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Relevant bibliographies by topics / Mattress Factory

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Academic literature on the topic 'Mattress Factory'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Mattress Factory"

1

Mohan, M., S. Kagen, and R. Muthiah. "Mattress Lung: Acrylonitrile-induced Asthma in a Mattress Factory Worker." Journal of Allergy and Clinical Immunology 117, no. 2 (February 2006): S98. http://dx.doi.org/10.1016/j.jaci.2005.12.394.

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Grenier, Lotus. "On Memory: Deborah Aschheim at the Mattress Factory." TEXTILE 5, no. 3 (December 2007): 328–31. http://dx.doi.org/10.2752/175183507x249495.

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Giannini, Claudia, and Michael Olijnyk. "Installations by Asian Artists in Residenceat the Mattress Factory: An Interview with Michael Olijnyk." Art Journal 59, no. 3 (September 2000): 86–95. http://dx.doi.org/10.1080/00043249.2000.10792017.

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Olijnyk, Michael, and Claudia Giannini. "Installations by Asian Artists in Residence at the Mattress Factory: An Interview with Michael Olijnyk." Art Journal 59, no. 3 (2000): 86. http://dx.doi.org/10.2307/778030.

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Bogomolov, Elizabeth, and Julie A. Wiebusch. "Assessing the origin of tonal sound emanating from refrigerant piping in the historic Mattress Factory project at the University of Washington Tacoma Campus." Journal of the Acoustical Society of America 125, no. 4 (April 2009): 2494. http://dx.doi.org/10.1121/1.4783330.

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Chao, Yao, Li Ming Shen, and Ming Peng Liu. "Mechanical characteristic and analytical model of novel air spring for ergonomic mattress." Mechanics & Industry 22 (2021): 37. http://dx.doi.org/10.1051/meca/2021035.

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Conventional mattresses can not adjust precisely according to the individualized spinal alignment. In addition, there is no theoretical basis for quantitative design and adjustment of mattresses firmness. The purpose of this paper is to overcome deficiency of traditional air chambers for research of ergonomic mattresses in accordance with spinal alignment. A novel variable stiffness air spring was designed and static experiments were conducted to analyze its mechanical properties and its influence factors. An analytical model based on geometric parameters and initial internal pressure was established. The results showed that the air spring has nonlinear stiffness during the working process. Furthermore, the model can predict the load of the air spring accurately at any equilibrium position with an average error of 6.96%. The initial stiffness, volume and assembly height could be predicted by means of geometric parameters and initial internal pressure. The conclusions are that the novel air spring can obtain predictable stiffness compared with cubic and the rod-shaped air chambers, which provides a theoretical basis and possible solution for the study of stiffness adaptive ergonomic mattress according to spinal alignment.

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Kumar, Sanjeev, Anil Kumar Sahu, and Sanjeev Naval. "Performance of Circular Footing on Expansive Soil Bed Reinforced with Geocells of Chevron Pattern." Civil Engineering Journal 5, no. 11 (November 3, 2019): 2333–48. http://dx.doi.org/10.28991/cej-2019-03091415.

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Results from laboratory model tests performed on circular footing are presented in this paper to understand the performance of geocell reinforced expansive soil. Naturally occurring expansive soil was used in this study as subsoil. Geocells of chevron pattern fabricated from geotextile made up of polypropylene were used to reinforce the soil bed. The parameters studied in this testing program were the placement depth of the geocell mattress, pocket size of geocell and the height of geocell mattress. Contrary to other researchers; the improvement in the performance of reinforced bed is evaluated at a settlement level equal to the failure settlement of unreinforced soil bed. The performance of reinforced bed is evaluated through two non-dimensional factors viz. bearing capacity improvement factor (If) and settlement reduction factor (PRS%). Test results indicated that with the introduction of geocell as reinforcement, a substantial improvement in bearing capacity and decrease in footing settlement can be achieved. Bearing capacity of reinforced bed increases by more than 200% and 81% reduction in footing settlement was achieved by using geocell mattress of optimal dimensions and placing it just below the footing base.

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Kotowski, Susan E., Kermit G. Davis, Neal Wiggermann, and Rachel Williamson. "Quantification of Patient Migration in Bed." Human Factors: The Journal of the Human Factors and Ergonomics Society 55, no. 1 (January 18, 2013): 36–47. http://dx.doi.org/10.1177/0018720812474300.

