Determinants of listed property trust bond ratings : Australian evidence

Using artificial neural networks (ANN) and ordinal regression (OR) as alternative methods to predict LPT bond ratings, we examine the role that various financial and industry variables have on Listed Property Trust (LPT) bond ratings issued by Standard and Poor’s from 1999-2006. Our study shows that both OR and ANN provide robust alternatives to rating LPT bonds and that there are no significant differences in results between the two full models. OR results show that of the financial variables used in our models, debt coverage and financial leverage ratios have the most profound effect on LPT bond ratings. Further, ANN results show that 73.0% of LPT bond rating is attributable to financial variables and 23.0% to industry-based variables with office LPT sector accounting for 2.6%, retail LPT 10.9% and stapled management structure 13.5%.

A study of Chinese private passenger cars based on BP neural network

This study employs BP neural network to simulate the development of Chinese private passenger cars. Considering the uncertain and complex environment for the development of private passenger cars, indicators of economy, population, price, infrastructure, income, energy and some other fields which have major impacts on it are selected at first. The network is proved to be operable to simulate the progress of chinese private passenger cars after modeling, training and generalization test. Based on the BP neural network model, sensitivity analysis of each indicator is carried on and shows that the sensitivity coefficients of fuel price change suddenly. This special phenomenon reveals that the development of Chinese private passenger cars may be seriously affected by the recent high fuel price. This finding is also consistent with facts and figures

Application of system dynamics for evaluating truck load regulations in Anhui, China

In the critical situation of prevailing overweight transportation and crag-fast enforcement in Chinese highway networks, this paper develops a methodological framework for truck weight regulation (TWR) evaluation using System Dynamics (SD). Composed of five interrelated subsystems, the framework is able to capture the highway, vehicle and freight variables that influence the effect of TWR and transportation efficiency over time. It specifically describes the development and use of the Truck Weight Regulation Evaluating Model (TWREM) for the highway freight system in Anhui province, China. Three policy alternatives are analyzed: 1) tolerant policy approach, which allows heavy-duty freight activity to continue in its current state, and is shown to lead to nearly catastrophic results; 2) rigid policy approach, which would terminate all heavy-duty freight activities immediately, and is shown to be economically infeasible; and 3) moderate policy approach, which advocates a gradual reduction of heavy-duty freight activities to a moderate state. The simulation results shows that the moderate policy approach is the most appropriate option to solve the social and economic problems arising from the activities of the heavy-duty freight transportation in Anhui. In addition, some suggestions of TWR policy in China are also made in this paper.

2,4-Diodoaniline

The structure of the title compound C6H6I2N shows a weak intermolecular amine-amine N--H...N hydrogen-bonding interaction giving a helical chain which extends along the axis. An intramolecular N-H...I hydrogen bond is also observed.

8-Ammonionaphthalene-2-sulfonate monohydrate : the zwitterionic hydrate of 1,7-Cleve's acid

The structure of 8-amino-2-naphthalenesulfonic acid monohydrate (1,7-Cleve's acid hydrate), C10H9NO3S.H2O, shows the presence of a sulfonate-aminium group zwitterion, both groups and the water molecule of solvation giving cyclic R3/3(8) intermolecular hydrogen-bonding interactions forming chains which extend down a axis of the unit cell. Additional peripheral associations, including weak aromatic ring pi-pi interactions [centroid-centroid distance 3.6299(15)A], result in a two-dimensional sheet structure.

A review on reliability models with covariates

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Suitable mathematical models that are capable of predicting Time-to-Failure (TTF) and the probability of failure in future time are essential. In traditional reliability models, the lifetime of assets is estimated using failure time data. However, in most real-life situations and industry applications, the lifetime of assets is influenced by different risk factors, which are called covariates. The fundamental notion in reliability theory is the failure time of a system and its covariates. These covariates change stochastically and may influence and/or indicate the failure time. Research shows that many statistical models have been developed to estimate the hazard of assets or individuals with covariates. An extensive amount of literature on hazard models with covariates (also termed covariate models), including theory and practical applications, has emerged. This paper is a state-of-the-art review of the existing literature on these covariate models in both the reliability and biomedical fields. One of the major purposes of this expository paper is to synthesise these models from both industrial reliability and biomedical fields and then contextually group them into non-parametric and semi-parametric models. Comments on their merits and limitations are also presented. Another main purpose of this paper is to comprehensively review and summarise the current research on the development of the covariate models so as to facilitate the application of more covariate modelling techniques into prognostics and asset health management.

High-level concept annotation using ontology and probabilistic inference

Image annotation is a significant step towards semantic based image retrieval. Ontology is a popular approach for semantic representation and has been intensively studied for multimedia analysis. However, relations among concepts are seldom used to extract higher-level semantics. Moreover, the ontology inference is often crisp. This paper aims to enable sophisticated semantic querying of images, and thus contributes to 1) an ontology framework to contain both visual and contextual knowledge, and 2) a probabilistic inference approach to reason the high-level concepts based on different sources of information. The experiment on a natural scene database from LabelMe database shows encouraging results.

Cate Consandine

The interpretation of evidence dominates contemporary television crime shows. Inanimate objects and disparate facts are made to speak; technology and expert opinion wring out their stories. In examining these dead pieces of evidence, the investigators search for patterns, discovering living perpetrators and fugitives. Psychology comes in where the evidence is interpreted; the investigators try to think through perpetrators' minds and presumably perverse rationales. Objects are examined. Banal things become precious, put into bags, marked, date- and time-stamped, and stepped around carefully. After a crime, the objects involved are different. After a crime show, our gaze is different; everything is potentially incriminating, perverse. Bags without people don't make sense. Under this gaze, objects acquire a psychology. When we look at a crime scene, the evidence violates us. The work of Melbourne artist Cate Consandine is about objects and how they occupy the space that they occupy. In her practice as a sculptor and throughout her studies at the Victorian College of the Arts, the Sydney College of the Arts, and now Monash, her work has cultivated violent ambiguity. Consandine's work extends across a range of different media, particularly vidoe, objects and spaces. Like a crime show, it activates a particular type of inquisition from the viewer.

