993 resultados para Religions (Proposed, universal, etc.)
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Overall, computer models and simulations have a rather disappointing record within the management sciences as a tool for predicting the future. Social and market environments can be influenced by an overwhelming number of variables, and it is therefore difficult to use computer models to make forecasts or to test hypotheses concerning the relationship between individual behaviours and macroscopic outcomes. At the same time, however, advocates of computer models argue that they can be used to overcome the human mind's inability to cope with several complex variables simultaneously or to understand concepts that are highly counterintuitive. This paper seeks to bridge the gap between these two perspectives by suggesting that management research can indeed benefit from computer models by using them to formulate fruitful hypotheses.
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Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc. Therefore, such network applications can be protected from malware infection by monitoring their ports to see if incoming packets contain any executable contents. This paper proposes a content-classification scheme that identifies executable content in incoming packets. The proposed scheme analyzes the packet payload in two steps. It first analyzes the packet payload to see if it contains multimedia-type data (such as . If not, then it classifies the payload either as text-type (such as or executable. Although in our experiments the proposed scheme shows a low rate of false negatives and positives (4.69% and 2.53%, respectively), the presence of inaccuracies still requires further inspection to efficiently detect the occurrence of malware. In this paper, we also propose simple statistical and combinatorial analysis to deal with false positives and negatives.
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Review of Coping with Choices to Die, by C. G. Prado. Cambridge: Cambridge University Press, 2011.
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Thin solid films were extensively used in the making of solar cells, cutting tools, magnetic recording devices, etc. As a result, the accurate measurement of mechanical properties of the thin films, such as hardness and elastic modulus, was required. The thickness of thin films normally varies from tens of nanometers to several micrometers. It is thus challenging to measure their mechanical properties. In this study, a nanoscratch method was proposed for hardness measurement. A three-dimensional finite element method (3-D FEM) model was developed to validate the nanoscratch method and to understand the substrate effect during nanoscratch. Nanoindentation was also used for comparison. The nanoscratch method was demonstrated to be valuable for measuring hardness of thin solid films.
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This chapter contains sections titled: -Adolescent Depression and the Australian National Mental Health Strategies -Preventive Interventions and Adolescent Depression -The Rationale and Content of the Interventions -Evaluations of the Resourceful Adolescent Programs
Resourceful adolescent program : a universal approach to the prevention of depression in adolescents
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The main aim of this paper is to outline a proposed program of research which will attempt to quantify the extent of the problem of alcohol and other drugs in the Australian construction industry, and furthermore, develop an appropriate industry-wide policy and cultural change management program and implementation plan to address the problem. This paper will also present preliminary results from the study. The study will use qualitative and quantitative methods (in the form of interviews and surveys, respectively) to evaluate the extent of the problem of alcohol and other drug use in this industry, to ascertain the feasibility of an industry-wide policy and cultural change management program, and to develop an appropriate implementation plan. The study will be undertaken in several construction organisations, at selected sites in South Australia, Victoria and Northern Territory. It is anticipated that approximately 500 employees from the participating organisations across Australia will take part in the study. The World Health Organisation’s Alcohol Use Disorders Identification Test (AUDIT) will be used to measure the extent of alcohol use in the industry. Illicit drug use, ‘‘readiness to change’’, impediments to reducing impairment, feasibility of proposed interventions, and employee attitudes and knowledge regarding workplace AOD impairment, will also be measured through a combination of interviews and surveys. Among the preliminary findings, for 51% (n=127) of respondents, score on the AUDIT indicated alcohol use at hazardous levels. Of the respondents who were using alcohol at hazardous levels, 76% reported (n97) that they do not have a problem with drinking and 54% (n=68) reported that it would be easy to ‘‘cut down’’ or stop drinking. Nearly half (49%) of all respondents (n=122) had used marijuana/cannabis at some time prior to being surveyed. The use of other illicit substances was much less frequently reported. Preliminary interview findings indicated a lack of adequate employee knowledge regarding the physical effects of alcohol and other drugs in the workplace. As for conclusions, the proposed study will address a major gap in the literature with regard to the extent of the problem of alcohol and other drug use in the construction industry in Australia. The study will also develop and implement a national, evidence-based workplace policy, with the aim of mitigating the deleterious effects of alcohol and other drugs in this industry.
