Because of the large scale of wireless sensor networks, the configuration needs to be done autonomously. In this paper, we present Scalable Data Collection (SDC) protocol, a tree-based protocol for collecting data over multi-hop, wireless sensor networks. The design of the protocol aims to satisfy the requirements of sensor networks that every sensor transmits sensed data to a sink node periodically or spontaneously. The sink nodes construct the tree by broadcasting a solicit packet to discover the child nodes. The sensor receiving this packet decides on an appropriate parent to which it will attach, it then broadcasts the same packet to discover its child nodes. Through this process, the tree is created autonomously without any flooding of the routing packets. SDC avoids periodic updating of routing information but the tree need to be reconstructed upon node failures or adding of new nodes. The states required on each sensor are constant and independent of network size, therefore SDC scales better than the existing protocols. Moreover, each sensor can make forwarding decisions regardless of the knowledge on geographical information. We evaluated the performance of SDC by using the ns-2 simulator and comparing with Directed Diffusion, DSR, AODV, and OLSR. The simulation results demonstrate that SDC achieves much higher delivery ratio, shorter delay, as well as high scalability in various scenarios.

An embodied interactive agent has a virtual body that is generally drawn by CG animation. We intuitively assume that the agent's body primarily expresses non-verbal messages, or symbolizes its social characteristics through its appearance. However, we have not objectively elucidated the expressive competence of an agent's body beyond the conclusions of our empirical and subjective intuition. Therefore, it is necessary to explore scientifically how users regard the functional competence of an agent's embodiment. Do users attribute the intelligence of an agent to its virtual body? We investigated how users physically interact with an agent which is merely a virtual entity drawn on the display by CG, through "showing" something to the eyes of the agent, "listening" to something from the mouth of the agent, and "speaking" something into the ears of the agent. However, such interaction does not necessarily attribute the intellectual processing function to the agent, and this issue is explored through two psychological experiments.

Volume Graphics Clusters (VG Clusters) have proven to be efficient in a wide range of visualization applications and have also shown promise in some other applications where the image composition device could be fully utilized. The main differentiating feature from other graphics clusters is a specialized image composition device, commercially available as the MPC Image Compositor, which enables the building of do-it-yourself VG Clusters. Although this device is highly scalable, the unidirectional composition flow limits the data subdivision to the quantity of physically available rendering nodes. In addition, the limited buffer memory limits the maximum capable image composition size, therefore limiting its use in large-scale data visualization and high-resolution visualization. To overcome these limitations, we propose and evaluate an image composition mechanism in which additional hardware is used for assisting the image composition process. Because of the synergistic use of two distinct image composition hardware devices we named it "Hybrid Image Composition". Some encouraging results were obtained showing the effectiveness of this solution in improving the VG Cluster 's potential. A low-cost parallel port based hardware barrier is also presented as an efficient method for further enhancing this kind of small-scale VG Cluster. Moreover, this solution has proven to be especially useful in clusters built using low-speed networks, such as Fast Ethernet, which are still in common use.

This letter proposes a modified orthogonal frequency division multiplexing (OFDM) system with low peak-to-average power ratio (PAPR) and reduced complexity. To do this, OFDM system exploits a frequency diversity equipped with a simple symbol repetition. From the presented results, we can see that the investigated OFDM system with one transmit antenna gives the same diversity gain to two-branch transmit diversity and can be implemented with reduced transmitter complexity and low peak power at the cost of decoding delay.

To understand the brightness uniformity for the driver of the LED array display, automatic electronic measurement equipment and its testing scheme will be proposed in this paper. The driving performance and dynamic characteristics will be investigated by using the proposed current-based bias voltage regulator. A complete testing procedure will be provided to assess the performance for the LED array display driver.

In this paper, Information-Spectrum characterization is derived for the reliable transmission of general correlated sources over the general multiple-access channels. We consider the necessary and sufficient conditions for the transmission of general correlated sources over the general multiple-access channels by using Information-Spectrum methods which are introduced by Han and Verdu.

The gamma correction for the CMOS image sensors are implemented by the method of piecewise linear approximation through a look-up table. In this paper, we propose a quantitative criterion to select the piece linear segment with the same output interval for the reduction of the error between the value of piece linear approximation and gamma correction. After the gamma correction is implemented, the average error occurred by implementing color interpolation in each segment is a basis for the optimum selecting of the piece linear segment of the gamma correction for the CMOS image sensors.

