title: Comparison of simulation and experimental results of a tractor seat with nonlinear stiffness and dead-band damping

authors: Duke, Mike

abstract: A low friction tractor seat with nonlinear stiffness and dead-band damping was investigated both by simulation and experimentation. The objective was to determine if a practical, soft suspension system could be developed that offered improved vibration performance compared to a typical mechanical commercial tractor seat suspension. A hard damper was used to prevent end stop impacts that were more likely with the soft suspension. In addition the damper had a dead-band centered at the seat's static equilibrium position. The dead-band damping was achieved with a switchable damper using relative seat displacement as the control signal. The objective of the dead-band was to allow a soft undamped operating region that gave good vibration attenuation. If the relative seat displacement passed the dead-band limits due to sudden harsh inputs, the hard damping would take over and prevent end stop impacts. An experimental rig with nonlinear seat and switchable damping was built and tested with the same parameters and inputs as those used in the simulations. The simulation and experimental results compared well. Both the simulation and experimental results showed that a combination of nonlinear stiffness and dead-band damping used on a tractor seat gives reduced rms acceleration compared to a linear, conventionally damped seat.

text: Comparison of simulation and experimental results of a tractor seat with nonlinear stiffness and dead-band damping A low friction tractor seat with nonlinear stiffness and dead-band damping was investigated both by simulation and experimentation. The objective was to determine if a practical, soft suspension system could be developed that offered improved vibration performance compared to a typical mechanical commercial tractor seat suspension. A hard damper was used to prevent end stop impacts that were more likely with the soft suspension. In addition the damper had a dead-band centered at the seat's static equilibrium position. The dead-band damping was achieved with a switchable damper using relative seat displacement as the control signal. The objective of the dead-band was to allow a soft undamped operating region that gave good vibration attenuation. If the relative seat displacement passed the dead-band limits due to sudden harsh inputs, the hard damping would take over and prevent end stop impacts. An experimental rig with nonlinear seat and switchable damping was built and tested with the same parameters and inputs as those used in the simulations. The simulation and experimental results compared well. Both the simulation and experimental results showed that a combination of nonlinear stiffness and dead-band damping used on a tractor seat gives reduced rms acceleration compared to a linear, conventionally damped seat.

year: 2012

title: Aging and rejuvenating strategies for fading windows in multi-label classification on data streams

authors: Roseberry, Martha

subjects: computer science

abstract: Combining the challenges of streaming data and multi-label learning, the task of mining a drifting, multi-label data stream requires methods that can accurately predict label sets, adapt to various types of concept drift, and run fast enough to process each data point before the next arrives. To achieve greater accuracy, many multi-label algorithms use computationally expensive techniques, such as multiple adaptive windows, with little concern for runtime and memory complexity. We present Aging and Rejuvenating kNN (ARkNN), which uses simple resources and efficient strategies to weight instances based on age, predictive performance, and similarity to the incoming data. We break down ARkNN into its component strategies to show the impact of each and experimentally compare ARkNN to seven state-of-the-art methods for learning from multi-label data streams. We demonstrate that it is possible to achieve competitive performance in multi-label classification on streams without sacrificing runtime and memory use, and without using complex and computationally expensive dual memory strategies.

text: Aging and rejuvenating strategies for fading windows in multi-label classification on data streams Combining the challenges of streaming data and multi-label learning, the task of mining a drifting, multi-label data stream requires methods that can accurately predict label sets, adapt to various types of concept drift, and run fast enough to process each data point before the next arrives. To achieve greater accuracy, many multi-label algorithms use computationally expensive techniques, such as multiple adaptive windows, with little concern for runtime and memory complexity. We present Aging and Rejuvenating kNN (ARkNN), which uses simple resources and efficient strategies to weight instances based on age, predictive performance, and similarity to the incoming data. We break down ARkNN into its component strategies to show the impact of each and experimentally compare ARkNN to seven state-of-the-art methods for learning from multi-label data streams. We demonstrate that it is possible to achieve competitive performance in multi-label classification on streams without sacrificing runtime and memory use, and without using complex and computationally expensive dual memory strategies.

year: 2023-03-27

title: Piahana Hou: a Ngati Rahiri rangatira

authors: Hart, Philip

abstract: Piahana Hou, as the half-brother of Karauna Hou, had an illustrious ancestry, but to Pakeha he was known as, briefly, the skipper of a river steamer and, for most of his life, as a labourer. His interests in several blocks of land enabled him to obtain money through selling some of his holdings, but he never became prosperous. He had minimal involvement in mining at Te Aroha.
Piahana came to prominence not as a rangatira but as a drunk, who was even involved in a bar fight at Te Aroha. Despite this weakness, his high status meant that hundreds attended his splendid tangi. Unlike some other rangatira, he did not use his status to play an important role in either Maori or Pakeha society.

text: Piahana Hou: a Ngati Rahiri rangatira Piahana Hou, as the half-brother of Karauna Hou, had an illustrious ancestry, but to Pakeha he was known as, briefly, the skipper of a river steamer and, for most of his life, as a labourer. His interests in several blocks of land enabled him to obtain money through selling some of his holdings, but he never became prosperous. He had minimal involvement in mining at Te Aroha.
Piahana came to prominence not as a rangatira but as a drunk, who was even involved in a bar fight at Te Aroha. Despite this weakness, his high status meant that hundreds attended his splendid tangi. Unlike some other rangatira, he did not use his status to play an important role in either Maori or Pakeha society.

year: 2016