We proposed and theoretically discussed a polarization switch based on a multiple quantum well (MQW) microring resonator (MRR) with an L-shaped waveguide as a dynamic polarization control device. The L-shaped waveguide was useful to obtain the rotation angle of the principal axis of 45° even when the core layer has form birefringence such as an MQW. The MRR functions as both a polarization converter and a wavelength filter. As an MQW core layer, a multiple five-layer asymmetric coupled quantum well (FACQW) was assumed. Polarization switching of an inputted light with a selected wavelength was successfully demonstrated at an operation voltage as low as 0.2 V using the electrorefractive index change in the MRR waveguide. The maximum polarization extinction ratio was more than 35 dB. The high-speed and low-voltage polarization switching can be realized with the proposed MRR polarization switch.

Constant weight codes have mathematical interest and practical applications such as coding for bandwidth-efficient channels and construction of spherical codes for modulation. In this letter, by using difference balanced functions with d-form property, we constructed a class of constant composition code with new parameters, which achieves the equal sign of generalized Johnson bound.

The present paper introduces a novel construction of structured ternary sequences having a zero-correlation zone (ZCZ) for both periodic and aperiodic correlation functions. The cross-correlation function and the side lobe of the auto-correlation function of the proposed sequence set are zero for phase shifts within the ZCZ. The proposed ZCZ sequence set can be generated from an arbitrary Hadamard matrix of order n. The sequence set of order 0 is identical to the r-th row of the Hadamard matrix. For m≥0, the sequence set of order (m+1) is constructed from the sequence set of order m by sequence concatenation and interleaving. The sequence set of order m has 2m subsets of size n. The length of the sequence is equal to n4m+2m+1(2m-1); The phase shift of the ZCZ for the whole sequence set is from -(2m-1) to (2m-1). The sequence set of order 0 is coincident with the rows of the given Hadamard sequence with no ZCZ. The subsets can be associated with a perfect binary tree of height m with 2m leaves. The r-th sequence subset consists of from the nr-th sequence to the ((n+1)r-1)-th sequence. The r-th subset is assigned to the r-th leaf of the perfect binary tree. For a longer distance between the corresponding leaves to the r-th and s-th sequences, the ZCZ of the r-th and s-th sequences is wider. This tree-structured width of ZCZ of a pair of the proposed sequences enables flexible design in applications of the proposed sequence set. The proposed sequence is suitable for a heterogeneous wireless network, which is one of the candidates for the fifth generation of radio access networks.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

Delay Tolerant Networks (DTN) protocols based on the store-and-carry principle offer useful functions such as forwarding, utility value, social networks, and network coding. Although many DTN protocol proposals have been offered, work continues to improve performance. In order to implement DTN functions, each protocol introduces multiple parameters; their performance is largely dependent on how the parameter values are set. In this paper, we focus on improving spray and wait (S&W) by proposing a communication protocol named a Spray and AHP-GRA-based Forwarding (S&AGF) and Spray and Fuzzy based Forwarding (S&FF) scheme for DTN. The proposed protocols include a new forwarding scheme intended to extend network lifetime as well as maintain acceptable delivery ratio by addressing a deficiency in existing schemes that do not take energy into consideration. We choose the most suitable relay node by taking the energy, mobility, measured parameters of nodes into account. The simulation-based comparison demonstrates that the proposed S&AGF and S&FF schemes show better balanced performance level in terms of both delivery ratio and network lifetime than original S&W and its variants.

Timing and frequency offsets are caused by imperfect synchronization at the receiver. These errors degrade the performance of OFDM systems by introducing inter-carrier-interference (ICI) and inter-symbol-interference (ISI). In this paper, we derive signal-to-interference ratio (SIR) analytically with timing and frequency offsets for the case that the sampling rate of analog-to-digital converter (ADC) in OFDM receiver is an integer fraction of the signal bandwidth. We find the exact form of interference power as a function of the fractional sampling rate. Our derived analysis is confirmed by simulations and can be applied to see the exact performance of OFDM systems with fractional sampling rate.

In this paper, we study partial key exposure attacks on RSA where the number of unexposed blocks of the private key is greater than or equal to one. This situation, called generalized framework of partial key exposure attack, was first shown by Sarkar [22] in 2011. Under a certain condition for the values of exposed bits, we present a new attack which needs fewer exposed bits and thus improves the result in [22]. Our work is a generalization of [28], and the approach is based on Coppersmith's method and the technique of unravelled linearization.

