A compact composite right/left-handed transmission-line (CRLH TL) stub resonator is presented. The bandpass frequency of the resonator and the adjacent transmission-zeros are determined by the negative order resonance modes of the stub line. We demonstrate that these resonance frequencies can be arbitrarily controlled by using non-identical, unbalanced unit cells, leading to enhanced loaded-Q as well as unloaded-Q. We show that despite the presence of lumped element loss the unloaded-Q is enhanced by a factor of 2 compared to that of microstrip line as a result of nearly-zero group velocity. As a consequence, the loaded-Q can be increased without incurring significant insertion loss as in the case of conventional stub resonators on the same substrate. The physical mechanisms of the distinct features are discussed based on an equivalent dispersion diagram, a concept introduced to model general one-port CRLH TL used as a stub line.

In this letter, we propose a novel Uniformity-Approximated Histogram Equalization (UAHE) algorithm to enhance the image as well as to preserve the image features. First, the UAHE algorithm generates the image histogram and computes the average value of all bins as the histogram threshold. In order to approximate the uniform histogram, the bins of image histograms greater than the above threshold are clipped, and the subtracted counts are averaged and uniformly assigned to the remaining bins lower than the threshold. The approximated uniform histogram is then applied to generate the intensity transformation function for image contrast enhancement. Experimental results show that our algorithm achieves the maximum entropy as well as the feature similarity values for image contrast enhancement.

The short-channel effect (SCE) in a MOSFET with an atomically thin MoS$_{2}$ channel was studied using a TCAD simulator. We derived the surface potential roll-up, drain-induced barrier lowering (DIBL), threshold voltage, and subthreshold swing (SS) as indexes of the SCE and analyzed their dependency on the channel thickness (number of atomic layers) and channel length. The minimum scalable channel length for a one-atomic-layer-thick MoS$_{2}$ MOSFET was determined from the threshold voltage roll-off to be 7.6,nm. The one-layer-thick device showed a small DIBL of 87,mV/V at a 20 nm gate length. By using high-k gate insulator, an SS lower than 70,mV/dec is achievable in sub-10-nm-scale devices.

Golf is a solitaire game, where the object is to move all cards from a 5×8 rectangular layout of cards to the foundation. A top card in each column may be moved to the foundation if it is either one rank higher or lower than the top card of the foundation. If no cards may be moved, then the top card of the stock may be moved to the foundation. We prove that the generalized version of Golf Solitaire is NP-complete.

Detecting traffic anomalies is an indispensable component of overall security architecture. As Internet and traffic data with more sophisticated attacks grow exponentially, preserving security with signature-based traffic analyzers or analyzers that do not support massive traffic are not sufficient. In this paper, we propose a novel method based on combined sketch technique and S-transform analysis for detecting anomalies in massive traffic streams. The method does not require any prior knowledge such as attack patterns and models representing normal traffic behavior. To detect anomalies, we summarize the entropy of traffic data over time and maintain the summarized data in sketches. The entropy fluctuation of the traffic data aggregated to the same bucket is observed by S-transform to detect spectral changes referred to as anomalies in this work. We evaluated the performance of the method with real-world backbone traffic collected at the United States and Japan transit link in terms of both accuracy and false positive rates. We also explored the method parameters' influence on detection performance. Furthermore, we compared the performance of our method to S-transform-based and Wavelet-based methods. The results demonstrated that our method was capable of detecting anomalies and overcame both methods. We also found that our method was not sensitive to its parameter settings.

How to retrieve the closest content from an in-network cache is one of the most important issues in Information-Centric Networking (ICN). This paper proposes a novel content discovery scheme called Local Tree Hunting (LTH). By adding branch-cast functionality to a local tree for content requests to a Content-Centric Network (CCN) response node, the discovery area for caching nodes expands. Since the location of such a branch-casting node moves closer to the request node when the content is more widely cached, the discovery range, i.e. the branch size of the local tree, becomes smaller. Thus, the discovery area is autonomously adjusted depending on the content dissemination. With this feature, LTH is able to find the “almost true closest” caching node without checking all the caching nodes in the in-network cache. The performance analysis employed in Zipf's law content distribution model and which uses the Least Recently Used eviction rule shows the superiority of LTH with respect to identifying the almost exact closest cache.

