2,679 research outputs found
Numerical computation for parallel plate thermoacoustic heat exchangers in standing wave oscillatory flow
No full textA simplified computational method for studying the heat transfer characteristics of parallel plate thermoacoustic heat exchangers is presented. The model integrates the thermoacoustic equations of the standard linear theory into an energy balance-based numerical calculus scheme. Details of the time-averaged temperature and heat flux density distributions within a representative domain of the heat exchangers
and adjoining stack are given. The effect of operation conditions and geometrical parameters on the heat exchanger performance is investigated and main conclusions relevant for HX design are drawn as far as fin length, fin spacing, blockage ratio, gas and secondary fluid-side heat transfer coefficients are concerned. Most relevant is that
the fin length and spacing affect in conjunction the heat exchanger behaviour and have to be simultaneously optimized to minimize thermal losses localized at the HX-stack
junctions. Model predictions fit experimental data found in literature within 36% and 49% respectively at moderate and high acoustic Reynolds numbers
A Scenario-Based Review of IPv6 Transition Tools
No full textMomentum for IPv6 transition is on the rise, and many transition tools and techniques are available to ISPs, enterprise networks, and unmanaged networks. From a transitioning perspective, the ISP environment is interesting because the operators migration approaches will define, quite strictly, the extent of IPv6 services that their customers receive. As such, the ISPs (scalable) migration decisions have direct knock-on effects for customers. In the future, customers might require ISPs to offer value-added lPv6 services that not only have performance-based restrictions, but security and mobility considerations, as well
A community-dwelling sample of people with Parkinson's disease: characteristics of fallers and non-fallers
No full textBackground: people with Parkinson's disease often fall. Objectives: to report the frequency of falls and characteristics of fallers and non-fallers in a community-based sample of people with Parkinson's disease. Method: we administered a battery of standardized tests in the home and the laboratory. Results: we recruited 63 people with Parkinson's disease through general practices. Forty (64%, 95% confidence interval 51–74%) had fallen in the previous 12 months. Many factors associated with falling in the general population were associated with Parkinson's disease fallers (e.g. use of multiple medication and greater physical disability). Fallers were more likely to be depressed and anxious than non-fallers. Condition-specific factors associated with falling included greater disease severity (although there were exceptions) and more marked response to levodopa treatment, including more dyskinesia and on–off phenomena. Fallers took more steps to complete a test of mobility. They also had a shorter functional reach and greater postural sway whilst completing a dual task than non-fallers. Conclusion: this community-based study confirms the high risk of falling in Parkinson's disease. Our results suggest that disease-specific factors contribute to the increased risk and that there is scope for specific therapeutic interventions
Predicting fallers in a community-based sample of people with Parkinson's disease
No full textBACKGROUND: The risk of people with Parkinson's disease (PD) falling is greater than that of the general population but to date, disease-specific predictors of falling have not been identified. OBJECTIVES: To identify one or more features, which would predict individuals at risk of falling during a 3-month prospective follow-up study. METHOD: A battery of standardised tests administered in the home and the laboratory with a 3-month follow-up telephone interview. RESULTS: Sixty-three people with PD were recruited from GP practices. Eleven interview variables and six gait laboratory variables were used with subsamples (55 and 44 subjects, respectively) to fit predictive models for identifying future fallers. The number of falls in the previous year was the most important variable, without exception, to be selected as a predictor in various logistic regression models. A history of two or more falls had a sensitivity of 86.4% (95% CI 67.3-96.2%) and a specificity of 85.7% (95% CI 71.2-94.2%) in predicting falling in the next 3 months. CONCLUSION: Healthcare workers should be asking their patients with PD regularly and carefully about falling, and should consider instigating programmes of fall management for patients with PD who have fallen two or more times in the previous 12 months
A portable stack-yard fence
No full textTitle from PDF caption (viewed on November 30, 2017).This archived document is maintained by the State Library of Oregon as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
STACK v3.0
No full textSTACK provides a question type for the Moodle quiz which is specifically designed to enable sophisticated computer-aided assessment in Mathematics and related disciplines, with emphasis on formative assessment. STACK is underpinned by computer algebra
Electrochemical transport in CuCl/HCl(aq) electrolyzer cells and stack of the Cu–Cl cycle
No full textThis paper develops a comprehensive predictive model for the CuCl/HCl(aq) electrolyzer stack in the electrochemical unit of the Cu–Cl cycle of hydrogen production. A strong aqueous anolyte is fed into the stack and forms complex speciation. The unit single cell is modeled to predict the decomposition voltage by applying the Gibbs energy minimization method (GEM). The kinetic correlations are incorporated to take into account the overpotential losses during the hydrogen generation process under a non-equilibrium condition with the stack under potential. To evaluate the single-cell contribution to the average performance of stack, a hydrodynamic analysis reveals the anolyte and catholyte flow distribution using a finite element method for solutions of the equation of mass and momentum conservation equations of the flow field. Using the simulated stack, the voltage spread across the individual cells in the stack, cell and stack voltage efficiency, and the sensitivity of stack performance under the operating conditions, are investigated. It is shown that the speciation model has good agreement with data in past literature. With an increase in the stack operating temperature from 25 °C to 65 °C, the average stack efficiency improves from 68% to 72%. Cells close to the anolyte or catholyte input ports possess a higher voltage efficiency than other cells. This is mainly due to less electrolyte received by the cells placed in the middle of the stack for the X-shape bipolar modules, resulting in less decomposition potential
