Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.

The case for the ability-based model of emotional intelligence in organizational behavior

In this second counterpoint article, we refute the claims of Landy, Locke, and Conte, and make the more specific case for our perspective, which is that ability-based models of emotional intelligence have value to add in the domain of organizational psychology. In this article, we address remaining issues, such as general concerns about the tenor and tone of the debates on this topic, a tendency for detractors to collapse across emotional intelligence models when reviewing the evidence and making judgments, and subsequent penchant to thereby discount all models, including the ability-based one, as lacking validity. We specifically refute the following three claims from our critics with the most recent empirically based evidence: (1) emotional intelligence is dominated by opportunistic academics-turned-consultants who have amassed much fame and fortune based on a concept that is shabby science at best; (2) the measurement of emotional intelligence is grounded in unstable, psychometrically flawed instruments, which have not demonstrated appropriate discriminant and predictive validity to warrant/justify their use; and (3) there is weak empirical evidence that emotional intelligence is related to anything of importance in organizations. We thus end with an overview of the empirical evidence supporting the role of emotional intelligence in organizational and social behavior.

Emotion and performance

The study of emotions in organizational settings has attained considerable prominence in recent years, but I critical issue remains unresolved. This is the relationship between emotion and performance. in this special issue, 5 articles address this topic from a variety of viewpoints. Two are theoretical essays that deal, respectively, with emotion and creativity and the relationships between individual and team performance. Three are empirical studies that canvass the emotion-performance nexus across levels of analysis: within person, between persons, and in groups. Between them, the 5 articles present a strong case for the nexus of emotions and performance, but, more important, they provide a platform for potentially fruitful future research in this burgeoning area.

Diversity and Emotion: The New Frontiers in Organizational Behavior Research

This article provides a review of recent developments in two topical areas of research in contemporary organizational behavior: diversity and emotions. In the section called “Diversity,”we trace the history of diversity research, explore the definitions and paradigms used in treatments of diversity, and signal new areas of interest. We conclude that organizational behavior in the 21st century is evolving to embrace a more eclectic and holistic view of humans at work. In the section called “Emotions,” we turn our attention to recent developments in the study of emotions in organizations. We identify four major topics: mood theory, emotional labor, affective events theory (AET), and emotional intelligence, and argue that developments in the four domains have significant implications for organizational research, and the progression of the study of organizational behavior. As with the study of diversity, the topic of emotions in the workplace is shaping up as one of the principal areas of development in management thought and practice for the next decade. Finally, we discuss in our conclusion how these two areas are being conceptually integrated, and the implications for management scholarship and research in the contemporary world.

Task Complexity and Variation in L2 Learner’s Oral Discourse

There are many factors which affect the L2 learner’s performance at the levels of phonology, morphology and syntax. Consequently when L2 learners attempt to communicate in the target language, their language production will show systematic variability across the above mentioned linguistic domains. This variation can be attributed to some factors such as interlocutors, topic familiarity, prior knowledge, task condition, planning time and tasks types. This paper reports the results of an on going research investigating the issue of variability attributed to the task type. It is hypothesized that the particular type of task learners are required to perform will result in variation in their performance. Results of the statistical analyses of this study investigating the issue of variation in the performance of twenty L2 learners at the English department of Tabriz University provided evidence in support of the hypothesis that performance of L2 learners show systematic variability attributed to task.

Proof Explanation in the DR-DEVICE System

Trust is a vital feature for Semantic Web: If users (humans and agents) are to use and integrate system answers, they must trust them. Thus, systems should be able to explain their actions, sources, and beliefs, and this issue is the topic of the proof layer in the design of the Semantic Web. This paper presents the design and implementation of a system for proof explanation on the Semantic Web, based on defeasible reasoning. The basis of this work is the DR-DEVICE system that is extended to handle proofs. A critical aspect is the representation of proofs in an XML language, which is achieved by a RuleML language extension.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Development of a dietary supplement database

Data describing the composition of dietary supplements are not readily available to the public health community. As a result, intake from dietary supplements is generally not considered in most dietary surveys and, hence, little is known about the significance of supplement intake in relation to total diet or disease risk. To enable a more comprehensive analysis of dietary data, a database of the composition of various dietary supplements has been compiled. Active ingredients of all dietary supplements sold in Australia are included in the Australian Register of Therapeutic Goods (ARTG), maintained by the Therapeutic Goods Administration. Products included in the database were restricted to those vitamin, mineral and other supplements identified in dietary data collected from studies conducted in southeast Queensland and New South Wales (850 supplements). Conversion factors from ingredients compounds to active elements were compiled from standard sources. No account has been made for bioavailability, consistent with current practice for food composition databases. The database can be queried by ARTG identification number, brand, product title, or a variety of other fields. Expected future developments include development of standard formulations for use when supplements are incompletely specified, and expansion of products included for more widespread use.

Expressed sequenced tags and new genes from the cattle tick, Boophilus microplus

We used the expressed sequenced tags (ESTs) approach to study the genome of the cattle tick Boophilus microplus. One hundred and forty-two of our 234 unique ESTs were from genes not previously identified from ticks, mites or any other arachnids. The largest class of identified ESTs (29%) was from genes involved in transcription and translation. Ninety-one ESTs (39% of all ESTs) did not match any sequences in international databases; some of these may be specific to ticks. Thirteen percent of our ESTs were from ribosomal proteins and two ESTs were for genes implicated in resistance to pesticides. (C) 1998 Chapman & Hall Ltd.

