Management framework for corporate telecommunication and data centre information security

Network security, particularly Internet security, is at the forefront of business and government networks. This research has discovered weaknesses in current professional practice, particularly in mitigation strategies to reduce the impacts of security violations in corporate telecommunications and data centres. The importance of integrating security policies, processes and operational practice is demonstrated. Leadership models and innovation mechanisms best suited to improved security design are also identified.

Subjective wellbeing and families : issues of measurement and data interpretation

Since April 2001 we have been monitoring the Subjective Wellbeing (SWB) of the Australian population using the Personal Wellbeing Index. Our aims are to establish normative values and to identify people with abnormally low SWB. Each of 18 surveys has involved a new sample of 2,000 people, randomly chosen but representing the geographical distribution of the population. The data are remarkable for their stability, with the variation in population mean scores being just 3.2 percentage points. The cause of such high reliability is Subjective Wellbeing Homeostasis. Here, in a manner analogous to the management of body temperature, the SWB for each person is normally held positive and within a narrow set-point range. However, all homeostatic systems have a limited capacity to absorb challenge and when aversive experiences are both strong and sustained, homeostasis fails. If this occurs, people lose their normal positive view of themselves and become depressed. Therefore, the second aim of these studies is to reveal the demographic character of families in distress, who are in need of additional resources. Our data reveal the extent to which family structure and responsibilities impact on wellbeing. They also yield important diagnostic information about individuals, and point to SWB as a crucial measure of intervention outcome. In sum, the Personal Wellbeing Index is a simple, reliable and valid measure of SWB. The measures it yields are theoretically embedded, they can be compared against solid normative data, and their interpretation is enhanced through an understanding of SWB homeostasis.

Animal migration : linking models and data beyond taxonomic limits

An international workshop on animal migration was held at the Lorentz Center in Leiden, The Netherlands, 2–6 March 2009, bringing together leading theoreticians and empiricists from the major migratory taxa, aiming at the identification of cutting-edge questions in migration research that cross taxonomic borders.

Yhh1p/Cft1p directly links poly(A) site recognition and RNA polymerase II transcription termination

RNA polymerase II (pol II) transcription termination requires co-transcriptional recognition of a functional polyadenylation signal, but the molecular mechanisms that transduce this signal to pol II remain unclear. We show that Yhh1p/Cft1p, the yeast homologue of the mammalian AAUAAA interacting protein CPSF 160, is an RNA-binding protein and provide evidence that it participates in poly(A) site recognition. Interestingly, RNA binding is mediated by a central domain composed of predicted -propeller-forming repeats, which occurs in proteins of diverse cellular functions. We also found that Yhh1p/Cft1p bound specifically to the phosphorylated C-terminal domain (CTD) of pol II in vitro and in a two-hybrid test in vivo. Furthermore, transcriptional run-on analysis demonstrated that yhh1 mutants were defective in transcription termination, suggesting that Yhh1p/Cft1p functions in the coupling of transcription and 3'-end formation. We propose that direct interactions of Yhh1p/Cft1p with both the RNA transcript and the CTD are required to communicate poly(A) site recognition to elongating pol II to initiate transcription termination.

The recognition and protection of well-known trade marks in Indonesia

Legal context The recognition and protection of well-known marks in Indonesia has improved over the last few years for a variety of reasons.

Key points First, the Asian Crisis resulted in the creation of a Commercial Court, which is a clear improvement over the previously responsible District Courts. Secondly, the increasingly frequent publication of court decisions has improved transparency and consistency of those decisions. Well-known marks are now clearly protected against use for similar goods/services. Protection is extended to dissimilar goods/services by applying Article 16(3) TRIPS directly or by arguing that registration occurred in bad faith. Nevertheless, decisions thus far concern almost exclusively revocation and invalidity of registrations. Civil remedies such as damages and interim injunctions are hardly used, because the outdated civil procedural law has not familiarised judges with such legal instruments. Clearing the register of infringing registrations is another matter of concern. Cancellation for non-use for three consecutive years can be difficult, because the plaintiff is required to provide evidence of the last use in the production of the goods/services rather than in the course of trade more generally.

Practical significance While it has become much easier to protect well-known marks in Indonesia, much work remains to be done regarding the procedural framework of civil infringement proceedings and regarding the clearing of the register.

Polar transformation system for offline handwritten character recognition

Offline handwritten recognition is an important automated process in pattern recognition and computer vision field. This paper presents an approach of polar coordinate-based handwritten recognition system involving Support Vector Machines (SVM) classification methodology to achieve high recognition performance. We provide comparison and evaluation for zoning feature extraction methods applied in Polar system. The recognition results we proposed were trained and tested by using SVM with a set of 650 handwritten character images. All the input images are segmented (isolated) handwritten characters. Compared with Cartesian based handwritten recognition system, the recognition rate is more stable and improved up to 86.63%.

Facial affect recognition and schizotypal personality characteristics

Aim: Deficits in facial affect recognition are well established in schizophrenia, yet relatively little research has examined facial affect recognition in hypothetically psychosis-prone or ‘schizotypal’ individuals. Those studies that have examined social cognition in psychosis-prone individuals have paid little attention to the association between facial emotion recognition and particular schizotypal personality features. The present study therefore sought to investigate relationships between facial emotion recognition and the different aspects of schizotypy.

Methods: Facial affect recognition accuracy was examined in 50 psychiatrically healthy individuals assessed for level of schizotypy using the Schizotypal Personality Questionnaire. This instrument provides a multidimensional measure of schizophrenia proneness, encompassing ‘cognitive-perceptual’, ‘interpersonal’ and ‘disorganized’ features of schizotypy. It was hypothesized that the cognitive-perceptual and interpersonal aspects of schizotypy would be associated with difficulties identifying facial expressions of emotion during a forced-choice recognition task using a standardized series of colour photographs.

Results: As predicted, interpersonal aspects of schizotypy (particularly social anxiety) were associated with reduced accuracy on the facial affect recognition task, but there was no association between affect recognition accuracy and cognitive-perceptual features of schizotypy.

Conclusions: These results suggest that subtle deficits in facial affect recognition in otherwise psychiatrically healthy individuals may be related to the vulnerability for interpersonal communication difficulties, as seen in schizophrenia.

A hybrid neural classifier for dimensionality reduction and data visualization and its application to fault detection and classification of induction motors

In this paper, a hybrid neural classifier combining the auto-encoder neural network and the Lattice Vector Quantization (LVQ) model is described. The auto-encoder network is used for dimensionality reduction by projecting high dimensional data into the 2D space. The LVQ model is used for data visualization by forming and adapting the granularity of a data map. The mapped data are employed to predict the target classes of new data samples. To improve classification accuracy, a majority voting scheme is adopted by the hybrid classifier. To demonstrate the applicability of the hybrid classifier, a series of experiments using simulated and real fault data from induction motors is conducted. The results show that the hybrid classifier is able to outperform the Multi-Layer Perceptron neural network, and to produce very good classification accuracy rates for various fault conditions of induction motors.