Return Link Systems for Wireless Mobile Camera Using 42 GHz-Band with Frequency and Space Diversity Techniques

In this paper, return link systems for wireless mobile camera using 42 GHz-band in multipath fading environments are proposed. The return link systems for wireless mobile camera require wireless transmission with high reliability as same as the conventional wired camera systems. The proposed return link systems achieve transmission with high reliability by taking into consideration frequency and space diversity techniques. The proposed systems can be classified as 3 three types of return link systems according to diversity techniques： FD （frequency diversity） systems, SD （space diversity） systems and FD＋SD system （frequency and space diversity）. Computer simulations are carried out in order to confirm the effectiveness of the proposed return link systems. It is confirmed that the proposed three types of return link systems have an advantage about BER performances and effectively exploit frequency and space resources.     

Fabrication of X-rays mask with carbon membrane for diffraction gratings

We have produced diffraction gratings for obtaining high resolution X-ray phase imaging, such as X-ray Talbot interferometer. These diffraction gratings were required to have a fine, high accuracy, high aspect ratio structure. Therefore, we decided to use the X-rays lithography technique that used synchrotron radiation of the directivity for a manufacture process. The accuracy of the completed structure depends largely on the accuracy of the X-ray mask. In our group, a resin material is conventionally used for the membrane of large X-ray masks. However, X-ray masks comprising a resin membrane have the disadvantage that, after several cycles of X-ray exposure, they crease and sag due to X-ray-derived heat. As a substitute for the conventional resin membrane, we experimentally fabricated a new X-ray mask using a carbon wafer membrane. The newly fabricated X-ray mask was subjected to X-ray exposure experiment. We succeeded in making the structure body which was almost shape. And the experimental results verified that the new mask did not deteriorate even when used repeatedly, demonstrating that it was highly durable.     

Fast computation of computer-generated hologram using Xeon Phi coprocessor

We report fast computation of computer-generated holograms (CGHs) using Xeon Phi coprocessors, which have massively x86-based processors on one chip, recently released by Intel. CGHs can generate arbitrary light wavefronts, and therefore, are promising technology for many applications: for example, three-dimensional displays, diffractive optical elements, and the generation of arbitrary beams. CGHs incur enormous computational cost. In this paper, we describe the implementations of several CGH generating algorithms on the Xeon Phi, and the comparisons in terms of the performance and the ease of programming between the Xeon Phi, a CPU and graphics processing unit (GPU).     

On‐Line Detection Of State‐Of‐Charge In Lead Acid Battery Using Radial Basis Function Neural Network

To realize a stable supply of electric power in an automobile, an accurate and reliable detection method of SOC (state‐of‐charge) in a lead acid battery is required. However the dynamics of the battery is very complicated. The characteristics of the battery greatly change due to its degradation. Moreover a automobile has many driving patterns, which are unknown beforehand. Thus it is not easy to detect the SOC analytically. In this paper, to overcome this problem, a new on‐line SOC detection method with a radial basis function neural network is proposed. In order to increase the detection accuracy of degraded batteries, physical values related to the degradation degree are used as input signal in the neural network. The detection accuracies for different sized batteries and various degradation states are investigated.     

Development of anthropomorphic multi-D.O.F. master-slave arm for mutual telexistence

We developed a robotic arm for a master-slave system to support "mutual telexistence", which realizes remote dexterous manipulation tasks and close physical communication with other people using gestures. In this paper, we describe the specifications of the experimental setup of the master-slave arm to demonstrate the feasibility of the mutual telexistence concept. We developed the master arm of a telexistence robot for interpersonal communication. The last degree of the 7-degree-of-freedom slave arm is resolved by placing a small orientation sensor on the operator's arm. This master arm is made light and impedance control is applied in order to grant the operator as much freedom of movement as possible. For this development stage, we compared three control methods and confirmed that the impedance control method is the most appropriate to this system.     

Travel Time Reliability in Vehicle Routing and Scheduling with Time Windows

This paper presents calibration of the Vehicle Routing and scheduling Problems with Time Windows-Probabilistic (VRPTW-P) model which takes into account the uncertainty of travel times. Probe vehicle data of travel times were obtained from usual operation of pickup-delivery trucks in South Osaka area. The optimal solution of the VRPTW-P model resulted in reducing total cost, running times and CO₂, NOx and Particle Materials (PM) emissions compared with the usual operation. This is attributed to better routing of VRPTW-P to choose more reliable roads. Therefore, VRPTW-P can contribute to establish efficient and environmentally friendly delivery systems in urban area.     

