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The Hoshikubo area of Amami-Oshima was surveyed by electric exploration. Electric resistivity was measured in the ground as deep as 50 m, and a three-dimensional map was developed from the profiles obtained to estimate the composition of the subsurface rock. The results of the analysis of cores drilled from the rock indicate that rock zones showing low resistivity in the electric exploration are rich in Fe and Ni.

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Estimating distances and directions of targets in short range is important for achieving hands-free speech interfaces and nursing-care robots. Conventionally, acoustic imaging methods based on time-of-flight (TOF) with ultrasound have been proposed to estimate the distances and directions of targets. However, these methods have difficulty estimating the distances and directions in the short range which has overlaps of the transmitted and reflected waves. Meanwhile, we have proposed the acoustic distance measurement method which can estimate the distances in the short range. Previously proposed method can be estimated the distance and direction of a single target, but cannot estimate that of multiple targets. Therefore, in the present paper, we propose a new acoustic imaging method based on phase interference between transmitted and reflected waves for estimating distances and directions of multiple targets in the short range. More specifically, we calculate range spectrogram by beamforming range spectra calculated from each microphone of the microphone-array. Also, the proposed method performs the distance attenuation normalization and the sidelobe suppression in range spectrogram. Finally, we confirm the validity and the effectiveness of the proposed method through computer simulations and evaluation experiments in a real environment.

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This paper describes a method of motion control for an omni-directional vehicle. The proposed control system consists of two controllers: self-tuning fuzzy feedforward controller to control the velocity and self-tuning fuzzy feedback controller to control the position and angle of the vehicle. In these controllers, the fuzzy rules are automatically adjusted by the tuning law to improve the responses of the position, angle and velocity; hence, the proposed control method has high-tracking performance. In the proposed self-localization method, the velocity of the vehicle is obtained using four optical mouse sensors as an internal sensor, and the position in the environment is calculated by ICP algorithm using a laser range finder as an external sensor. This information is combined using Kalman filter to eliminate the accumulated error which occurs by an optical mouse sensor. Therefore, the proposed self-localization method is able to estimate the state of vehicle with fast sampling time and high precision. An experiment, which uses an omni-directional vehicle with four omni-wheels, four optical mouse sensors and laser range finder, conducted to evaluate the proposed motion control system. The experimental results reflect the effectiveness of the proposed motion control system for an omni-directional vehicle.

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Motor drive systems are widely used in the industrial field. The rotor stiffness turns down relatively due to the demand of weight saving, and so on. Then the torsional vibration in the drive system appears because of the elasticity of shaft. Such systems consisting a motor and a load with elastic shaft often are modeled as the two-inertia system. When the eccentricity exists in the load, the system has difficulty to follow the constant load speed reference. This paper proposes both an identification method of the eccentricity in the load and a control method to regulate the rotating speed of load without using load-side sensors when the eccentricity exists.

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In recent years, there are increasing interests in statistical shape modeling of human anatomy. The statistical shape model can capture the morphological variations of human anatomy. Since the liver cirrhosis will cause significant morphological changes, the authors propose a computer-aided diagnosis method for liver cirrhosis based on statistical shape models. In the proposed method, the authors first construct a statistical shape model of the liver using 50 clinical CT datasets (25 sets of normal data and 25 sets of abnormal data). The authors apply marching cubes algorithm to convert the segmented liver volume to a triangulated mesh surface which containing 1000 vertex points. The coordinates of these vertex points are used to represent 3D liver shape as a shape vector. After normalization and correspondence finding between all datasets, Principal Component Analysis (PCA) is employed to find the principal variation modes of shape vectors. Then the authors propose a mode selection method based on class variations between the normal class and abnormal class. The authors found the top two modes of class variations are most effective for classification of normal and abnormal livers. The classification rate of abnormal livers and normal liver are 84% and 80%, respectively, by the use of a simple linear discriminant function.

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Genetic Programming (GP) is one of the widely used and practical optimization methods in the problem domain represented by a tree structure; hence, GP has been used to produce instances as a competitive method with human-produced ways, and numerous researchers have applied GP to a wide variety of fields, including electrical circuits, robotics, image filters. Namely, it is important to explore new application areas. In this paper, we define the generalized lighting control problem, and present a novel method using GP for individual lighting. Previous researches have reported that providing each worker's desired illuminance can enhance intellectual productivity and save energy consumption; however, it is difficult to determine an optimum light intensity which satisfies both different desired illuminance values and energy-saving. The proposed method automatically generates lighting control rules, and evaluates rules with observed illuminance data. According to the Building Block Hypothesis, we also propose a new subtree encapsulation method for lighting control based on frequent trees and depth information. First, by using three well-known benchmark problems, we verify that the proposed encapsulation method improves solution quality. Next, we demonstrate its effectiveness for the generalized lighting control problem.

