Investigations into Velocity and Distance Perception Based on Different Types of Moving Sound Sources with Respect to Auditory Virtual Environments

The characteristics of moving sound sources have strong implications on the listener's distance perception and the estimation of velocity. Modifications of the typical sound emissions as they are currently occurring due to the tendency towards electromobility have an impact on the pedestrian's safety in road traffic. Thus, investigations of the relevant cues for velocity and distance perception of moving sound sources are not only of interest for the psychoacoustic community, but also for several applications, like e.g. virtual reality, noise pollution and safety aspects of road traffic. This article describes a series of psychoacoustic experiments in this field. Dichotic and diotic stimuli of a set of real-life recordings taken from a passing passenger car and a motorcycle were presented to test subjects who in turn were asked to determine the velocity of the object and its minimal distance from the listener. The results of these psychoacoustic experiments show that the estimated velocity is strongly linked to the object's distance. Furthermore, it could be shown that binaural cues contribute significantly to the perception of velocity. In a further experiment, it was shown that - independently of the type of the vehicle - the main parameter for distance determination is the maximum sound pressure level at the listener's position. The article suggests a system architecture for the adequate consideration of moving sound sources in virtual auditory environments. Virtual environments can thus be used to investigate the influence of new vehicle powertrain concepts and the related sound emissions of these vehicles on the pedestrians' ability to estimate the distance and velocity of moving objects.

Converging evidence that common timing processes underlie temporal-order and simultaneity judgments: a model-based analysis

Perception of simultaneity and temporal order is studied with simultaneity judgment (SJ) and temporal-order judgment (TOJ) tasks. In the former, observers report whether presentation of two stimuli was subjectively simultaneous; in the latter, they report which stimulus was subjectively presented first. SJ and TOJ tasks typically give discrepant results, which has prompted the view that performance is mediated by different processes in each task. We looked at these discrepancies from a model that yields psychometric functions whose parameters characterize the timing, decisional, and response processes involved in SJ and TOJ tasks. We analyzed 12 data sets from published studies in which both tasks had been used in within-subjects designs, all of which had reported differences in performance across tasks. Fitting the model jointly to data from both tasks, we tested the hypothesis that common timing processes sustain simultaneity and temporal order judgments, with differences in performance arising from task-dependent decisional and response processes. The results supported this hypothesis, also showing that model psychometric functions account for aspects of SJ and TOJ data that classical analyses overlook. Implications for research on perception of simultaneity and temporal order are discussed.

Pattern-based analysis of EAI languages : the case of the business modelling language

Enterprise Application Integration (EAI) is a challenging area that is attracting growing attention from the software industry and the research community. A landscape of languages and techniques for EAI has emerged and is continuously being enriched with new proposals from different software vendors and coalitions. However, little or no effort has been dedicated to systematically evaluate and compare these languages and techniques. The work reported in this paper is a first step in this direction. It presents an in-depth analysis of a language, namely the Business Modeling Language, specifically developed for EAI. The framework used for this analysis is based on a number of workflow and communication patterns. This framework provides a basis for evaluating the advantages and drawbacks of EAI languages with respect to recurrent problems and situations.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Development of a data mining-based analysis framework for multi-attribute construction project information

Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

The effects of transformational leadership behaviors on follower outcomes : an identity-based analysis

The aim of this study was to explore two of the mechanisms by which transformational leaders have a positive influence on followers. It examined the mediating role of follower’s leader and group identification on the associations among different transformational leader behaviours and follower job satisfaction and supervisor-rated job performance. One hundred and seventy-nine healthcare employees and 44 supervisors participated in the study. The results from multilevel structural equation modelling provided results that partially supported the predicted model. Identification with the leader significantly mediated the positive associations between supportive leadership, intellectual stimulation, personal recognition, in the prediction of job satisfaction and job performance. Leader identification also mediated the relationship between supportive leadership, intellectual stimulation, personal recognition, and group identification. However, group identification did not mediate the associations between vision leadership and inspirational communication, in the prediction of job satisfaction and job performance. The results highlight the role of individualized forms of leadership and leader identification in enhancing follower outcomes.

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

Tensor-based analysis of genetic influences on brain integrity using DTI in 100 twins

Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

Primary total hip arthroplasty for primary osteoarthritis in Finland : A national register based analysis

