Using the transient current switch circuit in parallel with the energizing switching contacts for timely control of breaking operation, the increase of contact voltage is suppressed at the last stage of the breaking of electric contacts. Breaking contact voltage Vc and current Ic of electromagnetic relays with Ag contacting electrodes were measured with 12.5-50 V and 0.1-20 A for two hinge springs (Spring constants; 2 N/mm and 0.2 N/mm). The current-decreasing process was clearly measured at the melting voltage Um. After Vc=Um, the breaking time of contact current did not depend on mechanical motion controlled by the two hinge springs and energizing power-supply voltage, but depended on the contact current. The residue of melt electrode was observed optically as a white fusion spot, with radius depending on the energizing current.

This letter presents recursive frequency offset estimation for MIMO (Multiple Input Multiple Output) system in flat-fading channels. With the recursive estimation, the frequency offset range in MIMO system can be extended compared with normal estimation. Simulation results show that the recursive frequency offset estimation is valid for large frequency offset.

A group signature scheme introduced by Chaum and Van Heyst allows a group member to sign messages anonymously on behalf of the group. However, in the case of a dispute, the identity of a signer of a group signature can be revealed only by a privileged entity, called a group manager. The group signature scheme has mainly been studied from the viewpoint of computational security setting so far. The main contribution of this paper is to study group signature schemes in unconditional security. More specifically, we newly introduce strong security notions of unconditionally secure group signatures (USGS for short) based on the idea of those of computationally secure group signatures proposed by Bellare, Micciancio and Warinschi. We also provide a generic method to construct USGS that is provably secure in our security definition. More precisely, we construct USGS by combining an encryption scheme with a signature, and show that the constructed scheme is unconditionally secure if the encryption and the signature used in the construction are unconditionally secure. Finally, we provide an instantiation of the one-time secure group signature scheme based on the generic construction.

In OFDM systems, the estimation/correction of carrier frequency offset (CFO) is crucial to maintain orthogonality among subcarriers. However, the CFO estimation suffers from DC offset (DCO) generated in low-cost direct-conversion receivers (DCRs). More seriously, in practice, DCO is time-varying due to the automatic gain control. In this paper, a novel CFO estimator in the presence of time-varying DCO is proposed. It is shown the residual DCO after high-pass filtering varies in a linear fashion. Based on this observation and the periodicity of the training sequence, we derive a CFO estimator independent of DCO. Also, the residual DCO can be estimated, using the obtained CFO. The validity of the proposed estimation method is demonstrated by simulations.

In this study we introduce AdjScales, a method for scaling similar adjectives by their strength. It combines existing Web-based computational linguistic techniques in order to automatically differentiate between similar adjectives that describe the same property by strength. Though this kind of information is rarely present in most of the lexical resources and dictionaries, it may be useful for language learners that try to distinguish between similar words. Additionally, learners might gain from a simple visualization of these differences using unidimensional scales. The method is evaluated by comparison with annotation on a subset of adjectives from WordNet by four native English speakers. It is also compared against two non-native speakers of English. The collected annotation is an interesting resource in its own right. This work is a first step toward automatic differentiation of meaning between similar words for language learners. AdjScales can be useful for lexical resource enhancement.

The purpose of this paper is to study sender authenticated key agreements by a third party, which uses the received parameters to verify the fact that a sender of a message knows his long-term private key. In particular, we propose a standard model for the protocol among three entities for the first time. The security of this protocol depends on the difficulty of solving two new problems related to one-way isomorphisms and the decision co-bilinear Diffie-Hellman problem on multiplicative cyclic groups. It is the first time that the security of a key agreement has been formally proven by using negligible probability. We believe that our contribution gives many applications in the cryptographic community.

In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.

When a store sells items to customers, the store wishes to decide the prices of 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 the 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 consider the line highway problem (in which each customer is interested in an interval on the line of the items) and the cycle highway problem (in which each customer is interested in an interval on the cycle of the items), and show approximation algorithms for the line highway problem and the cycle highway problem in which the smallest valuation is s and the largest valuation is (this is called an [s,]-valuation setting) or all valuations are identical (this is called a single valuation setting).

In multiuser MIMO-BC (Multiple-Input Multiple-Output Broadcasting) systems, user selection is important to achieve multiuser diversity. The optimal user selection algorithm is to try all the combinations of users to find the user group that can achieve the multiuser diversity. Unfortunately, the high calculation cost of the optimal algorithm prevents its implementation. Thus, instead of the optimal algorithm, some suboptimal user selection algorithms were proposed based on semiorthogonality of user channel vectors. The purpose of this paper is to achieve multiuser diversity with a small amount of calculation. For this purpose, we propose a user selection algorithm that can improve the orthogonality of a selected user group. We also apply a channel prediction technique to a MIMO-BC system to get more accurate channel information at the transmitter. Simulation results show that the channel prediction can improve the accuracy of channel information for user selections, and the proposed user selection algorithm achieves higher sum rate capacity than the SUS (Semiorthogonal User Selection) algorithm. Also we discuss the setting of the algorithm threshold. As the result of a discussion on the calculation complexity, which uses the number of complex multiplications as the parameter, the proposed algorithm is shown to have a calculation complexity almost equal to that of the SUS algorithm, and they are much lower than that of the optimal user selection algorithm.

