In this article, we introduce a new concept for the future information environment, called an "ambient information environment (AmIE)." We first explain it, especially emphasizing the difference from the existing ubiquitous information environment (UbIE), which is an interaction between users and environments. Then, we focus on an ambient networking environment (AmNE) which supports the AmIE as a networking infrastructure. Our approach of a biologically inspired framework is next described in order to demonstrate why such an approach is necessary in the AmIE. Finally, we show some example for building the AmNE.

For variation-aware capacitance extraction, stochastic collocation method (SCM) based on Homogeneous Chaos expansion has the exponential convergence rate for Gaussian geometric variations, and is considered as the optimal solution using a quadratic model to model the parasitic capacitances. However, when geometric variations are measured from the real test chip, they are not necessarily Gaussian, which will significantly compromise the exponential convergence property of SCM. In order to pursue the exponential convergence, in this paper, a generalized stochastic collocation method (gSCM) based on generalized Polynomial Chaos (gPC) expansion and generalized Sparse Grid quadrature is proposed for variation-aware capacitance extraction that further considers the arbitrary random probability of real geometric variations. Additionally, a recycling technique based on Minimum Spanning Tree (MST) structure is proposed to reduce the computation cost at each collocation point, for not only "recycling" the initial value, but also "recycling" the preconditioning matrix. The exponential convergence of the proposed gSCM is clearly shown in the numerical results for the geometric variations with arbitrary random probability.

Nonnegative matrix factorization (NMF) and its extensions such as Nonnegative Tensor Factorization (NTF) have become prominent techniques for blind sources separation (BSS), analysis of image databases, data mining and other information retrieval and clustering applications. In this paper we propose a family of efficient algorithms for NMF/NTF, as well as sparse nonnegative coding and representation, that has many potential applications in computational neuroscience, multi-sensory processing, compressed sensing and multidimensional data analysis. We have developed a class of optimized local algorithms which are referred to as Hierarchical Alternating Least Squares (HALS) algorithms. For these purposes, we have performed sequential constrained minimization on a set of squared Euclidean distances. We then extend this approach to robust cost functions using the alpha and beta divergences and derive flexible update rules. Our algorithms are locally stable and work well for NMF-based blind source separation (BSS) not only for the over-determined case but also for an under-determined (over-complete) case (i.e., for a system which has less sensors than sources) if data are sufficiently sparse. The NMF learning rules are extended and generalized for N-th order nonnegative tensor factorization (NTF). Moreover, these algorithms can be tuned to different noise statistics by adjusting a single parameter. Extensive experimental results confirm the accuracy and computational performance of the developed algorithms, especially, with usage of multi-layer hierarchical NMF approach [3].

This paper proposes a pilot-based channel state information (CSI) feedback from a terminal to a base station (BS), considering the terminal's co-channel interference in a time-division duplex/multi-input multi-output system. In the proposed method, the terminal determines a precoding matrix according to the terminal's co-channel interference characteristics and transmits the precoded pilot signals on uplink. Using the responses of the precoded pilot signals, the BS determines appropriate weight vectors for downlink transmit beams considering the terminal's interference characteristics. Furthermore, the BS can predict the terminal's output signal-to-interference-plus-noise power ratio (SINR) for the downlink data stream. Numerical results show that the BS can achieve efficient transmission and accurate SINR prediction using the proposed CSI feedback.

Optical burst switching (OBS) is a promising approach for the realization of future flexible high-speed optical networks. In particular, a multicast forwarding method for optical bursts is important if an efficient high-speed grid computing network is to be realized. In OBS networks, the number of burst replicas generated at each node is strongly restricted due to optical power impairment of multicast bursts. Moreover, unrestricted replication of multicast bursts at each OBS node may not be advantageous because an increase in the number of multicast bursts within the network causes more frequent deflection forwarding of both multicast and unicast bursts. This paper proposes an efficient hop-by-hop multicast forwarding method for optical bursts, where idle output ports are selected based on scores simply calculated using a routing table that each OBS node holds. This method can mitigate increases in loss rate and transfer delay of multicast bursts, even if the number of burst replicas generated at each OBS node is strongly restricted. Moreover, this method can efficiently mitigate an increase in the number of multicast bursts within the network by avoiding unnecessary replication of multicast bursts at each OBS node. Simulation results show that the proposed method can actually mitigate degradation of the loss rate and transfer delay for multicast bursts under the restricted number of burst replicas at each OBS node. Moreover, when the arrival rate of multicast bursts is large relative to that of unicast bursts, the proposed method is able to improve the loss rates of both multicast and unicast bursts by switching the forwarding method for the multicast bursts to the simple unicast forwarding method without burst replication.

