We describe a cholesteric liquid crystal (ChLC) laser with an in-plane helix alignment where the ChLC helix lies in the in-plane direction of the cell and report an improvement in the threshold characteristics. The in-plane helix alignment of ChLCs was formed by applying an in-plane electric field in a cell with homeotropic surface treatment while cooling the sample from the isotropic phase. The energy threshold was 0.3 mJ/cm², which was found to be less than 1/10 of conventional planarly-aligned ChLC lasers. The threshold gain was measured using variable stripe length method and was determined as 1 cm^-1, which is approximately 1/100 of conventional planar devices with a cell-gap of 10 μm. The improvement of the energy threshold is attributed to small threshold gain attained in these devices.

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An EMC macro-model for LSIs, named the LECCS-core model, is under development for simulating high frequency noise in power supply currents. In this paper, the conventional LECCS-core model is extended by adding resistances in the ground connection of an LSI, in order to separate the core block and the analog block. The model parameters are identified using symbolic analysis and least-square optimization. Using this new model, the transfer impedances between different power supply pins can be simulated accurately. Additionally we derived the equivalent internal current sources by using that model. As a result, we confirmed that the internal current sources were improved. In conclusion, we confirmed that the configuration of the linear equivalent circuit and our modeling method can be applied widely to microcontrollers of the same block configuration.

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In order to avoid congestion in the network and to achieve a fair share of the resource among communication flows, the packet discarding method called RED (Random Early Detection) has been proposed. In that method, a router randomly discards arriving packets before its buffer overflows. Although some enhanced methods of RED have been proposed, they employ complicated controls to achieve high throughput and fairness among communication flows. However, many control parameters in the complicated methods would prevent from reaching their practical stages. This paper proposes a simple packet discarding method which reduces the number of parameters and provides better performance than existing ones. Concretely speaking, our method omits the probabilistic packet discard from RED. Via simulation, the proposed method provides higher throughput than existing ones and almost equal fairness.

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We propose a maglev transportation system that has only the Single-sided Linear Induction Motor (SLIM) without the levitation magnet and a novel control method of the attractive force and thrust force of the SLIM by the power source that has different frequency components. In the proposed system, the total force is the sum of the forces generated by the different frequency components. We verified the incoherent characteristics of the attractive force and thrust force by experiment.

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In recent years, the research of sensor networks advances and it is expected to be used in a wide variety of fields such as traceability system of products, environmental monitoring, health care, etc. We develop a M2M system with the sensor network technology for collection and analysis of the state of health and feedback of advices for better physical activity without human intervention. The system detects abnormality from pulse wave data from pulse wave sensor attached to the user. In this paper, we construct M2M sensor network system with continuous monitoring of arterial pulse wave and an advice generation function based on pr-installed rules, then we evaluate the usefulness of the system through experiment.

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In a large scale system like building air-conditioning system, measured time-series data is observed from many kinds of sensors. It is difficult to detect the fault by the administrators because only the limited experts can diagnose the unusual system. For this reasons, the new method is required, which can detect the fault from the measured data using a computer automatically.
This paper proposes how to extract feature pattern from measured time-series data using a learned neural network, and how to detect the fault with a knowledge expression model. The learned neural network can extract a feature pattern by calculating the weight of the neuron in output layer. The knowledge expression model can be constructed with the result of case analysis and the criteria. The result of the fault can be detected by the condition of the model, which is represented by the feature pattern. Through practical experiments, it is confirmed that the proposed method is effective to detect the fault of air conditioning system.

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The brains of living organisms have excellent information-processing functions. Although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. Reportedly, STDP (Spike Timing Dependent synaptic Plasticity) is generated between inputs of pre-synaptic neurons and backpropagation of the active potential from dendrites of post-synaptic neuron, as revealed by physiological experiments. Using electronic circuits, we are constructing a hardware model with the characteristics of biological neurons.
In this paper, we propose an active hardware dendrite model inducing STDP based on backpropagation phenomena of biological dendrites. Results clarified the following two points.
1. The synaptic transmission efficiency of constructed model is changed by timing of the action potential of the input of pre-synaptic neuron and the action potential of backpropagation of the dendrite of the post-synaptic neuron.
2. When Δt is small, the amplitude change becomes large. When Δt is large, the amplitude change becomes small

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Anomalous radiation of environmental electromagnetic wave is reported as a portent of earthquakes. Then, we are observing environmental electromagnetic waves of the ELF band all over Japan. We have been regarding the large amplitude in the observed signal as anomalous radiation. However, the observed signal contains a lot of slight amplitude anomalies hidden by background noise. To detect the earthquake precursor, it is necessary to detect not only large amplitude anomaly but also slight amplitude anomaly. In this paper, we propose the method of detecting anomalous radiation using the magnetic field azimuth which does not depend on the amplitude level. It is assumed that magnetic field azimuth has notable fluctuation when anomaly EM radiation occurs. We detect this fluctuation by the azimuthal standard deviation calculated every 20 minutes. Moreover, we show that it is dominant in anomaly detection to use the fluctuation in magnetic field azimuth instead of the amplitude level.