Optical CO2 sensor with the combination of colorimetric change of α-naphtholphthalein and internal reference fluorescent porphyrin dye

A new optical CO₂ sensor based on the overlay of the CO₂ induced absorbance change of pH indicator dye α-naphtholphthalein with the fluorescence of tetraphenylporphyrin (TPP) was developed. The observed luminescence intensity from TPP at 655 nm increased with increasing the CO₂ concentration. The ratio I₁₀₀/I₀ values of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer, where I₀ and I₁₀₀ represent the detected luminescence intensities from a layer exposed to 100% nitrogen and 100% CO₂, respectively, that the sensitivity of the sensor, are more than 53.9. The response and recovery times of the sensing films consisting of α-naphtholphthalein in ethyl cellulose layer and TPP in polystyrene layer were less than 5 s for switching from nitrogen to CO₂, and for switching from CO₂ to nitrogen. The signal changes were fully reversible and no hysterisis was observed during the measurements. The highly sensitive optical CO₂ sensor based on fluorescence intensity changes of TPP due to the absorption change of α-naphtholphthalein with CO₂ was achieved.     

Monitoring system to detect fall/non-fall event utilizing frequency feature from a microwave Doppler sensor: validation of relationship between the number of template datasets and classification performance

A fall event is a serious issue for the elderly because it may cause critical aftereffects. To reduce the risk of these aftereffects, early detection of the fall event is essential. However, it is difficult for caregivers to detect fall events early themselves, because they are required to constantly monitor the elderly to confirm their safety. Therefore, an automatic monitoring system which could detect fall events early is helpful in the healthcare field. We have proposed a fall event detection system utilizing a microwave Doppler sensor. The frequency feature is calculated, and compared with known fall or non-fall event data. However, for real-time detection, the number of template datasets must be as low as possible while maintaining high performance of the classification. In this paper, we attempt to identify the relationship between the number of template datasets and the performance of the proposed system.     

Efficient distribution-free population learning of simple concepts

We consider a variant of the ‘population learning model’ proposed by Kearns and Seung [8], in which the learner is required to be ‘distribution-free’ as well as computationally efficient. A population learner receives as input hypotheses from a large population of agents and produces as output its final hypothesis. Each agent is assumed to independently obtain labeled sample for the target concept and output a hypothesis. A polynomial time population learner is said to PAC-learn a concept class, if its hypothesis is probably approximately correct whenever the population size exceeds a certain bound which is polynomial, even if the sample size for each agent is fixed at some constant. We exhibit some general population learning strategies, and some simple concept classes that can be learned by them. These strategies include the ‘supremum hypothesis finder’, the ‘minimum superset finder’ (a special case of the ‘supremum hypothesis finder’), and various voting schemes. When coupled with appropriate agent algorithms, these strategies can learn a variety of simple concept classes, such as the ‘high–low game’, conjunctions, axis-parallel rectangles and others. We give upper bounds on the required population size for each of these cases, and show that these systems can be used to obtain a speed up from the ordinary PAC-learning model [11], with appropriate choices of sample and population sizes. With the population learner restricted to be a voting scheme, what we have is effectively a model of ‘population prediction’, in which the learner is to predict the value of the target concept at an arbitrarily drawn point, as a threshold function of the predictions made by its agents on the same point. We show that the population learning model is strictly more powerful than the population prediction model. Finally, we consider a variant of this model with classification noise, and exhibit a population learner for the class of conjunctions in this model. This revised version was published online in June 2006 with corrections to the Cover Date.     

Simultaneous rate-synchrony codes in populations of spiking neurons

Firing rates and synchronous firing are often simultaneously relevant signals, and they independently or cooperatively represent external sensory inputs, cognitive events, and environmental situations such as body position. However, how rates and synchrony comodulate and which aspects of inputs are effectively encoded, particularly in the presence of dynamical inputs, are unanswered questions. We examine theoretically how mixed information in dynamic mean input and noise input is represented by dynamic population firing rates and synchrony. In a subthreshold regime, amplitudes of spatially uncorrelated noise are encoded up to a fairly high input frequency, but this requires both rate and synchrony output channels. In a suprathreshold regime, means and common noise amplitudes can be simultaneously and separately encoded by rates and synchrony, respectively, but the input frequency for which this is possible has a lower limit.