Integrating voice and data on SALAN: an experimental local area network

This paper is concerned with the integration of voice and data on an experimental local area network used by the School of Automation, of the Indian Institute of Science. SALAN (School of Automation Local Area Network) consists of a number of microprocessor-based communication nodes linked to a shared coaxial cable transmission medium. The communication nodes handle the various low-level functions associated with computer communication, and interface user data equipment to the network. SALAN at present provides a file transfer facility between an Intel Series III microcomputer development system and a Texas Instruments Model 990/4 microcomputer system. Further, a packet voice communication system has also been implemented on SALAN. The various aspects of the design and implementation of the above two utilities are discussed.

Concordant molecular and phenotypic data delineate new taxonomy and conservation priorities for the endangered mountain yellow-legged frog

The mountain yellow-legged frog Rana muscosa sensu lato, once abundant in the Sierra Nevada of California and Nevada, and the disjunct Transverse Ranges of southern California, has declined precipitously throughout its range, even though most of its habitat is protected. The species is now extinct in Nevada and reduced to tiny remnants in southern California, where as a distinct population segment, it is classified as Endangered. Introduced predators (trout), air pollution and an infectious disease (chytridiomycosis) threaten remaining populations. A Bayesian analysis of 1901 base pairs of mitochondrial DNA confirms the presence of two deeply divergent clades that come into near contact in the Sierra Nevada. Morphological studies of museum specimens and analysis of acoustic data show that the two major mtDNA clades are readily differentiated phenotypically. Accordingly, we recognize two species, Rana sierrae, in the northern and central Sierra Nevada, and R. muscosa, in the southern Sierra Nevada and southern California. Existing data indicate no range overlap. These results have important implications for the conservation of these two species as they illuminate a profound mismatch between the current delineation of the distinct population segments (southern California vs. Sierra Nevada) and actual species boundaries. For example, our study finds that remnant populations of R. muscosa exist in both the southern Sierra Nevada and the mountains of southern California, which may broaden options for management. In addition, despite the fact that only the southern California populations are listed as Endangered, surveys conducted since 1995 at 225 historic (1899-1994) localities from museum collections show that 93.3% (n=146) of R. sierrae populations and 95.2% (n=79) of R. muscosa populations are extinct. Evidence presented here underscores the need for revision of protected population status to include both species throughout their ranges.

A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Site classification and estimation of surface level seismic hazard using geophysical data and probabilistic approach

This paper presents the site classification of Bangalore Mahanagar Palike (BMP) area using geophysical data and the evaluation of spectral acceleration at ground level using probabilistic approach. Site classification has been carried out using experimental data from the shallow geophysical method of Multichannel Analysis of Surface wave (MASW). One-dimensional (1-D) MASW survey has been carried out at 58 locations and respective velocity profiles are obtained. The average shear wave velocity for 30 m depth (Vs(30)) has been calculated and is used for the site classification of the BMP area as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs(30) values major part of the BMP area can be classified as ``site class D'', and ``site class C'. A smaller portion of the study area, in and around Lalbagh Park, is classified as ``site class B''. Further, probabilistic seismic hazard analysis has been carried out to map the seismic hazard in terms spectral acceleration (S-a) at rock and the ground level considering the site classes and six seismogenic sources identified. The mean annual rate of exceedance and cumulative probability hazard curve for S. have been generated. The quantified hazard values in terms of spectral acceleration for short period and long period are mapped for rock, site class C and D with 10% probability of exceedance in 50 years on a grid size of 0.5 km. In addition to this, the Uniform Hazard Response Spectrum (UHRS) at surface level has been developed for the 5% damping and 10% probability of exceedance in 50 years for rock, site class C and D These spectral acceleration and uniform hazard spectrums can be used to assess the design force for important structures and also to develop the design spectrum.

Multiresolution Area-based Fractal Dimension Estimation of Signals Applied to EEG Data

In this paper, we present an approach to estimate fractal complexity of discrete time signal waveforms based on computation of area bounded by sample points of the signal at different time resolutions. The slope of best straight line fit to the graph of log(A(rk)A / rk(2)) versus log(l/rk) is estimated, where A(rk) is the area computed at different time resolutions and rk time resolutions at which the area have been computed. The slope quantifies complexity of the signal and it is taken as an estimate of the fractal dimension (FD). The proposed approach is used to estimate the fractal dimension of parametric fractal signals with known fractal dimensions and the method has given accurate results. The estimation accuracy of the method is compared with that of Higuchi's and Sevcik's methods. The proposed method has given more accurate results when compared with that of Sevcik's method and the results are comparable to that of the Higuchi's method. The practical application of the complexity measure in detecting change in complexity of signals is discussed using real sleep electroencephalogram recordings from eight different subjects. The FD-based approach has shown good performance in discriminating different stages of sleep.