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Personal classification using sole pressure change is essential for intelligent control, security on home because the users do not need to have anything, such as ID-Card, PIN code and so on. In our study, we propose a personal classification system by sole pressure change obtained by mat type pressure sensor. Mat type pressure sensor is placed on the floor in the entrance of home. We employ four features for classifying each family member and do personal classification based on Euclidean distance based method. As the experimental result on healthy 60 volunteers ranged from 20 to 80 years old, we have evaluated the performance. The results showed that the proposed system successfully classified them and it is especially useful in home intelligent system.

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This paper investigates the L₂-gain analysis and synthesis issues under the Filippov framework for a class of nonlinear time-delay systems with discontinuity. First, an extension of L₂-gain property along all the Filippov solutions is given for the time-delay systems, and a sufficient condition is presented that guarantees the nonlinear time-delay systems is strongly stable in the sense of Filippov solution, and the L₂-gain less than a given level. The condition is described by functional partial differential inequality. Then, as an application of the presented condition, a feedback control design problem is solved that the controller strongly stabilized a given plant with pre-specified L₂-gain. Furthermore, as a special case study, the case of linear systems is discussed and it is shown that for the piecewise continuous linear systems, the sufficient condition is represented by algebraic Riccati inequalities.

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Inverted pendulums are very often used to verify many control theories, because they are typical unstable systems and also are interesting objects. However, few innovative methods with respect to the adaptive control of inverted pendulum (IP) are reported. This paper presents a stabilization method by using the adaptive control for a serial rotary-type double inverted pendulum (SRDIP) whose whole basic parameters are unknown. The control system of a SRDIP is achieved by separating the control mode to two stages. The first stage is an adaptive control mode of the single IP placing the second IP in downward directions and another stage is a LQ control mode of the SRDIP. The control system prepares two kinds of adaptive controllers, which are a variable structure system (VSS) robust adaptive control and a self-tuning control (STC). The rotational angle of the first IP is stabilized by the VSS adaptive control, and the stability of the rotary arm is also achieved by constructing the STC that guarantees the boundary reference angle of the first IP. It is then difficult to construct the STC by only adjustable parameters of the VSS adaptive control system. Whole basic parameters of a SRDIP are estimated by adopting the recursive least squares (RLS) estimation method in order to accomplish both of the STC system and the LQ design of a SRDIP. The RLS algorithm is performed by superposing an available perturbation signal to the adaptive manipulated variable on a limited short interval. The STC system updates a LQ controller based on the QR methods devised for the real time operation. Before completing the first stage, a LQ controller for the SRDIP is obtained through a state space description from the estimated basic parameters. The control law is changed to a LQ control for the SRDIP from an adaptive control mode in the second stage. Finally, it is verified by simulation studies and practical experiments that the proposed system is useful as a control strategy of the SRDIP with an unknown parameter.

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The proposed method can improve the response for the servo type Continuous-time Generalized Minimum Variance Control (CGMVC). The conventional CGMVC, which is tuned due to the controlled input weighting of the cost function, cannot freely adjust the response in the case of the servo type. This study proposes a new servo CGMVC of tuning the output weighting of the cost function. The proposed CGMVC is applied by the Partial Model Matching (PMM) method. The CGMVC with PMM and tuning the output weighting can improve both the response of tracking the reference signal and the load-disturbance rejection.

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This paper proposes measurement site selection to visualize a wafer characterization map and also monitor wafer-to-wafer and batch-to-batch variation. In the manufacturing line of thin film devices such as large-scale integrated circuits, magnetic heads of hard disk drives and thin-film-transistor substrates of liquid-crystal projectors, several critical dimensions are generally measured and monitored for quality control. To monitor wafer-to-wafer and batch-to-batch variation, engineers control average and standard deviation of measured dimensions as statistical process control. To monitor characterization across a wafer, the engineers observe an sculptured surface as a wafer map. The paper presents a selection method to decide measurement sites across a wafer for both of the wafer map visualization and the process monitoring and examines their accuracies experimentally.

