Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.

Sensitivity analysis of voltage imbalance in distribution networks with rooftop PVs

A comprehensive voltage imbalance sensitivity analysis and stochastic evaluation based on the rating and location of single-phase grid-connected rooftop photovoltaic cells (PVs) in a residential low voltage distribution network are presented. The voltage imbalance at different locations along a feeder is investigated. In addition, the sensitivity analysis is performed for voltage imbalance in one feeder when PVs are installed in other feeders of the network. A stochastic evaluation based on Monte Carlo method is carried out to investigate the risk index of the non-standard voltage imbalance in the network in the presence of PVs. The network voltage imbalance characteristic based on different criteria of PV rating and location and network conditions is generalized. Improvement methods are proposed for voltage imbalance reduction and their efficacy is verified by comparing their risk index using Monte Carlo simulations.

The impact of delayed blood centrifuging, choice of collection tube, and type of assay on 25-hydroxyvitamin D concentrations

Studies have examined the associations between cancers and circulating 25-hydroxyvitamin D [25(OH)D], but little is known about the impact of different laboratory practices on 25(OH)D concentrations. We examined the potential impact of delayed blood centrifuging, choice of collection tube, and type of assay on 25(OH)D concentrations. Blood samples from 20 healthy volunteers underwent alternative laboratory procedures: four centrifuging times (2, 24, 72, and 96 h after blood draw); three types of collection tubes (red top serum tube, two different plasma anticoagulant tubes containing heparin or EDTA); and two types of assays (DiaSorin radioimmunoassay [RIA] and chemiluminescence immunoassay [CLIA/LIAISON®]). Log-transformed 25(OH)D concentrations were analyzed using the generalized estimating equations (GEE) linear regression models. We found no difference in 25(OH)D concentrations by centrifuging times or type of assay. There was some indication of a difference in 25(OH)D concentrations by tube type in CLIA/LIAISON®-assayed samples, with concentrations in heparinized plasma (geometric mean, 16.1 ng ml−1) higher than those in serum (geometric mean, 15.3 ng ml−1) (p = 0.01), but the difference was significant only after substantial centrifuging delays (96 h). Our study suggests no necessity for requiring immediate processing of blood samples after collection or for the choice of a tube type or assay.

The effect of monocular and binocular cataract blur on postural stability among older adults

Purpose: First-eye cataract surgery can reduce the rate of falls among older adults, yet the effect of second-eye surgery on the rate of falling remains unclear. The present study investigated the effect of monocular and binocular simulated cataract blur on postural stability among older adults. Methods: Postural stability was assessed on 34 healthy older adults (mean 68.2 years, SD 3.5) with normal vision, using a portable force platform (BT4, HUR Labs, Finland) which collected data on centre of pressure (COP) displacement. Stability was assessed on firm and foam surfaces under four binocular viewing conditions using Vistech filters to simulate cataract blur: [1] best-corrected vision both eyes; [2] blur over non-dominant eye, [3] blur over dominant eye and [4] blur over both eyes. Binocular logMAR visual acuity, Pelli-Robson contrast sensitivity and stereoacuity were also measured under these viewing conditions and ocular dominance measured using the hole-in-card test. Generalized estimating equations with an exchangeable correlation structure examined the effect of the surface and vision conditions on postural stability. Results: Visual acuity and contrast sensitivity were significantly reduced under monocular and binocular cataract blur compared to normal viewing. All blur conditions resulted in loss of stereoacuity. Binocular cataract blur significantly reduced postural stability compared to normal vision on the firm (COP path length; p=0.013) and foam surface (anterior-posterior COP RMS, COP path length and COP area; p<0.01). However, no significant differences in postural stability were found between the monocular blur conditions compared to normal vision, or between the dominant and non-dominant monocular blur conditions on either the firm or foam surfaces. Conclusions: Findings indicate that binocular blur significantly impairs postural stability, and suggests that improvements in postural stability may justify first-eye cataract surgery, particularly during somatosensory disruption. Postural stability was not significantly impaired in the monocular cataract blur conditions compared to the normal vision condition, nor was there any effect of ocular dominance on postural stability in the presence of monocular cataract blur.