Application of various viscosity theories to the viscosity data of methyl methacrylate-acrylonitrile random copolymersstar

Values of Ko, Flory constant related to unperturbed dimensions, are evaluated for methyl methacrylate-acrylonitrile random copolymers using Flory-Fox, Kurata-Stockmayer and Inagaki-Ptitsyn methods and compared with the Ko values obtained by Stockmayer-Fixman method. Ko values are seen to be less in solvents which have large a (Mark-Houwink exponent) values. A correlation between Ko and a is developed to arrive at a more reliable estimate of Ko for this copolymer system.

Factors related to seat belt use : A Turkish case

Seat belts are effective safety devices used to protect car occupants from severe injuries and fatalities during road vehicle accidents. Despite the proven effectiveness of seat belts, seat belt use rates are quite low, especially in developing countries, such as Turkey. The general aim of the present study was to investigate a large variety of factors related to seat belt use among Turkish car occupants using different perspectives and methods and therefore, to contribute to the design of effective seat belt use interventions for increasing seat belt use rates in Turkey. Five sub-studies were conducted within the present study. In the first sub-study, environmental (e.g., road type) and psycho-social factors (e.g., belt use by other car occupants) related to the seat belt use of front-seat occupants were investigated using observation techniques. Being male, of a young age, and traveling on city roads were the main factors negatively related to seat belt use. Furthermore, seat belt use by the drivers and front-seat passengers was highly correlated and a significant predictors of each other. In the second sub-study, the motivations of the car occupants for seat belt use and non-use were investigated using interview techniques. Situational conditions, such as traveling on city roads and for short distances, and not believing in the effectiveness and relevance of seat belt use for safety, were the most frequently reported reasons for not using a seat belt. Safety, habit and avoiding punishment were among the most frequently reported reasons for using a seat belt. In the third sub-study, the Theory of Planned Behavior (TPB) and the Health Belief Model (HBM) were applied to seat belt use using Structural Equation Modeling techniques. The TPB model showed a good fit to the data, whereas the HBM showed a poor fit to the data. Within the TPB model, attitude and subjective norm were significant predictors of intentions to use a seat belt on both urban and rural roads. In the fourth sub-study, seat belt use frequency and motivations for seat belt use among taxi drivers were investigated and compared between free-time and work-time driving using a survey. The results showed that taxi drivers used seat belts more when driving a private car in their free-times compared to when driving a taxi during their work-times. The lack of a legal obligation to use a seat belt in city traffic and fear of being attacked or robbed by the passengers were found as two specific reasons for not using a seat belt when driving a taxi. Lastly, in the fifth sub-study, the relationship of seat belt use to driver and health behaviors was investigated using a survey. Although seat belt use was related both to health and driver behaviors, factor analysis results showed that it grouped with driver behaviors. Based on the results of the sub-studies, a tentative empirical model showing different predictors of seat belt use was proposed. According to the model, safety and normative motivations and perceived physical barriers related to seat belt use are the three important predictors of seat belt use. Keywords: Seat belt use; environmental factors; psycho-social factors; safety and normative motivations; the Theory of Planned Behavior; the Health Belief Model; health behaviors; driver behaviors; front-seat occupants; taxi drivers; Turkey.

Big data

Making Sense of Mass Education provides an engaging and accessible analysis of traditional issues associated with mass education. The book challenges preconceptions about social class, gender and ethnicity discrimination; highlights the interplay between technology, media, popular culture and schooling; and inspects the relevance of ethics and philosophy in the modern classroom. This new edition has been comprehensively updated to provide current information regarding literature, statistics and legal policies, and significantly expands on the previous edition's structure of derailing traditional myths about education as a point of discussion. It also features two new chapters on Big Data and Globalisation and what they mean for the Australian classroom. Written for students, practising teachers and academics alike, Making Sense of Mass Education summarises the current educational landscape in Australia and looks at fundamental issues in society as they relate to education.

Normative values for corneal nerve morphology assessed using corneal confocal microscopy: A multinational normative data set

OBJECTIVE Corneal confocal microscopy is a novel diagnostic technique for the detection of nerve damage and repair in a range of peripheral neuropathies, in particular diabetic neuropathy. Normative reference values are required to enable clinical translation and wider use of this technique. We have therefore undertaken a multicenter collaboration to provide worldwide age-adjusted normative values of corneal nerve fiber parameters. RESEARCH DESIGN AND METHODS A total of 1,965 corneal nerve images from 343 healthy volunteers were pooled from six clinical academic centers. All subjects underwent examination with the Heidelberg Retina Tomograph corneal confocal microscope. Images of the central corneal subbasal nerve plexus were acquired by each center using a standard protocol and analyzed by three trained examiners using manual tracing and semiautomated software (CCMetrics). Age trends were established using simple linear regression, and normative corneal nerve fiber density (CNFD), corneal nerve fiber branch density (CNBD), corneal nerve fiber length (CNFL), and corneal nerve fiber tortuosity (CNFT) reference values were calculated using quantile regression analysis. RESULTS There was a significant linear age-dependent decrease in CNFD (-0.164 no./mm(2) per year for men, P < 0.01, and -0.161 no./mm(2) per year for women, P < 0.01). There was no change with age in CNBD (0.192 no./mm(2) per year for men, P = 0.26, and -0.050 no./mm(2) per year for women, P = 0.78). CNFL decreased in men (-0.045 mm/mm(2) per year, P = 0.07) and women (-0.060 mm/mm(2) per year, P = 0.02). CNFT increased with age in men (0.044 per year, P < 0.01) and women (0.046 per year, P < 0.01). Height, weight, and BMI did not influence the 5th percentile normative values for any corneal nerve parameter. CONCLUSIONS This study provides robust worldwide normative reference values for corneal nerve parameters to be used in research and clinical practice in the study of diabetic and other peripheral neuropathies.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Analysis of EXAFS data of multiphasic heterogeneous catalysts