Leakage resilient cryptography is often considered in the presence of a very strong leakage oracle: An adversary may submit arbitrary efficiently computable function f to the leakage oracle to receive f(x), where x denotes the entire secret that a party possesses. This model is somewhat too strong in the setting of public-key encryption (PKE). It is known that no secret-key leakage resilient PKE scheme exists if the adversary may have access to the secret-key leakage oracle to receive only one bit after it was given the challenge ciphertext. Similarly, there exists no sender-randomness leakage resilient PKE scheme if one-bit leakage occurs after the target public key was given to the adversary. At TCC 2011, Halevi and Lin have broken the barrier of after-the-fact leakage, by proposing the so-called split state model, where a secret key of a party is explicitly divided into at least two pieces, and the adversary may have not access to the entire secret at once, but each divided pieces, one by one. In the split-state model, they have constructed post-challenge secret-key leakage resilient CPA secure PKEs from hash proof systems, but the construction of CCA secure post-challenge secret-key leakage PKE has remained open. They have also remained open to construct sender-randomness leakage PKE in the split state model. This paper provides a solution to the open issues. We also note that the proposal of Halevi and Lin is post-challenge secret-key leakage CPA secure against a single challenge ciphertext; not against multiple challenges. We present an efficient generic construction that converts any CCA secure PKE scheme into a multiple-challenge CCA secure PKE that simultaneously tolerates post-challenge secret-key and sender-randomness leakage in the split state model, without any additional assumption. In addition, our leakage amount of the resulting schemes is the same as that of Halevi and Lin CPA PKE, i.e., (1/2+γ)l/2 where l denotes the length of the entire secret (key or randomness) and γ denotes a universal (possitive) constant less than 1/2. Our conversion is generic and available for many other public-key primitives. For instance, it can convert any identity-based encryption (IBE) scheme to a post-challenge master-key leakage and sender-randomness leakage secure IBE.

A four-pixel-array superconducting transition-edge sensor (TES) microcalorimeter with a mushroom-shaped absorber was fabricated for the energy dispersive spectroscopy performed on a transmission electron microscope. The TES consists of a bilayer of Au/Ti with either a 50-nm or 120-nm thickness. The absorber of 5.0,$mu$m thick is made from a Au layer and its stem is deposited in the center of the TES surface. A Ta$_{2}$O$_{5}$ insulating layer of 100-nm thickness is inserted between the overhang region of the absorber and the TES surface. A selected pixel of the TES microcalorimeter was operated for the detection of Np L X-rays emitted from an $^{241}$Am source. A response of the TES microcalorimeter to L X-rays was obtained by analyzing detection signal pulses with using the optimal filter method. An energy resolution was obtained to be 33,eV of the full width at half maximum value at 17.751,keV of Np L$_{eta 1}$ considering its natural width of 13.4,eV. Response to L X-rays emitted from a mixture source of $^{238}$Pu, $^{239}$Pu and $^{241}$Am was obtained by operating the selected pixel of the TES microcalorimeter. Major L X-ray peaks of progeny elements of $alpha$ decay of Pu and Am isotopes were clearly identified in the obtained energy spectrum. The experimental results demonstrated the separation of $^{241}$Am and plutonium isotopes by L X-ray spectroscopy.

This paper presents our investigation of non-orthogonal multiple access (NOMA) as a novel and promising power-domain user multiplexing scheme for future radio access. Based on information theory, we can expect that NOMA with a successive interference canceller (SIC) applied to the receiver side will offer a better tradeoff between system efficiency and user fairness than orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems. This improvement becomes especially significant when the channel conditions among the non-orthogonally multiplexed users are significantly different. Thus, NOMA can be expected to efficiently exploit the near-far effect experienced in cellular environments. In this paper, we describe the basic principle of NOMA in both the downlink and uplink and then present our proposed NOMA scheme for the scenario where the base station is equipped with multiple antennas. Simulation results show the potential system-level throughput gains of NOMA relative to OMA.

Face recognition under variable illumination conditions is a challenging task. Numbers of approaches have been developed for solving the illumination problem. In this paper, we summarize and analyze some noteworthy issues in illumination processing for face recognition by reviewing various representative approaches. These issues include a principle that associates various approaches with a commonly used reflectance model and the shared considerations like contribution of basic processing methods, processing domain, feature scale, and a common problem. We also address a more essential question-what to actually normalize. Through the discussion on these issues, we also provide suggestions on potential directions for future research. In addition, we conduct evaluation experiments on 1) contribution of fundamental illumination correction to illumination insensitive face recognition and 2) comparative performance of various approaches. Experimental results show that the approaches with fundamental illumination correction methods are more insensitive to extreme illumination than without them. Tan and Triggs' method (TT) using L1 norm achieves the best results among nine tested approaches.

In this paper we describe and experimentally validate a dual-band digital predistortion (DPD) model we propose that takes account of the intermodulation and harmonic distortion produced when the center frequencies of input bands have a harmonic relationship. We also describe and experimentally validate our proposed novel dual-band power amplifier (PA) linearization architecture consisting of a single feedback loop employing a dual-band mixer. Experiment results show that the DPD linearization the proposed model provides can compensate for intermodulation and harmonic distortion in a way that the conventional two-dimensional (2-D) DPD approach cannot. The proposed feedback architecture should make it possible to simplify analog-to-digital converter (ADC) design and eliminate the time lag between different feedback paths.

