This paper proposes the first (practical) inner product encryption (IPE) scheme that is adaptively secure and fully attribute-hiding (attribute-hiding in the sense of the definition by Katz, Sahai and Waters), while the existing (practical) IPE schemes are either fully attribute-hiding but selectively secure or adaptively secure but weakly attribute-hiding. The proposed IPE scheme is proven to be adaptively secure and fully attribute-hiding under the decisional linear assumption in the standard model. The IPE scheme is comparably as efficient as the existing (practical) attribute-hiding IPE schemes. We also present a variant of the proposed IPE scheme with the same security that achieves shorter public and secret keys. A hierarchical IPE scheme can be constructed that is also adaptively secure and fully attribute-hiding under the same assumption. In this paper, we extend the dual system encryption technique by Waters into a more general manner, in which new forms of ciphertext and secret keys are employed and new types of information theoretical tricks are introduced along with several forms of computational reduction.

Symmetric predicate encryption schemes support a rich class of predicates over keyword ciphertexts while preserving both keyword privacy and predicate privacy. Most of these schemes treat each keyword as the smallest unit to be processed in the generation of ciphertexts and predicate tokens. To extend the class of predicates, we treat each symbol of a keyword as the smallest unit to be processed. In this letter, we propose a novel encoding to construct a symmetric inner-product encryption scheme for position-aware symbol-based predicates. The resulting scheme can be applied to a number of secure filtering and online storage services.

Neural networks are widely used in various fields due to their superior learning abilities. This paper proposes a hardware winner-take-all neural network (WTANN) that employs a new winner-take-all (WTA) circuit with phase-modulated pulse signals and digital phase-locked loops (DPLLs). The system uses DPLL as a computing element, so all input values are expressed by phases of rectangular signals. The proposed WTA circuit employs a simple winner search circuit. The proposed WTANN architecture is described by very high speed integrated circuit (VHSIC) hardware description language (VHDL), and its feasibility was tested and verified through simulations and experiments. Conventional WTA takes a global winner search approach, in which vector distances are collected from all neurons and compared. In contrast, the WTA in the proposed system is carried out locally by a distributed winner search circuit among neurons. Therefore, no global communication channels with a wide bandwidth between the winner search module and each neuron are required. Furthermore, the proposed WTANN can easily extend the system scale, merely by increasing the number of neurons. The circuit size and speed were then evaluated by applying the VHDL description to a logic synthesis tool and experiments using a field programmable gate array (FPGA). Vector classifications with WTANN using two kinds of data sets, Iris and Wine, were carried out in VHDL simulations. The results revealed that the proposed WTANN achieved valid learning.

The concept of dual pairing vector spaces (DPVS) was introduced by Okamoto and Takashima in 2009, and it has been employed in various applications, functional encryption (FE) including attribute-based encryption (ABE) and inner-product encryption (IPE) as well as attribute-based signatures (ABS), generic conversion from composite-order group based schemes to prime-order group based ones and public-key watermarking. In this paper, we show the concept of DPVS, the major applications to FE and the key techniques employed in these applications. This paper presents them with placing more emphasis on plain and intuitive descriptions than formal preciseness.

For compressed sensing, to address problems which do not involve reconstruction, a correlation analysis between measurements and the transform coefficients is proposed. It is shown that there is a linear relationship between them, which indicates that we can abstract the inner property of images directly in the measurement domain.

This paper studies the design of cooperative beamforming (CB) and cooperative jamming (CJ) for the physical layer security of an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. The secrecy rate maximization (SRM) problem of such a network is to maximize the difference of two concave functions, a problem which is non-convex and has no efficient solution. Based on the inner convex approximation (ICA) and semidefinite relaxation (SDR) techniques, we propose two novel low-complexity schemes to design CB and CJ for SRM in the AF network. In the first strategy, relay nodes adopt the CB only to secure transmission. Based on ICA, this design guarantees convergence to a Karush-Kuhn-Tucker (KKT) solution of the SDR of the original problem. In the second strategy, the optimal joint CB and CJ design is studied and the proposed joint design can guarantee convergence to a KKT solution of the original problem. Moreover, in the second strategy, we prove that SDR always has a rank-1 solution for the SRM problem. Simulation results show the superiority of the proposed schemes.

Recently, the wavelet-based estimation method has gradually been becoming popular as a new tool for software reliability assessment. The wavelet transform possesses both spatial and temporal resolution which makes the wavelet-based estimation method powerful in extracting necessary information from observed software fault data, in global and local points of view at the same time. This enables us to estimate the software reliability measures in higher accuracy. However, in the existing works, only the point estimation of the wavelet-based approach was focused, where the underlying stochastic process to describe the software-fault detection phenomena was modeled by a non-homogeneous Poisson process. In this paper, we propose an interval estimation method for the wavelet-based approach, aiming at taking account of uncertainty which was left out of consideration in point estimation. More specifically, we employ the simulation-based bootstrap method, and derive the confidence intervals of software reliability measures such as the software intensity function and the expected cumulative number of software faults. To this end, we extend the well-known thinning algorithm for the purpose of generating multiple sample data from one set of software-fault count data. The results of numerical analysis with real software fault data make it clear that, our proposal is a decision support method which enables the practitioners to do flexible decision making in software development project management.

