The isomorphism of polynomials with two secret (IP2S) problem is one candidate of computational assumptions for post-quantum cryptography. The idea of identification scheme based on IP2S is firstly introduced in 1996 by Patarin. However, the scheme was not described concretely enough and no more details are provided on how to transcribe the idea into a real-world implementation. Moreover, the security of the scheme has not been formally proven and the originally proposed security parameters are no longer secure based on the most recent research. In this paper, we propose a concrete identification scheme based on IP2S with the idea of Patarin as the starting point. We provide formal security proof of the proposed scheme against impersonation under passive attack, sequential active attack, and concurrent active attack. We also propose techniques to reduce the implementation cost such that we are able to cut the storage cost and average communication cost to an extent that under parameters for the standard 80-bit security, the scheme is implementable even on the lightweight devices in the current market.

Our previous work proposed a semi-blind single antenna interference cancellation scheme to cope with severe inter-cell interference in heterogeneous networks. This paper extends the scheme to allow multiple-receive-antenna implementation. It does not require knowledge of the training sequences of interfering signals and can cancel multiple interfering signals irrespective of the number of receive antennas. The proposed scheme applies an enhanced version of the quantized channel approach to suboptimal joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals, while reducing the computational complexity of optimum JCESD drastically. Different from the previous work, the proposed scheme applies the quantized channel generation and local search at each individual receive antenna so as to estimate transmitted symbol matrices during the training period. Then, joint estimation is newly introduced in order to estimate a channel matrix from the estimated symbol matrices, which operates in the same manner as the expectation maximization (EM) algorithm and considers signals received at all receive antennas. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) during the data period under the maximum likelihood (ML) criterion in order to cancel the interference. Computer simulations with two receive antennas under two-interfering-stream conditions show that the proposed scheme outperforms interference rejection combining (IRC) with perfect channel state information (CSI) and MUD with channels estimated by a conventional scheme based on the generalized Viterbi algorithm, and can achieve almost the same average bit error rate (BER) performance as MUD with channels estimated from sufficiently long training sequences of both the desired stream(s) and the interfering streams, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

3D ball tracking is of great significance in ping-pong game analysis, which can be utilized to applications such as TV contents and tactic analysis, with some of them requiring real-time implementation. This paper proposes a CPU-GPU platform based Particle Filter for multi-view ball tracking including 4 proposals. The multi-peak estimation and the ball-like observation model are proposed in the algorithm design. The multi-peak estimation aims at obtaining a precise ball position in case the particles' likelihood distribution has multiple peaks under complex circumstances. The ball-like observation model with 4 different likelihood evaluation, utilizes the ball's unique features to evaluate the particle's similarity with the target. In the GPU implementation, the double-queue structure and the vectorized data combination are proposed. The double-queue structure aims at achieving task parallelism between some data-independent tasks. The vectorized data combination reduces the time cost in memory access by combining 3 different image data to 1 vector data. Experiments are based on ping-pong videos recorded in an official match taken by 4 cameras located in 4 corners of the court. The tracking success rate reaches 99.59% on CPU. With the GPU acceleration, the time consumption is 8.8 ms/frame, which is sped up by a factor of 98 compared with its CPU version.

Pedestrian attribute information is important function for an advanced driver assistance system (ADAS). Pedestrian attributes such as body pose, face orientation and open umbrella indicate the intended action or state of the pedestrian. Generally, this information is recognized using independent classifiers for each task. Performing all of these separate tasks is too time-consuming at the testing stage. In addition, the processing time increases with increasing number of tasks. To address this problem, multi-task learning or heterogeneous learning is performed to train a single classifier to perform multiple tasks. In particular, heterogeneous learning is able to simultaneously train a classifier to perform regression and recognition tasks, which reduces both training and testing time. However, heterogeneous learning tends to result in a lower accuracy rate for classes with few training samples. In this paper, we propose a method to improve the performance of heterogeneous learning for such classes. We introduce a rarity rate based on the importance and class probability of each task. The appropriate rarity rate is assigned to each training sample. Thus, the samples in a mini-batch for training a deep convolutional neural network are augmented according to this rarity rate to focus on the classes with a few samples. Our heterogeneous learning approach with the rarity rate performs pedestrian attribute recognition better, especially for classes representing few training samples.

Early reviews, posted on online review sites shortly after products enter the market, are useful for estimating long-term evaluations of those products and making decisions. However, such reviews can be influenced easily by anomalous reviewers, including malicious and fraudulent reviewers, because the number of early reviews is usually small. It is therefore challenging to detect anomalous reviewers from early reviews and estimate long-term evaluations by reducing their influences. We find that two characteristics of heterogeneity on actual review sites such as Amazon.com cause difficulty in detecting anomalous reviewers from early reviews. We propose ideas for consideration of heterogeneity, and a methodology for computing reviewers' degree of anomaly and estimating long-term evaluations simultaneously. Our experimental evaluations with actual reviews from Amazon.com revealed that our proposed method achieves the best performance in 19 of 20 tests compared to state-of-the-art methodologies.

