Organizations as intergroup contexts: Communication, discourse, and identification

wenty-eight international scholars contribute 11 chapters on the key role of communication in intergroup relations. Following an introductory essay on intergroup theory and communication processes, the text focuses on specific intergroup contexts, examining communication within and between cultural, disability, age, sex and sexuality, and language groups. The remaining chapters explore the communicating of identity across communication contexts, including small group, organizational, mass, and Internet communications. The text is designed for scholars in the fields of communication and intergroup social psychology, and is also suited for use in upper- division undergraduate and introductory graduate courses in those areas. Annotation ©2004 Book News, Inc., Portland, OR

A secure framework and related protocols for ubiquitous access to electronic health records using Java sim cards

Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the point-ofcare could possibly lead to a fatality. The U.S. Institute of Medicine has reported that between 44,000 and 98,000 people die each year due to medical errors, such as incorrect medication dosages, due to poor legibility in manual records, or delays in consolidating needed information to discern the proper intervention. In this research we propose employing emergent technologies such as Java SIM Cards (JSC), Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHR). A partial EHR contained within a JSC can be used at the point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Health Records Centre (EHRC) when time and network availability permit. Moreover, this framework and related protocols enable patients to give their explicit consent to a doctor to access their personal medical data, by using their Smart Phone, when the doctor needs to see or update the patient’s medical information during an examination. Also our proposed solution would give the power to patients to modify the Access Control List (ACL) related to their EHRs and view their EHRs through their Smart Phone. Currently, very limited research has been done on using JSCs and similar technologies as a portable repository of EHRs or on the specific security issues that are likely to arise when JSCs are used with ubiquitous access to EHRs. Previous research is concerned with using Medicare cards, a kind of Smart Card, as a repository of medical information at the patient point-of-care. However, this imposes some limitations on the patient’s emergency medical care, including the inability to detect the patient’s location, to call and send information to an emergency room automatically, and to interact with the patient in order to get consent. The aim of our framework and related protocols is to overcome these limitations by taking advantage of the SIM card and the technologies mentioned above. Briefly, our framework and related protocols will offer the full benefits of accessing an up-to-date, precise, and comprehensive medical history of a patient, whilst its mobility will provide ubiquitous access to medical and patient information everywhere it is needed. The objective of our framework and related protocols is to automate interactions between patients, healthcare providers and insurance organisations, increase patient safety, improve quality of care, and reduce the costs.

Identification of acoustic emission wave modes for accurate source location in plate-like structures

Acoustic emission (AE) technique is a popular tool used for structural health monitoring of civil, mechanical and aerospace structures. It is a non-destructive method based on rapid release of energy within a material by crack initiation or growth in the form of stress waves. Recording of these waves by means of sensors and subsequent analysis of the recorded signals convey information about the nature of the source. Ability to locate the source of stress waves is an important advantage of AE technique; but as AE waves travel in various modes and may undergo mode conversions, understanding of the modes (‘modal analysis’) is often necessary in order to determine source location accurately. This paper presents results of experiments aimed at finding locations of artificial AE sources on a thin plate and identifying wave modes in the recorded signal waveforms. Different source locating techniques will be investigated and importance of wave mode identification will be explored.

A secure framework and related protocols for ubiquitous access to electronic health records using Java SIM cards

Ubiquitous access to patient medical records is an important aspect of caring for patient safety. Unavailability of sufficient medical information at the patient point-of-care could possibly lead to a fatality. In this paper we propose employing emergent technologies such as Java SIM Cards (JSC),Smart Phones (SP), Next Generation Networks (NGN), Near Field Communications (NFC), Public Key Infrastructure (PKI), and Biometric Identification to develop a secure framework and related protocols for ubiquitous access to Electronic Health Records (EHRs). A partial EHR contained within a JSC can be used at the patient point-of-care in order to help quick diagnosis of a patient’s problems. The full EHR can be accessed from an Electronic Healthcare Records Centre (EHRC).

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

Accelerated Partial Breast Irradiation (APBI) : a review of available techniques

Breast conservation therapy (BCT) is the procedure of choice for the management of the early stage breast cancer. However, its utilization has not been maximized because of logistics issues associated with the protracted treatment involved with the radiation treatment. Accelerated Partial Breast Irradiation (APBI) is an approach that treats only the lumpectomy bed plus a 1-2 cm margin, rather than the whole breast. Hence because of the small volume of irradiation a higher dose can be delivered in a shorter period of time. There has been growing interest for APBI and various approaches have been developed under phase I-III clinical studies; these include multicatheter interstitial brachytherapy, balloon catheter brachytherapy, conformal external beam radiation therapy and intra-operative radiation therapy (IORT). Balloon-based brachytherapy approaches include Mammosite, Axxent electronic brachytherapy and Contura, Hybrid brachytherapy devices include SAVI and ClearPath. This paper reviews the different techniques, identifying the weaknesses and strength of each approach and proposes a direction for future research and development. It is evident that APBI will play a role in the management of a selected group of early breast cancer. However, the relative role of the different techniques is yet to be clearly identified.