With the distributed data mining technique having been widely used in a variety of fields, the privacy preserving issue of sensitive data has attracted more and more attention in recent years. Our major concern over privacy preserving in distributed data mining is the accuracy of the data mining results while privacy preserving is ensured. Corresponding to the horizontally partitioned data, this paper presents a new hybrid algorithm for privacy preserving distributed data mining. The main idea of the algorithm is to combine the method of random orthogonal matrix transformation with the proposed secure multi-party protocol of matrix product to achieve zero loss of accuracy in most data mining implementations.

We propose a maximum likelihood estimation approach for the recovery of continuously-defined sparse signals from noisy measurements, in particular periodic sequences of Diracs, derivatives of Diracs and piecewise polynomials. The conventional approach for this problem is based on least-squares (a.k.a. annihilating filter method) and Cadzow denoising. It requires more measurements than the number of unknown parameters and mistakenly splits the derivatives of Diracs into several Diracs at different positions. Moreover, Cadzow denoising does not guarantee any optimality. The proposed approach based on maximum likelihood estimation solves all of these problems. Since the corresponding log-likelihood function is non-convex, we exploit the stochastic method called particle swarm optimization (PSO) to find the global solution. Simulation results confirm the effectiveness of the proposed approach, for a reasonable computational cost.

Genetic algorithm (GA) is now an important tool in the field of wireless communications. For multiple-input/multiple-output (MIMO) wireless communications system employing spatial multiplexing transmission, we evaluate the effects of GA parameters value on channel parameters in fading channels. We assume transmit-correlated Rayleigh and Rician fading with realistic Laplacian power azimuth spectrum. Azimuth spread (AS) and Rician K-factor are selected according to the measurement-based WINNER II channel model for several scenarios. Herein we have shown the effects of GA parameters and channel parameters in different WINNER II scenarios (i.e., AS and K values) and rank of the deterministic components. We employ meta GA that suitably selects the population (P), generation (G) and mutation probability (pm) for the inner GA. Then we show the cumulative distribution function (CDF) obtain experimentally for the condition number C of the channel matrix H. It is found that, GA parameters depend on the channel parameters, i.e., GA parameters are the functions of the channel parameters. It is also found that for the poorer channel conditions smaller GA parameter values are required for MIMO detection. This approach will help to achieve maximum performance in practical condition for the lower numerical complexity.

We propose a current mode sense amplifier that uses a current-mirror to increase the bitline sensing current, which dominates the sensing speed. A comparison of the sensing delay shows that the proposed sense amplifier can provide about 12.6∼15.4% improvement depending on different bitline loads in sensing speed over original WTA scheme.

A hybrid approach for the synthesis of square thinned arrays with low sidelobes is presented. The proposed method combines the advantages of a genetic algorithm and combinatorial technique-cyclic difference sets (CDSs). The peak sidelobe level (PSL) and the thinning factor are numerically evaluated to show the effectiveness and reliability of the proposed hybrid method. In the proposed GA-enhanced square arrays with the DS and the best CDS, reductions of the PSL, of 4.16 dB and 2.45 dB, respectively, were achieved as compared to the results of conventional rectangular DS and CDS arrays.

This paper proposes an inner-product encryption (IPE) scheme, which achieves selectively fully-attribute-hiding security in the standard model almost tightly reduced from the decisional linear (DLIN) assumption, and whose ciphertext is almost the shortest among the existing (weakly/fully) attribute-hiding IPE schemes, i.e., it consists of n+4 elements of G and 1 element of GT for a prime-order symmetric bilinear group (G, GT), where n is the dimension of attribute/predicate vectors. We also present a variant of the proposed IPE scheme that enjoys shorter public and secret keys with preserving the security. A hierarchical IPE (HIPE) scheme can be realized that has short ciphertexts and selectively fully-attribute-hiding security almost tightly reduced from the DLIN assumption.

In this paper, time-difference estimation of filtered random signals passed through multipath channels is discussed. First, we reformulate the approach based on innovation-rate sampling (IRS) to fit our random signal model, then use the IRS results to drive the nonlinear least-squares (NLS) minimization algorithm. This hybrid approach (referred to as the IRS-NLS method) provides consistent estimates even for cases with sub-Nyquist sampling assuming the use of compactly-supported sampling kernels that satisfies the recently-developed nonaliasing condition in the frequency domain. Numerical simulations show that the proposed NLS-IRS method can improve performance over the straight-forward IRS method, and provides approximately the same performance as the NLS method with reduced sampling rate, even for closely-spaced time delays. This enables, given a fixed observation time, significant reduction in the required number of samples, while maintaining the same level of estimation performance.