The problem of multi-body motion segmentation is important in many computer vision applications. In this paper, we propose a novel algorithm called fuzzy k-subspace clustering for robust segmentation. The proposed method exploits the property that under orthographic camera model the tracked feature points of moving objects reside in multiple subspaces. We compute a partition of feature points into corresponding subspace clusters. First, we find a "soft partition" of feature points based on fuzzy k-subspace algorithm. The proposed fuzzy k-subspace algorithm iteratively minimizes the objective function using Weighted Singular Value Decomposition. Then the points with high partition confidence are gathered to form the subspace bases and the remaining points are classified using their distance to the bases. The proposed method can handle the case of missing data naturally, meaning that the feature points do not have to be visible throughout the sequence. The method is robust to noise and insensitive to initialization. Extensive experiments on synthetic and real data show the effectiveness of the proposed fuzzy k-subspace clustering algorithm.

Given a set of n stations, the initialization problem is to assign each station a unique identification number, from 1 to n. In the single-hop wireless Networks with collision detection, Nakano and Olariu proposed an algorithm to build a partition tree and solve the problem. In this paper, we shall classify the partition tree into four parts. By reviewing the classification, we find that three ideas can improve the algorithm. We show that it needs 2.88n time slots for solving the problem containing n stations. After applying our three ideas, the number of time slots will be improved to 2.46n.

Access selection in future multiple radio access environments is considered in this paper from a new perspective, that of the consumer. A model is proposed for the automatic acquisition of user preferences to assist in access selection decision making. The proposed approach uses a two-level Bayesian C-Metanetwork that models individual user preferences in terms of affordable cost, acceptable level of quality of service and reputation of the access networks. User preferences under different contexts, such as leisure and business, are also considered. The model also adapts to the change of user preferences over time. A simulator has been developed to evaluate the proposed model and the simulation results are promising in terms of the proportion of correct preference predictions after a small number of training samples.

In this paper, we present a game of dice that combines multi-party communication with a tangible interface. The game has been used as a testbed to study typical conversational behavior patterns in interactions between human users and synthetic agents. In particular, we were interested in the question to what extent the interaction with the agent can be considered as natural. As an evaluation criterion, we propose to investigate whether the communicative behaviors of humans differ when conversing with an agent as opposed to conversing with other humans.

Recently, Juang proposed an efficient password authenticated key agreement scheme using smart cards for the multi-server architecture. Juang's scheme was intended to provide mutual authentication and session key agreement. Herein, we show that Juang's scheme is vulnerable to a privileged insider's attack and is not easily reparable. Furthermore, it does not provide forward secrecy and the user eviction mechanism.

This paper presents a novel method of structure selection and identification for Hammerstein type nonlinear systems. An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The connection coefficients of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. The adjusting parameters for the ACF model structure, i.e. the number and widths of the subdomains and the shape of the ACF are properly selected by using a genetic algorithm, in which the Akaike information criterion is utilized as the fitness value function. The effectiveness of the proposed method is confirmed through numerical experiments.

Multilayered filters with a dielectric distribution along their thickness forming a one-dimensional quasi-fractal structure are theoretically analyzed, focusing on exposing their resonant properties in order to understand a dielectric Menger's sponge resonator [4],[5]. "Quasi-fractal" refers to the triadic Cantor set with finite generation. First, a novel calculation method that has the ability to deal with filters with fine fractal structures is derived. This method takes advantage of Clifford algebra based on the theory of thin-film optics. The method is then applied to classify resonant modes and, especially, to investigate quality factors for them in terms of the following design parameters: a dielectric constant, a loss tangent, and a stage number. The latter determines fractal structure. Finally, behavior of the filters with perfect fractal structure is considered. A crucial finding is that the high quality factor of the modes is not due to the complete self-similarity, but rather to the breaking of such a fractal symmetry.

In deep submicron designs, the interconnect wires play a major role in the timing behavior of logic gates. The effective capacitance Ceff concept is usually used to calculate the delay of gate with interconnect loads. In this paper, we present a new method of Integration Approximation to calculate Ceff. In this new method, the complicated nonlinear gate output is assumed as a piecewise linear (PWL) waveform. A new model is then derived to compute the value of Ceff. The introduction of Integration Approximation results in Ceff being insensitive to output waveform shape. Therefore, the new method can be applied to various output waveforms of CMOS gates with RC-π loads. Experimental results show a significant improvement in accuracy.