In this paper, we define a wireless sensor network with multiple types of sensors as a wireless heterogeneous sensor network (WHSN), and propose an efficient query dissemination scheme (EDT) in the WHSN. The EDT based on total dominant pruning can forward queries to only the nodes with data requested by the user, thereby reducing unnecessary packet transmission. We show that the EDT is suitable for the WHSN environment through a variety of simulations.

Irreversible thermal paints or temperature sensitive paints are a kind of special temperature sensor which can indicate the temperature grad by judging the color change and is widely used for off-line temperature measurement during aero engine test. Unfortunately, the hot gases flow within the engine during measuring always make the paint color degraded, which means a serious saturation reduction and contrast loss of the paint colors. This phenomenon makes it more difficult to interpret the thermal paint test results. Present contrast enhancement algorithms can significantly increase the image contrast but can't protect the hue feature of the paint images effectively, which always cause color shift. In this paper, we propose a color restoration method for thermal paint image. This method utilizes the atmospheric scattering model to restore the lost contrast and saturation information, so that the hue can be protected and the temperature can be precisely interpreted based on the image.

In this letter, based on orthogonal Golay sequence sets and orthogonal matrices, general constructions of zero correlation zone (ZCZ) aperiodic complementary sequence (ZACS) sets are proposed. The resultant ZACSs have column sequence peak-to-mean envelop power ratio (PMEPR) of at most 2, and the parameters of the sequence sets are optimal with respect to the theoretical bound. The novel ZACS sets are suitable for approximately synchronized multi-carrier CDMA (MC-CDMA) communication systems.

This paper presents an overview of the advance of the China millimeter-wave multiple gigabit (CMMG) wireless local area network (WLAN) system which operates in the 45 GHz frequency band. The CMMG WLAN system adopts the multiple antennas technologies to support data rate up to 15Gbps. During the progress of CMMG WLAN standardization, some new key technologies were introduced to adapt the millimeter-wave characteristic, including the usage of the zero correlation zone (ZCZ) sequence, a novel lower density parity check code (LDPC)-based packet encoding, and multiple input multiple output (MIMO) single carrier transmission. Extensive numerical results and system prototype test are also given to validate the performance of the technologies adopted by CMMG WLAN system.

In this paper, we propose a new structure for a compact matched filter bank (MFB) for an optical zero-correlation zone (ZCZ) sequence set with Zcz=2z. The proposed MFB can reduces operation elements such as 2-input adders and delay elements. The number of 2-input adders decrease from O(N2) to O(N log2 N), delay elements decrease from O(N2) to O(N). In addition, the proposed MFBs for the sequence of length 32, 64, 128 and 256 with Zcz=2,4 and 8 are implemented on a field programmable gate array (FPGA). As a result, the numbers of logic elements (LEs) of the proposed MFBs for the sequences with Zcz=2 of length 32, 64, 128 and 256 are suppressed to about 76.2%, 84.2%, 89.7% and 93.4% compared to that of the conventional MFBs, respectively.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

This paper describes the design and measurements of two-gain-mode MMIC power amplifier modules (PAMs) for Band 1 and Band 5 WCDMA data communications. The PAMs are based on the two-stage single-chain amplifier topology with an L-shaped FET step attenuator (ATT) placed at the interstage, featuring not only high-efficiency operation but also both a small phase discontinuity and a small input return loss variation between the two gain modes: a high-gain mode (0-dB thru state for the ATT) and a low-gain mode (14-dB attenuation state for the ATT). The PAMs are assembled on a 3 mm × 3 mm FR-4 laminate together with several surface mount devices, and a high-directivity, 20-dB bilayer-type directional coupler is integrated on the laminate for accurate forward-power monitoring even under a 2.5:1-VSWR load mismatching condition. To validate the design and analysis for the PAMs using the L-shaped ATT, two PAM products — a Band 1 PAM and a Band 5 PAM — were fabricated using our in-house GaAs-BiFET process. The main RF measurements under the condition of a WCDMA (R99) modulated signal and a 3.4-V supply voltage are as follows. The Band 1 PAM can deliver a power-added efficiency (PAE) as high as 46% at an output power (Pout) of 28.25 dBm while maintaining a ±5-MHz-offset adjacent channel power ratio (ACLR1) of approximately -40 dBc or less and a small phase discontinuity of less than 5°. The Band 5 PAM can also deliver a high PAE of 46% at the same Pout and ACLR1 levels with small phase discontinuity of less than 4°. This small discontinuity is due to the phase-shift compensation capacitance embedded in the ATT. The measured input return loss is well maintained at better than 10 dB at the two modes. In addition, careful coupler design achieves a small detection error of less than 0.5 dB even under a 2.5:1-VSWR load mismatching condition.