The medical care day by day and more and more is associated with and reliant upon concepts and advances of electronics and electromagnetics. Numerous medical devices are implanted in the body for medical use. Tissue implanted devices are of great interest for wireless medical applications due to the promising of different clinical usage to promote a patient independence. It can be used in hospitals, health care facilities and home to transmit patient measurement data, such as pulse and respiration rates to a nearby receiver, permitting greater patient mobility and increased comfort. As this service permits remote monitoring of several patients simultaneously it could also potentially decrease health care costs. Advancement in radio frequency communications and miniaturization of bioelectronics are supporting medical implant applications. A central component of wireless implanted device is an antenna and there are several issues to consider when designing an in-body antenna, including power consumption, size, frequency, biocompatibility and the unique RF transmission challenges posed by the human body. The radiation characteristics of such devices are important in terms of both safety and performance. The implanted antenna and human body as a medium for wireless communication are discussed over Medical Implant Communications Service (MICS) band in the frequency range of 402-405 MHz.

When a store sells items to customers, the store wishes to determine the prices of the items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy those items, and also assume that each item i ∈ V has the production cost di and each customer ej ∈ E has the valuation vj on the bundle ej ⊆ V of items. When the store sells an item i ∈ V at the price ri, the profit for the item i is pi=ri-di. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that pi ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of "loss-leader," and showed that the seller can get more total profit in the case that pi < 0 is allowed than in the case that pi < 0 is not allowed. In this paper, we derive approximation preserving reductions among several item pricing problems and show that all of them have algorithms with good approximation ratio.

We propose a new filter method for feature selection for SELDI-TOF mass spectrum datasets. In the method, a new relevance index was defined to represent the goodness of a feature by considering the distribution of samples based on the counts. The relevance index can be used to obtain the feature sets for classification. Our method can be applied to mass spectrum datasets with extremely high dimensions and process the clinical datasets with practical sizes in acceptable calculation time since it is based on simple counting of samples. The new method was applied to the three public mass spectrum datasets and showed better or comparable results than conventional filter methods.

In this letter, we first investigate the bias of Doppler shift estimator based on autocorrelation function (ACF). Then we derive a signal-to-noise ratio (SNR) independent condition for Doppler shift estimation and achieve this condition by a adaptive process. Moreover, we present theoretical analysis about the convergency of our adaptive Doppler shift estimator, and derive a close-form expression for its mean square error (MSE). We verify the proposed estimator by computer simulation, the results of which are in agreement with the analysis, i.e., the proposed method achieves a good SNR-independent performance in a wide range of velocities and SNRs.

In this letter, a novel power allocation scheme is proposed to improve the outage performance of an amplify-and-forward (AF) cooperative communication network with multiple potential relays under the assumption that only mean channel gains are available at the transmitters. In this scheme, power allocation is studied jointly with a relay selection algorithm which has low computational complexity. Simulation results demonstrate the performance improvement of the proposed scheme in terms of outage behavior.

In this letter, we enumerate the number of cyclically inequivalent M-ary Sidel'nikov sequences of given length as well as the number of distinct autocorrelation distributions that they can have, while we change the primitive element for generating the sequence.

This paper presents the formulation for the evaluation of external coupling in the alternating-phase feed single-layer slotted waveguide array antenna with baffles by using the Spectrum of Two-Dimensional Solutions (S2DS) method. A one-dimensional slot array is extracted from the array by assuming the periodicity in transversal direction and introducing the perfect electric conductors in the external region. The uniform excitation over the finite array is synthesized iteratively to demonstrate the fast and accurate results by S2DS. A unit design model with the baffles is introduced to determine the initial parameters of the slot pair which accelerate the iteration. Experiment at 25.3 GHz demonstrates good uniformity of the aperture field distribution as well as the effects of the baffles. The directivity is 32.7 dB which corresponds to the aperture efficiency 90.5% and the reflection is below -15.0 dB over 1.3 GHz.

In this paper, we present the time-memory-data (TMD) trade-off attack on stream ciphers filter function generators and filter cominers based on Maiorana-McFarland functions. This can be considered as a generalization of the time-memory-data trade-off attack of Mihaljevic and Imai on Toyocrypt. First, we substitute the filter function in Toyocrypt (which has the same size as the LFSR) with a general Maiorana-McFarland function. This allows us to apply the attack to a wider class of stream ciphers. Second, we highlight how the choice of different Maiorana-McFarland functions can affect the effectiveness of our attack. Third, we show that the attack can be modified to apply on filter functions which are smaller than the LFSR and on filter-combiner stream ciphers. This allows us to cryptanalyze other configurations commonly found in practice. Finally, filter functions with vector output are sometimes used in stream ciphers to improve the throughput. Therefore the case when the Maiorana-McFarland functions have vector output is investigated. We found that the extra speed comes at the price of additional weaknesses which make the attacks easier.