Recently, P2PTV is a popular application to deliver video streaming data over the Internet. On the overlay network, P2PTV applications create logical links between pairs of peers considering round trip time (RTT) without physical network consideration. P2PTV packets are shared over a network without localization awareness which is a serious problem for Internet Service Providers (ISPs). A delay-insertion-based traffic localization scheme was proposed for solving this problem. However, this scheme sometimes leads the newly joining peer to download streaming traffic from a local neighbor peer which has only scarce upload bandwidth. This paper proposes a novel scheme of delay-insertion-based traffic localization in which the router estimates relay capability to each relay peer candidate and leads the newly joining peer to connect to a neighbor peer with sufficient performance for relaying video data. Parameters were evaluated for the optimized condition in the relay capability estimation process. In addition, experiments conducted on a real network show that our proposed scheme can prevent the newly joining peer from downloading video data from peers with insufficient relay capability and maintain video quality close to normal in a P2PTV system while ensuring efficient traffic localization at the level of the Autonomous System (AS) network.

A novel element is proposed for manipulating two orthogonally-polarized electromagnetic waves, resulting in a polarization-reconfigurable flat transmitarray. This element consists of four identical metallic patterns, including a square frame loaded with short stubs and an internal crossed dipole, which are printed on the two sides of three identical flat dielectric slabs, with no air gap among them. With a linearly-polarized (LP) feeder, the flat transmitarray can transform the LP incident wave into a circular, horizontal or vertical polarization wave in a convenient way. By rotating the LP feeder so that the polarization angle is 0°, 45°, 90° or 135°, the waves of linear horizontal, right-handed circular, linear vertical or left-handed circular polarization can be obtained alternately. Simulations and experiments are conducted to validate the performance. The measured axial ratio bandwidths for RHCP and LHCP transmitarrays are about 7.1% and 5.1%, respectively, the 3dB gain bandwidths are 16.19% and 22.4%, and the peak gains are 25.56dBi and 24.2dBi, respectively.

In our previous work, we introduced new concepts of secure scan design; shift register equivalent circuits (SR-equivalents, for short) and strongly secure circuits, and also introduced generalized shift registers (GSRs, for short) to apply them to secure scan design. In this paper, we combine both concepts of SR-equivalents and strongly secure circuits and apply them to GSRs, and consider the synthesis problem of strongly secure SR-equivalents using GSRs. We also consider the enumeration problem of GSRs that are strongly secure and SR-equivalent, i.e., the cardinality of the class of strongly secure SR-equivalent GSRs to clarify the security level of the secure scan architecture.

This paper proposes a read-only memory driving circuit for RFID tags based on a-IGZO thin-film transistors. The circuit consists of a Johnson counter and monotype complementary gates. By utilizing complementary signals to drive a decoder based on monotype complementary gates, the propagation delay can be decreased and the redundant current can be reduced. The Johnson counter reduces the number of registers. The new circuit can effectively avoid glitch generation, and reduce circuit power consumption and delay.

Existing image deblurring methods with a blurred/noisy image pair take a two-step approach: blur kernel estimation and image restoration. They can achieve better and much more stable blur kernel estimation than single image deblurring methods. On the other hand, in the image restoration step, they do not exploit the information on the noisy image, or they require ad hoc tuning of interdependent parameters. This paper focuses on the image restoration step and proposes a new restoration method of using a blurred/noisy image pair. In our method, the image restoration problem is formulated as a constrained convex optimization problem, where data-fidelity to a blurred image and that to a noisy image is properly taken into account as multiple hard constraints. This offers (i) high quality restoration when the blurred image also contains noise; (ii) robustness to the estimation error of the blur kernel; and (iii) easy parameter setting. We also provide an efficient algorithm for solving our optimization problem based on the so-called alternating direction method of multipliers (ADMM). Experimental results support our claims.

A novel dimensionality reduction method, Fisher Discriminant Locality Preserving Canonical Correlation Analysis (FDLP-CCA), for visualizing Web images is presented in this paper. FDLP-CCA can integrate two modalities and discriminate target items in terms of their semantics by considering unique characteristics of the two modalities. In this paper, we focus on Web images with text uploaded on Social Networking Services for these two modalities. Specifically, text features have high discriminate power in terms of semantics. On the other hand, visual features of images give their perceptual relationships. In order to consider both of the above unique characteristics of these two modalities, FDLP-CCA estimates the correlation between the text and visual features with consideration of the cluster structure based on the text features and the local structures based on the visual features. Thus, FDLP-CCA can integrate the different modalities and provide separated manifolds to organize enhanced compactness within each natural cluster.

