This paper discusses design challenges and possible solutions for 3D NAND. A 3D NAND array inherently has a larger parasitic capacitance and thereby critical area in terms of product yield. To mitigate such issues associated with 3D NAND technology, array control and divided array architecture for improving reliability and yield and for reducing area overhead, program time, energy per bit and array noise are proposed.

Deterministic ID-based signatures are digital signatures where secret keys are probabilistically generated by a key generation center while the signatures are generated deterministically. Although the deterministic ID-based signatures are useful for both systematic and cryptographic applications, to the best of our knowledge, there is no scheme with a tight reduction proof. Loosely speaking, since the security is downgraded through dependence on the number of queries by an adversary, a tighter reduction for the security of a scheme is desirable, and this reduction must be as close to the difficulty of its underlying hard problem as possible. In this work, we discuss mathematical features for a tight reduction of deterministic ID-based signatures, and show that the scheme by Selvi et al. (IWSEC 2011) is tightly secure by our new proof framework under a selective security model where a target identity is designated in advance. Our proof technique is versatile, and hence a reduction cost becomes tighter than the original proof even under an adaptive security model. We furthermore improve the scheme by Herranz (The Comp. Jour., 2006) to prove tight security in the same manner as described above. We furthermore construct an aggregate signature scheme with partial aggregation, which is a key application of deterministic ID-based signatures, from the improved scheme.

This paper describes a parametric representation of ultra-wideband radar signatures and its physical interpretation. Under the scattering theory of electromagnetic waves, a transfer function of radar scattering is factorized into three elementary parts and a radar signature with three parameters is derived. To use these parameters for radar target classification and identification, the relation between them and the response waveform is analytically revealed and numerically checked. The result indicates that distortion of the response waveform is sensitive to these parameters, and thus they can be expected to be used as features for radar target classification and identification.

Key predistribution schemes (KPSs) have played an important role in security of wireless sensor networks (WSNs). Due to comprehensive and simple structures, various types of combinatorial designs are used to construct KPSs. In general, compared to random KPSs, combinatorial KPSs have higher local connectivity but lower resilience against a node capture attack. In this paper, we apply two methods based on hash chains on KPSs based on transversal designs (TDs) to improve the resilience and the expressions for the metrics of the resulting schemes are derived.

An efficient reciprocity and passivity preserving balanced truncation for RLC networks is presented in this paper. Reciprocity and passivity are fundamental principles of linear passive networks. Hence, reduction with preservation of reciprocity and passivity is necessary to simulate behavior of the circuits including the RLC networks accurately and stably. Moreover, the proposed method is more efficient than the previous balanced truncation methods, because sparsity patterns of the coefficient matrices for the circuit equations of the RLC networks are fully available. In the illustrative examples, we will show that the proposed method is compatible with PRIMA, which is known as a general reduction method of RLC networks, in efficiency and used memory, and is more accurate at high frequencies than PRIMA.

In the advanced digital terrestrial/television multimedia broadcasting (DTMB-A) standard, a preamble based on distance detection (PBDD) is adopted for robust synchronization and signalling transmission. However, traditional signalling detection method will completely fail to work under severe frequency selective channels with ultra-long delay spread 0dB echoes. In this paper, a novel transmission parameter signalling detection method is proposed for the preamble in DTMB-A. Compared with the conventional signalling detection method, the proposed scheme works much better when the maximum channel delay is close to the length of the guard interval (GI). Both theoretical analyses and simulation results demonstrate that the proposed algorithm significantly improves the accuracy and robustness of detecting the transmitted signalling.

This paper proposes a novel wavelet de-noising scheme regarding the existing burst noises that consist of background and impulsive noises in power-line communications. The proposed de-noising scheme employs multi-level threshold functions to efficiently and adaptively reduce the given burst noises. The experiment results show that the proposed de-noising scheme significantly outperformed the conventional schemes.

Hotspots occur frequently in 3D multi-core processors (3D-MCPs), and they may adversely impact both the reliability and lifetime of a system. We present a new thermally constrained task scheduler based on a thermal-pattern-aware voltage assignment (TPAVA) to reduce hotspots in and optimize the performance of 3D-MCPs. By analyzing temperature profiles of different voltage assignments, TPAVA pre-emptively assigns different initial operating-voltage levels to cores for reducing temperature increase in 3D-MCPs. The proposed task scheduler consists of an on-line allocation strategy and a new voltage-scaling strategy. In particular, the proposed on-line allocation strategy uses the temperature-variation rates of the cores and takes into two important thermal behaviors of 3D-MCPs that can effectively minimize occurrences of hotspots in both thermally homogeneous and heterogeneous 3D-MCPs. Furthermore, a new vertical-grouping voltage scaling (VGVS) strategy that considers thermal correlation in 3D-MCPs is used to handle thermal emergencies. Experimental results indicate that, when compared to a previous online thermally constrained task scheduler, the proposed task scheduler can reduce hotspot occurrences by approximately 66% (71%) and improve throughput by approximately 8% (2%) in thermally homogeneous (heterogeneous) 3D-MCPs. These results indicate that the proposed task scheduler is an effective technique for suppressing hotspot occurrences and optimizing throughput for 3D-MCPs subject to thermal constraints.