In a seminal paper of identity based encryption (IBE), Boneh and Franklin [6] mentioned an interesting transform from an IBE scheme to a signature scheme, which was observed by Moni Naor. In this paper, we give formal security treatments for this transform and discover several implications and separations among security notions of IBE and transformed signature. For example, we show for such a successful transform, one-wayness of IBE is an essential condition. Additionally, we give a sufficient and necessary condition for converting a semantically secure IBE scheme into an existentially unforgeable signature scheme. Our results help establish strategies on design and automatic security proof of signature schemes from (possibly weak) IBE schemes. We also show some separation results which strongly support that one-wayness, rather than semantic security, of IBE captures an essential condition to achieve secure signature.

This paper presents an easy and efficient modification of simplified 2D ray-launching method, by approximately including multiple reflection effect inside walls for indoor environment. In order to precisely carry out the ray-launching procedure inside lossy wall, a simple modification using a true real refraction angle is first introduced, instead of complex one. Furthermore, an efficient approximation is carried out to collect the internal multiple reflected rays into the primary one. We here call it collective ray approach. Consequently, it is confirmed from the detailed considerations that the present ray representations obtained by introducing the real refraction angle are well suitable for indoor propagation analysis, and in particular the collective ray solution can be utilized confidently even when the internal reflections strongly contribute to the propagation feature of the considered indoor environment.

In the context of multiple constant multiplication (MCM) design, we propose a novel common sub-expression elimination (CSE) algorithm that models the optimal synthesis of coefficients into a 0-1 mixed-integer linear programming (MILP) problem with a user-defined generic logic depth constraint. We also propose an efficient solution space, which combines all minimal signed digit (MSD) representations and the shifted sum (difference) of coefficients. In the examples we demonstrate, the combination of the proposed algorithm and solution space gives a better solution comparing to existing algorithms.

Proofs written in algebraic specification languages are called proof scores. The proof score approach to design verification is attractive because it provides a flexible way to prove that designs for systems satisfy properties. Thus far, however, the approach has focused on safety properties. In this paper, we describe a way to verify that designs for systems satisfy liveness properties with the approach. A mutual exclusion protocol using a queue is used as an example. We describe the design verification and explain how it is verified that the protocol satisfies the lockout freedom property.

This paper proposes a novel algorithm for image feature extraction-the dual two-dimensional fuzzy class preserving projections ((2D)2FCPP). The main advantages of (2D)2FCPP over two-dimensional locality preserving projections (2DLPP) are: (1) utilizing the fuzzy assignation mechanisms to construct the weight matrix, which can improve the classification results; (2) incorporating 2DLPP and alternative 2DLPP to get a more efficient dimensionality reduction method-(2D)2LPP.

In real-time data-dominated communication and multimedia processing applications, a multi-layer memory hierarchy is typically used to enhance the system performance and also to reduce the energy consumption. Savings of dynamic energy can be obtained by accessing frequently used data from smaller on-chip memories rather than from large background memories. This paper focuses on the reduction of the dynamic energy consumption in the memory subsystem of multidimensional signal processing systems, starting from the high-level algorithmic specification of the application. The paper presents a formal model which identifies those parts of arrays more intensely accessed, taking also into account the relative lifetimes of the signals. Tested on a two-layer memory hierarchy, this model led to savings of dynamic energy from 40% to over 70% relative to the energy used in the case of flat memory designs.

In this paper, we propose an Adaptive Stochastic Collocation Method for block-based Statistical Static Timing Analysis (SSTA). A novel adaptive method is proposed to perform SSTA with delays of gates and interconnects modeled by quadratic polynomials based on Homogeneous Chaos expansion. In order to approximate the key atomic operator MAX in the full random space during timing analysis, the proposed method adaptively chooses the optimal algorithm from a set of stochastic collocation methods by considering different input conditions. Compared with the existing stochastic collocation methods, including the one using dimension reduction technique and the one using Sparse Grid technique, the proposed method has 10x improvements in the accuracy while using the same order of computation time. The proposed algorithm also shows great improvement in accuracy compared with a moment matching method. Compared with the 10,000 Monte Carlo simulations on ISCAS85 benchmark circuits, the results of the proposed method show less than 1% error in the mean and variance, and nearly 100x speeds up.