This paper presents implementation techniques of fast Ate pairing of embedding degree 12. In this case, we have no trouble in finding a prime order pairing friendly curve E such as the Barreto-Naehrig curve y2=x3+a, a∈Fp. For the curve, an isomorphic substitution from G2 ⊂ E(Fp12 into G'2 in subfield-twisted elliptic curve E'(Fp2) speeds up scalar multiplications over G2 and wipes out denominator calculations in Miller's algorithm. This paper mainly provides about 30% improvement of the Miller's algorithm calculation using proper subfield arithmetic operations. Moreover, we also provide the efficient parameter settings of the BN curves. When p is a 254-bit prime, the embedding degree is 12, and the processor is Pentium4 (3.6 GHz), it is shown that the proposed algorithm computes Ate pairing in 13.3 milli-seconds including final exponentiation.

A graph is an interval graph if and only if each vertex in the graph can be associated with an interval on the real line such that any two vertices are adjacent in the graph exactly when the corresponding intervals have a nonempty intersection. A number of interesting applications for interval graphs have been found in the literature. In order to find structural features common to structural data which can be represented by intervals, this paper proposes new interval graph structured patterns, called linear interval graph patterns, and a polynomial time algorithm for finding a minimally generalized linear interval graph pattern explaining a given finite set of interval graphs.

Eigen-beamforming (EB) transmission for multiple-input multiple-output (MIMO) systems is an effective means to maximize the receiver signal-to-noise ratio (SNR) in a noise-limited environment, but suffers a performance degradation when strong interference signals exist. In this letter, we propose an interference cancellation method for EB signals by constructing a new receive beamforming vector which jointly utilizes the EB matrix and minimum mean-square error (MMSE) spatial demultiplexing. The proposed method is shown to outperform the conventional EB receiver in the entire cell range, with a significant increase in the effective signal-to-interference plus noise ratio (SINR) near the cell boundary.

This paper analyzes the spurious sources in DDS synthesizers and deduces the simple model of DDS output signal. The method of feeding pseudo-random noise into the phase accumulator for spurious reduction is discussed. A new method for spurious reduction by compensating for DAC integer nonlinearity is proposed with two DACs and a power combiner. One DAC generates the error signal to compensate for the other DAC INL. The factor how the amplitude error and the phase error between the two combined signals affect the spurious level is also analyzed. The experiment shows that the spurious reduction can be improved by at least 18 dB, which proves the validity of the DAC INL compensation method for the spurious reduction.

Software model checking is typically applied to components of large systems. The assumption generation is the problem of finding the least restrictive environment in which the components satisfy a given safety property. There is an algorithm to compute the environment for properties given as a regular language. In this paper, we propose a general scheme for computing the assumption even for non-regular properties, and show the uniqueness of the least restrictive assumption for any class of languages. In general, dealing with non-regular languages may fall into undecidability of problems. We also show a method to compute assumptions based on visibly pushdown automata and their finite-state abstractions.

In equational theorem proving, convergent term rewriting systems play a crucial role. In order to compute convergent term rewriting systems, the standard completion procedure (KB) was proposed by Knuth and Bendix and has been improved in various ways. The multi-completion system MKB developed by Kurihara and Kondo accepts as input a set of reduction orders in addition to equations and efficiently simulates parallel processes each of which executes the KB procedure with one of the given orderings. Wehrman and Stump also developed a new variant of completion procedure, constraint-based completion, in which reduction orders need not be given by using automated modern termination checkers. As a result, the constraint-based procedures simulate the execution of parallel KB processes in a sequential way, but naive search algorithms sometimes cause serious inefficiency when the number of the potential reduction orders is large. In this paper, we present a new procedure, called a constraint-based multi-completion procedure MKBcs, by augmenting the constraint-based completion with the framework of the multi-completion for suppressing the combinatorial explosion by sharing inferences among the processes. The existing constraint-based system SLOTHROP, which basically employs the best-first search, is more efficient when its built-in heuristics for process selection are appropriate, but when they are not, our system is more efficient. Therefore, both systems have their role to play.