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Objective: The study objective was to quantify the movement of hospital bed occupants relative to the bed in typical bed articulations. Background: Movement of a patient in bed results in two common adverse events: (a) increase in shear and friction forces between the patient and bed, which are extrinsic pressure ulcer risk factors, and (b) musculoskeletal injuries to nurses, resulting from repositioning patients who have migrated down in bed. Method: The study involved 12 participants who lay supine in three hospital beds, which were articulated to common positions. Body movement relative to the bed was quantified with the use of motion capture. Cumulative movement, net displacement, and torso compression (shoulder to trochanter distance) were calculated for different bed types and bed movements. Results: Bed design and bed movement had a significant effect on most of the dependent variables. Bed design (e.g., type) influenced cumulative movement by up to 115%, net displacement by up to 70%, and torso compression by about 20%. Bed movement (e.g., knee elevation) reduced cumulative migration by up to 35%. Conclusion: The quantification of patient migration provides a metric for evaluating the interaction between body and bed surfaces. Overall, the measures were sensitive to design changes in bed frames, bed articulations, and mattress inflation. Application: Documentation of the cumulative movement, net displacement, and torso compression provides hospital bed designers quantifiable measures for reducing migration and potentially shear and friction forces when designing bed frames, bed articulations, and mattresses. Optimization of these metrics may ultimately have an impact on patient and caregiver health.

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Chen, C. M., A. Mielck, B. Fahlbusch, W. Bischof, O. Herbarth, M. Borte, H. E. Wichmann, and J. Heinrich. "Social factors, allergen, endotoxin, and dust mass in mattress." Indoor Air 17, no. 5 (October 2007): 384–93. http://dx.doi.org/10.1111/j.1600-0668.2007.00486.x.

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Chen, C. M., B. Fahlbusch, W. Bischof, O. Herbarth, M. Borte, W. H. -Erich, and J. Heinrich. "Social Factors and Indoor Biocontaminants and Dust on Mattress." Epidemiology 17, Suppl (November 2006): S384. http://dx.doi.org/10.1097/00001648-200611001-01022.

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Books on the topic "Mattress Factory"

1

Claudia, Giannini, and Mattress Factory, eds. Installations, Mattress Factory, 1990-1999. Pittsburgh, Pa: Mattress Factory, 2001.

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2

Factory, Mattress, ed. Mattress Factory--installation and performance, 1982-1989. Pittsburgh, Pa: The Factory, 1991.

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Book chapters on the topic "Mattress Factory"

1

Nozaki, Manami, Kageyu Noro, and Takayuki Sasaki. "Relevant Analysis on Rollover and Physical Properties of Mattresses." In Advances in Human Factors and Ergonomics Series, 453–60. CRC Press, 2010. http://dx.doi.org/10.1201/ebk1439834978-c52.

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"Relevant Analysis on Rollover and Physical Properties of Mattresses." In Advances in Human Factors and Ergonomics in Healthcare, 469–76. CRC Press, 2010. http://dx.doi.org/10.1201/ebk1439834978-54.

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Jackson, Chandra L. "Housing Conditions as Environmental and Social Determinants of Sleep Health." In The Social Epidemiology of Sleep, 373–408. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190930448.003.0014.

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The home environment is an important yet understudied determinant of sleep health. Although little is known about the living conditions that negatively affect sleep, many naturally occurring and artificial external factors in a person’s immediate physical and social sleeping environment can impact his or her sleep health and subsequent acute as well as chronic risk of disease and premature mortality. Using the socioecological model as a framework, this chapter discusses the indoor and immediate outdoor physical surroundings of spaces used for shelter including exposure to light and noise pollution, suboptimal room temperature/humidity, poor air quality, improper ventilation, and subpar mattress quality. Household crowding, safety, and housing insecurity are among social conditions of the living quarters that are also discussed as the aforementioned exposures may negatively impact sleep health across the life course. Published observational as well as experimental research findings investigating the impact of these factors on various sleep dimensions along with their potential impact on disease and mortality risk are also discussed before identifying important gaps in the current literature and providing future research directions.

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Conference papers on the topic "Mattress Factory"

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Yamaguchi, Takahiro, Hajime Kimura, Atsushi Sakuma, Kazushige Takahashi, and Shigetoshi Mimura. "Material and Posture Modeling for Sleeping on Soft Low-Density Porous Material." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87249.

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Sleeping is one of the most important factors that influence the quality of human life, and this state of existence should be thoroughly investigated to improve the quality of the life. The mechanical design of bedding has great influence on the comfort of a mattress. Thus, objective and conventional techniques to evaluate the mechanics of mattress comfort could help improve the quality of sleep. In this report, an analysis technique for the assessment of the sleeping posture of humans is presented to facilitate the development of mattress design technology. Herein, an analytical model which imitates the human body has been formulated to determine the design parameters of a mass-spring-joint system on a soft underlay. The physical model is composed of five components that represent the head, chest, hip, femur, and calf, with each body part being represented by a simple ball model. The spring joint connecting the five parts reflects the neck, lumbar, hip, and knee joints. The specifications of the body model are determined by actual measurements and previous studies. In order to determine the physical properties of the mattress, two types of mattress urethane foam material are tested using the ball indenter method. The parameters include Young’s modulus, plateau stress, and other physical parameters. Variation due to the type of mattress has been observed in the laying test using a pressure distribution sensor sheet. In the analysis performed using the physical model, the variation in the lying posture and the extent of body sinking are observed to be the same during experiments. Both variations are compared using the change in force distribution in each body part. In conclusion, it was found that the observed changes in distribution are the same in the experimental and physical models. Therefore, the proposed model reliably reflects the design characteristics of the mattress.