Nonprofit organizational and work unit identification and the occupational stress process

Research investigating the transactional approach to the work stressor-employee adjustment relationship has described many negative main effects between perceived stressors in the workplace and employee outcomes. A considerable amount of literature, theoretical and empirical, also describes potential moderators of this relationship. Organizational identification has been established as a significant predictor of employee job-related attitudes. To date, research has neglected investigation of the potential moderating effect of organizational identification in the work stressor-employee adjustment relationship. On the basis of identity, subjective fit and sense of belonging literature it was predicted that higher perceptions of identification at multiple levels of the organization would mitigate the negative effect of work stressors on employee adjustment. It was expected, further, that more proximal, lower order identifications would be more prevalent and potent as buffers of stressors on strain. Predictions were tested with an employee sample from five organizations (N = 267). Hierarchical moderated multiple regression analyses revealed some support for the stress-buffering effects of identification in the prediction of job satisfaction and organizational commitment, particularly for more proximal (i.e., work unit) identification. These positive stress-buffering effects, however, were present for low identifiers in some situations. The present study represents an extension of the application of organizational identity theory by identifying the effects of organizational and workgroup identification on employee outcomes in the nonprofit context. Our findings will contribute to a better understanding of the dynamics in nonprofit organizations and therefore contribute to the development of strategy and interventions to deal with identity-based issues in nonprofits.

Asset identification : addressing the climate change in public asset management process

Climate change is becoming increasingly apparent that is largely caused by human activities such as asset management processes, from planning to disposal, of property and infrastructure. One essential component of asset management process is asset identification. The aims of the study are to identify the information needed in asset identification and inventory as one of public asset management process in addressing the climate change issue; and to examine its deliverability in developing countries’ local governments. In order to achieve its aims, this study employs a case study in Indonesia. This study only discusses one medium size provincial government in Indonesia. The information is gathered through interviews of the local government representatives in South Sulawesi Province, Indonesia and document analysis provided by interview participants. The study found that for local government, improving the system in managing their assets is one of emerging biggest challenge. Having the right information in the right place and at the right time are critical factors in response to this challenge. Therefore, asset identification as the frontline step in public asset management system is holding an important and critical role. Furthermore, an asset identification system should be developed to support the mainstream of adaptation to climate change vulnerability and to help local government officers to be environmentally sensitive. Finally, findings from this study provide useful input for the policy makers, scholars and asset management practitioners to develop an asset inventory system as a part of public asset management process in addressing the climate change.

Identification of factors contributing to recurrence of venous leg ulcers

Background and Significance Venous leg ulcers are a significant cause of chronic ill-health for 1–3% of those aged over 60 years, increasing in incidence with age. The condition is difficult and costly to heal, consuming 1–2.5% of total health budgets in developed countries and up to 50% of community nursing time. Unfortunately after healing, there is a recurrence rate of 60 to 70%, frequently within the first 12 months after heaing. Although some risk factors associated with higher recurrence rates have been identified (e.g. prolonged ulcer duration, deep vein thrombosis), in general there is limited evidence on treatments to effectively prevent recurrence. Patients are generally advised to undertake activities which aim to improve the impaired venous return (e.g. compression therapy, leg elevation, exercise). However, only compression therapy has some evidence to support its effectiveness in prevention and problems with adherence to this strategy are well documented. Aim The aim of this research was to identify factors associated with recurrence by determining relationships between recurrence and demographic factors, health, physical activity, psychosocial factors and self-care activities to prevent recurrence. Methods Two studies were undertaken: a retrospective study of participants diagnosed with a venous leg ulcer which healed 12 to 36 months prior to the study (n=122); and a prospective longitudinal study of participants recruited as their ulcer healed and data collected for 12 months following healing (n=80). Data were collected from medical records on demographics, medical history and ulcer history and treatments; and from self-report questionnaires on physical activity, nutrition, psychosocial measures, ulcer history, compression and other self-care activities. Follow-up data for the prospective study were collected every three months for 12 months after healing. For the retrospective study, a logistic regression model determined the independent influences of variables on recurrence. For the prospective study, median time to recurrence was calculated using the Kaplan-Meier method and a Cox proportional-hazards regression model was used to adjust for potential confounders and determine effects of preventive strategies and psychosocial factors on recurrence. Results In total, 68% of participants in the retrospective study and 44% of participants in the prospective study suffered a recurrence. After mutual adjustment for all variables in multivariable regression models, leg elevation, compression therapy, self efficacy and physical activity were found to be consistently related to recurrence in both studies. In the retrospective study, leg elevation, wearing Class 2 or 3 compression hosiery, the level of physical activity, cardiac disease and self efficacy scores remained significantly associated (p<0.05) with recurrence. The model was significant (p <0.001); with a R2 equivalent of 0.62. Examination of relationships between psychosocial factors and adherence to wearing compression hosiery found wearing compression hosiery was significantly positively associated with participants’ knowledge of the cause of their condition (p=0.002), higher self-efficacy scores (p=0.026) and lower depression scores (p=0.009). Analysis of data from the prospective study found there were 35 recurrences (44%) in the 12 months following healing and median time to recurrence was 27 weeks. After adjustment for potential confounders, a Cox proportional hazards regression model found that at least an hour/day of leg elevation, six or more days/week in Class 2 (20–25mmHg) or 3 (30–40mmHg) compression hosiery, higher social support scale scores and higher General Self-Efficacy scores remained significantly associated (p<0.05) with a lower risk of recurrence, while male gender and a history of DVT remained significant risk factors for recurrence. Overall the model was significant (p <0.001); with an R2 equivalent 0.72. Conclusions The high rates of recurrence found in the studies highlight the urgent need for further information in this area to support development of effective strategies for prevention. Overall, results indicate leg elevation, physical activity, compression hosiery and strategies to improve self-efficacy are likely to prevent recurrence. In addition, optimal management of depression and strategies to improve patient knowledge and self-efficacy may positively influence adherence to compression therapy. This research provides important information for development of strategies to prevent recurrence of venous leg ulcers, with the potential to improve health and decrease health care costs in this population.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.