A biped static balance control and torque pattern learning under unknown periodic external forces

This paper addresses a biped balancing task in which an unknown external force is exerted, using the so-called ‘ankle strategy’ model. When an external force is periodic, a human adaptively maintains the balance, next learns how much force should be produced at the ankle joint from its repeatability, and finally memorized it as a motion pattern. To acquire motion patterns with balancing, we propose a control and learning method: as the control method, we adopt ground reaction force feedback to cope with an uncertain external force, while, as the learning method, we introduce a motion pattern generator that memorizes the torque pattern of the ankle joint by use of Fourier series expansion. In this learning process, the period estimation of the external force is crucial; this estimation is achieved based on local autocorrelation of joint trajectories. Computer simulations and robot experiments show effective control and learning results with respect to unknown periodic external forces.     

The effect of lutein supplementation on visual fatigue: A psychophysiological analysis

We used psychophysiological technology to examine the effect of an oral supplement, a combination of lutein, zeaxanthin and blackcurrant extract (LUT), on visual fatigue, within the context of a randomized, double-blind, placebo-controlled cross-over trial. The LUT supplement and placebo samples were randomly assigned to thirteen participants, who took the samples for two LUT (and vice versa) for another 2 week. Each participant completed visual proof reading tasks for 2 h during each of four testing sessions. Saccade tests were administered before and after the proof reading task, during which the participants moved their eyes back and forth between two targets positioned in the center of two checkerboards. We recorded EEG, EOG, heart rate, and facial muscle potential/performance during the saccade tests. Blood pressure was measured and subjective fatigue and stress scores were collected before and after the proof reading task. We averaged EEG starting at saccade offset in order to analyze eye fixation related potentials (EFRP). Our results suggested that the proof reading task induced visual fatigue. An analysis of EFRP and other psychophysiological data revealed significant differences between the LUT and placebo conditions. These results suggest that supplementation with LUT could help to reduce symptoms of visual fatigue.     

Damage to seagrass and seaweed beds in Matsushima Bay,Japan, caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011

Damage to seagrass and seaweed beds caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011 was investigated in Matsushima Bay, Miyagi Prefecture, Japan, by comparing satellite images taken before the tsunami in November 2009 and after the tsunami in May 2011. The results showed that the tsunami destroyed 220 ha of seagrass and seaweed beds, from 320 ha in 2009 to 100 ha just after the tsunami. Zostera marina beds on the sandy and muddy bottom were rather severely damaged compared with brown seaweed beds of Sargassum horneri on the rocky substrate. Substrates of the beds and directions of the tsunami seem to be responsible for the magnitude of the damage to the beds. Maps of the spatial distributions of the beds before and after the tsunami can provide information for the restoration of seagrass and seaweed beds as natural infrastructures of coastal fisheries resources.     

Probabilistic nearest neighbor query processing on distributed uncertain data

A nearest neighbor (NN) query, which returns the most similar object to a user-specified query object, plays an important role in a wide range of applications and hence has received considerable attention. In many such applications, e.g., sensor data collection and location-based services, objects are inherently uncertain. Furthermore, due to the ever increasing generation of massive datasets, the importance of distributed databases, which deal with such data objects, has been growing. One emerging challenge is to efficiently process probabilistic NN queries over distributed uncertain databases. The straightforward approach, that each local site forwards its own database to the central server, is communication-expensive, so we have to minimize communication cost for the NN object retrieval. In this paper, we focus on two important queries, namely top-k probable NN queries and probabilistic star queries, and propose efficient algorithms to process them over distributed uncertain databases. Extensive experiments on both real and synthetic data have demonstrated that our algorithms significantly reduce communication cost.     

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.     

Performance of SOR methods on modern vector and scalar processors

The building-cube method (BCM) is a new generation algorithm for CFD simulations. The basic idea of BCM is to simplify the algorithm in all stages of flow computation to achieve large-scale simulations. Calculation of a pressure field using the Successive Over Relaxation (SOR) method consumes most of the total execution time required for BCM. In this paper, effective implementations on modern vector and scalar processors are investigated. NEC SX-9 and Intel Nehalem-EX are the latest vector and scalar processors. Those processors have much higher peak performances than their previous-generation processors. However, their memory bandwidth improvement cannot catch up with the performance improvement of processors. This is the so-called memory wall problem. In our paper, we discuss optimization techniques for implementation of the SOR method based on architectural characteristics of these modern processors, and evaluate their effects on the sustained performances of these processors for BCM.     

Multiobjective evolutionary computation for supersonic wing-shapeoptimization

This paper discusses the design optimization of a wing for supersonic transport (SST) using a multiple-objective genetic algorithm (MOGA). Three objective functions are used to minimize the drag for supersonic cruise, the drag for transonic cruise, and the bending moment at the wing root for supersonic cruise. The wing shape is defined by 66 design variables. A Euler flow code is used to evaluate supersonic performance, and a potential flow code is used to evaluate transonic performance. To reduce the total computational time, flow calculations are parallelized on an NEC SX-4 computer using 32 processing elements. The detailed analysis of the resulting Pareto front suggests a renewed interest in the arrow wing planform for the supersonic wing     

A knowledge assimilation method for logic databases

In this paper we consider a deductive question-answering system for relational databases as a logic database system, and propose a knowledge assimilation method suitable for such a system. The concept of knowledge assimilation for deductive logic is constructed in an implementable form based on the notion of amalgamating object language and metalanguage. This concept calls for checks to be conducted on four subconcepts, provability, contradiction, redundancy, independency, and their corresponding internal database updates. We have implemented this logic database knowledge assimilation program in PROLOG, a logic programming language, and have found PROLOG suitable for knowledge assimilation implementation.