Device-parameter estimation sensors inside a chip are gaining its importance as the post-fabrication tuning is becoming of a practical use. In estimation of variational parameters using on-chip sensors, it is often assumed that the outputs of variation sensors are not affected by random variations. However, random variations can deteriorate the accuracy of the estimation result. In this paper, we propose a device-parameter estimation method with on-chip variation sensors explicitly considering random variability. The proposed method derives the global variation parameters and the standard deviation of the random variability using the maximum likelihood estimation. We experimentally verified that the proposed method improves the accuracy of device-parameter estimation by 11.1 to 73.4% compared to the conventional method that neglects random variations.

In automated transport applications, the design of a task allocation policy becomes a complex problem when there are several agents in the system and conflicts between them may arise, affecting the system's performance. In this situation, to achieve a globally optimal result would require the complete knowledge of the system's model, which is infeasible for real systems with huge state spaces and unknown state-transition probabilities. Reinforcement Learning (RL) methods have done well approximating optimal results in the processing of tasks, without requiring previous knowledge of the system's model. However, to our knowledge, there are not many RL methods focused on the task allocation problem in transportation systems, and even fewer directly used to allocate tasks, considering the risk of conflicts between agents. In this paper, we propose an option-based RL algorithm with conditioned updating to make agents learn a task allocation policy to complete tasks while preventing conflicts between them. We use a multicar elevator (MCE) system as test application. Simulation results show that with our algorithm, elevator cars in the same shaft effectively learn to respond to service calls without interfering with each other, under different passenger arrival rates, and system configurations.

Dielectric rod arrays in a metallic waveguide alter the propagation modes and group velocities of electromagnetic waves. We have focused on TE30-to-TE10 mode converters and investigated how their behavior varies with frequency. A mode converter is proposed that passes the TE10 mode at frequencies lower than 2fc, and converts the TE30 mode into the TE10 mode for frequencies higher than 3fc.

Let (X,Y) be a Rd R-valued random vector. In regression analysis one wants to estimate the regression function m(x):=E(Y|X=x) from a data set. In this paper we consider the convergence rate of the error for the k nearest neighbor estimators in case that m is (p,C)-smooth. It is known that the minimax rate is unachievable by any k nearest neighbor estimator for p > 1.5 and d=1. We generalize this result to any d ≥ 1. Throughout this paper, we assume that the data is independent and identically distributed and as an error criterion we use the expected L2 error.

This letter proposes a slot-based opportunistic spectrum access for cognitive radio networks. To reduce the slot-boundary impact, control frames are used to achieve channel reservation. The saturation throughput of our scheme is estimated by an analytical model. The accuracy of the model is validated by extensive simulation.

This paper presents a novel method for reconstructing 3D geometry of camera motion and human-face model from a video sequence. The approach combines the concepts of Powell's line minimization with gradient descent. We adapted the line minimization with bracketing used in Powell's minimization to our method. However, instead of bracketing and searching deep down a direction for the minimum point along that direction as done in their line minimization, we achieve minimization by bracketing and searching for the direction in the bracket which provides a lower energy than the previous iteration. Thus, we do not need a large memory as required by Powell's algorithm. The approach to moving in a better direction is similar to classical gradient descent except that the derivative calculation and a good starting point are not needed. The system's constraints are also used to control the bracketing direction. The reconstructed solution is further improved using the Levenberg Marquardt algorithm. No average face model or known-coordinate markers are needed. Feature points defining the human face are tracked using the active appearance model. Occluded points, even in the case of self occlusion, do not pose a problem. The reconstructed space is normalized where the origin can be arbitrarily placed. To use the obtained reconstruction, one can rescale the computed volume to a known scale and transform the coordinate system to any other desired coordinates. This is relatively easy since the 3D geometry of the facial points and the camera parameters of all frames are explicitly computed. Robustness to noise and lens distortion, and 3D accuracy are also demonstrated. All experiments were conducted with an off-the-shelf digital camera carried by a person walking without using any dolly to demonstrate the robustness and practicality of the method. Our method does not require a large memory or the use of any particular, expensive equipment.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

A perfect array is an array for which the autocorrelation function is impulsive. A parameterization of perfect arrays of real numbers is presented. Perfect arrays are represented by trigonometric functions. Three formulae are obtained according to the parities of the size of the array. Examples corresponding to each formula are shown. In the case of 66 arrays, the existence of a set of perfect arrays having integer components is shown.