In this paper, we propose a novel design method of two channel critically sampled compactly supported biorthogonal graph wavelet filter banks with half-band kernels. First of all, we use the polynomial half-band kernels to construct a class of biorthogonal graph wavelet filter banks, which exactly satisfy the PR (perfect reconstruction) condition. We then present a design method of the polynomial half-band kernels with the specified degree of flatness. The proposed design method utilizes the PBP (Parametric Bernstein Polynomial), which ensures that the half-band kernels have the specified zeros at λ=2. Therefore the constraints of flatness are satisfied at both of λ=0 and λ=2, and then the resulting graph wavelet filters have the flat spectral responses in passband and stopband. Furthermore, we apply the Remez exchange algorithm to minimize the spectral error of lowpass (highpass) filter in the band of interest by using the remaining degree of freedom. Finally, several examples are designed to demonstrate the effectiveness of the proposed design method.

Spectral compressive sensing is a novel approach that enables extraction of spectral information from a spectral-sparse signal, exclusively from its compressed measurements. Thus, the approach has received considerable attention from various fields. However, standard compressive sensing algorithms always require a sparse signal to be on the grid, whose spacing is the standard resolution limit. Thus, these algorithms severely degenerate while handling spectral compressive sensing, owing to the off-the-grid issue. Some off-the-grid algorithms were recently proposed to solve this problem, but they are either inaccurate or computationally expensive. In this paper, we propose a novel algorithm named parameterized ℓ1-minimization (PL1), which can efficiently solves the off-the-grid spectral estimation problem with relatively low computational complexity.

For subgraph enumeration problems, very efficient algorithms have been proposed whose time complexities are far smaller than the number of subgraphs. Although the number of subgraphs can exponentially increase with the input graph size, these algorithms exploit compressed representations to output and maintain enumerated subgraphs compactly so as to reduce the time and space complexities. However, they are designed for enumerating only some specific types of subgraphs, e.g., paths or trees. In this paper, we propose an algorithm framework, called the frontier-based search, which generalizes these specific algorithms without losing their efficiency. Our frontier-based search will be used to resolve various practical problems that include constrained subgraph enumeration.

Entity descriptions have been exponentially growing in community-generated knowledge databases, such as DBpedia. However, many of those descriptions are not useful for identifying the underlying characteristics of their corresponding entities because semantically redundant facts or triples are included in the descriptions that represent the connections between entities without any semantic properties. Entity summarization is applied to filter out such non-informative triples and meaning-redundant triples and rank the remaining informative facts within the size of the triples for summarization. This study proposes an entity summarization approach based on pre-grouping the entities that share a set of attributes that can be used to characterize the entities we want to summarize. Entities are first grouped according to projected multilingual categories that provide the multi-angled semantics of each entity into a single entity space. Key facts about the entity are then determined through in-group-based rankings. As a result, our proposed approach produced summary information of significantly better quality (p-value =1.52×10-3 and 2.01×10-3 for the top-10 and -5 summaries, respectively) than the state-of-the-art method that requires additional external resources.

Existing moving object's trajectory prediction algorithms suffer from the data sparsity problem, which affects the accuracy of the trajectory prediction. Aiming to the problem, we present an Entropy-based Sparse Trajectories Prediction method enhanced by Matrix Factorization (ESTP-MF). Firstly, we do trajectory synthesis based on trajectory entropy and put synthesized trajectories into the trajectory space. It can resolve the sparse problem of trajectory data and make the new trajectory space more reliable. Secondly, under the new trajectory space, we introduce matrix factorization into Markov models to improve the sparse trajectory prediction. It uses matrix factorization to infer transition probabilities of the missing regions in terms of corresponding existing elements in the transition probability matrix. It aims to further solve the problem of data sparsity. Experiments with a real trajectory dataset show that ESTP-MF generally improves prediction accuracy by as much as 6% and 4% compared to the SubSyn algorithm and STP-EE algorithm respectively.

We present a novel method to enable users to experience mobile interaction with digital content on external displays by embedding markers imperceptibly on the screen. Our method consists of two parts: marker embedding on external displays and marker detection. To embed markers, similar to previous work, we display complementary colors in alternating frames, which are selected by considering L*a*b color space in order to make the markers harder for humans to detect. Our marker detection process does not require mobile devices to be synchronized with the display, while certain constraints for the relation between camera and display update rate need to be fulfilled. In this paper, we have conducted three experiments. The results show 1) selecting complementary colors in the a*b* color plane maximizes imperceptibility, 2) our method is extremely robust when used with static contents and can handle animated contents up to certain optical flow levels, and 3) our method was proved to work well in case of small movements, but large movements can lead to loss of tracking.

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.