Granule mining and its application for network traffic characterization

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.

Strategizing public sector human resource management : the implications of working network

Networks have come to the fore as a means by which government can achieve its strategic objectives, particularly when addressing complex or “wicked” issues. Such joined-up arrangements differ in their operations from other forms of organizing as they require collaborative effort to deliver the collaborative advantage. Strategic Human Resource Management is concerned with the matching of human resource practices to the strategic direction of organizations. It is argued that the strategic direction of government has been towards network involvement and that, as a result, a reconfiguration of Human Resource Management practices is needed to support this new direction. Drawing on eight network case studies findings are presented in relation to the roles government is expected to play in networks and conclusions are drawn about what types of human resource management practices would best support those roles. Implications for Strategic Human Resource Management are posited.

Assessing the representativeness of a groundwater quality monitoring network

The monitoring sites comprising a state of the environment (SOE) network must be carefully selected to ensure that they will be representative of the broader resource. Hierarchical cluster analysis (HCA) is a data-driven technique that can potentially be employed to assess the representativeness of a SOE monitoring network. The objective of this paper is to explore the use of HCA as an approach for assessing the representativeness of the New Zealand National Groundwater Monitoring Programme (NGMP), which is comprised of 110 monitoring sites across the country.

Cold and heat waves in the United States

Extreme cold and heat waves, characterised by a number of cold or hot days in succession, place a strain on people’s cardiovascular and respiratory systems. The increase in deaths due to these waves may be greater than that predicted by extreme temperatures alone. We examined cold and heat waves in 99 US cities for 14 years (1987–2000) and investigated how the risk of death depended on the temperature threshold used to define a wave, and a wave’s timing, duration and intensity. We defined cold and heat waves using temperatures above and below cold and heat thresholds for two or more days. We tried five cold thresholds using the first to fifth percentiles of temperature, and five heat thresholds using the ninety-fifth to ninety-ninth percentiles. The extra wave effects were estimated using a two-stage model to ensure that their effects were estimated after removing the general effects of temperature. The increases in deaths associated with cold waves were generally small and not statistically significant, and there was even evidence of a decreased risk during the coldest waves. Heat waves generally increased the risk of death, particularly for the hottest heat threshold. Cold waves of a colder intensity or longer duration were not more dangerous. Cold waves earlier in the cool season were more dangerous, as were heat waves earlier in the warm season. In general there was no increased risk of death during cold waves above the known increased risk associated with cold temperatures. Cold or heat waves earlier in the cool or warm season may be more dangerous because of a build up in the susceptible pool or a lack of preparedness for cold or hot temperatures.

Neural network-based detection of virtual environment anomalies

The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.

Development of network-level project screening methods supporting the 4-Year pavement management plan in Texas

The Texas Department of Transportation (TxDOT) is concerned about the widening gap between pavement preservation needs and available funding. Thus, the TxDOT Austin District Pavement Engineer (DPE) has investigated methods to strategically allocate available pavement funding to potential projects that improve the overall performance of the District and Texas highway systems. The primary objective of the study presented in this paper is to develop a network-level project screening and ranking method that supports the Austin District 4-year pavement management plan development. The study developed candidate project selection and ranking algorithms that evaluated pavement conditions of each project candidate using data contained in the Pavement Management Information system (PMIS) database and incorporated insights from Austin District pavement experts; and implemented the developed method and supporting algorithm. This process previously required weeks to complete, but now requires about 10 minutes including data preparation and running the analysis algorithm, which enables the Austin DPE to devote more time and resources to conducting field visits, performing project-level evaluation and testing candidate projects. The case study results showed that the proposed method assisted the DPE in evaluating and prioritizing projects and allocating funds to the right projects at the right time.

Symptoms of heat illness in surface mine workers

Objective: To assess the symptoms of heat illness experienced by surface mine workers. Methods: Ninety-one surface mine workers across three mine sites in northern Australia completed a heat stress questionnaire evaluating their symptoms for heat illness. A cohort of 56 underground mine workers also participated for comparative purposes. Participants were allocated into asymptomatic, minor or moderate heat illness categories depending on the number of symptoms they reported. Participants also reported the frequency of symptom experience, as well as their hydration status (average urine colour). Results: Heat illness symptoms were experienced by 87 and 79 % of surface and underground mine workers, respectively (p = 0.189), with 81–82 % of the symptoms reported being experienced by miners on more than one occasion. The majority (56 %) of surface workers were classified as experiencing minor heat illness symptoms, with a further 31 % classed as moderate; 13 % were asymptomatic. A similar distribution of heat illness classification was observed among underground miners (p = 0.420). Only 29 % of surface miners were considered well hydrated, with 61 % minimally dehydrated and 10 % significantly dehydrated, proportions that were similar among underground miners (p = 0.186). Heat illness category was significantly related to hydration status (p = 0.039) among surface mine workers, but only a trend was observed when data from surface and underground miners was pooled (p = 0.073). Compared to asymptomatic surface mine workers, the relative risk of experiencing minor and moderate symptoms of heat illness was 1.5 and 1.6, respectively, when minimally dehydrated. Conclusions: These findings show that surface mine workers routinely experience symptoms of heat illness and highlight that control measures are required to prevent symptoms progressing to medical cases of heat exhaustion or heat stroke.