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For embedded systems, concurrency is required to respond to various changes in real world. Real-time processing is required also, because the response typically has a time limit. The concurrency is implemented by processing Tasks or Interrupt Service Routines (ISRs) concurrently. And the necessity of mutual exclusion arises in concurrent processing, to maintain integrity of shared data. Task execution is scheduled by Real-time OS (RTOS), and mutual exclusion is serviced by semaphore. However approximately 30% of embedded systems do not use RTOS. These systems have no notion of Tasks, and are purely driven by ISRs. As the sole mutual exclusion method between ISRs, a pair of interrupt disable/enable instructions provided by CPU is used in these systems. This method enables a lower priority ISR to protect its critical section from higher priority ISRs, but it also defers execution of unrelated ISRs as it disables all external interrupts. We have resolved this timing issue with an ISR-callable semaphore, but that design was not priority inversion safe. Namely a middle priority ISR may indirectly block a higher priority ISR if this higher priority ISR waits for a semaphore from a lower priority ISR, because the lower priority ISR can be preempted by the middle priority ISR. Priority inheritance is an effective protection method against this priority inversion problem, and it is expected to improve real-time performance of OS-less embedded systems. This paper proposes an ISR-callable priority inheritance semaphore which protects ISRs from priority inversion using hardware interrupt mechanism.

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Novel technique for measuring a position of a fiber with a high birefringence is proposed using polarization optical time domain reflectometer (P-OTDR) for the purpose of detecting the defective section in the optical transmission line. Our technique is based on the fact that the degree of polarization (DOP) of backscattered light from the position with high birefringence becomes large when the polarization state of the input pulse coincides with either fiber axes and it becomes small in other cases. Taking the above relation into account, the fiber position with the high birefringence can be detected in our technique, as the position with lower DOP which is obtained from the average backscattered light measured for the various polarization states of input light. Moreover, it is confirmed experimentally that the position of fiber coil with a diameter of 6 cm, which is inserted into the transmission line, can be detected by our present technique. It is also confirmed that our technique can be successfully applied to the optical cables installed outside.

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In this study, we have succeeded in detecting the neurotransmitters at nM level using multi-wall carbon nanotube (MWCNT) Bamboo and Hollow electrodes. CNT electrodes were created with mineral oil and graphite powder in order to press the electrode surface. In cyclic voltammetry measurements, dopamine was detected at 1 nM level using MWCNT Bamboo electrodes and serotonin at 1 nM level using MWCNT Hollow electrode. Moreover, in chronoamperometry measurement, dose-response relationships from 10 nM to 100 µM were observed in dopamine and serotonin. These results suggest that MWCNT bamboo and Hollow electrodes have a potential for the real-time measurement of neurotransmitters from living neurons.

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Nutrition feeding tubes are widely used in hospitals for patients who have difficulty in swallowing. The tube is expected to stay within the stomach, but is sometimes drawn up to the esophagus, which might cause diseases such as pneumonia. Therefore, it is necessary to confirm that the tip of tube exists in the stomach. For safely and easy monitoring of the tip position of the feeding tube within the body, we have developed a method using ac magneto-susceptometry to detect a magnetic marker that was inserted at the tube tip. We analyzed the magnetic field generated by the line current of a rectangular excitation coil and determined the geometry to detect the signal field in a direction perpendicular to the excitation field. The generated ac dipole-field in synchronization with the excitation field was measured as the voltage with a detection coil fixed near the excitation coil. As a result, we could detect the signal down to the order of 1 nT at a depth of 15 cm from the detection coil.

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The aim of this study was to develop a low-cost automated system to measure the three-dimensional curvature of the spine in patients with scoliosis. The conventional method for assessing the curvature of the spine in scoliosis is the Cobb method, which poses a health risk due to exposure to ionizing radiation. Therefore, several noninvasive methods for measuring the curvature of the spine have been developed; however, these have not yet gained widespread use in clinical practice.
We used a 3D camera to measure the curvature of the spine in 10 healthy young volunteers. An analysis of variance was used to show the difference in measurements of humps and twisted angles of the subjects' spines. The results for the hump measurement revealed an F value of 25.23 and a P value of <0.01, while those for the twisted angle measurement revealed an F value of 36.00 and a P value of <0.01.
Measurements of the curvature of the spine using our method were obtained in a short time (approximately 2 s). Therefore, this method can probably be applied to mass screening. The results confirmed the effectiveness of our 3D camera for measuring the curvature of the spine in patients with scoliosis.