Cu K-edge EXAFS spectra of Cu-Ni/Al2O3 and Cu-ZnO catalysts, both of which contain more than one Cu species, have been analysed making use of an additive relation for the EXAFS function. The analysis, which also makes use of residual spectra for identifying the species, shows good agreement between experimental and calculated spectra.

Nuorisokodista maailmalle : Kokemuksia nuorisokodissa elämisestä ja aikuisiässä selviytymisestä

This thesis studies the experiences of women who have lived in a youth home as girls. There are two main themes: 1) experiences of living in a youth home, and 2) experiences of coping as an adult. Data on the first theme is purely subjective; it derives from personal, recalled experiences. Data on the second theme is partly based on experiences and partly on facts about the current life situation of the research participants. A third theme of the thesis is concerned with the question of how the research participants’ placement in a youth home influenced their later life. The thesis contributes valuable knowledge concerning the experiences of young people who have been raised in substitute care, a topic that is rare in the literature. The empirical data of the study consists of responses to an initial inquiry and subsequent interviews. The inquiry was sent to 116 former inhabitants of a youth home. 62 altogether returned the inquiry, and 34 participated in the interview. The purpose of the inquiry was to produce an overview of the life situations of the research participants and to invite them to participate in the interview. In addition, the inquiry sought to produce an overview of how the participants enjoyed living in a youth home and how they saw its significance in terms of their later lives. The interviews concentrated on the research participants’ experiences concerning the processes of getting into a youth home, living there, and coping independently in life afterwards. The most central result relating to the first main theme was that the experiences were both shared and non-shared. Living in a youth home was characterized by six general sentiments: “wonderful, real home”, “new world!”, “safe haven”, “place to live”, “penal institution”, and “nightmare”. These sentiments seemed to be related first and foremost to whether one’s own, individual needs and expectations had been met in the youth home. The strongest and most common needs, as experienced, were the needs for safety, belongingness and respect. On the basis of the experiences, meeting these needs can be considered as the most important task of a youth home. The results relating to the second main theme of the study were examined in two different ways. Comparisons with the general female population (education, situation in working life and financial circumstances) showed that research participants had coped less well. Differences were also found to exist in family structures: nuclear families and single mother families were more unusual among research participants, and stepfamilies more common, than in the general population. More of the participants’ children than of the general population’s lived with somebody other than their parent. However, the experience of coping well was common among research participants, although the beginning of independent living had been generally experienced as difficult: feelings of loneliness, insecurity and restlessness were dominant. Later, a sense of life control developed and strengthened through joining with others (family, work, friends), through accepting one’s own life history and through creating one’s own model of living. As the most significant explanation of their coping, the research participants identified their own (innate) strength and will to cope. The majority of the research participants felt that the youth home had a positive influence on their later lives. Positive influences can be grouped in three “levels”: I) getting out of the home, II) having good experiences and learning useful things, and III) the essential effect on one’s own way of thinking and living. The second level’s influence includes strengthened self-esteem, increased social understanding and new knowledge and skills. Some research participants did not think the youth home had any significance in terms of their later lives, and some thought it had negative significance.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

100 Years of U.S. Consumer Spending: Data for the Nation, New York City, and Boston

[From Preface] The Consumer Expenditure Survey is among the oldest publications of the Bureau of Labor Statistics. With information on the expenditures, incomes, and demographic characteristics of households, the survey documents the spending patterns and economic status of American families. This report offers a new approach to the use of Consumer Expenditure Survey data. Normally, the survey presents an indepth look at American households at a specific point in time, the reference period being a calendar year. Here, the authors use consumer expenditure data longitudinally and draw on information from decennial census reports to present a 100-year history of significant changes in consumer spending, economic status, and family demographics in the country as a whole, as well as in New York City and Boston.

The Effect of Framing on Layoff Decisions: Are More-Experienced Managers More Rational? Does Computerized Data Make Any Difference?

[Excerpt] The effects of framing on decisions has been widely studied, producing research that suggests individuals respond to framing in predictable and fairly consistent ways (Bazerman, 1984, 1990; Tversky & Kahneman, 1986; Thaler, 1980). The essential finding from this body of research is that "individuals treat risks concerning perceived gains (for example, saving jobs and plants) differently from risks concerning perceived losses (losing jobs and plants)" (Bazerman, 1990, pp. 49-50). Specifically, individuals tend to avoid risks concerning gains, and seek risks concerning losses.