Effects of heated seat and foot heater on thermal comfort and heater energy consumption in vehicle

Subjective experiments involving 12 different conditions were conducted to investigate the effects of heated seats and foot heaters in vehicles on thermal sensation and thermal comfort. The experimental conditions involved various combinations of the operative temperature in the test room (10 or 20°C), a heated seat (on/off) and a foot heater (room operative temperature?+10 or?+20°C). The heated seat and foot heater improved the occupant's thermal sensation and comfort in cool environments. The room operative temperature at which the occupants felt a 'neutral' overall thermal sensation was decreased by about 3°C by using the heated seat or foot heater and by about 6°C when both devices were used. Moreover, the effects of these devices on vehicle heater energy consumption were investigated using simulations. As a result, it was revealed that heated seats and foot heaters can reduce the total heater energy consumption of vehicles. Statement of Relevance: Subjective experiments were conducted to investigate the effects of heated seats and foot heaters in vehicles on thermal comfort. The heated seat and foot heater improved the occupant's thermal sensation and comfort in cool environments. These devices can reduce the total heater energy consumption in vehicles.     

A Linear Algorithm for Computing the Homography from Conics in Correspondence

This paper presents a study, based on conic correspondences, on the relationship between two perspective images acquired by an uncalibrated camera. We show that for a pair of corresponding conics, the parameters representing the conics satisfy a linear constraint. To be more specific, the parameters that represent a conic in one image are transformed by a five-dimensional projective transformation to the parameters that represent the corresponding conic in another image. We also show that this transformation is expressed as the symmetric component of the tensor product of the transformation based on point/line correspondences and itself. In addition, we present a linear algorithm for uniquely determining the corresponding point-based transformation from a given conic-based transformation up to a scale factor. Accordingly, conic correspondences enable us to easily handle both points and lines in uncalibrated images of a planar object.     

Detection of environmental changes from network structure

We studied the networks of the temperature record in the atmosphere. They are made by the strength of the synchronization, including the delay between temperatures at locations on Earth. We consider these locations as nodes, and we consider a pair of locations as a link if the synchronization between them is stronger than a threshold. The network is scale-free, which is thought to contribute to the stability of the climate. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

A new learning method using prior information of neural networks

In this paper, we present a new learning method using prior information for three-layer neural networks. Usually when neural networks are used for identification of systems, all of their weights are trained independently, without considering interrelated weights values. Thus, the training results are usually not good. The reason for this in that each parameter has its influence on others during learning. To overcome this problem, we first give an exact mathematical equation that describes the relation between weight values given a set of data conveying prior information. The we present a new learning method that trains part of the weights and calculates the others using these exact mathematical equations. This method often a priori keeps the given mathematical structure exactly the same during learning; in other words, training is done so that the network follows a predetermined trajectory. Numerical computer simulation results are provided to support this approach. This work was presented, in part, at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999.     

Design of recursive digital filters for the selection or rejection of a particular velocity in seismic signals

In this paper a new type of velocity-selecting/rejecting filter which passes or stops a particular event in a seismic signal is proposed. The velocity-selecting filter is based on a time-space band-pass filter with sharp passband for a particular direction, and similarly, the velocity-rejecting filter is based on a time-space band-stop filter. A technique for designing such filters, in terms of an infinite-impulse-response (IIR) filter, is presented, in which a rotated version of separable filter is used. Finally, numerical examples are included to illustrate the design theory.     

MOSAIC for multiple-reward environments

Reinforcement learning (RL) can provide a basic framework for autonomous robots to learn to control and maximize future cumulative rewards in complex environments. To achieve high performance, RL controllers must consider the complex external dynamics for movements and task (reward function) and optimize control commands. For example, a robot playing tennis and squash needs to cope with the different dynamics of a tennis or squash racket and such dynamic environmental factors as the wind. In addition, this robot has to tailor its tactics simultaneously under the rules of either game. This double complexity of the external dynamics and reward function sometimes becomes more complex when both the multiple dynamics and multiple reward functions switch implicitly, as in the situation of a real (multi-agent) game of tennis where one player cannot observe the intention of her opponents or her partner. The robot must consider its opponent's and its partner's unobservable behavioral goals (reward function). In this article, we address how an RL agent should be designed to handle such double complexity of dynamics and reward. We have previously proposed modular selection and identification for control (MOSAIC) to cope with nonstationary dynamics where appropriate controllers are selected and learned among many candidates based on the error of its paired dynamics predictor: the forward model. Here we extend this framework for RL and propose MOSAIC-MR architecture. It resembles MOSAIC in spirit and selects and learns an appropriate RL controller based on the RL controller's TD error using the errors of the dynamics (the forward model) and the reward predictors. Furthermore, unlike other MOSAIC variants for RL, RL controllers are not a priori paired with the fixed predictors of dynamics and rewards. The simulation results demonstrate that MOSAIC-MR outperforms other counterparts because of this flexible association ability among RL controllers, forward models, and reward predictors.     

一种用于推挽式电压型逆变器的低损耗无源吸收电路

提出并实现了一种推挽式PWM电压型逆变器用无源吸收电路;设有独立的放电回路让缓冲电容器上的能量部分地回馈到直流电源中,高频放电能量不会叠加在输出电压上;缓冲电容器的电压被钳位,使得推挽电路特有的倍压不会在吸收电路上造成额外的损耗。给出吸收电路参数的设计准则和计算实例,在200VDC和30kW级的中压中功率逆变装置中发挥了推挽拓扑的优点。理论分析和实验验证了所提方法的有效性。     

金属注射成形冷作工具钢的超声疲劳性能

用超声疲劳试验研究了金属注射成形(MIM)冷作工具钢和锻轧钢(JIS SKD11)的高周疲劳性能。锻轧钢试样于423K回火1h。另一方面，为了评估回火温度对疲劳性能的影响，将MIM钢试样于不同温度下进行了回火。在N=103～108疲劳寿命范围内进行了超声疲劳试验。MIM钢试样的疲劳强度和锻轧钢试样相同。MIM钢试样的疲劳强度随着回火温度升高而减低。显微组织的观察结果表明，MIM钢试样的碳化物的直径与形状比锻轧钢试样的均一。     

How international is Computers and Composition?

In this article, I examine to what extent Computers and Composition: An International Journal for Teachers of Writing is international. My analysis of several aspects of the journal indicates limited international scope. I also discuss two issues important when considering the potential international scope of computers and writing research and practices: the differing uses of computers for writing by different language users and the differing concepts of identity and self in different cultures in relation to writing. I conclude with concrete suggestions for broadening our perspectives on computers and writing and making this journal truly international.