We investigate the problem of joint frequency and power allocation in wireless mesh networks, using a self-pricing game based solution. In traditional pricing game models, the price factor is determined from the global information of the network, which causes heavy communication overhead. To overcome this problem, we propose a self-pricing game model, in which the price factor is determined by the distributed access points processing their individual information; moreover, it is implemented in an autonomous and distributed fashion. The existence and the efficiency of Nash equilibrium (NE) of the proposed game are studied. It is shown that the proposed game based solution achieves near cooperative network throughput while it reduces the communication overhead significantly. Also, a forcing convergence algorithm is proposed to counter the vibration of channel selection. Simulation results verify the effectiveness and robustness of the proposed scheme.

Wireless body area networks (WBANs) provide medical and/or consumer electronics (CE) services within the vicinity of a human body. In a WBAN environment, immediate and reliable data transmissions during an emergency situation should be supported for medical services. In this letter, we propose a flexible emergency handling scheme for WBAN MAC protocols. The proposed scheme can be applied to superframe-structured MAC protocols such as IEEE 802.15.4 and its extended versions. In addition, our scheme can be incorporated into the current working draft for IEEE 802.15.6 standards. Extensive simulations were performed and the low latency of emergent traffics was validated.

Generally, the failure rate of a sealed relay is regarded as a constant value, no matter where and how it is used. However, the failure processes of sealed relays won't be the same under different conditions, even for one relay, its failure rate also will be changed during operations. This paper studies the failure process of a kind of sealed relay by analyzing the variations of its time parameters. Among contact resistance and all those time parameters, it is found that closing gap time can indicate the failure process of tested relay very well. For the purpose of verifying this conclusion derived from time parameters, the contacts are observed by microscope after the tested relay failed. Both theoretical calculation result of contacts gap and photos taken by microscope show that the hypothetic failure mode derived from time parameters is reasonable. Based on the failure analysis, the paper also proposes a dynamic reliability estimation method with closing gap time.

Break arcs are rotated with the radial magnetic field formed by a magnet embedded in the fixed contact. They are generated in a DC42 V resistive circuit. The circuit current when the contacts are closed varies from 5 A to 21 A. The strength of a radial magnetic field for rotating break arcs changes. Arc duration is investigated. Then rotational frequency, arc length and Lorentz force when the periodic rotation of break arcs starts are analyzed to investigate the conditions required to rotate break arcs. The following results are obtained. The arc length L when the rotational motion of the break arc starts is almost constant at a constant magnetic flux density with an increase in circuit current. The arc length L decreases with an increase in the magnetic flux density of the radial magnetic field. The rotational motion of break arcs starts when the arc length L reaches a certain value determined by magnetic flux density. Rotational frequency and Lorentz force increase linearly with an increase in circuit current.

A novel algorithm is presented for near-field source localization with a symmetric uniform linear array (ULA) consisting of an even number of sensors. Based on element reordering of a symmetric ULA, the steering vector is factorised with respect to the range-independent bearing parameters and range-relevant 2-D location parameters, which allows the range-independent bearing estimation with rank-reduction idea. With the estimated bearing, the range estimation for each source is then obtained by defining the 1-D MUSIC spectrum. Simulation results are presented to validate the performance of the proposed algorithm.

In existing systems of mobile routers, the frequency band is shared in uplinks from wireless terminals to mobile routers, and carrier sense multiple access with collision avoidance (CSMA/CA) is generally used as the medium access control protocol. To use the frequency band effectively, adaptive control is one promising approach. In this paper, a decentralized access control protocol in which mobile routers adaptively select the minimum contention window size is proposed. However, because of their mobility, which is one of the main difference between mobile routers and fixed access points, individual local area networks (LANs) consisting of the mobile routers and wireless terminals randomly interact with each other, and such random interactions can cause instability. To analyze the stability of the proposed control, evolutionary game theory is introduced because a system with random interactions between numerous decision-making entities can be analyzed by using evolutionary game theory. Using evolutionary game theory, the condition for existence of a convergence point is obtained. In addition, to implement the decentralized access control, a learning rule is proposed. In the proposed learning rule, each mobile router selects a strategy based on the result of past trials. From the simulation result, it is confirmed that the decentralized access control converges to a point closed to the stable state derived through evolutionary game theory.

This paper presents the development of a sound–specific vibration interface and its evaluation results by playing three commercial games with the interface. The proposed interface complements the pitfalls of existing frequency–based vibration interfaces such as vibrating headsets, mouses, and joysticks. Those interfaces may bring negative user experiences by generating incessant vibrations because they vibrate in response to certain sound frequencies. But the proposed interface which responds to only target sounds can improve user experiences effectively. The hardware and software parts of the interface are described; the structure and the implementation of a wrist pad that delivers vibration are discussed. Furthermore, we explain a sound-matching algorithm that extracts sound characteristics and a GUI-based pattern editor that helps users to design vibration patterns. The results from evaluating the performance show that the success ratio of the sound matching is over 90% at the volume of 20 dB and the delay time is around 400 msec. In the survey about user experiences, the users evaluates that the interface is more than four times effective in improving the reality of game playing than without using the vibration interfaces, and two times than the frequency–based ones.