This paper presents designs and performances of 76 GHz band alternating-phase fed single-layer slotted waveguide arrays. Two kinds of design, that is, uniform aperture illumination for maximum gain and Taylor distribution for sidelobe suppression of -25 dB, are conducted. High gain and high efficiency performance of 34.8 dBi with 57% is achieved for the former, while satisfactory sidelobe suppression of -20 dB in the H-plane and -23 dB in the E-plane with high efficiency is confirmed for the latter. The simple structure dispensing with electrical contact between the slotted plate and the groove feed structure is the key advantage of alternating-phase fed arrays and the slotted plate is just tacked on the feed structure with screws at the periphery. High gain and high efficiency performances predicted theoretically as well as design flexibility of the alternating-phase fed array are demonstrated in the millimeter wave frequency.

The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.

The requirement for achieving the smoothness of mode transit between track seeking and track following has become a challenging issue for hard disk drive (HDD) motion control. In this paper, a random-optimization-based self-organizing neuro-fuzzy controller (RO-SNFC) for HDD servo system is presented. The proposed controller is composed of three designs. First, the concept of pseudo-errors is used to detect the potential dynamics of the unknown plant for rule extraction. Second, the propensity of the obtained pseudo-errors is specified by a cubic regression model, with which the cluster-based self-organization is implemented to generate clusters. The generated clusters are regarded as the antecedents of the T-S fuzzy "IF-THEN" rules. The initial knowledge base of the RO-SNFC is established. Third, the well-known random optimization (RO) algorithm is used to evolve the controller parameters for control efficiency and robustness. In this paper, a motion reference curve for HDD read/write head is employed. With the reference velocity curve, the RO-SNFC is used to achieve the optimal positioning control. From the illustrations, the feasibility of the proposed approach for HDD servo systems is demonstrated. Through the comparison to other approaches, the excellent performance by the proposed approach in access time and positioning smoothness is observed.

In this paper we present a 3D adaptive nonlinear filter, namely the 3D adaptive CPWLN, based on the Canonical Piece Wise-Linear Network with an LMS L-filter type of adaptation. This filter is used to equalize nonlinear channel effect and remove impulsive/or mixed impulsive and Additive White Gaussian noise from video sequences. First, motion compensation is performed by a robust estimator. Then, a 3-D CPWLN LMS L-filter is applied. The overall combination is able to adequately remove undesired effects of communication channel and noise. Computer simulations on real-world image sequences are included. The algorithm yields promising results in terms of both objective and subjective quality of the restored sequence.

This paper aims at challenging Bernstein's problem called the "Degrees-of-Freedom problem," which remains unsolved from both the physiological and robotics viewpoints. More than a half century ago A.N. Bernstein observed that "dexterity" residing in human limb motion emerges from accumulated involvement of multi-joint movements in surplus DOF. It is also said in robotics that redundancy of DOFs in robot mechanisms may contribute to enhancement of dexterity and versatility. However, kinematic redundancy incurs a problem of ill-posedness of inverse kinematics from task-description space to joint space. In the history of robotics research such ill-posedness problem of inverse-kinematics has not yet been attacked directly but circumvented by introducing an artificial performance index and determining uniquely an inverse kinematics solution by minimizing it. Instead of it, this paper introduces two novel concepts named "stability on a manifold" and "transferability to a submanifold" in treating the case of human multi-joint movements of reaching and shows that a sensory feedback from task space to joint space together with a set of adequate dampings enables any solution to the overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that, without considering any type of inverse kinematics, the reaching task can be accomplished by a sensory feedback with adequate choice of a stiffness parameter and damping coefficients. It is also shown that these novel concepts can cope with annoying characteristics called "variability" of redundant joint motions seen typically in human skilled reaching. Finally, it is pointed out that the proposed control signals can be generated in a feedforward manner in case of human limb movements by referring to mechano-chemical characteristics of activation of muscles. Based on this observation, generation of human skilled movements of reaching can be interpreted in terms of the proposed "Virtual-Spring" hypothesis instead of the traditional "Equilibrium-Point" hypothesis.