The first aim of the current study was to evaluate the survival of total hip arthroplasty (THA) in patients aged 55 years and older on a nation-wide level. The second aim was to evaluate, on a nation wide-basis, the geographical variation of the incidence of primary THA for primary OA and also to identify those variables that are possibly associated with this variation. The third aim was to evaluate the effects of hospital volume: on the length of stay, on the numbers of re-admissions and on the numbers of complications of THR on population-based level in Finland. The survival of implants was analysed based on data from the Finnish Arthroplasty Register. The incidence and hospital volume data were obtained from the Hospital Discharge Register. Cementless total hip replacements had a significantly reduced risk of revision for aseptic loosening compared with cemented hip replacements. When revision for any reason was the end point in the survival analyses, there were no significant differences found between the groups. Adjusted incidence ratios of THA varied from 1.9- to 3.0-fold during the study period. Neither the average income within a region nor the morbidity index was associated with the incidence of THA. For the four categories of volume of total hip replacements performed per hospital, the length of the surgical treatment period was shorter for the highest volume group than for the lowest volume group. The odds ratio for dislocations was significantly lower in the high volume group than in the low volume group. In patients who were 55 years of age or older, the survival of cementless total hip replacements was as good as that of the cemented replacements. However, multiple wear-related revisions of the cementless cups indicate that excessive polyethylene wear was a major clinical problem with modular cementless cups. The variation in the long-term rates of survival for different cemented stems was considerable. Cementless proximal porous-coated stems were found to be a good option for elderly patients. When hip surgery was performed on with a large repertoire, the indications to perform THAs due to primary OA were tight. Socio-economic status of the patient had no apparent effect on THA rate. Specialization of hip replacements in high volume hospitals should reduce costs by significantly shortening the length of stay, and may reduce the dislocation rate.

Accurate mass-based analysis in human sport doping control : Application of liquid chromatography - time-of-flight mass spectrometry

Human sport doping control analysis is a complex and challenging task for anti-doping laboratories. The List of Prohibited Substances and Methods, updated annually by World Anti-Doping Agency (WADA), consists of hundreds of chemically and pharmacologically different low and high molecular weight compounds. This poses a considerable challenge for laboratories to analyze for them all in a limited amount of time from a limited sample aliquot. The continuous expansion of the Prohibited List obliges laboratories to keep their analytical methods updated and to research new available methodologies. In this thesis, an accurate mass-based analysis employing liquid chromatography - time-of-flight mass spectrometry (LC-TOFMS) was developed and validated to improve the power of doping control analysis. New analytical methods were developed utilizing the high mass accuracy and high information content obtained by TOFMS to generate comprehensive and generic screening procedures. The suitability of LC-TOFMS for comprehensive screening was demonstrated for the first time in the field with mass accuracies better than 1 mDa. Further attention was given to generic sample preparation, an essential part of screening analysis, to rationalize the whole work flow and minimize the need for several separate sample preparation methods. Utilizing both positive and negative ionization allowed the detection of almost 200 prohibited substances. Automatic data processing produced a Microsoft Excel based report highlighting the entries fulfilling the criteria of the reverse data base search (retention time (RT), mass accuracy, isotope match). The quantitative performance of LC-TOFMS was demonstrated with morphine, codeine and their intact glucuronide conjugates. After a straightforward sample preparation the compounds were analyzed directly without the need for hydrolysis, solvent transfer, evaporation or reconstitution. The hydrophilic interaction technique (HILIC) provided good chromatographic separation, which was critical for the morphine glucuronide isomers. A wide linear range (50-5000 ng/ml) with good precision (RSD<10%) and accuracy (±10%) was obtained, showing comparable or better performance to other methods used. In-source collision-induced dissociation (ISCID) allowed confirmation analysis with three diagnostic ions with a median mass accuracy of 1.08 mDa and repeatable ion ratios fulfilling WADA s identification criteria. The suitability of LC-TOFMS for screening of high molecular weight doping agents was demonstrated with plasma volume expanders (PVE), namely dextran and hydroxyethylstarch (HES). Specificity of the assay was improved, since interfering matrix compounds were removed by size exclusion chromatography (SEC). ISCID produced three characteristic ions with an excellent mean mass accuracy of 0.82 mDa at physiological concentration levels. In summary, by combining TOFMS with a proper sample preparation and chromatographic separation, the technique can be utilized extensively in doping control laboratories for comprehensive screening of chemically different low and high molecular weight compounds, for quantification of threshold substances and even for confirmation. LC-TOFMS rationalized the work flow in doping control laboratories by simplifying the screening scheme, expediting reporting and minimizing the analysis costs. Therefore LC-TOFMS can be exploited widely in doping control, and the need for several separate analysis techniques is reduced.

Space vector-based analysis of overmodulation in triangle-comparison based PWM for voltage source inverter

The equivalence of triangle-comparison-based pulse width modulation (TCPWM) and space vector based PWM (SVPWM) during linear modulation is well-known. This paper analyses triangle-comparison based PWM techniques (TCPWM) such as sine-triangle PWM (SPWM) and common-mode voltage injection PWM during overmodulation from a space vector point of view. The average voltage vector produced by TCPWM during overmodulation is studied in the stationary (a-b) reference frame. This is compared and contrasted with the average voltage vector corresponding to the well-known standard two-zone algorithm for space vector modulated inverters. It is shown that the two-zone overmodulation algorithm itself can be derived from the variation of average voltage vector with TCPWM. The average voltage vector is further studied in a synchronously revolving (d-q) reference frame. The RMS value of low-order voltage ripple can be estimated, and can be used to compare harmonic distortion due to different PWM methods during overmodulation. The measured values of the total harmonic distortion (THD) in the line currents are presented at various fundamental frequencies. The relative values of measured current THD pertaining to different PWM methods tally with those of analytically evaluated RMS voltage ripple.

Constraints based analysis of extended cybernetic models

The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms. (C) 2015 Elsevier Ireland Ltd. All rights reserved.