In this paper, we consider a nonparametric regression problem using a learning machine defined by a weighted sum of fixed basis functions, where the number of basis functions, or equivalently, the number of weights, is equal to the number of training data. For the learning machine, we propose a training scheme that is based on orthogonalization and thresholding. On the basis of the scheme, vectors of basis function outputs are orthogonalized and coefficients of the orthogonalized vectors are estimated instead of weights. The coefficient is set to zero if it is less than a predetermined threshold level assigned component-wise to each coefficient. We then obtain the resulting weight vector by transforming the thresholded coefficients. In this training scheme, we propose asymptotically reasonable threshold levels to distinguish contributed components from unnecessary ones. To see how this works in a simple case, we derive an upper bound for the generalization error of the training scheme with the given threshold levels. It tells us that an increase in the generalization error is of O(log n/n) when there is a sparse representation of a target function in an orthogonal domain. In implementing the training scheme, eigen-decomposition or the Gram–Schmidt procedure is employed for orthogonalization, and the corresponding training methods are referred to as OHTED and OHTGS. Furthermore, modified versions of OHTED and OHTGS, called OHTED2 and OHTGS2 respectively, are proposed for reduced estimation bias. On real benchmark datasets, OHTED2 and OHTGS2 are found to exhibit relatively good generalization performance. In addition, OHTGS2 is found to be obtain a sparse representation of a target function in terms of the basis functions.

This paper introduces a tensorial representation of multiple cameras with arbitrary curvilinear motions. It enables us to define a multilinear relationship among image points derived from non-rigid object motions viewed from multiple cameras with arbitrary curvilinear motions. We show the new multilinear relationship is useful for generating images and reconstructing 3D non-rigid object motions viewed from cameras with arbitrary curvilinear motions. The method is tested in real image sequences.

The tag collection algorithm in ISO/IEC 18000-7 has difficulty in collecting data from massive numbers of active RFID tags in a timely manner, so it should be improved to allow successful application in a wide variety of industrial fields. We propose two novel methods, a reduced-message method to improve the performance of data-tag collection and an efficient-sleep method to improve the performance of ID-tag collection. The reduced-message method decreases the slot size for a tag response by reducing the response size from the tag and reduces the number of commands issued from the reader. The efficient-sleep method utilizes redundant empty slots within the frame period to transmit sleep commands to the tags collected previously. We evaluated the performance improvement of tag collection by the proposed methods experimentally using an active RFID reader and 60 tags that we prepared for this study. The experimental results showed that the reduced-message method and the efficient-sleep method decreased the average tag collection time by 16.7% for data-tag collection and 9.3% for ID-tag collection compared with the standard tag collection. We also developed a simulation model for the active RFID system, reflecting the capture effect in wireless communication, and performed simulations to evaluate the proposed methods with a massive number of tags. The simulation results with up to 300 tags confirmed that the proposed methods could improve the tag collection performance, confirming the experimental results, even with larger numbers of tags.

An algorithm for estimating sinusoidal parameters is presented. In this paper, it is assumed that an observed signal is a single sinusoidal signal contaminated by white Gaussian noise. Based on this assumption, the sinusoidal parameters can be found by minimizing a cost function using the mean squared error (MSE) between the observed signal and a sinusoidal signal with arbitrary sinusoidal parameters. Because the cost function is nonlinear and not convex, it has undesirable local minima. To solve the minimization problem, we propose to use the roots of an algebraic equation. The algebraic equation is derived straightforwardly from the cost function. We show that the global solution is formulated by using the roots of the algebraic equation.

A perfect sequence is a sequence having an impulsive autocorrelation function. Perfect sequences have several applications, such as CDMA, ultrasonic imaging, and position control. A parameterization of a perfect sequence is presented in the present paper. We treat a set of perfect sequences as a zero set of quadratic equations and prove a decomposition law of perfect sequences. The decomposition law reduces the problem of the parameterization of perfect sequences to the problem of the parameterization of quasi-perfect sequences and the parameterization of perfect sequences of short length. The parameterization of perfect sequences for simple cases and quasi-perfect sequences should be helpful in obtaining a parameterization of perfect sequences of arbitrary length. According to our theorem, perfect sequences can be represented by a sum of trigonometric functions.