We identify a broadband equivalent circuit of an on-chip self-complementary antenna integrated with a µm-sized semiconductor mesa structure whose circuit elements can be interpreted by using closed-form analysis. Prior to the equivalent circuit analysis, an electromagnetic simulation is done to investigate frequency independency of the input impedance for the integrated self-complementary antenna in terahertz range.

A new class of sextic residue sequences of period prime p=4u2+27=6f+1 ≡ 3 ( mod 8) are presented. Their trace function representations are determined. And the exact value of the linear complexity is derived from the trace function representations. The result indicates that the new sextic sequences are quite good from the linear complexity viewpoint.

In this letter, we propose a novel singular value decomposition zero-forcing beamforming (SVD-ZFBF) relaying scheme in the multiuser downlink MIMO broadcasting channel with fixed relays. Based on the processing scheme, we apply SUS [5] to select users at the relay station (RS) and develop a joint power allocation strategy at the base station (BS) and RS. By increasing the power at RS or selecting active users to obtain more multiuser diversity, SVD-ZFBF can approach an upper bound and outperform SVD-ZFDPC [1] with much lower complexity. Moreover, we show that the noise power ratio of RS to users significantly impacts the performance.

An elementary formal system, EFS for short, is a kind of logic program over strings, and regarded as a set of rules to generate a language. For an EFS Γ, the language L(Γ) denotes the set of all strings generated by Γ. We consider a new form of EFS, called a restricted two-clause EFS, and denote by rEFS the set of all restricted two-clause EFSs. Then we study the learnability of rEFS in the exact learning model. The class rEFS contains the class of regular patterns, which is extensively studied in Learning Theory. Let Γ* be a target EFS in rEFS of learning. In the exact learning model, an oracle for superset queries answers "yes" for an input EFS Γ in rEFS if L(Γ) is a superset of L(Γ*), and outputs a string in L(Γ*)-L(Γ), otherwise. An oracle for membership queries answers "yes" for an input string w if w is included in L(Γ*), and answers "no", otherwise. We show that any EFS in rEFS is exactly identifiable in polynomial time using membership and superset queries. Moreover, for other types of queries, we show that there exists no polynomial time learning algorithm for rEFS by using the queries. This result indicates the hardness of learning the class rEFS in the exact learning model, in general.

Trust negotiation is an authorizing technique based on digital credentials, in which both a user and a server gradually establish trust in each other by repeatedly exchanging their credentials. A trust negotiation strategy is a function that answers a set of credentials to disclose to the other party, depending on policies and the set of already disclosed credentials. The disclosure tree strategy (DTS), proposed by Yu et al., is one of the strategies that satisfies preferable properties. DTS in a simple implementation requires exponential time and space; however, neither an efficient algorithm nor the lower-bound of its complexity was known. In this paper, we investigate the computational complexity of DTS. We formulate subproblems of DTS as problems on derivation trees of a context-free grammar (CFG), and analyze the computational complexity of the subproblems using the concepts of CFGs. As a result, we show that two subproblems EVL and MSET of DTS are NP-complete and NP-hard, respectively, while both are solvable in polynomial time if we modify EVL not to require non-redundancy and MSET not to answer any subset useless for leading the negotiation to success.

The wireless systems that establish multiple input multiple output (MIMO) channels through multiple antennas at both ends of the communication link, have been proved to have tremendous potential to linearly lift the capacity of conventional scalar channel. In this paper, we present two efficient decision feedback equalization algorithms that achieve optimal and suboptimal detection order in MIMO spatial multiplexing systems. The new algorithms combine the recursive matrix inversion and ordered QR decomposition approaches, which are developed for nulling cancellation interaface Bell Labs layered space time (BLAST) and back substitution interface BLAST. As a result, new algorithms achieve total reduced complexities in frame based transmission with various payload lengths compared with the earlier methods. In addition, they enable shorter detection delay by carrying out a fast hybrid preprocessing. Moreover, the operation precision insensitivity of order optimization greatly relaxes the word length of matrix inversion, which is the most computational intensive part within the MIMO detection task.