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In recent years, the reduction of TCO (Total Cost of Ownership) from system architecture to start-up, operation and maintenance has risen rapidly as demands for FA (Factory Automation) market. On the other hand, due to the complexity or combination of machines and devices, or the advancement for the high-speed and high-accuracy demands, it has come to be connected with a network between a controller and amplifier. However, the conventional servo network also had various problems in the point of TCO reduction.
The servo network proposed in this paper allowed us to obtain the situation of the position and speed of the amplifier on the other side in the synchronous control through the communication between the amplifiers conventionally unattainable. Compared with the conventional system, high-speed and high-accuracy operation can be realized with the new synchronous compensation control which utilized the data obtained between amplifiers, and the improvement in operation productivity was able to be verified with an actual machine. Conventionally, it was composed of plural electrical signals, however, the new network realizes the optical communication only for a pair by a circuit technology and it was also proved to be effective for high productivity in setup and maintenance on the market performance.

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In the selection of portraits for ID and a profile, it is useful to retrieve high quality facial images from a lot of portraits. In addition, overexposure may give a negative impact on us because overexposed facial parts look unnaturally white; therefore the recognition for qualitative meaning of overexposure is important for retrieval of high quality facial images. To get qualitative meaning by a image analysis method that can evaluate images quantitatively, it needs a quasi-quantitative evaluation method that can use an index of quantitative evaluation having qualitative meaning. In this paper, we investigated the index for quasi-quantitative estimation of overexposure in the facial image on the basis of the heuristic assumptions, and defined the index as the overexposure intensity (OI). We developed an algorithm with Support Vector Machine (SVM) for judging the OI. The results of experiment conducted with 11 evaluators for analyzing images suggest that the proposed method can retrieve a facial image for ID and the profile with an F-measure of 96.2%.

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The template matching is the basic technique of the industrial image processing for the object detection such as the defect inspection and OCR (Optical Character Recognition). It has a problem which requires a lot of computational time for detecting the XY displacement and the rotational angle of the target object. We have proposed the eigen template method for this problem. The proposed method can efficiently calculate correlation between images using principal component analysis. However, when an input image is complicated, the method failed to detect the target object correctly. Additionally, the computational time of the method remains large still. In this paper, we propose the edge based eigen template matching method with robustness for the complex image compared with the previous method. Moreover, we describe an efficient matching algorithm for the eigen template matching using approximate nearest neighbor search. In the evaluation experiments using a simulation image and a captured image, we show that the proposed method can detect the target object faster and more robust to the complex image than the previous methods.

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Usually, there are two processes in wafer inspection. One is detection of defects on a wafer, which is very important. The other is classification of the detected defects, which is done after defect detection as necessary. Recently, it has been necessary to simultaneously detect and classify defects on wafers in order to shorten the wafer inspection time with high resolution. Optical wafer inspection is the most effective method for detecting and classifying a defect and estimating its size in a short time. Optical wafer inspection utilizing scattered light distribution can easily detect and classify a defect since the distribution depends on both the type and size of the defect. The measured scattered light distribution is compared with a database of the previous scattered light distributions using pattern matching in order to classify the defect and estimate its size. Therefore, to achieve optical wafer inspection with scattered light distribution, it is necessary to gather scattered light distribution data for many various samples.
The first aim of this study is to develop a defect classification and size estimation method utilizing scattered light distribution. We propose a way for classifying a defect on a wafer and estimating its size. The proposed method uses pattern matching utilizing a parametric eigenspace. The second aim of the paper is to validate the proposed method by applying it to scattered light distribution samples. The light scattering distribution samples are generated by Discrete Dipole Approximation (DDA) simulation. The database of the light scattering distributions is easily created using the simulation.

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The data generated at a very high rate by sensors and RFIDs are required to be handled by continuous queries keeping real time response. DSMSs (Data Stream Management systems) are used in several cases of these large scale systems for its purpose. This paper describes the results of experimental evaluation of distributed data stream processing using SQLite which is a lightweight RDBMS as a stream processing engine node. In particular, it is necessary to correspond also to the increasing data rate flexibly in data stream processing. This paper proved that it could respond to the increase in a data rate by adding a processing node dynamically. In that case, it is necessary to perform synchronous processing in two or more processing nodes. Therefore, within the limits of this experiment, it turned out that it is realizable by performing synchronous processing by the side which divides and passes data.

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