A relay assignment scheme is proposed in this paper that minimizes the mean delay of transmission for energy harvesting (EH) cooperative communication systems, whose source node and relay nodes are all equipped with energy harvesters. We jointly consider the long-term channel side information (CSI) and energy side information (ESI) of all nodes, and formulate the delay minimization problem as an integer programming problem. To solve this problem, a refined cyclic coordinate method (RCCM) is proposed that considers the cases of fixed-packet-length (FPL) and variable-packet-length (VPL) transmission. Simulation results show that the proposed scheme achieves performance close to that of the real-time relay selection (RRS) scheme with instantaneous CSI and ESI, which gives upper bound of the performance. Moreover, compared with the simple relay rotation (SRR) scheme where each relay has equal service time, the performance of the proposed scheme is significantly improved.

The exchanged hypercube, denoted by EH(s,t), is a graph obtained by systematically removing edges from the corresponding hypercube, while preserving many of the hypercube's attractive properties. Moreover, ring-connected topology is one of the most promising topologies in Wavelength Division Multiplexing (WDM) optical networks. Let Rn denote a ring-connected topology. In this paper, we address the routing and wavelength assignment problem for implementing the EH(s,t) communication pattern on Rn, where n=s+t+1. We design an embedding scheme. Based on the embedding scheme, a near-optimal wavelength assignment algorithm using 2s+t-2+⌊2t/3⌋ wavelengths is proposed. We also show that the wavelength assignment algorithm uses no more than an additional 25 percent of (or ⌊2t-1/3⌋) wavelengths, compared to the optimal wavelength assignment algorithm.

Automatic design of analog circuits using a programmed algorithm is in great demand because optimal analog circuit design in a short time is required due to the limited development time. Although an automatic design using equation-based method can design simple circuits fast and accurately, it cannot solve complex circuits. On the other hand, an automatic design using optimization algorithm such as Ant Colony Optimization, Genetic Algorithm, and so on, can design complex circuits. However, because these algorithms are based on the stochastic optimization technique and determine the circuit parameters at random, a lot of circuits which do not operate in principle are generated and simulated to find the circuit which meets specifications. In this paper, to reduce the search space and the redundant simulations, automatic design using both equation-based method and a genetic algorithm is proposed. The proposed method optimizes the bias circuit blocks using the equation-based method and signal processing blocks using Genetic Algorithm. Simulation results indicate that the evaluation value which considers the trade-off of the circuit specification is larger than the conventional method and the proposed method can design 1.4 times more circuits which satisfy the minimum requirements than the conventional method.

In this paper, we propose a novel error recovery method for massive multiple-input multiple-output (MIMO) signal detection, which improves an estimate of transmitted signals by taking advantage of the sparsity and the discreteness of the error signal. We firstly formulate the error recovery problem as the maximum a posteriori (MAP) estimation and then relax the MAP estimation into a convex optimization problem, which reconstructs a discrete-valued sparse vector from its linear measurements. By using the restricted isometry property (RIP), we also provide a theoretical upper bound of the size of the reconstruction error with the optimization problem. Simulation results show that the proposed error recovery method has better bit error rate (BER) performance than that of the conventional error recovery method.

Sponsored search is a mechanism that shows the appropriate advertisements (ads) according to search queries. The orders and payments of ads are determined by the auction. However, the externalities which give effects to CTR and haven't been considered in some existing works because the mechanism with externalities has high computational cost. In addition, some algorithms which can calculate the approximated solution considering the externalities within the polynomial-time are proposed, however, it assumed that one bidder can propose only a single ad. In this paper, we propose the approximation allocation algorithm that one bidder can offer many ads considering externalities. The proposed algorithm employs the concept of the combinatorial auction in order to consider the combinational bids. In addition, the proposed algorithm can find the approximated allocation by the dynamic programming. Moreover, we prove the computational complexity and the monotonicity of the proposed mechanism, and demonstrate computational costs and efficiency ratios by changing the number of ads, slots and maximum bids. The experimental results show that the proposed algorithm can calculate 0.7-approximation solution even though the full search can't find solutions in the limited times.