Fast schemes for compressed-domain image size change, are proposed. Fast Winograd DCTs are applied to resizing images by a factor of two to one. First, we speed up the DCT domain downsampling scheme which uses the bilinear interpolation. Then, we speed up other image resizing schemes which use DCT lowpass truncated approximations. The schemes proposed here reduce the computational complexities significantly, while there is no difference in the overall quality of the images compared to previous works.

Two-Terminal Series Parallel (TTSP, for short) graphs are used as data models in applications for electric networks and scheduling problems. We propose a TTSP term graph which is a TTSP graph having structured variables, that is, a graph pattern over a TTSP graph. Let TGTTSP be the set of all TTSP term graphs whose variable labels are mutually distinct. For a TTSP term graph g in TGTTSP, the TTSP graph language of g, denoted by L(g), is the set of all TTSP graphs obtained from g by substituting arbitrary TTSP graphs for all variables in g. Firstly, when a TTSP graph G and a TTSP term graph g are given as inputs, we present a polynomial time matching algorithm which decides whether or not L(g) contains G. The minimal language problem for the class LTTSP={L(g) | g ∈ TGTTSP} is, given a set S of TTSP graphs, to find a TTSP term graph g in TGTTSP such that L(g) is minimal among all TTSP graph languages which contain all TTSP graphs in S. Secondly, we give a polynomial time algorithm for solving the minimal language problem for LTTSP. Finally, we show that LTTSP is polynomial time inductively inferable from positive data.

This paper proposes a method providing efficient test compression. The proposed method is for robust testable path delay fault testing with scan design facilitating two-pattern testing. In the proposed method, test data are interleaved before test compression using statistical coding. This paper also presents test architecture for two-pattern testing using the proposed method. The proposed method is experimentally evaluated from several viewpoints such as compression rates, test application time and area overhead. For robust testable path delay fault testing on 11 out of 20 ISCAS89 benchmark circuits, the proposed method provides better compression rates than the existing methods such as Huffman coding, run-length coding, Golomb coding, frequency-directed run-length (FDR) coding and variable-length input Huffman coding (VIHC).

This paper describes a general quantum lower bounding technique for the communication complexity of a function that depends on the inputs given to two parties connected via paths, which may be shared with other parties, on a network of any topology. The technique can also be employed to obtain a lower-bound of the quantum communication complexity of some functions that depend on the inputs distributed over all parties on the network. As a typical application, we apply our technique to the distinctness problem of deciding whether there are a pair of parties with identical inputs, on a k-party ring; almost matching upper bounds are also given.

The heterodyne laser interferometer acts as an ultra-precise measurement apparatus in semiconductor manufacture. However the periodical nonlinearity property caused from frequency cross-talk is an obstacle to improve the high measurement accuracy in nanometer scale. In order to minimize the nonlinearity error of the heterodyne interferometer, we propose a frequency cross-talk compensation algorithm using an artificial intelligence method. The feedforward neural network trained by back-propagation compensates the nonlinearity error and regulates to minimize the difference with the reference signal. With some experimental results, the improved accuracy is proved through comparison with the position value from a capacitive displacement sensor.

This paper introduces a new timetabling problem on universities, called interview timetabling. In this problem, some constant number, say three, of referees are assigned to each of 2n graduate students. Our task is to construct a presentation timetable of these 2n students using n timeslots and two rooms, so that two students evaluated by the same referee must be assigned to different timeslots. The optimization goal is to minimize the total number of movements of all referees between two rooms. This problem comes from the real world in the interview timetabling in Kyoto University. We propose two restricted models of this problem, and investigate their time complexities.

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 this letter, we propose a novel approach to feature compensation performed in the cepstral domain. Processing in the cepstral domain has the advantage that the spectral correlation among different frequencies is taken into consideration. By introducing a linear approximation with diagonal covariance assumption, we modify the conventional log-spectral domain feature compensation technique to fit to the cepstral domain. The proposed approach shows significant improvements in the AURORA2 speech recognition task.