Decision support system for improving construction companies’ business performance

As part of a decision making process, the controlling process in construction companies can be supported by computer application that provides faster and reliable decision. This paper discusses the development of a knowledge-based decision support system for controlling construction companies’ business performance. The knowledge-base was developed using questionnaire survey and case studies. A questionnaire survey was conducted to identify potential problems that can occur in construction companies as well as the source of the problems and their impact on companies’ performance. Case studies were used to identify and analyse various corrective actions. The result of the study shows that decision support system using knowledge-based management system improves the effectiveness and the efficiency of decision making process for selecting the most appropriate corrective action that can improve construction companies’ performance. The application, which had been developed in this research, was designed to support the process of controlling construction companies’ business performance and to assist young manager in selecting the most optimum corrective actions for the problems related to achieving companies’ objectives. This computer application can be used as a learning tool for identifying potential problems that a construction company faces and the most optimum corrective action.

Institutional problems of the emerging scientific community in Iran

This article attempts to explore the concept of scientific community at the macro-national level in the context of Iran. Institutionalisation of science and its professional growth has been constrained by several factors. The article first conceptualises the notion of science community as found in the literature in the context of Iran, and attempts to map through some indicators. The main focus, however, lies in mapping some institutional problems through empirical research. This was undertaken in 2002–04 in order to analyse the structure of the scientific community in Iran in the ‘exact sciences’ (mathematics, physics, chemistry, biology and earth sciences). The empirical work was done in two complementary perspectives: through a questionnaire and statistical analysis of it, and through semistructured interviews with the researchers. There are number of problems confronting scientists in Iran. Facilities provided by institutions is one of the major problems of research. Another is the tenuous cooperation among scientists. This is reported by most of the researchers, who deplore the lack of cooperation among their group. Relationships are mostly with the Ph.D. students and only marginally with colleagues. Our research shows that the more brilliant the scientists, the more frustrated they are from scientific institutions in Iran. Medium-range researchers seem to be much happier about the scientific institution to which they belong than the brighter scholars. The scientific institutions in Iran seem to be built for the needs of the former rather than the latter. These institutions seem not to play a positive role in the case of the best scientists. On the whole, many ingredients of the scientific community, at least at its inception, are present among Iranian scientists: the strong desire for scientific achievement in spite of personal, institutional and economic problems.

Temporal construal in advertising : the moderating role of temporal orientation and attribute importance in consumer evaluations

In two experiments, we study how the temporal orientation of consumers (i.e., future-oriented or present-oriented), temporal construal (distant future, near future), and product attribute importance (primary, secondary) influence advertisement evaluations. Data suggest that future-oriented consumers react most favorably to ads that feature a product to be released in the distant future and that highlight primary product attributes. In contrast, present-oriented consumers prefer near-future ads that highlight secondary product attributes. Study 2 shows that consumer attitudes are mediated by perceptions of attribute diagnosticity (i.e., the perceived usefulness of the attribute information). Together, these experiments shed light on how individual differences, such as temporal orientation, offer valuable insights into temporal construal effects in advertising.

Effects of susceptibility to normative influence and type of testimonial on attitudes toward print advertising

In two experiments, we show how a consumer’s susceptibility to normative influence (SNI) offers useful insights into the effectiveness of two types of testimonials: a typical person endorsement (Study 1) and a celebrity endorsement (Study 2). Specifically, we suggest that two variables moderate testimonial effects—SNI and product attribute information. Results show that in forming their evaluations, high-SNI consumers place a greater emphasis on the testimonial than on the attribute information. In contrast, low-SNI consumers are more influenced by attribute information. A mediation analysis shows that advertising attitudes for high-SNI consumers are mediated by testimonial thoughts, whereas the attitudes for low-SNI consumers are mediated by their attribute thoughts. Theoretical and managerial implications are presented.

The influence of ad model ethnicity and self-referencing on attitudes evidence from New Zealand

This paper examines consumers self-referencing as a mechanism for explaining ethnicity effects in advertising. Data was collected from a 2 (model ethnicity: Asian, white) x 2 (product stereotypicality: stereotypical, non-stereotypical) experiment. Measured independent variables included participant ethnicity and self-referencing. Results shows that (1) Asian exhibit greater self-referencing of Asian models than whites do; (2) self-referencing mediates ethnicity effects on attitude ( ie, attitude towards the model, attitude toward the add, brand attitude, and purchase intentions); (3) high self-referencing Asian have more favourable attitude towards the add and purchase intentions than low self referencing Asians; and (4) Asian models advertising atypical products generate more self-referencing and more favourable attitudes toward the model, A, and purchase intentions for both Asians and whites.

Prognosis of bearing failure based on health state estimation

This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

Adaptive load shedding and regional protection

The requirement for improved efficiency whilst maintaining system security necessitates the development of improved system analysis approaches and the development of advanced emergency control technologies. Load shedding is a type of emergency control that is designed to ensure system stability by curtailing system load to match generation supply. This paper presents a new adaptive load shedding scheme that provides emergency protection against excess frequency decline, whilst minimizing the risk of line overloading. The proposed load shedding scheme uses the local frequency rate information to adapt the load shedding behaviour to suit the size and location of the experienced disturbance. The proposed scheme is tested in simulation on a 3-region, 10-generator sample system and shows good performance.