Mining software testing knowledge from stack overflow
No full textThis paper aims to unveil and gather testing-related information from Stack Overflow, highlighting it as a valuable resource for practitioners seeking answers and guidance. The study aims to accumulate knowledge from real-life experiences shared on Stack Overflow and bridge the knowledge gap between industry practices and teaching practices.The paper explores different types of software testing, popular frameworks, temporal trends of testing-related technologies, controversial opinions, and recommended practices/advice/suggestions from Stack Overflow posts. The methodology involves determining search terms through literature, querying the Stack Exchange API, conducting frequency analysis of words from posts, and manually inspecting threads. Our results show that the most popular frameworks discussed are Selenium, Spring, JMeter, and React. Automated testing and JavaScript frameworks have shown an upward trajectory over the years. The recommendations made by practitioners were categorized based on the broad scope of topics covered. We draw comparisons and parallels with related previous research and discuss the technical limitations faced during the study.Overall, this paper uncovers valuable insights from Stack Overflow and provides practitioners with the current view on industry practices.CSE3000 Research ProjectComputer Science and Engineerin
RoCE based 100GbE RDMA network stack on FPGA hardware
No full textBig data analytics is one of the foundations for booming technologies such as machine learning, genetics/genomics, and computer vision. These big data applications require a large amount of data transfers for distributed and parallel processing. Networking is thus a crucial facilitator and could make big impact on big data processing.In a computing system with a common network stack such as the TCP/IP protocol suite, many expensive memory operations are necessary to process networking traffic. This means a large percentage of CPU resources are occupied by networking rather than data processing. The memory copying overhead introduced by networking not only reduces the throughput but also increases the latency. In this case, networking is becoming a major bottleneck for big data applications. This problem can be solved by applying Remote Direct Memory Access (RDMA) technology to the network stack. RDMA enables a zero-copy mechanism and has CPU bypass ability. With RDMA implemented, both the throughput and latency can be improved.In this work, we developed an open source 100 Gbps RDMA network stack on Field Programmable Gate Array (FPGA) hardware. The developed stack follows the RDMA over Converged Ethernet (RoCE) architecture and targets the Alveo FPGA platform. The stack includes a User kernel that can be customized for user applications. This means that computing applications can also be offloaded to this RoCE stack. Finally, we evaluate the stack and compare it with existing TCP/IP and RDMA stacks like the EasyNet and StRoM. The results show that the developed RDMA stack achieves a throughput of 100 Gbps and an RDMA READ operation latency around 4 us and an RDMA WRITE latency around 3.5 us for 64B data. It shows a great throughput advantage over the TCP/IP stack for message sizes smaller than 1 MB. The latency is also slightly lower than the TCP/IP stack.Big data analytics is one of the foundations for booming technologies such as machine learning, genetics/genomics, and computer vision. These big data applications require a large amount of data transfers for distributed and parallel processing. Networking is thus a crucial facilitator and could make big impact on big data processing.In a computing system with a common network stack such as the TCP/IP protocol suite, many expensive memory operations are necessary to process networking traffic. This means a large percentage of CPU resources are occupied by networking rather than data processing. The memory copying overhead introduced by networking not only reduces the throughput but also increases the latency. In this case, networking is becoming a major bottleneck for big data applications. This problem can be solved by applying Remote Direct Memory Access (RDMA) technology to the network stack. RDMA enables a zero-copy mechanism and has CPU bypass ability. With RDMA implemented, both the throughput and latency can be improved.In this work, we developed an open source 100 Gbps RDMA network stack on Field Programmable Gate Array (FPGA) hardware. The developed stack follows the RDMA over Converged Ethernet (RoCE) architecture and targets the Alveo FPGA platform. The stack includes a User kernel that can be customized for user applications. This means that computing applications can also be offloaded to this RoCE stack. Finally, we evaluate the stack and compare it with existing TCP/IP and RDMA stacks like the EasyNet and StRoM. The results show that the developed RDMA stack achieves a throughput of 100 Gbps and an RDMA READ operation latency around 4 us and an RDMA WRITE latency around 3.5 us for 64B data. It shows a great throughput advantage over the TCP/IP stack for message sizes smaller than 1 MB. The latency is also slightly lower than the TCP/IP stack.Electrical Engineerin
Comparison of post-stack and pre-stack seismic inversion methods
No full textIn this paper I review some seismic inversion methods. This methods of seismic inversion can be divide in two group: post-stack inversion and pre-stack inversion. The most recent approach of seismic inversion use pre-stack data. The earliest methods of seismic inversion use post-stack data. The author present comparison of two methods: resursive inversion and simultaneous inversion.W prezentowanej pracy opisano metody inwersji sejsmicznej, realizowanej przed i po procedurze składania. Przedstawiono wyniki obliczeń inwersji po procedurze składnia z wykorzystaniem metody inwersji rekursywnej. Uzyskane wyniki zestawiono z wynikami inwersji przed składaniem – inwersji symultanicznej. Następnie przy pomocy wykresów krzyżowych wykonano analizę służącą wskazaniu potencjalnych obszarów złożowych.praca magistersk
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