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In many engineering fields, distance to targets is very important. General distance measurement method uses a time delay between transmitted and reflected waves, but it is difficult to estimate the short distance. On the other hand, the method using phase interference to measure the short distance has been known in the field of microwave radar. Therefore, we have proposed the distance estimation method based on interference between transmitted and reflected audible sound, which can measure the distance between microphone and target with one microphone and one loudspeaker. In this paper, we propose talker localization method based on distance estimation using phase interference. We expand the distance estimation method using phase interference into two microphones (microphone array) in order to estimate talker position. The proposed method can estimate talker position by measuring the distance and direction between target and microphone array. In addition, talker's speech is regarded as a noise in the proposed method. Therefore, we also propose combination of the proposed method and CSP (Cross-power Spectrum Phase analysis) method which is one of the DOA (Direction Of Arrival) estimation methods. We evaluated the performance of talker localization in real environments. The experimental result shows the effectiveness of the proposed method.

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The adaptive notch filter that is composed of the exponential type all-pass circuit has the stable and the robust characteristics for the broadband signal. In this paper, a method to reduce the degree and the constant delay of the adaptive filter and a adaptive algorithm using the window function are presented. The application to the narrowband signal canceling in the speech signal, the sound noise canceling and the howling signal canceling are also presented.

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A navigator guides a ship for safe and efficient navigation, and s/he gets navigational information through the five senses. Visual information is most important because it is said to occupy more than eighty percents to whole information. We are researching the relationship between the visual image of seascape and the physiological/body response using ship bridge simulator, which is used to train and educate ship handling and how to handle a navigational instrument. The simulator-based training is popular worldwide. The simulator is able to control the traffic situation and to do the same scenarios for trainees. On the merchant ship simulator-based training, the ship movements- rolling, pitching, yawing, etc., never simulate by visual or motion platform. However, the ship movement is an important factor for the simulator-based training, and we need to confirm the influence of body and mental workload for the simulated ship movements. The purpose of this paper is to find characteristics of body response to artificial ship movements by visual and motion platform. The result shows characteristics of body response to artificial rolling and pitching by visual and motion platform differ.

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Ultrasonic sensors are often utilized to perceive the outside world. In this paper, we propose the construction of an object identification system that utilizes the ultrasonic waves reflected from a measured object. This identification system also detects the position and posture of an object. The system consists of an ultrasonic sensor array and a neural network. The ultrasonic sensor array is made up of plural ultrasonic transmitters and receivers that are arranged on the same plane. The receiver outputs the peak values of ultrasonic sound pressure waves. Their values are input into the neural network, which identifies the shape of the object and detects its position and posture. We have designed and built a prototype system and carried out numerous experiments using objects with primitive shapes or transparent bottles (PET bottles). The experimental results showed almost perfect shape identification and a measurement accuracy of up to one-half of one wavelength of the ultrasonic wave.

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There are diseases with the disorder in the face although human's face is an important body site with the social role. In this study, it is focused on “patient's facial expression” as a medium supporting communications between the patient with facial disorder and the doctor toward the satisfaction improvement to the patient's treatment on the medical treatment site. And, “expression to be expressed” and “difference between the expression actually expressed aiming at the expression to be expressed and the expression to be expressed” were selected as information transmitted through patient's expression. The design and development of an interface with the functions of an expression setting and an expression confirmation were carried out as an environmental setting for the patient to express selected information. Fourteen dentists in total who had the treatment experience of the facial disorder evaluated the possibility of the proposed interface as utility and a communication tool in the medical treatment site. The possibility of leading to the expression of the expectation for the patient's treatment was suggested as the results of the experiment, and concrete challenge points and the method for use in the medical treatment field were proposed.

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We propose a face-tracking system for AIBO by using the skin color, in the first step of acquiring user's characteristics. In this paper, we focus on the human-face, which has many kinds of characteristic parts in a human. We detect faces using the Neural Network (NN) for the purpose of estimating whether one pixel is skin color or not. However, the hierarchical NN may give this system false recognition for unknown color of background. In this paper, we propose high generality face recognition system for AIBO using the radial basis function (RBF) network. Also, in order to show the effectiveness of the proposed method, we perform computer simulations. First of all, we can see the skin color recognition results using the RBF network. In various light conditions, we have the relatively good results of the skin color recognition. Furthermore, we show output value distribution in color space. We can see the possibility of dealing with unknown color using the RBF network. Moreover, we have achieved the skin color recognition for AIBO in a real system. We will show that AIBO can track skin color in many kinds of light conditions.

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Scene analysis based on the images captured from rescue robot is used to be composed of the basic three image processing stages: edge detection, line detection, and object recognition. The key technology to do this is Hough transform for line detection. The FIHT3 method, a companion method of a Fast Incremental Hough Transform (FIHT), is very appropriate to such line detection, because it is the fastest in processing and is with highly accurate in performance. However, the processing time allowed by line detection is 10 ms or less to analyze the scene in real time. Because the FIHT3 method has achieved speed-up by the shift operation, the number of partitions in θ axis of Hough voting space can take only a certain limited value. Therefore, the FIHT3 method should be more improved so that it could be applicable to any number of partitions in θ axis. Because FIHT3 is not applicable to the odd number of angle partitions due to the basic property of the simultaneous recurrence formula. Then, in this research, we propose the improved FIHT method that can process even if the number of angle partitions is odd. Furthermore, in the experiments of rescue robot it was known experimentally that the improved FIHT method provides the complete accuracy and the fastest computation among conventional any other methods.

