Domestic and family violence

This chapter introduces domestic and family violence. It defines the terms and the types of violence they encompass, and summarizes patterns in perpetration and victimisation. The chapter reviews the historical development of domestic and family violence as recognizable social problems. It also explains how domestic violence and family violence are shaped by gender norms. Finally, it explains some key differences between these and other crimes.

Component modeling for SCADA network mapping

Supervisory Control and Data Acquisition systems (SCADA) are widely used to control critical infrastructure automatically. Capturing and analyzing packet-level traffic flowing through such a network is an essential requirement for problems such as legacy network mapping and fault detection. Within the framework of captured network traffic, we present a simple modeling technique, which supports the mapping of the SCADA network topology via traffic monitoring. By characterizing atomic network components in terms of their input-output topology and the relationship between their data traffic logs, we show that these modeling primitives have good compositional behaviour, which allows complex networks to be modeled. Finally, the predictions generated by our model are found to be in good agreement with experimentally obtained traffic.

The Corporate Governance Effects of Audit Committee

This chapter provides a synthesis and evaluation of empirical research on the governance effects associated with audit committees. Given recent policy recommendations in several countries aimed at strengthening these committees, it is important to establish what research evidence demonstrates about their existing governance contribution. A framework for analyzing the impact of audit committees is described, identifying potential perceived effects which may have led to their adoption and documented effects on aspects of the audit function, on financial reporting quality and on corporate performance. It is also shown that most of the existing research has focused on factors associated with audit committee existence, characteristics, and measures of activity and there is very little evidence on the processes associated with the operation of audit committees and the manner in which they influence organizational behavior. It is clear that there is no automatic relationship between the adoption of audit committee structures or characteristics and the achievement of particular governance effects, and caution may be needed over expectations that greater codification around factors such as audit committee members’ independence and expertise as the means of ‘‘correcting’’ past weaknesses in the arrangements for audit committees. The most fundamental question concerning what difference audit committees make in practice continues to be an important area for research development. For future research we suggest: (1) greater consideration of the organizational and institutional contexts in which audit committees operate; (2) explicit theorization of the processes associated with audit committee operation; (3) complementing extant research methods with field studies; and (4) investigation of unintended as well as expected consequences of audit committees.

Implementing ICT in Schools in a Developing Country : A Fijian Experience

Significant advances have been made towards the United Nations Millennium Development Goals on universal education. While there has been an increase in the number of children who now attend primary school, the quality of education remains an issue in many countries. Knowledge and the ability to use ICT are considered to be mandatory for citizens of this century. Information and Communication Technology (ICT) is becoming increasingly more common in classrooms in developed countries. However, ICT use is often beyond the reach of many school communities in developing countries. While supporting these developing countries through donations of technology is a start, there is an equal if not a greater need to build teacher capacity so that the resources are effective in classrooms. The Share, Engage and Educate (SEE) project is about creating educational opportunities for learners in developing countries using ICT. Through the efforts of volunteers, the project provides technological resources to schools and engages teachers in activities that develop their capacity. The SEE project has adopted a four-phase model for ICT integration: objectives, implementation, feedback, and reflection. This chapter reports upon the project’s ongoing implementation phase in Fiji, including the approach taken to build teacher capacity and the identification of factors which have impacted upon the project’s success.

Ecological approaches in planning for sustainable cities : a review of the literature

Rapid urbanization has brought environmentally, socially, and economically great challenges to cities and societies. To build a sustainable city, these challenges need to be faced efficiently and successfully. This paper focuses on the environmental issues and investigates the ecological approaches for planning sustainable cities through a comprehensive review of the relevant literature. The review focuses on several differing aspects of sustainable city formation. The paper provides insights on the interaction between the natural environment and human activities by identifying environmental effects resulting from this interaction; provides an introduction to the concept of sustainable urban development by underlining the important role of ecological planning in achieving sustainable cities; introduces the notion of urban ecosystems by establishing principles for the management of their sustainability; describes urban ecosystem sustainability assessment by introducing a review of current assessment methods, and; offers an outline of indexing urban environmental sustainability. The paper concludes with a summary of the findings.

Multilevel competing risk models to evaluate the risk of nosocomial infection

Introduction Risk factor analyses for nosocomial infections (NIs) are complex. First, due to competing events for NI, the association between risk factors of NI as measured using hazard rates may not coincide with the association using cumulative probability (risk). Second, patients from the same intensive care unit (ICU) who share the same environmental exposure are likely to be more similar with regard to risk factors predisposing to a NI than patients from different ICUs. We aimed to develop an analytical approach to account for both features and to use it to evaluate associations between patient- and ICU-level characteristics with both rates of NI and competing risks and with the cumulative probability of infection. Methods We considered a multicenter database of 159 intensive care units containing 109,216 admissions (813,739 admission-days) from the Spanish HELICS-ENVIN ICU network. We analyzed the data using two models: an etiologic model (rate based) and a predictive model (risk based). In both models, random effects (shared frailties) were introduced to assess heterogeneity. Death and discharge without NI are treated as competing events for NI. Results There was a large heterogeneity across ICUs in NI hazard rates, which remained after accounting for multilevel risk factors, meaning that there are remaining unobserved ICU-specific factors that influence NI occurrence. Heterogeneity across ICUs in terms of cumulative probability of NI was even more pronounced. Several risk factors had markedly different associations in the rate-based and risk-based models. For some, the associations differed in magnitude. For example, high Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were associated with modest increases in the rate of nosocomial bacteremia, but large increases in the risk. Others differed in sign, for example respiratory vs cardiovascular diagnostic categories were associated with a reduced rate of nosocomial bacteremia, but an increased risk. Conclusions A combination of competing risks and multilevel models is required to understand direct and indirect risk factors for NI and distinguish patient-level from ICU-level factors.

Design, construction and evaluation of systems to predict risk in obstetrics

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Infrared and raman spectroscopic characterization of the silicate mineral gilalite Cu5Si6O17.7H2O

Gilalite is a copper silicate mineral with a general formula of Cu5Si6O17 · 7H2O. The mineral is often found in association with another copper silicate mineral, apachite, Cu9Si10O29 · 11H2O. Raman and infrared spectroscopy have been used to characterize the molecular structure of gilalite. The structure of the mineral shows disorder, which is reflected in the difficulty of obtaining quality Raman spectra. Raman spectroscopy clearly shows the absence of OH units in the gilalite structure. Intense Raman bands are observed at 1066, 1083, and 1160 cm−1. The Raman band at 853 cm−1 is assigned to the –SiO3 symmetrical stretching vibration and the low-intensity Raman bands at 914, 953, and 964 cm−1 may be ascribed to the antisymmetric SiO stretching vibrations. An intense Raman band at 673 cm−1 with a shoulder at 663 cm−1 is assigned to the ν4 Si-O-Si bending modes. Raman spectroscopy complemented with infrared spectroscopy enabled a better understanding of the molecular structure of gilalite.

Editorial

The 2nd International Digital Human Modeling (DHM) Symposium was held at the renowned University of Michigan Transportation Research Institute (UMTRI) in Ann Arbor, Michigan in June 11–13, 2013. The symposium was co-organised by the UMTRI and Penn State University, and endorsed by the IEA Technical Committee on Human Simulation and Virtual Environments. The conference built on the very successful inaugural event DHM2011 held in Lyon two years before; and a decade of digital human modelling conferences held under the auspices of SAE International. Practitioners and scientists from 13 countries gathered to present their state-of-the-art developments and applied research, besides discussing the most recent advances in human modelling and directions for future work in DHM...