A TM010 cavity power combiner is presented, which achieves direct interface to microstrip lines via magnetic field coupling. A prototype is fabricated and its S-matrix measured. From the S-parameters we calculate that it shows less than 0.85 dB insertion loss over 250 MHz bandwidth at X-band. The return power to the input ports is less than -15 dB over this bandwidth. We verify the insertion loss estimation using S-matrix, by measuring transmission S-parameter of a concatenated 2-port divider-combiner network. Similarly analyzed is the case of performance of power combiner when one of the input fails. We find that we can achieve graceful degradation provided we ensure some particular reflection phase at the degraded port.

Massive amounts of computation involved in real-time evaluation of deep neural networks pose a serious challenge in battery-powered systems, and neuromorphic systems specialized in neural networks have been developed. This paper first shows the portion of active neurons at a time dwindles as going toward the output layer in recent large-scale deep convolutional neural networks. Spike-based, asynchronous neuromorphic systems take advantage of the sparse activation and reduce dynamic power consumption, while synchronous systems may waste much dynamic power even for the sparse activation due to clocks. We thus propose a clock gating-based dynamic power reduction method that exploits the sparse activation for synchronous neuromorphic systems. We apply the proposed method to a building block of a recently proposed synchronous neuromorphic computing system and demonstrate up to 79% dynamic power saving at a negligible overhead.

Group signature (GS) schemes guarantee anonymity of the actual signer among group members. Previous GS schemes assume that randomness in signing is never exposed. However, in the real world, full randomness exposure can be caused by implementation problems (e.g., using a bad random number generator). In this paper, we study (im)possibility of achieving anonymity against full randomness exposure. First, we formulate a new security model for GS schemes capturing full randomness exposure. Next, we clarify that it is impossible to achieve full-anonymity against full randomness exposure without any secure component (e.g., a tamper-proof module or a trusted outside storage). Finally, we show a possibility result that selfless-anonymity can be achieved against full randomness exposure. While selfless-anonymity is weaker than full-anonymity, it is strong enough in practice. Our transformation is quite simple; and thus, previous GS schemes used in real-world systems can be easily replaced by a slight modification to strengthen the security.

A fast parameter estimation method with a coarse estimation and a fine estimation for polyphase P coded signals is proposed. For a received signal with N sampling points, the proposed method has an improved performance when the signal-to-noise ratio (SNR) is larger than 2dB and a lower computational complexity O(N logs N) compared with the latest time-frequency rate estimation method whose computational complexity is O(N2).

In this paper, we propose a method for removing block noise which appears in JPEG (Joint Photographic Experts Group) encoded images. We iteratively perform the 3D wiener filtering and correction of the coefficients. In the wiener filtering, we perform the block matching for each patch in order to get the patches which have high similarities to the reference patch. After wiener filtering, the collected patches are returned to the places where they were and aggregated. We compare the performance of the proposed method to some conventional methods, and show that the proposed method has an excellent performance.

We propose a non-blind deconvolution algorithm of point cloud attributes inspired by multi-Wiener SURE-LET deconvolution for images. The image reconstructed by the SURE-LET approach is expressed as a linear combination of multiple filtered images where the filters are defined on the frequency domain. The coefficients of the linear combination are calculated so that the estimate of mean squared error between the original and restored images is minimized. Although the approach is very effective, it is only applicable to images. Recently we have to handle signals on irregular grids, e.g., texture data on 3D models, which are often blurred due to diffusion or motions of objects. However, we cannot utilize image processing-based approaches straightforwardly since these high-dimensional signals cannot be transformed into their frequency domain. To overcome the problem, we use graph signal processing (GSP) for deblurring the complex-structured data. That is, the SURE-LET approach is redefined on GSP, where the Wiener-like filtering is followed by the subband decomposition with an analysis graph filter bank, and then thresholding for each subband is performed. In the experiments, the proposed method is applied to blurred textures on 3D models and synthetic sparse data. The experimental results show clearly deblurred signals with SNR improvements.

An inter-subset uncorrelated zero-correlation zone (ZCZ) sequence pair set is one consisting of multiple ZCZ sequence pair subsets. What's more, two arbitrary sequence pairs which belong to different subsets should be uncorrelated sequence pairs in this set, i.e., the cross-correlation function (CCF) between arbitrary sequence pairs in different subsets are zeros at everywhere. Meanwhile, each subset is a typical ZCZ sequence pair set. First, a class of uncorrelated ZCZ (U-ZCZ) sequence pair sets is proposed from interleaving perfect sequence pairs. An U-ZCZ sequence pair set is a type of ZCZ sequence pair set, which of most important property is that the CCF between two arbitrary sequence pairs is zero at any shift. Then, a type of inter-subset uncorrelated ZCZ sequence pair set is obtained by interleaving proposed U-ZCZ sequence pair set. In particular, the novel inter-subset uncorrelated ZCZ sequence pair sets are expected to be useful for designing spreading codes for QS-CDMA systems.