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We propose a new method for analyzing dynamics of facial expression changes to identify persons. Several methods have been proposed to identify persons using facial images. In most methods, variations in facial expressions are one trouble factor because an input face image does not always contain the same facial expression as training images. However, the dynamics of facial expression changes are one measure of personal characteristics. In the proposed method, facial feature points are extracted using Active Appearance Models (AAMs) in the first frame of each video. They are then tracked using the Lucas-Kanade (LK) based feature point tracking method. Next, the starting and ending frames of facial expression changes are extracted by differences in the facial feature points' position between two successive frames. Finally, a feature vector is obtained as the sequence of the 2D coordinate variations of facial feature points. In the identification phase, an input feature vector is classified by calculating the distance between the input vector and the training vectors using dynamic programming matching (DP matching). We show the effectiveness of the proposed method using facial expression videos of the Facial Expressions and Emotions Database from Technical University of Munich (FEEDTUM database).

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For the analysis of soccer videos, positional information of players and ball is very essential. In order to obtain trajectories of the players, robust tracking for multiple players is highly required. In this paper, we propose a method to track multiple players in a soccer video which is captured by a single camera. In the case of capturing the video from a single view, there might be a lot of occluded situations of players. In order to overcome this problem, we propose a robust tracking method for multiple players by combining Particle Filter and Real AdaBoost Classifier. First, each target player is tracked by using Particle Filter. Next, an occluded situation is automatically detected by checking a distance between the target players. Then we resample the center of the gravities by classifier's detection after Particle Filter tracking. We show the experimental results and effectiveness of our proposed method.

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This paper proposes a new electronic voting (e-voting) scheme that fulfills all the security requirements of e-voting i.e. privacy, accuracy, universal verifiability, fairness, receipt-freeness, incoercibility, dispute-freeness, robustness, practicality and scalability; usually some of which are found to be traded. When compared with other existing schemes, this scheme requires much more simple computations and weaker assumptions about trustworthiness of individual election authorities. The key mechanism is the one that uses confirmation numbers involved in individual votes to make votes verifiable while disabling all entities including voters themselves to know the linkages between voters and their votes. Many existing e-voting schemes extensively deploy zero-knowledge proof (ZKP) to achieve verifiability. However, ZKP is expensive and complicated. The confirmation numbers attain the verifiability requirement in a much more simple and intuitive way, then the scheme becomes scalable and practical.

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There are a lot of information leakages because the files are copied from the removable storage medium and are left in the storage unit of personal computer without deleting. In order to prevent human mistakes, this paper proposes a method for detecting the remaining files copied from the removable storage medium. The proposed method records logs regarding changed information registering in a directory that is management list of files in storage unit and the hash values of file contents. The remaining files are detected when the removable storage medium removes from the personal computer, and they are displayed on the monitor. The detection processing works in five steps. First, copy operation toward file is detected by tracing the sequence of logs. Secondly, files copied from the removable storage medium are distinguished based on hash values. Thirdly, file operation and folder operation to copied files are distinguished. Fourthly, the deletion operation against the copied file is detected by using file name and path matching. Finally, file name and path using for tracing are changed according to folder operation. In case of the deletion operation is not found, it is judged that copied files are remaining. Our experimental result suggests that the proposed method can accurately detect remaining files left on the storage unit.

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The accuracy of registers is one factor determining the analog circuit accuracy. Therefore, we propose new estimation technique of the register value depending supply voltage using distortion characteristics. To use this technique, we show that the voltage-dependent is in inverse proportion to W×L.

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Farnsworth D15 test is one of famous color blindness tests. The type of the color blindness and as well its severity can be known by this test. When we perform Farnsworth D15 test using a PC, we investigate the conditions (i.e., color temperature, gamma characteristic and luminance) for a monitor, experimentally.

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In this paper, we propose a method for detecting white lane marks by extracting white regions with constant predefined width from bird's-eye road images after segmentation such as categorical color area one. The proposed method is based on constrained Delaunay triangulation. Experimental results for 187 bird's-eye actual road images show the effectiveness of the proposed method.

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We propose a robust control system which has robustness for disturbance and can deal with a nonlinear system with partially unknown structure by fusing reinforcement learning and robust control theory. First, we solved an optimal control problem without using unknown part of functions of the system, using neural network and the repetition learning of reinforcement learning algorithm. Second, we built the robust reinforcement learning control system which permits uncertainty and has robustness for disturbance by fusing the idea of H infinity control theory with above system.

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