Extended GNSS ambiguity resolution models with regularization criterion and constraints

This paper firstly presents an extended ambiguity resolution model that deals with an ill-posed problem and constraints among the estimated parameters. In the extended model, the regularization criterion is used instead of the traditional least squares in order to estimate the float ambiguities better. The existing models can be derived from the general model. Secondly, the paper examines the existing ambiguity searching methods from four aspects: exclusion of nuisance integer candidates based on the available integer constraints; integer rounding; integer bootstrapping and integer least squares estimations. Finally, this paper systematically addresses the similarities and differences between the generalized TCAR and decorrelation methods from both theoretical and practical aspects.

Three Carrier Ambiguity Resolutions : Generalised problems, models and solutions

In this paper, the problems of three carrier phase ambiguity resolution (TCAR) and position estimation (PE) are generalized as real time GNSS data processing problems for a continuously observing network on large scale. In order to describe these problems, a general linear equation system is presented to uniform various geometry-free, geometry-based and geometry-constrained TCAR models, along with state transition questions between observation times. With this general formulation, generalized TCAR solutions are given to cover different real time GNSS data processing scenarios, and various simplified integer solutions, such as geometry-free rounding and geometry-based LAMBDA solutions with single and multiple-epoch measurements. In fact, various ambiguity resolution (AR) solutions differ in the floating ambiguity estimation and integer ambiguity search processes, but their theoretical equivalence remains under the same observational systems models and statistical assumptions. TCAR performance benefits as outlined from the data analyses in some recent literatures are reviewed, showing profound implications for the future GNSS development from both technology and application perspectives.

Study of ICT adoption for building project management in the Indian construction industry

Building project management requires effective coordination and collaboration between multiple project members. It can be achieved through real time communication flow between all. In present scenario, it can be achieved through adoption of Information and Communication Technologies (ICT). Construction industry primarily comprises small and medium enterprises (SMEs). Also, ICT adoption has been slow in the industry.---------- Research is required to assess the factors that affect ICT adoption at the three levels of industry, organization and people, with focus on SMEs. This paper discusses a component of the research undertaken to study these factors and issues in the context of Indian construction industry. A questionnaire survey was conducted and through quantitative data analysis the extent of adoption of formal Project Management processes, ICT adoption for these processes and factors including perception based factors affecting ICT adoption were studied. Results of data analysis includes identification of issues that require action at the three study levels.---------- The results can be generalized for other countries with due considerations, specifically for countries where the construction industry is similar to Indian construction industry in terms of working methodologies or for large countries.

Analysing Seasonal Health Data

Seasonal patterns have been found in a remarkable range of health conditions, including birth defects, respiratory infections and cardiovascular disease. Accurately estimating the size and timing of seasonal peaks in disease incidence is an aid to understanding the causes and possibly to developing interventions. With global warming increasing the intensity of seasonal weather patterns around the world, a review of the methods for estimating seasonal effects on health is timely. This is the first book on statistical methods for seasonal data written for a health audience. It describes methods for a range of outcomes (including continuous, count and binomial data) and demonstrates appropriate techniques for summarising and modelling these data. It has a practical focus and uses interesting examples to motivate and illustrate the methods. The statistical procedures and example data sets are available in an R package called ‘season’. Adrian Barnett is a senior research fellow at Queensland University of Technology, Australia. Annette Dobson is a Professor of Biostatistics at The University of Queensland, Australia. Both are experienced medical statisticians with a commitment to statistical education and have previously collaborated in research in the methodological developments and applications of biostatistics, especially to time series data. Among other projects, they worked together on revising the well-known textbook "An Introduction to Generalized Linear Models," third edition, Chapman Hall/CRC, 2008. In their new book they share their knowledge of statistical methods for examining seasonal patterns in health.

Fraud detection in ERP systems using scenario matching

ERP systems generally implement controls to prevent certain common kinds of fraud. In addition however, there is an imperative need for detection of more sophisticated patterns of fraudulent activity as evidenced by the legal requirement for company audits and the common incidence of fraud. This paper describes the design and implementation of a framework for detecting patterns of fraudulent activity in ERP systems. We include the description of six fraud scenarios and the process of specifying and detecting the occurrence of those scenarios in ERP user log data using the prototype software which we have developed. The test results for detecting these scenarios in log data have been verified and confirm the success of our approach which can be generalized to ERP systems in general.