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Abramova, Svetlana, Artemij Voskobojnikov, Konstantin Beznosov, and Rainer Böhme. "Bits Under the Mattress: Understanding Different Risk Perceptions and Security Behaviors of Crypto-Asset Users." In CHI '21: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3411764.3445679.

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Shim, Jae Kyung, Chang Sup Shim, and Jin Wook Kwon. "Kinematic Synthesis of a Medical Bed for Decubitus Ulcer Patients." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-43109.

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A decubitus ulcer or bedsore is a pressure-induced ulceration of the skin occurring in persons confined to bed for long periods of time. Reduction of pressure over bony prominences is of primary importance to prevent and cure bedsores. For this purpose, specially designed mattresses can be used and/or the patient should be turned frequently to avoid ischemia of soft tissue. In addition to pressure, other principal factors causing bedsore are friction and shear forces. In this paper, we designed a new 5 degree of freedom bed mechanism that can be used to change the posture of pressure ulcer patients, which generates 7 motions including backrest elevation, kneerest elevation, lounge position, left and right rotation, trendelenberg and reverse trendelenberg motion, and straight elevation. Particularly, we focused on the synthesis of a backrest and seatrest assembly that can reduce sliding between the bed and the patient.

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Wang, James, and Paul Jukes. "An Integrated Design Approach to the Use of Sleepers as Vertical Upsets for Thermal Buckle Management." In 2008 7th International Pipeline Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ipc2008-64563.

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Pipe-in-Pipe (PIP) arrangements for offshore pipelines have become a viable approach to handling High Pressure and High Temperature (HPHT) conditions in deepwater. However, using sleepers to control the buckle location and stresses (thermal buckle management) in this type of pipeline is facing challenges regarding free spanning and sleeper embedment. A sleeper design should ensure adequate vertical upset of the pipeline, thus helping buckling of the pipeline as part of the thermal management plan. However, this approach generates free spans in the pipeline, which could become susceptible to Vortex Induced Vibration (VIV) if these free spans prove excessive. Further, PIP pipelines are usually heavy and may raise additional challenges in very soft soils, especially given the great uncertainty in predicted penetrations provided by currently available models. This paper presents an integrated approach to designing sleepers and the approach is applicable to both PIP and single pipes. It takes into account the interaction between pipeline structural integrity and sleeper embedment, thus determining the required sleeper general sizing and the possibility of the need for mudmats or mattresses. Finite element analysis of both the pipeline and sleepers is used in the presented approach. During the FEA modeling, importance is addressed for the model length, element size, concrete induced Stress Concentration Factor (SCF) at the field joints for single pipes, etc. In addition, the analysis scenarios are addressed to ensure the results from all the necessary cases are accurately identified. The sleeper design in the integrated approach details the appropriate selection of sleeper locations to release excessive axial loads as well as to ensure buckling stability. During the selection, some factors contributing to the buckling analysis results are discussed and these factors include route bends, pipe ovality, residual stress/strain, and rogue buckles. Different sleeper sizes are assessed with respect to the pipeline structural integrity (e.g., stresses and strains due to vertical bending, lateral buckling and VIV), coupled with an assessment of lost height due to sleeper penetration in the soil. Results indicate that the sleeper size should be maintained within a certain range to ensure proper function of the sleeper inducing lateral buckling of the pipeline, while reducing the possibility of excessive VIV. In some cases, this may require the help of mudmats or mattresses to support the sleeper. Results also show that the sleeper width should be selected such that after buckling, the pipeline would not fall off either end of the sleeper. The ULS check and fatigue assessment due to VIV/direct wave loading are also discussed for wave/current data and wave load application to interacting spans. To ensure that conservative estimates of the fatigue life, sensitivity studies are performed to account for the uncertainty due to soil properties and concrete conditions (intact or damaged). The tolerance for each item varies from case to case, thereby varying the inputs. This integrated design approach combines pipeline lateral buckling and span analyses together with the analysis of sleeper penetration in the soil. The proposed integrated analysis would ensure that the designed sleeper would not cause excessive VIV/direct wave load to the pipeline and that thermal stresses and buckling of the pipeline are properly managed.

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O’Beirne, Colm, Phil Watson, Conleth O’Loughlin, David White, Alexander Hodson, Sze-Yu Ang, Sebastiaan Frankenmolen, Jesper Hoj-Hansen, Matthew Kuo, and Toby Roe. "Pipe Clamping Mattresses to Mitigate Flowline Walking; Physical Modelling Trials on Three Offshore Soils." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/31064-ms.