In the big data era, messaging systems are required to process large volumes of message traffic with high scalability and availability. However, conventional systems have two issues regarding availability. The first issue is that failover processing itself has a risk of failure. The second issue is to find a trade-off between consistency and availability. We propose a resilient messaging system based on a distributed in-memory key-value store (KVS). Its servers are interconnected with each other and messages are distributed to multiple servers in normal processing state. This architecture can continue messaging services wherever in the messaging system server/process failures occur without using failover processing. Furthermore, we propose two methods for improved resilience: the round-robin method with a slowdown KVS exclusion and the two logical KVS counter-rotating rings to provide short-term-availability in the messaging system. Evaluation results demonstrate that the proposed system can continue service without failover processing. Compared with the conventional method, our proposed distribution method reduced 92% of error responses to clients caused by server failures.

Introducing pronunciation models into decoding has been proven to be benefit to LVCSR. In this paper, a discriminative pronunciation modeling method is presented, within the framework of the Minimum Phone Error (MPE) training for HMM/GMM. In order to bring the pronunciation models into the MPE training, the auxiliary function is rewritten at word level and decomposes into two parts. One is for co-training the acoustic models, and the other is for discriminatively training the pronunciation models. On Mandarin conversational telephone speech recognition task, compared to the baseline using a canonical lexicon, the discriminative pronunciation models reduced the absolute Character Error Rate (CER) by 0.7% on LDC test set, and with the acoustic model co-training, 0.8% additional CER decrease had been achieved.

It is widely known that decoding problems for random linear codes are computationally hard in general. Surprisingly, Kopparty and Saraf proved query-efficient list-decodability of sparse random linear codes by showing a reduction from a decoding problem for sparse random linear codes to that for the Hadamard code with small number of queries even under high error rate [11]. In this paper, we show a more direct list-decoding algorithm for sparse random linear codes with small number of queries from a Fourier-analytic approach.

Secure sets and defensive alliances in graphs are studied. They are sets of vertices that are safe in some senses. In this paper, we first present a fixed-parameter algorithm for finding a small secure set, whose running time is much faster than the previously known one. We then present improved bound on the smallest sizes of defensive alliances and secure sets for hypercubes. These results settle some open problems paused recently.

In order to verify the channel sum-rate improvement by multi-user multiple-input multiple-output (MU-MIMO) transmission in distributed antenna systems (DASs), we investigate and compare the characteristics of channel sum-rates in both centralized antenna systems (CASs) and DASs under the effects of path loss, spatially correlated shadowing, correlated multi-path fading, and inter-cell interference. In this paper, we introduce two different types of functions to model the shadowing, auto-correlation and cross-correlation, and a typical exponential decay function to model the multi-path fading correlation. Thus, we obtain the distribution of the channel sum-rate and investigate its characteristics. Computer simulation results indicate that DAS can improve the performance of the channel sum-rate compared to CAS, even in the case under consideration. However, this improvement decreases as interference power increases. Moreover, the decrease in the channel sum-rate due to the increase in the interference power becomes slow under the effect of shadowing correlation. In addition, some other analyses on the shadowing correlation that occurs on both the transmit and receiver sides are provided. These analysis results show that the average channel sum-rate in a DAS without inter-cell interference considerably decreases because of the shadowing correlation. In contrast, there appears to be no change in the CAS. Furthermore, there are two different types of sum-rate changes in a DAS because of the difference in shadowing auto-correlation and cross-correlation.

Three-dimensionally assembled TES X-ray microcalorimeter arrays may be utilized for three purposes: (1) to obtain wide X-ray energy coverage of TES microcalorimeters, (2) to distinguish charged particle events from X-ray events, (3) to reconstruct Compton-scattering geometry for hard X-ray Compton cameras. We have designed and fabricated three-dimensionally assembled array of the minimum format i.e. $2 imes 2 imes 2$ array in order to obtain a good energy resolution in a wide energy range of 0.5--20,keV and a high maximum counting rate of 2000,cps for energy dispersive X-ray spectrometer (EDS) system for a transmission electron microscope (TEM). Although we could not obtain required energy resolution because of a problem in the refrigerator system, we confirmed the operation of the three-dimensional array.

This letter deals with the carrier frequency offsets (CFO) estimation problem for orthogonal frequency division multiple access (OFDMA) uplink systems. Combined with centro-symmetric (CS) trimmed autocorrelation matrix and weighting subspace projection, the proposed estimator has better estimate performance than MVDR, MUSIC, CS-MUSIC, and ESPRIT estimators, especially in relatively less of OFDMA blocks and low SNR situations. Simulation results are presented to verify the efficiency of the proposed estimator.

Radio Frequency based Device-Free Localization (RFDFL) is an emerging localization technique without requirements of attaching any electronic device to a target. The target can be localized by means of measuring the shadowing of received signal strength caused by the target. However, the accuracy of RFDFL deteriorates seriously in environment with WiFi interference. State-of-the-art methods do not efficiently solve this problem. In this paper, we propose a dual-band method to improve the accuracy of RFDFL in environment without/with severe WiFi interference. We introduce an algorithm of fusing dual-band images in order to obtain an enhanced image inferring more precise location and propose a timestamp-based synchronization method to associate the dual-band images to ensure their one-one correspondence. With real-world experiments, we show that our method outperforms traditional single-band localization methods and improves the localization accuracy by up to 40.4% in real indoor environment with high WiFi interference.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.