Moneyless business exchange - Practitioners' attitudes to business-to-business barter in Australia

In recent years, domestic business-to-business barter has become institutionalized as an alternative marketing exchange system in Australia, and elsewhere. This article reports the findings of a survey of 164 members of Australia's largest trade exchange, Bartercard There are few, if any, published empirical studies on this topic. This study is exploratory. Most firms surveyed are small firms in the services sectors. Although Bartercard has an extensive membership, trading within the system is limited with most members trading less than once per week and with barter transactions contributing less than 5% of their annual gross sales. The main benefits of membership include new customers and increased sales and networking opportunities. The main limitations include the limited functionality of the trade dollar limited trading opportunities, and practical trading difficulties. In selling, there appears to be no differential between the cash and trade prices, whereas trade dollars are discounted in purchasing. Participants acknowledge that business-to-business barter will remain and grow regardless of cyclical macroeconomic changes. (C) 1998 Elsevier Science Inc.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Interval breast cancers in an Australian mammographic screening program

Objective: To determine the incidence of interval cancers which occurred in the first 12 months after mammographic screening at a mammographic screening service. Design: Retrospective analysis of data obtained by crossmatching the screening Service and the New South Wales Central Cancer Registry databases. Setting: The Central & Eastern Sydney Service of BreastScreen NSW. Participants: Women aged 40-69 years at first screen, who attended for their first or second screen between 1 March 1988 and 31 December 1992. Main outcome measures: Interval-cancer rates per 10 000 screens and as a proportion of the underlying incidence of breast cancer (as estimated by the underlying rate in the total NSW population). Results: The 12-month interval-cancer incidence per 10 000 screens was 4.17 for the 40-49 years age group (95% confidence interval [CI], 1.35-9.73) and 4.64 for the 50-69 years age group (95% CI, 2.47-7.94). Proportional incidence rates were 30.1% for the 40-49 years age group (95% CI, 9.8-70.3) and 22% for the 50-69 years age group (95% CI, 11.7-37.7). There was no significant difference between the proportional incidence rate for the 50-69 years age group for the Central & Eastern Sydney Service and those of major successful overseas screening trials. Conclusion: Screening quality was acceptable and should result in a significant mortality reduction in the screened population. Given the small number of cancers involved, comparison of interval-cancer statistics of mammographic screening programs with trials requires age-specific or age-adjusted data, and consideration of confidence intervals of both program and trial data.

Educational characteristics of students with high or low self-concept

In response to methodological concerns associated with previous research into the educational characteristics of students with high or low self-concept, the topic was re-examined using a significantly more representative sample and a contemporary self-concept measure. From an initial screening of 515 preadolescent, coeducational students in 18 schools, students significantly high or low in self-concept were compared using standardized tests in reading, spelling, and mathematics, and teacher interviews to determine students' academic and nonacademic characteristics. The teachers were not informed of the self-concept status of the students. Compared to students with low self-concept, students with high self-concept were rated by teachers as being more popular, cooperative, and persistent in class, showed greater leadership, were lower in anxiety, had more supportive families, and had higher teacher expectations for their future success. Teachers observed that students with low self-concept were quiet and withdrawn, while peers with high self-concept were talkative and more dominating with peers. Students with lower self-concepts were also lower than their peers in reading, spelling, and mathematical abilities. The findings support the notion that there is an interactive relationship between self-concept and achievement. (C) 1998 John Wiley & Sons, Inc.

Unsupervised cell nucleus segmentation with active contours

The task of segmenting cell nuclei from cytoplasm in conventional Papanicolaou (Pap) stained cervical cell images is a classical image analysis problem which may prove to be crucial to the development of successful systems which automate the analysis of Pap smears for detection of cancer of the cervix. Although simple thresholding techniques will extract the nucleus in some cases, accurate unsupervised segmentation of very large image databases is elusive. Conventional active contour models as introduced by Kass, Witkin and Terzopoulos (1988) offer a number of advantages in this application, but suffer from the well-known drawbacks of initialisation and minimisation. Here we show that a Viterbi search-based dual active contour algorithm is able to overcome many of these problems and achieve over 99% accurate segmentation on a database of 20 130 Pap stained cell images. (C) 1998 Elsevier Science B.V. All rights reserved.

International tourists and road safety in Australia: developing a national research and management programme

Motor vehicle crashes are the leading cause of injury death for international tourists. This makes road safety an important issue for tourism authorities. Unfortunately, as it is in other areas of tourist health, the common response from the travel and tourism industry is to remain silent about this problem and to leave any mishaps in the hands of insurers. At the same time, but for different reasons, international tourists are not usually targeted for road safety initiatives by transport authorities. Given that there are considerable 'hidden' costs associated with international tourists and motor vehicle crashes, the topic should be of concern to both tourism and transport groups. This paper examines issues concerned with driving in unfamiliar surroundings for international visitors in Australia, and proposes a national research and management programme to guide policy and planning in the area. (C) 1999 Elsevier Science Ltd. All rights reserved.