Contemporary dramaturgy in theatre for young people : the conceptual shape of displacement and installation

This thesis investigates Theatre for Young People (TYP) as a site of performance innovation. The inquiry is focused on contemporary dramaturgy and its fieldwork aims to identify new dramaturgical principles operating in the creation and presentation of TYP. The research then seeks to assess how these new principles contribute to Postdramatic Theatre theory. This research inquiry springs from an imperative based in practice: Young people under 25 years have a literacy based on online hypertextual experiences which take the reader outside the frames of a dramatic narrative and beyond principles such as linearity, dramatic unity, teleology and resolution. As a dramaturg and educator I wanted to understand the new ways that young people engage in cultural products, to identify and utilize the new principles of dramaturgy that are now in evidence. My research examines how two playwright/directors approach their work and the new principles that can be identified in their dramaturgy. The fieldwork is scoped into two case studies: the first on TJ Eckleberg working in Australian Theatre for Young People and the second on Kristo Šagor working in German Children’s and Young People’s Theatre (KJT). These case studies address both types of production dramaturgy - the dramaturgy emergent through process in devised performance making, and that emergent in a performance based on a written playscript. On Case Study One the researcher, as participant observer, worked as production dramaturg on a large scale, site specific performance, observing the dramaturgy in process of its director and chief devisor. On Case Study Two the researcher, as observer and analyst, undertook a performance analysis of three playscripts and productions by a contemporary German playwright and director. Utilizing participant observation, reflective practice and grounded analysis the case studies have identified two new principles animating the dramaturgy of these TYP practitioners, namely ‘displacement’ and ‘installation.’ Taking practice into theory, the thesis concludes by demonstrating how displacement and installation contribute to Postdramatic Theatre’s “arsenal of expressive gestures which serve as theatre’s response to changed social communication under the conditions of generalized communication technologies” (Lehmann, H.-T., 2006, p.23). This research makes an original contribution to knowledge by evidencing that the principles of Postdramatic Theory lie within the practice of contemporary Theatre for Young People. It also contributes valuable research to a specialized, often overlooked terrain, namely Dramaturgy in Theatre for Young People, presented here with a contemporary, international and intercultural perspective.

Kava and St. John's wort : current evidence for use in mood and anxiety disorders

Background: Mood and anxiety disorders pose significant health burdens on the community. Kava and St John’s wort (SJW) are the most commonly used herbal medicines in the treatment of anxiety and depressive disorders, respectively. Objectives: To conduct a comprehensive review of kava and SJW, to review any evidence of efficacy, mode of action, pharmacokinetics, safety and use in Major Depressive Disorder (MDD), Bipolar Disorder (BP), Seasonal Affective Disorder (SAD), Generalized Anxiety Disorder (GAD), Social Phobia (SP), Panic Disorder (PD), Obsessive-Compulsive Disorder (OCD), and Post Traumatic Stress Disorder (PTSD). Methods: A systematic review was conducted using the electronic databases MEDLINE, CINAHL, and The Cochrane Library during late 2008. The search criteria involved mood and anxiety disorder search terms in combination with kava, Piper methysticum, kavalactones, St John’s wort, Hypericum perforatum, hypericin and hyperforin. Additional search criteria for safety, pharmacodynamics , and pharmacokinetics was employed. A subsequent forward search was conducted of the papers using Web of Science cited reference search. Results: Current evidence supports the use of SJW in treating mild-moderate depression, and for kava in treatment of generalized anxiety. In respect to the other disorders, only weak preliminary evidence exists for use of SJW in SAD. Currently there is no published human trial on use of kava in affective disorders, or in OCD, PTSD, PD or SP. These disorders constitute potential applications that warrant exploration. Conclusions: Current evidence for herbal medicines in the treatment of depression and anxiety only supports the use of Hypericum perforatum for depression, and Piper methysticum for generalized anxiety.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Evaluation of distributed control signaling protocols in GMPLS

GMPLS is a generalized form of MPLS (MultiProtocol Label Switching). MPLS is IP packet based and it uses MPLS-TE for Packet Traffic Engineering. GMPLS is extension to MPLS capabilities. It provides separation between transmission, control and management plane and network management. Control plane allows various applications like traffic engineering, service provisioning, and differentiated services. GMPLS control plane architecture includes signaling (RSVP-TE, CR-LDP) and routing (OSPF-TE, ISIS-TE) protocols. This paper provides an overview of the signaling protocols, describes their main functionalities, and provides a general evaluation of both the protocols.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.