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Advances in safety research—trying to improve the collective understanding of motor vehicle crash causes and contributing factors—rest upon the pursuit of numerous lines of research inquiry. The research community has focused considerable attention on analytical methods development (negative binomial models, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might logically seek to know which lines of inquiry might provide the most significant improvements in understanding crash causation and/or prediction. It is the contention of this paper that the exclusion of important variables (causal or surrogate measures of causal variables) cause omitted variable bias in model estimation and is an important and neglected line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant opportunities to better understand contributing factors and/or causes of crashes. This study examines the role of important variables (other than Average Annual Daily Traffic (AADT)) that are generally omitted from intersection crash prediction models. In addition to the geometric and traffic regulatory information of intersection, the proposed model includes many spatial factors such as local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools—representing a mix of potential environmental and human factors that are theoretically important, but rarely used. Results suggest that these variables in addition to AADT have significant explanatory power, and their exclusion leads to omitted variable bias. Provided is evidence that variable exclusion overstates the effect of minor road AADT by as much as 40% and major road AADT by 14%.
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Process-aware information systems, ranging from generic workflow systems to dedicated enterprise information systems, use work-lists to offer so-called work items to users. In real scenarios, users can be confronted with a very large number of work items that stem from multiple cases of different processes. In this jungle of work items, users may find it hard to choose the right item to work on next. The system cannot autonomously decide which is the right work item, since the decision is also dependent on conditions that are somehow outside the system. For instance, what is “best” for an organisation should be mediated with what is “best” for its employees. Current work-list handlers show work items as a simple sorted list and therefore do not provide much decision support for choosing the right work item. Since the work-list handler is the dominant interface between the system and its users, it is worthwhile to provide an intuitive graphical interface that uses contextual information about work items and users to provide suggestions about prioritisation of work items. This paper uses the so-called map metaphor to visualise work items and resources (e.g., users) in a sophisticated manner. Moreover, based on distance notions, the work-list handler can suggest the next work item by considering different perspectives. For example, urgent work items of a type that suits the user may be highlighted. The underlying map and distance notions may be of a geographical nature (e.g., a map of a city or office building), but may also be based on process designs, organisational structures, social networks, due dates, calendars, etc. The framework proposed in this paper is generic and can be applied to any process-aware information system. Moreover, in order to show its practical feasibility, the paper discusses a full-fledged implementation developed in the context of the open-source workflow environment YAWL, together with two real examples stemming from two very different scenarios. The results of an initial usability evaluation of the implementation are also presented, which provide a first indication of the validity of the approach.
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The popularity of Bayesian Network modelling of complex domains using expert elicitation has raised questions of how one might validate such a model given that no objective dataset exists for the model. Past attempts at delineating a set of tests for establishing confidence in an entirely expert-elicited model have focused on single types of validity stemming from individual sources of uncertainty within the model. This paper seeks to extend the frameworks proposed by earlier researchers by drawing upon other disciplines where measuring latent variables is also an issue. We demonstrate that even in cases where no data exist at all there is a broad range of validity tests that can be used to establish confidence in the validity of a Bayesian Belief Network.
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As the service-oriented architecture paradigm has become ever more popular, different standardization efforts have been proposed by various consortia to enable interaction among heterongeneous environments through this paradigm. This chapter will overview the most prevalent of these SOA approaches. It will first show how technical services can be described, how they can interact with each other and be discovered by users. Next, the chapter will present different standards to facilitate service composition and to design service-oriented environments in light of a universal understanding of service orientation. The chapter will conclude with a summary and a discussion on the limitations of the reviewed standards along their ability to describe service properties. This paves the way to the next chapters where the USDL standard will be presented, which aims to lift such limitations.
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Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.
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Bactrocera dorsalis (Hendel) and B. papayae Drew & Hancock represent a closely related sibling species pair for which the biological species limits are unclear; i.e., it is uncertain if they are truely two biological species, or one biological species which has been incorrectly taxonomically split. The geographic ranges of the two taxa are thought to abut or overlap on or around the Isthmus of Kra, a recognised biogeographic barrier located on the narrowest portion of the Thai Peninsula. We collected fresh material of B. dorsalis sensu lato (i.e., B. dorsalis sensu stricto + B. papayae) in a north-south transect down the Thai Peninsula, from areas regarded as being exclusively B. dorsalis s.s., across the Kra Isthmus, and into regions regarded as exclusively B. papayae. We carried out microsatellite analyses and took measurements of male genitalia and wing shape. Both the latter morphological tests have been used previously to separate these two taxa. No significant population structuring was found in the microsatellite analysis and results were consistent with an interpretation of one, predominantly panmictic population. Both morphological datasets showed consistent, clinal variation along the transect, with no evidence for disjunction. No evidence in any tests supported historical vicariance driven by the Isthmus of Kra, and none of the three datasets supported the current taxonomy of two species. Rather, within and across the area of range overlap or abutment between the two species, only continuous morphological and genetic variation was recorded. Recognition that morphological traits previously used to separate these taxa are continuous, and that there is no genetic evidence for population segregation in the region of suspected species overlap, is consistent with a growing body of literature that reports no evidence of biological differentiation between these taxa.