• Title/Summary/Keyword: Nevada

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Supporting Those Who Provide Support: Work-Related Resources and Secondary Traumatic Stress Among Victim Advocates

  • Benuto, Lorraine T.;Singer, Jonathan;Gonzalez, Francis;Newlands, Rory;Hooft, Sierra
    • Safety and Health at Work
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    • v.10 no.3
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    • pp.336-340
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    • 2019
  • Background/Aims: Victim advocates are at risk of developing secondary traumatic stress (STS), which can result from witnessing or listening to accounts of traumatic events. This study investigated the relationship between victim status, years of experience, hours of direct contact with victims, and availability of workplace supports in the development of STS. Results: Of the 142 victim advocates, 134 were women. Regression analyses revealed that the only significant predictor of STS was the number of direct hours of victim services provided. Conclusion: The findings from this study found that women have high rates of STS and that more workplace support needs to be implemented.

Investigating the Maintenance Cost of Rest Areas: A Case Study of Nevada

  • Shrestha, Kishor;Shrestha, Pramen P.
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.624-631
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    • 2022
  • Highway Rest Areas are envisioned to provide an accessible space for rest and parking for travelers, especially those driving a long distance. In addition, modern highway Rest Areas provide many amenities to highway users, including wifi service, picnic tables, litter barrels, running water, public telephones, and sometimes even free coffee. Various studies were conducted in the domain of Rest Area facility design and their operating costs in different states; however, limited studies were conducted on the maintenance costs of these facilities. Therefore, this study's main objective is to compute the annual maintenance cost of Rest Areas in the state of Nevada. This study also analyzes the main cost categories of the maintenance works. The raw cost data of Nevada Rest Area maintenance from 1990 to 2012 were collected from the Nevada Department of Transportation (NDOT). Results show that the maintenance cost fluctuated over the study period; the maintenance cost decreased from 1991 to 2004 and then increased until 2012. The primary cost categories of maintenance work are labor, equipment, and material costs. Among these, labor cost was the largest category with 56 percent of the total maintenance cost, followed by equipment cost and material cost. The findings of this study may help NDOT and other transportation agencies plan their budget for future Rest Area maintenance activities.

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Ionic polymer-metal composite as energy harvesters

  • Tiwari, Rashi;Kim, Kwang J.;Kim, Sang-Mun
    • Smart Structures and Systems
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    • v.4 no.5
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    • pp.549-563
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    • 2008
  • The ability of an electroactive polymer, IPMC (Ionic Polymer Metal Composites,) to produce electric charge under mechanical deformations may be exploited for the development of next generation of energy harvesters. Two different electrode types (gold and platinum) were employed for the experiments. The sample was tested under dynamic conditions, produced through programmed shaking. In order to evaluate the potential of IPMC for dry condition, these samples were treated with ionic liquid. Three modes of mechanical deformations (bending, tension and shear) were analyzed. Experimental results clearly indicate that IPMCs are attractive applicants for energy harvesting, with inherent advantages like flexibility, low cost, negligible maintenance and virtually infinite longevity. Besides, preliminary energy harvesting model of IPMC has been formulated based upon the work of previous investigators (Newbury 2002, Newbury and Leo 2002, Lee, et al. 2005, Konyo, et al. 2004) and the simulation results reciprocate experimental results within acceptable error.

Generating a Simplistic 3D Model for Mobile Platform Applications

  • Ahmed, Naveed;Park, Jee Woong;Morris, Brendan
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1093-1099
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    • 2022
  • The number of buildings is increasing day by day. The next logical footstep is tackling challenges regarding scarcity of resources and sustainability, as well as shifting focus on existing building structures to renovate and retrofit. Many existing old and heritage buildings lack documentation, such as building models, despite their necessity. Technological advances allow us to use virtual reality, augmented reality, and mixed reality on mobile platforms in various aspects of the construction industry. For these purposes, having a BIM model or high detail 3D model is not always necessary, as a simpler model can serve the purpose within many mobile platforms. This paper streamlines a framework for generating a lightweight 3D model for mobile platforms. In doing so, we use an existing structure's site survey data for the foundation data, followed by mobile VR implementation. This research conducted a pilot study on an existing building. The study provides a process of swiftly generating a lightweight 3D model of a building with relative accuracy and cost savings.

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Neural Network Active Control of Structures with Earthquake Excitation

  • Cho Hyun Cheol;Fadali M. Sami;Saiidi M. Saiid;Lee Kwon Soon
    • International Journal of Control, Automation, and Systems
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    • v.3 no.2
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    • pp.202-210
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    • 2005
  • This paper presents a new neural network control for nonlinear bridge systems with earthquake excitation. We design multi-layer neural network controllers with a single hidden layer. The selection of an optimal number of neurons in the hidden layer is an important design step for control performance. To select an optimal number of hidden neurons, we progressively add one hidden neuron and observe the change in a performance measure given by the weighted sum of the system error and the control force. The number of hidden neurons which minimizes the performance measure is selected for implementation. A neural network was trained for mitigating vibrations of bridge systems caused by El Centro earthquake. We applied the proposed control approach to a single-degree-of-freedom (SDOF) and a two-degree-of-freedom (TDOF) bridge system. We assessed the robustness of the control system using randomly generated earthquake excitations which were not used in training the neural network. Our results show that the neural network controller drastically mitigates the effect of the disturbance.