Bounded Rationality,Group Formation and the Emergence of Trust: An Agent-Based Economic Model

Computational Economics - It is possible to model trust as an investment game, where a player in order to receive a reward or a better outcome, accepts a certain risk of defection by another...     

Out‐of‐Plane Strain Induced in a Moiré Superstructure of Monolayer MoS2 and MoSe2 on Au(111)

Making contact of transition metal dichalcogenides (TMDCs) with a metal surface is essential for fabricating and designing electronic devices and catalytic systems. It also generates strain in the TMDCs that plays significant role in both electronic and phonon structures. Therefore, detailed understanding of mechanism of the strain generation is important to fully comprehend the modulation effect for the electronic and phonon properties. Here, MoS₂ and MoSe₂ monolayers are grown on Au surface by chemical vapor deposition and it is demonstrated that the contact with a crystalline Au(111) surface gives rise to only out‐of‐plane strain in both MoS₂ and MoSe₂ layers, whereas no strain generation is observed on polycrystalline Au or SiO₂/Si surfaces. Scanning tunneling microscopy analysis provides information regarding consequent specific adsorption sites between lower S (Se) atoms in the S? Mo? S (Se? Mo? Se) structure and Au atoms via unique moiré superstructure formation for MoS₂ and MoSe₂ layers on Au(111). This observation indicates that the specific adsorption sites give rise to out‐of‐plane strain in the TMDC layers. Furthermore, it also leads to effective modulation of the electronic structure of the MoS₂ or MoSe₂ layer.     

Revolving Vernier Mechanism Controls Size of Linear Homomultimer

A new kind of the Vernier mechanism that is able to control the size of linear assembly of DNA origami nanostructures is proposed. The mechanism is realized by mechanical design of DNA origami, which consists of a hollow cylinder and a rotatable shaft in it connected through the same scaffold. This nanostructure stacks with each other by the shape complementarity at its top and bottom surfaces of the cylinder, while the number of stacking is limited by twisting angle of the shaft. Experiments have shown that the size distribution of multimeric assembly of the origami depends on the twisting angle of the shaft; the average lengths of the multimer are decamer, hexamer, and tetramer for 0°, 10°, and 20° twist, respectively. In summary, it is possible to affect the number of polymerization by adjusting the precise shape and movability of a molecular structure.     

Broadband Tuning of a Continuous-Wave, Doubly Resonant, Lithium Triborate Optical Parametric Oscillator from 791 to 1620 nm

We report the use of extreme broadband, high reflectivity >99.5%, optical parametric oscillator (OPO) cavity mirrors. A continuous-wave, doubly resonant, OPO demonstrated tuning over a range of 791-1620 nm with a single mirror set. Wavelength tuning was performed by temperature tuning the nonlinear material of lithium triborate. Narrow linewidth oscillation was confirmed throughout the tuning range, and threshold pump power increased gradually from 50 mW near the degeneracy to 800 mW at the tuning band edge in a double-pass pumping configuration.     

语料资源缺乏的连续语音识别方法的研究

由于少数民族语言有其本身的特点, 不能简单地套用现有的连续语音识别的方法. 本文以蒙古语为例, 研讨了声学和语言模型的建立, 并在日本国际电气通信基础技术研究所的连续语音识别器上实现了蒙古语的语音识别系统. 本文侧重于语言模型的建立, 基于蒙古语黏着性语言特点, 提出用相似词聚类方法建立多类N-gram模型. 实验结果显示, 应用我们提出的语言模型, 识别精度比用传统的词的N-gram识别法提高了5.5%.     

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.     

Incremental learning of gestures for human–robot interaction

For a robot to cohabit with people, it should be able to learn people’s nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human–robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: “Keep on going left slowly” has three meanings such as, “Keep on (1)”, “going left (2)”, “slowly (3)”. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN.     

Design and analysis of a pneumatic high-impact force drive mechanism for in-pipe inspection robots

A pneumatic actuator is suitable and safe for in-pipe inspection robots in inflammable circumstances because of its ability to withstand explosions. However, ordinary pneumatic actuators limit driving speed because of their slow response. In this paper, we propose a novel pneumatic drive mechanism that can produce a high-impact force to move the in-pipe robot forward with sufficient speed by a catastrophic phenomenon using rapid release between a magnet and springs. We also introduce an anisotropic friction mechanism that uses a self-locking phenomenon to transmit the impact force to the pipe walls efficiently. A pin retraction mechanism that releases the self-locking condition is applied to retrieve the robot from the pipes. Optimizations of the proposed design were conducted based on a motion simulation model and verified in experiments. The experimental results obtained for maximum driving speeds in a straight pipe with different material types were approximately 90 and 50 mm/s for horizontal and vertical pipes, respectively. Stable strokes were also observed at different driving frequencies from 0.5 to 2.0 Hz.     

A study on a quantum-inspired evolutionary algorithm based on pair swap

A quantum-inspired evolutionary algorithm (QEA) is proposed as a stochastic algorithm to perform combinatorial optimization problems. The QEA is evolutionary computation that uses quantum bits and superposition states in quantum computation. Although the QEA is a coarse-grained parallel algorithm, it involves many parameters that must be adjusted manually. This paper proposes a new method, named pair swap, which exchanges each best solution information between two individuals instead of migration in the QEA. Experimental results show that our proposed method is a simpler algorithm and can find a high quality solution in the 0-1 knapsack problem. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007