Shamir's (k,n)-threshold secret sharing scheme (threshold scheme) has two problems: a heavy computational cost is required to make shares and recover the secret, and a large storage capacity is needed to retain all the shares. As a solution to the heavy computational cost problem, several fast threshold schemes have been proposed. On the other hand, threshold ramp secret sharing schemes (ramp scheme) have been proposed in order to reduce each bit-size of shares in Shamir's scheme. However, there is no fast ramp scheme which has both low computational cost and low storage requirements. This paper proposes a new (k,L,n)-threshold ramp secret sharing scheme which uses just EXCLUSIVE-OR(XOR) operations to make shares and recover the secret at a low computational cost. Moreover, by proving that the fast (k,n)-threshold scheme in conjunction with a method to reduce the number of random numbers is an ideal secret sharing scheme, we show that our fast ramp scheme is able to reduce each bit-size of shares by allowing some degradation of security similar to the existing ramp schemes based on Shamir's threshold scheme.

This paper proposes a new sieving algorithm that employs a bucket sort as a part of a factoring algorithm such as the number field sieve. The sieving step requires an enormous number of memory updates; however, these updates usually cause cache hit misses. The proposed algorithm significantly reduces the number of cache hit misses when the size of the sieving region is roughly less than the square of the cache size, and the memory updates are several times faster than the straightforward implementation according to the PC experiments.

It has been proved that wireless network coding can increase the throughput of multi-access system [2] and bi-directional system [5] by taking the advantage of the broadcast nature of electromagnetic waves. In this paper, we introduce the wireless network coding to cooperative multicast system. We establish a basic 2-source and 2-destination cooperative system model with arbitrary number of relays (2-N-2 system). Then two regenerative network coding (RNC) protocols are designed to execute the basic idea of network coding in complex field (RCNC) and Galois field (RGNC) respectively. We illuminate how network coding can enhance the throughput distinctly in cooperative multicast system. Power allocation schemes as well as precoder design are also carefully studied to improve the system performance in terms of system frame error probability (SFEP).

A critical problem after a natural/manmade disaster is to provide immediate post-disaster communication links between the disaster victims and some overlay networks. This paper proposes a novel scheme that uses the surviving Mobile handSets (MS) as sensing nodes to form an auto-configured Hierarchical Cognitive Radio Network (H-CRN). The implementation of this H-CRN is explained through detailed problem scenario statement and step-by-step implementation of automatic identification of emergency situation by the MS nodes. An overview of the cross-layer framework used by the MS nodes is also presented. This novel scheme is tested through some hypothesis along with probability calculations for successful identification of emergency situation, formation of ad hoc group and Emergency Beacon Message (EBM) transmission.

Particle filter has attracted increasing attention from researchers of object tracking due to its promising property of handling nonlinear and non-Gaussian systems. In this paper, we mainly explore the problem of precisely estimating observation likelihoods of particles in the joint feature-spatial space. For this purpose, a mixture Gaussian kernel function based similarity is presented to evaluate the discrepancy between the target region and the particle region. Such a similarity can be interpreted as the expectation of the spatial weighted feature distribution over the target region. To adapt outburst of object motion, we also present a method to appropriately adjust state transition model by utilizing the priors of motion speed and object size. In comparison with the standard particle filter tracker, our tracking algorithm shows the better performance on challenging video sequences.

There are two main methods for pandemic simulations: the SEIR model and the MAS model. The SEIR model can deal with simulations quickly for many homogeneous populations with simple ordinary differential equations; however, the model cannot accommodate many detailed conditions. The MAS model, the multi-agent simulation, can deal with detailed simulations under the many kinds of initial and boundary conditions with simple social network models. However, the computing cost will grow exponentially as the population size becomes larger. Thus, simulations in the large-scale model would hardly be realized unless supercomputers are available. By combining these two methods, we may perform the pandemic simulations in the large-scale model with lower costs. That is, the MAS model is used in the early stage of a pandemic simulation to determine the appropriate parameters to be used in the SEIR model. With these obtained parameters, the SEIR model may then be used. To investigate the validity of this combined method, we first compare the simulation results between the SEIR model and the MAS model. Simulation results of the MAS model and the SEIR model that uses the parameters obtained by the MAS model simulation are found to be close to each other.

In this letter, we analyze the convergence speed of layered decoding of block-type low-density parity-check codes and verify that the layered decoding gives faster convergence speed than the sequential decoding with randomly selected check node subsets. Also, it is shown that using more subsets than the maximum variable node degree does not improve the convergence speed.

The spike timings of neurons are irregular and are considered to be a one-dimensional point process. The Bayesian approach is generally used to estimate the time-dependent firing rate function from sequences of spike timings. It can also be used to estimate the firing rate from only a single sequence of spikes. However, the rate function has too many degrees of freedom in general, so approximation techniques are often used to carry out the Bayesian estimation. We applied the transfer matrix method, which efficiently computes the exact marginal distribution, to the estimation of the firing rate and developed an algorithm that enables the exact results to be obtained for the Bayesian framework. Using this estimation method, we investigated how the mismatch of the prior hyperparameter value affects the marginal distribution and the firing rate estimation.

This paper presents a grouped scan slice encoding technique using scan slice repetition to simultaneously reduce test data volume and test application time. Using this method, many scan slices that would be incompatible with the conventional selective scan slice method can be encoded as compatible scan slices. Experiments were performed with ISCAS'89 and ITC'99 benchmark circuits, and results show the effectiveness of the proposed method.

A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.

The situations where several population parameters need to be estimated simultaneously arise frequently in wide areas of applications, including reliability modeling, survival analysis and biological study. In this paper, we propose Bayesian methods of estimation of the ordered parameters of the two exponential populations, which incorporate the prior information about the simple order restriction, but sometimes breaks the order restriction. A simulation study shows that the proposed estimators are more efficient (in terms of mean square errors) than the isotonic regression of the maximum likelihood estimators with equal weights. An illustrative example is finally presented.