminary analysis of the more recent models used in these US empirical studies in order to identify the key study area selection criteria and success factors. The paper concludes that many of the study area selection criteria are implicit rather than explicit. By collecting data across the models, some implicit criteria become apparent, whilst others remain elusive. This data will inform future research on whether an existing model can be adopted or adapted for use in Australia.

US Federal Government entrepreneurship : new enterprise structures

Purpose: The purpose of this paper is to guide the formation and to determine the structure of new governmental entrepreneurial ventures based on the nature of the public goods and the need for an entrepreneurial orientation. Design/methodology/research: This paper is conceptual and is based on reviews of appropriate organizational structure and entrepreneurship, cases studies, and the authors' experiences. Findings: Public or quasi-public entities may need to change their organizational structure in order to act more entrepreneurially and to be more effective in accomplishing their missions. Propositions are raised to guide the development of new public or private enterprises and provide the basis for future research. Research limitations/implications: This paper is conceptual and needs to be tested empirically. Though other levels of government and countries were included, a major focus is on the US federal government. Originality/value: This is the first published research on the topic of new enterprise government structures based on the nature of the goods and the requisite entrepreneurial orientation. It will help governmental and quasi-governmental organizations in developing efficient and effective organizational structures.

Book review : Frew, A.J., (Ed). Information and Communication Technologies in Tourism 2005. New York: Springer Wien

This volume represents the proceedings of the 12th ENTER conference held at Innsbruck in 2005. While the conference also accepts work-in-progress papers and includes a Ph.D. workshop, the proceedings contain 51 research papers by 102 authors. The general theme of the conference was eBusiness is here—what is next? and the papers cover a diverse range of topics across nine tracks. This reviewer has adopted the approach of succinctly summarising the contribution of each of the papers, in the order they appear....

China's new Creative Clusters : Governance, Human Capital and Investment

Recognising that creativity is a major driving force in the post-industrial economy, the Chinese government has recently established a range of "creative clusters" – industrial parks devoted to media industries, and arts districts – in order to promote the development of the creative industries. This book examines these new creative clusters, outlining their nature and purpose, and assessing their effectiveness. Drawing on case studies of a range of cluster models, and comparing them with international examples, the book demonstrates that creativity, both in China and internationally, is in fact a process of fitting new ideas to existing patterns, models and formats. It shows how large and exceptionally impressive creative clusters have been successfully established, but raises the important questions of whether profit or culture is the driving force, and of whether the bringing together of independent-minded, creative people, entrepreneurial businessmen, preferential policies and foreign investment may in time lead to unintended changes in social and political attitudes in China, including a weakening of state bureaucratic power. An important contribution to the existing literature on the subject, this book will be of great interest to scholars of urban studies, cultural geography, cultural economics and Asian studies.

Serious fears across cultures about the collapse of the world order

This chapter approaches resilience from an evolutionary psychology (socio-biological) perspective. It argues that the internal constitution and mental toughness of the individual will provide a core protection for life’s inevitable tests in the innumerable micro and macro environments humans find themselves. The many descriptors of the construct of resilience used in various studies are explored. Finally, the difference psychologists can make in the therapy of clients whose resilience is being tested, is examined by means of case examples.