Multilinear maps have lots of cryptographic applications including multipartite key exchange and indistinguishability obfuscations. Since the concept of multilinear map was suggested, three kinds of candidate multilinear maps are constructed. However, the security of multilinear maps suffers from various attacks. In this paper, we overview suggested multilinear maps and cryptanalysis of them in diverse cases.

Based on the known binary and quaternary zero correlation zone (ZCZ) sequence sets, a class of 16-QAM sequence sets with ZCZ is presented, where the term “QAM sequence” means the sequence over the quadrature amplitude modulation (QAM) constellation. The sequence sets obtained by this method achieve an expansion in the number of 16-QAM sequence sets with ZCZ. The proposed sequence sets can be applied to quasi-synchronous code division multiple access (QS-CDMA) systems to eliminate the multiple access interference (MAI) and multipath interference (MPI) and improve the transmission data rate (TDR).

In this work we utilize feature transformations that are common in supervised learning without having prior supervision, with the goal to improve Dirichlet process Gaussian mixture model (DPGMM) based acoustic unit discovery. The motivation of using such transformations is to create feature vectors that are more suitable for clustering. The need of labels for these methods makes it difficult to use them in a zero resource setting. To overcome this issue we utilize a first iteration of DPGMM clustering to generate frame based class labels for the target data. The labels serve as basis for learning linear discriminant analysis (LDA), maximum likelihood linear transform (MLLT) and feature-space maximum likelihood linear regression (fMLLR) based feature transformations. The novelty of our approach is the way how we use a traditional acoustic model training pipeline for supervised learning to estimate feature transformations in a zero resource scenario. We show that the learned transformations greatly support the DPGMM sampler in finding better clusters, according to the performance of the DPGMM posteriorgrams on the ABX sound class discriminability task. We also introduce a method for combining posteriorgram outputs of multiple clusterings and demonstrate that such combinations can further improve sound class discriminability.

This paper studies the zero error capacity of the Nearest Neighbor Error (NNE) channels with a multilevel alphabet. In the NNE channels, a transmitted symbol is a d-tuple of elements in {0,1,2,...,l-1}. It is assumed that only one element error to a nearest neighbor element in a transmitted symbol can occur. The NNE channels can be considered as a special type of limited magnitude error channels, and it is closely related to error models for flash memories. In this paper, we derive a lower bound of the zero error capacity of the NNE channels based on a result of the perfect Lee codes. An upper bound of the zero error capacity of the NNE channels is also derived from a feasible solution of a linear programming problem defined based on the confusion graphs of the NNE channels. As a result, a concise formula of the zero error capacity is obtained using the lower and upper bounds.

In this letter, three constructions of perfect Gaussian integer sequences are constructed based on cyclic difference sets. Sufficient conditions for constructing perfect Gaussian integer sequences are given. Compared with the constructions given by Chen et al. [12], the proposed constructions relax the restrictions on the parameters of the cyclic difference sets, and new perfect Gaussian integer sequences will be obtained.

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.

In this correspondence, two types of multiple binary zero correlation zone (ZCZ) sequence sets with inter-set zero cross-correlation zone (ZCCZ) are constructed. Based on orthogonal matrices with order N×N, multiple binary ZCZ sequence sets with inter-set even and odd ZCCZ lengthes are constructed, each set is an optimal ZCZ sequence set with parameters (2N2, N, N+1)-ZCZ, among these ZCZ sequence sets, sequences possess ideal cross-correlation property within a zone of length 2Z or 2Z+1. These resultant multiple ZCZ sequence sets can be used in quasi-synchronous CDMA systems to remove the inter-cell interference (ICI).

Massive MIMO (mMIMO) is a promising technology for smart multimedia and wireless communication fields. In this paper, we investigate pilot allocation problem in two-tier time division duplex (TDD) heterogeneous network (HetNet) with mMIMO. First, we propose a new pilot allocation scheme for maximizing ergodic downlink sum rate of macro users (MUs) and small cell users (SUs), where the uplink pilot overhead and cross-tier interference are jointly considered. Then, we theoretically analyze the formulated problem and propose a low complexity one-dimensional search algorithm to obtain the optimum pilot allocation. In addition, we propose two suboptimal pilot allocation algorithms to simplify the computational process and improve SUs' fairness, respectively. Finally, simulation results show that the performance of the proposed scheme outperforms that of the traditional schemes.