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Abstract Pipe clamping mattresses (PCMs) are a relatively new system for providing anchoring force to pipelines, to mitigate offshore flowline ‘walking’. They represent a cost-effective and highly efficient alternative to anchor piles, rock dump and conventional concrete mattresses. The system comprises a hinged concrete structure that clamps onto a section of laid pipeline, with concrete ballast logs securing the clamping action – with the benefit that 100% of the submerged weight of the PCM contributes to axial friction. PCMs have been applied successfully to one deepwater project, but performance data showing the influence of soil type, and allowing a general design framework to be established, has not yet been available. This paper addresses this gap by investigating the performance of PCMs through three series of centrifuge tests, supported by three Operators. Each series comprises tests on a different reconstituted deepwater soil as follows: (a) West African clay; (b) Gulf of Mexico clay; and (c) carbonate silty sand. In each test, a scaled pipeline is installed in-flight and cycled axially to represent its prior operating life. Scaled PCM models and ballast units are then installed onto the pipe in-flight, mimicking the use of PCMs to mitigate pipeline walking during operation. After installation of the PCMs, further axial cycles are applied, with the system settlement and changes in axial resistance and excess pore pressure measured. The paper shows the performance and applicability of PCMs for a range of soil types, highlighting variations in axial resistance and settlement. The suite of results will help to calibrate design tools for industry, removing unnecessary conservatism and enabling an optimised pipeline anchoring solution to be designed. Key results are equivalent friction factors for the combined pipe-PCM system and PCM settlement, which both show behaviour dependent on soil type. In the clay soils, friction increases significantly over time due to ‘consolidation hardening’. This provides validation of an important effect that has only recently been recognised in pipeline design. In contrast, hardening behavior is not evident in silty sand – although the study suggests there is potential for increasing resistance associated with settlement, which appears to mobilize additional (wedging) stress around the pipeline. Upon PCM installation, the pipelines embed further due to the added weight. Additional settlement occurs during cycling of the system, due to immediate soil deformation and consolidation-related compression. The magnitude of embedment is greater for the clay soils, but in all cases does not cause the clamping action to release. Overall, the efficiency of the PCM system in providing a high level of anchoring force per unit weight placed on the seabed is confirmed. Long term anchoring forces in the range 50-100% of the submerged weight of the PCM are demonstrated. This is several times more efficient than the commonly used alternative of a rock berm.

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Bhowmik, Subrata. "Machine Learning-Based Optimization for Subsea Pipeline Route Design." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/31031-ms.

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Abstract Optimal route selection for the subsea pipeline is a critical task for the pipeline design process, and the route selected can significantly affect the overall project cost. Therefore, it is necessary to design the routes to be economical and safe. On-bottom stability (OBS) and fixed obstacles like existing crossings and free spans are the main factors that affect the route selection. This article proposes a novel hybrid optimization method based on a typical Machine Learning algorithm for designing an optimal pipeline route. The proposed optimal route design is compared with one of the popular multi-objective optimization method named Genetic Algorithm (GA). The proposed pipeline route selection method uses a Reinforcement Learning (RL) algorithm, a particular type of machine learning method to train a pipeline system that would optimize the route selection of subsea pipelines. The route optimization tool evaluates each possible route by incorporating Onbottom stability criteria based on DNVGL-ST-109 standard and other constraints such as the minimum pipeline route length, static obstacles, pipeline crossings, and free-span section length. The cost function in the optimization method simultaneously handles the minimization of length and cost of mitigating procedures. Genetic Algorithm, a well established optimization method, has been used as a reference to compare the optimal route with the result from the proposed Reinforcement Learning based optimization method. Three different case studies are performed for finding the optimal route selection using the Reinforcement Learning (RL) approach considering the OBS criteria into its cost function and compared with the Genetic Algorithm (GA). The RL method saves upto 20% pipeline length for a complex problem with 15 crossings and 31 free spans. The RL optimization method provides the optimal routes, considering different aspects of the design and the costs associated with the various factors to stabilize a pipeline (mattress, trenching, burying, concrete coating, or even employing a more massive pipe with additional steel wall thickness). OBS criteria significantly influence the best route, indicating that the tool can reduce the pipeline's design time and minimize installation and operational costs of the pipeline. Conventionally the pipeline route optimization is performed by a manual process where the minimum roule length and static obstacles are considered to find an optimum route. The engineering is then performed to fulfill the criteria of this route, and this approach may not lead to an optimized engineering cost. The proposed Reinforced Learning method for route optimization is a mixed type, faster, and cost-efficient approach. It significantly minimizes the pipeline's installation and operational costs up to 20% of the conventional route selection process.

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