This paper presents an efficient implementation of OFDM inner receiver on a programmable multi-core processor platform with CMMB as an application. The platform consists of an array of programmable SIMD processors interconnected in a 2-D mesh network, which can provide high performance and is quite suitable for wireless communication applications. Implemented on one cluster with 8 cores, the receiver includes symbol timing, carrier frequency offset and sampling frequency offset synchronization, channel estimation and equalization. Multiple optimization techniques are explored to improve system throughput such as: task-level parallelism on many cores, data-level parallelism on SIMD cores, minimization of memory access and route-length-minimization task mapping techniques. Besides, efficient memory strategy and specific instructions for complex computation increase the performance. The simulation results show that the inner receiver could achieve a throughput of up to 120 Mbps when operating at 750 MHz.

This paper reports on a theoretical study and modeling of a 1.55 µm quantum dot heterostructure laser using InN as a promising candidate for the first time. Details of design and theoretical analysis of probability distribution of the optical transition energy, threshold current density, modal gain, and differential quantum efficiency are presented considering a single layer of quantum dots. Dependence of threshold current density on the RMS value of quantum dot size fluctuations and the cavity length is studied. A low threshold current density of ∼51 Acm-2 is achieved at room temperature for a cavity length of 640 µm. An external differential efficiency of ∼65% and a modal gain of ∼12.5 cm-1 are obtained for the proposed structure. The results indicate that the InN based quantum dot laser is a promising one for the optical communication system.

We address a problem of sampling and reconstructing periodic piecewise polynomials based on the theory for signals with a finite rate of innovation (FRI signals) from samples acquired by a sinc kernel. This problem was discussed in a previous paper. There was, however, an error in a condition about the sinc kernel. Further, even though the signal is represented by parameters, these explicit values are not obtained. Hence, in this paper, we provide a correct condition for the sinc kernel and show the procedure. The point is that, though a periodic piecewise polynomial of degree R is defined as a signal mapped to a periodic stream of differentiated Diracs by R + 1 time differentiation, the mapping is not one-to-one. Therefore, to recover the stream is not sufficient to reconstruct the original signal. To solve this problem, we use the average of the target signal, which is available because of the sinc sampling. Simulation results show the correctness of our reconstruction procedure. We also show a sampling theorem for FRI signals with derivatives of a generic known function.

Drain collapse in AlGaN/GaN HFET is analyzed using a two-dimensional device simulator. Two-step saturation is obtained, assuming hole-trap type surface states on the AlGaN surface and a short negative-charge-injected region at the drain side of the gate. Due to the surface electric potential pinning by the surface traps, the negative charge injected region forms a constant potential like in a metal gate region and it acts as an FET with a virtual gate. The electron concentration profile reveals that the first saturation occurs by pinch-off in the virtual gate region and the second saturation occurs by the pinch-off in the metal gate region. Due to the short-channel effect of the virtual gate FET, the saturation current increases until it finally reaches the saturation current of the intrinsic metal gate FET. Current collapses with current degradation at the knee voltage in the I-V characteristics can be explained by the formation of the virtual gate.

We investigated the influence of the thickness of the AlN interlayer for InAlN/GaN and InAlN/AlGaN/GaN heterostructures. The AlN thickness strongly affects the surface morphology and electron mobility of the InAlN/GaN structures. The rms roughness of the surface increases from 0.35 to 1.2 nm with increasing AlN thickness from 0 to 1.5 nm. Large pits are generated when the AlN is thicker than 1 nm. The highest electron mobility of 1470 cm2/VS is obtained for a 0.75-nm-thick AlN interlayer. The mobility, however, becomes lower with increasing deviation from 0.75 nm. It is only 200 cm2/VS for the 0-nm thick AlN. Inserting AlGaN between AlN and InAlN suppresses the influence of the AlN interlayer thickness. A smooth surface with rms roughness of 0.35 nm is obtained for all samples with 0-1.5-nm-thick AlN. The electron mobility ranges from 1000 to 1690 cm2/VS. The variation is smaller than that for InAlN/GaN. We fabricated field effect transistors (FETs) with gate length of 2 µm. The electron mobility in the access region affects the transconductance (gm) of FETs. As a results, the influence of the AlN thickness for InAlN/GaN FETs is larger than that for InAlN/AlGaN/GaN FETs, which reduces gate leakage current. The transconductance varies from 93 to 235 mS/mm for InAlN/GaN FETs. In contrast, it varies from 180 to 230 mS/mm for InAlN/AlGaN/GaN FETs. These results indicate that the InAlN/AlGaN/GaN heterostructures could lead to the development of GaN-based FETs.

This paper describes diffusion of electric vehicles and novel social infrastructure from the viewpoint of systems innovation theory considering both human society aspects and elemental technological aspects. Firstly, fundamentals of the systems innovation theory and the platform theory are mentioned. Secondly, discussion on mobility from the viewpoint of the human-society layer and discussion of electrical vehicles from the viewpoint of the elemental techniques are carried out. Thirdly, based on those, R & D, measures are argued such as establishment of the ubiquitous noncontact feeding and authentication payment system is important. Finally, it is also insisted that after the establishment of this system the super smart grid with temporal and spatial control including demand itself with the low social cost will be expected.