National Institute for Clinical Studies Report for Phase 1, Evidence Uptake Network : Best Practice Community Care for Clients with Chronic Venous Leg Ulcers

Chronic leg ulcers cause significant pain, cost, decreased quality of life and morbidity for a considerable segment of the older population (Graham et al., 2003a). At any given time the prevalence of patients with open leg ulcers receiving treatment is between 0.11% - 0.18% (Briggs & Closs 2003). Chronic leg ulcers occur in approximately 1 - 2% of the over 60 population in the US, UK, Europe and Australia (Baker & Stacey 1994; Johnson 1995; Lees & Lambert 1992; Margolis et al. 2002). Considerable research has been undertaken to determine the best treatment practices that will aid in the management and the healing of these ulcers, and practical and effective strategies and techniques for healing venous leg ulcers have been trialled to demonstrate their beneficial effects (Nelson et al. 2004; Cullum et al. 2001)...

Thermoregulatory responses to ice-slush beverage ingestion and exercise in the heat

We compared the effects of an ice-slush beverage (ISB) and a cool liquid beverage (CLB) on cycling performance, changes in rectal temperature (T (re)) and stress responses in hot, humid conditions. Ten trained male cyclists/triathletes completed two exercise trials (75 min cycling at similar to 60% peak power output + 50 min seated recovery + 75% peak power output x 30 min performance trial) on separate occasions in 34A degrees C, 60% relative humidity. During the recovery phase before the performance trial, the athletes consumed either the ISB (mean +/- A SD -0.8 +/- A 0.1A degrees C) or the CLB (18.4 +/- A 0.5A degrees C). Performance time was not significantly different after consuming the ISB compared with the CLB (29.42 +/- A 2.07 min for ISB vs. 29.98 +/- A 3.07 min for CLB, P = 0.263). T (re) (37.0 +/- A 0.3A degrees C for ISB vs. 37.4 +/- A 0.2A degrees C for CLB, P = 0.001) and physiological strain index (0.2 +/- A 0.6 for ISB vs. 1.1 +/- A 0.9 for CLB, P = 0.009) were lower at the end of recovery and before the performance trial after ingestion of the ISB compared with the CLB. Mean thermal sensation was lower (P < 0.001) during recovery with the ISB compared with the CLB. Changes in plasma volume and the concentrations of blood variables (i.e., glucose, lactate, electrolytes, cortisol and catecholamines) were similar between the two trials. In conclusion, ingestion of ISB did not significantly alter exercise performance even though it significantly reduced pre-exercise T (re) compared with CLB. Irrespective of exercise performance outcomes, ingestion of ISB during recovery from exercise in hot humid environments is a practical and effective method for cooling athletes following exercise in hot environments.

The effects of increased endurance training load on biomarkers of heat intolerance during intense exercise in the heat

The effects of increased training (IT) load on plasma concentrations of lipopolysaccharides (LPS), proinflammatory cytokines, and anti-LPS antibodies during exercise in the heat were investigated in 18 male runners, who performed 14 days of normal training (NT) or 14 days of 20% IT load in 2 equal groups. Before (trial 1) and after (trial 2) the training intervention, all subjects ran at 70% maximum oxygen uptake on a treadmill under hot (35 degrees C) and humid (similar to 40%) conditions, until core temperature reached 39.5 degrees C or volitional exhaustion. Venous blood samples were drawn before, after, and 1.5 h after exercise. Plasma LPS concentration after exercise increased by 71% (trial 1, p < 0.05) and 21% (trial 2) in the NT group and by 92% (trial 1, p < 0.01) and 199% (trial 2, p < 0.01) in the IT group. Postintervention plasma LPS concentration was 35% lower before exercise (p < 0.05) and 47% lower during recovery (p < 0.01) in the IT than in the NT group. Anti-LPS IgM concentration during recovery was 35% lower in the IT than in the NT group (p < 0.05). Plasma interleukin (IL)-6 and tumor necrosis factor (TNF)-alpha concentrations after exercise (IL-6, 3-7 times, p < 0.01, and TNF-alpha, 33%, p < 0.01) and during recovery (IL-6, 2-4 times, p < 0.05, and TNF-alpha, 30%, p < 0.01) were higher than at rest within each group. These data suggest that a short-term tolerable increase in training load may protect against developing endotoxemia during exercise in the heat.

Larger or broader : performance implications of size and diversity of the knowledge worker's egocentric network. [更多或更广：知识员工个人中心网络大小和 多样性对绩效的影响]

Management scholars and practitioners emphasize the importance of the size and diversity of a knowledge worker's social network. Constraints on knowledge workers’ time and energy suggest that more is not always better. Further, why and how larger networks contribute to valuable outcomes deserves further understanding. In this study, we offer hypotheses to shed insight on the question of the diminishing returns of large networks and the specific form of network diversity that may contribute to innovative performance among knowledge workers. We tested our hypotheses using data collected from 93 R&D engineers in a Sino-German automobile electronics company located in China. Study findings identified an inflection point, confirming our hypothesis that the size of the knowledge worker's egocentric network has an inverted U-shaped effect on job performance. We further demonstrate that network dispersion richness (the number of cohorts that the focal employee has connections to) rather than network dispersion evenness (equal distribution of ties across the cohorts) has more influence on the knowledge worker's job performance. Additionally, we found that the curvilinear effect of network size is fully mediated by network dispersion richness. Implications for future research on social networks in China and Western contexts are discussed.